Carbon dioxide and methane are the two most important greenhouse gases and are closely related to global warming and extreme weather events. To master their spatial and temporal variations, the CO₂ and CH₄ concentration data monitored by the GOSAT satellite in 2020 and 2021 were used to map and analyse the annual, seasonal and monthly changes in CO₂ and CH₄ concentrations in the world and major countries/regions. The results demonstrate that (1) in 2021, the average annual CO₂ concentration over the global land area was 412.74 ppm, an increase in 0.64% compared with the same period last year, and there were spatial differences in the distribution of CO₂ concentration, with high values mostly concentrated in the middle latitudes of the Northern Hemisphere; (2) compared with 2020, the CO₂ concentration in China, the United States, India, the European Union and other countries/regions increased significantly; (3) in 2020 and 2021, the quarterly CO₂ trend of the global and major countries/regions was the same, which was higher in the first (January, February, March) and second (April, May, June) quarters, significantly lower in the third (July, August, September) quarter, and gradually increased in the fourth (October, November, December) quarter. Further work on long time series and validation needs to be conducted.

In recent years, large-area heavy haze pollution cases occur frequently in eastern China, especially evident in Beijing-Tianjin-Hebei and the surrounding regions. In order to operationally monitor the process of larger regional heavy haze events, a type of quantitative method based on satellite remote sensing and numerical simulations was first established and applied in multiple heavy haze processes in the research area. First, this study proposed the operational haze aerosol optical depth (HOD) method by combining Terra, Aqua satellite and WRF-NAQPM numerical simulation in haze days. Second, based on the coupled HOD data, we proposed the quantitative method for obtaining the process and severity degree for larger regional heavy haze events. Finally, this study used the method applying it to several typical heavy pollution events which occurred in Beijing-Tianjin-Hebei and its three surrounding provinces in the winter season from 1 November 2015 to 4 January 2016. The validation for HOD retrieval results showed that the couple HOD from this study have good accuracy, the linear correlation coefficient between retrieval HOD and the AERONET Beijing station data reached over 0.8, and the linear correlation coefficient between the retrieval HOD and the regional ground monitoring station PM_2.5 data reached over 0.7. The applied results showed that the method in this study is feasible to reflect the whole process of heavy haze events. Analysis of the typical heavy haze pollution events showed that the set of quantitative haze judging method in this study was consistent with the meteorological conditions in haze days also verifying that the method for haze inversion and the process analysis is reliable.