publications

2022:7

1. The Associations of Dietary Copper with Cognitive Outcomes: The ARIC Study

   Wei, Jingkai, Gianattasio, Kan Z, Bennett, Erin E, Stewart, James D, Xu, Xiaohui, Park, Eun Sug, Smith, Richard L,  Ying, Qi, Whitsel, Eric A, and Power, Melinda C

   American journal of epidemiology, Mar 2022

   Abs Doi

   Dietary copper intake may be associated with cognitive decline and dementia. We used data from 10,269 participants of the Atherosclerosis Risks in Communities Study to study the associations of dietary copper intake with 20-year cognitive decline and incident dementia. Dietary copper intake from food and supplements was quantified using food frequency questionnaires. Cognition was assessed using three cognitive tests at study visits; dementia was ascertained at study visits and via surveillance. Multiple imputation by chained equations was applied to account for the missing information of cognitive function during follow-up. Survival analysis with parametric models and mixed-effect models were used to estimate the associations for incident dementia and cognitive decline, respectively. During 20 years of follow-up (1996-1998 to 2016-2017), 1,862 incident cases of dementia occurred. Higher intake of dietary copper from food was associated with higher risk of incident dementia among those with high intake of saturated fat (hazards ratio: 1.49, 95% confidence interval (CI): 1.04, 1.95). Higher intake of dietary copper from food was associated with greater decline in language overall (beta: -0.12, 95% CI: -0.23, -0.02). Therefore, a diet high in copper, particularly when combined with a diet high in saturated fat, may increase the risk of cognitive impairment.

2. Characteristics of movers and predictors of residential mobility in the Atherosclerosis Risk in Communities (ARIC) cohort

   Bennett, Erin E., Lynch, Katie M., Xu, Xiaohui, Park, Eun Sug,  Ying, Qi, Wei, Jingkai, Smith, Richard L., Stewart, James D., Whitsel, Eric A., and Power, Melinda C.

   Health & place, Mar 2022

   Abs Doi

   Current efforts to characterize movers and identify predictors of moving have been limited. We used the ARIC cohort to characterize non-movers, short-distance movers, and long-distance movers, and employed best subset algorithms to identify important predictors of moving, including interactions between characteristics. Short- and long-distance movers were notably different from non-movers, and important predictors of moving differed based on the distance of the residential move. Importantly, systematic inclusion of interaction terms enhanced model fit and was substantively meaningful. This work has important implications for epidemiologic studies of contextual exposures and those treating residential mobility as an exposure.

3. An explainable integrated optimization methodology for source apportionment of ambient particulate matter components

   Shen, Juanyong, Zhao, Qianbiao,  Ying, Qi, Cheng, Zhen, Xu, Junzhe, Zhang, Hairui, and Fu, Qingyan

   Journal of environmental management, May 2022

   Abs Doi

   Source apportionment of fine particulate matter (PM2.5) components is crucial for air pollution control. Prediction accuracies by the chemical transport model (CTM) significantly affect source apportionment results. Many efforts have been made to improve source apportionment results based on the CTM using mathematical algorithms, but the reasons for uncertainties in source apportionment results are less concerned. Here, an integrated optimization methodology is developed to quantify deviations from emission inventory and chemical mechanism in the model for improving prediction and source apportionment accuracies. Emission deviations of primary aerosols and gaseous pollutants are firstly calculated by an optimization algorithm with observation and receptor model constraints. Emission inventory is then adjusted for a new CTM simulation. Deviations from chemical mechanism for secondary conversions are evaluated by biases between observations and new predictions. Source apportionment results are adjusted according to both emission and chemical mechanism deviations. A winter month in 2016 at the Qingpu supersite in eastern China is selected as a case study. Results show that our integrated optimization methodology can successfully adjust emissions to pull original predictions towards observations. Total deviations of emissions for elemental carbon, organic carbon, primary sulfate, primary nitrate, primary ammonium, sulfur dioxide (SO2), nitrogen oxides (NOx) and ammonia (NH3) are estimated +59.6%, +95.9%, +72.9%, +82.2%, +75.9%, −6.4%, +67.6% and −17.6%, respectively. Also, major directions of deviations from chemical mechanisms can be captured. Deviations from SO2 to secondary sulfate, nitrogen dioxide (NO2) to secondary nitrate and NH3 to secondary ammonium conversions are estimated −77.3%, +27.1% and −38.8%, respectively. Consequently, source apportionment results are significantly improved. This developed methodology provides an efficient way to quantify deviations from emissions and chemical mechanisms to improve source apportionment for air pollution management.

4. Assessment of sectoral NOx emission reductions during COVID-19 lockdown using combined satellite and surface observations and source-oriented model simulations

   Kang, Mingjie, Zhang, Jie, Cheng, Zhen, Guo, Song, Su, Fangcheng, Hu, Jianlin, Zhang, Hongliang, and Ying, Qi

   Geophysical research letters, Jan 2022

   Abs Doi

   Abstract Large emission reductions of anthropogenic nitrogen oxides (NOx) due to the coronavirus disease 2019 (COVID-19) lockdown policies in China have been extensively reported since the outbreak, while assessments of sectoral emission changes during that period are still limited. In this study, a source-oriented community multiscale air quality (CMAQ) model was applied to quantify NO2 concentrations from major emission sectors. A new optimization approach was employed to obtain the sectorial emission reductions using satellite and ground-level observations as constraints. The optimized emissions significantly improved the model performance of NO2 during the lockdown period. February NOx emission changes varied with regions and sectors, with relatively larger reductions in transportation (286.6 kt) and industrial sources (260.1 kt). The maximum amount of NOx emission reduction occurred in the North China Plain (230.6 kt). Our work presents a quick and reliable technique for assessing sector-specific emission changes due to short-term emission control policies.

5. Modeling secondary organic aerosol tracers and tracer-to-SOA ratios for monoterpenes and sesquiterpenes Using a chemical transport model

   Zhang, Jie, He, Xiao, Ding, Xiang, Yu, Jian Zhen, and Ying, Qi

   Environmental science & technology, Jan 2022

   Abs Doi

   The community multiscale air quality (CMAQ) model was modified to simulate secondary organic aerosol (SOA) formation from five explicit (α-pinene, β-pinene, d-limonene, Δ3-carene, and sabinene) and one lumped monoterpene (MT) species and sesquiterpenes (SQTs). The contribution of each oxidation pathway [including OH, O3, NO3, and O(3P)] was explicitly tracked in the SOA module. Three MT SOA tracers (pinic acid, PA; pinonic acid, PNA; and 3-methyl-1,2,3-butanetricarboxylic acid, MBTCA) and one SQT SOA tracer (β-caryophyllinic acid, BCARYA) were modeled to assess the tracer-to-SOA ratios (fSOA) for ambient SOA estimation. Good model performance for BCARYA and MBTCA and reasonable agreement between model predictions and observations of PA and PNA were achieved. The modeled daily fSOA showed significant variations, suggesting that using the chamber-derived constant fSOA could lead to large errors in estimating terpene SOA. Among the four tracers, MBTCA and BCARYA were more appropriate for tracking MT and SQT SOA due to their nonvolatility. Their fSOA values mainly depend on the organic aerosol loading and could be approximated using simple power-law equations. In addition, equations directly linking the tracer concentrations to the corresponding SOA concentrations were proposed and could lead to good SOA estimations. This work provides new insights into the formation of the key MT and SQT SOA tracers and would allow better assessments of the biogenic emissions to regional and global aerosol burden.

6. Assessment of summertime O3 formation and the O3-NOX-VOC sensitivity in Zhengzhou, China using an observation-based model

   Wang, Xudong, Yin, ShaSha, Zhang, Ruiqin, Yuan, Minghao, and Ying, Qi

   Science of the total environment, Jan 2022

   Abs Doi

   Zhengzhou, the provincial capital of Henan province in central China and a major hub of the country’s transportation network, has been suffering from severe summertime ozone (O3) pollution. Simultaneous field measurements of O3 and its precursors, including NOx, CO, HONO, and 106 volatile organic compounds (VOCs), were conducted at an urban site (the municipal environmental monitoring station, MEM) in Zhengzhou in July 2019. The community multiscale air quality (CMAQ) model, which incorporates the Master Chemical Mechanism (MCMv3.3.1), was modified to work as a 0-D observation-based photochemical box model to assess the sources and sinks of HOx radicals and O3, and the OH reactivity (KOH) and ozone formation potential (OFP) of major VOC groups. In addition, the O3-NOx-VOC sensitivity was evaluated using the relative incremental reactivity (RIR) and O3 formation isopleth techniques. The OH radicals were mainly generated from the propagation reaction of HO2 + NO (91–95%). The daily average mixing ratios of OH and HO2 radicals were significantly higher during high O3 days, reaching as high as 4.8 × 106 and 7.7 × 108 molecules cm−3, respectively. Photochemical O3 formation was mostly due to the conversion of NO to NO2 by HO2 radicals (52–54%), while the NO2 + OH reaction was the main contributor to O3 destruction (70– 76%). Alkenes and aromatics were the main anthropogenic VOC contributors to KOH and OFP. Contributions of biogenic VOCs became much more important on high O3 days, correlating with the increase in temperature and solar radiation. RIR analysis showed that the O3 formation was under the VOC-limited on low O3 days but was in the transition regime during the O3 pollution buildup and persisting days. These results are generally consistent with those based on the O3 formation isopleth. This paper provides important corroborative scientific evidence urgently needed by local governments to formulate O3 pollution control strategies.

7. Evaluation of a highly condensed SAPRC chemical mechanism and two emission inventories for ozone source apportionment and emission control strategy assessments in China

   Kang, Mingjie, Hu, Jianlin, Zhang, Hongliang, and Ying, Qi

   Science of the total environment, Mar 2022

   Abs Doi

   The response of summertime O3 to changes in the nitrogen oxides (NOx) and volatile organic compounds (VOC) emissions, and contributions of different NOx and VOC sources to O3 in China are studied using a highly condensed photochemical mechanism in the Statewide Air Pollution Research Center (SAPRC) family (CS07A) and two popular anthropogenic emission inventories, the Multi-resolution Emission Inventory for China (MEIC) and Regional Emission inventory in ASia (REAS). Although CS07A predicts slightly lower O3 concentrations than the standard fix-parameter version of the SAPRC-11 mechanism, the two mechanisms predict almost identical relative responses to daily maximum 8-hour O3 (O3-8h) due to NOx and VOC emission reductions. A source-oriented version of the CS07A is applied to determine source contributions of NOx and VOCs to O3 using MEIC and REAS. The two inventories lead to similar model performance of O3, with MEIC predicting higher O3 in Beijing and Shanghai, especially on high O3 days. Source apportionment results showed that industry and transportation are the top two contributors to non-background O3 for both inventories, followed by power and biogenic emissions. In general, the two inventories lead to similar source contribution estimations to O3 attributable to NOx. However, their estimations of relative contributions to VOC-related O3 differ for the industrial and transportation sectors. Differences in the source apportionment results are more significant in some urban areas, although both emissions capture the spatial variations in the source contributions. Our results suggest that future emission control policies be assessed using multiple emission inventories, and the condensed CS07A is suitable for policy applications when a large number of simulations are needed.

2021:16

1. Assessing regional model predictions of wintertime SOA from aromatic compounds and monoterpenes with precursor-specific tracers

   Zhang, Jie, He, Xiao, Gao, Yaqin, Zhu, Shuhui, Jing, Shengao, Wang, Hongli, Yu, Jian Zhen, and Ying, Qi

   Aerosol and air quality research, Mar 2021

   Abs Doi

   ABSTRACT The Community Multiscale Air Quality (CMAQ) model, with modifications to track precursor-specific SOA, was applied to model SOA formation from aromatic compounds and monoterpenes in Shanghai in November 2018. The modeled total aromatic SOA showed a strong correlation with measured 2,3-dihydroxy-4-oxopentanoic acid (DHOPA) concentrations in the ambient aerosols (R \textgreater 0.5 for hourly data and R \textgreater 0.75 for daily average data). The ratios of observed DHOPA and modeled aromatic SOA with all components included is around (0.5–1.6) × 10–3, lower than the commonly used ratio of 4 × 10–3 determined for toluene in a series of smog chamber experiments. This suggests that aromatic SOA could be underestimated when directly using the chamber-derived ratios. The predicted monoterpene SOA shows a stronger correlation with the sum of two α-pinene tracers (α-pinT), pinic acid and 3-MBTCA, with R \textgreater 0.6 and R \textgreater 0.8 for hourly and daily data, respectively. The α-pinT to modeled monoterpene SOA ratios are 0.13–0.25, which generally match the ratio of 0.168 ± 0.081 reported in chamber studies. However, since the current model does not treat α-pinene and its SOA explicitly, future modeling studies should include a more detailed treatment of monoterpene emissions and reactions to predict SOA from these important precursors and compare with the ambient precursor-specific SOA-tracers.

2. Age-Resolved Source and Region Contributions to Fine Particulate Matter During an Extreme Haze Episode in China

   Xie, Xiaodong, Shi, Zhihao,  Ying, Qi, Zhang, Hongliang, and Hu, Jianlin

   Geophysical research letters, Mar 2021

   Abs Doi

   A source- and age-resolved algorithm (SARA) was developed in the CMAQ model and applied to study the sources and ages of primary fine particulate matter (PPM) and secondary inorganic aerosols (SNA) in China during January 2013. Residential and industry are the major contributors to PPM and sulfate, especially for fresh particles. The contributions of power increase with age, accounting for 25% and 51% of aged sulfate and nitrate (\textgreater48 hr), respectively. Local emissions and intra-regional transport with younger age contribute to over 70% of PPM and SNA in Beijing, while long-range transport from northern China with older age becomes more significant in Shanghai. On pollution days, the ages of PPM and SNA consistently increase, suggesting enhanced contributions from regional transport. This study highlights that the age-specific particle source and region information produced by our SARA algorithm can help design cost-effective emission control strategies to reduce extreme haze pollution.

3. Impacts of chlorine chemistry and anthropogenic emissions on secondary pollutants in the Yangtze river delta region

   Li, Jingyi, Zhang, Na, Wang, Peng, Choi, Minsu,  Ying, Qi, Guo, Song, Lu, Keding, Qiu, Xionghui, Wang, Shuxiao, Hu, Min, Zhang, Yuanhang, and Hu, Jianlin

   Environmental pollution, Oct 2021

   Abs Doi

   Multiphase chemistry of chlorine is coupled into a 3D regional air quality model (CMAQv5.0.1) to investigate the impacts on the atmospheric oxidation capacity, ozone (O-3), as well as fine particulate matter (PM2.5) and its major components over the Yangtze River Delta (YRD) region. The developed model has significantly improved the simulated hydrochloric acid (HCl), particulate chloride (PCl), and hydroxyl (OH) and hydroperoxyl (HO2) radicals. O-3 is enhanced in the high chlorine emission regions by up to 4% and depleted in the rest of the region. PM2.5 is enhanced by 2-6%, mostly due to the increases in PCl, ammonium, organic aerosols, and sulfate. Nitrate exhibits inhomogeneous variations, by up to 8% increase in Shanghai and 2-5% decrease in most of the domain. Radicals show different responses to the inclusion of the multiphase chlorine chemistry during the daytime and nighttime. Both OH and HO2 are increased throughout the day, while nitrate radicals (NO3) and organic peroxy radicals (RO2) show an opposite pattern during the daytime and nighttime. Higher HCl and PCl emissions can further enhance the atmospheric oxidation capacity, O-3, and PM2.5. Therefore, the anthropogenic chlorine emission inventory must be carefully evaluated and constrained.

4. Estimation of Aromatic Secondary Organic Aerosol Using a Molecular Tracer-A Chemical Transport Model Assessment

   Zhang, Jie, He, Xiao, Gao, Yaqin, Zhu, Shuhui, Jing, Shengao, Wang, Hongli, Yu, Jian Zhen, and Ying, Qi

   Environmental science & technology, Oct 2021

   Abs Doi

   A modified community multiscale air quality model, which can simulate the regional distributions of 2,3-dihydroxy-4-oxopentanoic acid (DHOPA), a marker species for monoaromatic secondary organic aerosol (SOA), was applied to assess the applicability of using the DHOPA to aromatic SOA mass ratio (f(SOA)) from smog chamber experiments to estimate aromatic SOA during a three-week wintertime air quality campaign in urban Shanghai. The modeled daily DHOPA concentrations based on the chamber-derived mass yields agree well with the organic marker field measurements (R = 0.79; MFB = 0.152; and MFE = 0.440). Two-thirds of the DHOPA are from the oxidation of ARO1 (lumped less-reactive aromatic species; mostly toluene), with the rest from ARO2 (lumped more-reactive aromatic species; mostly xylenes). Modeled DHOPA is mainly in the particle phase under ambient organic aerosol (OA) loading but could exhibit significant gas-particle partitioning when a higher estimation of the DHOPA vapor pressure is used. The modeled f(SOA) shows a strong dependence on the OA loading when only semivolatile aromatic SOA components are included in the f(SOA) calculations. However, this OA dependence becomes weaker when non-volatile oligomers and dicarbonyl SOA products are considered. A constant f(SOA) value of similar to 0.002 is determined when all aromatic SOA components are included, which is a factor of 2 smaller than the commonly applied chamber-based fSOA value of 0.004 for toluene. This model-derived f(SOA) value does not show much spatial variation and is not sensitive to alternative estimates of DHOPA vapor pressures and SOA yields, and thus provides an appropriate scaling factor to assess aromatic SOA from DHOPA measurements. This result helps refine the quantification of SOA attributable to monoaromatic hydrocarbons in urban environments and thereby facilitates the evaluation of control measures targeting these specific precursors.

5. Assessing the Uncertainties in Ozone and SOA Predictions due to Different Branching Ratios of the Cresol Pathway in the Toluene -OH Oxidation Mechanism

   Zhang, Jie, Choi, Minsu, Ji, Yuemeng, Zhang, Renyi, Zhang, Ruiqin, and Ying, Qi

   Acs earth and space chemistry, Aug 2021

   Abs

   Oxidation of toluene by OH radicals plays a significant role in forming ozone (03) and secondary organic aerosol (SOA) in polluted urban atmospheres. However, the branching ratio of the cresol formation pathway after OH addition to the aromatic ring remains uncertain, affecting model predictions of 03 and SOA. In this study, SOA formation under low (18%) and high (48%) cresol branching ratio conditions are determined by modeling chamber experiments on toluene SOA formation, using a photochemical box model with the semiexplicit master chemical mechanism (MCM) v3.2 and an SOA module for the equilibrium gas -to -particle partitioning of semivolatile products. The modeled SOA concentrations are fitted to determine the SOA yields and saturation concentrations using the classical two product representation. These parameters are then applied in the community multiscale air quality (CMAQ) model to assess the impact of the cresol branching ratio on SOA formation. The reaction products of ARO1 (the lump species that includes mostly toluene) with OH are also modified to reflect the higher cresol branching ratio. Two sets of CMAQsimulations for China (CO, with low SOA yields and unmodified ARO1 + OH reaction, and Cl, with high SOA yields and modified ARO1 + OH reaction) are conducted for January and July 2013. Predicted monoaromatic compound concentrations in major urban areas are 4-7 ppb in January and 1.5-3 ppb in July, which generally agree with measurements. The higher cresol branching ratio simulations lead to slightly lower OH radicals and 03 predictions. Less than 1 ppb decrease of monthly average daily maximum 8 h and peak hour 03 is found in the urban areas in July and with broader spatial coverage in January. The increase in January ARO1 SOA is approximately 1.2 deg m 3, corresponding to a relative increase of 40-70% to ARO1 SOA or an 10% increase of total SOA. This change reflects the combined effects of increasing ARO1 SOA due to higher yields and reduced formation of semivolatile organic products and glyoxal and methylglyoxaI due to lower OH radicals.

6. Quantifying the impacts of inter-city transport on air quality in the Yangtze River Delta urban agglomeration, China: Implications for regional cooperative controls of PM2.5 and O-3

   Gong, Kangjia, Li, Lin, Li, Jingyi, Qin, Momei, Wang, Xueying,  Ying, Qi, Liao, Hong, Guo, Song, Hu, Min, Zhang, Yuanhang, and Hu, Jianlin

   Science of the total environment, Jul 2021

   Abs Doi

   The Yangtze River Delta (YRD) urban agglomeration is one of the most developed regions in China. During recent decades, this region has experienced severe regional haze and photochemical smog pollution problems. In this study, we used a source-oriented chemical transport model to quantitatively estimate the effects of inter-city transport on fine particulate matter (PM2.5) and ozone (O-3) among the 41 cities in the YRD urban agglomeration during the EXPLORE-YRD (EXPeriment on the eLucidation of the atmospheric Oxidation capacity and aerosol foRmation, and their Effects in the Yangtze River Delta) campaign (May 17 to June 17, 2018). The results show that intercity transport is very significant in the YRD region. On average, the emissions from the local city, the other YRD cities, and the regions outside of the YRD contribute 25.3%, 49.9%, and 24.8% to the PM2.5, respectively, and they contribute 33.7%, 46.8%, and 19.5% of the non-background O-3, respectively. On PM2.5 or O-3 pollution days, the transport contribution from the non-local YRD cities becomes much more important, while the local emissions and the transport from non-YRD emissions become less important. The results also suggest that the cities within a distance of 184 km and 94 km contribute 60% of the PM2.5 and O-3, respectively. Therefore, we recommend that regional cooperative control programs in the YRD consider emission controls over cities within these ranges. The range for primary PM2.5 (92 km) is very different from that for secondary PM2.5 (515 km). Cooperative emission controls of SO2 and NOx on a much larger regional scale are required to reduce the secondary PM2.5 in the YRD. (C) 2021 Elsevier B.V. All rights reserved.

7. Atmospheric deposition of sulfur and nitrogen in the West China rain zone: Fluxes, concentrations, ecological risks, and source apportionment

   Qiao, Xue, Shu, Xi, Tang, Ya, Duan, Lei, Seyler, Barnabas C., Guo, Hao, Xiao, Yao,  Ying, Qi, and Zhang, Hongliang

   Atmospheric research, Jul 2021

   Abs Doi

   The West China Rain Zone (WCRZ; 25,000 km(2)) is a broad mountainous ecotone between the urbanized Sichuan Basin (SCB) and the rural Qinghai-Tibetan Plateau (QTP). The WCRZ is rich in biodiversity and may be influenced by the air pollutants transported from the SCB towards the QTP. As air pollution can cause adverse effects on ecosystem health, this study investigated the fluxes, ecological risks, and sources of sulfur and nitrogen deposition by using a source-oriented community multiscale air quality (CMAQ) model for the entire WCRZ and its constituent national nature reserves in 2015. Results indicate that for sulfur (75%) and nitrogen (70%), the majority of the WCRZ area had annual total deposition fluxes higher than their critical loads. In addition, the annual volume-weighted mean (VWM) total inorganic nitrogen (TIN) wet deposition concentrations in almost the entire WCRZ exceeded the standard for total nitrogen of surface water in protected areas (0.2 mg N L-1). This exceedance is detrimental for the headwater watersheds that have precipitation as their sole water source. In each of the national nature reserves (NNRs), the average annual total deposition fluxes ranged between similar to 12-38 (sulfur) and similar to 15-38 kg S(N) ha(-1) a(-1) (nitrogen). About 40-100% (sulfur) and 5-85% (nitrogen) of the areas have annual total fluxes higher than the corresponding critical loads. Furthermore, the average VWM TIN concentration of wet deposition in each WCRZ NNR is higher than 0.2 mg N L-1. Therefore, sulfur and nitrogen deposition likely pose severe risks to some important natural ecosystems in the WCRZ. Based on the source apportionment results, to reduce sulfur and nitrogen deposition in the WCRZ, both SCB and non-SCB emissions should be controlled. In addition, the agricultural NH3 emissions and the industrial and power plant SO2 and NOx emissions should be reduced by larger extents than that of other sectors. This study provides a basis for future atmospheric and ecological observations in the WCRZ.

8. Premature Mortality Associated with Exposure to Outdoor Black Carbon and Its Source Contributions in China

   Wang, Yiyi, Li, Xun, Shi, Zhihao, Huang, Lin, Li, Jingyi, Zhang, Hongliang,  Ying, Qi, Wang, Meng, Ding, Deping, Zhang, Xiaoling, and Hu, Jianlin

   Resources conservation and recycling, Jul 2021

   Abs Doi

   Epidemiological studies have shown that outdoor black carbon (BC) has higher health risks than other constituents and the total fine particulate matter (PM2.5). In this study, we estimated premature mortality attributed to BC in China in 2013 using a health impact model combined with annual average BC concentrations predicted using the Community Multi-scale Air Quality model. Source contributions to BC from six different source sectors were estimated using the source-oriented method, including residential, industrial, transportation, open burning, power, and other sources. The sensitivity of BC-related premature mortality to emission reductions in different sources was quantified in different regions of China. The results showed that the total all-cause premature mortality related to BC was approximately 1,436,957 (95% CI: 998,746-2,029,210) in China in 2013. Residential, industrial, and transportations sources were the three main sources of BC-induced premature mortality. Central China, Yangtze River Delta, and Sichuan Basin had the highest BC-induced mortality due to a high level of emissions and a dense population. A sensitivity test by assuming the same exposure-response coefficient of BC as the total PM2.5 showed the number of deaths was 265,122 thousand (95% CI: 541,90, 445,943) which can be treated as the lower limit of the BC-related mortality in China. Despite the uncertainties in estimates, it is suggested that reducing BC emissions in China would lead to significant health benefits. Controlling BC from industrial and transportation sources would bring more relative mortality reductions, from a percentage point of view, in most provinces of China.

9. Responses of fine particulate matter and ozone to local emission reductions in the Sichuan Basin, southwestern China

   Qiao, Xue, Liu, Lu, Yang, Chun, Yuan, Yanping, Zhang, Mengyuan, Guo, Hao, Tang, Ya,  Ying, Qi, Zhu, Shengqiang, and Zhang, Hongliang

   Environmental pollution, May 2021

   Abs Doi

   The Sichuan Basin (SCB) in southwestern China is largely affected by air pollution. Understanding the responses of air pollutant concentrations to emission changes is critical for designing and evaluating effective control strategies. Thus, this study used the Community Multi-scale Air Quality (CMAQ) model to simulate PM2.5 (i.e., particulate matter with an aerodynamic diameter <= 2.5 mu m) in winter (January 2015) and ozone (O-3) in summer (July 2015) under nine emission reduction scenarios. For each scenario, the anthropogenic emissions of each air pollutant in each SCB grid cell were reduced by the same percentage, ranging from 10% to 90%. We found that approximately 30-70% emission reductions are required to reduce the January mean PM2.5 concentrations in all the SCB urban centers to a value that is less than the Chinese standard for daily mean PM2.5 (24-h PM2.5: 75 mg m(-3)). However, the January mean PM2.5 concentrations under 90% emission reduction still exceeded the World Health Organization (WHO) guideline (25 mg m(-3)) in 16 SCB urban centers. Moreover, reducing both SCB and non-SCB emissions were critical for achieving the PM2.5 level recommended by WHO. An 80% emission reduction was required to prevent the occurrence of 8-h O-3 (i.e., daily maximum 8-h mean O-3) non-attainment days in all SCB urban centers. Under 90% emission reduction, July mean 8-h O-3 concentrations still exceeded the WHO guideline of 47 ppb in approximately 35% of the SCB areas. In conclusion, this study suggests that (1) compared with the governmental emission reduction targets for 2015-2020 (2-27%), more significant emission reductions are required to meet the Chinese and WHO pollution standards; and (2) both SCB and non-SCB emissions must significantly reduce to achieve the desired pollution targets. (C) 2021 Elsevier Ltd. All rights reserved.

10. Atmospheric Age Distribution of Primary and Secondary Inorganic Aerosols in a Polluted Atmosphere

    Ying, Qi, Zhang, Jie, Zhang, Hongliang, Hu, Jianlin, and Kleeman, Michael J.

    Environmental science & technology, May 2021

    Abs Doi

    The community multiscale air quality (CMAQ) model was modified to track the evolution of the atmospheric age (tau) distribution of primary particulate matter (PPM) and secondary inorganic aerosol components (nitrate, sulfate, and ammonium ion, NSA). The modified CMAQ gas and aerosol mechanisms represent the same species emitted at different times as an age-resolved mixture, using multiple age-tagged variables and a dynamic age-bin advancing scheme. The model was applied to study the spatial and temporal evolution of tau for PPM and NSA in January 2013 to understand the formation and regional transport of PM and the precursor gases during severe winter pollution episodes in China. The results showed that increases in PPM and NSA concentrations during high pollution periods in polluted urban areas were typically associated with increases in the mean atmospheric age ((tau) over bar) due to the accumulation of local emissions and regional transport of aged pollutants. Some of the rapid sulfate growth events at the beginning of multiday air pollution episodes were driven by regional transport of aged particles. In heavily polluted cities, while most of the monthly average PPM had tau less than 10 h, more than half of the sulfate had tau greater than 20-30 h. Regional distributions showed that very aged sulfate particles with tau > 96 h accounted for a significant portion of the total sulfate and had a very broad spatial distribution. However, aged ammonium ions had very low concentrations. Aged nitrate also had lower concentrations and more limited spatial distributions than sulfate due to differences in the atmospheric lifetime between SO2 and NOx. The estimated NOx lifetime of approximately similar to 24 h in China agrees with a satellite-based estimation of 21 h. Potential applications of the age distribution analysis include evaluating the impacts of meteorology on air quality and developing short-term emission control strategies.

11. A multiple linear regression model with multiplicative log-normal error term for atmospheric concentration data

    Liao, Kezheng, Park, Eun Sug, Zhang, Jie, Cheng, Linjun, Ji, Dongsheng,  Ying, Qi, and Yu, Jian Zhen

    Science of the total environment, May 2021

    Abs Doi

    The homoscedasticity assumption (the variance of the error term is the same across all the observations) is a key assumption in the ordinary linear squares (OLS) solution degrees fa linear regression model. The validity of this assumption is examined for a multiple linear regression model used to determine the source contributions to the observed black carbon concentrations at 12 background monitoring sites across China using a hybrid modeling approach. Residual analysis from the traditional OLS method, which assumes that the error term is additive and normally distributed with a mean of zero, shows pronounced heterosceclasticity based on the Breusch-Pagan test for 11 datasets. Noticing that the atmospheric black carbon data are log-normally distributed, we make a new assumption that the error terms are multiplicative and log-normally distributed. When the coefficients of the multilinear regression model are determined using the maximum likelihood estimation (MLE), the distribution of the residuals in 8 out of the 12 datasets is in good accordance with the revised assumption. Furthermore, the MLE computation under this novel assumption could be proved mathematically identical to minimizing a log-scale objective function, which considerably reduces the complexity in the MLE calculation. The new method is further demonstrated to have dear advantages in numerical simulation experiments of a 5-variable multiple linear regression model using synthesized data with prescribed coefficients and lognormally distributed multiplicative errors. Under all 9 simulation scenarios, the new method yields the most accurate estimations of the regression coefficients and has significantly higher coverage probability (on average, 95% for all five coefficients) than OLS (79%) and weighted least squares (WLS, 72%) methods. (C) 2020 Elsevier B.V. All rights reserved.

12. On the Relevancy of Observed Ozone Increase during COVID-19 Lockdown to Summertime Ozone and PM2.5 Control Policies in China

    Kang, Mingjie, Zhang, Jie, Zhang, Hongliang, and Ying, Qi

    Environmental science & technology letters, Apr 2021

    Abs Doi

    In February 2020, China’s strict lockdown policies led to significant reductions in anthropogenic nitrogen oxides (NOx) emissions, and notable increases in surface ozone (O-3) followed in many urban areas, raising concerns about potential rises in summertime O-3 due to NOx emission controls. On the basis of O-3 isopleths from a series of air quality simulations under different levels of NOx and volatile organic compound (VOC) emission reductions, we found that such concerns are not necessary. As NOx emissions have been reduced in recent years for particulate matter control, future NOx reductions are generally favorable for summertime maximum daily average 8-h (MDA8) O-3 reductions. Decreases in summertime O-3 due to NOx reductions will also lead to lower atmospheric oxidation capacity, characterized by decreased OH and NO3 concentrations, resulting in further reduction of secondary inorganic aerosols (nitrate, sulfate, and ammonium ion, NSA) formation. VOC emission reductions help to further reduce MDA8 O-3 and are needed to control HCHO and primary air toxics simultaneously, but they are ineffective in reducing NSA. This study indicates that a nationwide NOx emission reduction policy has great potential in controlling O-3 and PM2.5 simultaneously. However, its effectiveness could be greatly reduced when applied on a limited spatial scale.

13. Molecular characteristics, source contributions, and exposure risks of polycyclic aromatic hydrocarbons in the core city of Central Plains Economic Region, China: Insights from the variation of haze levels

    Dong, Zhe, Jiang, Nan, Zhang, Ruiqin, Xu, Qixiang,  Ying, Qi, Li, Qiang, and Li, Shengli

    Science of the total environment, Feb 2021

    Abs Doi

    In this study, molecular characteristics, source contributions, and health risks of polycyclic aromatic hydrocarbons (PAHs) in PM2.5 for four haze levels in Zhengzhou, a megacity in central China with severe air pollution problems, have been analyzed. The concentrations of PAHs and PM2.5 on heavy haze (HH) days were 63% and 122% higher than non-haze (NH) days. The occurrence of high PAH concentration was often accompanied by the northwest wind along with adverse meteorological conditions that limit regional dispersion. The source apportionment results indicated that almost all sources contributed more PAH concentration on haze days. In particular, coal combustion and vehicle emissions contributions were almost doubled on HH days. The incremental lifetime cancer risk (ILCR) of PAHs has been assessed. BaP and DahA showed relatively high contributions to ILCR, and 31%-48% of ILCR is due to exposure to PAHs on high HH days. (C) 2020 Elsevier B.V. All rights reserved.

14. Modelling air quality during the EXPLORE-YRD campaign - Part II. Regional source apportionment of ozone and PM2.5

    Li, Lin, Hu, Jianlin, Li, Jingyi, Gong, Kangjia, Wang, Xueying,  Ying, Qi, Qin, Momei, Liao, Hong, Guo, Song, Hu, Min, and Zhang, Yuanhang

    Atmospheric environment, Feb 2021

    Abs Doi

    A source-oriented Community Multiscale Air Quality model was used to quantify the contributions of different sources to ground-level fine particulate matter (PM2.5) and ozone (O-3) over the Yangtze River Delta (YRD) region during the EXPLORE-YRD (EXPeriment on the eLucidation of the atmospheric Oxidation capacity and aerosol foRmation, and their Effects in the Yangtze River Delta) campaign (17 May to June 17, 2018). O-3 formation in most urban areas of YRD is attributed to volatile organic compounds (VOCs) (81.1%, 78.5%, 60.2%, and 55.1% in Shanghai, Nanjing, Hefei, and Hangzhou, respectively), but is affected more by nitrogen oxides (NOx) in suburban and rural areas. Industry and transportation are the two major sources of O-3 and PM2.5. In addition to the two sources, NOx produced owing to power generation, and VOC emissions from biogenic sources are important source of O-3. Industry contributes the most to the total mass of PM2.5 in the YRD during the study period (9-25 mu g/m(3)), followed by transportation (2-7 mu g/m(3)). Industry, residential emissions, and transportation are the major sources of primary organic carbon and elemental carbon, whereas industry, transportation, and power generation account for most of the sulphate (SO2-4) and nitrate (NO-3) in the YRD. Agriculture is the most dominant source of ammonium emissions (NH+ 4). In Shanghai, Nanjing, Hefei, and Taizhou, secondary organic aerosol (SOA) are mainly contributed by industrial emissions. However, in Hangzhou, biogenic emissions contribute more than 40% of SOA. During all types of pollution episodes, industry and transportation are generally the two greatest sources of O-3 and PM2.5 in YRD. The contribution of industry is higher during high PM2.5 pollution episodes, whereas biogenic and open burning contributions are more important during high O-3 episodes. Overall, anthropogenic sources dominate the formation of O-3 and PM2.5 pollution in the YRD, whereas biogenic emissions contribute significantly to O-3 attributable to VOC emissions (O3_VOCs) accounting for 9-20% in urban areas of the YRD.

