High-resolution estimation of urban anthropogenic carbon emissions

• High-resolution anthropogenic CO₂ emission maps were generated using big data. • These maps reveal finer spatial details than the ODIAC product. • Spatial emission patterns are broadly similar between Shenzhen and Shanghai. • Inter-city differences in structure led to varying COVID-19 impacts on emissions. Urban areas are primary sources of anthropogenic carbon emissions, making their detailed spatial distribution crucial for effective mitigation strategies. While previous research has modeled city-level CO₂ emissions through simulations, often at a coarse resolution, high-resolution intra-city variations remain less explored. This study leverages big data to construct high-resolution maps of anthropogenic CO₂ emissions in Shanghai and Shenzhen. We link sector-specific emissions to spatial locations using sector characteristics and aggregate the results into 1 km grids. A comparative analysis spanning 2019–2022 reveals finer spatial detail than existing products like the Open-source Data Inventory for Anthropogenic CO 2 (ODIAC), highlighting significantly higher emissions in city centers. Overall emission trends for both cities show a decrease, followed by an increase, and then another decrease. Furthermore, the impact of the COVID-19 pandemic varied between the two cities: Shenzhen, with its focus on high-tech and emerging industries, experienced a smaller impact compared to Shanghai, which has a larger proportion of traditional manufacturing. The high-resolution emission maps provide valuable insights into emission patterns, contributing to more targeted and effective strategies for energy conservation and sustainable urban development.