This project aims to explore the model of atmospheric methane sources and sinks in Taiwan. Our work targets include comparative analysis of methane monitoring systems among the world's advanced countries, calibration of methane monitoring data, correlation analysis of methane and other air pollutants, developing methane inverse models with case application, and conducting a seminar. We analyzed the methane monitoring systems of the world's advanced countries and found the global atmospheric monitoring networks mostly focus on greenhouse gases and other important trace gases. The observation sites of these networks mainly distribute around Europe, North America, and the North Atlantic area, while the monitoring frequency and site density are relatively lower in other regions. Taiwan’s Environmental Protection Agency's methane monitoring system is more similar to that of Japan’s Ministry of the Environment, both focusing on air pollutants monitoring. The monitoring results from their high density of observation sites also contribute to the methane monitoring in Asia and the Pacific area. The accuracy of HC analyzers in EPA stations was verified by synchronous measurements of the ambient air using LGR UGGA infrared gas analyzer and the on-site HC system. The results showed a significant discrepancy between the two measurement systems. The extent of differences varied among stations. The on-site dilution system for the production of standard gases may have resulted this problem. We used the optical analyzer to check the zero span mode of the dilution calibrator, and recalculated the methane concentrations according to the corrected calibration parameters. The results showed great improvement in the accuracy of the measurement. We analyzed the correlations between methane and other air pollutants in the EPA's monitoring data over the years. The results showed that the correlations were weak. Atmospheric methane can react with the hydroxyl produced through the photoreaction of ozone in the troposphere, but our analysis of the correlation between the methane and ozone was quite weak. The result suggested that there might be other potential mechanisms at the site scale, such as atmospheric diffusion conditions, emission source characteristics, sampling heights and site positions. We analyzed the back-trajectory patterns and the wind field data of the high methane concentration events in Kaohsiung and Pingtung area. We compared between the back-trajectories and the TEDS emission hotspots, and found that the emission sources centered around the old Kaohsiung city area and the adjacent old Kaohsiung county area. The cause of high methane concentration events may be emissions from point sources with the favorite atmospheric conditions that facilitate the situation. However, the emission intensity of Pingtung Station’s back-trajectory was weak, and we could not identify the emission sources from the TEDS database. Further grid simulation is needed.

Greenhouse Gas, Methane Monitoring System, Inverse Modeling of Methane, Source and Sink