15. On the effectiveness of short-term intensive emission controls on ozone and particulate matter in a heavily polluted megacity in central China

    Su, Fangcheng, Xu, Qixiang, Wang, Ke, Yin, Shasha, Wang, Shenbo, Zhang, Ruiqin, Tang, Xiaoyan, and Ying, Qi

    Atmospheric environment, Feb 2021

    Abs Doi

    Intensive temporary air pollution control measures were implemented in Zhengzhou (ZZ), a megacity in central China, and six neighboring cities during the 2019 National Games of Ethnic Minorities. The Community Multiscale Air Quality (CMAQ) model and a high-resolution local emission inventory were applied to evaluate the control measures. Reductions of similar to 35-60% of primary PM (PPM), 45-65% of VOCs, similar to 5% of NH3, 35-45% of NOx, and 30-70% of SO2 emissions in the central area (i.e., ZZ) and collaborative cities (i.e., the six neighboring cities) lead to significant reductions of daily PM2.5 by 25-45% in ZZ. Hourly concentrations of PM2.5 are reduced by as much as 100 mu g m(-3). Most of the reduction in PM2.5 is due to primary PM, and NO3-, SO42-, and NH4+ ion concentrations only decrease by 5-6%. Emission reductions in the collaborative cities contribute to 10-30% of the decrease in PM2.5 and PM10 in ZZ. Concentrations of daily maximum 8-hr (DM8H) O-3 increase by 2-5% on high O-3 days. Isopleth analysis suggests that the local molar reductions ratio of NOx to VOC needs to be < 0.5 to avoid the increases. More stable meteorology conditions make emission controls in ZZ more effective for PM2.5 and PM10 but lead to higher increases in DM8H O-3. These results suggest that control of PPM emissions in ZZ is the most effective in reducing PM2.5 and PM10. However, reductions of precursor gaseous in ZZ and the six neighboring cities alone are not effective in reducing the secondary PM components and most likely lead to increases in DM8H O-3.

16. Revealing the origin of fine particulate matter in the Sichuan Basin from a source-oriented modeling perspective

    Qiao, Xue, Yuan, Yanping, Tang, Ya,  Ying, Qi, Guo, Hao, Zhang, Yueying, and Zhang, Hongliang

    Atmospheric environment, Jan 2021

    Abs Doi

    The Sichuan Basin (SCB) with 18 cities is one of the regions that are greatly affected by PM2.5 (i.e., particulate matter (PM) with an aerodynamic equivalent diameter less than or equal to 2.5 mu m) in China. In this study, we used the Weather Research Forecasting (WRF) model and a source-oriented version of the Community Multiscale Air Quality (CMAQ) model to quantify the contributions from different sectors and regions to PM2.5 for the SCB in 2015. The annual PM2.5 concentrations in the 18 SCB urban centers (i.e., the central urban areas) are 42-112 mu g m(-3), much higher than the World Health Organization (WHO) guideline (10 mu g m(-3)) and having 20-86, 6-17, and 6-10 mu g m(-3) due to SCB, non-SCB, and unidentified emissions, respectively. Non-SCB emissions can contribute up to 87 mu g m(-3) to 24-h PM2.5 concentrations for an urban center. Industrial and residential activities are the largest sectors for annual PM2.5 concentrations in the urban centers, and each of them contributes similar to 25%-50%. The combined residential and industrial contributions (>similar to 60%) are always much higher than that from each of the other sources on PM2.5 pollution and extreme pollution days (>75 and > 150 mu g m(-3), respectively). This study suggests that China’s standard for annual PM2.5 (35 mu g m(-3)) in most of the SCB cities might be achieved mainly through controlling SCB emissions (particularly those from industrial and residential activities); however, to meet the WHO guideline and to reduce PM2.5 pollution days and extreme pollution days, both SCB and non-SCB emissions should be greatly reduced.

2020:18

1. Source-Receptor Relationship Revealed by the Halted Traffic and Aggravated Haze in Beijing during the COVID-19 Lockdown

   Lv, Zhaofeng, Wang, Xiaotong, Deng, Fanyuan,  Ying, Qi, Archibald, Alexander T., Jones, Roderic L., Ding, Yan, Cheng, Ying, Fu, Mingliang, Liu, Ying, Man, Hanyang, Xue, Zhigang, He, Kebin, Hao, Jiming, and Liu, Huan

   Environmental science & technology, Dec 2020

   Abs Doi

   The COVID-19 outbreak greatly limited human activities and reduced primary emissions particularly from urban on-road vehicles but coincided with Beijing experiencing “pandemic haze,” raising the public concerns about the effectiveness of imposed traffic policies to improve the air quality. This paper explores the relationship between local vehicle emissions and the winter haze in Beijing before and during the COVID-19 lockdown based on an integrated analysis framework, which combines a real-time on-road emission inventory, in situ air quality observations, and a localized numerical modeling system. We found that traffic emissions decreased substantially during the COVID-19 pandemic, but its imbalanced emission abatement of NOx (76%, 125.3 Mg/day) and volatile organic compounds (VOCs, 53%, 52.9 Mg/day) led to a significant rise of atmospheric oxidants in urban areas, resulting in a modest increase in secondary aerosols due to inadequate precursors, which still offset reduced primary emissions. Moreover, the enhanced oxidizing capacity in the surrounding regions greatly increased the secondary particles with relatively abundant precursors, which was transported into Beijing and mainly responsible for the aggravated haze pollution. We recommend that mitigation policies should focus on accelerating VOC emission reduction and synchronously controlling regional sources to release the benefits of local traffic emission control.

2. Sensitivity analysis of the surface ozone and fine particulate matter to meteorological parameters in China

   Shi, Zhihao, Huang, Lin, Li, Jingyi,  Ying, Qi, Zhang, Hongliang, and Hu, Jianlin

   Atmospheric chemistry and physics, Nov 2020

   Abs Doi

   Meteorological conditions play important roles in the formation of ozone (O-3) and fine particulate matter (PM2.5). China has been suffering from serious regional air pollution problems, characterized by high concentrations of surface O-3 and PM2.5. In this study, the Community Multiscale Air Quality (CMAQ) model was used to quantify the sensitivity of surface O-3 and PM2.5 to key meteorological parameters in different regions of China. Six meteorological parameters were perturbed to create different meteorological conditions, including temperature (T), wind speed (WS), absolute humidity (AH), planetary boundary layer height (PBLH), cloud liquid water content (CLW) and precipitation (PCP). Air quality simulations under the perturbed meteorological conditions were conducted in China in January and July of 2013. The changes in O-3 and PM2.5 concentrations due to individual meteorological parameters were then quantified. T has a great influence on the daily maximum 8 h average O-3 (O-3-8 h) concentrations, which leads to O-3-8 h increases by 1.7 in January in Chongqing and 1.1 ppb K-1 in July in Beijing. WS, AH, and PBLH have a smaller but notable influence on O-3-8 h with maximum change rates of 0.3 ppb %(-1), -0.15 ppb %(-1), and 0.14 ppb %(-1), respectively. T, WS, AH, and PBLH have important effects on PM2.5 formation of both in January and July. In general, PM2.5 sensitivities are negative to T, WS, and PBLH and positive to AH in most regions of China. The sensitivities in January are much larger than in July. PM2.5 sensitivity to T, WS, PBLH, and AH in January can be up to -5 mu gm(-3) K-1, -3 mu gm(-3)%(-1), -1 mu g m(-3) %(-1), and +0.6 mu g m(-3) %(-1), respectively, and in July it can be up to -2 mu g m(-3) K-1, -0.4 mu g m(-3) %(-1), -0.14 mu g m(-3) %(-1), and +0.3 mu g m(-3) %(-1), respectively. Other meteorological factors (CLW and PCP) have negligible effects on O-3-8 h (less than 0.01 ppb %(-1)) and PM2.5 (less than 0.01 mu g m(-3) %(-1)). The results suggest that surface O-3 and PM2.5 concentrations can change significantly due to changes in meteorological parameters, and it is necessary to consider these effects when developing emission control strategies in different regions of China.

3. Study of Secondary Organic Aerosol Formation from Chlorine Radical-Initiated Oxidation of Volatile Organic Compounds in a Polluted Atmosphere Using a 3D Chemical Transport Model

   Choi, Min Su, Qu, Xionghui, Zhang, Jie, Wang, Shuxiao, Li, Xinghua, Sun, Yele, Chen, Jianmin, and Ying, Qi

   Environmental science & technology, Nov 2020

   Abs Doi

   The impact of chlorine (Cl) chemistry on the formation of secondary organic aerosol (SOA) during a severe wintertime air pollution episode is investigated in this study. The Community Multiscale Air Quality (CMAQ) model v5.0.1 with a modified SAPRC-11 gas-phase mechanism and heterogeneous reactions for reactive chlorine species is updated to include the formation of chlorine radical (Cl-center dot)- initiated SOA (Cl-SOA) from aromatic compounds, terpenes, and isoprene. Reported SOA yield data on Cl-SOA formation from environmental chamber studies are used to derive the mass yield and volatility data for the two-product equilibrium-partitioning model. The heterogeneous reaction of particulate chloride (pCl(-)) leads to a significant increase in the Cl-center dot and hydroxyl radical (OH) concentrations throughout the domain. Monthly Cl-SOA concentrations range from 0.7 to 3.0 mu g m(-3), with increasing anthropogenic Cl emissions leading to higher Cl-SOA concentrations. Indirectly, this also leads to an increase of monthly SOA by up to 2.5-3.0 g mu m(-3) from the traditional OH oxidation pathways as well as the surface uptake of glyoxal and methylglyoxal. Increased OH concentrations, however, do not always lead to higher overall SOA concentrations in the entire domain. High OH reduces the lifetime of glyoxal/methylglyoxal (GLY/MGLY), making them less available to form SOA. In the Sichuan Basin (SCB) and part of Southwest China where high O-3 concentrations meet high pCl emissions, a higher Cl-center dot/OH ratio leads to net O-3 loss from the Cl-center dot + O-3 reaction, thus reducing SOA formation from the O-3 oxidation of volatile organic compounds (VOCs). Also, the competition between Cl-center dot and OH for VOCs could lead to lower overall SOA because the molar yields of the semivolatile products in Cl-VOC reactions are lower than their OH + VOC reaction counterparts. When Cl-center dot concentrations are further increased with higher emissions of Cl, precursor gases can be depleted and become the limiting factor in SOA formation. This study reveals the direct and indirect impacts of chlorine chemistry on SOA in polluted winter conditions, which are greatly affected by the Cl emissions, the ambient O-3 level, and the availability of SOA precursors.

4. Insights into source origins and formation mechanisms of nitrate during winter haze episodes in the Yangtze River Delta

   Shen, Juanyong, Zhao, Qianbiao, Cheng, Zhen, Wang, Peng,  Ying, Qi, Liu, Jie, Duan, Yusen, and Fu, Qingyan

   Science of the total environment, Nov 2020

   Abs Doi

   Nitrate became the most significant component of secondary inorganic aerosols (SNA, the sum of sulfate, nitrate and ammonium ions) as the emissions of sulfur dioxide (SO2) have been greatly reduced in China in recent years. In the Yangtze River Delta (YRD), nitrate could contribute 56% of SNA and 34% of total PM2.5 during haze episodes. In this study, a modified Community Multiscale Air Quality (CMAQ) model was used to provide a comprehensive understanding of nitrate source and formation under severe pollution during winter 2015 and 2016. Three haze episodes (HEP1, HEP2 and HEP3) and one clean episode (CEP) were selected to investigate the emission sector and regional contributions to nitrate at six environmental monitoring sites in the YRD. Source apportionment results showed that industry (35%), transportation (32%) and power (28%) sectors were the important sources of nitrate during haze episodes. Regional transport (60-98%) was responsible for the high nitrate concentrations in the YRD. During haze episodes, the high ozone production (PO3) rate (up to 700 ppb/h) and hydroxyl radicals (OH) removal rate (up to 9 ppb/h) were observed in the daytime indicating the important atmospheric oxidation capacity in the YRD. Also, the nitrogen oxidation ratio (NOR) analysis elucidated that daytime photochemistry played an important role in nitrate formation and the heterogeneous chemistry enhanced the high nitrate at night. Results from emission scenario analysis demonstrated that averaged nitrate concentration in Shanghai decreased by 18% during haze episodes under emission reductions of 20% NOx, NH3 and VOC in the YRD, and Shandong, Shanxi, Henan and Hebei provinces. Emission reduction on the regional scale (one city and its surrounding areas) is an efficient strategy to reduce nitrate concentration in the YRD. (c) 2020 Elsevier B.V. All rights reserved.

5. Importance of Wintertime Anthropogenic Glyoxal and Methylglyoxal Emissions in Beijing and Implications for Secondary Organic Aerosol Formation in Megacities

   Qiu, Xionghui, Wang, Shuxiao,  Ying, Qi, Duan, Lei, Xing, Jia, Cao, Jingyuan, Wu, Di, Li, Xiaoxiao, Chengzhi, Xing, Yan, Xiao, Liu, Cheng, and Hao, Jiming

   Environmental science & technology, Oct 2020

   Abs Doi

   Atmospheric glyoxal (GLY) and methylglyoxal (MGLY) are key precursors of secondary organic aerosol (SOA). However, anthropogenic emissions of GLY and MGLY and their contribution to surface GLY and MGLY concentrations, as well as the secondary organic aerosol (SOA) formation, are not well quantified. By developing an emission inventory of anthropogenic GLY and MGLY and improving the Community Multiscale Air Quality Model (CMAQ) with SOA formation from irreversible surface uptake of GLY and MGLY, as well as a precursor-origin resolved technique, we quantified the source contributions of GLY and MGLY and their impact on wintertime SOA formation in Beijing, China. The total emissions of GLY and MGLY in Beijing in 2017 are 1.1 x 10(4) kmol and 7.0 x 10(3) kmol, respectively. Anthropogenic primary emissions are found to be the dominant contributor to wintertime GLY and MGLY concentrations (similar to 74% for GLY and similar to 63% for MGLY). Anthropogenic primary emissions of GLY and MGLY contributes to 30% of GLY/MGLY SOA daily average concentration and accounts for up to 45% of nighttime GLY/MGLY SOA in winter. The study suggests that the anthropogenic GLY and MGLY emissions, mainly from gasoline vehicles and cooking, are important for SOA formation and shall be strictly controlled in Chinese megacities.

6. Ozone pollution in the west China rain zone and its adjacent regions, Southwestern China: Concentrations, ecological risk, and Sources

   Cao, Yuanfei, Qiao, Xue, Hopke, Philip K.,  Ying, Qi, Zhang, Yueying, Zeng, Yingying, Yuan, Yanping, and Tang, Ya

   Chemosphere, Oct 2020

   Abs Doi

   Located in the transitional region between the Sichuan Basin (SCB) and Qinghai-Tibetan Plateau (QTP), the West China Rain Zone (WCRZ) is a large-scale ecotone and partially belongs to the Southwest China Mountains, which is one of the world’s 34 biodiversity hotspots. Using observation data from national air quality stations and our own monitoring data, we investigated the risk from O-3 to vegetation and the major source-region of O-3 for two UNESCO (i.e., United Nations Educational, Scientific and Cultural Organization) world heritage properties (Mt. Qingcheng and Mt. Emei) and one city (Ya’an) in the WCRZ. The results show that the annual mean maximum daily 8-h average (MDA8) O-3 concentration in Mt. Qingcheng (54 ppb) was higher than that in the adjacent SCB cities (38-48 ppb). The acute and chronic risk levels from O-3 to vegetation were also higher in Mt. Qingcheng than at all the other sites. The mean MDA8 O-3 concentrations and the O-3 risk levels to vegetation in Mt. Emei and Ya’an fell in the range of that at the SCB and QTP cities. However, O-3 exposures at all the WCRZ, SCB, and QTP sites exceeded the empirical critical loads for natural ecosystems, forest trees, and highly O-3-sensitive plants. The SCB was identified as the largest source-region of O-3 for Mt. Qingcheng and Mt. Emei but other Chinese regions and northern India also had considerable contributions. To protect biodiversity and ecosystem services, there is a need to further systematically study O-3 and its ecological impacts for the entire WCRZ. (C) 2020 Elsevier Ltd. All rights reserved.

7. Estimating ground level PM2.5 concentrations and associated health risk in India using satellite based AOD and WRF predicted meteorological parameters

   Sahu, Shovan Kumar, Sharma, Shubham, Zhang, Hongliang, Chejarla, Venkatesh, Guo, Hao, Hu, Jianlin,  Ying, Qi, Xing, Jia, and Kota, Sri Harsha

   Chemosphere, Sep 2020

   Abs Doi

   PM2.5 concentrations in most of the Indian cities are in alarming levels. However, the current network of 308 monitoring stations are heterogeneously placed and do not cover many parts of the country. This limits the ability of agencies to measure the concentration which people are exposed to. In this study, ground level PM2.5 concentrations and the associated risk and mortality in India using satellite based AOD data for the year 2015 was estimated to identify the state specific number of more monitoring sites required. Results indicate that average PM2.5 concentrations were 89 mu g/m(3), which caused 1.61 million deaths including 0.34 million Chronic Obstructive Pulmonary Disease (COPD) deaths, 0.2 million Lung Cancer (LC) deaths, 0.53 million Ischemic Heart Disease (IHD) deaths and 0.70 million deaths due to Stroke. The years of life lost (YLL) per 1000 population due to exposure to PM2.5 indicated Delhi (North-India) to be severely affected by PM2.5 resulting in 227.47 years of life lost and was closely followed by Bihar (Eastern-India) (225.18), Rajasthan (Western-India) (225.05) and Uttar Pradesh (Northern-India) (213.16). Eastern India had the highest population weighted concentration (102.09 mu g/m(3)) and contributed to 23.46% of premature mortality and was followed by Central (75.32 mu g/m(3)) and Northern India (75.12 mu g/m(3)), thus indicating severity of air pollution in India and need for its constant monitoring. As per Indian regulatory agency’s guidelines, India still needs 1638 more air quality monitoring stations, of which North-Indian states require maximum number of additional stations i.e. 400, followed by 382 in eastern states. (C) 2020 Elsevier Ltd. All rights reserved.

8. Contribution of biogenic sources to secondary organic aerosol in the summertime in Shaanxi, China

   Xu, Yong, Chen, Yonggui, Gao, Jingsi, Zhu, Shengqiang,  Ying, Qi, Hu, Jianlin, Wang, Peng, Feng, Liguo, Kang, Haibin, and Wang, Dexiang

   Chemosphere, Sep 2020

   Abs Doi

   A revised Community Multi-scale Air Quality (CMAQ) model with updated secondary organic aerosol (SOA) yields and a more detailed description of SOA formation from isoprene (ISOP) oxidation was applied to study the spatial distribution of SOA, its components and precursors in Shaanxi in July of 2013. The emissions of biogenic volatile organic compounds (BVOCs) were generated using the Model of Emissions of Gases and Aerosols from Nature (MEGAN), of which ISOP and monoterpene (MONO) were the top two, with 1.73 x 10(9) mol and 1.82 x 10(8) mol, respectively. The spatial distribution of BVOCs emission was significantly correlated with the vegetation coverage distribution. ISOP and its intermediate semi-volatile gases were up to similar to 7.0 and similar to 1.4 ppb respectively in the ambient. SOA was generally 2 - 6 mu g/m(3), of which biogenic SOA (BSOA) accounted for as high as 84% on average. There were three main BVOCs Precursors including ISOP (58%) and MONO (8%) emit in the studied domain, and ISOP (9%) transported. The Guanzhong Plain had the highest BSOA concentrations of 3-5 mu g/m(3), and the North Shaanxi had the lowest of 2-3 mu g/m(3). More than half of BSOA was due to reactive surface uptake of ISOP epoxide (0.2-0.7 mu g/m(3), similar to 19%), glyoxal (GLY) (0.2-0.5 mu g/m(3), similar to 11%) and methylglyoxal (MGLY) (0.4 - 1.4 mu g/m(3), similar to 32%), while the remaining was due to the traditional equilibrium partitioning of semi- volatile components (0.1-1.2 mu g/m(3), similar to 25%) and oligomerization (0.2-0.4 mu g/m(3), similar to 12%). Overall, SOA formed from ISOP contributed 1-3 mu g/m(3) (similar to 80%) to BSOA. (C) 2020 Elsevier Ltd. All rights reserved.

9. Forecasting the cumulative number of COVID-19 deaths in China: a Boltzmann function-based modeling study

   Gao, Yuanyuan, Zhang, Zuqin, Yao, Wei,  Ying, Qi, Long, Cheng, and Fu, Xinmiao

   Infection control and hospital epidemiology, Jul 2020

   Abs Doi

   The COVID-19 outbreak is ongoing in China. Here, Boltzmann function-based analyses reveal the potential total numbers of COVID-19 deaths: 3,260 (95% confidence interval [CI], 3187-3394) in China; 110 (95% CI, 109-112) in Hubei Province; 3,174 (95% CI, 3095-3270) outside Hubei; 2,550 (95% CI, 2494-2621) in Wuhan City; and 617 (95% CI, 607-632) outside Wuhan.

10. Impacts of water partitioning and polarity of organic compounds on secondary organic aerosol over eastern China

    Li, Jingyi, Zhang, Haowen,  Ying, Qi, Wu, Zhijun, Zhang, Yanli, Wang, Xinming, Li, Xinghua, Sun, Yele, Hu, Min, Zhang, Yuanhang, and Hu, Jianlin

    Atmospheric chemistry and physics, Jun 2020

    Abs Doi

    Secondary organic aerosol (SOA) is an important component of fine particular matter (PM2.5). Most air quality models use an equilibrium partitioning method along with the saturation vapor pressure (SVP) of semivolatile organic compounds (SVOCs) to predict SOA formation. However, the models typically assume that the organic particulate matter (OPM) is an ideal mixture and ignore the partitioning of water vapor to OPM. In this study, the Community Multiscale Air Quality model (CMAQ) is updated to investigate the impacts of water vapor partitioning and nonideality of the organic-water mixture on SOA formation during winter (January) and summer (July) of 2013 over eastern China. The updated model treats the partitioning of water vapor molecules into OPM and uses the universal functional activity coefficient (UNIFAC) model to estimate the activity coefficients of species in the organic-water mixture. The modified model can generally capture the observed surface organic carbon (OC) with a correlation coefficient R of 0.7 and the surface organic aerosol (OA) with the mean fractional bias (MFB) and mean fractional error (MFE) of -0.28 and 0.54, respectively. SOA concentration shows significant seasonal and spatial variations, with high concentrations in the North China Plain (NCP), central China, and the Sichuan Basin (SCB) regions during winter (up to 25 mu g m(-3)) and in the Yangtze River Delta (YRD) during summer (up to 16 mu g m(-3)). In winter, SOA decreases slightly in the updated model, with a monthly averaged relative change of 10 %-20 % in the highly concentrated areas, mainly due to organic- water interactions. The monthly averaged concentration of SOA increases greatly in summer, by 20 %-50 % at the surface and 30 %-60 % in the whole column. The increase in SOA is mainly due to the increase in biogenic SOA in inland areas and anthropogenic SOA in coastal areas. As a result, the averaged aerosol optical depth (AOD) is increased by up to 10 %, and the cooling effect of aerosol radiative forcing (ARF) is enhanced by up to 15 % over the YRD in summer. The aerosol liquid water content associated with OPM (ALW(org)) at the surface is relatively high in inland areas in winter and over the ocean in summer, with a monthly averaged concentration of 0.5-3.0 and 5-7 mu g m(-3), respectively. The hygroscopicity parameter kappa of OA based on the kappa-Kohler theory is determined using the modeled ALW(org). The correlation of kappa with the O : C ratio varies significantly across different cities and seasons. Analysis of two representative cities, Jinan (in the NCP) and Nanjing (in the YRD), shows that the impacts of water partitioning and nonideality of the organic-water mixture on SOA are sensitive to temperature, relative humidity (RH), and the SVP of SVOCs. The two processes exhibit opposite impacts on SOA in eastern China. Water uptake increases SOA by up to 80 % in the organic phase, while including nonunity activity coefficients decreases SOA by up to 50 %. Our results indicate that both water partitioning into OPM and the activity coefficients of the condensed organics should be considered in simulating SOA formation from gas particle partitioning, especially in hot and humid environments.

11. Assessment of mobile source contributions in El Paso by PMF receptor modeling coupled with wind direction analysis

    Park, Eun Sug, Sullivan, David W., Kang, Dong Hun,  Ying, Qi, and Spiegelman, Clifford H.

    Science of the total environment, Jun 2020

    Abs Doi

    It is well-known that El Paso is the only border area in Texas that has violated national air quality standards. Mobile source emissions (including vehicle exhaust) contribute significantly to air pollution, along with other sources including industrial, residential, and cross-border. This study aims at separating unobserved vehicle emissions from air-pollution mixtures indicated by ambient air quality data. The level of contributions from vehicle emissions to air pollution cannot be determined by simply comparing ambient air quality data with traffic levels because of the various other contributors to overall air pollution. To estimate contributions from vehicle emissions, researchers employed advanced multivariate receptor modeling called positive matrix factorization (PMF) to analyze hydrocarbon data consisting of hourly concentrations measured from the Chamizal air pollution monitoring station in El Paso. The analysis of hydrocarbon data collected at the Chamizal site in 2008 showed that approximately 25% of measured Total Non-Methane Hydrocarbons (TNMHC) was apportioned to motor vehicle exhaust. Using wind direction analysis, researchers also showed that the motor vehicle exhaust contributions to hydrocarbons were significantly higher when winds blow from the south (Mexico) than those when winds blow from other directions. The results from this research can be used to improve understanding source apportionment of pollutants measured in El Paso and can also potentially inform transportation planning strategies aimed at reducing emissions across the region. (C) 2020 Elsevier B.V. All rights reserved.

12. Simulating and forecasting the cumulative confirmed cases of SARS-CoV-2 in China by Boltzmann function-based regression analyses

    Fu, Xinmiao,  Ying, Qi, Zeng, Tieyong, Long, Tao, and Wang, Yan

    Journal of infection, May 2020

    Doi
13. Ozone pollution over China and India: seasonality and sources

    Gao, Meng, Gao, Jinhui, Zhu, Bin, Kumar, Rajesh, Lu, Xiao, Song, Shaojie, Zhang, Yuzhong, Jia, Beixi, Wang, Peng, Beig, Gufran, Hu, Jianlin,  Ying, Qi, Zhang, Hongliang, Sherman, Peter, and McElroy, Michael B.

    Atmospheric chemistry and physics, Apr 2020

    Abs Doi

    A regional fully coupled meteorology-chemistry model, Weather Research and Forecasting model with Chemistry (WRF-Chem), was employed to study the seasonality of ozone (O-3) pollution and its sources in both China and India. Observations and model results suggest that O-3 in the North China Plain (NCP), Yangtze River Delta (YRD), Pearl River Delta (PRD), and India exhibit distinctive seasonal features, which are linked to the influence of summer monsoons. Through a factor separation approach, we examined the sensitivity of O-3 to individual anthropogenic, biogenic, and biomass burning emissions. We found that summer O-3 formation in China is more sensitive to industrial and biogenic sources than to other source sectors, while the transportation and biogenic sources are more important in all seasons for India. Tagged simulations suggest that local sources play an important role in the formation of the summer O-3 peak in the NCP, but sources from Northwest China should not be neglected to control summer O-3 in the NCP. For the YRD region, prevailing winds and cleaner air from the ocean in summer lead to reduced transport from polluted regions, and the major source region in addition to local sources is Southeast China. For the PRD region, the upwind region is replaced by contributions from polluted PRD as autumn approaches, leading to an autumn peak. The major upwind regions in autumn for the PRD are YRD (11 %) and Southeast China (10 %). For India, sources in North India are more important than sources in the south. These analyses emphasize the relative importance of source sectors and regions as they change with seasons, providing important implications for O-3 control strategies.

14. Wet deposition of sulfur and nitrogen at Mt. Emei in the West China Rain Zone, southwestern China: Status, inter-annual changes, and sources

    Zhang, Yueying, Cao, Yuanfei, Tang, Ya,  Ying, Qi, Hopke, Philip K., Zeng, Yingying, Xu, Xiaobin, Xia, Zhonglin, and Qiao, Xue

    Science of the total environment, Apr 2020

    Abs Doi

    The West China Rain Zone (WCRZ) is of ecological importance and thus, anthropogenic impacts on its vitality are of concern. To ascertain if China’s SO2 and NOx emissions reductions in the recent years are reflected in reduced impacts, sulfur and nitrogen wet deposition at Mt. Emei was observed during 2017-2019. The source contributions to sulfur and nitrogen wet deposition were estimated using the positive matrix factorization (PMF) and the source-oriented Community Multi-scale Air Quality (CMAQ) model. The annual Volume Weighted Mean (VWM) pH of precipitation increased from 4.01 to 4.75 in the 1980s-2000s to 5.39 in 2017-2019. However, 12% of the samples during 2017-2019 had pH < 4.50. The VWM SO42- concentration decreased from 80.9 to 26.0 mu eq L-1 from 2007-2009 to 2017-2019. The VWM NO3- concentration (18.3 mu eq L-1) in 2017-2019 was close to that measured in 2007-2009. Although the dry deposition fluxes onto forest canopy were underestimated, the mean annual total wet and dry deposition flux of nitrogen (24.3 kg N ha(-1) yr(-1)) was higher than the critical load (CL: 10.0-15.0 kg N ha(-1) yr(-1)), while the flux of sulfur (12.1 kg S ha(-1) yr(-1)) was lower than the CL (16.0-32.0 kg S ha(-1) yr(-1)). The annual wet deposition fluxes of SO42- and NO3- were mainly from industries (54%and 43%, respectively) and power plants (21% and 25%, respectively), and that of NH4+ was mostly from agriculture (88%). Emissions within and outside the Sichuan Basin (SCB) were both important sources& the wet deposition fluxes of sulfur (45% and 39%, respectively) and nitrogen (68% and 29%, respectively), and other unidentified sources accounted for I 6% and 3% of the sulfur and nitrogen fluxes, respectively. This study suggests that to protect Mt. Emei’s ecosystems, efforts are needed to further control sulfur and nitrogen deposition through reducing emissions within and outside the SCB. (C) 2020 Elsevier B.V. All rights reserved.

15. Source apportionment and regional transport of anthropogenic secondary organic aerosol during winter pollution periods in the Yangtze River Delta, China

    Liu, Jie, Shen, Juanyong, Cheng, Zhen, Wang, Peng,  Ying, Qi, Zhao, Qianbiao, Zhang, Yihua, Zhao, Yue, and Fu, Qingyan

    Science of the total environment, Mar 2020

    Abs Doi

    Since the concentrations of primary particles and secondary inorganic aerosol components have been reduced significantly due to stringent emission controls, quantifying the source contributions and regional transport of secondary organic aerosol (SOA) is critical to further improve air quality in eastern China. In this study, the Community Multiscale Air Quality (CMAQ) model coupled with the updated SAPRC-11 photochemical mechanism and a revised SOA module was applied to investigate the emission sector and regional contributions to SOA in winter 2015 (January 5-26, 2015) and 2016 (December 20, 2015 January 20, 2016) in the Yangtze River Delta (YRD). The model is generally capable of reproducing the observed SOA concentrations at the Qingpu Supersite in Shanghai. The observed and predicted SOA concentrations are 6.4 mu g/m(3) and 6.9 mu g/m(3) in winter 2015, and 5.7 mu g/m(3) and 9.6 mu g/m(3) in winter 2016. The mean fraction bias (MFB) of the hourly SOA predictions is 0.22 and 0.32, respectively. High SOA concentrations in the wintertime of YRD are mainly due to aromatic compounds and dicarbonyls (glyoxal and methylglyoxal), which, on average, account for 43% and 53% of total SOA, respectively. The average contributions of industrial, residential, and transportation sectors in the YRD region during the entire simulation periods are 61%, 22%, and 17%, respectively. At the Qingpu Supersite in Shanghai, the industrial sector contributes to as much as 65% of total SOA in the heavy pollution episode of 2016. The contributions from transportation and residential sectors are 16% and 17%. respectively, during the same episode. The industry - Corresponding 2, emissions from the Jiangsu, Zhejiang, and Shanghai are major contributors to the SOA at the Qingpu supersite during the heavy-polluted episodes, accounting for 31%, 19%, and 14% of the total predicted SOA. This study represents the first detailed regional modeling study of source region contributions to SOA in the YRD region and the detailed analyses of SOA in two winters months complement the previous SOA source apportionment studies focusing on seasonal average contributions. (C) 2019 Elsevier B.V. All rights reserved.

16. Regional source apportionment of summertime ozone and its precursors in the megacities of Beijing and Shanghai using a source-oriented chemical transport model

    Wang, Peng, Wang, Tao, and Ying, Qi

    Atmospheric environment, Mar 2020

    Abs Doi

    The Community Multiscale Air Quality (CMAQ) model with a source-oriented SAPRC-11 photochemical mechanism is developed in this study to quantify the source region contributions to surface O-3 in Beijing and Shanghai in August 2013. Non-background O-3 attributed to NOx (O-3_NOx) and volatile organic compounds (O-3_VOC) emitted from different source regions is determined using a three-regime approach that correctly attributes O-3 to NOx and VOC precursors throughout the entire range of NOx-VOC-O-3 formation sensitivity. Averaged over the entire month and all grid cells, local emissions (51%) and emissions from Hebei (31%) are the two major contributors to non-background daily maximum 8-h (DM8H) O-3 in Beijing. In Shanghai, local, Zhejiang and Jiangsu emissions account for 53%, 19% and 14% of the non-background DM8H O-3. Significant variations in local emission contributions are predicted among different model grid cells for both cities (Beijing, 6-80%; Shanghai, 3-76%). On high O-3 days in Beijing, the wind is persistently from the south with high wind speed (similar to 5 m s(-1)) in the evening and night. This leads to significant regional contributions of O-3 from Hebei, along with regional transport of VOCs and NOx. In Shanghai, high O-3 days are associated with southwesterly/westerly wind in the morning, rotating to southeast in the early afternoon in a counter-clockwise direction. The surface wind then gradually turns back to southwest in the afternoon until the next morning, along with reduced wind speed. In Shanghai, daytime O-3 at the urban center is almost entirely due to local emissions. Low wind speed in the evening and night time allows local NOx emissions to efficiently titrate regional O-3. In both cities, NOx emissions are not transported regionally as efficiently as VOCs. Source region contribution analysis of the concentration weighted maximum incremental reactivity (CWMIR) shows that VOCs from other regions are less reactive than locally emitted VOCs. HCHO and acetaldehyde (CCHO) generated from the oxidation of other VOCs are important contributors to regionally transported reactive VOCs. In both regions, the overall CWMIR in both cities is quite similar (similar to 4 mol O-3 per mole of VOC).

