We used multiyear Greenhouse Gases Observing Satellite (GOSAT) dry air, column-integrated CO₂ (XCO₂) retrievals (2010–2013) to evaluate urban and local-scale CO₂ emissions over East Asia and examined whether GOSAT XCO₂ captures the impact of strong local CO₂ emissions over South Korea, an East Asian downwind region with high atmospheric aerosol loading and strong summer monsoons. We chose a region in western Mongolia (upwind region) as the XCO₂ background, and estimated XCO₂ enhancements in South Korea to gauge local and regional emissions. We found that the cold season (November–February) was better suited for estimating XCO₂ enhancements of local emissions due to the summer monsoon and stronger transboundary impacts in other seasons. In particular, we focused on three local GOSAT XCO₂ footprints (about 10.5 km in diameter) in South Korea: the Seoul Metropolitan Area (SMA), the Gwangyang Steelworks and Hadong power plants (GYG), and the Samcheonpo power plants (SCH). The range of XCO₂ enhancement was 7.3–10.7 ppm (14.1–21.3 mg m⁻³ in standard temperature and pressure (STP)). By estimating other important contributions to XCO₂ enhancements such as the XCO₂ latitudinal gradients and Chinese fossil fuel combustions, we estimated the net enhancements caused mainly by local CO₂ emissions in the range of 4.2–7.6 ppm (8.1–14.7 mg m⁻³ in STP) These high enhancements imply that large point source contributions are an important factor in determining these enhancements, even if contributions are also made by broader-scale emissions. Additionally, differences in net XCO₂ enhancements and trends between GYG (+ 4.2 ppm (+ 8.2 mg m⁻³ in STP), – 0.2 ppm year⁻¹ (–0.4 mg m⁻³ year⁻¹ in STP)) and SCH (+ 7.6 ppm (+ 14.9 mg m⁻³ in STP), + 1.3 ppm year⁻¹ (+ 2.6 mg· m⁻³ year⁻¹ in STP)) indicate that these closely located footprints (approximately 26 km apart) are separable. These results will be useful in evaluating and reducing uncertainties in regional and local anthropogenic greenhouse gas (GHG) emissions over East Asia.

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.

We investigated regional climate changes in South Korea over the last 40 years (1980 ~ 2019). The country was divided into 10 areas of Seoul, Gyeonggi, Gangwon, Chungbuk, Chungnam, Jeonbuk, Jeonnam, Gyeongbuk, Gyeongnam, and Jeju. We used the regional climate data (daily temperature and precipitation) measured by Korea Meteorological Administration (KMA) at 61 sites. There has been an annual average temperature increase of 1.4℃ for the last 40 years in Korea, with a range of +1.0℃ (Jeonnam) ~ +1.8℃ (Gangwon). The increases in annual minimum and maximum temperatures were even larger; the increase in annual maximum temperature was as high as 2.2℃ over a broad range of trends (+0.2℃ (Jeonnam) ~ +5.6℃ (Gyeonggi)). The change of annual total precipitation was not clear, but the southern part of Korea showed an increasing trend (Jeju(+206.4 mm/40years)), and the central part of Korea showed a decreasing trend (Chungnam (-119.6mm/40years)). The trend of annual temperature variability was negative in central Korea (Gyeonggi (-4.2℃/40 years)) and positive in southern Korea (Gyeongnam (+1.0℃ /40years)). The changes in the trends of monthly temperature variabilitiy differed by season; March (Gangwon (+0.1℃/40years) ~ Seoul (+3.6℃/40years)) and August (Jeju (-0.9℃/40 years) ~ Chungbuk (+2.9℃/40 years)) showed increasing trends due to the greater increase in maximum monthly temperatures. In comparison, September (Gyeongnam (-0.6℃/40 years) ~ Jeju (-3.5℃/40years)) and December (Seoul (+0.2℃/40 years) ~ Jeonbuk (-4.4℃/40 years)) showed decreasing trends due to the greater increase in minimum monthly temperatures. Those changes might cause different seasonal health impacts. Warming trends were noted in climate extreme indices over the last 40 years. For example, there was an almost one-month increase in the number of summer days (Tmax ≥ 25℃) in Seoul and 15-day increase in the number of tropical nights (Tmin ≥ 25℃) in Jeju. There was a similar decrease (14 days) in cold days (Tmin ≤ -12℃) in Gangwon. Our results show that regional differences in climate change over the last 40 years should be considered for establishing and implementing regional climate change adaptation policies.

