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Article: Near-real-time daily estimates of fossil fuel CO2 emissions from major high-emission cities in China

TitleNear-real-time daily estimates of fossil fuel CO<inf>2</inf> emissions from major high-emission cities in China
Authors
Issue Date2022
Citation
Scientific Data, 2022, v. 9, n. 1, article no. 684 How to Cite?
AbstractCities in China are on the frontline of low-carbon transition which requires monitoring city-level emissions with low-latency to support timely climate actions. Most existing CO2 emission inventories lag reality by more than one year and only provide annual totals. To improve the timeliness and temporal resolution of city-level emission inventories, we present Carbon Monitor Cities-China (CMCC), a near-real-time dataset of daily CO2 emissions from fossil fuel and cement production for 48 major high-emission cities in China. This dataset provides territory-based emission estimates from 2020-01-01 to 2021-12-31 for five sectors: power generation, residential (buildings and services), industry, ground transportation, and aviation. CMCC is developed based on an innovative framework that integrates bottom-up inventory construction and daily emission estimates from sectoral activities and models. Annual emissions show reasonable agreement with other datasets, and uncertainty ranges are estimated for each city and sector. CMCC provides valuable daily emission estimates that enable low-latency mitigation monitoring for cities in China.
Persistent Identifierhttp://hdl.handle.net/10722/334880

 

DC FieldValueLanguage
dc.contributor.authorHuo, Da-
dc.contributor.authorLiu, Kai-
dc.contributor.authorLiu, Jianwu-
dc.contributor.authorHuang, Yingjian-
dc.contributor.authorSun, Taochun-
dc.contributor.authorSun, Yun-
dc.contributor.authorSi, Caomingzhe-
dc.contributor.authorLiu, Jinjie-
dc.contributor.authorHuang, Xiaoting-
dc.contributor.authorQiu, Jian-
dc.contributor.authorWang, Haijin-
dc.contributor.authorCui, Duo-
dc.contributor.authorZhu, Biqing-
dc.contributor.authorDeng, Zhu-
dc.contributor.authorKe, Piyu-
dc.contributor.authorShan, Yuli-
dc.contributor.authorBoucher, Olivier-
dc.contributor.authorDannet, Grégoire-
dc.contributor.authorLiang, Gaoqi-
dc.contributor.authorZhao, Junhua-
dc.contributor.authorChen, Lei-
dc.contributor.authorZhang, Qian-
dc.contributor.authorCiais, Philippe-
dc.contributor.authorZhou, Wenwen-
dc.contributor.authorLiu, Zhu-
dc.date.accessioned2023-10-20T06:51:24Z-
dc.date.available2023-10-20T06:51:24Z-
dc.date.issued2022-
dc.identifier.citationScientific Data, 2022, v. 9, n. 1, article no. 684-
dc.identifier.urihttp://hdl.handle.net/10722/334880-
dc.description.abstractCities in China are on the frontline of low-carbon transition which requires monitoring city-level emissions with low-latency to support timely climate actions. Most existing CO2 emission inventories lag reality by more than one year and only provide annual totals. To improve the timeliness and temporal resolution of city-level emission inventories, we present Carbon Monitor Cities-China (CMCC), a near-real-time dataset of daily CO2 emissions from fossil fuel and cement production for 48 major high-emission cities in China. This dataset provides territory-based emission estimates from 2020-01-01 to 2021-12-31 for five sectors: power generation, residential (buildings and services), industry, ground transportation, and aviation. CMCC is developed based on an innovative framework that integrates bottom-up inventory construction and daily emission estimates from sectoral activities and models. Annual emissions show reasonable agreement with other datasets, and uncertainty ranges are estimated for each city and sector. CMCC provides valuable daily emission estimates that enable low-latency mitigation monitoring for cities in China.-
dc.languageeng-
dc.relation.ispartofScientific Data-
dc.titleNear-real-time daily estimates of fossil fuel CO<inf>2</inf> emissions from major high-emission cities in China-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1038/s41597-022-01796-3-
dc.identifier.pmid36357411-
dc.identifier.scopuseid_2-s2.0-85141550708-
dc.identifier.volume9-
dc.identifier.issue1-
dc.identifier.spagearticle no. 684-
dc.identifier.epagearticle no. 684-
dc.identifier.eissn2052-4463-

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