Evaluation of comprehensive monthly-gridded methane emissions from natural and anthropogenic sources in China

Growing contribution to radiative forcing from China's on-farm nitrous oxide emissions requires more attention

Agricultural systems are important emission sources of non-CO2 greenhouse gases (GHGs), including the relatively short-lived GHG methane (CH4). As a pivotal emitter, China's CH4 emissions have received wide attention. For the first time, this study applied an indicator of radiative forcing-based climate footprint (RFCF) to compare the climate impacts of China's on-farm non-CO2 GHG emissions including CH4 and nitrous oxide (N2O). We found that, with short atmospheric lifetime, CH4's contribution to RFCF has plateaued in 2011 at 3.37 mW m-2 and achieved the goal of net zero increase to radiative forcing (RF) in 2017. However, the long-lived N2O emissions form an increasingly important proportion of the total RFCF at China's farm gate over time. The contribution from CH4 emissions to the total global on-farm RFCF experienced a downward trend, while that from N2O emissions has been trending upward during 1961-2021. It indicates the need of more attention on the long-lived climate forcer N2O in China. The RFCF indicator informs about whether progress is being made toward RF stabilization. It is recommended to widely apply the RFCF approach to re-examine and inform climate actions in China's agricultural systems as well as sectors with substantial biogenic CH4 emissions.

Satellite-Based Monitoring of Methane Emissions from China's Rice Hub

Rice cultivation is one of the major anthropogenic methane sources in China and globally. However, accurately quantifying regional rice methane emissions is often challenging due to highly heterogeneous emission fluxes and limited measurement data. This study attempts to address this issue by quantifying regional methane emissions from rice cultivation with a high-resolution inversion of satellite methane observations from the Tropospheric Monitoring Instrument (TROPOMI). We apply the method to the largest rice-producing province (Heilongjiang) in China for 2021. Our satellite-based estimation finds a rice methane emission of 0.85 (0.69-1.03) Tg a-1 from the province or an average emission factor of 22.0 (17.8-26.6) g m-2 a-1 when normalized by rice paddy areas. The satellite-based analysis reveals a 2 to 4 times lower bias in widely used global and national inventories, which lack up-to-date regional information. The inversion reduces the uncertainty of regional rice emissions by 73% relative to bottom-up estimates based on field flux measurements. The satellite inversion also shows that the highest rice methane emissions occur in June during the tillering stage of rice, decreasing toward ripening, indicating that the predominant water management practice in the region involves drainage and intermittent flooding after initial flooding. Process-based modeling further suggests that this practice can lead to a reduction of methane emissions by more than 50% compared to continuous flooding of rice paddies and natural wetlands.

A long-term high-resolution dataset of grasslands grazing intensity in China

Grazing is a significant anthropogenic disturbance to grasslands, impacting their function and composition, and affecting carbon budgets and greenhouse gas emissions. However, accurate evaluations of grazing impacts are limited by the absence of long-term high-resolution grazing intensity data (i.e., the number of livestock per unit area). This study utilized census livestock data and a satellite-based vegetation index to develop the first Long-term High-resolution Grazing Intensity (LHGI) dataset of grassland in seven pastoral provinces in western China from 1980 to 2022. The LHGI dataset effectively captured spatial variations in grazing intensity, with validation at 73 sites showing a correlation coefficient (R2) of 0.78. The county-level validation showed an averaged R2 values of 0.73 ± 0.03 from 1980 to 2022. This dataset serves as a vital resource for estimating grassland carbon cycling and livestock system CH4 emissions, as well as contributing to grassland management.

Characteristics of China's coal mine methane emission sources at national and provincial levels