17. Long-term Field Evaluation of Low-cost Particulate Matter Sensors in Nanjing

    Bai, Lu, Huang, Lin, Wang, Zhenglu,  Ying, Qi, Zheng, Jun, Shi, Xiaowen, and Hu, Jianlin

    Aerosol and air quality research, Feb 2020

    Abs Doi

    Low-cost particulate matter (PM) sensors can be widely deployed to measure aerosol concentrations at higher spatial and temporal resolutions than traditional instruments, but they need to be carefully calibrated under ambient conditions. In this study, a long-term field experiment was conducted from December 2015 to May 2017 at a site in Nanjing to evaluate the capabilities of in-house built low-cost PM monitors using the Shinyei PPD42NS sensor for ambient PM2.5 monitoring. A BAM-1020 particulate monitor was co-located with the low-cost sensors to provide reference readings. Least-square regressions with linear and power-law functions, and an artificial neural network (ANN) technique were used to convert electrical instrument readings to ambient aerosol concentrations. Applying the ANN technique resulted in the best estimation of the hourly PM2.5 (R-2 = 0.84; mean normalized bias = 12.7% and mean normalized error (MNE) = 29.7%). The low-cost sensors displayed relatively good performance with high aerosol concentrations but larger errors with concentrations below 35 mu g m(-3). High humidity (RH > 75%) can cause a larger MNE for these sensors, but the impact of temperature was negligible in this study. A clear sensor deterioration trend was observed during the 18-month field calibration. High correlations were found between the data from a single low-cost sensor and the data from the BAM-1020 when the low-cost sensor was individually calibrated, but the correlations between measurements taken by different low-cost sensor units were only moderate, possibly due to internal sensor variations. The results suggest that these low-cost sensors can measure ambient PM2.5 concentrations with an acceptable level of accuracy, which can and should be improved by calibrating each sensor individually. Special attention should be paid to the accuracy of these sensors after long-term application and in highly humid environments.

18. Sources and health risks of ambient polycyclic aromatic hydrocarbons in China

    Han, Fenglin, Guo, Hao, Hu, Jianlin, Zhang, Jie,  Ying, Qi, and Zhang, Hongliang

    Science of the total environment, Jan 2020

    Abs Doi

    Polycydic aromatic hydrocarbons (PAHs) in the environment are of significant concerns due to their high toxicity to human health. PAHs measurements at limited air quality monitoring stations alone are insufficient to gain a complete understanding of ambient levels and public exposure of PAHs in China. This study simulated the concentrations of PAHs in China, identified the source contributions, and estimated the health risks. Anthropogenic emissions of 16 priority PAHs directly associated with health risks were generated from the global high-resolution PKU-FUEL-2007 inventory. Open biomass burning emissions were generated from the Fire Inventory from NCAR (FINN). PAHs concentrations in January, April, July, and October 2013 were simulated using the Community Multiscale Air Quality (CMAQ) model after incorporation of chemistry, partitioning, and deposition of PAHs. Predicted PAHs were in good agreement with seasonal and annual averaged observations from previous studies. The surface concentrations of 16-PAHs were higher in winter, with population weight average of 0.8 mu g/m(3) and peak value of 2.0 mu g/m(3) in urban areas in the North China Plain (NCP) and the Yangtze River Delta (YRD). Summer and spring exhibited lower concentrations of approximately 0.2 mu g/m(3) in most areas. The most important sources to PAHs were biomass burning and coal combustion in winter and industrial processes and oil and gas activities in summer. The cancer risk due to inhalation exposure of naphthalene (NAPH) and seven carcinogenic PAHs was significant, with the incremental lifetime cancer risk (ILCR) of >5 x 10(-4) in many urban and industrial areas. Exposure to PAHs was estimated to result in 15,198 excess lifetime cancer cases in China. Oil and gas burning associated with transport, residential and commercial activities were major contributors to ILCR in China. Coal combustion was predominant in Shanxi but less important in other regions. (C) 2019 Elsevier B.V. All rights reserved.

2019:22

1. Significant impact of heterogeneous reactions of reactive chlorine species on summertime atmospheric ozone and free-radical formation in north China

   Qiu, Xionghui,  Ying, Qi, Wang, Shuxiao, Duan, Lei, Wang, Yuhang, Lu, Keding, Wang, Peng, Xing, Jia, Zheng, Mei, Zhao, Minjiang, Zheng, Haotian, Zhang, Yuanhang, and Hao, Jiming

   Science of the total environment, Nov 2019

   Abs Doi

   Heterogeneous reactions of N2O5, O-3, OH, CIONO2, HOCl, CINO2, and NO2, with chlorine-containing particles are incorporated in the Community Multiscale Air Quality (CMAQ) model to evaluate the impact of heterogeneous reactions of reactive chlorine species on ozone and free radicals. Changes of summertime ozone and free radical concentrations due to the additional heterogeneous reactions in north China were quantified. These heterogeneous reactions increased the O-3, OH, HO2 and RO2 concentrations by up to 20%, 28%, 36% and 48% for some regions in the Beijing-Tianjin-Hebei (13TH) area. These areas typically have a larger amount of NOx emissions and a lower VOC/NOx ratio. The zero-out method evaluates that the photolysis of CINO2 and Cl-2 are the major contributors (42A% and 57.6%, respectively) to atmospheric Cl-center dot in the early morning hours but the photolysis of Cl-2 is the only significant contributor after 10:00 am. The results highlight that heterogeneous reactions of reactive chlorine species are important to atmospheric ozone and free-radical formation. Our study also suggests that the on-going NOx emission controls in the NCT region with a goal to reduce both O-3 and secondary nitrate can also have the co-benefit of reducing the formation Cl-center dot from CINO2 and Cl-2, which may also lead to lower secondary organic aerosol formation and thus the control of summertime PM2.5 in the region. (C) 2019 Elsevier B.V. All rights reserved.

2. Fine Particulate Matter and Ozone Pollution in the 18 Cities of the Sichuan Basin in Southwestern China: Model Performance and Characteristics

   Qiao, Xue, Guo, Hao, Wang, Pengfei, Tang, Ya,  Ying, Qi, Zhao, Xing, Deng, Wenye, and Zhang, Hongliang

   Aerosol and air quality research, Oct 2019

   Abs Doi

   The Sichuan Basin (SCB) is located in southwestern China and has a total population of 108.1 million across 18 cities, including the 2 largest in western China (Chengdu and Chongqing). As most air quality monitoring stations are located in urban areas, we simulated the PM2.5 (i.e., particulate matter with an aerodynamic diameter < 2.5 mu m) and ozone (O-3) in the entire SCB during winter (December 2014-February 2015) and summer (June-August 2015) by using the Weather Research and Forecasting (WRF) and the Community Multi-scale Air Quality (CMAQ) models. The simulated concentrations of 24-h PM2.5 and its major components generally agree with observations during both seasons, but the simulated 1-h and 8-h O-3 are acceptable only for summer. Increasing in severity from the rim of the SCB to its inner areas, the PM2.5, as well as its major components, exhibits hotspots near the central urban areas of Chongqing and Chengdu, with concentrations of 150-200 mu g m(-3) and 40-60 mu g m(-3) during winter and summer, respectively. The 1-h and 8-h O-3 exhibit no hotspots in the urban centers of Chongqing and Chengdu but show elevated levels in some rural and suburban areas (55-70 ppb and 65-80 ppb, respectively), including those on the western and southwestern rim of the SCB, and downwind of the urban center of Chongqing. Despite the great spatial variations in the PM2.5 and O-3 concentrations, the vast majority of the basin fails to meet the WHO guidelines for 24-h PM2.5 (25 mu g m(-3)) and 8-h O-3 (similar to 47 ppb) on > 70% of the days during winter and > 40% of the days during summer, respectively. Based on the aforementioned spatial patterns of the PM2.5 and O-3 concentrations, and the wind directions within the basin, strictly controlling emissions originating in the SCB may greatly reduce PM2.5 and O-3 concentrations within the basin.

3. Source apportionment of organic pollutants in fine and coarse atmospheric particles in Doha, Qatar

   Javed, Wasim, Iakovides, Minas, Garaga, Rajyalakshmi, Stephanou, Euripides G., Kota, Sri Harsha,  Ying, Qi, Wolfson, Jack M., Koutrakis, Petros, and Guo, Bing

   Journal of the air & waste management association, Nov 2019

   Abs Doi

   In this study, we investigated the sources of organic pollutants associated with fine (PM2.5) and coarse (PM2.5-10) atmospheric particulate matter in Doha, Qatar based on an eight-month sampling campaign conducted from May to December 2015. Multiple organic compound tracers including 36 PAH members, 25 n-alkane homologs, 17 hopanes, and 12 steranes were used for organic aerosols source apportionment. Source apportionment based on specific molecular markers, molecular diagnostic ratios/indices, and positive matrix factorization (PMF) modeling showed that similar sources are responsible for both fine- and coarse-particle organic pollutants. PMF analysis showed that biogenic aerosols, fugitive dust emissions, gasoline engine emissions, diesel engine emissions, and heavy oil combustion were the five main pollution sources of organic aerosols, which agreed well with the results from the diagnostic ratios analysis. The conditional bivariate probability functions (CPF) and potential source contribution function (PSCF) indicated that both regional (i.e., mixed biogenic/secondary particles and oil refinery/shipping emissions) and local sources contributed to airborne organic aerosol concentrations observed at the site, depending on the wind speed and direction. It appears that the relatively high levels of organic pollutants were contributed by local anthropogenic sources, such as fossil fuel combustion, vehicular emissions, and fugitive dust emissions. The high levels of local contributions indicated that there might be great opportunities for Qatar to considerably reduce emissions so that population exposures to carbonaceous aerosols and the public health risks associated with air pollution can be minimized. Implications: Multiple organic tracers and various source apportionment techniques have been used for convincing source apportionment. It was found that both long-range and local sources have a significant impact on atmospheric carbonaceous particles in the area, depending on the wind conditions. Relatively high levels of organic pollutants attributed to local anthropogenic sources indicate that there are great opportunities for Qatar to establish and implement more efficient pollution control measures and policies. Regional sources such as petroleum refineries and shipping-vessels emissions in the Gulf region should also be regulated and managed through regional cooperation to improve the air quality in the region.

4. Simulation of summer ozone and its sensitivity to emission changes in China

   Guo, Hao, Chen, Kaiyu, Wang, Pengfei, Hu, Jianlin,  Ying, Qi, Gao, Aifang, and Zhang, Hongliang

   Atmospheric pollution research, Sep 2019

   Abs Doi

   Rapid economic growth and associated emission increase in China have led to severe air pollution in recent decades. As fine particulate matter concentration is decreasing due to strict control measures, ozone (O-3) concentration has an increasing trend with adverse effects on human health and ecosystems. In this study, the Community Multi-scale Air Quality (CMAQ) model was used to investigate the formation of O-3 in China during three high concentration episodes in summer 2013 and analyzed its sensitivity to emission changes. Compared with observation data, O-3 performance met the EPA criteria of mean normalized bias (MNB) within +/- 0.15 in major parts of China including five megacities. The diurnal variation of O-3 had similar trend with temperature. The August episode (6-12) had the highest daily maximum 1-h O-3 of similar to 100 ppb in North China Plain (NCP), while the July episode (11-19) had the lowest concentrations of similar to 50 ppb. The O-3 production rates (OPR) were higher at NCP and the Yangzi River Delta (YRD), but O-3 production efficiencies (OPE) acted in contrary. O-3 isopleth showed that NOx controlled O-3 concentration in most areas of China. Reducing VOC would have minor effects on O-3 concentrations while reducing NOx could largely reduce O-3 concentration except for urban areas such as Shanghai and Guangzhou. Linear correlations were observed between secondary organic aerosol (SOA) and O-x(O-3 + NO2) concentrations in August at Shanghai and Guangzhou, indicating correlations between O-3 and other photochemical compounds. This study provides valuable information for designing effective control strategies for O-3 in China.

5. Source apportionment of summertime ozone in China using a source-oriented chemical transport model

   Wang, Peng, Chen, Yuan, Hu, Jianlin, Zhang, Hongliang, and Ying, Qi

   Atmospheric environment, Aug 2019

   Abs Doi

   Contributions of industries, power plants, residential, transportation, open burning, and biogenic sectors to summertime ozone (O-3) in China in August 2013 are quantified using an improved O-3 source apportionment method implemented in a source-oriented Community Multiscale Air Quality (CMAQ) model. The new O-3 source apportionment method attributes in-situ O-3 formed in each time step to nitrogen oxides (NOx) and volatile organic compounds (VOCs) with a new attribution scheme that considers NOx-VOC-O-3 formation sensitivity in NOx-limited, transition, and VOC-limited regimes (three regimes, 3R). This represents an improvement from the traditional O-3 source apportionment models, in which O-3 formation sensitivity is divided into two-regimes (2R), either NOx-limited or VOC-limited. An expanded source-oriented gas phase chemical mechanism is developed to concurrently track NOx and primary VOCs and their oxidation products from different sources. The source-resolved NO2 photolysis rates and the NO to NO2 conversion rates by peroxy radicals from the source-oriented chemical mechanism are then used to apportion O-3 to NOx (O-3-NOx) and VOCs (O-3_VOC) from different emission sources. Industries, transportation, power plants and biogenic sources are the major emission sectors to O-3. High industrial O3NOx (8-15 ppb; 20-25% of total O-3) is mainly located in north and northeast China, the Yantze River Delta (YRD) and part of the Sichuan Basin (SCB). Transportation O3NOx accounts for 10-15% of total O-3 in most urban areas. Power plants’ contributions to O-3_NOx (10-15%) are mostly located in Shanxi, Shaanxi, Ningxia and part of Shandong and Jiangsu. The contribution of soil NOx to O-3_NOx is highest in regions in west, central and south China with less direct anthropogenic emission influences. VOC-limited grid cells are mostly located at urban cores and large city clusters in the YRD and Pearl River Delta (PRD) regions. Biogenic and industrial sectors are the most important emission sectors that contribute to O-3_VOC, accounting for more than 85% of the O-3_VOC in China. In north and east provinces, more than 50% of the O-3 is non-background, with the provinces in north China having higher overall O-3. The Beijing-Tianjin-Hebei (BTH) region has an area-averaged 8-hr O-3 of 75 ppb in August 2013 and about half is non-background. Contributions of industries, transportation, power and biogenic sources to non-background O-3 are 37%, 22%, 13% and 23%, respectively. The relative contribution of biogenic emissions to non-background O-3 is lower on high 8-hr O-3 days. The 2R and 3R approaches show significant differences in assessing the relative importance of O-3_NOx and O3VOC, with the 2 regime approach predicting lower O3NOx but higher O3VOC. The new source allocation method for O-3_VOC can lead to up to 10% differences for industrial and biogenic sectors.

6. Using Chemical Transport Model Predictions To Improve Exposure Assessment of PM(2.5 )Constituents

   Hu, Jianlin, Ostro, Bart, Zhang, Hongliang,  Ying, Qi, and Kleeman, Michael J.

   Environmental science & technology letters, Aug 2019

   Abs Doi

   Air pollution health-effect studies commonly use central monitor concentrations (CMCs) of airborne fine particulate matter (PM2.5) to represent population exposure near the monitoring sites. The spatial distribution of PM2.5 constituents is presumed to be the same and is well-represented by the CMC. Here we apply chemical transport models in California and show that the population-weighted concentrations (PWCs) of secondary PM2.5 constituents within the 12 km buffer zone are within +/- 20% of the respective CMC values, but the PWCs of primary PM2.5 constituents differ from the CMC values by -40 to +60%. The appropriate CMC representative distance varies significantly in different cities due to the unique combination of population distribution, emissions patterns, and meteorology at each location. We conclude that exposure misclassification can be significant if the same representative distance is assumed for multiple CMC PM2.5 constituents across all sites in a single air pollution epidemiology study that has a large spatial and temporal range. This misclassification will increase the variance around the effect estimate and therefore reduce the likelihood of finding a statistically significant effect.

7. Spatial-temporal variations and source contributions to forest ozone exposure in China

   Qiao, Xue, Wang, Peng, Zhang, Jie, Zhang, Hongliang, Tang, Ya, Hu, Jianlin, and Ying, Qi

   Science of the total environment, Jul 2019

   Abs Doi

   As surface ozone (O-3) concentrations have significantly increased in many regions of China, it is concerned that O-3 may cause negative impacts on forests in the country. To estimate the risks of O-3 exposure to forest health, several frequently used O-3 exposure indices (M7, M24, N100, SUM60, W126, and AOT40f) were calculated for the entire year of 2013 and the source contributions to exposure in April and August were quantified using a source-oriented version of the Community Multiscale Air Quality (CMAQ) model. Critical loads for natural ecosystems (12 ppm-h for SUM60) and for moderately sensitive plant species (23.8 ppm-h for W126) are exceeded in 85% and 75% of the forest areas in China, respectively. About 90% of the forest areas have AOT40f higher than the critical load of 10 ppm-h. Forests in the western rim of the Sichuan Basin (WSCB), parts of the southern rim of the Qinghai-Tibetan Plateau (SQTP), Yunnan Province, and the North China Plain (NCP) have higher O-3 exposure than that of other areas. In spring, transport of O-3 and precursors from Southeast Asia have significant contributions to O-3 exposure for forests in Yunnan, SQTP and to a less extent in WSCB. In both spring and summer, industries and transportation sectors have large contributions to O-3 exposure along the WSCB and in the NCP. A higher priority in future field investigations to assess O-3 impacts on forests in China should be given to these regions. The results also suggest that O-3 production in China is much more due to nitrogen oxides (NOx) than due to volatile organic compounds (VOCs). In order to protect China’s forest from O-3, it would be most efficient to reduce NOx emissions from industries, transportation, and other countries in general. (C) 2019 Elsevier B.V. All rights reserved.

8. Past and future trends of vehicle emissions in Tianjin, China, from 2000 to 2030

   Sun, Shida, Zhao, Gang, Wang, Ting, Jin, Jiaxin, Wang, Peng, Lin, Yingchao, Li, Haobo,  Ying, Qi, and Mao, Hongjun

   Atmospheric environment, Jul 2019

   Abs Doi

   The rapid growth of the vehicle population was regarded as an important factor that contributed to the urban air pollution in China during the past decades. We used Tianjin, a typical megacity facing vehicle pollution problems, as the study domain to investigate a comprehensive estimation of vehicle emissions, including carbon monoxide (CO), volatile organic compounds (VOCs), nitrogen oxides (NOx), inhalable particles (PM10), carbon dioxide (CO2) and sulphur dioxide (SO2), from 2000 to 2030. The Computer Programme to calculate Emissions from Road Transport (COPERT) model was used to simulate the vehicle emission factors. Historical simulations show that the total emissions of CO, VOCs, NOx, PM10, CO2, and SO2 changed from 545.1 Gg, 70.04 Gg, 60.19 Gg, 6.57 Gg, 6.82 Tg and 12.88 Gg to 259.11 Gg, 34.01 Gg, 55.14 Gg, 3.42 Gg, 25.30 Tg and 0.16 Gg from 2000 to 2016, respectively. Passenger cars (PC) and light-duty vehicles (LDV) were the main contributors to the CO and VOCs emissions. Heavy-duty trucks (HDT) and buses (BUS) were the important contributors to NOx and PM10. PC was the major contributor to CO2 and SO2. With respect to the future, four Single Control Policy Scenarios (SCPS), including Passenger car Population Regulation (PPR), Emission Standard Updating (ESU), Public Transportation Promotion (PTP) and Electric Vehicle Popularity (EVP), and Integrated Scenarios (IS), were assembled to describe the impact of future policies on vehicle pollution from 2017 to 2030. Among all SCPS, the results show that the ESU is the more effective policy to control emissions of CO, NOx and PM10, while PPR is the more effective way to reduce emissions of VOCs, CO2, and SO2.

9. Aerosol Ammonium in the Urban Boundary Layer in Beijing: Insights from Nitrogen Isotope Ratios and Simulations in Summer 2015

   Wu, Libin, Ren, Hong, Wang, Peng, Chen, Jing, Fang, Yunting, Hu, Wei, Ren, Lujie, Deng, Junjun, Song, Yu, Li, Jie, Sun, Yele, Wang, Zifa, Liu, Cong-Qiang,  Ying, Qi, and Fu, Pingqing

   Environmental science & technology letters, Jul 2019

   Abs Doi

   This study investigates the concentrations and delta N-15 values of NH4+ in PM2.5 at three heights (8, 120, and 260 m) on a 325 m tower in urban Beijing. NH4+ concentrations were lower during the Parade Blue Period (August 20 to September 3, 2015) due to strict air pollution control and favorable meteorological conditions, while delta N-15-NH4+ values were higher because the regional transport of agricultural sources (lower ratios of delta N-15-NH4+) was less significant. Vertical profiles of NH4+ increased with height while delta N-15-NH4+ decreased, indicating an enhanced contribution from regional transport at high altitudes. The results of the “MixSIAR” isotopic mixing model indicate that agricultural emission produces 47% of the ground-surface NH4+ and reaches 51-56% at high altitudes. Results from a source-oriented air quality model and the 2016 MEIC emission inventory suggest that non-agricultural NH3 emissions are likely underestimated and NH3 slip from selective catalytic reduction processes should be included to explain the observed source contributions.

10. Sources of humic-like substances (HULIS) in PM2.5 in Beijing: Receptor modeling approach

    Li, Xinghua, Yang, Kaiqiang, Han, Junzan,  Ying, Qi, and Hopke, Philip K.

    Science of the total environment, Jun 2019

    Abs Doi

    Recent work has identified the presence of humic-like substances (HULIS) in ambient fine particulate matter (PM2.5) in Beijing, China and that residential coal combustion as well as biomass burning are significant contributors to its presence. These results were based on the characterization of emissions from representative stoves and modeling of the aerosol with the Community Multiscale Air Quality (CMAQ) chemical transport model. The CMAQ source apportionment estimated that residential coal and biofuel burning and secondary aerosol formation were important annual sources of ambient HULIS, contributing 47.1%, 15.1%, and 38.9%, respectively. In this study, chemical composition data including concentrations of water-soluble organic carbon and HULIS across four seasons during 2012-2013 were analyzed with positive matrix factorization (PMF) to provide a complementary source apportionment. The PMF results indicate that the identified sources were Traffic, Biomass Burning, Nitrate/Sulfate, Incineration, Sulfate, Coal Combustion/Ammonium Chloride, Residential Coal/Biofuel Combustion, and Road Dust/Soil with mass contributions (fractions) to PM2.5 of 12.35 (10.4%), 8.70 (8.9%), 24.51 (22.4%), 5.64 (7.2%), 25.14 (24.5%), 7.10 (6.2%), 14.18 (15.4%), and 5.33 mu g/m(3) (5.0%), respectively. The contributions to the observed HULIS concentrations were 0.63 (10.9%), 0.38 (6.4%), 0.07 (1.7%), 0.00 (0%), 1.12 (28.8%), 0.00 (0%), 1.50 (52.2%), and 0.01 mu g/m(3) (0.3%), respectively. These PMF modeling results were in reasonable agreement with the CMAQ values supporting the attribution of significant amounts of primary HULIS to residential coal and biofuel combustion. Currently, efforts are underway in China to replace solid fuel combustion for heating and cooking with natural gas and electricity by 2020. Thus, future studies should be able to see substantial reductions in both PM2.5 and HULIS in the near term future. (C) 2019 Elsevier B.V. All rights reserved.

11. Modeling the impact of heterogeneous reactions of chlorine on summertime nitrate formation in Beijing, China

    Qiu, Xionghui,  Ying, Qi, Wang, Shuxiao, Duan, Lei, Zhao, Jian, Xing, Jia, Ding, Dian, Sun, Yele, Liu, Baoxian, Shi, Aijun, Yan, Xiao, Xu, Qingcheng, and Hao, Jiming

    Atmospheric chemistry and physics, May 2019

    Abs Doi

    Comprehensive chlorine heterogeneous chemistry is incorporated into the Community Multiscale Air Quality (CMAQ) model to evaluate the impact of chlorine-related heterogeneous reaction on diurnal and nocturnal nitrate formation and quantify the nitrate formation from gasto-particle partitioning of HNO3 and from different heterogeneous pathways. The results show that these heterogeneous reactions increase the atmospheric Cl-2 and ClNO2 level (similar to 100 %), which further affects the nitrate formation. Sensitivity analyses of uptake coefficients show that the empirical uptake coefficient for the O-3 heterogeneous reaction with chlorinated particles may lead to the large uncertainties in the predicted Cl-2 and nitrate concentrations. The N2O5 uptake coefficient with particulate Cl- concentration dependence performs better in capturing the concentration of ClNO2 and nocturnal nitrate concentration. The reaction of OH and NO2 in the daytime increases the nitrate by similar to 15 % when the heterogeneous chlorine chemistry is incorporated, resulting in more nitrate formation from HNO3 gas-to-particle partitioning. By contrast, the contribution of the heterogeneous reaction of N2O5 to nitrate concentrations decreases by about 27 % in the nighttime, when its reactions with chlorinated particles are considered. However, the generated gas-phase ClNO2 from the heterogeneous reaction of N2O5 and chlorine-containing particles further reacts with the particle surface to increase the nitrate by 6 %. In general, this study highlights the potential of significant underestimation of daytime concentrations and overestimation of nighttime nitrate concentrations for chemical transport models without proper chlorine chemistry in the gas and particle phases.

12. Local and regional contributions to fine particulate matter in the 18 cities of Sichuan Basin, southwestern China

    Qiao, Xue, Guo, Hao, Tang, Ya, Wang, Pengfei, Deng, Wenye, Zhao, Xing, Hu, Jianlin,  Ying, Qi, and Zhang, Hongliang

    Atmospheric chemistry and physics, May 2019

    Abs Doi

    The Sichuan Basin (SCB) is one of the regions suffering from severe air pollution in China, but fewer studies have been conducted for this region than for the more developed regions in eastern and northern China. In this study, a source-oriented version of the Community Multiscale Air Quality (CMAQ) model was used to quantify contributions from nine regions to PM2.5 (i.e., particulate matter, PM, with an aerodynamic diameter less than 2.5 mu m) and its components in the 18 cities within the SCB in the winter (December 2014 to February 2015) and summer (June to August 2015). In the winter, citywide average PM2.5 concentrations are 45-126 mu g m(-3), with 21 %-51 % and 39 %-66 % being due to local and nonlocal emissions, respectively. In the summer, 15 %-45 % and 25 %-52 % of citywide average PM2.5 (14-31 mu g m(-3) ) are due to local and nonlocal emissions, respectively. Compared to primary PM (PPM), the inter-region transport of secondary inorganic aerosols (SIA), including ammonia, nitrate, and sulfate ions (NH4+, NO3-, and SO42-, respectively), and their gas-phase precursors are greater. The region to the east of SCB (R7, including central and eastern China and others) is the largest contributor outside the SCB, and it can contribute approximately 80 % of PM2.5 in the eastern, northeastern, and southeastern rims of the SCB but only 10 % in other SCB regions in both seasons. Under favorable transport conditions, regional transport of air pollutants from R7 could account for up to 35-100 mu g m(-3) of PM2.5 in each of the SCB cities in the winter. This study demonstrates that it is important to have joint emission control efforts among cities within the SCB and regions to the east in order to reduce PM2.5 concentrations and prevent high PM2.5 days for the entire basin.

13. Evaluation of particulate matter deposition in the human respiratory tract during winter in Nanjing using size and chemically resolved ambient measurements

    Liu, Xiaoyuan, Nie, Dongyang, Zhang, Kai, Wang, Ziyao, Li, Xiaoqian, Shi, Zhihao, Wang, Yiyi, Huang, Lin, Chen, Mindong, Ge, Xinlei,  Ying, Qi, Yu, Xingna, Liu, Xingang, and Hu, Jianlin

    Air quality atmosphere and health, May 2019

    Abs Doi

    Size-segregated ambient aerosols were collected by a five-stage impactor at a suburban Nanjing site during the winter of 2016-2017 to estimate the chemical composition and size distribution of particles deposited in different parts of the human respiratory tract. Chemical compositions of carbonaceous aerosols, water-soluble ions, and trace heavy metals were measured. Particulate matter (PM) mass deposited in nasopharyngeal (NOPL), tracheobronchial (TB), and pulmonary (P) was obtained by integrating the size-dependent deposition fractions. During the sampling period, the average PM10 and PM2.5 concentrations were 108.8 +/- 30.8 and 77.2 +/- 24.2g/m(3), respectively. Organic matter and water-soluble ions were major components in fine particles. The fine particles had a significant contribution to the particulate pollution in winter Nanjing. The mass concentration of particles increases significantly from the clean days to the pollution days, especially for particles in 1-2.5m. The proportion of NO3- and undetected components in particulate matter increases on pollution days, while the proportion of elemental carbon (EC), SO42-, and NH4+ decreases. During the study period, the total particulate matter deposit per minute in the NOPL, TB, and P was 1.06 +/- 0.35, 0.10 +/- 0.03, and 0.42 +/- 0.14g, respectively, assuming normal respiration of tidal volumes of 1450cm(3) per breath and 15 breaths per minute. Particles in 2.5-10m had the highest deposition mass in NOPL of 0.57 +/- 0.16g, while particles in <0.5m had the highest deposition mass in TB (0.03 +/- 0.01g), and particles in 1-2.5m had the highest deposition mass in P (0.14 +/- 0.06g). The total particulate matter deposited in the NOPL, TB, and P increased from 0.79 +/- 0.25, 0.08 +/- 0.02, and 0.30 +/- 0.09g on the clean days to 1.23 +/- 0.29g, 0.12 +/- 0.03g, and 0.49 +/- 0.11g on the pollution days. More secondary inorganic aerosol (SNA) and metals (especially Zn, Cr, and Cu) were in the PM deposited in TB and P than in the ambient PM, while more undetected components in the PM deposited in NOPL. The chemical composition fractions deposited in a specific region were different from those measured in the ambient atmosphere, indicating that health effect studies of PM should consider the deposition rates of PM in the human respiratory tract, in addition to the ambient size and chemical characteristics of ambient PM.

14. Responses of PM2.5 and O-3 concentrations to changes of meteorology and emissions in China

    Wang, Pengfei, Guo, Hao, Hu, Jianlin, Kota, Sri Harsha,  Ying, Qi, and Zhang, Hongliang

    Science of the total environment, Apr 2019

    Abs Doi

    Tremendous efforts have been made to reduce the severe air pollution in China since 2013. However, the annual and peak fine particulate matter (PM2.5) concentrations during severe events in winter did not always reduce as expected. This is partially due to the inter-annual variation of meteorology, which affects the emission, transport, transformation, and deposition processes of air pollutants. In this study, the responses of PM2.5 and ozone (O-3) concentrations to changes in emission and meteorology from 2013 to 2015 were investigated based on ambient measurements and the Community Multi-Scale Air Quality (CMAQ) model simulations with anthropogenic emissions. It is found that emission reductions in 2014 and 2015 effectively reduced PM2.5 concentrations by 23.9 and 43.5 mu g/m(3), respectively, but was partially counteracted by unfavorable meteorology. The negative effects from unfavorable meteorology were significant in extreme pollution events. For example, in December 2015, unfavorable meteorology caused a great increase (90 mu g/m(3)) of PM2.5 in Beijing. Reduction of primary PM and gaseous precursors led to 13.4 and 16.5 ppb increase of O-3-8 h daily concentrations in the summertime in 2014 and 2015 in comparison of 2013, which was likely caused by the increase of solar actinic flux due to PM reduction. In addition, reduction of nitrogen oxides (NOx) emissions in areas with negative NOx-O-3 sensitivity could lead to an increase of O-3 formation when the reduction of volatile organic compounds (VOCs) was not sufficient. This unintended enhanced O-3 formation could also lead to higher O-3 in downwind areas. This study emphasizes the role of meteorology in pollution control, validates the effectiveness of PM2.5 control measures in China, and highlights the importance of appropriate joint reduction of NOx and VOCs to simultaneously decrease O-3 and PM2.5 for higher air quality. (C) 2019 Elsevier B.V. All rights reserved.

15. Source contributions to poor atmospheric visibility in China

    Li, Xun, Huang, Lin, Li, Jingyi, Shi, Zhihao, Wang, Yiyi, Zhang, Hongliang,  Ying, Qi, Yu, Xingna, Liao, Hong, and Hu, Jianlin

    Resources conservation and recycling, Apr 2019

    Abs Doi

    China suffers from serious haze pollution characterized by extremely low visibility due to intensive air pollutant emissions. Designing effective visibility impairment control strategies requires quantitative measures of the contributions of different sources. In this study, a source-oriented Community Multiscale Air Quality model was applied to quantitatively determine the source contributions to visibility impairment in China in 2013. Emissions of air pollutants from seven source categories (power plants, residential sources, industries, transportation, open burning, dust, and agriculture) were separately tracked. The industrial sector dominates the visibility impairment in Beijing, Chongqing, Guangzhou, and Shanghai, contributing to 32.6-40.7% of the overall light extinction coefficient (b(ext)). Agriculture and power sources contribute 13.0-16.7% and 12.6-14.9% to b(ext), respectively. The residential sector is the largest source of visibility impairment in Xi’an (39.5%). It also contributes 12.3-25.2% in Beijing, Chongqing, Guangzhou, and Shanghai. Transportation (6.3-10.2%), open burning (1.7-8.8%), and dust emission (1.0-3.6%) have relatively smaller contributions to b(ext) in these cities. The source contributions to b(ext) exhibit strong spatial and seasonal variations. Contributions from industrial, power, and residential sectors are higher in the North China Plain, Northeast China, and Sichuan Basin than in other regions of China. Industrial and residential emissions become the most important sources of visibility impairment in winter. In other seasons, industrial, power, and agriculture sources are important. The large spatial and seasonal variations in the sources of b(ext), suggest that different pollutants mitigation programs should be designed for different regions and times of the year.

16. Investigating the PM2.5 mass concentration growth processes during 2013-2016 in Beijing and Shanghai

    Sun, Jinjin, Liang, Mingjie, Shi, Zhihao, Shen, Fuzhen, Li, Jingyi, Huang, Lin, Ge, Xinlei, Chen, Qi, Sun, Yele, Zhang, Yanlin, Chang, Yunhua, Ji, Dongsheng,  Ying, Qi, Zhang, Hongliang, Kota, Harsha, and Hu, Jianlin

    Chemosphere, Apr 2019

    Abs Doi

    The North China Plain and the Yangtze River Delta are the two of the most heavily polluted regions in China. Observational studies revealed that ‘explosive’ PM2.5 mass concentration growths frequently occurred in the two regions. This study analyzed all the PM2.5 mass concentration growth processes from clean condition (i.e., <35 mu g m(-3)) to heavy pollution condition (i.e., >150 mu g m(-3)) in Beijing (BJ) and Shanghai (SH), two representative cities of the two regions, using hourly monitored PM2.5 concentrations during 2013-2016. 173 and 76 growth processes were identified in BJ and SH, respectively. PM2.5 rising rates (PMRR) and dynamic growth durations were calculated to illustrate the characteristics of the growth processes. Hourly particulate chemical composition data and meteorological data in BJ and SH were further analyzed. The 4-year averaged PMRR of PM2.5 total mass were similarly of 7.11 +/- 9.82 mu g m(-3) h(-1) in BJ and 6.71 +/- 6.89 mu g m(-3) h(-1) in SH. A decreasing trend was found for the PM2.5 growth processes in two cities from 2013 to 2016, reflecting the effectiveness of emission controls implemented in the past years. The contributions of particulate components to the PM2.5 total mass growth were different in BJ and SH. Average PMRR value of PM1 organic aerosols (OA), SO24-, NO3-, and NH4+ in BJ was 1.90, 0.95, 0.82, and 0.53 mu g m(-3) h(-1), respectively. Average PMRR of PM2.5 OA, SO42-, NO3-, and NH4+ in SH was 1.70, 1.18, 1.99 and 1.14 mu g m(-3) h(-1), respectively. Based on the contributions of different components, the PM2.5 mass concentration growth processes in BJ and SH were proposed to be classified into ‘other components-dominant growth processes’, ‘all components-contributing growth processes’, ‘one or more explosive secondary components-dominant growth processes’, and ‘mixed-factor growth processes’. Potential source contribution function analysis and the meteorological condition analysis showed that source origins and prevailing wind for the two cities during different categories of growth processes had substantial difference. The important source areas included Hebei and Shandong for BJ, and Jiangsu and Anhui for SH. The dominant wind directions during growth processes were northeast, south and southwest in BJ, and were west to north in SH. The results suggested the contributing components, the prevailing wind conditions, and the formation processes were substantially different in the two cities, despite the similar PMRR of PM2.5 total mass during the growth processes between BJ and SH. Future research is needed to study the detailed formation mechanisms of the different PM2.5 mass concentration growth processes in the two cities. (C) 2019 Elsevier Ltd. All rights reserved.

