In support of the first Tropospheric Ozone Assessment Report (TOAR) a relational database of global surface ozone observations has been developed and populated with hourly measurement data and enhanced metadata. A comprehensive suite of ozone data products including standard statistics, health and vegetation impact metrics, and trend information, are made available through a common data portal and a web interface. These data form the basis of the TOAR analyses focusing on human health, vegetation, and climate relevant ozone issues, which are part of this special feature. Cooperation among many data centers and individual researchers worldwide made it possible to build the world’s largest collection of in-situ hourly surface ozone data covering the period from 1970 to 2015. By combining the data from almost 10,000 measurement sites around the world with global metadata information, new analyses of surface ozone have become possible, such as the first globally consistent characterisations of measurement sites as either urban or rural/remote. Exploitation of these global metadata allows for new insights into the global distribution, and seasonal and long-term changes of tropospheric ozone and they enable TOAR to perform the first, globally consistent analysis of present-day ozone concentrations and recent ozone changes with relevance to health, agriculture, and climate. Considerable effort was made to harmonize and synthesize data formats and metadata information from various networks and individual data submissions. Extensive quality control was applied to identify questionable and erroneous data, including changes in apparent instrument offsets or calibrations. Such data were excluded from TOAR data products. Limitations of a posteriori data quality assurance are discussed. As a result of the work presented here, global coverage of surface ozone data for scientific analysis has been significantly extended. Yet, large gaps remain in the surface observation network both in terms of regions without monitoring, and in terms of regions that have monitoring programs but no public access to the data archive. Therefore future improvements to the database will require not only improved data harmonization, but also expanded data sharing and increased monitoring in data-sparse regions.

We have constructed an atmospheric inversion framework based on TM5-4DVAR to jointly assimilate measurements of methane and δ¹³C of methane in order to estimate source-specific methane emissions. Here we present global emission estimates from this framework for the period 1999–2016. We assimilate a newly constructed, multi-agency database of CH₄ and δ¹³C measurements. We find that traditional CH₄-only atmospheric inversions are unlikely to estimate emissions consistent with atmospheric δ¹³C data, and assimilating δ¹³C data is necessary to derive emissions consistent with both measurements. Our framework attributes ca. 85 % of the post-2007 growth in atmospheric methane to microbial sources, with about half of that coming from the tropics between 23.5^∘ N and 23.5^∘ S. This contradicts the attribution of the recent growth in the methane budget of the Global Carbon Project (GCP). We find that the GCP attribution is only consistent with our top-down estimate in the absence of δ¹³C data. We find that at global and continental scales, δ¹³C data can separate microbial from fossil methane emissions much better than CH₄ data alone, and at smaller scales this ability is limited by the current δ¹³C measurement coverage. Finally, we find that the largest uncertainty in using δ¹³C data to separate different methane source types comes from our knowledge of atmospheric chemistry, specifically the distribution of tropospheric chlorine and the isotopic discrimination of the methane sink.

To understand the carbon cycle at policy-relevant spatial scales, a high density of high-quality CO ₂ measurement sites is needed. In 2012, the Korea Meteorological Administration (KMA) installed CO ₂ monitoring systems at Anmyeondo (AMY) in the west, Jejudo Gosan Suwolbong (JGS) in the southwest, and Ulleungdo (ULD) in the east of South Korea. Three stations were instrumented with identical greenhouse gas measurement systems based on cavity ring-down spectroscopy (CRDS) and a new drying system developed by KMA and the Korea Research Institute of Standards and Science (KRISS). This drying system is suitable in humid areas; water vapor measured using CRDS in ambient air was 0.001 % to 0.004 % across the stations. Measurement uncertainties expressed by the quadrature sum of the uncertainties from the drying system, scale propagations, repeatability, and reproducibility were ∼0.11 ppm from all KMA stations in the 68 % confidence interval. Average monthly CO ₂ enhancements above the local background at each station were 4.3±3.3 ppm at AMY, 1.7±1.3 ppm at JGS, and 1±1.9 ppm (1 σ ) at ULD, respectively, during 2012 to 2016. At AMY station, located between China and South Korea, CO ₂ annual means and seasonal variations are also greater than the other KMA stations, indicating that it is affected not only by local vegetation, but also added anthropogenic sources. Selected baseline CO ₂ at AMY and at JGS in the west of South Korea is more sensitive to East Asia (e.g., China) according to wind direction and speed. Through the comparison of long-term trends and growth rates at AMY with other East Asian stations over 15 years, it was suggested that they could be affected not only by local vegetation but also by measurement quality.

