Green and low-carbon are the keywords of the 2022 Beijing Winter Olympic Games (WOG) and the core of sustainable development. Beijing's P M 2.5 and C O 2 emissions attracted worldwide attention during WOG. However, the complex emission sources and frequently changing weather patterns make it impossible for a single monitoring approach to meet the high-resolution, full-coverage monitoring requirements. Therefore, we proposed an active-passive remote sensing fusion method to address this issue. The haze layer height (HLH) was first retrieved from vertical aerosol profiles measured by our high-spectral-resolution lidar located near Olympic venues, which provides new insights into the nonuniform boundary layer and the residual aerosol aloft above it. Second, we developed a bootstrap aggregating (bagging) method that assimilates the lidar-based HLH, satellite-based AOD, and meteorological data to estimate the hourly P M 2.5 with 1km resolution. The P M 2.5 at Beijing region, Bird's Nest, and Yanqing venues during WOG was 23.00±18.33, 22.91±19.48, and 16.33±10.49µg/m 3, respectively. Third, we also derived the C O 2 enhancements, C O 2 spatial gradients resulting from human activities, and annual growth rate (AGR) to estimate the performance of carbon emission management in Beijing. Based on the top-down method, the results showed an average C O 2 enhancement of 1.62ppm with an annual decline rate of 2.92ppm. Finally, we compared the monitoring data with six other international cities. The results demonstrated that Beijing has the largest P M 2.5 annual decline rate of 7.43µg/m 3, while the C O 2 AGR is 1.46ppm and keeps rising, indicating Beijing is still on its way to carbon peaking and needs to strive for carbon neutrality.