17. Projected air quality and health benefits from future policy interventions in, India

    Chen, Kaiyu, Guo, Hao, Hu, Jianlin, Kota, Sri, Deng, Wenye,  Ying, Qi, Myllyvirta, Lauri, Dahiya, Sunil, and Zhang, Hongliang

    Resources conservation and recycling, Mar 2019

    Abs Doi

    Air pollutants have been an urgent environmental problem in India due to adverse impacts on human health and social-economical lost. Different control strategies have been discussed to reduce air pollution, but possible outputs have not been identified. In this study, the Community Multi-scale Air Quality (CMAQ) model was applied to simulate potential benefits from future emission control with unchanged meteorology. Fourteen scenarios towards energy, residential, agriculture, industry, and open burning were simulated and the changes in ozone (O-3) and PM2.5 as well as health outcomes were evaluated. PM2.5 concentrations decreased significantly by reducing uses of solid fuels (S4), uses of diesel generating sets (S13) and applying new standards to industry facilities (S11) with maximum reductions of similar to 50 mu g/m(3), similar to 30 mu g/m(3) and similar to 15 mu g/m(3) in north India, separately. Reducing uses of solid fuels caused significant O-3 reduction by maximum > 8 ppb (S4, December), significant effects also occurred when applying new standards to current power plants (S1) (similar to 4 ppb, October.) and in S13 (similar to 3 ppb, December). Combination of all possible strategies would reduce O-3, primary PM components (PPM) and total PM2.5 in December by > 20 ppb, > 40 mu g/m(3) and > 60 mu g/m(3) in north India, while O-3 and secondary inorganic aerosol (SIA) would increase by 5 ppb and 2 mu g/m(3) in October in western and southern India. SIA also increased in part of northern regions in December by similar to 2 mu g/m(3). A total of up to 0.68 million premature mortality and 43% years of life lost (YLL) would be avoided by applying all controlling strategies.

18. Health risk associated with potential source regions of PM2.5 in Indian cities

    Sahu, Shovan Kumar, Zhang, Hongliang, Guo, Hao, Hu, Jianlin,  Ying, Qi, and Kota, Sri Harsha

    Air quality atmosphere and health, Mar 2019

    Abs Doi

    This paper estimates the regional contribution of high PM2.5 concentration and associated mortality using HYSPLIT back trajectory analysis in eight Indian cities during 2015-2016. Health risk and mortality estimation were carried out using the Integrated Exposure Response function (IER) which was verified using our previous time series study in Delhi. Risk estimates from IER were observed to be slightly over-predicted (2.14%) when compared to health risk from time series study in Delhi. Health risk in the eight cities across the four seasons indicated higher chronic obstructive pulmonary disease (COPD), lung cancer (LC), ischemic heart disease (IHD), and stroke in the northern (COPD=1.35, LC=1.50, IHD=1.39, Stroke=2.06) and eastern cities (COPD=1.27, LC=1.38, IHD=1.35, Stroke=1.93) as compared to in southern or western cities. Risk of stroke was observed to be the highest: North=1.37-1.52, South=1.20-1.31, East=1.40-1.52, and West=1.24-1.35 times to that of other diseases. Uttar Pradesh was observed to be a major contributor to premature mortality in Delhi, Lucknow, and Patna accounting for 30, 71, and 42% of total premature death due to high PM2.5 concentration during winter. Similarly, high PM2.5 concentration from West Bengal and Bangladesh was responsible for 52% of total premature mortality in Kolkata while the Indian Ocean was a major contributor to premature mortality in western and southern cities during winter. Reduction of both local and regional pollution is required to yield a significant reduction in pollution of all cities except Delhi and Lucknow where regional and local sources respectively are dominant.

19. Quantifying primary and secondary humic-like substances in urban aerosol based on emission source characterization and a source-oriented air quality model

    Li, Xinghua, Han, Junzan, Hopke, Philip K., Hu, Jingnan, Shu, Qi, Chang, Qing, and Ying, Qi

    Atmospheric chemistry and physics, Feb 2019

    Abs Doi

    Humic-like substances (HULIS) are a mixture of high-molecular-weight, water-soluble organic compounds that are widely distributed in atmospheric aerosol. Their sources are rarely studied quantitatively. Biomass burning is generally accepted as a major primary source of ambient humic-like substances (HULIS) with additional secondary material formed in the atmosphere. However, the present study provides direct evidence that residential coal burning is also a significant source of ambient HULIS, especially in the heating season in northern China based on source measurements, ambient sampling and analysis, and apportionment with source-oriented CMAQ modeling. Emission tests show that residential coal combustion produces 5% to 24% of the emitted organic carbon (OC) as HULIS carbon (HULISc). Estimation of primary emissions of HULIS in Beijing indicated that residential biofuel and coal burning contribute about 70% and 25% of annual primary HULIS, respectively. Vehicle exhaust, industry, and power plant contributions are negligible. The average concentration of ambient HULIS in PM2.5 was 7.5 mu g m(-3) in urban Beijing and HULIS exhibited obvious seasonal variations with the highest concentrations in winter. HULISc accounts for 7.2% of PM2.5 mass, 24.5% of OC, and 59.5% of water-soluble organic carbon. HULIS are found to correlate well with K+, Cl-, sulfate, and secondary organic aerosol, suggesting its sources include biomass burning, coal combustion, and secondary aerosol formation. Source apportionment based on CMAQ modeling shows residential biofuel and coal burning and secondary formation are important sources of ambient HULIS, contributing 47.1 %, 15.1 %, and 38.9 %, respectively.

20. Characterization and source apportionment of marine aerosols over the East China Sea

    Kang, Mingjie, Guo, Hao, Wang, Pengfei, Fu, Pingqing,  Ying, Qi, Liu, Huan, Zhao, Ye, and Zhang, Hongliang

    Science of the total environment, Feb 2019

    Abs Doi

    Awareness of the importance of marine atmosphere for accurately estimating global aerosol budget and climate impacts has arisen recently. However, studies are limited due to the difficulty and inconvenience in sampling as well as the diversity of sources. In this study, the Community Multiscale Air Quality (CMAQ) model was applied to investigate the fine particulate matter (PM2.5) and its chemical components over the East China Sea (ECS) and offshore regions. In spite of slight under-predictions, model predictions agree well with observations over the ECS and along the coast. PM2.5 and its major components in the mainland are higher than in marine area, suggesting Asian continent is a major emitter of marine aerosols. PM2.5 and its components in marine regions show higher abundance during daytime than nighttime, while it is opposite in continental regions. Aerosol phase SO42- is the most abundant component of PM2.5 over the ECS with an average concentration of 5.12 mu g m(-3), followed by NH4+ (1.02 mu g m(-3)) and primary organic aerosol (POA) (0.92 mu g m(-3)). Industry and ship emissions are the top two contributors to primary (PPM) and total PM2.5 over the ECS, while industry and agriculture sectors are major sources for secondary inorganic aerosols (SIA), followed by ship emissions. For terrestrial regions, industry and agriculture are predominant sources of PM2.5 and SIA, while industry and residential activities are the top two contributors to PPM. This study improves the understanding of transport and accumulation of air pollutants over the ECS and adjacent regions, and provides useful information for designing efficient control strategies. (c) 2018 Published by Elsevier B.V.

21. Attribution of Tropospheric Ozone to NOx and VOC Emissions: Considering Ozone Formation in the Transition Regime

    Wang, Peng, Chen, Yuan, Hu, Jianlin, Zhang, Hongliang, and Ying, Qi

    Environmental science & technology, Feb 2019

    Abs Doi

    An improved three-regime (3R) O-3 attribution technique for O-3 source apportionment in regional chemical transport models is developed to divide the entire range of VOC-NOx-O-3 formation sensitivity to VOC-limited, transition, and NOx-limited regimes based on the value of a regime indicator R. The threshold R values to mark the start(R-ts) and end (R-te) of the transition regime are defined at the point where O-3-NOx sensitivity turns from negative to positive and where O-3-NOx sensitivity is ten times higher than O-3-VOC sensitivity, respectively. R-ts and R-te are determined using NO and VOC sensitivity simulations in a box model with a modified SAPRC-11 mechanism. For the widely used indicator ration R = (P-H2O2 +P-ROOH)/PHNO3, which is based on the production rates of H2O2, HNO3 and organic hydroperoxides (ROOH), the recommended Rts and Rte values are 0.047 and 5.142, respectively. Parameterized attribution functions, depending only on the values of R, are developed to apportion modeled in situ O-3 formation in the transition regime to NO and VOCs. The new 3R and the traditional two-regime (2R) schemes are incorporated into the Community Multiscale Air Quality (CMAQ) model to quantify NOx and VOC contributions to regional O-3 concentrations in China in August 2013. The 3R approach predicts approximately 5-10 ppb and up to 15 ppb higher NOx contributions to 8 h O-3 in in the North China Plain, the Yangtze River Delta and the Pearl River Delta than the 2R approach. The big differences in O-3 attribution between 2R and 3R can have significant policy implications for air pollution emission controls.

22. Modeling Atmospheric Age Distribution of Elemental Carbon Using a Regional Age-Resolved Particle Representation Framework

    Zhang, Hongliang, Guo, Hao, Hu, Jianlin,  Ying, Qi, and Kleemani, Michael J.

    Environmental science & technology, Jan 2019

    Abs Doi

    The aging process of soot particles has significant implications when estimating their impacts on air quality and climate. In this study, the source-oriented University of California at Davis/California Institute of Technology model with externally mixed aerosol representation is expanded to track the age distribution of elemental carbon (EC) in Southeast Texas. EC with the age of 0-3 h (i.e., emitted less than 3 h ago) accounted for similar to 70-90% of the total in urban Houston and 20-40% in rural areas of southeast Texas in August 2000. Significant diurnal variations in the mean age of EC are predicted, with higher contributions from fresh particles during the morning and early evening due to increased traffic emission and reduced atmospheric mixing. Spatially, the mean age of EC decreases with proximity to major sources. Ground-level EC with the age >6 h is less than 20% of the first age group over land, and background EC accounts for the majority over the Gulf of Mexico. Differences in EC spatial distribution indicate that age distribution could have regional impact on aerosol optical and hygroscopic properties, and thus potentially affect cloud formation and radiation balance. Appropriately accounting for the differential properties due to age distribution is needed to better evaluate aerosol direct and indirect effects.

2018:9

1. The impact of power generation emissions on ambient PM2.5 pollution and human health in China and India

   Gao, Meng, Beig, Gufran, Song, Shaojie, Zhang, Hongliang, Hu, Jianlin,  Ying, Qi, Liang, Fengchao, Liu, Yang, Wang, Haikun, Lu, Xiao, Zhu, Tong, Carmichael, Gregory R., Nielsen, Chris P., and McElroy, Michael B.

   Environment international, Dec 2018

   Abs Doi

   Emissions from power plants in China and India contain a myriad of fine particulate matter (PM25, PM <= 2.5 mu m in diameter) precursors, posing significant health risks among large, densely settled populations. Studies isolating the contributions of various source classes and geographic regions are limited in China and India, but such information could be helpful for policy makers attempting to identify efficient mitigation strategies. We quantified the impact of power generation emissions on annual mean PM2.5 concentrations using the state-of-the-art atmospheric chemistry model WRF-Chem (Weather Research Forecasting model coupled with Chemistry) in China and India. Evaluations using nationwide surface measurements show the model performs reasonably well. We calculated province-specific annual changes in mortality and life expectancy due to power generation emissions generated PM2.5 using the Integrated Exposure Response (IER) model, recently updated IER parameters from Global Burden of Disease (GBD) 2015, population data, and the World Health Organization (WHO) life tables for China and India. We estimate that 15 million (95% Confidence Interval (CI): 10 to 21 million) years of life lost can be avoided in China each year and 11 million (95% CI: 7 to 15 million) in India by eliminating power generation emissions. Priorities in upgrading existing power generating technologies should be given to Shandong, Henan, and Sichuan provinces in China, and Uttar Pradesh state in India due to their dominant contributions to the current health risks.

2. Impacts of shipping emissions on PM2.5 pollution in China

   Lv, Zhaofeng, Liu, Huan,  Ying, Qi, Fu, Mingliang, Meng, Zhihang, Wang, Yue, Wei, Wei, Gong, Huiming, and He, Kebin

   Atmospheric chemistry and physics, Nov 2018

   Abs Doi

   With the fast development of seaborne trade and relatively more efforts on reducing emissions from other sources in China, shipping emissions contribute more and more significantly to air pollution. In this study, based on a shipping emission inventory with high spatial and temporal resolution within 200 nautical miles (Nm) to the Chinese coastline, the Community Multiscale Air Quality (CMAQ) model was applied to quantify the impacts of the shipping sector on the annual and seasonal concentrations of PM2.5 for the base year 2015 in China. Emissions within 12 Nm accounted for 51.2%-56.5% of the total shipping emissions, and the distinct seasonal variations in spatial distribution were observed. The modeling results showed that shipping emissions increased the annual averaged PM2.5 concentrations in eastern China up to 5.2 mu g m(-3), and the impacts in YRD (Yangtze River Delta) and PRD (Pearl River Delta) were much greater than those in BTH (Beijing-Tianjin-Hebei). Shipping emissions influenced the air quality in not only coastal areas but also the inland areas hundreds of kilometers (up to 960 km) away from the sea. The impacts on the PM2.5 showed obvious seasonal variations, and patterns in the north and south of the Yangtze River were also quite different. In addition, since the onshore wind can carry ship pollutants to inland areas, the daily contributions of shipping emissions in onshore flow days were about 1.8-2.7 times higher than those in the rest of the days. A source-oriented CMAQ was used to estimate the contributions of shipping emissions from maritime areas within 0-12, 12-50, 50-100 and 100-200 Nm to PM2.5 concentrations. The results indicated that shipping emissions within 12 Nm were the dominant contributor, with contributions 30 %-90% of the total impacts induced by emissions within 200 Nm, while a relatively high contribution (40%-60%) of shipping emissions within 20-100 Nm was observed in the north of the YRD region and south of Lianyungang, due to the major water traffic lanes far from land. The results presented in this work implied that shipping emissions had significant influence on air quality in China, and to reduce its pollution, the current Domestic Emission Control Area (DECA) should be expanded to at least 100 Nm from the coastline.

3. Source contributions and potential reductions to health effects of particulate matter in India

   Guo, Hao, Kota, Sri Harsha, Chen, Kaiyu, Sahu, Shovan Kumar, Hu, Jianlin,  Ying, Qi, Wang, Yuan, and Zhang, Hongliang

   Atmospheric chemistry and physics, Oct 2018

   Abs Doi

   Health effects of exposure to fine particulate matter (PM2.5) in India were estimated in this study based on a source-oriented version of the Community Multiscale Air Quality (CMAQ) model. Contributions of different sources to premature mortality and years of life lost (YLL) were quantified in 2015. Premature mortality due to cerebrovascular disease (CEVD) was the highest in India (0.44 million), followed by ischaemic heart disease (IHD, 0.40 million), chronic obstructive pulmonary disease (COPD, 0.18 million), and lung cancer (LC, 0.01 million), with a total of 1.04 million deaths. The states with highest premature mortality were Uttar Pradesh (0.23 million), Bihar (0.12 million), and West Bengal (0.10 million). The highest total YLL was 2 years in Delhi, and the Indo-Gangetic plains and eastern India had higher YLL (similar to 1 years) than other regions. The residential sector was the largest contributor to PM2.5 concentrations (similar to 40 mu gm(3)), total premature mortality (0.58 million), and YLL (similar to 0 : 2 years). Other important sources included industry (similar to 20 mu gm(3)), agriculture (similar to 10 mu gm 3), and energy (similar to 5 mu gm(3)) with their national averaged contributions of 0.21, 0.12, and 0.07 million to premature mortality, and 0.12, 0.1, and 0.05 years to YLL. Reducing PM2.5 concentrations would lead to a significant reduction of premature mortality and YLL. For example, premature mortality in Uttar Pradesh including Delhi) due to PM2.5 exposures would be reduced by 79% and YLL would be reduced by 83% when reducing PM2.5 concentrations to 10 mu gm(-3).

4. Sources of particulate matter in China: Insights from source apportionment studies published in 1987-2017

   Zhu, Yanhong, Huang, Lin, Li, Jingyi,  Ying, Qi, Zhang, Hongliang, Liu, Xingang, Liao, Hong, Li, Nan, Liu, Zhenxin, Mao, Yuhao, Fang, Hao, and Hu, Jianlin

   Environment international, Jun 2018

   Abs Doi

   Particulate matter (PM) in the atmosphere has adverse effects on human health, ecosystems, and visibility. It also plays an important role in meteorology and climate change. A good understanding of its sources is essential for effective emission controls to reduce PM and to protect public health. In this study, a total of 239 PM source apportionment studies in China published during 1987-2017 were reviewed. The documents studied include peer-reviewed papers in international and Chinese journals, as well as degree dissertations. The methods applied in these studies were summarized and the main sources in various regions of China were identified. The trends of source contributions at two major cities with abundant studies over long-time periods were analyzed. The most frequently used methods for PM source apportionment in China are receptor models, including chemical mass balance (CMB), positive matrix factorization (PMF), and principle component analysis (PCA). Dust, fossil fuel combustion, transportation, biomass burning, industrial emission, secondary inorganic aerosol (SIA) and secondary organic aerosol (SOA) are the main source categories of fine PM identified in China. Even though the sources of PM vary among seven different geographical areas of China, SIA, industrial, and dust emissions are generally found to be the top three source categories in 2007-2016. A number of studies investigated the sources of SIA and SOA in China using air quality models and indicated that fossil fuel combustion and industrial emissions were the most important sources of SIA (total contributing 63.5%-88.1% of SO42-, and 47.3%-70% NO3-), and agriculture emissions were the dominant source of NH4+ (contributing 53.9%-90%). Biogenic emissions were the most important source of SOA in China in summer, while residential and industrial emissions were important in winter. Long-term changes of PM sources at two megacities of Beijing and Nanjing indicated that the contributions of fossil fuel and industrial sources have been declining after stricter emission controls in recent years. In general, dust and industrial contributions decreased and transportation contributions increased after 2000. PM2.5 emissions are predicted to decline in most regions during 2005-2030, even though the energy consumptions except biomass burning are predicted to continue to increase. Industrial, residential, and biomass burning sources will become more important in the future in the businuess-as-usual senarios. This review provides valuable information about main sources of PM and their trends in China. A few recommendations are suggested to further improve our understanding the sources and to develop effective PM control strategies in various regions of China.

5. Improve regional distribution and source apportionment of PM2.5 trace elements in China using inventory-observation constrained emission factors

   Ying, Qi, Feng, Miao, Song, Danlin, Wu, Li, Hu, Jianlin, Zhang, Hongliang, Kleeman, Michael J., and Li, Xinghua

   Science of the total environment, May 2018

   Abs Doi

   Contributions to 15 trace elements in airborne particulate matter with aerodynamic diameters <2.5 mu m (PM2.5) in China from five major source sectors (industrial sources, residential sources, transportation, power generation and windblown dust) were determined using a source-oriented Community Multiscale Air Quality (CMAQ) model. Using emission factors in the composite speciation profiles from US EPA’s SPECIATE database for the five sources leads to relatively poor model performance at an urban site in Beijing. Improved predictions of the trace elements are obtained by using adjusted emission factors derived from a robust multilinear regression of the CMAQ predicted primary source contributions and observation at the urban site. Good correlations between predictions and observations are obtained for most elements studied with R > 0.5, except for crustal elements Al, Si and Ca, particularly in spring. Predicted annual and seasonal average concentrations of Mn, Fe, Zn and Pb in Nanjing and Chengdu are also consistently improved using the adjusted emission factors. Annual average concentration of Fe is as high as 2.0 mu g m(-3) with large contributions from power generation and transportation. Annual average concentration of Pb reaches 300-500 ng m(-3) in vast areas, mainly from residential activities, transportation and power generation. The impact of high concentrations of Fe on secondary sulfate formation and Pb on human health should be evaluated carefully in future studies. (C) 2017 Elsevier B.V. All rights reserved.

6. Year-long simulation of gaseous and particulate air pollutants in India

   Kota, Harsha, Guo, Hao, Myllyvirta, Lauri, Hu, Jianlin, Sahu, Shovan Kumar, Garaga, Rajyalakshmi,  Ying, Qi, Gao, Aifang, Dahiya, Sunil, Wang, Yuan, and Zhang, Hongliang

   Atmospheric environment, May 2018

   Abs Doi

   Severe pollution events occur frequently in India but few studies have investigated the characteristics, sources, and control strategies for the whole country. A year-long simulation was carried out in India to provide detailed information of spatial and temporal distribution of gas species and particulate matter (PM). The concentrations of O-3, NO2, SO2, CO, as well as PM2.5 and its components in 2015 were predicted using Weather Research Forecasting (WRF) and the Community Multiscale Air Quality (CMAQ) models. Model performance was validated against available observations from ground based national ambient air quality monitoring stations in major cities. Model performance of O-3 does not always meet the criteria suggested by the US Environmental Protection Agency (EPA) but that of PM2.5 meets suggested criteria by previous studies. The performance of model was better on days with high O-3 and PM2.5 levels. Concentrations of PM2.5, NO2, CO and SO2 were highest in the Indo-Gangetic region, including northern and eastern India. PM2.5 concentrations were higher during winter and lower during monsoon season. Winter nitrate concentrations were 160-230% higher than yearly average. In contrast, the fraction of sulfate in total PM2.5 was maximum in monsoon and least in winter, due to decrease in temperature and solar radiation intensity in winter. Except in southern India, where sulfate was the major component of PM2.5, primary organic aerosol (POA) fraction in PM2.5 was highest in all regions of the country. Fractions of secondary components were higher on bad days than on good days in these cities, indicating the importance of control of precursors for secondary pollutants in India. Capsule abstract: Predicted gaseous and particulate air pollutants in India using WRF/CMAQ in 2015 were validated and the variations were analyzed for future source and health analysis.

7. Wet deposition of sulfur and nitrogen in Jiuzhaigou National Nature Reserve, Sichuan, China during 2015-2016: Possible effects from regional emission reduction and local tourist activities

   Qiao, Xue, Du, Jie, Kota, Sri Harsha,  Ying, Qi, Xiao, Weiyang, and Tang, Ya

   Environmental pollution, Feb 2018

   Abs Doi

   In order to understand the impacts of regional emission changes and local tourism on sulfur and nitrogen wet deposition in Jiuzhaigou National Nature Reserve of southwestern China, wet deposition was monitored at a background site (Rize) and a tourist-affected site (PE: park entrance) in the reserve during 2015-2016. The observation data were compared between Rize and PE and between 2010-2011 and 2015-2016 monitoring campaigns. Also, the observation data were used in the Positive Matrix Factorization (PMF) model to identify the major sources of sulfur and nitrogen wet deposition. The results show that although local tourism emissions had considerable contributions to NH4+, NO2-, NO3-, and SO42- concentrations in wet deposition (p < 0.05), most of the annual Volume Weighted Mean (VWM) concentrations of these four ions were likely from emissions outside Jiuzhaigou. Annual wet deposition fluxes of the four ions were also affected more by precipitation and regional emissions than by local emissions. Although annual precipitation was higher at Rize (818 mm) during 2015-2016 than at another background site near Long Lake (LL: 752 mm) during 2010-2011, the annual concentrations and fluxes of SO42- and NO3- wet deposition decreased by 77% and 74% for SO42- and by 12% and 19% for NO3-, respectively, most likely due to regional emission reductions. Similar large reductions in SO42- and NO3- concentrations have been also found in some other sites in southwestern China. In contrast, the annual concentration and flux of NH4+ wet deposition at Rize during 2015-2016 were 1.4 and 1.2 times of that measured at LL during 2010-2011, respectively. The results of source apportionment analysis and tour bus emission estimates suggest that elevated NH4+ wet deposition was possibly related to NH3 emissions from local tour buses, but additional studies on NH3 emissions from tour buses in the reserve are needed to confirm this. (C) 2017 Elsevier Ltd. All rights reserved.

8. Source apportionment of PM2.5 for 25 Chinese provincial capitals and municipalities using a source-oriented Community Multiscale Air Quality model

   Qiao, Xue,  Ying, Qi, Li, Xinghua, Zhang, Hongliang, Hu, Jianlin, Tang, Ya, and Chen, Xue

   Science of the total environment, Jan 2018

   Abs Doi

   Source contributions to fine airborne particulate matter with aerodynamic diameters < 2.5 mu m(PM2.5) during 2013 were determined for 25 Chinese provincial capitals and municipalities using a source-oriented version of the Community Multiscale Air Quality (CMAQ) model. Based on the hierarchical clustering analysis of the observed PM2.5 concentrations, the 25 cities were categorized into nine groups. Generally, annual PM2.5 concentrations were highest in the cities in the north (81-154 mu g m(-3)) and lowest in the cities close to seas in the south and east (27-57 mu g m(-3)). Seasonal PM2.5 observations in the cities were generally higher in winter than in the other seasons. Industrial or residential sources were predicted to be the largest contributor to PM2.5 for all the city groups, with annually fractional contributions of 25.0%-38.6% and 9.6%-27%, respectively. The annual contributions from power plants, agriculture NH3, windblown dust, and secondary organic aerosol (SOA) for the city groups were 8.7%-12.7%, 9.5%-12%, 6.1%-12.5%, and 5.4%-15.5%, respectively. Meanwhile, the annual contributions from transportation, sea salt, and open burning were relatively low (< 8%, < 2%, and < 6%, respectively). Secondary PM2.5 accounted for 47%-63% of total annual PM2.5 concentrations in the cities and contributed to as much as 70% of daily PM2.5 concentrations on PM2.5 pollution days ( daily concentrations > 75 mu g m(-3)). Industrial or residential sources were generally the largest contributor on PM2.5 pollution days for all the city groups in each season, except that open burning, SOA, and windblown dust could be more important on some days, particularly in spring. The results of this study would be helpful to develop measures to reduce annual PM2.5 concentrations and the number of PM2.5 pollution days for different regions of China. (C) 2017 Elsevier B.V. All rights reserved.

9. Spatial and temporal variations in criteria air pollutants in three typical terrain regions in Shaanxi, China, during 2015

   Xu, Yong,  Ying, Qi, Hu, Jianlin, Gao, Yuan, Yang, Yang, Wang, Dexiang, and Zhang, Hongliang

   Air quality atmosphere and health, Jan 2018

   Abs Doi

   Numerous studies have investigated air pollution in severely polluted plains, but the characteristics of pollutants are not well understood in other terrain regions. In this study, air pollution characteristics were analyzed in three typical terrain regions (plateau, plain, and mountain regions) in Shaanxi, based on hourly ambient monitoring of particulate matter with diameter less than 2.5 mu m (PM2.5) and less than 10 mu m (PM10), CO, SO2, NO2, and O-3 in 2015. PM2.5 and PM10 were the dominant pollutants in three regions, and their annual concentrations exceeded the Grade II standards by 9.4-68.6 and 6.0-73.9%, respectively. PM2.5, PM10, CO, SO2, and NO2 concentrations had similar seasonal trends with highest values in winter and lowest values in summer, whereas O-3 concentrations exhibited the opposite trend. Guanzhong Plain had higher PM2.5, PM10, NO2, and SO2 concentrations but lower CO, 1-h peak O-3, and 8-h peak O-3 (8 h-O-3) compared to other regions. PM2.5, PM10, and 8 h-O-3 were the three main dominant pollutants. The nonattainment rate was highest in winter and lowest in summer or autumn. Pollution also exhibited synergy, especially in the plateau region and Guanzhong Plain. PM2.5 was significantly correlated with PM10. NO2 and SO2 were positively correlated with PM2.5 and PM10, while 8 h-O-3 generally had significant negative correlations with other pollutants, especially in the winter. These results provide a comprehensive understanding of pollution status in the three typical terrain regions in Shaanxi and are helpful for improving air quality.

2017:15

1. AERMOD for near-road pollutant dispersion: Evaluation of model performance with different emission source representations and low wind options

   Askariyeh, Mohammad Hashem, Kota, Sri Harsha, Vallamsundar, Suriya, Zietsman, Josias, and Ying, Qi

   Transportation research part d-transport and environment, Dec 2017

   Abs Doi

   The performance of the regulatory dispersion model AERMOD in simulating vehicle-emitted pollutant concentrations near-roadway using area or volume source representation of emissions and with different low wind options was assessed using the SF6 tracer data from the General Motors (GM) Sulfur Dispersion Experiment. At downwind receptor locations, AERMOD, using either area or volume source emissions, can reasonably predict the tracer concentrations near the surface (0.5 m) but the model performance decreases at higher elevations (3.5m and 9.5m above the surface). For upwind receptors, using an area source representation leads to significant under predictions due to AERMOD’s lack of treatment of lateral plume meander, but using volume source representation leads to over -predictions of upwind concentrations regardless of the low wind options for plume meander. Among the three low wind options currently available in AERMOD, best model performance is obtained with low wind option 3, which treats plume meander with a higher minimal standard deviation of the horizontal crosswind component (sigma(v,min) = 0.3 m s(-1)), eliminates upwind component of dispersion and uses an effective lateral dispersion parameter (sigma(y)) to replicate centerline concentration. The optional adjustment of the surface friction velocity in the meteorological preprocessor AERMET does not lead to obvious improvements in predicted near-road concentrations for this application.

2. Source apportionment of PM2.5 in North India using source-oriented air quality models

   Guo, Hao, Kota, Sri Harsha, Sahu, Shovan Kumar, Hu, Jianlin,  Ying, Qi, Gao, Aifang, and Zhang, Hongliang

   Environmental pollution, Dec 2017

   Abs Doi

   In recent years, severe pollution events were observed frequently in India especially at its capital, New Delhi. However, limited studies have been conducted to understand the sources to high pollutant concentrations for designing effective control strategies. In this work, source-oriented versions of the Community Multi-scale Air Quality (CMAQ) model with Emissions Database for Global Atmospheric Research (EDGAR) were applied to quantify the contributions of eight source types (energy, industry, residential, on-road, off-road, agriculture, open burning and dust) to fine particulate matter (PM2.5) and its components including primary PM (PPM) and secondary inorganic aerosol (SIA) i.e. sulfate, nitrate and ammonium ions, in Delhi and three surrounding cities, Chandigarh, Lucknow and Jaipur in 2015. PPM mass is dominated by industry and residential activities (>60%). Energy (similar to 39%) and industry (similar to 45%) sectors contribute significantly to PPM at south of Delhi, which reach a maximum of 200 mu g/m(3) during winter. Unlike PPM, SIA concentrations from different sources are more heterogeneous. High SIA concentrations (similar to 25 mu g/m(3)) at south Delhi and central Uttar Pradesh were mainly attributed to energy, industry and residential sectors. Agriculture is more important for SIA than PPM and contributions of on road and open burning to SIA are also higher than to PPM. Residential sector contributes highest to total PM2.5 (similar to 80 mu g/m(3)), followed by industry (similar to 70 mu g/m(3)) in North India. Energy and agriculture contribute similar to 25 mu g/m(3) and similar to 16 mu g/m(3) to total PM2.5, while SOA contributes <5 mu g/m(3). In Delhi, industry and residential activities contribute to 80% of total PM2.5. (C) 2017 Elsevier Ltd. All rights reserved.

3. Source apportionment of fine particulate matter in China in 2013 using a source-oriented chemical transport model

   Shi, Zhihao, Li, Jingyi, Huang, Lin, Wang, Peng, Wu, Li,  Ying, Qi, Zhang, Hongliang, Lu, Li, Liu, Xuejun, Liao, Hong, and Hu, Jianlin

   Science of the total environment, Dec 2017

   Abs Doi

   China has been suffering high levels of fine particulate matter (PM2.5). Designing effective PM2.5 control strategies requires information about the contributions of different sources. In this study, a source-oriented Community Multiscale Air Quality (CMAQ) model was applied to quantitatively estimate the contributions of different source sectors to PM2.5 in China. Emissions of primary PM2.5 and gas pollutants of SO2, NOx, and NH3, which are precursors of particulate sulfate, nitrate, and ammonium (SNA, major PM2.5 components in China), from eight source categories (power plants, residential sources, industries, transportation, open burning, sea salt, windblown dust and agriculture) were separately tracked to determine their contributions to PM2.5 in 2013. Industrial sector is the largest source of SNA in Beijing, Xi’an and Chongqing, followed by agriculture and power plants. Residential emissions are also important sources of SNA, especially in winter when severe pollution events often occur. Nationally, the contributions of different source sectors to annual total PM2.5 from high to low are industries, residential sources, agriculture, power plants, transportation, windblown dust, open burning and sea salt. Provincially, residential sources and industries are the major anthropogenic sources of primary PM2.5, while industries, agriculture, power plants and transportation are important for SNA in most provinces. For total PM2.5, residential and industrial emissions are the top two sources, with a combined contribution of 40-50% in most provinces. The contributions of power plants and agriculture to total PM2.5 are about 10%, respectively. Secondary organic aerosol accounts for about 10% of annual PM2.5 in most provinces, with higher contributions in southernprovinces such as Yunnan (26%), Hainan (25%) and Taiwan (21%). Windblown dust is an important source in western provinces such as Xizang (55% of total PM2.5), Qinghai (74%), Xinjiang (59%). The large variation in sources of PM2.5 across China suggests that PM2.5 mitigation programs should be designed separately for different regions/provinces. (C) 2017 Elsevier B.V. All rights reserved.

4. Ensemble prediction of air quality using the WRF/CMAQ model system for health effect studies in China

   Hu, Jianlin, Li, Xun, Huang, Lin,  Ying, Qi, Zhang, Qiang, Zhao, Bin, Wang, Shuxiao, and Zhang, Hongliang

   Atmospheric chemistry and physics, Nov 2017

   Abs Doi

   Accurate exposure estimates are required for health effect analyses of severe air pollution in China. Chemical transport models (CTMs) are widely used to provide spatial distribution, chemical composition, particle size fractions, and source origins of air pollutants. The accuracy of air quality predictions in China is greatly affected by the uncertainties of emission inventories. The Community Multiscale Air Quality (CMAQ) model with meteorological inputs from the Weather Research and Forecasting (WRF) model were used in this study to simulate air pollutants in China in 2013. Four simulations were conducted with four different anthropogenic emission inventories, including the Multi-resolution Emission Inventory for China (MEIC), the Emission Inventory for China by School of Environment at Tsinghua University (SOE), the Emissions Database for Global Atmospheric Research (EDGAR), and the Regional Emission inventory in Asia version 2 (REAS2). Model performance of each simulation was evaluated against available observation data from 422 sites in 60 cities across China. Model predictions of O-3 and PM2.5 generally meet the model performance criteria, but performance differences exist in different regions, for different pollutants, and among inventories. Ensemble predictions were calculated by linearly combining the results from different inventories to minimize the sum of the squared errors between the ensemble results and the observations in all cities. The ensemble concentrations show improved agreement with observations in most cities. The mean fractional bias (MFB) and mean fractional errors (MFEs) of the ensemble annual PM2.5 in the 60 cities are -0.11 and 0.24, respectively, which are better than the MFB (-0.25 to -0.16) and MFE (0.26-0.31) of individual simulations. The ensemble annual daily maximum 1 h O-3 (O-3-1h) concentrations are also improved, with mean normalized bias (MNB) of 0.03 and mean normalized errors (MNE) of 0.14, compared to MNB of 0.06-0.19 and MNE of 0.16-0.22 of the individual predictions. The ensemble predictions agree better with observations with daily, monthly, and annual averaging times in all regions of China for both PM2.5 and O-3-1h. The study demonstrates that ensemble predictions from combining predictions from individual emission inventories can improve the accuracy of predicted temporal and spatial distributions of air pollutants. This study is the first ensemble model study in China using multiple emission inventories, and the results are publicly available for future health effect studies.

