Satellite-based Analysis of CO2 Emissions in Global Cities: Regional, Economic, and Demographic Attributes

Cities play a crucial role in reducing global greenhouse gas emissions. While activity-based 26 (“bottom up”) emission estimates are widely used for global cities, they often lack independent 27 verification. In this study, we use remotely-sensed CO2 observations from the Orbiting Carbon 28 Observatory-3 (OCO-3) to “top-down” estimate CO2 emissions for 54 global cities. This global29 scale analysis is enabled by a computationally efficient, low latency Cross-Sectional Flux (CSF) 30 approach, which constrains urban plume shape using NO2 observations from TROPOMI and 31 trajectory simulations from HYSPLIT. Our satellite-based emission estimates for 54 global cities 32 agrees within 7% to two widely used bottom-up datasets but reveal regional discrepancies. 33 Bottom-up estimates tend to overestimate emissions for cities in Central East Asia and South and 34 West Asia, while underestimating emissions in Africa, East and Southeast Asia & Oceania, 35 Europe, and North America. Additionally, our satellite-based socioeconomic analysis shows that 36 1) high-income cities tend to have less carbon-intensive economies: North American cities emit 37 0.1 kg CO2 per USD of economic output, while African cities emit 0.5 kg CO2 per USD, and 2) 38 per capita emissions decrease with increasing population size, from 7.7 tCO2/person for cities manuscript submitted to AGU Advances 39 under 5 million residents to 1.8 tCO2/person for cities over 20 million residents. This study 40 highlights the potential of satellite data to bridge gaps between top-down and bottom-up 41 emission estimates, enhancing the robustness and transparency of emissions monitoring. Our 42 findings emphasize the growing role of satellite data in verifying urban CO2 emissions and 43 supporting efforts to mitigate emissions for global cities.