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Efforts to enhance greenhouse gas (GHG) emission reduction in East Asia play a pivotal role on both global and regional scales in advancing climate mitigation strategies. This study aimed to better constrain anthropogenic CO 2 emission estimates by expanding the network of near-surface in-situ stations for CO 2 observations across South Korea. To achieve an optimal CO 2 network design, we conducted an Observing System Simulation Experiment (OSSE) coupled with the Stochastic Lagrangian Transport model (STILT), utilizing meteorological data from the Korean Integrated Model (KIM). Our inversion setup incorporated two CO 2 emission datasets with a 0.1o resolution: EDGAR v6 for prior emissions and GRACED for truth emissions. A uniform model-mismatch error of 3 ppm was introduced across sites. The effectiveness of the existing five in-situ stations, termed the base network, in South Korea was evaluated to gauge their ability to constrain CO 2 surface flux estimates. However, the findings revealed a reduction in flux uncertainty of only 29.2%, which fell short of the desired uncertainty reduction goal. In this base network, the Lotte World Tower (LWT: 37.5126°E, 127.1025°E) in Seoul and the Anmyeondo (AMY: 36.538576° N, 126.330071° E) site in Taean county stood as major contributors, with estimated reductions of 17.48% and 6.35%, respectively. Consequently, we proposed and developed an extended network, identifying seven candidate sites based on consideration of logistical factors, existing infrastructures, and proximity to the emission source regions. An incremental optimization scheme ranked their contributions, resulting in an additional 25% reduction, bringing the total to 54.13%. However, it is noteworthy that diminishing returns (ranging from 13% to less than 0.1%) were observed with an increase in station count mainly due to the possibility that adding a station earlier in the sequence might render subsequent stations redundant. Despite this, the proposed CO 2 network successfully reduced uncertainty in emissions, narrowing the gap with the objectives of the Global Greenhouse Gas Watch (G3W). • Designing CO 2 near-surface observation network over South Korea. • New stations selected considering logistic factors, existing infrastructures, and proximity to emission sources. • The base network was able to reduce 29.18% of the uncertainty in CO 2 emissions. • Extending network, by adding new seven candidate sites, led to a total uncertainty reduction of 54.13%. [ABSTRACT FROM AUTHOR]

The ozone concentration in the atmosphere has been recovering with the reduction in atmospheric ozone-depleting substances (ODS). However, ODS remain in the atmosphere for long periods, slowing recovery. Furthermore, greenhouse gas-induced climate change complicates ozone recovery. East Asia is a significant contributor to global climate change due to the increase in industrialization and the presence of complex climate conditions. We investigated ozone variations in East Asia using total column ozone data based on satellite and ground observations and compared the results and trends derived from a multi-linear regression (MLR) model. We found that the MLR model has relatively poor explanatory power for recent extraterrestrial and dynamical proxies, but the uncertainty can be reduced using monthly data and atmospheric proxies. The ozone trend in East Asia had the greatest increase in the vicinity of the Korean Peninsula and Manchuria from 1997 to 2017 (~1% per decade). Similarly, the trend derived from Brewer spectrophotometer data was 1.02 ± 1.45% per decade in Pohang and 1.27 ± 0.85% per decade in Seoul. When the analysis period was extended to 2020, the impact of atmospheric variability was greater, suggesting that recent climate change can increasingly contribute to total ozone variability. [ABSTRACT FROM AUTHOR]

The Yellow Sea serves as a pathway for air pollution transport from the Asian continent into Korea and is annually monitored by the Korean Meteorological Administration (KMA) research vessel during the spring season. This study investigated the spatio-temporal variation of long-range transported greenhouse gases (CO 2 and CH 4) and air pollutants (CO, NO x , SO 2 , O 3) in the Yellow Sea during the Yellow Sea Air Quality (YES-AQ) campaign. Our analysis reveals that GHGs and air pollutants exhibit a clear latitudinal distribution. Lower concentrations are observed in the range of 31.2–34.5°N, primarily influenced by air masses traversing the ocean and the western part of Korean Peninsula. In contrast, higher concentrations occur more frequently at 34.5–37.8°N, primarily affected by continental air masses. The regression slopes of CO and CO 2 vary depending on regional characteristics, particularly in air originating from Korea and China. Regression slope analysis between CO, CO 2, and CH 4 , except for high plume of CH 4 (>2.05 ppm), indicates that fossil fuel sources play a significant role. A high plume of CH 4 (>2.05 ppm) was observed on April 22nd, coinciding with the maximum O 3 concentrations during the period of highest temperatures throughout the voyage. The potential source regions were identified in the west-southern coast of Korea, using footprint analysis from Stochastic Time-Inverted Lagrangian Transport (STILT) and column-averaged dry-air mole fraction of CH 4 (XCH 4) retrieval from the TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor (S5P) satellite. The high CH 4 enhancements are most likely due to biogenic emissions triggered by favorable near-surface temperatures for microbial activities in soil. Furthermore, the high CH 4 enhancements were not correlated with CO and CO 2 , indicating that the source was not related to fossil fuel combustion. On March 29–30, a high plume of NO x was detected and is likely attributed to the Bohai Sea, which is located just above the Yellow Sea and surrounded by highly industrialized and semi-enclosed areas. • Yellow Sea Air Quality campaign studies greenhouse/air pollutants distribution. • Greenhouse/air pollutants show a clear latitudinal gradient over Yellow Sea. • CO, CO 2 , CH 4 correlation suggests fossil fuel-based sources mainly from China and Korea. • Highly elevated CH 4 linked to microbial-related biogenic emissions from Korean based on STILT analysis. [ABSTRACT FROM AUTHOR]