Gridded Emission Inventory Establishment And Simulation Prediction Of Regional Atmospheric Polycyclic Aromatic Hydrocarbons

Polycyclic aromatic hydrocarbons(PAHs)have "carcinogenic,teratogenic,mutagenic" effects and can enter the surrounding environment through environmental processes.With the huge increase in energy consumption,China’s atmospheric PAHs emissions have ranked first in the world.The establishment of gridded PAH emission inventory is of great significance for the pollution control and the improvement of the PAHs simulation accuracy of the atmospheric transport model.The emission inventory and simulation prediction of atmospheric PAHs have become a research hotspot in the field of environmental science.Previous studies have focused on the investigation and analysis of atmospheric PAHs based on sample data in a given year and the transformation of atmospheric PAHs at the urban scale,which have a relatively low space-time resolution.It cannot accurately characterize the transport of atmospheric PAHs.Yangtze River Delta region(YRD)is one of the most developed urban agglomerations in China,and its energy consumption has increased by 4.6 times since 2001,much higher than other areas of China,causing widespread pollution of atmospheric PAHs.The long-term spatial and temporal simulation of atmospheric PAHs in the YRD region has important guiding significance for achieving accurate pollution control and regional ecological sustainable development.Based on the improved PAHs emission inventories,this study systematically simulated the atmospheric PAHs using atmospheric transport model in the YRD in 2001-2016,and clarified the spatio-temporal differences of atmospheric PAHs and their lung cancer risk.Firstly,using POI big data and nighttime light data,the spatial allocation method for industrial PAHs source has been improved in the PAHs emission inventory(the key input of the atmospheric transport model),and respectively established two PAHs emission inventories in China mainland in 2016 and in YRD region from 2001 to 2016.Based on the above emission inventories and the PKU-PAH inventoy,the daily BaP(the most carcinogen species in 16 PAHs)concentrations in the YRD were simulated using atmospheric transport model.The interannual variation,spatial-temporal difference of atmospheric BaP concentration were revealed.A oneyear atmospheric PAHs monitoring was carried out in the typical area of the YRD where atmospheric PAHs was seriously polluted.The simulation results of the atmospheric transport model were verified using monitoring data.Then,the atmospheric BaP in 2030 were predicted based on the different scenarios.Combined with lung cancer risk assessment model,the spatio-temporal differences of lung cancer risk in the Yangtze River Delta from 2001 to 2016 were discussed.And the change of lung cancer risks under different scenarios in 2030 were simulated.Finally,the policy recommendations for the YRD region were proposed.The main conclusions of the study are as follows:(1)Using the POI big data can significantly improve the spatial allocation accuracy of industrial sources in the PAHs emission inventory.The PAHs emissions in mainland China are significantly different.Baidu POI data and official industrial energy consumption were applied to allocate industrial energy consumptions in mainland China(DPOI method).The industrial enterprise POI data fits well with the number of industrial enterprises above designated size(R2=0.72)and the number of Google Earth POI(city-scale:R2=0.82,county-scale R2=0.63),which indicated that the POI big data had high precision.The DPOI method was validated at the city scale and in the city by collecting 107 city statistical yearbooks and 136 county statistical yearbooks.It can be found that DPOI is obviously superior to other traditional spatial allocation methods.RMSE is the lowest.The gridded PAHs emission inventory in 2016 in mainland China was established based on the different spatial allocation methods(DPOI and other allocation proxies)and provincial PAHs emissions.PAHs emissions were 107.4 Gg in mainland China.The domestic/commercial sector(49.4%)and industrial sources(28.8%)were the largest sources of emissions.The proportion of carcinogenic PAHs(7.5%)was higher than that of developed countries(5.73%),which indicated that higher cancer risk can be occurred in China under same PAHs emissions.The difference in energy structure has led to huge differences in PAHs emissions in various sectors.The domestic/commercial sector in some regions like the northeast region has greater emission intensity.The areas with large emissions of the industrial and transportation sectors are concentrated in developed areas such as the Tianjin-Hebei,the Pearl River Delta and the Yangtze River Delta.The overall PAHs emissions in mainland China are generally higher in the east,lower in the west,and higher in the north and lower in the south.