Observed changes in China’s methane emissions linked to policy drivers

Zhang, Yuzhong; Fang, Shuangxi; Chen, Jianmeng; Lin, Yi; Chen, Yuanyuan; Liang, Ruosi; Ke, Jau‐Chuan; Parker, Robert J.; Boesch, Hartmut; Steinbacher, Martin; Sheng, Jianxiong; Lu, Xiao; Song, Shaojie; Peng, Shushi

doi:10.1073/pnas.2202742119

Cited by 45 publications

(39 citation statements)

References 41 publications

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“…Similarly, our estimate is ∼40% lower national total emissions than EDGAR v6.0, 9 with much lower emissions from rice cultivation but slightly higher emissions from livestock and oil and gas supply chain. Our estimate is also lower than the top-down emissions, 17,48,49 driven by much lower rice and livestock emissions. Nevertheless, the total CH 4 emissions from China in this study is within the range of previous bottom-up inventories (36.6−57.6 Tg/yr), albeit with a major gap for individual sector, such as rice cultivation, coal supply chain, and oil and gas supply chain.…”

Section: Comparisons With Other Inventories Figure 5 Compiles the Tot...contrasting

confidence: 52%

“…It is also reported that the COVID-19 led to a strong reduction of anthropogenic activities such as fossil fuel use, probably accompanied by a drop of CH 4 emissions in 2020 . Previous studies ,,, indicated that CH 4 emissions have increased significantly after 1990, with annual average growth rates of 2.6–4.0% during 2000–2010 but slower growth rates of 0.5–2.2% during 2011–2015, and the emissions became relatively stable, with growth rates of 0.3–0.8% during 2015–2019 because of the stable emissions from the energy sector, which is mainly attributed to the China’s energy policy of “consolidation to large coal mines” and “phase out of small coal mines.” With the further implementation of “coal-to-gas” transition in energy policy in China, emission from coal mines may be reduced, while gas emissions may continue to increase in the future. Solid waste generation has been increasing in the past decade, but the increasing fraction is incinerated rather than landfilled .…”

Section: Resultsmentioning

confidence: 99%

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

Liu

Wang

et al. 2023

Environ. Sci. Technol.

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Understanding fossil-fuel/food production and consumption patterns is the first step toward reducing the climate impacts of associated methane (CH 4 ) emissions but remains unclear in China. Here, based on the bottom-up method, wholeindustrial-chain CH 4 emission in China (CH 4 -CHINA) is developed to track CH 4 emissions from production to use and finally to disposal. The estimated Chinese national CH 4 emissions in 2020 are 39288.3 Gg (25,345.7 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 CH 4 emissions, which account for ∼53.5% of the total anthropogenic CH 4 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 CH 4 emissions. The results discussed in this study provide critical insights to design and formulate effective CH 4 emission mitigation strategies.

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Section: Comparisons With Other Inventories Figure 5 Compiles the Tot...contrasting

confidence: 52%

Section: Resultsmentioning

confidence: 99%

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

Liu

Wang

et al. 2023

Environ. Sci. Technol.

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“…Among these previous studies, only Zhang et al. (2022) provided the a priori and posteriori CH 4 emissions from different source categories. We examined the ratio between the posteriori and a priori coal + gas + oil CH 4 emissions for Shanxi province and TJM area.…”

Section: Resultsmentioning

confidence: 99%

“…(2021) and Zhang et al. (2022) used both satellite and tower‐based observations to constrain CH 4 emissions. The spatial resolutions for these studies were 2.0° × 2.5° latitude‐longitude, 0.25° × 0.3125°, 4° × 5°, and 0.5° × 0.625°, respectively.…”

Section: Resultsmentioning

confidence: 99%

Estimation of Anthropogenic CH₄ and CO₂ Emissions in Taiyuan‐Jinzhong Region: One of the World's Largest Emission Hotspots

