三角洲
环境科学
排放清单
空气质量指数
大气科学
天气研究与预报模式
长江
中国
植被(病理学)
水文学(农业)
自然地理学
气候学
环境化学
气象学
地理
化学
医学
岩土工程
考古
病理
航空航天工程
地质学
工程类
作者
Yanyu Wang,Cheng Huang,Xiao‐Ming Hu,Chong Wei,Jingyu An,Rusha Yan,Wenling Liao,Jun Tian,Hongli Wang,Yusen Duan,Qizhen Liu,Wei Wang,Qiang Ma,Qiu He,Tiantao Cheng,Hang Su,Renhe Zhang
摘要
Abstract 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 (CO 2 ) concentrations is still yet to be assessed. In this study, the impact of emission reductions on spatiotemporal changes of CO 2 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 CO 2 concentrations from dynamic emission inventory shows a better agreement with surface observations compared with the Open‐source Data Inventory for Anthropogenic CO 2 and Emission Database for Global Atmospheric Research emission, providing confidence in the quantification of CO 2 concentrations variations. Our results show that emission reductions during the COVID‐19 pandemic lead to a CO 2 decrease by 4.6 ppmv (−1.1%) in Shanghai and 3.1 ppmv (−0.7%) in YRD region. For the column‐averaged CO 2 concentrations (denoted as XCO 2 ), 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 CO 2 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 CO 2 concentrations to different sectors, which is helpful for emission management and climate adaption policies.
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