4.7 Article

Advances in quantifying power plant CO2 emissions with OCO-2

期刊

REMOTE SENSING OF ENVIRONMENT
卷 264, 期 -, 页码 -

出版社

ELSEVIER SCIENCE INC
DOI: 10.1016/j.rse.2021.112579

关键词

Orbiting Carbon Observatory 2 (OCO-2); Atmospheric remote sensing; Power plants; Spectroscopic observations; Anthropogenic emissions; Satellite remote sensing; CO(2 )emissions

资金

  1. JPL [1439002]
  2. Jet Propulsion Laboratory, California Institute of Technology

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Emission estimates for twenty power plants and related facilities from various countries based on NASA's OCO-2 satellite data show improved results from previous work due to enhancements in data quality and methodology. Discrepancies between estimated and reported emissions for US sites range from 1.4% to 26.7%, with an average difference of 15.1%, but the total estimated emissions for all US sites are within 0.8% of reported values.
We present CO(2 )emission estimates for twenty power plants and related facilities in the United States, India, South Africa, Poland, Russia and South Korea, derived from space-based CO2 observations from NASA's Orbiting Carbon Observatory 2 (OCO-2) satellite. Improvements to OCO-2 data quality and to our methodology yield improved results relative to earlier work. These new results include emission quantification for both larger and smaller power plants, the first power plant emission estimate based on ocean glint data and emissions from a small city with multiple industrial facilities. CO2 emission estimates are compared against reported facility emissions where available, including high temporal resolution data for the eight US sites. The difference with respect to reported values for the US sites ranges from 1.4% to 26.7%, with a mean of 15.1%, although the estimated emission sum for all US sites is within 0.8% of the reported value, suggesting the errors are largely random. This finding reinforces the importance of revisit rate for future space-based emission monitoring systems and furthermore confirms that making multiple overpasses of a power plant can reduce errors to an accuracy useful to support climate policy.

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