Impacts Of Intermediate Volatile Organic Compounds(IVOC) Emission And 1.5D-VBS Mechanism On The Formation Simulation Of Secondary Organic Aerosol Over The Yangtze River Delta Region

Secondary organic aerosol（SOA）is an important component of fine particulate matter(PM_2.5)with significant impacts on air quality,climate change and human health.However,due to the absence of precursor emission inventory and uncertainties in the modeling scheme,SOA is usually underestimated compared to observations.Therefore,the objective of this study was to quantify the impact of intermediate volatile organic compounds（IVOC）emissions and the 1.5D-VBS mechanism on simulated SOA over the Yangtze River Delta（YRD）region of China using an integrated meteorology and air quality model（WRF-CAMx）.IVOC is reported to be one of the key precursors of SOA but was not considered in the modeling of SOA over the YRD region.In this study,IVOC emission inventory with high spatial and temporal resolution was first developed for the YRD region based on two methods（i.e.,the emission factor method and the emission ratio method of IVOC to primary organic aerosol,POA）.Secondly,the impacts of IVOC emissions and 1.5D-VBS mechanism on the simulation of SOA over the YRD region were investigated,respectively.Finally,source apportionment of SOA in the YRD region was simulated.IVOC emissions from vehicles and their corresponding SOA formation potential based on two methods both exhibit substantial differences.Based on the IVOC/POA coefficient method,the total amount of IVOC emissions are estimated to be 730 Gg with on-road and industry sectors being the main contributors（36.1%and 21.4%,respectively）.The total IVOC emissions estimated by the emission factor method are333 Gg,which is about half of the first method,with industry and off-road sectors being the major contributors,accounting for 46.9%and 22.4%,respectively.In the base scenario,the simulated SOA concentration for July 2018 based on the default emission inventories（no IVOC emission inventory）and the default modeling scheme（Secondary Organic Aerosol Processor,SOAP）significantly underestimated observed SOA concentration by 61%at the Dianshan Lake monitoring site（DSL）.After adding the IVOC emissions,simulated SOA concentration increased by 7.9%～26.8%,8.2%～27.6%,5.2%～26.2%at DSL,Shanghai,and the YRD region,respectively.Increasing the SOA mass yields from IVOC by a factor of five leads to better agreement with observations with average simulated SOA concentration increased by 135.8%at the DSL site;simulated SOA concentrations in Shanghai and over the YRD region both increased significantly.The 1.5D-VBS approach increases simulated SOA concentration by 76%at DSL compared to the base scenario（default SOAP scheme and yields）,and the simulated SOA concentrations in Shanghai and YRD region increased by 89.7%and 41.9%,respectively.In addition,with the 1.5D-VBS scheme,the simulated SOA concentrations were nearly 2 times better than the base scenario in spring,autumn and winter.These results show that both IVOC emission and 1.5D-VBS scheme can greatly enhance the SOA formation.Considering that the VBS scheme has not been applied with source apportionment,PSAT with the default scheme（i.e.SOAP）was used to simulate the source apportionment of SOA over the YRD region in 2018,which is evaluated against the results obtained using a Brute Force method based on 1.5D-VBS scheme.Evaluation results between the two methods showed good agreements.The results of SOA regional source apportionment show that Anhui,Jiangsu and Zhejiang provinces are the main contributors of SOA in the YRD region.In spring and summer,Zhejiang province contributed 20.3%and 28.4%to SOA concentration,respectively.In autumn and winter,the contribution from Jiangsu province was 28.2%and 26.1%respectively.Industrial source emissions contribute most to SOA concentration in the YRD region in spring and winter with contribution rates of 55.5%and 65.8%,respectively,while the contribution of natural source is higher during the summer with contribution of 36.1%.In autumn,the main contribution sources were solvent use sources and industrial sources,with contribution of 40.1%and 34.8%,respectively.The results of source apportionment in national monitors in Shanghai show that the contribution of natural sources at the background site（DSL）is higher than those at other stations in summer,and the contribution of local sources at all stations show negligible differences.The results in Hefei,Nanjing and Hangzhou showed that industrial sources contributed more in spring and winter,while solvent use sources and industrial sources contributed more in summer and autumn.