Methane is a significant greenhouse gas (GHG), and it is imperative to understand its spatiotemporal distribution and primary sources in areas with higher methane concentrations, as such insights are essential for informing effective mitigation policies. In this study, we employed TROPOMI satellite retrievals to analyze the spatiotemporal patterns of methane distributions and identify major emission sources in South Korea over the period from August 2018 to July 2019. Additionally, we examined the spatial correlations between satellite methane retrievals and emission sources to characterize regions with higher methane levels on an annual basis.Concerning spatial distributions, concentrations exceeding 1870 ppb were predominantly observed in western non-mountainous regions, particularly in rice paddy areas. Moreover, sporadic concentrations exceeding 1880 ppb were detected in large ports and industrial zones, primarily located in coastal regions of South Korea.Our spatial correlation analysis, conducted using the SDMSelect method, identified specific emissions contributing to regions with higher methane concentrations. There were some areas with relatively strong correlations between high XCH₄ and emissions from the domestic livestock industry, fossil fuel utilization (specifically, the oil and gas sector), landfills, and rice paddies. This analysis, incorporating domestic emission inventories and satellite data, provides valuable insights into the characteristics of regional methane concentrations. In addition, this analysis can assess national methane emissions inventories, where there is limited information on the spatial distributions, offering critical information for the prioritization of domestic regional policies aimed at reducing greenhouse gas emissions.

As one of the main drivers for climate change, it is important to understand changes in anthropogenic aerosol emissions and evaluate the climate impact. Anthropogenic aerosols have affected global climate while exerting a much larger influence on regional climate by their short lifetime and heterogeneous spatial distribution. In this study, the effective radiative forcing (ERF), which has been accepted as a useful index for quantifying the effect of climate forcing, was evaluated to understand the effects of aerosol on regional climate over a historical period (1850–2014). Eastern United States (EUS), Western European Union (WEU), and Eastern Central China (ECC), are regions that predominantly emit anthropogenic aerosols and were analyzed using Coupled Model Intercomparison Project 6 (CMIP6) simulations implemented within the framework of the Aerosol Chemistry Model Intercomparison Project (AerChemMIP) in the UK’s Earth System Model (UKESM1). In EUS and WEU, where industrialization occurred relatively earlier, the negative ERF seems to have been recovering in recent decades based on the decreasing trend of aerosol emissions. Conversely, the radiative cooling in ECC seems to be strengthened as aerosol emission continuously increases. These aerosol ERFs have been largely attributed to atmospheric rapid adjustments, driven mainly by aerosol-cloud interactions rather than direct effects of aerosol such as scattering and absorption.

This study analyzes the relationship between various atmospheric fields and the observed PM₁₀ concentrations in the Seoul metropolitan area, South Korea, during the winters of the 2001–2014 period to find suitable atmospheric indices for predicting high PM₁₀ episodes in the region. The analysis shows that PM₁₀ concentration in the metropolitan area is mainly affected by the intensity of horizontal ventilation and the 500 hPa high-pressure system over the Korean peninsula. The modified Korea particulate matter index (MKPI) is proposed based on a 10 m wind speed for surface ventilation and 500 hPa zonal wind for the intensity of a 500 hPa high-pressure system over the Korean peninsula. It is found that a positive MKPI value is closely correlated with the occurrence of high PM₁₀ concentration episodes, and hence, can be used as a predictor for high PM₁₀ episodes in the area. A future projection of the MKPI using two three-member general circulation model (GCM) ensembles with four shared socioeconomic pathway (SSP) scenarios in Coupled Model Intercomparison Project Phase 6 (CMIP6) shows that positive MKPI events and high PM₁₀ episodes are expected to increase by 5.4−16.4% depending on the SSP scenarios in the 2081−2100 period from the present-day period of 1995−2014.