We analyzed the multi-year relationship between particulate matter (PM₁₀ and PM_2.5) concentrations and possible precursors including NO₂, SO₂, and NH₃ based on local observations over the Seoul Metropolitan Area (SMA) from 2015 to 2017. Surface NH₃ concentrations were obtained from Cross-track Infrared Sounder (CrIS) retrievals, while other pollutants were observed at 142 ground sites. We found that NH₃ had the highest correlation with PM_2.5 (R = 0.51) compared to other precursors such as NO₂ and SO₂ (R of 0.16 and 0.14, respectively). The correlations indicate that NH₃ emissions are likely a limiting factor in controlling PM_2.5 over the SMA in a high-NOx environment. This implies that the current Korean policy urgently requires tools for controlling local NH₃ emissions from the livestock industry (for example, from hog manure). These findings provide the first satellite-based trace gas evidence that implementing an NH₃ control strategy could play a key role in improving air quality in the SMA.

Objectives : This study aims to discuss air quality policy improvement that reflect regional characteristics through analyzing recent PM2.5 concentration, air pollutant emission sources and those contributions to annual PM2.5 concentration in Chungcheong region (Daejeon Metropolitan City, Sejong Metropolitan Autonomous City, the Province of Chungcheongnam-do, and Chungcheongbuk-do) in South Korea. In addition, we identified the characteristics of the PM2.5 pollution at the level of fundamental local government, and demonstrated the number of vulnerable population exposed to high level of PM2.5 concentration in order to propose policy implications in Chungcheong region.Methods : Based on the national emissions estimates (CAPSS: Clean Air Policy Support System) and air quality modelling system, major sectors/sources of air pollutants emission and national contributions of PM2.5 concentrations in Chungcheong region were analyzed. Furthermore, the study identified the number of people exposed to the higher PM2.5 concentrations (>25 µg/m3) by the measurement data and demographics available in 2019.Results and Discussion : The national air pollutants emissions in Chungcheong region were emitted from Chungnam (about 59% of NOx emission volume, 89% of SOx, 70% of NH3, 54% of VOCs, 79% of PM2.5, and 68% of TSP respectively), mainly from industry, domestic, energy, and road sector. According to the results of the air quality modelling, Chungcheong region also had the largest contribution on the average annual PM2.5 concentration in South Korea (27%). Chungnam emitted the largest emission volume of air pollutants, mainly from industry and power generation sectors (especially in Dangjin, Seosan, and Boryeong), while Asan, Yesan, Hongseong, and Cheongyang were classified as the areas with higher PM2.5 concentrations (>25 µg/m3), showing a gap between the areas with large emission volume and high concentration. Chungbuk and Sejong had higher annual PM2.5 concentration due to the influence of external sources and their geographical characteristics. The largest vulnerable population (over 65 years old and under 18 years old) exposed to high PM2.5 concentrations annually lived in Cheongju. Chungbuk had about 40% more air pollutant emission volume than Chungnam, but about 17% more vulnerable population.Conclusions : At the current stage of “master plan” in Chungcheong region, it is important to mitigate air pollutants emissions on the basis of the local emissions characteristic at the level of fundamental local government (such as industry sector in Dangjin, Seosan, and Danyang/ Domestic buring in Cheongju, Cheonan, and Daejeon/power generation in Boryeong, Taean and Dangjin/ road in Daejeon, Cheongju, and Cheoan). In addition, Chungbuk requires management of the areas with higher PM2.5 concentration such as Goesan, Boeun, Okcheon, and Yeongdong located outside “air control zone”. To reduce high level of PM2.5 concentration in Chungcheong region, cooperation with neighboring local governments such as Gyeonggi Province is crucial, and policy solutions are needed between the stakeholders to resolve the disparity issues between areas with larger emission volume and higher PM2.5 concentration.

Growing concern about particulate matter (PM_2.5) pressures Korea to reduce the health risks associated with its high dependency on fossil fuels. The Korean economy relies heavily on large thermal power plants—a major source of PM_2.5 emissions. Although air quality regulations can negatively impact local economies, the Korean government announced two strict air quality mitigation policies in 2019. We develop a regional static computable general equilibrium model to simulate the economic and environmental impacts of these polices under alternative hypothetical scenarios. We separate two regions, Chungcheongnam-do, the most polluted region, and the rest of the country, in our model. As policy options, we introduce a regional development tax and a tradable market for PM emission permits, similar to an air pollution tax and a carbon permits market, respectively. The results show that allowing higher tax rates and a tradable permits market gives the optimal combination, with the PM_2.5 emissions reduced by 2.35% without sacrificing economic growth. Since alternative options present, for example, a 0.04% loss of gross domestic product to reduce PM emissions by the same amount, our results here may present a new policy paradigm for managing air pollutants such as PM_2.5.