Impact Of Crop-Burning On Urban Air Quality Based On WRF-Chem Simulations

Smoke from open crop straw burning which is the main form of biomass fire emission in China has a notable impact on ambient, regional and global air quality. Otherwise, anthropogenic emission is another most important reason for air pollution in China.Firstly, based on Global Mosaics of the standard MODIS land cover type data product (MCD12Q1) in the IGBP Land Cover Type Classification from 2001 to 2012 and FINN v1.5 MODIS Terra+Aqua fire detections from 2002 to 2015, we summarize five key regions of fire emission in China. Northeast of China (NEC), Huai River Basin of China (HRB), Southwest of China (SWC), Southeast of China (SEC), Yangtze River Delta and Pearl River Delta (YRD&PRD). Crop straw burning in NEC, HRB, YRD and PRD is serious, are concentrated in spring and autumn season, the early of summer and autumn season, the end of spring and summer, and summer. Wildfire in SWC and SEC is serious, are concentrated in winter and spring season. In addition to straw burning in NEC has increased in recent years, the rest of the key fire regions has decreased.Secondly, the crop straw burning smoke events of 11 June 2015 and 1 October 2015 in Huai River Basin of China has been simulated using the Weather Research and Forecasting Model coupled with chemistry (WRF-Chem). We focused on the evolution of the fire plume composition and its impact on urban air quality of 83 cities in Henan, Shangdong, Jiangsu and Anhui provinces with two simulations. The first simulation referred to as WRF-FIRE included the Fire Inventory from NCAR (FINN) fire emission dataset, EDGAR-HTAP anthropogenic emissions and Model of Emission of Gases and Aerosols from Nature (MEGAN) while the other referred to as WRF-NOFIRE has been run without FINN fire emission. The results show WRF-FIRE simulation have revealed most of the location of fires and the spreading of the fire plume were properly captured. We found reasonable agreement between the WRF-FIRE run and both ground-based measurements of O3, CO, PM2.5 and PM10. The total correlation coefficient between simulation and observation is up to 0.50. Based on the difference between simulations with and without fire emission, the concentrations of O3, CO, PM2.5 and PM10 increased vary from different cities. The maximum hourly bias (MHB) of CO, PM2.5 and PM10 are up to tripled standard deviations of simulations without fire emission near the source. Emissions of nitrogen oxides (NOx) and volatile organic compounds (VOCs) from fire tend to increase more modeled O3 concentrations downwind from fire location, MHB is almost tripled standard deviations of simulations without fire emission. Meanwhile, the impacts of fires were different in each component of urban air pollution. The basic concentrations of NO2 and SO2 probably decreased due to the high level surface O3 far downwind from fire location.Thirdly, WRF-SMOKE-CMAQ model system and GIS data are applied to study the air pollution and the total anthropogenic emissions reduction scenario simulation in Hefei, Anhui province. The statistical area emissions in Anhui are spatially distributed by GIS tools, and the key industrial emissions are collected as point sources and processed into the SMOKE model. The SMOKE emissions are used to drive CMAQ for simulating the air pollution in Hefei from 11 November 2014 to 10 December 2014. Comparing hourly simulated concentration of PM2.5, PM10, CO NO2,03 and SO2with the observational data. After the area emissions spatially distributed by GIS data, the model system shows good performance on simulating PM2.5, PM10, NO2 and SO2 concentration in Anhui province, especially aerosol particles. The total anthropogenic emissions reduction scenario simulations show daily average of aerosol and gas traces concentration reduction percentage is lower than the percentage of emissions inventories, but the ozone concentration increased because of NOx emission reduction.