(2)Using nighttime light data significantly improved the spatial allocation accuracy of industrial sources in PAHs emission inventory under long-term trends.The PAHs emissions in the Yangtze River Delta(YRD)region is gradually reduced,and the reduction of biomass burning is the main influence factor.The spatial allocation of industrial PAHs emission were optimized using two kinds of nighttime light data(DMSP and NPP-VIIRS).The predicted gridded GDP23 using the corrected nighttime light data were used to allocate the industrial sources in Yangtze River Delta during 2001-2016,which largely increased the comparability of spatial allocation proxies in different years.The industrial PAHs emissions calculated by using official energy consumption were used to vertify the accuracy of various spatial distribution methods.It can be found that the predicted gridded GDP23 using the corrected NPP-VIIRS(GDP23-NPP-VIIRS)had the highest precision(RMSE=39.7),which was nearly doubled compared to the population proxies.In 2001-2016,the PAHs emissions gradually decreased(2001:5445 t,2016:2390 t).Indoor biomass burning contributed the most to the decline of PAHs emissions.The industrial PAHs emissions showed a trend of rising first and then decreasing,but the proportion keeped increasing.From 2001 to 2016,the high-emission areas of Jiangsu PAHs have gradually shifted from the northern Jiangsu region to southern Jiangsu,while the high-emission regions in Zhejiang have remained in the northeastern region of Zhejiang.The PAHs emissions in most of the urban areas in the YRD region began to reduce after 2010.(3)The atmospheric transport model simulation showed that the atmospheric BaP concentration of the YRD increased first and then decreased during 2001-2016.The atmospheric BaP pollution in Jiangsu Province was the most serious.The model results and measured data are well verified.Atmospheric BaP concentration peaked at 0.72 ng/m3 in 2005.The average yearly BaP concentrations in Jiangsu,Shanghai,and Zhejiang were 0.84 ng/m3,0.81 ng/m3,and 0.16 ng/m3,respectively.During 2001-2005,the increase of the biomass burning caused an increase of the BaP concentration in the Northern Jiangsu.The BaP concentration increased rapidly with the increase of industrial energy consumption in southern Jiangsu.After 2005,the concentration of each region declined overall.There are certain areas exceeding the standard in all years.In 2005,the proportion of over-standard areas was as high as 30.4%.Jiangsu captured the largest proportion of BaP over-standard areas.The atmospheric BaP concentration was the largest in winter(1.01 ng/m3)and the smallest in summer(0.23 ng/m3)in YRD.The average over-standard areas proportion in Jiangsu winter was as high as 69.09%,and it is urgent to control BaP pollution.A one-year atmospheric PAHs monitoring(June 2017 to June 2018)was carried out in the typical area of the YRD where atmospheric PAHs were seriously polluted.The average concentration of PAHs in this region was 41.46 ng/m3.The PAHs concentrations in Jiangsu(44.47 ng/m3)was higher than that in Zhejiang(36.04 ng/m3)and Shanghai(36.62 ng/m3).There are highest in winter(52.21 ng/m3),and lowest in summer(31.23 ng/m3).The simulated BaP concentrations was verified by combining the above monitoring data and the literature data.It can be found that there was a significant correlation between them(R2=0.45,P<0.01).It can be indicated that the PAHs emission inventories and the atmospheric transport model have high accuracy.(4)The BaP concentrations under different scenarios in 2030 have a huge difference.Long-term potential risk of lung cancer existed in the YRD region during 2001-2016.The BaP concentration and lung cancer risk could be reduced by reducing the key pollution sources and improving the technological level.The BaP concentration under scenario I(according to current energy consumption trends)to scenario V(improving technology levels and reducing emissions)are reduced in turn.The BaP concentration in scenario I increased by 30.1%compared with 2016.The BaP concentration in Jiangsu is sensitive to different scenarios.The population-weighted lung cancer risk(PILCR)during 2001-2016 was between 6.67×10-6 and 1.50×10-5,which represents the YRD always had the potential lung cancer risk.In 2005,the high lung cancer risk areas were mainly distributed in parts of northwestern and southern Jiangsu and Shanghai.In 2016,the lung cancer risk decreased,and the northwestern part of Jiangsu became the region with the largest decline.The number of patients with additional lung cancer risk in YRD also increased first and then decreased during 20012016.The annual patients of Shanghai was 1.56 times higher than that of Zhejiang.The numbers of patients in Jiangsu was highest.The seasonal difference of PILCR is winter>autumn>spring>summer.The PILCR of all seasons in 2005 exceeded the acceptable range,and significantly reduced in 2016,but it still needs to pay more attention in autumn and winter.The patients of winter in 2005 and 2016 accounts for 47.61%and 46.90%of the whole year.The risk of lung cancer caused by BaP in winter of Jiangsu is urgently needs attention.The lung cancer risk simulation under different scenarios in 2030 implied that higher population density increased lung cancer risk.The contribution of emission reduction to the decline of lung cancer risk is higher than the improvement of the technological level.The combination of emission reduction and technological improvement can effectively decrease the atmospheric BaP concentrations and lung cancer risk.