Published January 2021 | Version v1
Journal article

Assessing the recent impact of COVID-19 on carbon emissions from China using domestic economic data

  • 1. State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing (China)
  • 2. Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD (United States)
  • 3. Department of Atmospheric and Oceanic Science, University of Maryland, College Park, MD (United States)
  • 4. Goddard Earth Sciences Research and Technology, Universities Space Research Association, Columbia, MD (United States)
  • 5. Integrated Research for Energy, Environment and Society, Energy and Sustainability Research Institute Groningen, University of Groningen, Groningen 9747 AG (Netherlands)
  • 6. State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing (China)

Description

Highlights: • Provincial CO2 decreases for China are reported, and Hubei, the northern and eastern China provinces have obvious declines. • National total decrease is -257.7 Mt (-11.0%). Using GDP as an indicator, the method is easy to be applied in other regions. • Working from home and holding teleconferences reduce CO2 emissions. Our results serve as spatial constraints for modelers. The outbreak of coronavirus disease 2019 (COVID-19) has caused tremendous loss to human life and economic decline in China and worldwide. It has significantly reduced gross domestic product (GDP), power generation, industrial activity and transport volume; thus, it has reduced fossil-related and cement-induced carbon dioxide (CO2) emissions in China. Due to time delays in obtaining activity data, traditional emissions inventories generally involve a 2–3-year lag. However, a timely assessment of COVID-19's impact on provincial CO2 emission reductions is crucial for accurately understanding the reduction and its implications for mitigation measures; furthermore, this information can provide constraints for modeling studies. Here, we used national and provincial GDP data and the China Emission Accounts and Datasets (CEADs) inventory to estimate the emission reductions in the first quarter (Q1) of 2020. We find a reduction of 257.7 Mt. CO2 (11.0%) over Q1 2019. The secondary industry contributed 186.8 Mt. CO2 (72.5%) to the total reduction, largely due to lower coal consumption and cement production. At the provincial level, Hubei contributed the most to the reductions (40.6 Mt) due to a notable decrease of 48.2% in the secondary industry. Moreover, transportation significantly contributed (65.1 Mt), with a change of −22.3% in freight transport and −59.1% in passenger transport compared with Q1 2019. We used a point, line and area sources (PLAS) method to test the GDP method, producing a close estimate (reduction of 10.6%). One policy implication is a change in people's working style and communication methods, realized by working from home and holding teleconferences, to reduce traffic emissions. Moreover, GDP is found to have potential merit in estimating emission changes when detailed energy activity data are unavailable. We provide provincial data that can serve as spatial disaggregation constraints for modeling studies and further support for both the carbon cycle community and policy makers.

Availability note (English)

Available from http://dx.doi.org/10.1016/j.scitotenv.2020.141688

Additional details

Identifiers

DOI
10.1016/j.scitotenv.2020.141688;
PII
S0048969720352177;

Publishing Information

Journal Title
Science of the Total Environment
Journal Volume
750
Journal Page Range
vp.
ISSN
0048-9697
CODEN
STENDL

Optional Information

Copyright
Copyright (c) 2020 Elsevier B.V. All rights reserved.