Methane (CH4) is the second most abundant greenhouse gas. China is the largest CH4 emitter in the world, with coal mine methane (CMM) being one of the main anthropogenic contributions. Thus, there is an urgent need for comprehensive estimates and strategies for reducing CMM emissions in China. However, the development of effective strategies is currently challenged by a lack of information on temporal variations in the contributions of different CMM sources and the absence of provincial spatial analysis. Here, considering five sources and utilization, we build a comprehensive inventory of China's CMM emissions from 1980 to 2022 and quantify the contributions of individual sources to the overall CMM emissions at the national and provincial levels. Our results highlight a significant shift in the source contributions of CMM emissions, with the largest contributor, underground mining, decreasing from 89% in 1980 to 69% in 2022. Underground abandoned coal mines, which were ignored or underestimated in past inventories, have become the second source of CMM emissions since 1999. From 2011 to 2022, we identified Shanxi, Guizhou, and Shaanxi as the three largest CMM-emitting provinces, while the Emissions Database for Global Atmospheric Research (EDGAR) v8 overestimated emissions from Inner Mongolia, ranking it third. Notably, we observed a substantial decrease (exceeding 1 Mt) in CMM emissions in Sichuan, Henan, Liaoning, and Hunan between 2011 and 2022, which was not captured by EDGAR v8. To develop targeted CMM emission reduction strategies at the provincial level, we classified 31 provinces into four groups based on their CMM emission structures. In 2022, the number of provinces with CMM emissions mainly from abandoned coal mines has exceeded that of provinces with mainly underground mines, which requires attention. This study reveals the characteristics of the source of CMM emissions in China and provides emission reduction directions for four groups of provinces.

Long-term changes of methane emissions from rice cultivation during 2000 - 2060 in China: Trends, driving factors, predictions and policy implications

Regional budget assessments of methane (CH4) are critical for future climate and environmental management. CH4 emissions from rice cultivation (CH4-rice) constitute one of the most significant sources. However, previous studies mainly focus on historical emission estimates and lack consideration of future changes in CH4-rice under climate change or anthropogenic policy intervention, which hampers our understanding of long-term trends and the implementation of targeted emission reduction efforts. This study investigates the spatiotemporal variations of CH4-rice over the past two decades, using an integrated method to identify the major drivers and predict future emissions under climate change scenarios and policy perspectives. Results indicate that the CH4-rice emissions in China ranged between 6.21 and 6.57 Tg yr-1 over the past two decades, with a spatial distribution characterized by decreases in the south and increases in the north, associated with economic development, dietary shifts, technological advancements, and climate change. Factors such as the rate of straw added (RSA), fertilization, soil texture, temperature, and precipitation significantly influence CH4 emissions per unit rice production (CH4-urp), with RSA identified as the most significant tillage management factor, explaining 32 % of the variance. Lowering RSA to 8 % is beneficial for reducing CH4-urp. Scenario analysis indicates that under policies focusing on production or demand, CH4-rice is expected to increase by 0.3 % to 5.6 %, while adjusting RSA can reduce CH4-rice by 9.4 % to 10.0 %. Structural adjustments and regional cooperation serve as beneficial starting points for controlling and reducing CH4-rice in China, while optimizing industrial layouts contributes to regional development and CH4-rice control. Implementing policies related to maintaining field and crop yields can achieve a balance between rice supply and demand ahead of schedule. Dynamic adjustment of rice cultivation based on supply-demand balance can effectively reduce CH4-rice from excess rice production. By 2060, the reduction effect could reach 8.95 %-12.01 %. Introducing policy-driven tillage management measures as reference indicators facilitates the reduction of CH4-rice.

Greenhouse gases emissions and global climate change: Examining the influence of CO2, CH4, and N2O

An in-depth analysis of the role of greenhouse gases (GHGs) in climate change is examined here along with their diverse sources, including the combustion of fossil fuels, agriculture, and industrial processes. Key GHG components such as carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) are considered, along with data on emissions across various economic sectors. The consequences of climate change are also highlighted, ranging from more frequent and intense extreme weather events to rising sea levels and impacts on ecosystems and human health. The industrial revolution and unrestricted use of fossil fuels are key factors leading to an increase in GHG concentrations in the atmosphere. Global efforts to reduce emissions are considered, starting with the 1997 Kyoto Protocol and culminating in the 2015 Paris Agreement. The limited effectiveness of early initiatives is underscored, emphasizing the significant importance of the Paris Agreement that provides a global framework for establishing goals to reduce GHG emissions by country. The Green Climate Fund and other international financial mechanisms are also considered as essential tools for financing sustainable projects in developing countries. The global community faces the challenge and necessity for more ambitious efforts to achieve the set goals for reducing GHG emissions. Successful strategies are examined by Sweden, Costa Rica, and Denmark to achieve zero GHG emissions that integrate renewable energy sources and technologies. The importance of global cooperation for creating a sustainable future is also emphasized.

