Assessment of thermal power plant CO emissions quantification performance and uncertainty of measurements by ground-based remote sensing.

Environ Pollut

Anhui Institute of Optics and Fine Mechanics, Hefei Institute of Physical Science, Chinese Academy of Sciences, Hefei, 230031, China; University of Science and Technology of China, Hefei, 230026, China; Key Laboratory of General Optical Calibration and Characterization Technology, Hefei Institutes o

Published: November 2024


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Article Abstract

Thermal power plants serve as significant CO sources, and accurate monitoring of their emissions is crucial for improving the precision of global carbon emission estimates. In this study, a measurement method based on measuring point source plumes was employed in ground-based remote sensing experiments at the thermal power plant. By simulating CO plumes, we analyzed the impact of surrounding urban structures, the geometric relationship between measurement points and plumes, and the influence on measurement points selection. We also assessed the capability and uncertainties in quantifying CO emissions. For the Hefei power plant, CO emission estimates were on average 7.98 ± 10.01 kg/s higher with surface buildings compared to scenarios without buildings (approximately 4.09% error). By selectively filtering discrete data, the emission estimation errors were significantly reduced by 7.31 ± 7.13 kg/s compared to pre-filtered data. Regarding the relationship between observation paths and plume geometry, simulation studies indicated that the ability to estimate CO emissions varied for near and middle segment observations. The lowest emission rate error was found in the mid-segment near 1.5-2.0 km, reaching 7.13 ± 5.39 kg/s. CO distribution at the mid-segment position becomes more uniform relative to the near segment, making it more suitable for meeting emission estimation requirements. Optimizing measurement schemes by considering environmental factors and precisely selecting measurement points significantly enhances emission estimation accuracy, providing crucial technical support for top-down estimates of anthropogenic CO emissions.

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http://dx.doi.org/10.1016/j.envpol.2024.124886DOI Listing

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