环境科学
卫星
污染
跟踪(教育)
大气科学
数据同化
碳循环
遥感
气象学
工程类
地理
生态系统
教育学
生物
地质学
航空航天工程
生态学
心理学
作者
Donghao Fan,Tianhai Cheng,Hao Zhu,Xiaotong Ye,Tao Tang,Haoran Tong,Xingyu Li,Lili Zhang
标识
DOI:10.1021/acs.est.5c01100
摘要
The potential of satellite-based CO2 emission estimation from power plants is gaining increasing attention. However, the limited spatiotemporal coverage of current satellite-derived XCO2 data poses significant challenges to tracking CO2 variations on a large scale and over extended periods. In view of this, this study uses satellite-derived NO2 data as a suitable proxy and tracks CO2 emissions from 38 selected power plants globally by integrating near-synchronously observed TROPOMI NO2 data and OCO-2 XCO2 data. The results show that our method significantly increases the effective observation frequency by almost 200 times compared to using OCO-2 data alone. Compared to the emissions reported by the power plants, the correlation coefficient of the method used in this study (0.78) is higher than that of the emission inventory estimates (0.43-0.62), resulting in an accuracy improvement of approximately 1.8-2.3 Mt/yr per power plant. The use of satellite-derived NO2 data significantly enhances the ability to remotely estimate CO2 emissions from power plants, which gives us confidence in studying anthropogenic point-source CO2 emissions across different spatial and temporal scales. This enhances the understanding of their variability and mitigation potential, supporting the development of refined carbon inventories and advanced carbon cycle assimilation systems.
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