5. Modelling secondary organic aerosols in China

   Chen, Qi, Fu, Tzung-May, Hu, Jianlin,  Ying, Qi, and Zhang, Lin

   National science review, Nov 2017

   Doi
6. Current and future emissions of primary pollutants from coal-fired power plants in Shaanxi, China

   Xu, Yong, Hu, Jianlin,  Ying, Qi, Hao, Hongke, Wang, Dexiang, and Zhang, Hongliang

   Science of the total environment, Oct 2017

   Abs Doi

   A high-resolution inventory of primary atmospheric pollutants from coal-fired power plants in Shaanxi in 2012 was built based on a detailed database compiled at unit level involving unit capacity, boiler size and type, commission time, corresponding control technologies, and average coal quality of 72 power plants. The pollutants included SO2, NOx, fine particulate matter (PM2.5), inhalable particulate matter (PM10), organic carbon (OC), elemental carbon (EC), carbon monoxide (CO) and non-methane volatile organic compounds (NMVOC). Emission factors for SO2, NOx, PM2.5 and PM10 were adopted from standardized official promulgation, supplemented by those from local studies. The estimated annual emissions of SO2, NOx, PM2.5, PM10, EC, OC, CO and NMVOC were 152.4, 314.8, 16.6, 26.4, 0.07, 0.27, 64.9 and 2.5 kt, respectively. Small units (<100 MW), which accounted for similar to 60% of total unit numbers, had less coal consumption but higher emission rates compared to medium (>= 100 MW and <300 MW) and large units (>= 300 MW). Main factors affecting SO2, NOx, PM2.5 and PM10 emissions were decontamination efficiency, sulfur content and ash content of coal. Weinan and Xianyang were the two cities with the highest emissions, and Guanzhong Plain had the largest emission density. Despite the projected growth of coal consumption, emissions would decrease in 2030 due to improvement in emission control technologies and combustion efficiencies. SO2 and NOx emissions would experience significant reduction by similar to 81% and similar to 84%, respectively. PM2.5, PM10, EC and OC would be decreased by similar to 43% and CO and NMVOC would be reduced by similar to 16%. (C) 2017 Elsevier B.V. All rights reserved.

7. Premature Mortality Attributable to Particulate Matter in China: Source Contributions and Responses to Reductions

   Hu, Jianlin, Huang, Lin, Chen, Mindong, Liao, Hong, Zhang, Hongliang, Wang, Shuxiao, Zhang, Qiang, and Ying, Qi

   Environmental science & technology, Sep 2017

   Abs Doi

   Excess mortality (Delta Mort) in China due to exposure to ambient fine particulate matter with aerodynamic diameter <= 2.5 mu m (PM2.5) was determined using an ensemble prediction of annual average PM2.5 in 2013 by the community multiscale air quality (CMAQ) model with four emission inventories and observation data fusing. Estimated Delta Mort values due to adult ischemic heart disease, cerebrovascular disease, chronic obstructive pulmonary disease, and lung cancer are 0.30, 0.73, 0.14, and 0.13 million in 2013, respectively, leading to a total Delta Mort of 1.3 million. Source-oriented CMAQ modeling determined that industrial and residential sources were the two leading sources of Delta Mort, contributing to 0.40 (30.5%) and 0.28 (21.7%) million deaths, respectively. Additionally, secondary ammonium ion from agriculture, secondary organic aerosol, and aerosols from power generation were responsible for 0.16, 0.14, and 0.13 million deaths, respectively. A 30% ?Mort reduction in China requires an average of 50% reduction of PM2.5 throughout the country and a reduction by 62%, 50%, and 38% for the Beijing-Tianjin-Hebei, Jiangsu-Zhejiang-Shanghai, and Pearl River Delta regions, respectively. Reducing PM2.5 to the CAAQS grade II standard of 35 mu g m(-3) would only lead to a small reduction in mortality, and a more stringent standard of <15 mu g m(-3) would be needed for more remarkable reduction of Delta Mort.

8. Investigation of relationships between meteorological conditions and high PM10 pollution in a megacity in the western Yangtze River Delta, China

   Zu, Yaqun, Huang, Lin, Hu, Jianlin, Zhao, Zhan, Liu, Hang, Zhang, Hongliang,  Ying, Qi, and Chen, Mindong

   Air quality atmosphere and health, Aug 2017

   Abs Doi

   Nanjing, a megacity in the western Yangtze River Delta of China, has been suffering high PM10 pollution during recent decades. The meteorological conditions that affect the formation of high PM10 pollution in Nanjing remain unknown. In this study, 12-year daily PM10 concentrations and ground-level meteorological conditions from 2001 to 2012 were analyzed. The relationships between PM10 concentrations and meteorological parameters including wind direction, wind speed, temperature, relative humidity, and precipitation were investigated with multiple methods, including occurrence frequency, back trajectory, multiple linear regression (MLR), and artificial neural network (ANN) analysis. The results show that PM10 pollution in Nanjing was severe during 2001-2012. The 12-year mean is 109 mu g/m(3), which is 56% higher than the grade II annual PM10 standard of China. Declining trends are found for both the annual averages and the episode averages during the most polluted events, with a rate of 3.5 and 4.0 mu g/m(3) per year, respectively. High PM10 pollution events are more likely to occur on no-precipitation days when wind is from east with speed of 1.0 to 3.0 m/s, temperature is 10 to 20 degrees C, relative humidity is below 80%, and sea-level pressure is 1015-1025 hPa. The 72- and 24-h back trajectory analysis shows that over half of the air masses on the high PM10 pollution days are from east-south with an average transport distance of around 400 km in 72 h and 200 km in 24 h, respectively. Including the previous day concentration in the MLR models substantially improves model performance for predicting daily PM10, with an increase of the Pearson correlation coefficient from 0.25 to 0.61. The ANN model generally performs better than the MLR models and can be considered as a better method for future PM10 forecasting. However, both models have difficulties accurately predicting very severe pollution events, and more factors should be considered in future studies.

9. Uncertain Henry’s law constants compromise equilibrium partitioning calculations of atmospheric oxidation products

   Wang, Chen, Yuan, Tiange, Wood, Stephen A., Goss, Kai-Uwe, Li, Jingyi,  Ying, Qi, and Wania, Frank

   Atmospheric chemistry and physics, Jun 2017

   Abs Doi

   Gas-particle partitioning governs the distribution, removal, and transport of organic compounds in the atmosphere and the formation of secondary organic aerosol (SOA). The large variety of atmospheric species and their wide range of properties make predicting this partitioning equilibrium challenging. Here we expand on earlier work and predict gas-organic and gas-aqueous phase partitioning coefficients for 3414 atmospherically relevant molecules using COSMOtherm, SPARC Performs Automated Reasoning in Chemistry (SPARC), and poly-parameter linear free-energy relationships. The Master Chemical Mechanism generated the structures by oxidizing primary emitted volatile organic compounds. Predictions for gas-organic phase partitioning coefficients (K-WIOM/G) by different methods are on average within 1 order of magnitude of each other, irrespective of the numbers of functional groups, except for predictions by COSMOtherm and SPARC for compounds with more than three functional groups, which have a slightly higher discrepancy. Discrepancies between predictions of gas-aqueous partitioning (K-W/G) are much larger and increase with the number of functional groups in the molecule. In particular, COSMOtherm often predicts much lower K-W/G for highly functionalized compounds than the other methods. While the quantum-chemistry-based COSMOtherm accounts for the influence of intra-molecular interactions on conformation, highly functionalized molecules likely fall outside of the applicability domain of the other techniques, which at least in part rely on empirical data for calibration. Further analysis suggests that atmospheric phase distribution calculations are sensitive to the partitioning coefficient estimation method, in particular to the estimated value of K-W/G. The large uncertainty in K-W/G predictions for highly functionalized organic compounds needs to be resolved to improve the quantitative treatment of SOA formation.

10. Air pollution and cardiovascular events at labor and delivery: a case-crossover analysis

    Ha, Sandie, Mannisto, Tuija, Liu, Danping, Sherman, Seth,  Ying, Qi, and Mendola, Pauline

    Annals of epidemiology, Jun 2017

    Abs Doi

    Purpose: In this case-crossover study, we investigated the odds of having a labor/delivery with cardiovascular event (i.e., ischemic heart disease, stroke, heart failure, cardiac arrest/failure, and other or unspecified cardiovascular events) associated with acute exposure to common air pollutants. Methods: We selected 680 women with singleton pregnancy and cardiovascular events at labor/delivery from 12 U.S. clinical sites (2002-2008). Exposures to six criteria air pollutants, six particulate constituents, and 26 air toxics were obtained using modified Community Multiscale Air Quality models. Conditional logistic regression models calculated the odds ratio (OR) and 95% confidence intervals (CI) comparing exposures during the day of delivery, the week before delivery, and each of the days of the week before delivery to two control periods before and after. Results: An interquartile range increase in particulate matter (PM) <= 2.5 microns and nitric oxide exposures during the week before delivery was associated with an 11% (OR 1.11, 95% CI: 1.01-1.23) and 21% (OR 1.21, 95% CI: 1.04-1.42) increased cardiovascular events odds, respectively. These pollutants, sulfur dioxide, carbon monoxide, PM <= 10 microns, and some PM constituents showed associations with event odds for days 0, 1, 5, and 6 before delivery. Inverse associations were observed for O-3 and some PM constituents as well as air toxics. Conclusions: Cardiovascular events at labor/delivery merit more attention in relation to air pollution. Published by Elsevier Inc.

11. Long-term particulate matter modeling for health effect studies in California - Part 2: Concentrations and sources of ultrafine organic aerosols

    Hu, Jianlin, Jathar, Shantanu, Zhang, Hongliang,  Ying, Qi, Chen, Shu-Hua, Cappa, Christopher D., and Kleeman, Michael J.

    Atmospheric chemistry and physics, Apr 2017

    Abs Doi

    Organic aerosol (OA) is a major constituent of ultrafine particulate matter (PM0.1). Recent epidemiological studies have identified associations between PM0.1 OA and premature mortality and low birth weight. In this study, the source-oriented UCD/CIT model was used to simulate the concentrations and sources of primary organic aerosols (POA) and secondary organic aerosols (SOA) in PM0.1 in California for a 9-year (2000-2008) modeling period with 4 km horizontal resolution to provide more insights about PM0.1 OA for health effect studies. As a related quality control, predicted monthly average concentrations of fine particulate matter (PM2.5)total organic carbon at six major urban sites had mean fractional bias of -0.31 to 0.19 and mean fractional errors of 0.4 to 0.59. The predicted ratio of PM2.5 SOA / OA was lower than estimates derived from chemical mass balance (CMB) calculations by a factor of 23, which suggests the potential effects of processes such as POA volatility, additional SOA formation mechanism, and missing sources. OA in PM0.1, the focus size fraction of this study, is dominated by POA. Wood smoke is found to be the single biggest source of PM0.1 OA in winter in California, while meat cooking, mobile emissions (gasoline and diesel engines), and other anthropogenic sources (mainly solvent usage and waste disposal) are the most important sources in summer. Biogenic emissions are predicted to be the largest PM0.1 SOA source, followed by mobile sources and other anthropogenic sources, but these rankings are sensitive to the SOA model used in the calculation. Air pollution control programs aiming to reduce the PM0.1 OA concentrations should consider controlling solvent usage, waste disposal, and mobile emissions in California, but these findings should be revisited after the latest science is incorporated into the SOA exposure calculations. The spatial distributions of SOA associated with different sources are not sensitive to the choice of SOA model, although the absolute amount of SOA can change significantly. Therefore, the spatial distributions of PM0.1 POA and SOA over the 9-year study period provide

12. Estimating population exposure to ambient polycyclic aromatic hydrocarbon in the United States - Part I: Model development and evaluation

    Zhang, Jie, Li, Jingyi, Wang, Peng, Chen, Gang, Mendola, Pauline, Sherman, Seth, and Ying, Qi

    Environment international, Feb 2017

    Abs Doi

    PAHs (polycyclic aromatic hydrocarbons) in the environment are of significant concern due to their negative impact on human health. PAH measurements at the air toxics monitoring network stations alone are not sufficient to provide a complete picture of ambient PAH levels or to allow accurate assessment of public exposure in the United States. In this study, speciation profiles for PAHs were prepared using data assembled from existing emission profile data bases, and the Sparse Matrix Operator Kernel Emissions (SMOKE) model was used to generate the gridded national emissions of 16 priority PAHs in the US. The estimated emissions were applied to simulate ambient concentration of PAHs for January, April, July and October 2011, using a modified Community Multiscale Air Quality (CMAQ) model (v5.0.1) that treats the gas and particle phase partitioning of PAHs and their reactions in the gas phase and on particle surface. Predicted daily PAH concentrations at 61 air toxics monitoring sites generally agreed with observations, and averaging the predictions over a month reduced the overall error. The best model performance was obtained at rural sites, with an average mean fractional bias (MFB) of -0.03 and mean fractional error (MFE) of 0.70. Concentrations at suburban and urban sites were underestimated with overall MFB = -0.57 and MFE = 0.89. Predicted PAH concentrations were highest in January with better model performance (MFB = 0.12, MFE = 0.69; including all sites), and lowest in July with worse model performance (MFB = 0.90, MFE = 1.08). Including heterogeneous reactions of several PAHs with O-3 on particle surface reduced the over-prediction bias in winter, although significant uncertainties were expected due to relative simple treatment of the heterogeneous reactions in the current model. (C) 2016 Elsevier Ltd. All rights reserved.

13. Proximity to major roadways and prospectively-measured time-to-pregnancy and infertility

    Mendola, Pauline, Sundaram, Rajeshwari, Louis, Germaine M. Buck, Sun, Liping, Wallace, Maeve E., Smarr, Melissa M., Sherman, Seth, Zhu, Yeyi,  Ying, Qi, and Liu, Danping

    Science of the total environment, Jan 2017

    Abs Doi

    We aimed to study the potential impact of proximity to major roadways on time-to-pregnancy and infertility in couples attempting pregnancy in the Longitudinal Investigation of Fertility and Environment (LIFE) study (20052009), a population-based, prospective cohort study. Couples attempting pregnancy (n = 500) were enrolled and followed prospectively until pregnancy or 12 months of trying and 393 couples (78%) had complete data and full follow-up. Time-to-pregnancy was based on a standard protocol using fertility monitors, tracking estrone-3-glucuonide and luteinizing hormone, and pregnancy test kits to detect human chorionic gonadotropin (hCG). The fecundability odds ratio (FOR) and 95% confidence interval (CI) were estimated using proportional odds models. Infertility was defined as 12 months of trying to conceive without an hCG pregnancy and the relative risk (RR) and 95% CI were estimated with log-binomial regression. Final models were adjusted for age, parity, study site, and salivary alpha-amylase, a stress marker. Infertile couples (53/393; 14%) tended to live closer to major roadways on average than fertile couples (689 m vs. 843 m, respectively) but the difference was not statistically significant. The likelihood of pregnancy was increased 3% for every 200 m further away the couples residence was from a major roadway (FOR = 1.03; CI = 1.01-1.06). Infertility also appeared elevated at moderate distances compared to 1000 m or greater, but estimates lacked precision. Our findings suggest that proximity to major roadways may be related to reductions in fecundity. Prospective data from larger populations is warranted to corroborate these findings. Published by Elsevier B.V.

14. Modeling biogenic and anthropogenic secondary organic aerosol in China

    Hu, Jianlin, Wang, Peng,  Ying, Qi, Zhang, Hongliang, Chen, Jianjun, Ge, Xinlei, Li, Xinghua, Jiang, Jingkun, Wang, Shuxiao, Zhang, Jie, Zhao, Yu, and Zhang, Yingyi

    Atmospheric chemistry and physics, Jan 2017

    Abs Doi

    A revised Community Multi-scale Air Quality (CMAQ) model with updated secondary organic aerosol (SOA) yields and a more detailed description of SOA formation from isoprene oxidation was applied to study the spatial and temporal distribution of SOA in China in the entire year of 2013. Predicted organic carbon (OC), elemental carbon and volatile organic compounds agreed favorably with observations at several urban areas, although the high OC concentrations in wintertime in Beijing were under-predicted. Predicted summer SOA was generally higher (1015 mu g m(-3)) due to large contributions of isoprene (country average, 61 %), although the relative importance varies in different regions. Winter SOA was slightly lower and was mostly due to emissions of alkane and aromatic compounds (51 %). Contributions of monoterpene SOA was relatively constant (8-10 %). Overall, biogenic SOA accounted for approximately 75% of total SOA in summer, 50-60% in autumn and spring, and 24% in winter. The Sichuan Basin had the highest predicted SOA concentrations in the country in all seasons, with hourly concentrations up to 50 mu g m(-3). Approximately half of the SOA in all seasons was due to the traditional equilibrium partitioning of semivolatile components followed by oligomerization, while the remaining SOA was mainly due to reactive surface uptake of isoprene epoxide (5-14 %), glyoxal (14-25 %) and methylglyoxal (23-28 %). Sensitivity analyses showed that formation of SOA from biogenic emissions was significantly enhanced due to anthropogenic emissions. Removing all anthropogenic emissions while keeping the biogenic emissions unchanged led to total SOA concentrations of less than 1 mu g m(-3), which suggests that manmade emissions facilitated biogenic SOA formation and controlling anthropogenic emissions would result in reduction of both anthropogenic and biogenic SOA.

15. Improved MEGAN predictions of biogenic isoprene in the contiguous United States

    Wang, Peng, Schade, Gunnar, Estes, Mark, and Ying, Qi

    Atmospheric environment, Jan 2017

    Abs Doi

    Isoprene emitted from biogenic sources significantly contributes to ozone and secondary organic aerosol formation in the troposphere. The Model of Emissions of Gases and Aerosols from Nature (MEGAN) has been widely used to estimate isoprene emissions from local to global scales. However, previous studies have shown that MEGAN significantly over-predicts isoprene emissions in the contiguous United States (US). In this study, ambient isoprene concentrations in the US were simulated by the Community Multiscale Air Quality (CMAQ) model (v5.0.1) using biogenic emissions estimated by MEGAN v2.10 with several different gridded isoprene emission factor (EF) fields. Best isoprene predictions were obtained with the EF field based on the Biogenic Emissions Landcover Database v4 (BELD4) from US EPA for its Biogenic Emission Inventory System (BEIS) model v3.61 (MEGAN-BEIS361). A seven-month simulation (April to October 2011) of isoprene emissions with MEGAN-BEIS361 and ambient concentrations using CMAQ shows that observed spatial and temporal variations (both diurnal and seasonal) of isoprene concentrations can be well predicted at most non-urban monitors using isoprene emission estimation from the MEGAN-BEIS361 without significant biases. The predicted monthly average vertical column density of formaldehyde (HCHO), a reactive volatile organic compound with significant contributions from isoprene oxidation, generally agree with the spatial distribution of HCHO column density derived using satellite data collected by the Ozone Monitoring Instrument (OMI), although summer month vertical column densities in the southeast US were overestimated, which suggests that isoprene emission might still be overestimated in that region. The agreement between observation and prediction may be further improved if more accurate PAR values, such as those derived from satellite-based observations, were used in modeling the biogenic emissions. (C) 2016 Elsevier Ltd. All rights reserved.

2016:3

1. Estimating population exposure to ambient polycyclic aromatic hydrocarbon in the United States - Part II: Source apportionment and cancer risk assessment

   Zhang, Jie, Wang, Peng, Li, Jingyi, Mendola, Pauline, Sherman, Seth, and Ying, Qi

   Environment international, Dec 2016

   Abs Doi

   A revised Community Multiscale Air Quality (CMAQ) model was developed to simulate the emission, reactions, transport, deposition and gas-to-particle partitioning processes of 16 priority polycyclic aromatic hydrocarbons (PAHs), as described in Part I of the two-part series. The updated CMAQ model was applied in this study to quantify the contributions of different emission sources to the predicted PAH concentrations and excess cancer risk in the United States (US) in 2011. The cancer risk in the continental US due to inhalation exposure of outdoor naphthalene (NAPH) and seven larger carcinogenic PAHs (cPAHs) was predicted to be significant. The incremental lifetime cancer risk (ILCR) exceeds 1 x 10(-5) in many urban and industrial areas. Exposure to PAHs was estimated to result in 5704 (608-10,800) excess lifetime cancer cases. Point sources not related with energy generation and the oil and gas processes account for approximately 31% of the excess cancer cases, followed by non-road engines with 18.6% contributions. Contributions of residential wood combustion (16.2%) are similar to that of transportation- related sources (mostly motor vehicles with small contributions from railway and marine vessels; 13.4%). The oil and gas industry emissions, although large contributors to high concentrations of cPAHs regionally, are only responsible of 4.3% of the excess cancer cases, which is similar to the contributions of non-US sources (6.8%) and non-point sources (7.2%). The power generation units pose the most minimal impact on excess cancer risk, with contributions of approximately 2.3%. (C) 2016 Elsevier Ltd. All rights reserved.

2. One-year simulation of ozone and particulate matter in China using WRF/CMAQ modeling system

   Hu, Jianlin, Chen, Jianjun,  Ying, Qi, and Zhang, Hongliang

   Atmospheric chemistry and physics, Aug 2016

   Abs Doi

   China has been experiencing severe air pollution in recent decades. Although an ambient air quality monitoring network for criteria pollutants has been constructed in over 100 cities since 2013 in China, the temporal and spatial characteristics of some important pollutants, such as particulate matter (PM) components, remain unknown, limiting further studies investigating potential air pollution control strategies to improve air quality and associating human health outcomes with air pollution exposure. In this study, a yearlong (2013) air quality simulation using the Weather Research and Forecasting (WRF) model and the Community Multi-scale Air Quality (CMAQ) model was conducted to provide detailed temporal and spatial information of ozone (O-3), total PM2.5, and chemical components. Multi-resolution Emission Inventory for China (MEIC) was used for anthropogenic emissions and observation data obtained from the national air quality monitoring network were collected to validate model performance. The model successfully reproduces the O-3 and PM2.5 concentrations at most cities for most months, with model performance statistics meeting the performance criteria. However, overprediction of O-3 generally occurs at low concentration range while underprediction of PM2.5 happens at low concentration range in summer. Spatially, the model has better performance in southern China than in northern China, central China, and Sichuan Basin. Strong seasonal variations of PM2.5 exist and wind speed and direction play important roles in high PM2.5 events. Secondary components have more boarder distribution than primary components. Sulfate (SO42-), nitrate (NO3-), ammonium (NH4+ ) , and primary organic aerosol (POA) are the most important PM2.5 components. All components have the highest concentrations in winter except secondary organic aerosol (SOA). This study proves the ability of the CMAQ model to reproduce severe air pollution in China, identifies the directions where improvements are needed, and provides information for human exposure to multiple pollutants for assessing health effects.

3. Preterm birth and air pollution: Critical windows of exposure for women with asthma

   Mendola, Pauline, Wallace, Maeve, Hwang, Beom Seuk, Liu, Danping, Robledo, Candace, Mannisto, Tuija, Sundaram, Rajeshwari, Sherman, Seth,  Ying, Qi, and Grantz, Katherine L.

   Journal of allergy and clinical immunology, Aug 2016

   Abs Doi

   Ambient air pollutants may increase preterm birth (PTB) risk, but critical exposure windows are uncertain. The interaction of asthma and pollutant exposure is rarely studied. Objective: We sought to assess the interaction of maternal asthma and air pollutant exposures in relation to PTB risk. Methods: Electronic medical records for 223,502 US deliveries were linked with modified Community Multiscale Air Quality model outputs. Logistic regression with generalized estimating equations estimated the odds ratio and 95% CIs for PTB on the basis of the interaction of maternal asthma and particulate matter with aerodynamic diameter of less than 2.5 microns and particulate matter with aerodynamic diameter of less than 10 microns, ozone (O-3), nitrogen oxides (NOx), sulfur dioxide (SO2), and carbon monoxide (CO) per interquartile range. For each gestational week 23 to 36, exposures among women who delivered were compared with those remaining pregnant. Three-month preconception, whole pregnancy, weeks 1 to 28, and the last 6 weeks of gestation averages were also evaluated. Results: On assessing PTB by gestational week, we found that significant asthma interactions were sporadic before 30 weeks but more common during weeks 34 to 36, with higher risk among mothers with asthma for NOx, CO, and SO2 exposure and an inverse association with O-3 in week 34. Odds of PTB were significantly higher among women with asthma for CO and NOx exposure preconception and early in pregnancy. In the last 6 weeks of pregnancy, PTB risk associated with particulate matter with aerodynamic diameter of less than 10 microns was higher among women with asthma. Conclusions: Mothers with asthma may experience a higher risk for PTB after exposure to traffic-related pollutants such as CO and NOx, particularly for exposures 3-months preconception and in the early weeks of pregnancy.

2015:15

1. Source contributions and regional transport of primary particulate matter in China

   Hu, Jianlin, Wu, Li, Zheng, Bo, Zhang, Qiang, He, Kebin, Chang, Qing, Li, Xinghua, Yang, Fumo,  Ying, Qi, and Zhang, Hongliang

   Environmental pollution, Dec 2015

   Abs Doi

   A source-oriented CMAQ was applied to determine source sector/region contributions to primary particulate matter (PPM) in China. Four months were simulated with emissions grouped to eight regions and six sectors. Predicted elemental carbon (EC), primary organic carbon (POC), and PPM concentrations and source contributions agree with measurements and have significant spatiotemporal variations. Residential is a major contributor to spring/winter EC (50-80%), POC (60%-90%), and PPM (30-70%). For summer/fall, industrial contributes 30-50% for EC/POC and 40-60% for PPM. Transportation is more important for EC (20-30%) than POC/PPM (<5%). Open burning is important in summer/fall of Guangzhou and Chongqing. Dust contributes to 1/3-1/2 in spring/fall of Beijing, Xi’an and Chongqing. Based on sector region combination, local residential/transportation and residential/industrial from Heibei are major contributors to spring PPM in Beijing. In summer/fall, local industrial is the largest. In winter, residential/industrial from local and Hebei account for >90% in Beijing. (C) 2015 Elsevier Ltd. All rights reserved.

2. Molecular view modeling of atmospheric organic particulate matter: Incorporating molecular structure and co-condensation of water

   Pankow, James F., Marks, Marguerite C., Barsanti, Kelley C., Mahmud, Abdullah, Asher, William E., Li, Jingyi,  Ying, Qi, Jathar, Shantanu H., and Kleeman, Michael J.

   Atmospheric environment, Dec 2015

   Abs Doi

   Most urban and regional models used to predict levels of organic particulate matter (OPM) are based on fundamental equations for gas/particle partitioning, but make the highly simplifying, anonymized-view (AV) assumptions that OPM levels are not affected by either: a) the molecular characteristics of the condensing organic compounds (other than simple volatility); or b) co-condensation of water as driven by non-zero relative humidity (RH) values. The simplifying assumptions have allowed parameterized chamber results for formation of secondary organic aerosol (SOA) (e.g., “two-product” (2p) coefficients) to be incorporated in chemical transport models. However, a return towards a less simplistic (and more computationally demanding) molecular view (MV) is needed that acknowledges that atmospheric OPM is a mixture of organic compounds with differing polarities, water, and in some cases dissolved salts. The higher computational cost of MV modeling results from a need for iterative calculations of the composition-dependent gas/particle partition coefficient values. MV modeling of OPM that considered water uptake (but not dissolved salts) was carried out for the southeast United States for the period August 29 through September 7, 2006. Three model variants were used at three universities: CMAQ-RH-2p (at PSU), UCD/CIT-RH-2p (at UCD), and CMAQ-RH-MCM (at TAMU). With the first two, MV structural characteristics (carbon number and numbers of functional groups) were assigned to each of the 2p products used in CMAQv.4.7.1 such that resulting predicted Km; values matched those in CMAQv.4.7.1. When water uptake was allowed, most runs assumed that uptake occurred only into the SOA portion, and imposed immiscibility of SOA with primary organic aerosol (POA). (POA is often viewed as rather non-polar, while SOA is commonly viewed as moderately-to-rather polar. Some runs with UCD/CIT-RH-2p were used to investigate the effects of POA/SOA miscibility.) CMAQ-RH-MCM used MCM to generate oxidation products, and assumed miscibility of SOA and POA. In a similar to 500 km wide band from Louisiana through to at least North Carolina, CMAQ-RH-2p and UCD/CIT-RH-2p predicted that water uptake can increase SOA levels by as much as 50-100% (from a range of similar to 1-2 mu g m(-3) to a range of similar to 1-4 mu g m(-3)). CMAQ-RH-MCM predicted much lower effects of water uptake on SOA levels (<10% increase). The results from CMAQ-RH-2p and UCD/CIT-RH-2p are considered more reflective of reality. In the Alabama/Georgia hotspot, both CMAQ-RH-2p and UCD/CIT-RH-2p predicted aerosol water levels that are up to nearly half the predicted SOA levels, namely similar to 0.5-2 mu g m(-3). Such water levels in SOA will affect particle optical properties, viscosity, gas/particle partitioning times, and rates of hydrolysis and water elimination reactions. (C) 2015 Elsevier Ltd. All rights reserved.

3. Characterizing multi-pollutant air pollution in China: Comparison of three air quality indices

   Hu, Jianlin,  Ying, Qi, Wang, Yungang, and Zhang, Hongliang

   Environment international, Nov 2015

   Abs Doi

   Multi-pollutant air pollution (i.e., several pollutants reaching very high concentrations simultaneously) frequently occurs in many regions across China. Air quality index (AQI) is used worldwide to inform the public about levels of air pollution and associated health risks. The current AQI approach used in China is based on the maximum value of individual pollutants, and does not consider the combined health effects of exposure to multiple pollutants. In this study, two novel alternative indices - aggregate air quality index (AAQI) and health-risk based air quality index (HAQI) - were calculated based on data collected in six megacities of China (Beijing, Shanghai, Guangzhou, Shjiazhuang, Xi’an, and Wuhan) during 2013 to 2014. Both AAQI and HAQI take into account the combined health effects of various pollutants, and the HAQI considers the exposure (or concentration)-response relationships of pollutants. AAQI and HAQI were compared to AQI to examine the effectiveness of the current AQI in characterizing multi-pollutant air pollution in China. The AAQI and HAQI values are higher than the AQI on days when two or more pollutants simultaneously exceed the Chinese Ambient Air Quality Standards (CAAQS) 24-hour Grade II standards. The results of the comparison of the classification of risk categories based on the three indices indicate that the current AQI approach underestimates the severity of health risk associated with exposure to multi-pollutant air pollution. For the AQI-based risk category of ‘unhealthy’, 96% and 80% of the days would be ‘very unhealthy’ or ‘hazardous’ if based on AAQI and HAQI, respectively; and for the AQI-based risk category of ‘very unhealthy’, 67% and 75% of the days would be ‘hazardous’ if based on AAQI and HAQI, respectively. The results suggest that the general public, especially sensitive population groups such as children and the elderly, should take more stringent actions than those currently suggested based on the AQI approach during high air pollution events. Sensitivity studies were conducted to examine the assumptions used in the AAQI and HAQI approaches. Results show that AAQI is sensitive to the choice of pollutant irrelevant constant. HAQI is sensitive to the choice of both threshold values and pollutants included in total risk calculation. (C) 2015 Elsevier Ltd. All rights reserved.

4. Modeling dry and wet deposition of sulfate, nitrate, and ammonium ions in Jiuzhaigou National Nature Reserve, China using a source-oriented CMAQ model: Part I. Base case model results

   Qiao, Xue, Tang, Ya, Hu, Jianlin, Zhang, Shuai, Li, Jingyi, Kota, Sri Harsha, Wu, Li, Gao, Huilin, Zhang, Hongliang, and Ying, Qi

   Science of the total environment, Nov 2015

   Abs Doi

   A source-oriented Community Multiscale Air Quality (CMAQ) model driven by the meteorological fields generated by the Weather Research and Forecasting (WRF) model was used to study the dry and wet deposition of nitrate (NO3-), sulfate (SO42-), and ammonium (NH4+) ions in the Jiuzhaigou National Nature Reserve (JNNR), China from June to August 2010 and to identify the contributions of different emission sectors and source regions that were responsible for the deposition fluxes. The model performance is evaluated in this paper and the source contribution analyses are presented in a companion paper. The results show that WRF is capable of reproducing the observed precipitation rates with a Mean Normalized Gross Error (MNGE) of 8.1%. Predicted wet deposition fluxes of SO42- and NO3- at the Long Lake (LL) site (3100 m a.s.l.) during the three-month episode are 2.75 and 0.34 kg S(N) ha(-1), which agree well with the observed wet deposition fluxes of 2.42 and 0.39 kg S(N) ha(-1), respectively. Temporal variations in the weekly deposition fluxes at LL are also well predicted. Wet deposition flux of NH4+ at LL is over-predicted by approximately a factor of 3 (1.60 kg N ha(-1) vs. 0.56 kg N ha(-1)), likely due to missing alkaline earth cations such as Ca2+ in the current CMAQ simulations. Predicted wet deposition fluxes are also in general agreement with observations at four Acid Deposition Monitoring Network in East Asia (EANET) sites in western China. Predicted dry deposition fluxes of SO42- (including gas deposition of SO2) and NO3- (including gas deposition of HNO3) are 0.12 and 0.12 kg S(N) ha(-1) at LL and 0.07 and 0.08 kg S(N) ha(-1) at Jiuzhaigou Bureau (JB) in JNNR, respectively, which are much lower than the corresponding wet deposition fluxes. Dry deposition flux of NH4+ (including gas deposition of NH3) is 0.21 kg N ha(-1) at LL, and is also much lower than the predicted wet deposition flux. For both dry and wet deposition fluxes, predictions from the 12-km resolution nested domain are similar to those from the 36-km resolution parent domain. (C) 2015 Elsevier B.V. All rights reserved.

5. Modeling dry and wet deposition of sulfate, nitrate, and ammonium ions in Jiuzhaigou National Nature Reserve, China using a source-oriented CMAQ model: Part II. Emission sector and source region contributions

   Qiao, Xue, Tang, Ya, Kota, Sri Harsha, Li, Jingyi, Wu, Li, Hu, Jianlin, Zhang, Hongliang, and Ying, Qi

   Science of the total environment, Nov 2015

   Abs Doi

   A source-oriented Community Multiscale Air Quality (CMAQ) model driven by the meteorological fields generated by the Weather Research and Forecasting (WRF) modelwas used to study the dry and wet deposition of nitrate (NO3-), sulfate (SO42-), and ammonium (NH4+) ions in the Jiuzhaigou National Nature Reserve (JNNR), China from June to August 2010 and to identify the contributions of different emission sectors and source regions that were responsible for the deposition fluxes. Contributions from power plants, industry, transportation, domestic, biogenic, windblown dust, open burning, fertilizer, and manure management sources to deposition fluxes in JNNR watershed and four EANET sites are determined. In JNNR, 96%, 82%, and 87% of the SO42-, NO3- and NH4+ deposition fluxes are in the form of wet deposition of the corresponding aerosol species. Industry and power plants are the two major sources of SO42- deposition flux, accounting for 86% of the total wet deposition of SO42-, and industry has a higher contribution (56%) than that of power plants (30%). Power plants and industry are also the top sources that are responsible for NO3- wet deposition, and contributions from power plants (30%) are generally higher than those from industries (21%). The major sources of NH4+ wet deposition flux in JNNR are fertilizer (48%) and manure management (39%). Source-region apportionment confirms that SO2 and NOx emissions from local and two nearest counties do not have a significant impact on predicted wet deposition fluxes in JNNR, with contributions less than 10%. While local NH3 emissions account for a higher fraction of the NH4+ deposition, approximately 70% of NH4+ wet deposition in JNNR originated from other source regions. This study demonstrates that S and N deposition in JNNR is mostly from long-range transport rather than from local emissions, and to protect JNNR, regional emission reduction controls are needed. (C) 2015 Elsevier B.V. All rights reserved.

