Cities are central to global climate change mitigation efforts due to their substantial carbon emissions. Effective, evidence-based climate policy requires a detailed understanding of urban carbon metabolism, allowing for targeted mitigation pathways and the accurate evaluation of sustainability. However, a persistent lack of clarity on how carbon flows are distributed spatially and sectorally within cities has hindered tailored climate action, particularly in rapidly developing megacities. Here we map the shifting landscape of carbon emissions in Chinese megacities and show that accountability for these emissions has undergone a profound spatial and sectoral transformation. We found that the primary burden of emission responsibility has moved from production-focused sectors, such as industry and energy generation, to consumption-based end-users, including residential and commercial buildings. This transition is driven by a structural shift in accounting boundaries from direct fossil fuel combustion (Scope 1) to indirect emissions from electricity consumption (Scope 2), fundamentally redistributing carbon liability across urban districts. Our landscape-level framework reveals the hidden carbon dependencies of end-use sectors and provides a model for equitable and effective accounting, enabling the design of region-specific strategies to address the complexities of urban carbon emissions.

Retrievals of satellite-observed emissions of atmospheric pollutants and greenhouse gases provide essential information and data for understanding the sources of these key atmospheric compositions and for implementing precise emission control measures. Over the past two decades, significant progress has been made in the field of emission inversion, with Chinese researchers playing a substantial role. In celebration of the 100th anniversary of the Chinese Meteorological Society and Acta Meteorologica Sinica, this paper systematically reviews the advances in satellite-based emission inversion research by Chinese scientists during this period. (1) Several widely used inversion methodologies, including data assimilation, local mass balance, Gaussian models, two-dimensional (2D) models, and machine learning, are briefly summarized. (2) Emission inversion studies focusing on major atmospheric pollutants— such as nitrogen oxides (NO_x), ammonia (NH₃), formaldehyde (HCHO), glyoxal (CHOCHO), sulfur dioxide (SO₂), and carbon monoxide (CO)—as well as greenhouse gases like carbon dioxide (CO₂) and methane (CH₄), are systematically elaborated. (3) Finally, the historical evolution of inversion methods and target species, challenges in current satellite-based emission inversion, and future research directions are discussed to promote more accurate quantification of atmospheric pollutants and greenhouse gas emissions. It is worth noting that contributions from Chinese researchers have provided critical scientific support to environmental protection and carbon neutrality efforts in China.

Nitrogen oxides (NO_x), significant contributors to air pollution and climate change, form aerosols and ozone in the atmosphere. Accurate, timely, and transparent information on NO_x emissions is essential for decision-making to mitigate both haze and ozone pollution. However, a comprehensive understanding of the trends and drivers behind anthropogenic NO_x emissions from China—the world's largest emitter—has been lacking since 2020 due to delays in emissions reporting. Here we show a consistent decline in China's NO_x emissions from 2020 to 2022, despite increased fossil fuel consumption, utilizing satellite observations as constraints for NOemission estimates through atmospheric inversion. This reduction is corroborated by data from two independent spaceborne instruments: the TROPOspheric Monitoring Instrument (TROPOMI) and the Ozone Monitoring Instrument (OMI). Notably, a reduction in transport emissions, largely due to the COVID-19 lockdowns, slightly decreased China's NO_x emissions in 2020. In subsequent years, 2021 and 2022, reductions in NO_x emissions were driven by the industry and transport sectors, influenced by stringent air pollution controls. The satellite-based inversion system developed in this study represents a significant advancement in the real-time monitoring of regional air pollution emissions from space.

Wastewater treatment is an important source of greenhouse gases (GHGs). Yet large uncertainties remain in the quantification of GHG emissions from municipal wastewater treatment plants (MWWTPs) in China. A high-resolution and technology-specific emission inventory is still lacking to support mitigation strategies of MWWTPs. Here we develop a plant-level and technology-based MWWTP emission inventory for China covering 8703 plants and 19 treatment technology categories by compiling and harmonizing the most up-to-date facility-level databases. China's methane (CH₄) and nitrous oxide (N₂O) emissions from MWWTPs in 2020 are estimated to be 150.6 Gg and 22.0 Gg, respectively, with the uncertainty range of −30% to 37% and −30% to 26% at 95% confidence interval. We find an emission inequality across cities, with the richest cities emitting two times more CH₄ and N₂O per capita from municipal wastewater treatment than the poorest cities. The emitted CH₄ and N₂O are dominated by Anaerobic/Anoxic/Oxic-, Sequencing Batch Reactor-, Oxidation Ditch-, and Anoxic/Oxic-based MWWTPs of less than 20 years old. Considering the relatively young age structure of China's MWWTPs, the committed emissions highlight the importance of reducing on-site GHG emissions by optimization of operating conditions and innovation management. The emission differences among our estimates, previous studies, and the Intergovernmental Panel on Climate Change guidelines are largely attributed to the uncertainties in emission factors, implying the urgent need for more plant-integrated measurements to improve the accuracy of emission accounting.