The newest emission inventory of anthropogenic full-volatility organic in Central China

Organic aerosol (OA) is the largest and most complicated component of aerosols that has significant impacts on human health and global climate. However, current models cannot accurately predict the concentrations and sources of primary and secondary OA due to the oversimplification of traditional organic emission inventories. Traditional emission inventories do not consider important precursors of secondary organic aerosols (SOA), such as semi -volatile and intermediate -volatility organic compounds (SVOCs and IVOCs). To improve the accuracy of OA prediction and source identification, it is essential to refine precursor emissions. In this study, a full -volatility organic compounds emission inventory was established for the Central China, with Henan Province as a representative in 2020. The anthropogenic emissions of ultralow volatility organic compounds (xLVOCs), SVOCs, IVOCs, and VOCs were 53.9 kt, 55.3 kt, 182.1 kt, and 586.3 kt, respectively, effectively filling the gap of 181.3 kt in traditional organic compound emission inventory. Residential biomass burning was identified as the primary contribution source for xLVOCs and SVOCs, accounting for 70.1% and 42.2%, respectively. Industrial process was the main contributor for IVOCs and VOCs, accounting for 31.7% and 44.0% of their emissions, respectively. Meanwhile, the emission of volatile organic compound from different sources showed an increasing trend as volatility increased. The gas -phase emission was 212.1 kt, primarily from industrial process (33.9% contribution), while the particle -phase emission was 79.2 kt, mainly from domestic biomass combustion (65.0% contribution). xLVOCs and SVOCs emissions were mainly concentrated in cities with agricultural activities, such as Zhoukou, while IVOCs and VOCs were concentrated in highly industrialized and urbanized areas, such as Zhengzhou. It is hoped that the incompleteness of emission factors (EFs) for full -volatility organic compounds, which mainly contributes to the uncertainty of this study's results, can be further improved to better understand source contributions.