气候变化领域集成服务门户(CCPortal): Model bias in simulating major chemical components of PM2.5in China

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DOI	10.5194/acp-20-12265-2020
	Model bias in simulating major chemical components of PM2.5in China
	Miao R.; Chen Q.; Zheng Y.; Cheng X.; Sun Y.; Palmer P.I.; Shrivastava M.; Guo J.; Zhang Q.; Liu Y.; Tan Z.; Ma X.; Chen S.; Zeng L.; Lu K.; Zhang Y.
发表日期	2020
ISSN	16807316
起始页码	12265
结束页码	12284
卷号	20 期号:20
英文摘要	High concentrations of PM2.5 (particulate matter with an aerodynamic diameter less than 2.5 μ m) in China have caused severe visibility degradation. Accurate simulations of PM2.5 and its chemical components are essential for evaluating the effectiveness of pollution control strategies and the health and climate impacts of air pollution. In this study, we compared the GEOS-Chem model simulations with comprehensive datasets for organic aerosol (OA), sulfate, nitrate, and ammonium in China. Model results are evaluated spatially and temporally against observations. The new OA scheme with a simplified secondary organic aerosol (SOA) parameterization significantly improves the OA simulations in polluted urban areas, highlighting the important contributions of anthropogenic SOA from semivolatile and intermediate-volatility organic compounds. The model underestimates sulfate and overestimates nitrate for most of the sites throughout the year. More significant underestimation of sulfate occurs in winter, while the overestimation of nitrate is extremely large in summer. The model is unable to capture some of the main features in the diurnal pattern of the PM2.5 chemical components, suggesting inaccuracies in the presented processes. Potential model adjustments that may lead to a better representation of the boundary layer height, the precursor emissions, hydroxyl radical concentrations, the heterogeneous formation of sulfate and nitrate, and the wet deposition of nitric acid and nitrate have been tested in the sensitivity analysis. The results show that uncertainties in chemistry perhaps dominate the model biases. The proper implementation of heterogeneous sulfate formation and the good estimates of the concentrations of sulfur dioxide, hydroxyl radical, and aerosol liquid water are essential for the improvement of the sulfate simulation. The update of the heterogeneous uptake coefficient of nitrogen dioxide significantly reduces the modeled concentrations of nitrate. However, the large overestimation of nitrate concentrations remains in summer for all tested cases. The possible bias in the chemical production and the wet deposition of nitrate cannot fully explain the model overestimation of nitrate, suggesting issues related to the atmospheric removal of nitric acid and nitrate. A better understanding of the atmospheric nitrogen budget, in particular, the role of the photolysis of particulate nitrate, is needed for future model developments. Moreover, the results suggest that the remaining underestimation of OA in the model is associated with the underrepresented production of SOA. © 2020 Author(s).
语种	英语
scopus关键词	aerosol; ammonium; chemical composition; concentration (composition); hydroxyl radical; modeling; nitrate; particulate matter; sulfate; sulfur dioxide; China
来源期刊	Atmospheric Chemistry and Physics
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/143875
作者单位	State Key Joint Laboratory of Environmental Simulation and Pollution Control, BIC-ESAT and IJRC, College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China; State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China; School of GeoSciences, University of Edinburgh, Edinburgh, EH9 3FF, United Kingdom; Pacific Northwest National Laboratory, Richland, WA 99352, United States; State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing, 100081, China; Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, 100084, China; Institute of Energy and Climate Research, IEK-8: Troposphere, Forschungszentrum Jülich GmbH, Jülich, 52425, Germany
推荐引用方式 GB/T 7714	Miao R.,Chen Q.,Zheng Y.,et al. Model bias in simulating major chemical components of PM2.5in China[J],2020,20(20).
APA	Miao R..,Chen Q..,Zheng Y..,Cheng X..,Sun Y..,...&Zhang Y..(2020).Model bias in simulating major chemical components of PM2.5in China.Atmospheric Chemistry and Physics,20(20).
MLA	Miao R.,et al."Model bias in simulating major chemical components of PM2.5in China".Atmospheric Chemistry and Physics 20.20(2020).