资源环境科技发展态势分析平台

Emission datasets of nitrogen oxides (NOx) at high horizontal resolutions (e.g., 0.05 degrees x 0.05 degrees) are crucial for understanding human influences at fine scales, air quality studies, and pollution control. Yet high-resolution emission data are often missing or contain large uncertainties especially for the developing regions. Taking advantage of long-term satellite measurements of nitrogen dioxide (NO2), here we develop a computationally efficient method of estimating NOx emissions in major urban areas at the 0.05 degrees x 0.05 degrees resolution. The top-down inversion method accounts for the nonlinear effects of horizontal transport, chemical loss, and deposition. We construct a two-dimensional Peking University High-resolution Lifetime-Emission-Transport model (PHLET), its adjoint model (PHLET-A), and a satellite conversion matrix approach to relate emissions, lifetimes, simulated NO2, and satellite NO2 data. The inversion method is applied to the summer months of 2012-2015 in the Yangtze River Delta (YRD; 29-34 degrees N, 118-123 degrees E) area, a major polluted region of China, using the NO2 vertical column density data from the Peking University Ozone Monitoring Instrument NO(2 )product (POMINO). A systematic analysis of inversion errors is performed, including using an independent test based on GEOS-Chem simulations. Across the YRD area, the summer average emissions obtained in this work range from 0 to 15.3 kg km(-2) h(-1), and the lifetimes (due to chemical loss and deposition) range from 0.6 to 3.3 h. Our emission dataset reveals fine-scale spatial information related to nighttime light, population density, road network, maritime shipping, and land use (from a Google Earth photo). We further compare our emissions with multiple inventories. Many of the fine-scale emission structures are not well represented or not included in the widely used Multi-scale Emissions Inventory of China (MEIC).