High resolution residential emission inventory and relationships between urban residential emissions and incomes in megacity Zhengzhou, China.

Residential emissions significantly affect indoor air quality and human health; a high-resolution emissions inventory of air pollutants is necessary for conducting accurate exposure assessments and developing effective mitigation strategies. In this study, an income-stratified residential emission inventory was constructed for Zhengzhou, a megacity in China. In 2019, the total emissions from urban residences in Zhengzhou were as follows (in tons): nitrogen oxides (NOx, 1039.5), sulphur dioxide (SO2, 861.3), carbon monoxide (CO, 2661.7), ammonia (NH3, 200.7), particulate matter with diameter ≤10 μm (PM10, 1177.7), particulate matter with diameter ≤2.5 μm (PM2.5, 817.4), black carbon (BC, 148.5), organic carbon (OC, 466.0), and volatile organic compounds (VOCs, 4050.4). Solvent usage was the primary contributor of VOCs (95 %), Cooking contributed more than 57 % to the PM2.5, PM10, and OC emissions. Coal combustion accounted for over 87 % of the SO2, CO, and BC emissions, pipeline natural gas (PNG) combustion contributed over 80 % of the NO2 and NH3 emissions. Spatially, combustion-related species were mainly concentrated at the borders of counties and districts; additionally, we noted income-driven disparities in the concentrations of these pollutants. Over 50 % of the SO2, CO, and BC emissions were from low-income residents, and more than 30 % of the total NOx, NH3, and VOCs emissions were from high-income residential. The distributions of the NOx, NH3, and VOCs emissions corresponded to the spatial distribution of high-income urban residents, which were concentrated to the downtown area. Notably, the income level of the urban residences was inversely proportional to their proximity the city centre. Overall, this study presents an emission allocation method based on the residential income level. The proposed method can be used to enhance the accuracy and accessibility of residential emission inventory and facilitate the identification of grid-level emission characteristics.