Quantification of Central and Eastern China's atmospheric CH4 enhancement changes and its contributions based on machine learning approach

Methane is the second largest anthropogenic greenhouse gas, and changes in atmospheric methane concentrations can reflect the dynamic balance between its emissions and sinks. Therefore, the monitoring of CH4 concentration changes and the assessment of underlying driving factors can provide scientific basis for the government's policy making and evaluation. China is the world's largest emitter of anthropogenic methane. However, due to the lack of ground-based observation sites, little work has been done on the spatial-temporal variations for the past decades and influencing factors in China, especially for areas with high anthropogenic emissions as Central and Eastern China. Here to quantify atmospheric CH4 enhancements trends and its driving factors in Central and Eastern China, we combined the most up-to-date TROPOMI satellite-based column CH4 (xCH4) concentration from 2018 to 2022, anthropogenic and natural emissions, and a random forest-based machine learning approach, to simulate atmospheric xCH4 enhancements from 2001 to 2018. The results showed that (1) the random forest model was able to accurately establish the relationship between emission sources and xCH4 enhancement with a correlation coefficient (R²) of 0.89 and a root mean-square error (RMSE) of 11.98 ppb; (2)The xCH4 enhancement only increased from 48.21±2.02 ppb to 49.79±1.87 ppb from the year of 2001 to 2018, with a relative change of 3.27%±0.13%; (3) The simulation results showed that the energy activities and waste treatment were the main contributors to the increase in xCH4 enhancement, contributing 68.00% and 31.21%, respectively, and the decrease of animal ruminants contributed -6.70% of its enhancement trend.

City-level livestock methane emissions in China from 2010 to 2020

Livestock constitute the world's largest anthropogenic source of methane (CH4), providing high-protein food to humans but also causing notable climate risks. With rapid urbanization and increasing income levels in China, the livestock sector will face even higher emission pressures, which could jeopardize China's carbon neutrality target. To formulate targeted methane reduction measures, it is crucial to estimate historical and current emissions on fine geographical scales, considering the high spatial heterogeneity and temporal variability of livestock emissions. However, there is currently a lack of time-series data on city-level livestock methane emissions in China, despite the flourishing livestock industry and large amount of meat consumed. In this study, we constructed a city-level livestock methane emission inventory with dynamic spatial-temporal emission factors considering biological, management, and environmental factors from 2010 to 2020 in China. This inventory could serve as a basic database for related research and future methane mitigation policy formulation, given the population boom and dietary changes.

Methane emission and influencing factors of China's oil and natural gas sector in 2020-2060: A source level analysis

The Chinese oil and gas industry requires targeted policies to reduce methane emissions. To achieve this goal, it is necessary to predict future methane emission trends and analyze the factors that influence them. However, changing economic development patterns, insufficient analysis of various factors influencing emissions, and inadequate resolution of methane emission inventories have made these goals difficult to achieve. Accordingly, this study aims to expand the methane emission estimation method to compile source-level emission inventories for future emissions, analyze the factors influencing them, and form a mechanistic understanding of the methane emissions from the local oil and gas industry. The research results indicate that methane emissions deriving from this industry will increase rapidly before 2030, after which they will decline slowly in all scenarios. The production and utilization processes in the natural gas supply chain, i.e., compressors and liquid unloading, include the main sources of methane emissions. Emissions are affected significantly by total production and consumption. Change in the overall supply and demand of natural gas affects change in methane emissions more significantly than adopting new technologies and strengthening facility maintenance, i.e., the overall supply and demand of natural gas are the dominant factors in controlling methane emissions. This study suggests that controlling the total demand for oil and gas should be at the core of the methane emission control policy for the local oil and gas industry. Moreover, equipment maintenance and emission reduction technologies should be used more effectively to reduce total emissions.

Agricultural Methane Emissions in China: Inventories, Driving Forces and Mitigation Strategies

Identification of the spatial distribution, driving forces, and future trends of agricultural methane (AGM) emissions is necessary to develop differentiated emission control pathways and achieve carbon neutrality by 2060 in China, which is the largest emitter of AGM. However, such research is currently lacking. Here, we estimated China's AGM emissions from 2010 to 2020 and then decomposed six factors that affect AGM emissions via the LMDI model. The results indicated that the AGM emissions in China in 2020 were 23.39 Tg, with enteric fermentation being the largest source, accounting for 43.9% of the total emissions. A total of 39.3% of the AGM emissions were from western China. The main driver of AGM emission reduction was emission intensity, accounting for 59% and 33.7% of methane emission reduction in the livestock sector and rice cultivation, respectively. Additionally, higher levels of urbanization contributed to AGM emission reductions, accounting for 31.3% and 43.0% of the livestock sector and rice cultivation emission reductions, respectively. Based on the SSP-RCP scenarios, we found that China's AGM emissions in 2060 were reduced by approximately 90% through a combination of technology measures, behavioral changes, and innovation policies. Our study provides a scientific basis for optimizing existing AGM emission reduction policies not only in China but also potentially in other high AGM-emitting countries, such as India and Brazil.