6. Acute and recent air pollution exposure and cardiovascular events at labour and delivery

   Mannisto, Tuija, Mendola, Pauline, Grantz, Katherine Laughon, Leishear, Kira, Sundaram, Rajeshwari, Sherman, Seth,  Ying, Qi, and Liu, Danping

   Heart, Sep 2015

   Abs Doi

   Objective To study the relationship between acute air pollution exposure and cardiovascular events during labour/delivery. Methods The Consortium on Safe Labor (2002-2008), an observational US cohort with 223 502 singleton deliveries provided electronic medical records. Air pollution exposure was estimated by modified Community Multiscale Air Quality models. Cardiovascular events (cardiac failure/arrest, stroke, myocardial infarcts and other events) were recorded in the hospital discharge records for 687 pregnancies (0.3%). Logistic regression with generalised estimating equations estimated the relationship between cardiovascular events and daily air pollutant levels for delivery day and the 7 days preceding delivery. Results Increased odds of cardiovascular events were observed for each IQR increase in exposure to nitric oxides at 5 and 6 days prior to delivery (OR= 1.17, 99% CI 1.04 to 1.30 and OR= 1.15, 1.03 to 1.28, respectively). High exposure to toxic air pollution species such as ethylbenzene (OR= 1.50, 1.08 to 2.09), m-xylene (OR= 1.54, 1.11 to 2.13), o-xylene (OR= 1.51, 1.09 to 2.09), p-xylene (OR= 1.43, 1.03 to 1.99) and toluene (OR= 1.42, 1.02 to 1.97) at 5 days prior to delivery were also associated with cardiovascular events. Decreased odds of events were observed with exposure to ozone. Conclusions Air pollution in the days prior to delivery, especially nitrogen oxides and some toxic air pollution species, was associated with increased risk of cardiovascular events during the labour/delivery admission.

7. Significant Contributions of Isoprene to Summertime Secondary Organic Aerosol in Eastern United States

   Ying, Qi, Li, Jingyi, and Kota, Sri Harsha

   Environmental science & technology, Jul 2015

   Abs Doi

   A modified SAPRC-11 (S11) photochemical mechanism with more detailed treatment of isoprene oxidation chemistry and additional secondary organic aerosol (SOA) formation through surface-Controlled, reactive uptake of dicarbonyls, isoprene epoxydiol and rnethacrylic acid epoxide was incorporated in tie Community Multiscale Air Quality Model (CMAQ) to quantitatively determine contributions of isoprene to Summertime ambient SOA concentrations in the eastern United States. The modified model utilizes a precursor-origin resolved approach to determine secondary glyoxal and methylglyoxal produced by oxidation Of isoprene and other major volatile organic compounds (VOCs). Predicted OC concentrations show good agreement with field measurements without significant bias (MFB similar to 0.07 and MFE similar to 0.50), and predicted SOA reproduces observed day-to-day and diurnal variation of Oxygenated Organic Aerosol (OOA) determined by an aerosol mass spectrometer (AMS) at two locations in Houston, Texas. On average, isoprene SOA accounts for 55.5% of total predicted near-surface SOA in the eastern U.S, followed by aromatic compounds (13.2%), sesquiterpenes (13.0%) and monoterpenes (10.9%). Aerosol surface uptake of isoprene-generated glyoxal, methylglyoxal and epoxydiol accounts for approximately 83% of total isoprene SOA or more than 45% of total SOA. A domain wide reduction of NO emissions by 40% leads to a slight decrease of domain average SOA by 3.6% and isoprene SOA by approximately 2.6%. Although most of the isoprene SOA component concentrations are decreased, SOA from isoprene epoxydiol is increased by similar to 16%.

8. Relationships between meteorological parameters and criteria air pollutants in three megacities in China

   Zhang, Hongliang, Wang, Yungang, Hu, Jianlin,  Ying, Qi, and Hu, Xiao-Ming

   Environmental research, Jul 2015

   Abs Doi

   Meteorological conditions play a crucial role in ambient air pollution by affecting both directly and indirectly the emissions, transport, formation, and deposition of air pollutants. In this study, the relationships between meteorological parameters and ambient air pollutants concentrations in three megacities in China, Beijing, Shanghai, and Guangzhou were investigated. A systematic analysis of air pollutants including PM2.5, PM10, CO, SO2, NO2, and O-3 and meteorological parameters including temperature, wind speed (WS), wind direction (WD) and relative humanity (RH) was conducted for a continuous period of 12 months from March 2013 to February 2014. The results show that all three cities experienced severe air quality problems. Clear seasonal trends were observed for PM2.5, PM10, CO, SO2 and NO2 with the maximum concentrations in the winter and the minimum in the summer, while O-3 exhibited an opposite trend. Substantially different correlations between air pollutants and meteorological parameters were observed among these three cities. WS reversely correlated with air pollutants, and temperature positively correlated with O-3. Easterly wind led to the highest PM2.5 concentrations in Beijing, westerly wind led to high PM2.5 concentrations in Shanghai, while northern wind blew air parcels with the highest PM2.5 concentrations to Guangzhou. In Beijing, days of top 10% PM2.5, PM10, CO, and NO2 concentrations were with higher RH compared to days of bottom 10% concentrations, and SO2 and O-3 showed no distinct RH dependencies. In Guangzhou, days of top 10% PM2.5, PM10, CO, SO2, NO2 and O-3 concentrations were with lower RH compared to days of bottom 10% concentrations. Shanghai showed less fluctuation in RH between top and bottom 10%. These results confirm the important role of meteorological parameters in air pollution formation with large variations in different seasons and geological areas. These findings can be utilized to improve the understanding of the mechanisms that produce air pollution, enhance the forecast accuracy of the air pollution under different meteorological conditions, and provide effective measures for mitigating the pollution. (C) 2015 Elsevier Inc. All rights reserved.

9. Evaluation of MEGAN predicted biogenic isoprene emissions at urban locations in Southeast Texas

   Kota, Sri Harsha, Schade, Gunnar, Estes, Mark, Boyer, Doug, and Ying, Qi

   Atmospheric environment, Jun 2015

   Abs Doi

   Summertime isoprene emissions in the Houston area predicted by the Model of Emissions of Gases and Aerosol from Nature (MEGAN) version 2.1 during the 2006 TexAQS study were evaluated using a source-oriented Community Multiscale Air Quality (CMAQ) Model. Predicted daytime isoprene concentrations at nine surface sites operated by the Texas Commission of Environmental Quality (TCEQ) were significantly higher than local observations when biogenic emissions dominate the total isoprene concentrations, with mean normalized bias (MNB) ranges from 2.0 to 7.7 and mean normalized error (MNE) ranges from 2.2 to 7.7. Predicted upper air isoprene and its first generation oxidation products of methacrolein (MACR) and methyl vinyl ketone (MVK) were also significantly higher (MNB = 8.6, MNE = 9.1) than observations made onboard of NOAA’s WP-3 airplane, which flew over the urban area. Over-prediction of isoprene and its oxidation products both at the surface and the upper air strongly suggests that biogenic isoprene emissions in the Houston area are significantly overestimated. Reducing the emission rates by approximately 3/4 was necessary to reduce the error between predictions and observations. Comparison of gridded leaf area index (LAI), plant functional type (PFT) and gridded isoprene emission factor (EF) used in MEGAN modeling with estimates of the same factors from a field survey north of downtown Houston showed that the isoprene over-prediction is likely caused by the combined effects of a large overestimation of the gridded EF in urban Houston and an underestimation of urban Lied. Nevertheless, predicted ozone concentrations in this region were not significantly affected by the isoprene over-predictions, while predicted isoprene SOA and total SOA concentrations can be higher by as much as 50% and 13% using the higher isoprene emission rates, respectively. (C) 2015 Elsevier Ltd. All rights reserved.

10. Formation of Urban Fine Particulate Matter

    Zhang, Renyi, Wang, Gehui, Guo, Song, Zarnora, Misti L.,  Ying, Qi, Lin, Yun, Wang, Weigang, Hu, Min, and Wang, Yuan

    Chemical reviews, May 2015

    Doi
11. Atmospheric wet deposition of sulfur and nitrogen in Jiuzhaigou National Nature Reserve, Sichuan Province, China

    Qiao, Xue, Xiao, Weiyang, Jaffe, Daniel, Kota, Sri Harsha,  Ying, Qi, and Tang, Ya

    Science of the total environment, Apr 2015

    Abs Doi

    In the last two decades, remarkable ecological changes have been observed in Jiuzhaigou National Nature Reserve (JNNR). Some of these changes might be related to excessive deposition of sulfur (S) and nitrogen (N), but the relationship has not been quantified due to lack of monitoring data, particularly S and N deposition data. In this study, we investigated the concentrations, fluxes, and sources of S and N wet deposition in JNNR from April 2010 to May 2011. The results show that SO42-, NO3-, and NH4+ concentrations in the wet deposition were 39.4-170.5,6.2-34.8, and 0.2-61.2 mu eq L-1, with annual Volume-Weighted Mean (VWM) concentrations of 70.5, 12.7,.and 13.4 mu eq L-1, respectively. Annual wet deposition fluxes of SO42-, NO3-, and NH4+ were 8.06, 1.29, and 139 kg S(N) ha(-1), respectively, accounting for about 90% of annual atmospheric inputs of these species at the monitoring site. The results of Positive Matrix Factorization (PMF) analysis show that fossil fuel combustion, agriculture, and aged sea salt contributed to 99% and 83% of annual wet deposition fluxes of SO42- and NO3-, respectively. Agriculture alone contributed to 89% of annual wet deposition flux of NH4+. Although wet deposition in JNNR was polluted by anthropogenic acids, the acidity was largely neutralized by the Ca2+ from crust and 81% of wet deposition samples had a pH higher than 6.00. However, acid rain mainly caused by SO(4)(2-)continued to occur in the wet season, when ambient alkaline dust concentration was lower. Since anthropogenic emissions have elevated S and N deposition and caused acid rain in JNNR, further studies are needed to better quantify the regional sources and ecological effects of S and N deposition for JNNR. (C) 2014 Elsevier B.V. All rights reserved.

12. Modeling regional secondary organic aerosol using the Master Chemical Mechanism

    Li, Jingyi, Cleveland, Meredith, Ziemba, Luke D., Griffin, Robert J., Barsanti, Kelley C., Pankow, James F., and Ying, Qi

    Atmospheric environment, Feb 2015

    Abs Doi

    A modified near-explicit Master Chemical Mechanism (MCM, version 3.2) with 5727 species and 16,930 reactions and an equilibrium partitioning module was incorporated into the Community Air Quality Model (CMAQ) to predict the regional concentrations of secondary organic aerosol (SOA) from volatile organic compounds (VOCs) in the eastern United States (US). In addition to the semi-volatile SOA from equilibrium partitioning, reactive surface uptake processes were used to simulate SOA formation due to isoprene epoxydiol, glyoxal and methylglyoxal. The CMAQ-MCM-SOA model was applied to simulate SOA formation during a two-week episode from August 28 to September 7, 2006. The southeastern US has the highest SOA, with a maximum episode-averaged concentration of similar to 12 mu g m(-3). Primary organic aerosol (POA) and SOA concentrations predicted by CMAQ-MCM-SOA agree well with AMS-derived hydrocarbon-like organic aerosol (HOA) and oxygenated organic aerosol (OOA) urban concentrations at the Moody Tower at the University of Houston. Predicted molecular properties of SOA (O/C, H/C, N/C and OM/OC ratios) at the site are similar to those reported in other urban areas, and O/C values agree with measured O/C at the same site. Isoprene epoxydiol is predicted to be the largest contributor to total SOA concentration in the southeast US, followed by methylglyoxal and glyoxal. The semi-volatile SOA components are dominated by products from beta-caryophyllene oxidation, but the major species and their concentrations are sensitive to errors in saturation vapor pressure estimation. A uniform decrease of saturation vapor pressure by a factor of 100 for all condensable compounds can lead to a 150% increase in total SOA. A sensitivity simulation with UNIFAC-calculated activity coefficients (ignoring phase separation and water molecule partitioning into the organic phase) led to a 10% change in the predicted semivolatile SOA concentrations. (C) 2014 Elsevier Ltd. All rights reserved.

13. Temporal variation in the acute effects of air pollution on blood pressure measured at admission to labor/delivery

    Maennistoe, Tuija, Mendola, Pauline, Liu, Danping, Leishear, Kira,  Ying, Qi, and Sundaram, Rajeshwari

    Air quality atmosphere and health, Feb 2015

    Abs Doi

    Same day or recent air pollution exposure increases blood pressure in pregnant women. Temporal blood pressure variation associated with hourly air pollution is unstudied. We randomly selected 500 women (249 normotensive, 191 with hypertensive disorders, and 60 with chronic hypertension) with singleton pregnancies and blood pressure measured at labor/delivery admission from a large cohort, the Consortium on Safe Labor. Community multiscale air quality models estimated hourly air pollutant exposures for the admission hour (lag 0) and for the 24 h preceding labor/delivery admission (lags 1-24). Linear regression estimated the effect of 10 % increase in pollutants on blood pressure at each time point, adjusting for maternal characteristics, labor type, and time of day. Women with chronic hypertension had higher systolic blood pressure with exposure to particulate matter < 10 mu m (by 1.0-1.3 mmHg at 0-4 h), sulfur dioxide (by 0.7-0.9 mmHg at 0-3, 16-20, and 22-23 h) and with some air toxics. Diastolic blood pressure was higher in normotensive women with ozone exposure (by 0.1-0.4 mmHg at 0-1 and 23-24 h). Similar effects for systolic blood pressure were seen among women with hypertensive disorders (by 0.6 mmHg at 19-20 h), but most pollutants were associated with lower blood pressure in these women. Substantial variation in the impact of hourly air pollutant measures on blood pressure was observed during the day prior to labor/delivery admission, both by mothers’ hypertensive status and by the lag time prior to BP measurement. Effects were largest near admission (lags 0-4) and among women with chronic hypertension.

14. Preconception and early pregnancy air pollution exposures and risk of gestational diabetes mellitus

    Robledo, Candace A., Mendola, Pauline, Yeung, Edwina, Maennistoe, Tuija, Sundaram, Rajeshwari, Liu, Danping,  Ying, Qi, Sherman, Seth, and Grantz, Katherine L.

    Environmental research, Feb 2015

    Abs Doi

    Background: Air pollution has been linked to gestational diabetes mellitus (GDM) but no studies have evaluated impact of preconception and early pregnancy air pollution exposures on GDM risk. Methods: Electronic medical records provided data on 219,952 singleton deliveries to mothers with (n=11,334) and without GDM (n=208,618). Average maternal exposures to particulate matter (PM) <= 2.5 mu m (PM2.5) and PM2.5 constituents, PM <= 10 mu m (PM10), nitrogen oxides (NOx), carbon monoxide, sulfur dioxide (SO2) and ozone (O-3) were estimated for the 3-month preconception window, first trimester, and gestational weeks 1-24 based on modified Community Multiscale Air Quality models for delivery hospital referral regions. Binary regression models with robust standard errors estimated relative risks (RR) for GDM per interquartile range (IQR) increase in pollutant concentrations adjusted for study site, maternal age and race/ethnicity. Results: Preconception maternal exposure to NOX (RR=1.09, 95% CI: 1.04, 1.13) and SO2 (RR=1.05, 1.01, 1.09) were associated with increased risk of subsequent GDM and risk estimates remained elevated for first trimester exposure. Preconception O-3 was associated with lower risk of subsequent GDM (RR=0.93, 0.90, 0.96) but risks increased later in pregnancy. Conclusion: Maternal exposures to NOx and SO2 preconception and during the first few weeks of pregnancy were associated with increased GDM risk. O-3 appeared to increase GDM risk in association with mid-pregnancy exposure but not in earlier time windows. These common exposures merit further investigation. Published by Elsevier Inc.

15. Long-term particulate matter modeling for health effect studies in California - Part 1: Model performance on temporal and spatial variations

    Hu, J., Zhang, H.,  Ying, Q., Chen, S. -H., Vandenberghe, F., and Kleeman, M. J.

    Atmospheric chemistry and physics, Feb 2015

    Abs Doi

    For the first time, a similar to decadal (9 years from 2000 to 2008) air quality model simulation with 4 km horizontal resolution over populated regions and daily time resolution has been conducted for California to provide air quality data for health effect studies. Model predictions are compared to measurements to evaluate the accuracy of the simulation with an emphasis on spatial and temporal variations that could be used in epidemiology studies. Better model performance is found at longer averaging times, suggesting that model results with averaging times >= 1 month should be the first to be considered in epidemiological studies. The UCD/CIT model predicts spatial and temporal variations in the concentrations of O-3, PM2.5, elemental carbon (EC), organic carbon (OC), nitrate, and ammonium that meet standard modeling performance criteria when compared to monthly-averaged measurements. Predicted sulfate concentrations do not meet target performance metrics due to missing sulfur sources in the emissions. Predicted seasonal and annual variations of PM2.5, EC, OC, nitrate, and ammonium have mean fractional biases that meet the model performance criteria in 95, 100, 71, 73, and 92% of the simulated months, respectively. The base data set provides an improvement for predicted population exposure to PM concentrations in California compared to exposures estimated by central site monitors operated 1 day out of every 3 days at a few urban locations. Uncertainties in the model predictions arise from several issues. Incomplete understanding of secondary organic aerosol formation mechanisms leads to OC bias in the model results in summertime but does not affect OC predictions in winter when concentrations are typically highest. The CO and NO (species dominated by mobile emissions) results reveal temporal and spatial uncertainties associated with the mobile emissions generated by the EMFAC 2007 model. The WRF model tends to overpredict wind speed during stagnation events, leading to underpredictions of high PM concentrations, usually in winter months. The WRF model also generally underpredicts relative humidity, resulting in less particulate nitrate formation, especially during winter months. These limitations must be recognized when using data in health studies. All model results included in the current manuscript can be downloaded free of charge at < a href=’http://faculty.engineering.ucdavis.edu/kleeman/’target=’_blank’> http://faculty.engineering.ucdavis.edu/kleeman/</a > .

2014:12

1. Spatial and temporal variations of six criteria air pollutants in 31 provincial capital cities in China during 2013-2014

   Wang, Yungang,  Ying, Qi, Hu, Jianlin, and Zhang, Hongliang

   Environment international, Dec 2014

   Abs Doi

   Long-term air pollution data with high temporal and spatial resolutions are needed to support the research of physical and chemical processes that affect the air quality, and the corresponding health risks. However, such datasets were not available in China until recently. For the first time, this study examines the spatial and temporal variations of PM2.5, PM10, CO, SO2, NO2, and 8 h 03 in 31 capital cities in China between March 2013 and February 2014 using hourly data released by the Ministry of Environmental Protection (MEP) of China. The annual mean concentrations of PM2.5 and PM10 exceeded the Chinese Ambient Air Quality Standards (CAAQS), Grade I standards (15 and 40 mu g/m(3) for PM2.5 and PM10, respectively) for all cities, and only Haikou, Fuzhou and Lasa met the CAAQS Grade II standards (35 and 70 mu g/m(3) for PM2.5 and PM10, respectively). Observed PM2.5, PM10, CO and SO2 concentrations were higher in cities located in the North region than those in the West and the South-East regions. The number of non-attainment days was highest in the winter, but high pollution days were also frequently observed in the South-East region during the fall and in the West region during the spring. PM2.5 was the largest contributor to the air pollution in China based on the number of non-attainment days, followed by PM10, and O-3. Strong correlation was found between different pollutants except for O-3. These results suggest great impacts of coal combustion and biomass burning in the winter, long range transport of windblown dust in the spring, and secondary aerosol formation throughout the year. Current air pollution in China is caused by multiple pollutants, with great variations among different regions and different seasons. Future studies should focus on improving the understanding of the associations between air quality and meteorological conditions, variations of emissions in different regions, and transport and transformation of pollutants in both intra-and inter-regional contexts. (C) 2014 Elsevier Ltd. All rights reserved.

2. Source contributions to primary and secondary inorganic particulate matter during a severe wintertime PM2.5 pollution episode in Xi’an, China

   Wang, Dexiang, Hu, Jianlin, Xu, Yong, Lv, Di, Xie, Xiaoyang, Kleeman, Michael, Xing, Jia, Zhang, Hongliang, and Ying, Qi

   Atmospheric environment, Nov 2014

   Abs Doi

   Average PM2.5 concentrations of similar to 250 mu g m(-3) and peak concentrations of similar to 500 mu g m(-3) were observed in Xi’an, the largest city in Northwest China during an extreme event in January 2013. The source-oriented versions of the Community Multi-scale Air Quality (CMAQ) model with anthropogenic emissions from Emissions Database for Global Atmospheric Research (EDGAR) were used to study the source contributions of six different source categories including energy production, industries, transportation, residential activities, “other” (agriculture, biomass, waste burning, and biogenic sources), and windblown dust to primary and secondary inorganic PM2.5 (nitrate and sulfate) during this episode. The model generally captured the variation and magnitude of PM2.5 concentrations at monitoring sites. The monthly average concentration of the predicted PM2.5 in Xi’an was >200 mu g m(-3), comparing favorably with the measurement of similar to 250 mu g m(-3). Predicted concentrations of elemental carbon (EC), organic aerosol (OA), sulfate, nitrate, and ammonium were 6, 35, 18, 22, and 12 mu g m(-3), respectively. Chemically unresolved PM2.5 components (PM2.5 Other) were similar to 80 mu g m(-3). Industries and residential activities dominated EC, organic carbon (OC) and PM2.5 Other, contributing 85%, 95%, and 83%, respectively. Energy production (mainly coal combustion) was the dominating source for secondary nitrate, contributing 46%. Other local and upwind sources were also important, contributing 43% and 11% of total nitrate, respectively. Primary sulfate was similar to 10 mu g m(-3) in vicinity surrounding point sources. Secondary sulfate from upwind sources was also important with concentrations of similar to 4-5 mu g m(-3). Secondary sulfate formed by SO2 emitted from local sources was dominated by energy production. Based on the contributions of different sources to primary components and secondary nitrate and sulfate, the contributions of different sources to PM2.5 total mass in Xi’an during the extremely polluted months are: energy 5%, industries 58%, transportation 2%, residential activities 16%, dust 4%, and other (including other components, inexplicit sources, and upwind sources) 15%. (C) 2014 Elsevier Ltd. All rights reserved.

3. Spatial and temporal variability of PM2.5 and PM10 over the North China Plain and the Yangtze River Delta, China

   Hu, Jianlin, Wang, Yungang,  Ying, Qi, and Zhang, Hongliang

   Atmospheric environment, Oct 2014

   Abs Doi

   The North China Plain (NCP) and the Yangtze River Delta (YRD) in China have been experiencing severe particulate matter (PM) pollution problems associated with the rapid economic growth and the accelerated urbanization. In this study, hourly mass concentrations of PM2.5 and PM10 during June 1st-August 31st, 2013 were collected in 13 cities located in or adjacent to the NCP region and 20 cities located in the YRD region. The overall average PM2.5 and PM10 concentrations were 77.0 mu g/m(3) and 136.2 mu g/m(3) in the NCP region, respectively, and 42.8 mu g/m(3) and 74.9 mu g/m(3) in the YRD region, respectively. The frequencies of occurrence of concentrations exceeding the China’s Ambient Air Quality Standard (AAQS) (BG3095-12) Grade I standards were 83% for PM2.5 and 93% for PM10 in the NCP region, and 51% for PM2.5 and 66% for PM10 in the YRD region. Strong temporal correlation for both PM2.5 and PM10 between cities within 250 km was frequently observed. PM2.5 was found to be negatively associated with wind speed. On the PM2.5 episode days (when the 24 h PM2.5 concentration is greater than 75 mu g/m(3)), average PM2.5 concentrations were 2-4 times greater compared to the non-episode days. The PM2.5 to PM10 ratio increased from 0.50 (0.57) on the non-episode days to 0.64 (0.64) on the episode days in the NCP (YRD) region. No distinct weekday/weekend difference was observed for PM2.5, PM10, and other gaseous pollutants (CO, SO2, NO2, and O-3) in all cities. The results presented in this paper will serve as an important basis for future regional air quality modeling and source apportionment studies. (C) 2014 Elsevier Ltd. All rights reserved.

4. Impacts of Stabilized Criegee Intermediates, surface uptake processes and higher aromatic secondary organic aerosol yields on predicted PM2.5 concentrations in the Mexico City Metropolitan Zone

   Ying, Qi, Cureno, Iris V., Chen, Gang, Ali, Sajjad, Zhang, Hongliang, Malloy, Meagan, Bravo, Humberto A., and Sosa, Rodolfo

   Atmospheric environment, Sep 2014

   Abs Doi

   The Community Multiscale Air Quality Model (CMAQ) with the SAPRC-99 gas phase photochemical mechanism and the AERO5 aerosol module was applied to model gases and particulate matter (PM) concentrations in the Mexico City Metropolitan Zone (MCMZ) and the surrounding regions for March 2006 using the official 2006 emission inventories, along with emissions from biogenic sources, biomass burning, windblown dust, the Tula Industrial Complex and the Popocatepetl volcano. The base case model was capable of reproducing the observed hourly concentrations of O-3 and attaining CO, NO2 and NOx performance similar to previous modeling studies. Although the base case model performance of hourly PM2.5 and PM10 meets the model performance criteria, under-prediction of high PM2.5 concentrations in late morning indicates that secondary PM, such as sulfate and secondary organic aerosol (SOA), might be under-predicted. Several potential pathways to increase SOA and secondary sulfate were investigated, including Stabilized Criegee Intermediates (SCIs) from ozonolysis reactions of unsaturated hydrocarbons and their reactions with SO2, the reactive uptake processes of SO2, glyoxal and methylglyoxal on particle surface and higher SOA formation due to higher mass yields of aromatic SOA precursors. Averaging over the entire episode, the glyoxal and methylglyoxal reactive uptake and higher aromatics SOA yields contribute to similar to 0.9 mu g m(-3) and similar to 1.25 mu g m(-3) of SOA, respectively. Episode average SOA in the MCMZ reaches similar to 3 mu g m(-3). The SCI pathway increases PM2.5 sulfate by 0.2-0.4 mu g m(-3) or approximately 10-15%. The relative amount of sulfate increase due to SCI agrees with previous studies in summer eastern US. Surface SO2 uptake significantly increases sulfate concentration in MCMZ by 1-3 mu g m(-3) or approximately 50-60%. The higher SOA and sulfate leads to improved PM2.5 and PM10 model performance. (C) 2014 Elsevier Ltd. All rights reserved.

5. Local and inter-regional contributions to PM2.5 nitrate and sulfate in China

   Ying, Qi, Wu, Li, and Zhang, Hongliang

   Atmospheric environment, Sep 2014

   Abs Doi

   Emissions of NOx, SO2 and primary nitrate and sulfate from seven regions in China (North, Northeast, East, Central, South, Southwest and Northwest) were separately tracked in a source-oriented Community Multiscale Air Quality (CMAQ) model to quantify the local and inter-regional contributions to PM2.5 nitrate and sulfate concentrations in different cities and provinces. In January, high concentrations of nitrate (similar to 30 mu g m(-3)) occurred in the North China Plain (NCP) and the Middle and Lower Yangtze Plain (MLYP), as well as the Sichuan Basin. NOx emissions from North, Central and East China were transported over long distances to form rather uniform concentration of nitrate in the NCP and MLYP regions and significantly impacted nitrate concentrations in downwind regions as far as the Pearl River Delta (PRD) region in South China. Wintertime sulfate concentrations demonstrated a more significant inter-regional southward transport pattern and wider spatial distributions than nitrate. The top-five ranked provinces with combined nitrate and sulfate concentrations (Chongqing, Sichuan, Guizhou, Anhui and Hunan) were all affected by emissions from the North, Central and East China, in addition to their local region emissions. In August, slower northerly and northeasterly wind reduced inter-regional transport. Nitrate and sulfate concentrations peaked in North China as dilution was more severely restricted by mountain ranges further north. Three of the top five high concentration provinces (Tianjin, Hebei and Beijing) were located in North China and had more than 55% of local region contributions. Emissions from North China accounted for similar to 20% in the remaining two provinces (Shandong in East China and Henan in Central China). In addition to emissions from North China, similar to 30% or more of the nitrate and sulfate concentrations in four of the top five high concentration provinces (Tianjin, Henan, Hebei and Shandong) were due to emissions from East China. Time series of daily regional contributions in three megacities (Beijing, Shanghai and Chongqing) and a large city cluster (PRD) also indicated stronger and more frequent inter-regional transport in winter than in summer. Although the cities were mostly affected by local region emissions, influences of long range transport were especially obvious for sulfate concentration in the PRD region in winter, where emissions from North, East and Central China often accounted for more than 80% of the total concentrations. The results from this study suggest that provincial or region-level emission controls alone may not be sufficient to effectively reduce nitrate and sulfate concentrations in many areas and coordinated local and inter-regional emission control strategies are necessary for the country. (C) 2014 Elsevier Ltd. All rights reserved.

6. Source apportionment of sulfate and nitrate particulate matter in the Eastern United States and effectiveness of emission control programs

   Zhang, Hongliang, Hu, Jianlin, Kleeman, Michael, and Ying, Qi

   Science of the total environment, Aug 2014

   Abs Doi

   Reducing population exposure to PM2.5 in the eastern US will require control of secondary sulfate and nitrate. A source-oriented Community Multi-scale Air Quality (CMAQ) model is used to determine contributions of major emission sources to nitrate and sulfate concentrations in the seven eastern US cities (New York City, Pittsburgh, Baltimore, Chicago, Detroit, St. Paul, and Winston-Salem) in January and August of 2000 and 2006. Identified major nitrate sources include on-road gasoline-powered vehicles, diesel engines, natural gas and coal combustion. From 2000 to 2006, January nitrate concentrations decreased by 25-68% for all the seven cities. On average, similar to 53% of this change was caused by emissions controls while 47% was caused by meteorology variations. August nitrate concentrations decreased by a maximum of 68% in New York City but Detroit experienced increasing August nitrate concentrations by up to 33%. On average, similar to 33% of the reduction in nitrate is offset by increases associated with meteorological conditions that favor nitrate formation. Coal combustion and natural gas are the dominant sources for sulfate in both seasons. January sulfate decrease from 2000 to 2006 in all cities by 4-58% except New York City, which increases by 13%. On average, similar to 93% of the reduction in sulfate was attributed to emission controls with 7% associated with changes in meteorology. August sulfate concentrations decrease by 11-44% in all cities. On average, emission controls alone between 2000 and 2006 would have caused 6% more reduction but the effectiveness of the controls was mitigated by meteorology conditions more favorable to sulfate production in 2006 vs. 2000. The results of this study suggest that regional emissions controls between 2000 and 2006 have been effective at reducing population exposure to PM2.5 in the eastern US, but yearly variations in meteorology must be carefully considered when assessing the exact magnitude of the control benefits. (C) 2014 Elsevier B.V. All rights reserved.

7. Evaluation of observation-fused regional air quality model results for population air pollution exposure estimation

   Chen, Gang, Li, Jingyi,  Ying, Qi, Sherman, Seth, Perkins, Neil, Rajeshwari, Sundaram, and Mendola, Pauline

   Science of the total environment, Jul 2014

   Abs Doi

   In this study, Community Multiscale Air Quality (CMAQ) model was applied to predict ambient gaseous and particulate concentrations during 2001 to 2010 in 15 hospital referral regions (HRRs) using a 36-km horizontal resolution domain. An inverse distance weighting based method was applied to produce exposure estimates based on observation-fused regional pollutant concentration fields using the differences between observations and predictions at grid cells where air quality monitors were located. Although the raw CMAQ model is capable of producing satisfying results for O-3 and PM2.5 based on EPA guidelines, using the observation data fusing technique to correct CMAQ predictions leads to significant improvement of model performance for all gaseous and particulate pollutants. Regional average concentrations were calculated using five different methods: 1) inverse distance weighting of observation data alone, 2) raw CMAQ results, 3) observation-fused CMAQ results, 4) population-averaged raw CMAQ results and 5) population-averaged fused CMAQ results. It shows that while O-3 (as well as NOx) monitoring networks in the HRRs are dense enough to provide consistent regional average exposure estimation based on monitoring data alone, PM2.5 observation sites (as well as monitors for CO, SO2, PM10 and PM2.5 components) are usually sparse and the difference between the average concentrations estimated by the inverse distance interpolated observations, raw CMAQ and fused CMAQ results can be significantly different. Population-weighted average should be used to account for spatial variation in pollutant concentration and population density. Using raw CMAQ results or observations alone might lead to significant biases in health outcome analyses. (C) 2014 Elsevier B.V. All rights reserved.

8. Predicting Primary PM2.5 and PM0.1 Trace Composition for Epidemiological Studies in California

   Hu, Jianlin, Zhang, Hongliang, Chen, Shu-Hua, Wiedinmyer, Christine, Vandenberghe, Francois,  Ying, Qi, and Kleeman, Michael J.

   Environmental science & technology, May 2014

   Abs Doi

   The University of California-Davis_Primary (UCD_P) chemical transport model was developed and applied to compute the primary airborne particulate matter (PM) trace chemical concentrations from similar to 900 sources in California through a simulation of atmospheric emissions, transport, dry deposition and wet deposition for a 7-year period (2000-2006) with results saved at daily time resolution. A comprehensive comparison between monthly average model results and available measurements yielded Pearson correlation coefficients (R) >= 0.8 at >= 5 sites (out of a total of eight) for elemental carbon (EC) and nine trace elements: potassium, chromium, zinc, iron, titanium, arsenic, calcium, manganese, and strontium in the PM2.5 size fraction. Longer averaging time increased the overall R for PM2.5 EC from 0.89 (I day) to 0.94 (1 month), and increased the number of species with strong correlations at individual sites. Predicted PM0.1 mass and PM0.1 EC exhibited excellent agreement with measurements (R = 0.92 and 0.94, respectively). The additional temporal and spatial information in the UCD_P model predictions produced population exposure estimates for PM2.5 and PM0.1 that differed from traditional exposure estimates based on information at monitoring locations in California Metropolitan Statistical Areas, with a maximum divergence of 58% at Bakersfield. The UCD_P model has the potential to improve exposure estimates in epidemiology studies of PM trace chemical components and health.

9. Identifying PM2.5 and PM0.1 Sources for Epidemiological Studies in California

   Hu, Jianlin, Zhang, Hongliang, Chen, Shuhua,  Ying, Qi, Wiedinmyer, Christine, Vandenberghe, Francois, and Kleeman, Michael J.

