China is set to actively reduce its methane emissions in the coming decade. A comprehensive evaluation of the current situation can provide a reference point for tracking the country’s future progress. Here, using satellite and surface observations, we quantify China’s methane emissions during 2010–2017. Including newly available data from a surface network across China greatly improves our ability to constrain emissions at subnational and sectoral levels. Our results show that recent changes in China’s methane emissions are linked to energy, agricultural, and environmental policies. We find contrasting methane emission trends in different regions attributed to coal mining, reflecting region-dependent responses to China’s energy policy of closing small coal mines (decreases in Southwest) and consolidating large coal mines (increases in North). Coordinated production of coalbed methane and coal in southern Shanxi effectively decreases methane emissions, despite increased coal production there. We also detect unexpected increases from rice cultivation over East and Central China, which is contributed by enhanced rates of crop-residue application, a factor not accounted for in current inventories. Our work identifies policy drivers of recent changes in China’s methane emissions, providing input to formulating methane policy toward its climate goal.

Triple collocation (TC) shows potential in estimating the errors of various geographical data in the absence of the truth. In this study, the TC techniques are first applied to evaluate the performances of multiple column-averaged dry air CO₂ mole fraction (XCO₂) estimates derived from the Greenhouse Gases Observing Satellite (GOSAT), the Orbiting Carbon Observatory 2 (OCO-2) and the CarbonTracker model (CT2019B) at a global scale. A direct evaluation with the Total Carbon Column Observing Network (TCCON) measurements is also employed for comparison. Generally, the TC-based evaluation results are consistent with the direct evaluation results on the overall performances of three XCO₂ products, in which the CT2019B performs best, followed by OCO-2 and GOSAT. Correlation coefficient estimates of the TC show higher consistency and stronger robustness than root mean square error estimates. TC-based error estimates show that most of the terrestrial areas have larger error than the marine areas overall, especially for the GOSAT and CT2019B datasets. The OCO-2 performs well in areas where CT2019B or GOSAT have large errors, such as most of China except the northwest, and Russia. This study provides a reference for characterizing the performances of multiple CO₂ products from another perspective.

As the most economically developed region in China, the Yangtze River Delta (YRD) region contributed to ~17% of the total anthropogenic CO₂ emissions from China. However, the studies of atmospheric CO₂ and CH₄ in this area are relatively sparse and unsystematic. Here, we analyze the changing characters of those gases in different development periods of China, based on the 11-year atmospheric CO₂ and CH₄ records (from 2010 to 2020) at one of the four Chinese sites participating in the World Meteorological Organization/Global Atmospheric Watch (WMO/GAW) program (Lin’an regional background station), located in the center of YRD region, China. The annual average atmospheric CO₂ and CH₄ mole fractions at LAN have been increasing continuously, with growth rates of 2.57 ± 0.14 ppm yr⁻¹ and 10.3 ± 1.3 ppb yr⁻¹, respectively. Due to the complex influence of regional sources and sinks, the characteristics of atmospheric CO₂ and CH₄ varied in different periods: (i) The diurnal and seasonal variations of both CO₂ and CH₄ in different periods were overall similar, but the amplitudes were different. (ii) The elevated mole fractions in all wind sectors tended to be uniform. (iii) The potential source regions of both gases expanded over time. (iv) The growth rate in recent years (2016–2020) changed significantly less than that in the earlier period (2010–2015). Our results indicated that the CO₂ and CH₄ mole fractions were mainly correlated to the regional economic development, despite the influence of special events such as the G20 Summit and COVID-19 lockdown.

A new meteorological station (DMS) was established at the Morning Glory summit in Zhejiang Province to provide regional background information on atmospheric composition in the Yangtze River Delta (YRD) region, China. This study investigated the first carbon monoxide (CO) records at DMS from September 2020 to January 2022. The annual average concentration of CO was 233.4 ± 3.8 ppb, which exceeded the measurements recorded at the other Asian background sites. The winter CO concentration remained elevated but peaked in March in the early spring due to the combined effect of regional emissions within the YRD and transportation impacts of North China and Southeast Asia sources. The diurnal cycle had a nocturnal peak and a morning valley but with a distinct afternoon climb, as the metropolis in the YRD contributed to a local concentration enhancement. The back trajectory analysis and the Weighted Potential Sources Contribution Function (WPSCF) maps highlighted emissions from Anhui, Jiangxi, Zhejiang, and Jiangsu provinces as significant sources. Due to well-mixed air conditions and fewer anthropogenic influences, DMS records closely aligned with the CO averages derived from the Copernicus Atmospheric Monitoring Service (CAMS) covering the YRD, confirming its representativeness for regional CO levels. This study underscored DMS as a valuable station for monitoring and understanding CO spatiotemporal characteristics in the YRD region.

The Yangtze River Delta (YRD) is the most developed region in China. Influenced by intensive and complex anthropogenic activities, atmospheric pollution in this region is highly variable, and reports are sparse. In this study, a seven-year history of the atmospheric O₃ and NO_x mixing ratios over a typical city, Hangzhou, was presented to enrich the studies on air pollution in the YRD region. Our results revealed that the diurnal variation in NO_x corresponded to traffic rush hours, while O₃ was mainly impacted by photochemical reactions in the daytime. The weekend effect was significant for NO_x, but inapparent for O₃. Two O₃ peaks in May and September were caused by seasonal atmospheric stability and climatic conditions. The lower NO_x and higher O₃ levels observed suggested direct effects from traffic restrictions and large-scale industrial shutdowns during the COVID-19 lockdown in 2020 compared with those in the periods before and after lockdown. The model simulation results showed that O₃ mixing ratios were not only related to regional anthropogenic emissions but were impacted by air mass transportation from surrounding provinces and the China shelf seas. The NO_x mixing ratios showed a decreasing trend, while the O₃ mixing ratios showed the opposite trend from 2015 to 2021, which is indicative of the implementation of the Air Pollution Prevention and Control Acton Plan issued by the Chinese government in 2013.