Effects Of Changes In Emissions And Meteorological Conditions On Ambient Fine Particulate Levels At City Scale

In recent years,with the promulgation and implementation of national policies such as "The 12th Five-Year Period Plan(12th FYP)" and "National Ten Measures to Prevent and Control Air Pollution",the concentration of particulate matter based on the observation in Chinese cities showed a downward trend.As an important city located in the Yangtze River Economic Belt,Nanjing has been taking great efforts to control the emissions from large pollutant sources.As air quality can be affected both by meteorological conditions and emissions,differentiation and quantification of their contribution is thus important both for confirming the benefits of emission control and for further policy making of air quality improvement.Based on the Environmental Statistics,Pollution Source Census and field survey on local large emitters,we establish a comprehensive database of pollution sources in Nanjing.Moreover,the bottom-up air pollution inventories of Nanjing from 2012 to 2016 are established using emission-factor method in this study.The results revealed that the total emissions of SO2,NO2,PM2.5,BC(Black carbon),OC(Organic carbon),CO and NH3 had decreased 70%,22%,64%,65%,72%,86%and 49%,respectively while moderate growth was found for VOCs(Volatile organic compounds).By comparing Nanjing emission inventories and satellite observation data of summer tropospheric NO2 vertical column density(VCD)derived from Ozone Monitoring Instrument(OMI),we found that the inter-annual variabilities of NO2 emissions and NO2 VCD were consistent with each other.The result indicates that emission inventory of NO2 from 2012 to 2016 was reliable.The data from nine state control observation site in Nanjing are used to evaluate the results from Air quality modeling system,Models-3/Community Multi-scale Air Quality(CMAQ).The normalized mean bias(NMB)and the normalized mean errors(NME)of SO2,NO2 and PM2.5 with important chemical species between ground-based observation and simulations with Nanjing emission inventory were effectively controlled within-50%to 50%.The comparison thus implied the satisfying model performance and thereby reliability of emission inventory.To assess the effect of emissions and meteorological conditions on the interannual variation of PM2.5 in Nanjing,we perform several simulations:VALL is a simulation of PM2.5 with variations in both meteorological parameters and anthropogenic emssions;VMET is a simulation to quantify the impact of variations in meteorological parameters alone;and VEMIS is a simulation to quantify the impact of variations in anthropogenic emssions.The results indicate that from 2012 to 2015,the emission abatement in January,April,July and October could reduce PM2.5 concentration by 15%,14%,3%and 10%respectively if meteorogology was unchanged.Meteorological conditions of April,July and October have adverse effect on PM2.5:If emissions are fixed at 2012 level,the concentration of PM2.5 would increase 2%,17%and 17%respectively.From 2012 to 2016,emission reduction helped decreasing PM2.5 concentration.If meteorological parameters are fixed,the concentration of PM2.5 would decrease 16%,26%,4%and 18%in January,April,July and October respectively.If emission sources are fixed,meteorological conditions would led to 21%and 37%reduction in PM2.5 concentration in January and October respectively.The results revealed that emission reduction in the 12th FYP is beneficial to PM2.5 concentration reduction.The inter-annual variations of PM2 5 concentration from 2012 to 2016 are quantified by mean absolute deviation(MAD)and absolute percent departure from the mean(APDM).Comparing with the other seasons,the MAD and APDM in October were the largest at 1.72ug/m3 and 36.72%in VALL simulation,respectively.Sensitivity simulations show that the interannual variations in PM2.5 concentration are dominated by variations in meteorological parameters in January,July and October.To understand the impact of meteorological variability on spatial distribution of surface PM2.5 and correlations with meteorological variables,we compare the 2012 and 2016 years.The results indicate that decrease in sea level pressure surpresses increase of PM2.5 in January with a correlation coefficient of-0.51;sea level pressure and precipitation water have negative contribution to PM2.5 concentration with a correlation coefficient of-0.53 and-0.35 in April respectively;and precipitation water plays an important role in decrease of PM2.5 in July,with a correlation coefficient of-0.60.In October,temperature,sea level pressure,precipitation water and wind speed had negative contribution on PM2.5 concentration with correlation coefficients of-0.35,-0.43,-0.42 and-0.45.In general,model sensitivity simulations indicated that five years trends of surface concentrations of PM2.5 were mainly driven by changes in emissions,while the interannual variations depended largely on variations of meteorological parameters.Furthermore,Precipitation and wind speed account for more contributions than other meteorological parameters to the change of the concentration of PM2.5.