High-resolution (0.05°×0.05°) NOx emissions in the Yangtze River Delta inferred from OMI

Emission datasets of nitrogen oxides ( NO x ) at high horizontal resolutions (e.g., 0.05 ∘ × 0.05 ∘ ) 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 ( NO 2 ), here we develop a computationally efficient method of estimating NO x emissions in major urban areas at the 0.05 ∘ × 0.05 ∘ 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 NO 2, and satellite NO 2 data. The inversion method is applied to the summer months of 2012–2015 in the Yangtze River Delta (YRD; 29–34 ∘  N, 118–123 ∘  E) area, a major polluted region of China, using the NO 2 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).