Carbon monoxide (CO) and nitrous oxide (N₂O) are two key parameters in the observation of the atmosphere, relevant to air quality and climate change, respectively. For CO, various analytical techniques have been in use over the last few decades. In contrast, N₂O was mainly measured using gas chromatography (GC) with an electron capture detector (ECD). In recent years, new spectroscopic methods have become available which are suitable for both CO and N₂O. These include infrared (IR) spectroscopic techniques such as cavity ring-down spectroscopy (CRDS), off-axis integrated cavity output spectroscopy (OA-ICOS) and Fourier transform infrared spectroscopy (FTIR). Corresponding instruments became recently commercially available and are increasingly used at atmospheric monitoring stations. We analysed results obtained through performance audits conducted within the framework of the Global Atmosphere Watch (GAW) quality management system of the World Meteorology Organization (WMO). These results reveal that current spectroscopic measurement techniques have clear advantages with respect to data quality objectives compared to more traditional methods for measuring CO and N₂O. Further, they allow for a smooth continuation of historic CO and N₂O time series. However, special care is required concerning potential water vapour interference on the CO amount fraction reported by near-IR CRDS instruments. This is reflected in the results of parallel measurement campaigns, which clearly indicate that drying the sample air leads to an improved accuracy of CO measurements with such near-IR CRDS instruments.

To understand the Korean Peninsula's carbon dioxide (CO ₂ ) emissions and sinks as well as those of the surrounding region, we used 70 flask-air samples collected during May 2014 to August 2016 at Anmyeondo (AMY; 36.53 ^∘ N, 126.32 ^∘ E; 46 m a.s.l.) World Meteorological Organization (WMO) Global Atmosphere Watch (GAW) station, located on the west coast of South Korea, for analysis of observed ¹⁴ C in atmospheric CO ₂ as a tracer of fossil fuel CO ₂ contribution ( C _ff ). Observed ¹⁴ C ∕ C ratios in CO ₂ (reported as Δ values) at AMY varied from −59.5 ‰ to 23.1 ‰, with a measurement uncertainty of ±1.8 ‰. The derived mean value C _ff of (9.7±7.8) µmol mol ⁻¹ (1 σ ) is greater than that found in earlier observations from Tae-Ahn Peninsula (TAP; 36.73 ^∘ N, 126.13 ^∘ E; 20 m a.s.l., 28 km away from AMY) of (4.4±5.7) µmol mol ⁻¹ from 2004 to 2010. The enhancement above background mole fractions of sulfur hexafluoride (Δ x (SF ₆ )) and carbon monoxide (Δ x (CO)) correlate strongly with C _ff ( r >0.7) and appear to be good proxies for fossil fuel CO ₂ at regional and continental scales. Samples originating from the Asian continent had greater Δ x (CO) : C _ff ( R _CO ) values, (29±8) to (36±2) nmol µmol ⁻¹ , than in Korean Peninsula local air ((8±2) nmol µmol ⁻¹ ). Air masses originating in China showed (1.6±0.4) to (2.0±0.1) times greater R _CO than a bottom-up inventory, suggesting that China's CO emissions are underestimated in the inventory, while observed R _SF6 values are 2–3 times greater than inventories for both China and South Korea. However, R _CO values derived from both inventories and observations have decreased relative to previous studies, indicating that combustion efficiency is increasing in both China and South Korea.

Understanding the temporal variability of atmospheric methane (CH₄) and its potential drivers can advance the progress toward mitigating changes to the climate. To comprehend interannual variability and spatial characteristics of anomalous CH₄ mole fractions and its drivers, we used integrated data from different platforms such as in situ measurements and satellites (TROPOspheric Monitoring Instrument (TROPOMI) and Greenhouse Gases Observing SATellite (GOSAT)) retrievals. A pronounced change of annual growth rate was detected at Anmyeondo (AMY), Republic of Korea, ranging from −16.8 to 31.3 ppb yr⁻¹ as captured in situ through 2015–2020 and 3.9 to 16.4 ppb yr⁻¹ detected by GOSAT through 2014–2019, respectively. High growth rates were discerned in 2016 (31.3 ppb yr⁻¹ and 13.4 ppb yr⁻¹ from in situ and GOSAT, respectively) and 2019 (27.4 ppb yr⁻¹ and 16.4 ppb yr⁻¹ from in situ and GOSAT, respectively). The high growth in 2016 was essentially explained by the strong El Niño event in 2015–2016, whereas the large growth rate in 2019 was not related to ENSO. We suggest that the growth rate that appeared in 2019 was related to soil temperature according to the Noah Land Surface Model. The stable isotopic composition of ¹³C/¹²C in CH₄ (δ¹³-CH₄) collected by flask-air sampling at AMY during 2014–2019 supported the soil methane hypothesis. The intercept of the Keeling plot for summer and autumn were found to be −53.3‰ and −52.9‰, respectively, which suggested isotopic signature of biogenic emissions. The isotopic values in 2019 exhibited the strongest depletion compared to other periods, which suggests even a stronger biogenic signal. Such changes in the biogenic signal were affected by the variations of soil temperature and soil moisture. We looked more closely at the variability of XCH₄ and the relationship with soil properties. The result indicated a spatial distribution of interannual variability, as well as the captured elevated anomaly over the southwest of the domain in autumn 2019, up to 70 ppb, which was largely explained by the combined effect of soil temperature and soil moisture changes, indicating a pixel-wise correlation of XCH₄ anomaly with those parameters in the range of 0.5–0.8 with a statistical significance (p < 0.05). This implies that the soil-associated drivers are able to exert a large-scale influence on the regional distribution of CH₄ in Korea.