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Characterizing Regional-Scale Combustion Using Satellite Retrievals of CO, NO2 and CO2

Performance Evaluation for China’s Planned CO2-IPDA

International School of Software, Wuhan University, Wuhan 430079, China
Electronic Information School, Wuhan University, Wuhan 430079, China
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
Key Laboratory of Earthquake Geodesy, Institute of Seismology, China Earthquake Administration, Wuhan 430071, China
School of Environmental Science and Tourism, Nanyang Normal University, Wolong Road 1638, Nan Yang 473061, China
Authors to whom correspondence should be addressed.
Remote Sens. 2017, 9(8), 768;
Received: 15 June 2017 / Revised: 21 July 2017 / Accepted: 21 July 2017 / Published: 26 July 2017
(This article belongs to the Special Issue Remote Sensing of Greenhouse Gases)
Active remote sensing of atmospheric XCO2 has several advantages over existing passive remote sensors, including global coverage, a smaller footprint, improved penetration of aerosols, and night observation capabilities. China is planning to launch a multi-functional atmospheric observation satellite equipped with a CO2-IPDA (integrated path differential absorption Lidar) to measure columnar concentrations of atmospheric CO2 globally. As space and power are limited on the satellite, compromises have been made to accommodate other passive sensors. In this study, we evaluated the sensitivity of the system’s retrieval accuracy and precision to some critical parameters to determine whether the current configuration is adequate to obtain the desired results and whether any further compromises are possible. We then mapped the distribution of random errors across China and surrounding regions using pseudo-observations to explore the performance of the planned CO2-IPDA over these regions. We found that random errors of less than 0.3% can be expected for most regions of our study area, which will allow the provision of valuable data that will help researchers gain a deeper insight into carbon cycle processes and accurately estimate carbon uptake and emissions. However, in the areas where major anthropogenic carbon sources are located, and in coastal seas, random errors as high as 0.5% are predicted. This is predominantly due to the high concentrations of aerosols, which cause serious attenuation of returned signals. Novel retrieving methods must, therefore, be developed in the future to suppress interference from low surface reflectance and high aerosol loading. View Full-Text
Keywords: IPDA; atmospheric CO2; performance evaluation; remote sensing satellite IPDA; atmospheric CO2; performance evaluation; remote sensing satellite
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MDPI and ACS Style

Han, G.; Ma, X.; Liang, A.; Zhang, T.; Zhao, Y.; Zhang, M.; Gong, W. Performance Evaluation for China’s Planned CO2-IPDA. Remote Sens. 2017, 9, 768.

AMA Style

Han G, Ma X, Liang A, Zhang T, Zhao Y, Zhang M, Gong W. Performance Evaluation for China’s Planned CO2-IPDA. Remote Sensing. 2017; 9(8):768.

Chicago/Turabian Style

Han, Ge, Xin Ma, Ailin Liang, Tianhao Zhang, Yannan Zhao, Miao Zhang, and Wei Gong. 2017. "Performance Evaluation for China’s Planned CO2-IPDA" Remote Sensing 9, no. 8: 768.

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