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Improving the estimation of greenhouse gas emissions from the Chinese coal-to-electricity chain by a bottom-up approach
Resources, Conservation and Recycling ( IF 13.2 ) Pub Date : 2020-11-06 , DOI: 10.1016/j.resconrec.2020.105237
Junjie Li , Yajun Tian , Yelin Deng , Yueling Zhang , Kechang Xie

Accurately estimating greenhouse gas (GHG) emissions from the Chinese coal-to-electricity chain is critical to meet the global goal of carbon reduction, but the efforts in previous work based on statistical data were not ideal. Here, we ingeniously proposed an improved estimation method from a bottom-up perspective, integrating ten technical indicators affecting point-source GHG emissions from coal mines, coal transport routes, and coal power units. This method quantifies provincial GHG emission factors of the coal-to-electricity chain in 2016, varying greatly within 964-1232 g CO2eq / kWh, and explains for the first time how the micro technical indicators affect macro carbon emission levels. Our estimates have a higher spatial resolution and lower uncertainty than existing studies, which can well represent the status quo in different provinces. Based on these emission factors, the total GHG emissions from the Chinese the coal-to-electricity chain in 2016 are estimated at 4232 Mt CO2eq and being spatially intensive in northern and eastern China. They are expected to peak in 2025 according to current policy but in advance by 2019 if transformation is accelerated. The variation province by province suggests that carbon reduction strategies should be tailored to the local specific situation and overall coordinated across the country.

更新日期:2020-11-06
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