Quantifying the Impact of COVID-19 Pandemic on the Spatiotemporal Changes of CO2 Concentrations in the Yangtze River Delta, China

被引:4
作者
Wang, Yanyu [1 ,2 ]
Huang, Cheng [1 ]
Hu, Xiao-Ming [3 ]
Wei, Chong [4 ]
An, Jingyu [1 ]
Yan, Rusha [1 ]
Liao, Wenling [1 ]
Tian, Junjie [1 ]
Wang, Hongli [1 ]
Duan, Yusen [5 ]
Liu, Qizhen [5 ]
Wang, Wei [6 ]
Ma, Qianli [7 ]
He, Qianshan [8 ,9 ]
Cheng, Tiantao [10 ,11 ]
Su, Hang [1 ,12 ]
Zhang, Renhe [2 ]
机构
[1] Shanghai Acad Environm Sci, State Environm Protect Key Lab Format & Prevent Ur, Shanghai, Peoples R China
[2] Fudan Univ, Inst Atmospher Sci, Dept Atmospher & Ocean Sci, Shanghai, Peoples R China
[3] Univ Oklahoma, Ctr Anal & Predict Storms, Norman, OK 73072 USA
[4] Chinese Acad Sci, Shanghai Carbon Data Res Ctr, CAS Key Lab Low Carbon Convers Sci & Engn, Shanghai Adv Res Inst, Shanghai, Peoples R China
[5] Shanghai Environm Monitoring Ctr, Shanghai, Peoples R China
[6] Chinese Acad Sci, Anhui Inst Opt & Fine Mech, Hefei Inst Phys Sci, Key Lab Environm Opt & Technol, Hefei, Peoples R China
[7] Zhejiang Linan Reg Background Natl Observat & Res, Hangzhou, Peoples R China
[8] Shanghai Meteorol Serv, Shanghai, Peoples R China
[9] Shanghai Key Lab Meteorol & Hlth, Shanghai, Peoples R China
[10] Shanghai Qi Zhi Inst, Shanghai, Peoples R China
[11] Inst Ecochongming SIEC, Shanghai, Peoples R China
[12] Max Planck Inst Chem, Multiphase Chem Dept, Mainz, Germany
基金
中国博士后科学基金;
关键词
regional model; CO2; simulation; COVID-19; pandemic; WRF-VPRM; anthropogenic emission reduction; FOSSIL-FUEL CO2; ATMOSPHERIC BOUNDARY-LAYER; VERTICAL-DISTRIBUTION; MODELING SYSTEM; EMISSIONS; TRANSPORT; UNCERTAINTIES; SIMULATIONS; INVENTORY; ERRORS;
D O I
10.1029/2023JD038512
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
While the reduction in anthropogenic emissions due to Coronavirus disease 2019 (COVID-19) lockdown in China and its impact on air quality have been reported extensively, its impact on ambient carbon dioxide (CO2) concentrations is still yet to be assessed. In this study, the impact of emission reductions on spatiotemporal changes of CO2 concentrations during the COVID-19 pandemic was quantified in the Yangtze River Delta region (YRD), using high-resolution dynamic emission inventory and the Weather Research and Forecasting model coupled with the Vegetation Photosynthesis and Respiration Model (WRF-VPRM). The simulated CO2 concentrations from dynamic emission inventory shows a better agreement with surface observations compared with the Open-source Data Inventory for Anthropogenic CO2 and Emission Database for Global Atmospheric Research emission, providing confidence in the quantification of CO2 concentrations variations. Our results show that emission reductions during the COVID-19 pandemic lead to a CO2 decrease by 4.6 ppmv (-1.1%) in Shanghai and 3.1 ppmv (-0.7%) in YRD region. For the column-averaged CO2 concentrations (denoted as XCO2), it also decreases by 0.20 ppmv (-0.05%) in Shanghai and 0.15 ppmv (-0.04%) in YRD region. Furthermore, emission reductions from transportation and industry are major contributors to the decline in CO2 concentrations at the near surface, accounting for 45.8% (41.1%) and 34.9% (41.0%) in Shanghai (YRD). Our study deepens the understanding of the response of CO2 concentrations to different sectors, which is helpful for emission management and climate adaption policies.
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页数:17
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