825 citations · 1.2k across the 10 of their papers we have counts for
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Reconstructing Global Daily CO2 Emissions via Machine Learning
Tao Li, Lixing Wang, Zihan Qiu +9
High temporal resolution CO2 emission data are crucial for understanding the drivers of emission changes, however, current emission dataset is only available on a yearly basis. Her…
Global Gridded Daily CO Emissions
Xinyu Dou, Yilong Wang, Philippe Ciais +15
Precise and high-resolution carbon dioxide (CO) emission data is of great importance of achieving the carbon neutrality around the world. Here we present for the first time the…
Global Daily CO emissions for the year 2020
Zhu Liu, Zhu Deng, Philippe Ciais +25
The diurnal cycle CO emissions from fossil fuel combustion and cement production reflect seasonality, weather conditions, working days, and more recently the impact of the COVI…
De-carbonization of global energy use during the COVID-19 pandemic
Zhu Liu, Biqing Zhu, Philippe Ciais +15
The COVID-19 pandemic has disrupted human activities, leading to unprecedented decreases in both global energy demand and GHG emissions. Yet a little known that there is also a low…
Estimates of daily ground-level NO2 concentrations in China based on big data and machine learning approaches
Xinyu Dou, Cuijuan Liao, Hengqi Wang +11
Nitrogen dioxide (NO2) is one of the most important atmospheric pollutants. However, current ground-level NO2 concentration data are lack of either high-resolution coverage or full…