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; Zhang, Hongliang

doi:10.1016/j.envpol.2015.08.037

Cited by 156 publications

(80 citation statements)

References 47 publications

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“…RH is generally underpredicted except for July and August. The performance in this study is comparable to other studies using WRF in China (Hu et al, 2015a;Wang et al, 2010;Wang et al, 2014b;Ying et al, 2014b;, despite the differences in model, resolution, and study region in different studies. Generally, the WRF model has acceptable performance on meteorological parameters.…”

Section: Meteorology Validationsupporting

confidence: 78%

“…Dust and sea salt emissions were generated in line during the CMAQ simulations. In this updated CMAQ model, dust emission module was updated to be compatible with the 20-category MODIS land use data (Hu et al, 2015a). Initial and boundary conditions were based on the default vertical distributions of concentrations that represent clean continental conditions as provided by the CMAQ model.…”

Section: Model Applicationmentioning

confidence: 99%

“…Using the Comprehensive Air Quality Model with extensions (CAMx) and the Particulate Source Apportionment Technology (PSAT), X. determined the contributions of 7 emission categories and 11 source regions to regional air pollution in China and suggested a strong need for regional joint emission control efforts in Beijing. More recently, Hu et al (2015a) used a tracer-based technique in a source-oriented CMAQ to determine source sector/region contributions to primary PM in different seasons in 2012-2013. It was found that residential and industrial emissions from local area and the neighboring Hebei province contribute to high primary PM events in Beijing.…”

Section: Introductionmentioning

confidence: 99%

“…All above modeling studies except Hu et al (2015a) were focused on the formation and source apportionment of airborne PM during the severe pollution episode of January 2013 in northern China. Although additional PM formation pathways and/or emission adjustments were implemented and tuned to better predict this extreme episode, model predictions were only evaluated against a small number of measurements in and near Beijing for a relatively short period of time.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2016

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Abstract. 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 PM 2.5 , 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 PM 2.5 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 PM 2.5 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 PM 2.5 exist and wind speed and direction play important roles in high PM 2.5 events. Secondary components have more boarder distribution than primary components. Sulfate (SO 2− 4 ), nitrate (NO − 3 ), ammonium (NH + 4 ), and primary organic aerosol (POA) are the most important PM 2.5 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.

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Section: Meteorology Validationsupporting

confidence: 78%

Section: Model Applicationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

et al. 2016

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“…This has led to an increasing number of studies aimed at attributing pollution to sources at high spatial, temporal, and sectoral resolutions (e.g., Chambliss et al, 2014;Zhang et al, 2015;Turner et al, 2015;. An important finding of these studies is that regional air quality is in many cases strongly influenced by pollution produced in other regions and transported in the atmosphere across regional boundaries (e.g., Hu et al, 2015;. For instance, a recent study found that during the month of January 2013-2015, roughly half of the PM 2.5 present in Beijing and Tianjin (47 and 55 %, respectively) was due to emissions produced in other regions .…”

Section: Introductionmentioning

confidence: 99%

Effects of atmospheric transport and trade on air pollution mortality in China

Zhao

Zhang

et al. 2017

Atmos. Chem. Phys.

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Abstract. Air quality is a major environmental concern in China, where premature deaths due to air pollution have exceeded 1 million people per year in recent years. Here, using a novel coupling of economic, physical and epidemiological models, we estimate the premature mortality related to anthropogenic outdoor PM 2.5 air pollution in seven regions of China in 2010 and show for the first time how the distribution of these deaths in China is determined by a combination of economic activities and physical transport of pollution in the atmosphere. We find that 33 % (338 600 premature deaths) of China's PM 2.5 -related premature mortality in 2010 were caused by pollutants emitted in a different region of the country and transported in the atmosphere, especially from north to south and from east to west. Trade further extended the cross-regional impact; 56 % of (568 900 premature deaths) China's PM 2.5 -related premature mortality was related to consumption in another region, including 423 800 (42 % of total) and 145 100 (14 %) premature deaths from domestic consumption and international trade respectively. Our results indicate that multilateral and multi-stage cooperation under a regional sustainable development framework is in urgent need to mitigate air pollution and related health impacts, and efforts to reduce the health impacts of air pollution in China should be prioritized according to the source and location of emissions, the type and economic value of the emitting activities, and the related patterns of consumption.

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Wintertime nitrate formation pathways in the North China Plain: Importance of N2O5 heterogeneous hydrolysis

Bei

et al. 2020

Preprint

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Source contributions and regional transport of primary particulate matter in China

Cited by 156 publications

References 47 publications

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

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

Effects of atmospheric transport and trade on air pollution mortality in China

Wintertime nitrate formation pathways in the North China Plain: Importance of N2O5 heterogeneous hydrolysis

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