2020, Liu, Zhu, Ciais, Philippe, Deng, Zhu, Lei, Ruixue, Davis, Steven J., Feng, Sha, Zheng, Bo, Cui, Duo, Dou, Xinyu, Zhu, Biqing, Guo, Rui, Ke, Piyu, Sun, Taochun, Lu, Chenxi, He, Pan, Wang, Yuan, Yue, Xu, Wang, Yilong, Lei, Yadong, Zhou, Hao, Cai, Zhaonan, Wu, Yuhui, Guo, Runtao, Han, Tingxuan, Xue, Jinjun, Boucher, Olivier, Boucher, Eulalie, Chevallier, Frédéric, Tanaka, Katsumasa, Wei, Yiming, Zhong, Haiwang, Kang, Chongqing, Zhang, Ning, Chen, Bin, Xi, Fengming, Liu, Miaomiao, Bréon, François-Marie, Lu, Yonglong, Zhang, Qiang, Guan, Dabo, Gong, Peng, Kammen, Daniel M., He, Kebin, Schellnhuber, Hans Joachim

The COVID-19 pandemic is impacting human activities, and in turn energy use and carbon dioxide (CO2) emissions. Here we present daily estimates of country-level CO2 emissions for different sectors based on near-real-time activity data. The key result is an abrupt 8.8% decrease in global CO2 emissions (−1551 Mt CO2) in the first half of 2020 compared to the same period in 2019. The magnitude of this decrease is larger than during previous economic downturns or World War II. The timing of emissions decreases corresponds to lockdown measures in each country. By July 1st, the pandemic’s effects on global emissions diminished as lockdown restrictions relaxed and some economic activities restarted, especially in China and several European countries, but substantial differences persist between countries, with continuing emission declines in the U.S. where coronavirus cases are still increasing substantially.

2021, Zheng, Heran, Többen, Johannes, Dietzenbacher, Erik, Moran, Daniel, Meng, Jing, Wang, Daoping, Guan, Dabo

Cities are pivotal hubs of socioeconomic activities, and consumption in cities contributes to global environmental pressures. Compiling city-level multi-regional input-output (MRIO) tables is challenging due to the scarcity of city-level data. Here we propose an entropy-based framework to construct city-level MRIO tables. We demonstrate the new construction method and present an analysis of the carbon footprint of cities in China's Hebei province. A sensitivity analysis is conducted by introducing a weight reflecting the heterogeneity between city and province data, as an important source of uncertainty is the degree to which cities and provinces have an identical ratio of intermediate demand to total demand. We compare consumption-based emissions generated from the new MRIO to results of the MRIO based on individual city input-output tables. The findings reveal a large discrepancy in consumption-based emissions between the two MRIO tables but this is due to conflicting benchmark data used in the two tables.