Abstract
Organic aerosol (OA) makes up a substantial fraction of atmospheric particulate matter that exerts tremendous impacts on air quality, climate, and human health. Yet current chemical transport models fail to reproduce both the concentrations and temporal variations of OA, especially the secondary organic aerosol (SOA), hindering the identification of major contribution sources. One possibility is that precursors that are not yet included in the model exist, and intermediate-volatility and semi-volatile organic compounds (I/SVOCs) are advocated to be one of them. Herein, we established a high-resolution emission inventory of I/SVOCs and by incorporating it into the CMAQ model, concentrations, temporal variations, and spatial distributions of POA and SOA originated from different sources in the Yangtze River Delta (YRD) region of China were successfully simulated. Compared with the comprehensive observation data obtained in the region, i.e., volatile organic compounds (VOCs), organic carbon (OC), primary organic aerosol (POA) and SOA, significant model improvements in the simulations of different OA components were demonstrated. Furthermore, spatial and seasonal variations of different source contributions to OA production were identified. We found cooking emissions are predominant sources of POA in the densely populated urban area of the region. I/SVOC emissions from industrial sources are dominant contributors to the SOA formation, followed by those from mobile sources. While the former concentrated in eastern, central, and northern YRD, the latter mainly focused on the urban area. Our results indicate that future control measures should be specifically tailored on intraregional scale based on the different source characteristics to achieve the national goal of continuous improvement in air quality. In addition, local source profiles and emission factors of I/SVOCs as well as SOA formation mechanisms in model framework are urgently needed to be updated to further improve the model performance and thus the accuracy of source identifications.
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