Xiao

Griffis

et al. 2023

JGR Atmospheres

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Coal mining ranks as the largest anthropogenic CH 4 source in China with emission factors (EFs) varying up to 30-fold among inventories when applied to different provinces. The lack of independent evaluation of coal mining CH 4 EFs in China is one of the main uncertainties in estimating national total CH 4 emissions. Shanxi province, which supplies 25% of the national coal production, is the largest coal mining CH 4 emission region in China and even among the world's largest coal production regions. This area is also a significant anthropogenic CO 2 source because of high-density power and industrial activities. Given the large uncertainties in CH 4 and CO 2 inventories from provincial to city scales, questions remain whether state-of-theart inventories have accurately estimated these emission hotspots. Here, we evaluate CH 4 and CO 2 emissions from one of the world's largest coal production regions near Taiyuan City, the capital of Shanxi province, China. CH 4 and CO 2 concentrations were measured from March 2018 to February 2019 from a 30-m tower. These data were used within an inverse modeling framework to simulate both CH 4 and CO 2 concentrations and to evaluate EFs for this region. Results show generally good agreement between observed and simulated CH 4 concentrations. However, the CO 2 simulations were much lower compared to the observations. Given the minor role of NEE-induced CO 2 enhancements, we believe that the large difference is attributed to the underestimation of anthropogenic CO 2 emissions. In general, the derived posteriori anthropogenic CH 4 emissions were 85.2(±18.1)% of a priori emissions, where fugitive CH 4 from coal mining accounted for ∼92.7% of total anthropogenic emissions. The derived coal mining EF was 23.2(±4.9) m 3 CH 4 /ton coal, close to the default value of high CH 4 -content coal, but twofold the province average that were reported by previous observation-based studies in Shanxi province, indicating large spatial inhomogeneity in the coal mining CH 4 EF. The posteriori CO 2 emissions were 1.6-fold of the a priori emissions, highlighting underestimation of CO 2 emissions in industrial cities and some potential large emission sources that are missing from state-of-the-art inventories. Finally, we also emphasize the use of satellite observations and denser tower-based networks are essential in resolving the spatial inhomogeneity of greenhouse gas emissions. Plain Language SummaryThe understanding of anthropogenic CH 4 and CO 2 emissions is basis for climate mitigation especially for global top emitting countries, but the largest issue before addressing above question is that many previous studies have found considerable bias of greenhouse gas emission for almost all inventories from city to regional scales. These facts hindered the government to make and evaluate corresponding mitigation policies. Here, to quantify CH 4 and CO 2 emissions at one of global largest CH 4 and CO 2 hotspot in China, we conducted 1 year tower-based atmospheric CH 4 and CO 2 concentration measurements a...

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“…For example, previous results also based on GOSAT data indicate a large increase in coal emissions in N. China, despite stated decreasing inventories , consistent with the results shown here. However, the characterization provided by the optimal estimation approach suggest that at least part of this observed increase result from spatial correlations in the inversion as demonstrated by Figure 2c (Zhang et al 2022). Consequently, a more robust conclusion is that the posited EDGAR decline in coal is too steep but a slight decrease in coal emissions cannot be falsified.…”

Section: Ricementioning

confidence: 95%

Verifying Methane Inventories and Trends With Atmospheric Methane Data

Worden

Pandey

Zhang

et al. 2023

Preprint

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The 2015 Paris Climate Agreement and Global Methane Pledge formalized agreement for countries to report and reduce methane emissions to mitigate near-term climate change. Emission inventories generated through surface activity measurements are reported annually or bi-annually and evaluated periodically through a “Global Stocktake”. Emissions inverted from atmospheric data support evaluation of reported inventories, but their systematic use is stifled by spatially variable biases from prior errors combined with limited sensitivity of observations to emissions (smoothing error), as-well-as poorly characterized information content. Here, we demonstrate a Bayesian, optimal estimation (OE) algorithm for evaluating a state-of-the-art inventory (EDGAR v6.0) using satellite-based emissions from 2009 to 2018. The OE algorithm quantifies the information content (uncertainty reduction, sectoral attribution, spatial resolution) of the satellite-based emissions and disentangles the effect of smoothing error when comparing to an inventory. We find robust differences between satellite and EDGAR for total livestock, rice, and coal emissions: 14 ± 9, 12 ± 8, -11 ± 6 Tg CH4/yr respectively. EDGAR and satellite agree that livestock emissions are increasing (0.25 to 1.3 Tg CH4/ yr / yr), primarily in the Indo-Pakistan region, sub-tropical Africa, and the Brazilian arc of deforestation; East Asia rice emissions are also increasing, highlighting the importance of agriculture on the atmospheric methane growth rate. In contrast, low information content for the waste and fossil emission trends confounds comparison between EDGAR and satellite; increased sampling and spatial resolution of satellite observations are therefore needed to evaluate reported changes to emissions in these sectors.

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Observed changes in China’s methane emissions linked to policy drivers

Cited by 45 publications

References 41 publications

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

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

Estimation of Anthropogenic CH₄ and CO₂ Emissions in Taiyuan‐Jinzhong Region: One of the World's Largest Emission Hotspots

Verifying Methane Inventories and Trends With Atmospheric Methane Data

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Observed changes in China’s methane emissions linked to policy drivers

Cited by 45 publications

References 41 publications

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

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

Estimation of Anthropogenic CH4 and CO2 Emissions in Taiyuan‐Jinzhong Region: One of the World's Largest Emission Hotspots

Verifying Methane Inventories and Trends With Atmospheric Methane Data

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Product

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Estimation of Anthropogenic CH₄ and CO₂ Emissions in Taiyuan‐Jinzhong Region: One of the World's Largest Emission Hotspots