摘要
中国的二氧化碳减排工作一直承受着国际社会的压力.新型冠状病毒肺炎疫情(COVID-19,简称"新冠疫情")对全球碳排放产生了显著影响.准确估算新冠疫情对中国二氧化碳排放量及其排放趋势的影响,对评估中国对全球变化的贡献有重要意义.本研究系统构建了基于活动数据的中国省级日碳排放数据库,对涵盖了化石燃料燃烧和水泥生产造成的所有人为源二氧化碳排放进行定量化的动态评估.本研究发现中国各省的碳排放在新冠疫情期间受到不同程度的影响.江苏、湖北和浙江三省的碳排放受疫情影响最严重,其碳排放减少量分别占总排放减少量的19.4%、17.0%和12.5%.青海省和西藏自治区受疫情的影响最小.从排放部门方面看,电力部门是多数省份减排量的主要贡献源,对于湖北、重庆、青海和福建等省份,工业部门是碳减排的主要贡献源.对于北京、天津这样的大城市以及四川和黑龙江两省,新冠疫情对交通部门的减排作用最显著.从疫情对碳排放的时间影响看,江苏省的碳排放在2020年1和2月份下降最多,3月份之后,湖北省的碳排放减少量最为突出.而宁夏回族自治区、新疆维吾尔自治区、福建省、陕西省和云南省受疫情影响较小的地区3月份的碳排放已经率先恢复到2019年同期水平.进入4月份,除湖北省的碳排放相比2019年同期下降4.9 Mt二氧化碳外,其他省份均接近或已经恢复到2019年同期水平.
Assessing the impact of the COVID-19 pandemic on China’s carbon emissions is crucial for China to lead global climate change mitigation.However,thorough quantitative analyses of the pandemic’s effects on energy use and emissions are still lacking.This is largely because well-known published datasets of greenhouse gas emissions are based on annual statistics that commonly become available one or more years after they are gathered.A high temporal resolution emission dataset is critical to capture the immediate effects of an event such as the COVID-19 pandemic.Such an improved resolution might also allow policy makers to more quickly observe the effects of policies aimed at decreasing CO_(2)emissions,facilitating rapid adjustments.Here,based on a newly developed,near real-time global emission dataset,Carbon Monitor,we estimate China’s daily energy consumption and associated CO_(2)emissions and use this dataset to estimate the impact of COVID-19 on CO_(2)emission trends.Such a near-real-time CO_(2)emission database based on activity data quantifies both anthropogenic CO_(2)emissions from fossil fuel combustion and cement production.We show that the higher-resolution emission dataset can be used to assess the impact of COVID-19(and similar future disruptions)within a reasonable range of uncertainty.This study finds that China’s CO_(2)emissions in the first four months of 2020 decreased by 6.9%compared to the same period in 2019,with a total emission reduction of 234.5 million tons of CO_(2).The provinces of Jiangsu,Hubei,and Zhejiang were most severely affected by COVID-19,accounting for 19.4%,17.0%and 12.5%of the total reduction in CO_(2)emissions,respectively.The reduction of CO_(2)emissions from Shandong,Hebei,Anhui,Henan and Chongqing provinces is more than 10 Mt CO_(2),and the sum of the reduction from these five provinces accounts for 28.8%of the national total reductions.CO_(2)emissions in Yunnan Province,Gansu Province,Guangxi Zhuang Autonomous Region,Ningxia Hui Autonomous Region,Shaanxi Province and
作者
刘竹
崔夺
邓铸
汪宜龙
钟海旺
乐旭
张宁
陈彬
任小波
魏伟
吕永龙
姜克隽
窦新宇
朱碧青
郭睿
孙韬淳
柯丕煜
关大博
宫鹏
Zhu Liu;Duo Cui;Zhu Deng;Yilong Wang;Haiwang Zhong;Xu Yue;Ning Zhang;Bin Chen;Xiaobo Ren;Wei Wei;Yonglong Lü;Kejun Jiang;Xinyu Dou;Biqing Zhu;Rui Guo;Taochun Sun;Piyu Ke;Dabo Guan;Peng Gong(Department of Earth System Science,Tsinghua University,Beijing 100084,China;Key Laboratory of Land Surface Pattern and Simulation,Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences,Beijing 100101,China;Department of Electrical Engineering,Tsinghua University,Beijing 100084,China;School of Environment Science and Engineering,Nanjing University of Information Science and Technology,Nanjing 210044,China;Institute of Frontier and Interdisciplinary Science,Shandong University at Weihai,Weihai 264209,China;School of Environment,Beijing Normal University,Beijing 100875,China;Bureau of Major R&D Programs,Chinese Academy of Sciences,Beijing 100864,China;Shanghai Advanced Research Institute,Chinese Academy of Sciences,Shanghai 201203,China;State Key Laboratory of Urban and Regional Ecology,Research Center for Eco-Environmental Sciences,Chinese Academy of Sciences,Beijing 100085,China;Energy Research Institute,Academy of Macroeconomic Research,Beijing 100038,China)
出处
《科学通报》
EI
CAS
CSCD
北大核心
2021年第15期1912-1922,共11页
Chinese Science Bulletin
基金
国家自然科学基金(71874097,41921005)
北京市自然科学基金(JQ19032)
求是科技基金会项目资助。
关键词
新冠疫情
省级二氧化碳排放
日排放清单
全球变化
COVID-19 pandemic
provincial CO_(2) emission
daily emission inventory
global change