Association of long-term exposure to air pollutant mixture and incident cardiovascular disease in a highly polluted region of China

Despite growing evidence that links long-term air pollution exposure to cardiovascular disease (CVD), the combined effects of air pollutants and particulate matter with an aerodynamic diameter of less than 2.5 μm (PM_2.5) components are still limited. A prospective cohort study was performed based on the Cohort Study on Chronic Disease of the Community Natural Population in the Beijing-Tianjin-Hebei Region (CHCN-BTH) to assess the association of long-term air pollutants with incident CVD and the combined effect of the air pollutants mixture among 26,851 adults. Three-year residential exposure to air pollutants (PM_2.5, O₃, PM₁₀, PM₁, NO₂, SO₂ and CO) and PM_2.5 components [black carbon (BC), NH₄⁺, SO₄^2-, NO₃^- and organic matter (OM)] were calculated based on well-validated models. Proportional hazard models were applied to assess the association of air pollutants with incident CVD. Quantile g-Computation was used to examine the combined effect of the pollutant mixture. During the 56,090 person-years follow-up, 629 participants reported incident CVD. Adjusted hazard ratios with 95% confidence intervals (CIs) of CVD per interquartile range increase in O₃, PM_2.5, PM₁, NO₂, BC, and OM concentrations were 4.52 (95%CI: 2.61, 7.83), 2.39 (95%CI: 1.83, 3.13), 2.37 (95%CI: 1.20, 4.70), 1.36 (95%CI: 1.19, 1.56), 3.84 (95%CI: 2.38, 6.18), and 3.07 (95%CI: 2.01, 4.69), respectively. In multi-pollutant models, the combined effect of air pollutant mixture on incident CVD was 2.37 (95%CI: 2.30, 2.44). PM_2.5 and O₃ contributed 54.3% and 44.5% of the combined effect of the air pollutant mixture, respectively. After using PM_2.5 components instead of PM_2.5 as part of the mixture, OM drove 55.2% of the combined effect. The findings indicated associations of air pollutant mixtures with CVD incidence. PM_2.5 (especially OM) and O₃ might strongly contribute to air pollutant mixtures that lead to incident CVD.

Fossil-Fuel and Food Systems Equally Dominate Anthropogenic Methane Emissions in China

Understanding fossil-fuel/food production and consumption patterns is the first step toward reducing the climate impacts of associated methane (CH₄) emissions but remains unclear in China. Here, based on the bottom-up method, whole-industrial-chain CH₄ emission in China (CH₄-CHINA) is developed to track CH₄ emissions from production to use and finally to disposal. The estimated Chinese national CH₄ emissions in 2020 are 39288.3 Gg (25,230.8-53,345.7 Gg), with 50.4 and 49.6% emissions generated from fossil-fuel and food systems, respectively. ∼130,000 point sources are included to achieve a highly resolved inventory of CH₄ emissions, which account for ∼53.5% of the total anthropogenic CH₄ emissions in 2020. Our estimate is 36% lower than the Chinese inventory reported to the UNFCCC and 40% lower than EDGAR v6.0, mainly driven by lower emissions from rice cultivation, waste management, and coal supply chain in this study. Based on the emission flow, we observe that previous studies ignored the emissions from natural gas vehicles and residential appliances, coke production, municipal solid waste predisposal, septic tanks, biogas digesters, and food sewage treatment, which totally contribute ∼12.4% of the national anthropogenic CH₄ emissions. The results discussed in this study provide critical insights to design and formulate effective CH₄ emission mitigation strategies.

Atmospheric observations suggest methane emissions in north-eastern China growing with natural gas use

The dramatic increase of natural gas use in China, as a substitute for coal, helps to reduce CO₂ emissions and air pollution, but the climate mitigation benefit can be offset by methane leakage into the atmosphere. We estimate methane emissions from 2010 to 2018 in four regions of China using the GOSAT satellite data and in-situ observations with a high-resolution (0.1° × 0.1°) inverse model and analyze interannual changes of emissions by source sectors. We find that estimated methane emission over the north-eastern China region contributes the largest part (0.77 Tg CH₄ yr^-1) of the methane emission growth rate of China (0.87 Tg CH₄ yr^-1) and is largely attributable to the growth in natural gas use. The results provide evidence of a detectable impact on atmospheric methane observations by the increasing natural gas use in China and call for methane emission reductions throughout the gas supply chain and promotion of low emission end-use facilities.