   Environmental science & technology, May 2014

   Abs Doi

   The University of California-Davis_Primary (UCD_P) model was applied to simultaneously track similar to 900 source contributions to primary particulate matter (PM) in California for seven continuous years (January 1st, 2000 to December 31st, 2006). Predicted source contributions to primary PM2.5 mass, PM1.8 elemental carbon (EC), PM1.8 organic carbon (OC), PM0.1 EC, and PM0.1 OC were in general agreement with the results from previous source apportionment studies using receptor-based techniques. All sources were further subjected to a constraint check based on model performance for PM trace elemental composition. A total of 151 PM2.5 sources and 71 PM0.1 sources contained PM elements that were predicted at concentrations in general agreement with measured values at nearby monitoring sites. Significant spatial heterogeneity was predicted among the 151 PM2.5 and 71 PM0.1 source concentrations, and significantly different seasonal profiles were predicted for PM2.5 and PM0.1 in central California vs southern California. Population-weighted concentrations of PM emitted from various sources calculated using the UCD_P model spatial information differed from the central monitor estimates by up to 77% for primary PM2.5 mass and 148% for PM2.5 EC because the central monitor concentration is not representative of exposure for nearby population. The results from the UCD_P model provide enhanced source apportionment information for epidemiological studies to examine the relationship between health effects and concentrations of primary PM from individual sources.

10. Evaluation of on-road vehicle CO and NOx National Emission Inventories using an urban-scale source-oriented air quality model

    Kota, Sri Harsha, Zhang, Hongliang, Chen, Gang, Schade, Gunnar W., and Ying, Qi

    Atmospheric environment, Mar 2014

    Abs Doi

    The MOBILE6.2 model was replaced by the Motor Vehicle Emission Simulator (MOVES) in 2012 as an official tool recommended by the United States Environmental Protection Agency (US EPA) to predict vehicular pollutant emission factors. In this study, on-road vehicle emission inventories of CO and NOx for Southeast Texas generated by MOVES and MOBILE6.2 in two versions of the 2005 National Emission Inventory (NEI) were studied by comparing predicted CO and NOx using the EPA’s Community Multiscale Air Quality (CMAQ) Model incorporated with a source-oriented gas phase chemical mechanism with measurements made at six urban and industrial sites in Southeast Texas. The source tracing technique allows direct determination of contributions of on-road vehicles to overall CO and NOx concentrations and identification of ambient concentration measurements which are mostly impacted by vehicle emissions. By grouping the fractional bias (FB) values of the hourly predictions based on vehicle contributions to total CO or NOx concentrations, clear trends in the FB were observed, indicating systematic biases in the emission inventory for these species. Data points dominated by vehicle emissions suggest that surface CO concentrations due to vehicle exhaust are significantly over-estimated by a factor of 2 using either MOVES or MOBILE6.2. NOx concentrations are overestimated by approximately 20-35% and 70% by using the MOBILE6.2 and MOVES emissions, respectively. Emission scaling runs show that a domain-wide reduction of MOBILE6.2 CO emissions by 60% and NOx emissions by 15-25% leads to better model performance of exhaust CO and NOx concentrations in the current study. (C) 2013 Elsevier Ltd. All rights reserved.

11. Evaluation of a seven-year air quality simulation using the Weather Research and Forecasting (WRF)/Community Multiscale Air Quality (CMAQ) models in the eastern United States

    Zhang, Hongliang, Chen, Gang, Hu, Jianlin, Chen, Shu-Hua, Wiedinmyer, Christine, Kleeman, Michael, and Ying, Qi

    Science of the total environment, Mar 2014

    Abs Doi

    The performance of the Weather Research and Forecasting (WRF)/Community Multi-scale Air Quality (CMAQ) system in the eastern United States is analyzed based on results from a seven-year modeling study with a 4-km spatial resolution. For 2-m temperature, the monthly averaged mean bias (MB) and gross error (GE) values are generally within the recommended performance criteria, although temperature is over-predicted with MB values up to 2 K. Water vapor at 2-m is well-predicted but significant biases (>2 g kg(-1)) were observed in wintertime. Predictions for wind speed are satisfactory but biased towards over-prediction with 0 < MB <0.5 m s(-1) and root mean square error (RMSE) around 1.5 to 2 m s(-1). Wind direction, predicted without observation nudging, is not well-reproduced with GE values as large as 50 degrees in summertime. Performance in other months is better with RMSE around 20-30 degrees and MB within +/- 10 degrees. O-3 performance meets the EPA criteria of mean normalized bias (MNB) within +/- 0.15 and accuracy of unpaired peak (AUP) within 0.2. Normalized gross error (NGE) is mostly below 0.25, lower than the criteria of 035. Performance of PM10 is satisfactory with mean fractional bias (MFB) within +/- 0.6, but a large under-prediction in springtime was frequently observed. Performance of PM2.5 and its components is mostly within performance goals except for organic carbon (OC), which is universally under-predicted with MFB values as large as -0.8. The predicted frequency distribution of PM2.5 generally agrees with observations although the predictions are slightly biased towards more frequent high concentrations in most areas. Elemental carbon (EC), nitrate and sulfate concentrations are also well reproduced. The other unresolved PM2.5 components (OTHER) are significantly overestimated by more than a factor of two. No conclusive explanations can be made regarding the possible cause of this universal overestimation, which warrants a follow-up study to better understand this problem. (C) 2013 Elsevier B.V. All rights reserved.

12. Estimation of VOC emission factors from flux measurements using a receptor model and footprint analysis

    Kota, Sri Harsha, Park, Changhyoun, Hale, Martin C., Werner, Nicholas D., Schade, Gunnar W., and Ying, Qi

    Atmospheric environment, Jan 2014

    Abs Doi

    Fluxes of 18 volatile organic compounds (VOCs) collected during May to July 2008 from a tower platform 60 m above the surface in an urban Houston residential area were analyzed using receptor-oriented statistical models and an analytical flux-footprint model to resolve daytime source specific emissions rates. The Multilinear Engine version 2 (ME-2) was used to determine that five sources were responsible for the measured flux at the tower: (i) vehicle exhaust, (ii) a foam plastics industrial source with significant pentane emissions, (iii) consumer and commercial solvent use emissions, (iv) a biogenic emissions source dominated by isoprene, and, (v) evaporative fuel emissions. The estimated median daytime (0700-1900 CST) hourly emission rate from the foam plastics industry was 15.7 +/- 3.1 kg h(-1), somewhat higher than its permitted hourly emission rates. The median daytime vehicle exhaust VOC emission rate of 14.5 +/- 2 g h(-1) vehicle(-1), was slightly higher than our estimation using the Motor Vehicle Emission Simulator (MOVES) with a county-representative vehicle fleet of year 2008 (11.6 +/- 02 g h(-1) vehicle(-1)). The median daytime evaporative fuel VOCs emission rate from parked vehicles was 2.3 1.0 g h(-1) vehicle(-1), which is higher than MOVES estimations and could not be explained by the age of the vehicle fleet, indicating either locally higher evaporative emission sources in the footprint or an underestimation of evaporative emissions by MOVES, or both. (C) 2013 Elsevier Ltd. All rights reserved.

2013:5

1. Role of stabilized Criegee Intermediates in the formation of atmospheric sulfate in eastern United States

   Li, Jingyi,  Ying, Qi, Yi, Bingqi, and Yang, Ping

   Atmospheric environment, Nov 2013

   Abs Doi

   A community Multiscale Air Quality model with the Master Chemical Mechanism is applied to evaluate the reactions of stabilized Criegee Intermediates SCIs with SO2 (k(SCI+SO2)) on sulfate aerosols in the eastern United States (US) during the summer of 2006. Surface sulfate concentrations and total sulfate columns increased by as much as 18% and 6%, respectively, when (k(SCI+SO2)) was increased from 7 x 10(-14) cm(3) s(-1) to a suggested value of 3.9 x 10(-11) cm(3) s(-1). The episode-average increase of the top-of-atmosphere direct radiative forcing due to the additional sulfate can be as much as -0.7 W m(-2) (5%). However, if the SCI + H2O reaction rate constant (k(SCI+H2O)) was also increased based on the reported ratio of k(SCI+H2O) to (k(SCI+SO2)) (6.1 x 10(-5)), the surface sulfate and total sulfate column increases were less than 0.5%, which suggests that the impact of SCIs on sulfate may be insignificant and additional studies are needed to better determine k(SCI+H2O). Small SCIs such as CH2OO and CH3CHOO, and SCIs from isoprene (MVKOO) and monoterpene (APINBOO) oxidation are the dominant SCIs in the eastern US. (C) 2013 Elsevier Ltd. All rights reserved.

2. PRECONCEPTION AIR POLLUTION EXPOSURES INCREASE THE RISK OF GESTATIONAL DIABETES MELLITUS

   Robledo, Candace, Mendola, Pauline, Yeung, Edwina, Sundaram, Rajeshwari, Liu, Danping,  Ying, Qi, Sherman, Seth, Lipsky, Leah, and Katherine, Laughon

   American journal of epidemiology, Jun 2013
3. Simulating near-road reactive dispersion of gaseous air pollutants using a three-dimensional Eulerian model

   Kota, Sri Harsha,  Ying, Qi, and Zhang, Yunlong

   Science of the total environment, Jun 2013

   Abs Doi

   In this study, the TAMNROM-3D model, a 3D Eulerian near-road air quality model with vehicle induced turbulence parameterization and a MOVES based emission preprocessor, is tested using near-road gaseous pollutants data collected near a rural freeway with 34% heavy duty vehicle traffic. Exhaust emissions of gasses from the vehicles are estimated using a lumped vehicle classification scheme based on the number of vehicle axles and the default county-level MOVES vehicle fleet database. The predicted dilution of CO and NOx in the downwind direction agrees well with observation, although the total NOx emission has to be scaled to 85% of its original emission rate estimated by the MOVES model. Using the atmospheric turbulent diffusion coefficient parameterization of Degrazia et al. (2000) with variable horizontal turbulent diffusion coefficient (K-xx) leads to slightly better predictions than a traditional non-height-dependent K-xx. parameterization. The NO2 concentrations can be better predicted when emission of total NOx is split into NO and NO2 using the NO2 to NOx ratio of 29% measured near the road. Simulations using the SAPRC99 photochemical mechanism do not show significant changes in the predicted NO and NO2 concentrations near the road compared to simulations using a simple three-reaction mechanism that involves only NOx and O-3. A regional air quality simulation in Houston, Texas during a high 03 episode in August 2000 shows that using the NO2 to NOx ratio of 29% instead of the traditional 5% leads to as much as 6 ppb increase in 8-h O-3 predictions. (C) 2013 Elsevier B.V. All rights reserved.

4. Source apportionment of formaldehyde during TexAQS 2006 using a source-oriented chemical transport model

   Zhang, Hongliang, Li, Jingyi,  Ying, Qi, Guven, Birnur Buzcu, and Olaguer, Eduardo P.

   Journal of geophysical research-atmospheres, Feb 2013

   Abs Doi

   In this study, a source-oriented version of the Community Multiscale Air Quality (CMAQ) model was developed and used to quantify the contributions of five major local emission source types in Southeast Texas (vehicles, industry, natural gas combustion, wildfires, biogenic sources), as well as upwind sources, to regional primary and secondary formaldehyde (HCHO) concentrations. Predicted HCHO concentrations agree well with observations at two urban sites (the Moody Tower [MT] site at the University of Houston and the Haden Road #3 [HRM-3] site operated by Texas Commission on Environmental Quality). However, the model underestimates concentrations at an industrial site (Lynchburg Ferry). Throughout most of Southeast Texas, primary HCHO accounts for approximately 20-30% of total HCHO, while the remaining portion is due to secondary HCHO (30-50%) and upwind sources (20-50%). Biogenic sources, natural gas combustion, and vehicles are important sources of primary HCHO in the urban Houston area, respectively, accounting for 10-20%, 10-30%, and 20-60% of total primary HCHO. Biogenic sources, industry, and vehicles are the top three sources of secondary HCHO, respectively, accounting for 30-50%, 10-30%, and 5-15% of overall secondary HCHO. It was also found that over 70% of PAN in the Houston area is due to upwind sources, and only 30% is formed locally. The model-predicted source contributions to HCHO at the MT generally agree with source apportionment results obtained from the Positive Matrix Factorization (PMF) technique. Citation: Zhang, H., J. Li, Q. Ying, B. B. Guven, and E. P. Olaguer (2013), Source apportionment of formaldehyde during TexAQS 2006 using a source-oriented chemical transport model, J. Geophys. Res. Atmos., 118, 1525-1535, doi:10.1002/jgrd.50197.

5. Underground water migration studies based on the damage variable coupling with seepage and rock stress

   Xu, Bo, Chen, Bo, Huang, Hao, Qi, Ying, Xinhua, Xie, and Xu, Hang

   Journal of food agriculture & environment, Feb 2013

   Abs

   The rock material damage, which has a natural relationship to permeability change of underground water, is the result of new internal fissures generation and original fissures interconnected under stress environment. This article, creatively introduces the damage variable to the research of seepage and rock stress coupling, describing the process of rock fracture permeability and groundwater seepage field evolution through the establishment of relation equation between the rock damage and its permeability coefficient. A laboratory experiment was carried out to investigate the evolution relationship between rock mass stress and strain, permeability and strain, strain and damage and permeability and damage. The results show that the coupling research of rock damage, stress and permeability is feasible and appears high precision.

2012:4

1. Source apportionment of PM2.5 nitrate and sulfate in China using a source-oriented chemical transport model

   Zhang, Hongliang, Li, Jingyi,  Ying, Qi, Yu, Jian Zhen, Wu, Dui, Cheng, Yuan, He, Kebin, and Jiang, Jingkun

   Atmospheric environment, Dec 2012

   Abs Doi

   Nitrate and sulfate account for a significant fraction of PM2.5 mass and are generally secondary in nature. Contributions to these two inorganic aerosol components from major sources need to be identified for policy makers to develop cost effective regional emission control strategies. In this work, a source-oriented version of the Community Multiscale Air Quality (CMAQ) model that directly tracks the contributions from multiple emission sources to secondary PM2.5 is developed to determine the regional contributions of power, industry, transportation and residential sectors as well as biogenic sources to nitrate and sulfate concentrations in China in January and August 2009. The source-oriented CMAQ model is capable of reproducing most of the available PM10 and PM2.5 mass, and PM2.5 nitrate and sulfate observations. Model prediction suggests that monthly average PM2.5 inorganic components (nitrate + sulfate + ammonium ion) can be as high as 60 mu g m(-3) in January and 45 mu g m(-3) in August, accounting for 20-40% and 50-60% of total PM2.5 mass. The model simulations also indicate significant spatial and temporal variation of the nitrate and sulfate concentrations as well as source contributions in the country. In January, nitrate is high over Central and East China with a maximum of 30 mu g m(-3) in the Sichuan Basin. In August, nitrate is lower and the maximum concentration of 16 mu g m(-3) occurs in North China. In January, highest sulfate occurs in the Sichuan Basin with a maximum concentration of 18 mu g m(-3) while in August high sulfate concentration occurs in North and East China with a similar maximum concentration. Power sector is the dominating source of nitrate and sulfate in both January and August. Transportation sector is an important source of nitrate (20-30%) in both months. Industry sector contributes to both nitrate and sulfate concentrations by approximately 20 -30%. Residential sector contributes to approximately 10-20% of nitrate and sulfate in January but its contribution is low in August. (C) 2012 Elsevier Ltd. All rights reserved.

2. Secondary organic aerosol from polycyclic aromatic hydrocarbons in Southeast Texas

   Zhang, Hongliang, and Ying, Qi

   Atmospheric environment, Aug 2012

   Abs Doi

   Recent chamber studies show that low-volatility gas phase precursors such as polycyclic aromatic hydrocarbons (PAHs) can be a significant source of secondary organic aerosol (SOA). In this work, formation of SOA from the photo-oxidation products of PAHs is added to the SOA modeling framework of the Community Multiscale Air Quality (CMAQ) model to determine the regional distribution of SOA products from PAHs (PAH-SOA) and the contributions from sources in Southeast Texas during the Texas Air Quality Study 2006 (TexAQS 2006). Results show that PAHs released from anthropogenic sources can produce SOA mass as much as 10% of that from the traditional light aromatics or approximately 4% of total anthropogenic SOA. In areas under the influence of wildfire emissions, the amount of PAH-SOA can be as much as 50% of the SOA from light aromatics. A source-oriented modeling framework is adopted to determine the major sources of PAH-SOA by tracking the emitted PAHs and their oxidation products in the gas and aerosol phases from different sources separately. Among the eight sources (vehicles, solvent utilization, residential wood, industries, natural gas combustion, coal combustion, wildfire and other sources) that are tracked in the model, wildfire, vehicles, solvent and industries are the major sources of PAH-SOA. Coal and natural gas combustion appear to be less important in terms of their contributions to PAH-SOA. (C) 2012 Elsevier Ltd. All rights reserved.

3. Comparison of the SAPRC07 and SAPRC99 photochemical mechanisms during a high ozone episode in Texas: Differences in concentrations, OH budget and relative response factors

   Li, Jingyi, Zhang, Hongliang, and Ying, Qi

   Atmospheric environment, Jul 2012

   Abs Doi

   The latest SAPRC photochemical mechanism SAPRC07 (S07), an update from SAPRC99 (S99), is implemented into the Community Multi-scale Air Quality (CMAQ) model and applied to simulate a high ozone episode during the Texas Air Quality Study 2000 (TexAQS 2000). The results from the S07 mechanism are compared with those from the S99 mechanism. In general, the predicted 03 concentrations by S07 are lower than those of S99 with maximum difference as high as 20%. The two mechanisms also show significant differences in the predicted OH, HNO3, PAN and HCHO concentrations. S99 predicts higher OH concentration by 7-20%, higher PAN by approximately 20-25% and higher HCHO by approximately 15% than S07. OH budget analysis suggests that OH propagation factor (P-OH) is higher in urban and industrial areas but lower in rural areas. Although S07 generally predicts similar or higher P-OH, S99 predicts higher new OH formation rate from H2O + O(D-1) and leads to higher OH and thus higher O-3 in most part of the domain. OH reactions with VOCs and CO accounts for a majority part of reacted OH. Secondary VOCs photolysis is not a main path of regenerated OH. New OH mainly comes from H2O + O(D-1) reaction. Although the two mechanisms predict different ozone concentrations, the relative response factor (RRF) of ozone at rural, urban and industrial sites under emission controls of anthropogenic NO. and VOC controls by factors 0.6-1.4 predicted by the two mechanisms are very similar. This suggests that although the absolute predictions are different, both models will provide nearly identical attainment assessment in regulatory applications. (C) 2012 Elsevier Ltd. All rights reserved.

4. Development and Application of Reverse Transcription Loop-Mediated Isothermal Amplification for Detecting Live Shewanella putrefaciens in Preserved Fish Sample

   Li, Chenghua,  Ying, Qi, Su, Xiurong, and Li, Taiwu

   Journal of food science, Apr 2012

   Abs Doi

   Given that live Shewanella putrefaciens is one of the major causes of spoilage for aquatic products even in chill storage, the rapid and accurate detection process is the first priority. In the present study, a novel reverse transcription loop-mediated isothermal amplification (RT-LAMP) detecting assay was developed by targeting internal transcribed spacer (ITS) sequence between 16S and 23S rRNA. At the same time, a new procaryotic mRNA isolation strategy was also established by introducing a polyA tail to RNA during cDNA synthesis step. Under the optimal reaction time (60 min) and temperature (64.1 degrees C), S. putrefaciens could be specially identified from a variety of other tested bacteria by RT-LAMP. The sensitivity analysis showed that RT-LAMP could be identified as lower as 5.4 copies per reaction, which is over 200-fold higher than that of standard PCR (1.08 X 103 copies per reaction). The method could be effectively identified S. putrefaciens in artificially contaminated or spoilaged fish samples with dose-dependent manners. To our knowledge, this is the first report using RT-LAMP assay to detect live S. putrefaciens in fish.

2011:4

1. Physical and chemical processes of wintertime secondary nitrate aerosol formation

   Ying, Qi

   Frontiers of environmental science & engineering in china, Sep 2011

   Abs Doi

   The UCD/CIT model was modified to include a process analysis (PA) scheme for gas and particulate matter (PM) to study the formation of secondary nitrate aerosol during a stagnant wintertime air pollution episode during the California Regional PM2.5/PM10 Air Quality Study (CRPAQS) where detailed measurements of PM components are available at a few sites. Secondary nitrate is formed in the urban areas from near the ground to a few hundred meters above the surface during the day with a maximum modeled net increase rate of 4 mu g center dot m(-3)center dot d(-1) during the study episode. The secondary nitrate formation rate in rural areas is lower due to lower NO2. In the afternoon hours, near-surface temperature can be high enough to evaporate the particulate nitrate. In the nighttime hours, both the gas phase N2O5 reactions with water vapor and the N2O5 heterogeneous reactions with particle-bound water are important for secondary nitrate formation. The N2O5 reactions are most import near the surface to a few hundred meters above surface with a maximum modeled net secondary nitrate increase rate of 1 mu g center dot m(-3)center dot d(-1) and are more significant in the rural areas where the O-3 concentrations are high at night. In general, vertical transport during the day moves the nitrate formed near the surface to higher elevations. During the stagnant days, process analysis indicates that the nitrate concentration in the upper air builds up and leads to a net downward flux of nitrate through vertical diffusion and a rapid increase of surface nitrate concentration.

2. Implementation and initial application of the near-explicit Master Chemical Mechanism in the 3D Community Multiscale Air Quality (CMAQ) model

   Ying, Qi, and Li, Jingyi

   Atmospheric environment, Jun 2011

   Abs Doi

   A modified Master Chemical Mechanism (MCM) with 4642 species and 13,566 reactions was incorporated into the 3D Community Multiscale Air Quality (CMAQ) model (CMAQ MCM) and applied to study a three-week high ozone episode in Southeast Texas during the Texas Air Quality Study 2000 (TexAQS 2000). The 3D CMAQ MCM model successfully reproduced the observed ozone concentrations throughout the Southeast Texas region, with model performance similar to that of the standard SAPRC07 mechanism. The CMAQ MCM has been used to evaluate the VOC emission inventory by directly simulating the concentrations of a large number of VOCs. The simulated 1-h and 24-h average concentrations of major ozone precursor VOCs show that most of the alkanes and alkenes are universally lower than the observed values by a factor of 2-5. The under-prediction of ethane and propane is more significant, by a factor of approximately 5-10. Major aromatic compounds generally agree better with observation within a factor of 2. At the Clinton Drive site, most of the under-predictions occur in the afternoon when industrial facilities are in the immediate upwind direction. The observed concentrations of a number of the under-predicted species show strong correlations with temperature, suggesting that evaporative emissions are underestimated in the emission inventory. (C) 2011 Elsevier Ltd. All rights reserved.

3. Contributions of local and regional sources of NOx to ozone concentrations in Southeast Texas

   Zhang, Hongliang, and Ying, Qi

   Atmospheric environment, Jun 2011

   Abs Doi

   The Community Multi-scale Air Quality (CMAQ) model with a modified SAPRC-99 photochemical mechanism was used to investigate the contributions of local and upwind NOx sources to O-3 concentrations in Southeast Texas during the 2000 Texas Air Quality Study (TexAQS 2000) from August 25 to September 5, 2000. Contributions from eight different local NO source types and eight different source regions to the 8-h average daytime O-3 concentrations from 1100 to 1800 CST (referred to as AD O-3 hereafter) are determined. Both diesel engines and highway gasoline vehicles account for 25 ppb of AD O-3 in the urban Houston area. NOx from natural gas combustion produces 35 ppb of AD O-3 in the industrial area of Houston. Contributions from industrial sources and coal combustion to AD O-3 have comparatively less broad spatial distribution with maximum values of 14 ppb and 20 ppb, respectively. Although the local sources are the most important sources, upwind sources have non-negligible influences (20-50%) on AD O-3 in the entire domain, with a maximum of 50 ppb in rural and coastal areas and 20 ppb in urban and industrial areas. To probe the origins of upwind sources contributions, NOx emissions in the entire eastern United States are divided into eight different regions and their contributions to O-3 concentrations in the Houston-Galveston-Brazoria (HGB) and Beaumont-Port Arthur (BPA) areas are determined. Among the various NOx source regions resolved in this study, other Texas counties near the HGB and BPA areas and southeastern states are the most important non-local sources of O-3. Under favorable transport conditions, emissions from neighbor states and northeastern states could also contribute to non-negligible O-3 concentrations (7-15%) in the HGB and BPA areas. This indicates that in addition to reduce local emissions, regional NOx emission controls, especially from the neighbor counties and states, are also necessary to improve O-3 air quality in Southeast Texas. (C) 2011 Elsevier Ltd. All rights reserved.

4. Secondary organic aerosol formation and source apportionment in Southeast Texas

   Zhang, Hongliang, and Ying, Qi

   Atmospheric environment, Jun 2011

   Abs Doi

   The latest version of US EPA’s Community Multi-scale Air Quality (CMAQ v4.7) model with the most recent update on secondary organic aerosol (SOA) formation pathways was adapted into a source-oriented modeling framework to determine the contributions of different emission sources to SOA concentrations from a carbon source perspective in Southeast Texas during the 2000 Texas Air Quality Study (TexAQS 2000) from August 25 to September 5, 2000. A comparison of the VOC and SOA predictions with observations shows that anthropogenic emissions of long chain alkanes and aromatics are likely underestimated in the EPA’s Clean Air Interstate Rule (CAIR) inventory and the current SOA mechanism in CMAQ still under-predicts SOA. The peak SOA concentrations measured at La Porte are more accurately predicted by increasing the emissions of the anthropogenic SOA precursors by a factor of 5 although the overall precursor concentrations are better predicted by increasing the emissions by a factor of 2. A linear correlation between SOA and odd oxygen (Delta SOA/Delta O-x = 23.0-28.4 mu g m(-3)/pPm O-x) can be found when they are formed simultaneously in the air masses passing the urban Houston area on high SOA days. Based on the adjusted emissions (a factor of 2 increase in the alkane and aromatics precursor emissions), approximately 20% of the total SOA in the Houston-Galveston Bay area is due to anthropogenic sources. Solvent utilization and gasoline engines are the main anthropogenic sources. SOA from alkanes and aromatics accounts for approximately 2-4% and 5-9% of total SOA, respectively. The predicted overall anthropogenic SOA concentrations are not sensitive to the half-life time used to calculate the conversion rate of semi-volatile organic compounds to non-volatile oligomers in the particle phase. The main precursors of biogenic SOA are sesquiterpenes, which contribute to approximately 12-35% of total SOA. Monoterpenes contribute to 3-14% and isoprene accounts for approximately 6-9% of the total SOA. Oligomers from biogenic SOA account for approximately 30-58% of the total SOA, indicating that long range transport is an important source of SOA in this region. (C) 2011 Elsevier Ltd. All rights reserved.

2010:9

1. Traffic assignment considering air quality

   Zhang, Yunlong, Lv, Jinpeng, and Ying, Qi

   Transportation research part d-transport and environment, Dec 2010

   Abs Doi

   This paper presents a methodology of assigning traffic in a network with the consideration of air quality. Traffic assignment is formulated as an optimization problem considering travel cost and on-road emissions. It introduces a cell-based approach to model emission concentrations so that either the average or maximum emissions in a network can be considered in the optimization process. The emissions in a cell are modeled taking into consideration the influence of the emission sources from all cells in the network. A case study demonstrates that minimizing travel cost and reducing air pollutants may not be always achieved simultaneously. The traffic assignment procedure can effectively reduce emission concentrations at those locations with the worst air quality conditions, with only a marginal increase in travel time and average emission concentration in the network. Published by Elsevier Ltd.

2. MicroRNA-125b Suppressesed Human Liver Cancer Cell Proliferation and Metastasis by Directly Targeting Oncogene LIN28B

   Liang, Linhui, Wong, Chun-Ming, Ying, Qiao, Fan, Dorothy Ngo-Yin, Huang, Shenglin, Ding, Jie, Yao, Jian, Yan, Mingxia, Li, Jinjun, Yao, Ming, Ng, Irene Oi-Lin, and He, Xianghuo

   Hepatology, Nov 2010

   Abs Doi

   MicroRNAs (miRNAs) are small, noncoding RNAs that can act as oncogenes or tumor suppressors in human cancer. Our previous study showed that miR-125b was a prognostic indicator for patients with hepatocellular carcinoma (HCC), but its functions and exact mechanisms in hepatic carcinogenesis are still unknown. Here we demonstrate that miR-125b suppressed HCC cell growth in vitro and in vivo. Moreover, miR-125b increased p21Cip1/Waf1 expression and arrested cell cycle at G(1) to S transition. In addition, miR-125b inhibited HCC cell migration and invasion. Further studies revealed that LIN28B was a downstream target of miR-125b in HCC cells as miR-125b bound directly to the 3’ untranslated region of LIN28B, thus reducing both the messenger RNA and protein levels of LIN28B. Silencing of LIN28B recapitulated the effects of miR-125b overexpression, whereas enforced expression of LIN28B reversed the suppressive effects of miR-125b. Conclusion: These findings indicate that miR-125b exerts tumor-suppressive effects in hepatic carcinogenesis through the suppression of oncogene LIN28B expression and suggest a therapeutic application of miR-125b in HCC. (HEPATOLOGY 2010;52:1731-1740)

3. Source contributions of volatile organic compounds to ozone formation in southeast Texas

   Ying, Qi, and Krishnan, Anupama

   Journal of geophysical research-atmospheres, Sep 2010

   Abs Doi

   A source-oriented SAPRC-99 gas phase photochemical mechanism was incorporated into the Community Multiscale Air Quality (CMAQ) model to determine the contributions of volatile organic compounds (VOCs) to predicted net ozone (O-3) formation rates during the Texas Air Quality Study (TexAQS) from 16 August to 7 September 2000. Contributions from biogenic sources, diesel vehicles, highway gasoline vehicles, off-highway gasoline vehicles, solvent utilization, petroleum industries, other industries and wildfires were determined. Peak column-averaged O-3 formation rate due to industrial sources averaged over this episode was approximately 8.5 ppb hr(-1). Contributions of gasoline vehicles and solvent utilization were large in urban areas to the west of the industrial region with highest column-averaged formation rates of 3.7 and 1.4 ppb hr(-1), respectively. Large regional contributions of biogenic sources to O-3 formation were predicted with highest O-3 formation rate of 11.9 ppb hr(-1) in downwind rural areas. Wildfires could contribute to large O-3 formation but their influence was generally localized. Analysis of 2400 back-trajectories from areas with maximum daily 8-h O-3 greater than 90 ppb showed that industrial sources were the largest anthropogenic sources of VOC that contributed to the these high O-3 events, followed by gasoline vehicle sources. The median of relative contributions from biogenic and anthropogenic sources from this analysis was approximately 60% and 40%, respectively. Analysis of the back-trajectories where 1-h peak O-3 concentrations were greater than 120 ppb showed that the median relative contributions due to anthropogenic sources were increased to over 60%. This suggests that high O-3 events in the HGB region were driven by anthropogenic VOC emissions from industrial sources.

4. Source apportionment of airborne particulate matter in Southeast Texas using a source-oriented 3D air quality model

   Zhang, Hongliang, and Ying, Qi

   Atmospheric environment, Sep 2010

   Abs Doi

   A nested version of the source-oriented externally mixed UCD/CIT model was developed to study the source contributions to airborne particulate matter (PM) during a two-week long air quality episode during the Texas 2000 Air Quality Study (TexAQS 2000). Contributions to primary PM and secondary ammonium sulfate in the Houston Galveston Bay (HGB) and Beaumont-Port Arthur (BPA) areas were determined. The predicted 24-h elemental carbon (EC), organic compounds (DC), sulfate, ammonium ion and primary PM25 mass are in good agreement with filter-based observations. Predicted concentrations of hourly sulfate, ammonium ion, and primary OC from diesel and gasoline engines and biomass burning organic aerosol (BBOA) at La Porte, Texas agree well with measurements from an Aerodyne Aerosol Mass Spectrometer (AMS). The UCD/CIT model predicts that EC is mainly from diesel engines and majority of the primary OC is from internal combustion engines and industrial sources. Open burning contributes large fractions of EC, DC and primary PM25 mass. Road dust, internal combustion engines and industries are the major sources of primary PM25. Wildfire dominates the contributions to all primary PM components in areas near the fires. The predicted source contributions to primary PM are in general agreement with results from a chemical mass balance (CMB) model. Discrepancy between the two models suggests that further investigations on the industrial PM emissions are necessary. Secondary ammonium sulfate accounts for the majority of the secondary inorganic PM. Over 80% of the secondary sulfate in the 4 km domain is produced in upwind areas. Coal combustion is the largest source of sulfate. Ammonium ion is mainly from agriculture sources and contributions from gasoline vehicles are significant in urban areas. (C) 2010 Elsevier Ltd. All rights reserved.

5. TLR9 expression in glioma tissues correlated to glioma progression and the prognosis of GBM patients

   Wang, Chao, Cao, Shouqiang, Yan, Ying, Ying, Qiao, Jiang, Tao, Xu, Ke, and Wu, Anhua

   Bmc cancer, Aug 2010

   Abs Doi

   Background: Our study aims to evaluate the expression of TLR9 in glioma tissues, examine the association between TLR9 expression, clinicopathological variables, and glioma patient outcome, we further characterized the direct effects of TLR9 agonist CpG ODN upon the proliferation and invasion of glioma cells in vitro. Methods: RT-PCR and immunofluorescence were used to determine the expression of TLR9 in glioma cell lines and clinical glioma samples. Tissue microarry and immunohistochemistry were applied to evaluated TLR9 expression in 292 newly diagnosed glioma and 13 non-neoplastic brain tissues. We further investigated the effect of CpG ODN on the proliferation and invasion of glioma cells in vitro with MTT assays and matrigel transwell assay respectively. Results: RT-PCR showed that TLR9 expressed in all the glioma samples and glioma cell lines we examined. The tissue array analysis indicated that TLR9 expression is correlated with malignancy of glioma (p < 0.01). Multivariate Cox regression analysis revealed that TLR9 expression is an independent prognostic factor for PFS of GBM patients (P = 0.026). TLR9 agonist CpG ODN has no significant effect on glioma proliferation, but matrigel transwell analysis showed that TLR9 agonist CpG ODN can significantly enhance glioma invasion in vitro. Conclusions: Our data indicated that TLR9 expression increases according to the histopathological grade of glioma, and the TLR9 expression level is related to the PFS of GBM patients. In addition, our findings warrant caution in the directly injection of TLR9 agonist CpG ODN into glioma tissues for the glioma immunotherapy.

6. Source apportionment of wintertime secondary organic aerosol during the California regional PM10/PM2.5 air quality study

   Chen, Jianjun,  Ying, Qi, and Kleeman, Michael J.

   Atmospheric environment, Mar 2010

   Abs Doi

   The UCD/CIT air quality model with the Caltech Atmospheric Chemistry Mechanism (CACM) was used to predict source contributions to secondary organic aerosol (SOA) formation in the San Joaquin Valley (SJV) from December 15, 2000 to January 7, 2001. The predicted 24-day average SOA concentration had a maximum value of 4.26 mu g m(-3) 50 km southwest of Fresno. Predicted SOA concentrations at Fresno, Angiola, and Bakersfield were 2.46 mu g m(-3), 1.68 mu g m(-3), and 2.28 mu g m(-3), respectively, accounting for 6%, 37%, and 4% of the total predicted organic aerosol. The average SOA concentration across the entire SJV was 1.35 mu g m(-3), which accounts for approximately 20% of the total predicted organic aerosol. Averaged over the entire SJV, the major SOA sources were solvent use (28% of SOA), catalyst gasoline engines (25% of SOA), wood smoke (16% of SOA), non-catalyst gasoline engines (13% of SOA), and other anthropogenic sources (11% of SOA). Diesel engines were predicted to only account for approximately 2% of the total SOA formation in the SJV because they emit a small amount of volatile organic compounds relative to other sources. In terms of SOA precursors within the SJV, long-chain alkanes were predicted to be the largest SOA contributor, followed by aromatic compounds. The current study identifies the major known contributors to the SOA burden during a winter pollution episode in the SJV, with further enhancements possible as additional formation pathways are discovered. (C) 2009 Elsevier Ltd. All rights reserved.

