High loadings of anthropogenic carbonaceous aerosols in Chinese air influence the air quality for over one billion people and impact the regional climate. A large fraction (17–80%) of this aerosol carbon is water-soluble, promoting cloud formation and thus climate cooling. Recent findings, however, suggest that water-soluble carbonaceous aerosols also absorb sunlight, bringing additional direct and indirect climate warming effects, yet the extent and nature of light absorption by this water-soluble "brown carbon" and its relation to sources is poorly understood. Here, we combine source estimates constrained by dual carbon isotopes with light-absorption measurements of water-soluble organic carbon (WSOC) for a March 2011 campaign at the Korea Climate Observatory at Gosan (KCOG), a receptor station in SE Yellow Sea for the outflow from northern China. The mass absorption cross section at 365 nm (MAC₃₆₅) of WSOC for air masses from N. China were in general higher (0.8–1.1 m² g⁻¹), than from other source regions (0.3–0.8 m² g⁻¹). However, this effect corresponds to only 2–10% of the radiative forcing caused by light absorption by elemental carbon. Radiocarbon constraints show that the WSOC in Chinese outflow had significantly higher fraction fossil sources (30–50%) compared to previous findings in S. Asia, N. America and Europe. Stable carbon (δ¹³C) measurements were consistent with aging during long-range air mass transport for this large fraction of carbonaceous aerosols.

SO₂ column densities from Ozone Monitoring Instrument provide important information on emission trends and missing sources, but there are discrepancies between different retrieval products. We employ three Ozone Monitoring Instrument SO₂ retrieval products (National Aeronautics and Space Administration (NASA) standard (SP), NASA prototype, and BIRA) to study the magnitude and trend of SO₂ emissions. SO₂ column densities from these retrievals are most consistent when viewing angles and solar zenith angles are small, suggesting more robust emission estimates in summer and at low latitudes. We then apply a hybrid 4D‐Var/mass balance emission inversion to derive monthly SO₂ emissions from the NASA SP and BIRA products. Compared to HTAPv2 emissions in 2010, both posterior emission estimates are lower in United States, India, and Southeast China, but show different changes of emissions in North China Plain. The discrepancies between monthly NASA and BIRA posterior emissions in 2010 are less than or equal to 17% in China and 34% in India. SO₂ emissions increase from 2005 to 2016 by 35% (NASA)–48% (BIRA) in India, but decrease in China by 23% (NASA)–33% (BIRA) since 2008. Compared to in situ measurements, the posterior GEOS‐Chem surface SO₂ concentrations have reduced NMB in China, the United States, and India but not in South Korea in 2010. BIRA posteriors have better consistency with the annual growth rate of surface SO₂ measurement in China and spatial variability of SO₂ concentration in China, South Korea, and India, whereas NASA SP posteriors have better seasonality. These evaluations demonstrate the capability to recover SO₂ emissions using Ozone Monitoring Instrument observations.

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.

We measured peroxyacetyl nitrate (PAN) and other reactive species such as O ₃ , NO ₂ , CO, and SO ₂ with aerosols including mass, organic carbon (OC), and elemental carbon (EC) in PM _2. 5 and K ⁺ in PM _1. 0 at Gosan Climate Observatory in Korea (33.17° N, 126.10° E) during 19 October–6 November 2010. PAN was determined through fast gas chromatography with luminol chemiluminescence detection at 425 nm every 2 min. The PAN mixing ratios ranged from 0.1 (detection limit) to 2.4 ppbv with a mean of 0.6 ppbv. For all measurements, PAN was unusually better correlated with PM _2. 5 (Pearson correlation coefficient, γ = 0.79) than with O ₃ ( γ = 0.67). In particular, the O ₃ level was highly elevated with SO ₂ at midnight, along with a typical midday peak when air was transported rapidly from the Beijing areas. The PAN enhancement was most noticeable during the occurrence of haze under stagnant conditions. In Chinese outflows slowly transported over the Yellow Sea, PAN gradually increased up to 2.4 ppbv at night, in excellent correlation with a concentration increase in PM _2. 5 OC and EC, PM _2. 5 mass, and PM _1. 0 K ⁺ . The high K ⁺ concentration and OC ∕ EC ratio indicated that the air mass was impacted by biomass combustion. This study highlights PAN decoupling with O ₃ in Chinese outflows and suggests PAN as a useful indicator for diagnosing continental outflows and assessing their perturbation of regional air quality in northeast 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.