Temporal Variation and Source Analysis of Atmospheric CH4 at Different Altitudes in the Background Area of Yangtze River Delta

Through an analysis of CH4 data observed at different altitudes at the atmospheric background station in Lin’an from 2016 to 2020, in combination with back-trajectory and distribution characteristics of potential source areas, the CH4 concentration variations at higher and lower altitudes and their relationships with sources and sinks were studied. The results showed that the CH4 concentration was characterized by notable diurnal variations. The largest concentration difference occurred between 5 and 7 am; the concentration difference in summer was higher than that in the other three seasons. Background filtering of the hourly CH4 concentration was carried out using a numerical method. The results showed that the difference in the CH4 background concentration between the two altitudes was 4.6 ppb (SD = 7.9). The CH4 background concentrations at the two altitudes had the same seasonal variation: double peaks and valleys. The peaks appeared in May and December, and the valleys appeared in March and July. In spring and summer, the potential CH4 source areas were mainly distributed in the rice planting and wetland discharge regions. In autumn, they were mainly distributed in regions affected by fugitive emissions from rice planting and coal mining. In winter, they were mainly distributed in livestock and poultry management regions.

Analysis of the Characteristics of CH4 Emissions in China's Coal Mining Industry and Research on Emission Reduction Measures

CH₄ is the second-largest greenhouse gas and has a significant impact on global warming. China has the largest amount of anthropogenic coal mine methane (CMM) emissions in the world, with coal mining emissions (or gas emissions) accounting for 90% of total energy industry emissions. The results of CH₄ emission inventories from previous studies vary widely, with differences in the spatial and temporal dimensions of gas emission factors of belowground mining being the main points of disagreement. Affected by the policies of “eliminating backward production capacity” and “transferring energy base to the northwest”, China’s coal production layout has changed greatly in the past ten years, but the closely related CH₄ emission factors have not been dynamically adjusted. This paper investigated 23 major coal producing provinces in China, obtained CH₄ emission data from coal mining, calculated CH₄ emission factors in line with current production conditions, and studied the reduction measures of coal mine gas emission. According to the CH₄ emission data of China’s coal mines in 2018, 15.8 Tg of methane is released per year in the coal mining industry in China, and 11.8 Tg after deducting recycling. Shanxi Province’s CH₄ emissions are much higher than those of other provinces, accounting for 35.5% of the country’s total emissions. The weighted CH₄ emission factor of coal mining in China is 6.77 m³/t, of which Chongqing is the highest at approximately 60.9 m³/t. Compared with the predicted value of the IPCC, the growth trend of CCM has slowed significantly, and the CH₄ utilization rate has gradually increased. This change may be aided by China’s coal industry’s policy to resolve excess capacity by closing many high-gas and gas outburst coal mines. In addition, the improvement of coal mine gas extraction and utilization technology has also produced a relatively significant effect. This paper determines the distribution of methane emissions and emission sources in China’s coal mining industry, which is useful in formulating CCM emission reduction targets and adopting more efficient measures.

The Spatial and Temporal Distribution Patterns of XCH4 in China: New Observations from TROPOMI

Methane is the second most important greenhouse gas after carbon dioxide. The intensity and distribution of methane source/sink in China are unknown. We collected the column-averaged dry air mixing ratio of CH4 (abbreviated as XCH4 hereafter) from TROPOMI for the period from 2018 to 2021, to study spatial distribution and temporal change of atmospheric CH4 concentration, providing clues and foundations for understanding the source/sink in China. It was found that the distribution of XCH4 is roughly high in the East, low in the West, high in the South and low in the North. Additionally, an evidently positive linear relationship between XCH4 and population density was witnessed, suggesting anthropogenic emissions may account for a large portion of total methane emissions. XCH4 exhibits evident seasonal characteristics, with the peak in summer and trough in winter, regardless of the different regions. Moreover, we used XCH4 anomalies to identify the emission sources and found its great potential in the detection of methane emission from mining plants, landfill, rice fields and even geological fracture zones.