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 1 km 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 1.62 ppm with an annual decline rate of 2.92 ppm. 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 1.46 ppm and keeps rising, indicating Beijing is still on its way to carbon peaking and needs to strive for carbon neutrality.