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One-year simulation of ozone and particulate matter in China using WRF/CMAQ modeling system
by
Zhang, Hongliang
, Chen, Jianjun
, Hu, Jianlin
, Ying, Qi
in
Aerosols
/ Air monitoring
/ Air pollution
/ Air pollution control
/ Air pollution research
/ Air quality
/ Air quality models
/ Ammonium
/ Ammonium compounds
/ Analysis
/ Anthropogenic factors
/ Chemistry
/ Components
/ Computer simulation
/ Criteria
/ Emission inventories
/ Environmental health
/ Environmental monitoring
/ Health aspects
/ Meteorological research
/ Modelling
/ Monitoring systems
/ Outdoor air quality
/ Ozone
/ Particulate emissions
/ Particulate matter
/ Pollutants
/ Pollution control
/ Pollution monitoring
/ Seasonal variations
/ Secondary aerosols
/ Simulation
/ Spatial data
/ Statistical methods
/ Studies
/ Sulfates
/ Suspended particulate matter
/ VOCs
/ Volatile organic compounds
/ Weather forecasting
/ Wind speed
2016
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One-year simulation of ozone and particulate matter in China using WRF/CMAQ modeling system
by
Zhang, Hongliang
, Chen, Jianjun
, Hu, Jianlin
, Ying, Qi
in
Aerosols
/ Air monitoring
/ Air pollution
/ Air pollution control
/ Air pollution research
/ Air quality
/ Air quality models
/ Ammonium
/ Ammonium compounds
/ Analysis
/ Anthropogenic factors
/ Chemistry
/ Components
/ Computer simulation
/ Criteria
/ Emission inventories
/ Environmental health
/ Environmental monitoring
/ Health aspects
/ Meteorological research
/ Modelling
/ Monitoring systems
/ Outdoor air quality
/ Ozone
/ Particulate emissions
/ Particulate matter
/ Pollutants
/ Pollution control
/ Pollution monitoring
/ Seasonal variations
/ Secondary aerosols
/ Simulation
/ Spatial data
/ Statistical methods
/ Studies
/ Sulfates
/ Suspended particulate matter
/ VOCs
/ Volatile organic compounds
/ Weather forecasting
/ Wind speed
2016
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One-year simulation of ozone and particulate matter in China using WRF/CMAQ modeling system
by
Zhang, Hongliang
, Chen, Jianjun
, Hu, Jianlin
, Ying, Qi
in
Aerosols
/ Air monitoring
/ Air pollution
/ Air pollution control
/ Air pollution research
/ Air quality
/ Air quality models
/ Ammonium
/ Ammonium compounds
/ Analysis
/ Anthropogenic factors
/ Chemistry
/ Components
/ Computer simulation
/ Criteria
/ Emission inventories
/ Environmental health
/ Environmental monitoring
/ Health aspects
/ Meteorological research
/ Modelling
/ Monitoring systems
/ Outdoor air quality
/ Ozone
/ Particulate emissions
/ Particulate matter
/ Pollutants
/ Pollution control
/ Pollution monitoring
/ Seasonal variations
/ Secondary aerosols
/ Simulation
/ Spatial data
/ Statistical methods
/ Studies
/ Sulfates
/ Suspended particulate matter
/ VOCs
/ Volatile organic compounds
/ Weather forecasting
/ Wind speed
2016
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One-year simulation of ozone and particulate matter in China using WRF/CMAQ modeling system
Journal Article
One-year simulation of ozone and particulate matter in China using WRF/CMAQ modeling system
2016
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Overview
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 (O3), 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 O3 and PM2.5 concentrations at most cities for most months, with model performance statistics meeting the performance criteria. However, overprediction of O3 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.
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