Methane (CH₄) is the second most important greenhouse gas in the atmosphere after carbon dioxide. Mastering precise methods for monitoring atmospheric CH₄ is essential for addressing the greenhouse effect and environmental changes. This helps us better understand and predict climate change and provides policymakers with the data needed to formulate effective emission reduction measures. By accurately monitoring CH₄ variations, we can identify major emission sources and assess the effectiveness of mitigation strategies, thus promoting the achievement of global climate goals.

We use ground-based high-resolution Fourier transform infrared (FTIR) spectroscopy to collect near-infrared solar absorption spectra. These spectra are then analyzed using a nonlinear least squares fitting algorithm to retrieve the column concentrations of atmospheric CH₄ in Hefei from 2018 to 2022. Our algorithm, GFIT, is the standard retrieval method of the Total Carbon Column Observing Network (TCCON), consisting of a forward model and iterative fitting process. The forward model calculates atmospheric absorption spectra through an atmospheric radiative transfer model, combining solar parameters, atmospheric parameters, and instrument line shape parameters to generate solar absorption spectra. The iterative process then compares calculated and measured spectra, adjusting retrieval parameters to achieve the best fit. Next, we process the atmospheric CH₄ concentration data monitored by FTIR spectroscopy to determine the annual growth rate of atmospheric CH₄ and study its seasonal variations. We then validate the ground-based FTIR CH₄ data against the TROPOspheric Monitoring Instrument (TROPOMI) satellite data. Finally, by calculating the incremental values of CH₄ and carbon monoxide (CO) relative to their background values (${\Delta }_{\mathrm{C}{\mathrm{H}}_{\mathrm{4}}}$ and ${\Delta }_{\mathrm{C}\mathrm{O}}$), we analyze the sources of atmospheric CH₄ in Hefei, examining the seasonal correlations between ${\Delta }_{\mathrm{C}{\mathrm{H}}_{\mathrm{4}}}$ and ${\Delta }_{\mathrm{C}\mathrm{O}}$.

Our study first uses FTIR spectroscopy to investigate the variation characteristics of atmospheric CH₄ in Hefei from 2018 to 2022, as shown in Figs. 2, 3, and 4. The results show an annual increase in atmospheric $X_{\mathrm{C}{\mathrm{H}}_{\mathrm{4}}}$ in Hefei with seasonal variations, peaking in autumn and decreasing to its lowest in spring (March to April) of the following year. Second, we use ground-based CH₄ data to validate TROPOMI satellite observations in Hefei, revealing good consistency between datasets, as shown in Figs. 5 and 6. The average absolute deviation between the two datasets is 5×10^-9, with an average relative deviation of 0.26%, indicating a slight overestimation of CH₄ column concentration by TROPOMI. Additionally, the correlation coefficient between satellite and ground-based data is 0.91, confirming TROPOMI’s high reliability in monitoring atmospheric CH₄. Finally, we analyze the correlation between atmospheric CH₄ and CO in Hefei to infer CH₄ sources. As CO primarily originates from human activities, its correlation with CH₄ can indicate the main sources of CH₄. A high correlation coefficient would suggest CH₄ is mainly anthropogenic, while a low correlation would suggest natural sources as the primary contributor, as shown in Fig. 7.

Atmospheric CH₄ column concentrations in Hefei show a slow annual increase, with an approximate growth rate of 0.73%. The atmospheric CH₄ column concentrations are lower in spring and winter, and higher in summer and autumn. Monthly averages peak in September and reach their lowest in March, at 1940×10^-9 and 1890×10^-9, respectively, with a seasonal variation amplitude of 50×10^-9. Subsequently, we compare satellite data from the TROPOMI onboard the ESA Sentinel-5P satellite with ground-based FTIR data. The results demonstrate strong consistency between the two datasets, with an average absolute deviation of 5×10^-9 and a correlation coefficient of 0.91. Finally, we conducted a correlation analysis between atmospheric CH₄ and CO observed in Hefei, calculating the correlations of ${\Delta }_{\mathrm{C}{\mathrm{H}}_{\mathrm{4}}}$and ${\Delta }_{\mathrm{C}\mathrm{O}}$ across four seasons over the five-year observation period from 2018 to 2022. The analysis shows a poor correlation between these gases in all seasons, suggesting that natural emissions are the primary source of atmospheric CH₄ in Hefei. These findings provide effective methods for monitoring greenhouse gases in Hefei, particularly CH₄, and offer valuable data support for the formulation and implementation of scientifically grounded environmental protection policies and emission reduction measures.