7. Source Apportionment of Wintertime Secondary Organic Aerosol During the California Regional Particulate Matter Study

   Chen, Jianjun,  Ying, Qi, and Kleeman, Michael J.

   In AIR POLLUTION MODELING AND ITS APPLICATION XX, Mar 2010

   Abs

   The quantity and origin of secondary organic aerosol (SOA) formation in the San Joaquin Valley from December 15, 2000 to January 7, 2001 were studied using the UCD/CIT air quality model with the Caltech Atmospheric Chemistry Mechanism (CACM). Average SOA concentration across the entire SJV was 1.4 mu g/m(3), which accounted for approximately 20% of predicted organic aerosol. Major SOA sources in the SJV were solvent uses (28% of SOA), catalytic gasoline engines (25% of SOA), wood smoke (16% of SOA), non-catalyst gasoline engines (13% of SOA), and other anthropogenic sources (11% of SOA). This study highlighted the importance of considering SOA formation during wintertime periods in the SJV.

8. Particulate air quality model predictions using prognostic vs. diagnostic meteorology in central California

   Hu, Jianlin,  Ying, Qi, Chen, Jianjun, Mahmud, Abdullah, Zhao, Zhan, Chen, Shu-Hua, and Kleeman, Michael J.

   Atmospheric environment, Jan 2010

   Abs Doi

   Comparisons were made between three sets of meteorological fields used to support air quality predictions for the California Regional Particulate Air Quality Study (CRPAQS) winter episode from December 15, 2000 to January 6, 2001. The first set of fields was interpolated from observations using an objective analysis method. The second set of fields was generated using the WRF prognostic model without data assimilation. The third set of fields was generated using the WRF prognostic model with the four-dimensional data assimilation (FDDA) technique. The UCD/CIT air quality model was applied with each set of meteorological fields to predict the concentrations of airborne particulate matter and gaseous species in central California. The results show that the WRF model without data assimilation over-predicts surface wind speed by similar to 30% on average and consequently yields under-predictions for all PM and gaseous species except sulfate (S(VI)) and ozone(O-3). The WRF model with FDDA improves the agreement between predicted and observed wind and temperature values and consequently yields improved predictions for all PM and gaseous species. Overall, diagnostic meteorological fields produced more accurate air quality predictions than either version of the WRF prognostic fields during this episode. Population-weighted average PM2.5 exposure is 40% higher using diagnostic meteorological fields compared to prognostic meteorological fields created without data assimilation. These results suggest diagnostic meteorological fields based on a dense measurement network are the preferred choice for air quality model studies during stagnant periods in locations with complex topography. (C) 2009 Elsevier Ltd. All rights reserved.

9. TAMNROM-3D Three-Dimensional Eulerian Model to Simulate Air Quality near Highways

   Kota, Sri Harsha,  Ying, Qi, and Zhang, Yunlong

   Transportation research record, Jan 2010

   Abs Doi

   Most models for the study of near-road air quality are based on either steady-state Gaussian equations or Lagrangian puff formulations to describe nonreactive pollutant concentrations at receptor sites. The accuracy of the dispersion calculation is often limited because of simplifications that are necessary to derive the analytical solutions. The general source receptor structure of these models limits their capabilities to treat rapid chemical and physical processes that were recently observed in the near-road environment. A new three-dimensional (3-D) Eulerian near-road air quality model, the Texas A&M Near-Road Model (TAMNROM-3D), was developed. The enhanced pollutant turbulent diffusion caused by moving vehicles is handled in TAMNROM-3D by a revised vehicle-induced turbulence parameterization scheme. The performance of TAMNROM-3D on nonreactive tracer dispersion is evaluated with the SF, data set collected by General Motors during a 1975 sulfate dispersion experiment. Predicted concentrations show good agreement with observations under different wind conditions. Model performance statistics are compared favorably with those reported by the ROADWAY-2 model. Sensitivity studies indicate that the model is robust to reasonable uncertainties in the model parameters and input data.

2009:4

1. Source apportionment of visual impairment during the California regional PM10/PM2.5 air quality study

   Chen, Jianjun,  Ying, Qi, and Kleeman, Michael J.

   Atmospheric environment, Dec 2009

   Abs Doi

   Cases and particulate matter predictions from the UCD/CIT air quality model were used in a visibility model to predict source contributions to visual impairment in the San Joaquin Valley (SJV), the southern portion of California’s Central Valley, during December 2000 and January 2001. Within the SJV, daytime (0800-1700 PST) light extinction was dominated by scattering associated with airborne particles. Measured daytime particle scattering coefficients were compared to predicted values at approximately 40 locations across the SJV after correction for the increased temperature and decreased relative humidity produced by “smart heaters” placed upstream of nephelometers. Mean fractional bias and mean fractional error were -0.22 and 0.65, respectively, indicating reasonable agreement between model predictions and measurements. Particulate water, nitrate, organic matter, and ammonium were the major particulate species contributing to light scattering in the SJV. Daytime light extinction in the SJV averaged between December 25. 2000 and January 7, 2001 was mainly associated with animal ammonia sources (28%), diesel engines (18%). catalyst gasoline engines (9%), other anthropogenic sources (9%). and wood smoke (7%) with initial and boundary conditions accounting for 13% The source apportionment results from this study apply to wintertime conditions when airborne particulate matter concentrations are typically at their annual maximum. Further study would be required to quantify source contributions to light extinction in other seasons. (C) 2009 Elsevier Ltd. All rights reserved

2. Simulating PM concentration during a winter episode in a subtropical valley: Sensitivity simulations and evaluation methods

   Livingstone, P. L., Magliano, K., Guerer, K., Allen, P. D., Zhang, K. M.,  Ying, Q., Jackson, B. S., Kaduwela, A., Kleeman, M., Woodhouse, L. F., Turkiewicz, K., Horowitz, L. W., Scott, K., Johnson, D., Taylor, C., O’Brien, G., DaMassa, J., Croes, B. E., Binkowski, F., and Byun, D.

   Atmospheric environment, Dec 2009

   Abs Doi

   We investigated a two-week episode with high PM concentrations in California Central Valley during the Christmas-New Year of 2000-2001 using a modeling system that consists of a computationally efficient, 3-D photochemical-microphysical transport model, a mesoscale meteorological model, emission models, and an evaluation package. One hundred simulations were conducted with fine resolutions and observational constraints, to reproduce spatial and temporal features of observed PM concentrations and to understand the formation mechanism of the episode. Simulated PM concentrations consist of secondary inorganic components, mainly ammonium nitrate, and total carbon in areas with elevated concentrations in the accumulation mode, and consist of mainly dust and sea salt in the coarse mode. Simulated oxidants and nitrate were significantly elevated over the valley, and the latter showed much less amplitude than the former. Simulated PM concentrations were evaluated with observations systematically with spatially and temporally paired method, a more restrictive multivariate method (NMFROC), and a more flexible “gradient evaluation” method. The paired evaluation shows that high correlation coefficient (R = similar to 0.8) and low fractional error (FE = similar to 0.1) could be achieved at stations with elevated 24-h concentration of PM in the accumulation mode in some simulations. The NMFROC method was used to extract useful information from seemingly failed simulations. A “gradient evaluation” method is introduced here to extract additional information from simulations. We found that emission reductions of NOx and AVOC showed similar effects on percentage basis in different areas, and both are more effective than reducing NH3 for abating elevated concentrations of accumulation mode PM in California Central Valley during the winter episode. Published by Elsevier Ltd.

3. Regional contributions to airborne particulate matter in central California during a severe pollution episode

   Ying, Qi, and Kleeman, Michael

   Atmospheric environment, Feb 2009

   Abs Doi

   The externally-mixed source-oriented UCD/CIT air quality model was applied to determine the significance of inter-regional transport for primary and secondary particulate matter (PM) in California’s Central Valley during a severe wintertime PM pollution episode from December 15, 2000 to January 7, 2001, The gases and primary PM emitted from eight different geographical sub-regions were tracked separately in a model simulation that included transport, physical and chemical transformation and deposition processes. The model results directly predict the contribution that each sub-region makes to PM concentrations throughout the entire model domain. The boundary layer was relatively stagnant during the Simulated 3-week air quality episode, and no consistent transport pattern for primary PM Was predicted. Several significant inter-regional transport events were identified that each lasted a few days. Each of these inter-regional events was characterized by transport of gas-phase precursors of nitrate that combined with local emissions of ammonia to produce particulate nitrate. Nitrate already in the particle phase was not transported efficiently doe to hi.-her city deposition rates for particles relative to gas-phase nitrogen oxides. The distinctive pattern of transport for nitrate precursors reflects the relatively long timescales required to convert NOx emissions to nitrate during winter conditions characterized by low temperatures, weak photolysis rates, and low oxidant concentrations. The equilibrium partitioning of nitrate and ammonia to the particle phase is relatively fast once the nitrate has been produced. The most-likely transport distance for nitrate during the Current episode varied from 130-140 km for the northern portion of the Central Valley to 50-60 km in the Southern portion of the Central Valley. Sub-regions further south in the Valley have smaller transport distances because of slower wind speeds and the greater abundance of ammonia in these areas, leading to faster conversion of gas-phase reactive nitrogen into particulate nitrate, which has a higher city deposition rate than the gas-phase species. The most-likely transport distance for primary organic compounds (OC) was found to be less than that for nitrate, varying from 50 to 60 kin for the northern portion of the Valley to 20-30 km for southern portion of the Valley. Overall, 68% of the particulate nitrate formed in the most polluted sub-regions of the Central Valley originates from emissions in those same sub-regions. Local emissions controls Should therefore provide an effective strategy to reduce airborne particulate matter, concentrations to acceptable levels. (C) 2008 Elsevier Ltd. All rights reserved.

4. Modeling air quality during the California Regional PM10/PM2.5 Air Quality Study (CPRAQS) using the UCD/CIT source-oriented air quality model - Part III. Regional source apportionment of secondary and total airborne particulate matter

   Ying, Qi, Lu, Jin, and Kleeman, Michael

   Atmospheric environment, Jan 2009

   Abs Doi

   A comprehensive air quality modeling project was carried out to simulate regional source contributions to secondary and total (=primary+secondary) airborne particle concentrations in California’s Central Valley. A three-week stagnation episode lasting from December 15, 2000 to January 7, 2001, was chosen for study using the air quality and meteorological data collected during the California Regional PM10/PM2.5 Air Quality Study (CRPAQS). The UCD/CIT mechanistic air quality model was used with explicit decomposition of the gas phase reaction chemistry to track source contributions to secondary PM. Inert artificial tracers were used with an internal mixture representation to track source contributions to primary PM. Both primary and secondary source apportionment calculations were performed for 15 size fractions ranging from 0.01 to 10 mu m particle diameters. Primary and secondary source contributions were resolved for fugitive dust, road dust, diesel engines, catalyst equipped gasoline engines, non-catalyst equipped gasoline engines, wood burning, food cooking, high sulfur fuel combustion, and other anthropogenic sources. Diesel engines were identified as the largest source of secondary nitrate in central California during the study episode, accounting for approximately 40% of the total PM2.5 nitrate. Catalyst equipped gasoline engines were also significant, contributing approximately 20% of the total secondary PM2.5 nitrate. Agricultural sources were the dominant source of secondary ammonium ion. Sharp gradients of PM concentrations were predicted around major urban areas. The relative source contributions to PM2.5 from each source category in urban areas differ from those in rural areas, due to the dominance of primary OC in urban locations and secondary nitrate in the rural areas. The source contributions to ultra-fine particle mass PM0.1 also show clear urban/rural differences. Wood smoke was found to be the major source of PM0.1 in urban areas while motor vehicle sources were the major contributor of PM0.1 in rural areas, reflecting the influence from two major highways that transect the Valley. (C) 2008 Elsevier Ltd. All rights reserved.

2008:2

1. Modeling air quality during the California Regional PM10/PM2.5 Air Quality Study (CRPAQS) using the UCD/CIT source-oriented air quality model - Part I. Base case model results

   Ying, Qi, Lu, Jin, Allen, Paul, Livingstone, Paul, Kaduwela, Ajith, and Kleeman, Michael

   Atmospheric environment, Dec 2008

   Abs Doi

   A comprehensive air quality modeling project was carried out to simulate size and composition resolved airborne particulate matter concentrations in northern and central California using the pollutant concentration and meteorological data collected during the California Regional PM10/PM2.5 Air Quality Study (CRPAQS) from December 15, 2000 to January 7, 2001. Measured 24-h average PM2.5 concentrations during this time period exceeded 180 mu g m(-3) at Bakersfield, making it the most severe PM2.5 air quality episode ever recorded in the United States with a rigorous measurement database to support modeling. In this paper, the UCD/CIT source-oriented air quality model is used to predict the concentrations of O-3, NO, NO2, CO, elemental carbon (EC), organic compounds (OC), nitrate and PM2.5 mass concentration over a 24-day period using a horizontal resolution of 4 km x 4 km to cover all of central California. This is the first extensive evaluation of an air quality model in central California using the fine spatial resolution appropriate for the mountain-valley topography of the region combined with the relatively long multi-week time scales associated with winter stagnation events. Fractional bias (FB) values were calculated at all sites on each day of the study to quantify model performance. The CO (FB = -0.5 to +0.3), O-3 (FB = -0.5 to +0.25), NO (FB = -0.9 to -0.1) and NO2 (FB = 0 to +0.4) concentrations predicted by the UCD/CIT model are in general agreement with observations at most monitoring stations throughout the Valley. The predicted PM2.5 concentrations (FB = -0.5 to +0.75) generally agree with observations at Bethel Island, Sacramento, Fresno and Bakersfield spanning the entire length of the model domain. PM2.5 concentrations are over-predicted at the remote monitoring site Angiola in the central portion of the domain. Part of the over-prediction is due to excess fugitive dust emissions. CO, NO, EC and OC were all under-predicted at Angiola, indicating possible missing combustion sources in the emission inventory. The regional nitrate (FB = -1.5 to +1.25) formation dynamics were correctly reproduced by the model simulation but imperfect wind fields cause differences between the predicted vs. measured spatial distribution of nitrate during the last several days of simulation leading to the broader range of fraction bias. Overall, the results of the current study confirm the ability of the air quality model to capture the major features of a severe particulate air pollution event in northern and central California providing a foundation for future studies on source apportionment and emissions control. (C) 2008 Elsevier Ltd. All rights reserved.

2. Modeling air quality during the California Regional PM10/PM2.5 Air Quality Study (CPRAQS) using the UCD/CIT Source Oriented Air Quality Model - Part II. Regional source apportionment of primary airborne particulate matter

   Ying, Qi, Lu, Jin, Kaduwela, Ajith, and Kleeman, Michael

   Atmospheric environment, Dec 2008

   Abs Doi

   A comprehensive air quality modeling project was carried out to simulate regional source contributions to primary airborne particle concentrations in California’s central Valley. A 3-week stagnation episode lasting from December 15, 2000 to January 7, 2001, was chosen for study using the air quality and meteorological data collected during the California Regional PM10/PM2.5 Air Quality Study (CRPAQS). The UCD/CIT source oriented air quality model was applied to this episode using both the source-oriented external mixture configuration and an internal mixture with artificial tracers so that source contribution information could be retrieved in less time. The majority of the predicted and measured primary airborne particulate matter mass was composed of elemental carbon (EC) and organic carbon (OC). Previous work has shown that base case EC and OC predictions made by the UCD/CIT model are in good agreement with observations. Model results from the current study show that the highest EC and OC concentrations occur in urban areas and along transportation corridors where primary emissions are largest. Lower concentrations of primary EC and OC are predicted at rural locations in the San Joaquin Valley (SJV). Source contributions predicted by the UCD/CIT air quality model were compared to receptor-oriented source apportionment results produced by the Chemical Mass Balance (CMB) model at Fresno and Angiola. The relative contributions from major sources predicted by the UCD/CIT model agree with the CMB model results, building confidence in the accuracy of the UCD/CIT model predictions at locations where the CMB results are not available. Wood smoke was identified as the major regional source of primary OC in airborne particles in the winter SJV episode, accounting for approximately 50% of the total PM2.5. Diesel engines were also found to be a significant contributor to primary PM2.5 OC and the largest contributor to the predicted PM2.5 EC averaged over a typical day. EC contributions from wood smoke increased at night and sometimes reached as high as 40% of the total PM2.5 EC. The contribution of fugitive dust to primary PM2.5 mass was also predicted to be significant, especially in rural areas, but this result is likely biased high by the lack of an appropriate diurnal profile for dust emissions. The results of the current study suggest that reductions in wood burning and diesel engine activity would reduce the regional concentration of primary PM2.5 during severe winter stagnation events in the SJV. (C) 2008 Elsevier Ltd. All rights reserved.

2007:2

1. Verification of a source-oriented externally mixed air quality model during a severe photochemical smog episode

   Ying, Qi, Fraser, Matthew P., Griffin, Robert J., Chen, Jianjun, and Kleeman, Michael J.

   Atmospheric environment, Mar 2007

   Abs Doi

   The CIT/UCD three-dimensional source-oriented externally mixed air quality model is tested during a severe photochemical smog episode (Los Angeles, 7-9 September 1993) using two different chemical mechanisms that describe the formation of ozone and secondary reaction products. The first chemical mechanism is the secondary organic aerosol mechanism (SOAM) that is based on SAPRC90 with extensions to describe the formation of condensable organic products. The second chemical mechanism is the caltech atmospheric chemistry mechanism (CACM) that is based on SAPRC99 with more detailed treatment of organic oxidation products. The predicted ozone concentrations from the CIT/UCD/SOAM and the CIT/UCD/CACM models agree well with the observations made at most monitoring sites with a mean normalized error of approximately 0.4-0.5. Good agreement is generally found between the predicted and measured NOx concentrations except during morning rush hours of 6-10 am when NOx concentrations are under-predicted at most locations. Total VOC concentrations predicted by the two chemical mechanisms agree reasonably well with the observations at three of the four sites where measurements were made. Gas-phase concentrations of phenolic compounds and benzaldehyde predicted by the UCD/CIT/CACM model are higher than the measured concentrations whereas the predicted concentrations of other aromatic compounds approximately agree with the measured values. The fine airborne particulate matter mass concentrations (PM2.5) predicted by the UCD/CIT/SOAM and UCD/CIT/ CACM models are slightly greater than the observed values during evening hours and lower than observed values during morning rush hours. The evening over-predictions are driven by an excess of nitrate, ammonium ion and sulfate. The UCD/CIT/CACM model predicts higher nighttime concentrations of gaseous precursors leading to the formation of particulate nitrate than the UCD/CIT/SOAM model. Elemental carbon and total organic mass are under-predicted by both models during morning rush hour periods. When this latter finding is combined with the NO, under-predictions that occur at the same time, it suggests a systematic bias in the diesel engine emissions inventory. The mass of particulate total organic carbon is under-predicted by both the UCD/CIT/SOAM and UCD/CIT/CACM models during afternoon hours. Elemental carbon concentrations generally agree with the observations at this time. Both the UCD/CIT/SOAM and UCD/CIT/CACM models predict low concentrations of secondary organic aerosol (SOA) (< 3.5 mu g m(-3)) indicating that both models could be missing SOA formation pathways. The representation of the aerosol as an internal mixture vs. a source-oriented external mixture did not significantly affect the predicted concentrations during the current study. (c) 2006 Elsevier Ltd. All rights reserved.

2. Source apportionment of secondary organic aerosol during a severe photochemical smog episode

   Kleeman, Michael J.,  Ying, Qi, Lu, Jin, Mysliwiec, Mitchel J., Griffin, Robert J., Chen, Jianjun, and Clegg, Simon

   Atmospheric environment, Jan 2007

   Abs Doi

   The UCD/CIT air quality model was modified to predict source contributions to secondary organic aerosol (SOA) by expanding the Caltech Atmospheric Chemistry Mechanism to separately track source apportionment information through the chemical reaction system as precursor species react to form condensable products. The model was used to predict source contributions to SOA in Los Angeles from catalyst-equipped gasoline vehicles, non-catalyst equipped gasoline vehicles, diesel vehicles, combustion of high sulfur fuel, other anthropogenic sources, biogenic sources, and initial/boundary conditions during the severe photochemical smog episode that occurred on 9 September 1993. Gasoline engines (catalyst + non-catalyst equipped) were found to be the single-largest anthropogenic source of SOA averaged over the entire model domain. The region-wide 24-h average concentration of SOA produced by gasoline engines was predicted to be 0.34 mu g m(-3) with a maximum 24-h average concentration of 1.81 mu g m(-3) downwind of central Los Angeles. The region-wide 24-h average concentration of SOA produced by diesel engines was predicted to be 0.02 mu g m(-3), with a maximum 24-h average concentration of 0.12 mu g m(-3) downwind of central Los Angeles. Biogenic sources are predicted to produce a region-wide 24-h average SOA value of 0.16 mu g m(-3), with a maximum 24-h average concentration of 1.37 mu g m(-3) in the less-heavily populated regions at the northern and southern edges of the air basin (close to the biogenic emissions sources). SOA concentrations associated with anthropogenic sources were weakly diurnal, with slightly lower concentrations during the day as mixing depth increased. SOA concentrations associated with biogenic sources were strongly diurnal, with higher concentrations of aqueous biogenic SOA at night when relative humidity (RH) peaked and little biogenic SOA formation during the day when RH decreased. (c) 2006 Elsevier Ltd. All rights reserved.

2006:2

1. Source contributions to the regional distribution of secondary particulate matter in California

   Ying, Qi, and Kleeman, MJ

   Atmospheric environment, Feb 2006

   Abs Doi

   Source contributions to PM2.5 nitrate, sulfate and ammonium ion concentrations in California’s San Joaquin Valley (SJV) (4-6 January 1996) and South Coast Air Basin (SoCAB) surrounding Los Angeles (23-25 September 1996) were predicted using a three-dimensional source-oriented Eulerian air quality model. The air quality model tracks the formation of PM2.5 nitrate, sulfate and ammonium ion from primary particles and precursor gases emitted from different sources though a mathematical simulation of emission, chemical reaction, gas-to-particle conversion, transport and deposition. The observed PM2.5 nitrate, sulfate and ammonium ion concentrations, and the mass distribution of nitrate, sulfate and ammonium ion as a function of particle size have been successfully reproduced by the model simulation. Approximately 45-57% of the PM2.5 nitrate and 34-40% of the PM2.5 ammonium ion in the SJV is formed from precursor gaseous species released from sources upwind of the valley. In the SoCAB, approximately 83% of the PM2.5 nitrate and 82% of the PM2.5 ammonium ion is formed from precursor gaseous species released from sources within the air basin. In the SJV, transportation related sources contribute approximately 24-30% of the PM2.5 nitrate (diesel engines similar to 13.5-17.0%, catalyst equipped gasoline engines similar to 10.2-12.8% and non-catalyst equipped gasoline engines similar to 0.3-0.4%). In the SoCAB, transportation related sources directly contribute to approximately 67% of the PM2.5 nitrate (diesel engines 34.6%, noncatalyst equipped gasoline engine 4.7% and catalyst equipped gasoline engine 28.1%). PM2.5 ammonium ion concentrations in the SJV were dominated by area (including animal) NH3 sources (16.7-25.3%), soil (7.2-10.9%), fertilizer NH3 sources (11.4-17.3%) and point NH3 sources (14.3-21.7%). In the SoCAB, ammonium ion is mainly associated with animal sources (28.2%) and catalyst equipped gasoline engines (16.2%). In both regions, the majority of the relatively low PM2.5 sulfate (< 5 mu g m(-3)) is associated with upwind sources. Most of the locally generated sulfate is emitted from diesel engines and high-sulfur fuel combustion processes in both modeling domains. Emissions control programs should target the sources listed above to reduce PM2.5 concentrations. (c) 2005 Elsevier Ltd. All rights reserved.

2. Dominant mechanisms that shape the airborne particle size and composition distribution in central California

   Herner, Jorn D.,  Ying, Qi, Aw, Jeremy, Gao, Oliver, Chang, Daniel P. Y., and Kleeman, Michael J.

   Aerosol science and technology, Feb 2006

   Abs Doi

   The size and composition of ambient airborne particulate matter is reported for winter conditions at five locations in (or near) the San Joaquin Valley in central California. Two distinct types of airborne particles were identified based on diurnal patterns and size distribution similarity: hygroscopic sulfate/ammonium/nitrate particles and less hygroscopic particles composed of mostly organic carbon with smaller amounts of elemental carbon. Daytime PM10 concentrations for sulfate/ammonium/nitrate particles were measured to be 10.1 mu g m(-3), 28.3 mu g m(-3), and 52.8 mu g m(-3) at Sacramento, Modesto and Bakersfield, California, respectively. Nighttime concentrations were 10-30% lower, suggesting that these particles are dominated by secondary production. Simulation of the data with a box model suggests that these particles were formed by the condensation of ammonia and nitric acid onto background or primary sulfate particles. These hygroscopic particles had a mass distribution peak in the accumulation mode (0.56-1.0 mu m) at all times. Daytime PM10 carbon particle concentrations were measured to be 9.5 mu g m(-3), 15.1 mu g m(-3), and 16.2 mu g m(-3) at Sacramento, Modesto, and Bakersfield, respectively. Corresponding nighttime concentrations were 200-300% higher, suggesting that these particles are dominated by primary emissions. The peak in the carbon particle mass distribution varied between 0.2-1.0 mu m. Carbon particles emitted directly from combustion sources typically have a mass distribution peak diameter between 0.1-0.32 mu m. Box model calculations suggest that the formation of secondary organic aerosol is negligible under cool winter conditions, and that the observed shift in the carbon particle mass distribution results from coagulation in the heavily polluted concentrations experienced during the current study. The analysis suggests that carbon particles and sulfate/ammonium/nitrate particles exist separately in the atmosphere of the San Joaquin Valley until coagulation mixes them in the accumulation mode.

2005:2

1. Control strategies for the reduction of airborne particulate nitrate in California’s San Joaquin Valley

   Kleeman, MJ,  Ying, Qi, and Kaduwela, A.

   Atmospheric environment, Sep 2005

   Abs Doi

   The effect of NO,, volatile organic compound (VOC), and NH3 emissions control programs on the formation of particulate ammonium nitrate in the San Joaquin Valley (SJV) was examined under the typical winter conditions that existed on 4-6 January, 1996. The UCD/CIT photochemical transport model was used for this study so that the source origin of primary particulate matter and secondary particulate matter could be identified. When averaged across the entire SJV, the model results predict that 13-18 % of the reactive nitrogen (NOy = NOx+ reaction products of NOx) emitted from local sources within the SJV was converted to nitrate at the ground level. Each gram of NO, emitted locally within the SJV (expressed as NO2) produced 0.23-0.31 g of particulate ammonium nitrate (NH4NO3 which is much smaller than the maximum theoretical yield of 1.7 g of NH4NO3 per gram of NO2. The fraction of reactive nitrogen converted to nitrate varied strongly as a function of location. Urban regions with large amounts of fresh NO emissions converted little reactive nitrogen to nitrate, while remote areas had up to 70% conversion (equivalent to approximately 1.2 g of NH4NO3 per gram of NO2). The use of a single spatially averaged ratio of NH4NO3/NOx as a predictor of how changes to NO, emissions would affect particulate nitrate concentrations would not be accurate at all locations in the SJV under the conditions studied. The largest local sources of particulate nitrate in the SJV were predicted to be diesel engines and catalyst equipped gasoline engines under the conditions experienced on 6 January, 1996. Together, these sources accounted for less than half of the ground-level nitrate aerosol in the SJV. The remaining fraction of the aerosol nitrate originated from reactive nitrogen originally released upwind of the SJV. The majority of this upwind reactive nitrogen was already transformed to nitrate by the time it entered the SJV. The effect of local emissions controls on this upwind material was small. A 50% reduction in NOx emissions applied to sources within the SJV reduced the predicted concentration of total nitrate by approximately 25% during the study episode. VOC emissions controls were less effective, while reasonable NH3 emissions controls had the smallest effect on the amount of ammonium nitrate produced. A 50% reduction in VOC emissions lowered predicted concentrations of total nitrate by 17.5%, while a 50% reduction in NH3 emissions lowered predicted concentrations of total nitrate by only 10%. This latter result is expected since the formation of ammonium nitrate aerosol is limited by the availability of gas-phase nitric acid, with large amounts of excess NH3 available. NO, emissions controls appear to be the most efficient method to reduce the concentration of locally generated particulate nitrate in the SJV under the conditions experienced on 4-6 January, 1996. (c) 2005 Elsevier Ltd. All rights reserved.

2. A comparison of the UCD/CIT air quality model and the CMB source-receptor model for primary airborne particulate matter

   Held, T,  Ying, Qi, Kleeman, MJ, Schauer, JJ, and Fraser, MP

   Atmospheric environment, Apr 2005

   Abs Doi

   Source contributions to primary airborne particulate matter calculated using the source-oriented UCD/ClT air quality model and the receptor- oriented chemical mass balance (CMB) model are compared for two air quality episodes in different parts of California. The first episode occurred in the San Joaquin Valley on 4-6 January 1996, with peak 24 h average PM2.5 concentrations exceeding 100 mu g m(-3). This episode was characterized by low photochemical activity and high particulate nitrate concentrations, with localized regions of high particulate carbon concentrations around urban centers. The second episode occurred in the South Coast Air Basin on 7-9 September 1993, with peak 4 It average PM2.5 concentrations reaching 86 mu g m(-3). This episode was characterized by high photochemical activity and high secondary organic aerosol concentrations. The results from the two independent source apportionment calculations show strong agreement for source contributions to primary PN12.5 total organic mass at 7 receptor sites across the two studies, with a correlation slope of 0.84 and a correlation coefficient (R) of 0.70. Agreement for source contributions to primary PN12.5 total mass was similarly strong, with a correlation slope of 0.83 and a correlation coefficient (R-2) of 0.55. Wood smoke was identified as the dominant source of primary PM2.5 at urban locations in the SJV by both source apportionment techniques. Transportation sources including paved road dust, gasoline engines, and diesel engines, were identified as the dominant source of primary PM2.5 at all locations in the SoCAB by both models. The amount of secondary particulate matter (organic and inorganic) was in good agreement with the measured values minus the primary material identified by the CMB calculation. The UCD/CIT air quality model is able to predict source contributions to airborne particulate matter at all locations and times throughout the study domain. The regional plots of source contributions to primary PM2.5 mass concentrations generated by the UCD/ClT air quality model suggest that high concentrations (25 mu g m(-3)) of primary PM2.5 mass released from the combustion of fuel with high sulfur content exist in areas adjacent to the Los Angeles International Airport and the port of Los Angeles. Emissions profiles for these sources should be developed so that they can be included in future CMB calculations. (c) 2005 Elsevier Ltd. All rights reserved.

2004:2

1. Modeling particulate matter in the San Joaquin Valley with a source-oriented externally mixed three-dimensional photochemical grid model

   Held, T.,  Ying, Qi, Kaduwela, A., and Kleeman, MJ

   Atmospheric environment, Jul 2004

   Abs Doi

   Air pollution in California’s San Joaquin Valley (SJV) rivals that of the Los Angeles area and ranks among the worst in the United States for particulate matter (PM) and ozone. The application and validation of an atmospheric chemical transport model to the SJV will aid in the design of emissions control programs to improve air quality. The extensive data required for meaningful Eulerian modeling of airborne PM in the SJV region were collected as a part of the 1995 Integrated Monitoring Study (IMS95). In the current study, the CIT-UCD source-oriented air quality model is applied to the IMS95 data set to verify model performance in the SJV. This article represents the first published application of a full-scale photochemical grid model with diagnostic meteorological data to simulate PM concentrations in the SJV and is the first study outside of the Los Angeles area to include complete PM model performance statistics. The CIT-UCD model results show excellent agreement with most measurements collected during the IMS95 4 6 January 1996 modeling episode. The fractional bias (FBIAS) for SJV ozone and PM10 are approximately 0.16 and -0.19, respectively, for all SJV stations excluding Bakersfield. Most modeled criteria gases, PM precursor gases, and chemically speciated PM concentrations show strong agreement with their corresponding measurements at the Chowchilla, Fresno, Kern Wildlife Refuge, and Bakersfield sampling stations. Furthermore, the modeled PM size distribution of nitrate, ammonium ion, and sulfate agree well with cascade impactor measurements made at Bakersfield on 5 January 1996. Given the robust model agreement with both gas and condensed phase measurements, it appears that the CIT-UCD model adequately captures the fundamental transport and chemical reactivity of air pollutants in the IMS95 domain during a typical severe pollution episode. These results suggest that the CIT-UCD model can be used to explore control scenarios designed to improve air quality in the SJV. (C) 2004 Elsevier Ltd. All rights reserved.

2. Source apportionment of visibility impairment using a three-dimensional source-oriented air quality model

   Ying, Qi, Mysliwiec, M, and Kleeman, MJ

   Environmental science & technology, Feb 2004

   Abs Doi

   A three-dimensional source-oriented Eulerian air quality model is developed that can predict source contributions to the visibility reduction. Particulate matter and precursor gases from 14 different sources (crustal material, paved road dust, diesel engines, meat cooking, noncatalyst-equipped gasoline engines, catalyst-equipped gasoline engines, high-sulfur fuel, sea salt, refrigerant losses, residential production, animals, soil and fertilizer application, other anthropogenic sources, and background sources) are tracked though a mathematical simulation of emission, chemical reaction, gas-to-particle conversion, transport, and deposition. A visibility model based on Mie theory is modified to use the calculated source contributions to airborne particulate matter size and composition as well as gas-phase pollutant concentrations to quantify total source contributions to visibility impairment. The combined air quality-visibility model is applied to predict source contributions to visibility reduction in southern California for a typical air pollution episode (September 23-25, 1996). The model successfully predicts a severe visibility reduction in the eastern portion of the South Coast Air Basin where the average daytime visibility is measured to be less than 10 km. In the relatively clean coastal portion of the domain, the model successfully predicts that the average daytime visibility is greater than 65 km. Transportation-related sources directly account for approximately 50% of the visibility reduction (diesel engines similar to15-20%, catalyst-equipped gasoline engines similar to10-20%, noncatalyst-equipped gasoline engines similar to3-5%, crustal and paved road dust similar to5%) in the region with the most severe visibility impairment. Ammonia emissions from animal sources account for approximately 10-15% of the visibility reduction.

2003:1

1. Effects of aerosol UV extinction on the formation of ozone and secondary particulate matter

   Ying, Qi, and Kleeman, MJ

   Atmospheric environment, Nov 2003

   Abs Doi

   A radiative transfer model based on the Delta-Eddington approximation is coupled into the framework of a three-dimensional air quality model that represents airborne particles as a source-oriented external mixture. Model simulations performed for Southern California on 25 September 1996 show that ultra-violet (UV) irradiance calculated by the model is in good agreement with measured ground level UV at central Los Angeles. Ozone performance statistics show that the use of the fully coupled radiative transfer calculation within the air quality models leads to more realistic predictions in regions with significant concentration gradients of airborne particulate matter and absorbing gases. The new air quality model with fully coupled radiative transfer calculations predicts lower ozone concentrations (10-22% reduction) and lower PM2.5 concentrations (2.3-8.5% reduction) relative to air quality models that use decoupled radiative transfer calculations or surface UV observations from sparse measurement networks. The greatest ozone reduction predicted by the fully coupled model occurs in polluted regions where photolysis rates are greatly reduced. The feedback effect on ozone concentrations decreased when VOC emissions increased but was insensitive to temperature. The greatest PM2.5 reduction occurs in regions with high gas-phase ammonia and particle-phase ammonium nitrate concentrations. The representation of airborne particulate matter as an internal mixture vs. source-oriented external mixture and homogenous particle vs. core-and-shell configuration did not have a significant effect on the relationship between UV feedback and secondary pollutant concentrations. (C) 2003 Elsevier Ltd. All rights reserved.