Estimation of Emission Inventory with High-Resolution of Anthropogenic PM2.5 in Wuhan Metropolitan Area from 2017 to 2023 and Its Spatial-Temporal Evolution
Chen Deliang
Wu Jian
Kong Shaofei
Dong Haoyu
Jiang Weisi
Qi Shihua
Abstract：The lack of high spatio-temporal resolution emission inventories for atmospheric fine particulate matter(PM2.5)in the Wuhan metropolitan area limits the accurate simulation and control of regional PM2.5 pollution.In this study,the emission factor method was adopted,integrating point of interest data from Amap as well as relevant allocation indices including population,road network and land use type,etc.,to construct a high-spatial-resolution(1 km×1 km)emission inventory of anthropogenic PM2.5 emissions in the region from 2017 to 2023.Its uncertainty was evaluated,and its temporal and spatial evolution patterns were revealed.Results show that the total PM2.5 emissions peaked in 2018 at 164.59 kt,dropped to 137.15 kt in 2020 due to the pandemic,and rebounded to 149.97 kt in 2023.The uncertainty of PM2.5 emissions from various source categories ranged from-31.7％to 42.2％,fossil fuel combustion sources(-13.2％to 35.8％)and process sources(-15.2％to 34.3％)have high uncertainty,while dust sources have the lowest uncertainty(-8.2％to 15.4％).Industrial and dust sources were the main contributors,accounting for 46.5％-52.6％and 26.7％-31.8％of total PM2.5 emissions,respectively.The emission intensity of PM2.5 in urban central area was 600-800 t/km2,which was 40-50 times that in suburban and rural areas.This study can provide reliable high-precision emission inventory data support for improving the accuracy of atmospheric chemistry numerical simulations.
Keywords：Wuhan metropolitan areafine particulate matteremission inventoryhigh resolutionspatial-temporal evolutionatmospheric chemistryair pollution
Publication Date：2025-09-30
Online Publishing Date：2025-10-15(First online date of this platform, not the publication date of the document)
Pages：18( 3488-3505 )