Source Contribution Of PM_2.5 Over Yangtze River Delta Region Based On WRF-Chem

With the rapid achievement of economic construction,the continuous growth of resources consumption and the increasing number of city vehicles,the atmospheric environment is under severe conditions.The regional and complex air pollution characteristics have frequently emerged,especially in economically developed areas.This problem seriously restricts the sustainable development of economy and threatens the human health.The Yangtze River Delta is a more thickly populated and economically developed region where haze pollution occurs frequently,influencing in wide range.Haze is the fine particle aerosol pollution during which PM_2.5concentration exceeds permissible standard.The particles could remain suspended in the air for a while or be transmitted over a long distance for the small size which would be harmful to our health and bring inconvenience to our daily lives.Although the environment has been greatly improved as well as PM_2.5 concentration decreased a lot in the past few years,there still a long way to go.Figuring out the characteristics and rules of pollution interactions over the Yangtze River Delta is important to the joint prevention and control mechanism and regional environmental crisis alleviation.Haze days selected from 2012 to 2016 were classified based on their meteorological circulation situations.We apply the online-coupled meteorology and chemistry model WRF-Chem?Weather Research and Forecasting/Chemistry?to simulate these haze episodes and conduct sensitivity tests by clearing out the emissions of different contribution sources from the inventory.The spatial distribution of PM_2.5 in the Yangtze River Delta,the contribution rates and contributions of emission sources under different synoptic weather patterns were calculated.The research results were listed as follows:?1?The simulations and observations of Shanghai,Nanjing and Hangzhou which are known as typical cities in the Yangtze River Delta are extracted in December of 2013 to evaluate model performance.The simulation results of wind,temperature,relative humidity,and PM_2.5 concentration in these three cities can well agree with the observed values,showing strong consistency.The correlation coefficient values between simulated and observed temperature in Shanghai,Nanjing and Hangzhou are 0.92,0.71 and 0.87 and the values of relative humidity are 0.75,0.67 and 0.74 respectively.In these cities,the correlation coefficient values of PM_2.5are between 0.57 and 0.67.Compared with the observed data,simulated wind speed values are relatively high and there are errors in PM_2.5 concentrations due to the uncertainty of the emission inventory and flaws in the model.However,our results are still within the acceptable range.?2?ERA-Interim data of geopotential height in both 500hPa and 850hPa,as well as sea level pressure which are provided by European Centre for Medium-Range Weather Forecasts were put into COST733 software to get our haze days classified.All the haze days were divided into five types based on the circulation situation.The number of haze days in the first type?uniform pressure field/front of anticyclone?accounts for 40.86%with 143 days,highest among all the five types.The proportion of the second synoptic weather pattern?cold front/front of anticyclone?is 29.71%and mostly happened in January,October,November and December.The haze days under the third type?rear of anticyclone?mostly occurred in Spring and Winter.The proportions of the fourth?bottom of anticyclone?and the fifth type?cyclone/front of inverted trough?of weather conditions are both the smallest at a rate of 6.86%.Haze days which are under the fourth weather type are occurred in September and October.?3?Sensitivity tests were carried out by clearing the anthropogenic emissions from Shanghai,Jiangsu,Zhejiang,the Yangtze River Delta,and outside regions.The Yangtze River Delta is the main contributor to Shanghai,Jiangsu and Zhejiang among five synoptic patterns and the average contribution rates are 32.12%,24.61%and31.49%respectively.For Shanghai,Jiangsu and Zhejiang,the contribution rate of local emission is much higher than that of the other two provinces or cities.Emissions from Zhejiang contributed more PM_2.5 to Shanghai while the contribution rate of Jiangsu is slightly higher.Shanghai and Zhejiang contributed small amount of PM_2.5concentration to Jiangsu province,and the contribution rates are all lower than 11%under five circulation types.The PM_2.5 contribution rates of the Yangtze River Delta and the outside regions are basically the same except for Jiangsu when under the first and second types of weather conditions and Shanghai when under the second pattern.?4?Five weather conditions show different characteristics and dominant wind direction is closely related with the spatial distribution of PM_2.5 under each pattern type.Shanghai anthropogenic emissions contribute over 15?g/m³ PM_2.5 to itself and the contributions of Shanghai to Jiangsu and Zhejiang are both lower than 25?g/m³.The emissions from Zhejiang province mainly influence northern Zhejiang and the junction of the three provinces and city with PM_2.5 concentration greater than 35?g/m³.Emissions from Jiangsu have a greater impact on itself and its neighboring province Anhui and contribute more than 35?g/m³ of PM_2.5 concentration in most parts of Jiangsu while PM_2.5 growth in areas of southern Jiangsu is over 55?g/m³,and PM_2.5 in Shanghai and Zhejiang increase less than 25?g/m³.The northwest to northeast wind is the main wind directions under the first and second weather conditions,and the area influenced by emissions from the Yangtze River Delta with PM_2.5.5 increased over 75?g/m³ is relatively small.Meanwhile,the prevailing east and southwest wind under the third and fifth weather types lead to a worse PM_2.5 pollution in the north part of Yangtze River Delta,Jiangsu as an example.Dominated by the northeast wind direction,the anthropogenic emissions are more likely to spread to the southwest even most of southern China under the fourth weather pattern.