Near-real-time estimation of fossil fuel CO2 emissions from China based on atmospheric observations on Hateruma and Yonaguni Islands, Japan

Author:

Tohjima YasunoriORCID,Niwa Yosuke,Patra Prabir K.,Mukai Hitoshi,Machida Toshinobu,Sasakawa Motoki,Tsuboi Kazuhiro,Saito Kazuyuki,Ito Akihiko

Abstract

AbstractWe developed a near-real-time estimation method for temporal changes in fossil fuel CO2(FFCO2) emissions from China for 3 months [January, February, March (JFM)] based on atmospheric CO2and CH4observations on Hateruma Island (HAT, 24.06° N, 123.81° E) and Yonaguni Island (YON, 24.47° N, 123.01° E), Japan. These two remote islands are in the downwind region of continental East Asia during winter because of the East Asian monsoon. Previous studies have revealed that monthly averages of synoptic-scale variability ratios of atmospheric CO2and CH4(ΔCO2/ΔCH4) observed at HAT and YON in JFM are sensitive to changes in continental emissions. From the analysis based on an atmospheric transport model with all components of CO2and CH4fluxes, we found that the ΔCO2/ΔCH4ratio was linearly related to the FFCO2/CH4emission ratio in China because calculating the variability ratio canceled out the transport influences. Using the simulated linear relationship, we converted the observed ΔCO2/ΔCH4ratios into FFCO2/CH4emission ratios in China. The change rates of the emission ratios for 2020–2022 were calculated relative to those for the preceding 9-year period (2011–2019), during which relatively stable ΔCO2/ΔCH4ratios were observed. These changes in the emission ratios can be read as FFCO2emission changes under the assumption of no interannual variations in CH4emissions and biospheric CO2fluxes for JFM. The resulting average changes in the FFCO2emissions in January, February, and March 2020 were 17 ± 8%, − 36 ± 7%, and − 12 ± 8%, respectively, (− 10 ± 9% for JFM overall) relative to 2011–2019. These results were generally consistent with previous estimates. The emission changes for January, February, and March were 18 ± 8%, − 2 ± 10%, and 29 ± 12%, respectively, in 2021 (15 ± 10% for JFM overall) and 20 ± 9%, − 3 ± 10%, and − 10 ± 9%, respectively, in 2022 (2 ± 9% for JFM overall). These results suggest that the FFCO2emissions from China rebounded to the normal level or set a new high record in early 2021 after a reduction during the COVID-19 lockdown. In addition, the estimated reduction in March 2022 might be attributed to the influence of a new wave of COVID-19 infections in Shanghai.

Funder

Ministry of the Environment, Japan

Publisher

Springer Science and Business Media LLC

Subject

General Earth and Planetary Sciences

Reference49 articles.

1. Bauwens M, Compernolle S, Stavrakou T, Muller J-F, van Gent J, Eskes H, Levelt PF, Van Der AR, Veefkind JP, Vlietinck J, Yu H, Zehner C (2020) Impact of coronavirus outbreak on NO2 pollution assessed using TROPOMI and OMI observations. Geophys Res Lett 47:e2020GL087978. https://doi.org/10.1029/2020GL087978

2. Buchwitz M, Reuter M, Noël S, Bramstedt K, Schneising O, Hilker M, Andrade BF, Bovensmann H, Burrows JP, Di Noia A, Boesch H, Wu L, Landgraf J, Aben I, Retscher C, O’Dell CW, Crisp D (2021) Can a regional-scale reduction of atmospheirc CO2 during the COVID-19 pandemic be detected from space? A case study for East China using satellite XCO2 retrievals. Atmos Meas Tech 14:2141–2166. https://doi.org/10.5194/amt-14-2141-2021

3. Friedlingstein P, Jones MW, O’Sullivan M, Andrew RM, Bakker DCE, Hauck J, Le Quéré C, Peters GP, Peters W, Pongratz J, Sitch S, Canadell JG, Ciais P, Jackson RB, Alin SR, Anthoni P, Bates NR, Becker M, Bellouin N, Bopp L, Chau TTTC, Chevallier F, Chini LP, Cronin M, Currie KI, Decharme B, Djeutchouang LM, Dou X, Evans W, Feely RA et al (2022) Glocal carbon budget 2021. Earth Syst Sci Data 14:1917–2005. https://doi.org/10.5194/essd-14-1917-2022

4. Gilfillan D, Marland G (2021) CDIAC-FF: global and national CO2 emissions from fossil fuel combustion and cement manufacture: 1751–2017. Earth Syst Sci Data 13:1667–1680. https://doi.org/10.5194/essd-13-1667-2021

5. Hirsch RM, Gilroy EJ (1984) Methods of fitting a straight line to data: examples in water resources. J Am Water Resour Assoc 20:705–711

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3