Analyzing nitrogen oxides to carbon dioxide emission ratios from space: A case study of Matimba Power Station in South Africa. (April 2021)

• Record Type: Journal Article
• Authors: Hakkarainen, Janne; Szeląg, Monika E.; Ialongo, Iolanda; Retscher, Christian; Oda, Tomohiro; Crisp, David
• Is Part Of: Atmospheric environment. Volume 10(2021)
• Publication Date: 2021-04
• Subjects: Carbon dioxide -- Nitrogen oxides -- Orbiting Carbon Observatory -- TROPOspheric Monitoring Instrument -- Emission estimation -- Emission ratio -- Matimba power station
• DOI: 10.1016/j.aeaoa.2021.100110
• Languages: English
• ISSNs: 2590-1621

Abstract

Abstract: We describe a new methodology for deriving source-specific emission ratios of nitrogen oxides (NO x ) to carbon dioxide (CO2 ) from space-based TROPOspheric Monitoring Instrument (TROPOMI) and Orbiting Carbon Observatory-2 (OCO-2) observations. The approach is based on scaling the observed ratio along the OCO-2 track with simulated data, in order to obtain the NO x -to-CO2 emission ratio at the source. We analyze fourteen TROPOMI/OCO-2 collocations from near the Matimba coal-fired power station in South Africa. We obtain a mean NO x -to-CO2 emission ratio of 2 . 6 × 10 − 3 and standard deviation of 0 . 6 × 10 − 3 (or 23%). When applied to NO x emission estimates derived from TROPOMI data, we obtain annual CO2 emissions of 62, 60 and 58 kt/d for the years 2018, 2019 and 2020, respectively, with standard deviation of 20 kt/d (or 33%). These values are consistent with existing inventories such as the Open-source Data Inventory for Anthropogenic CO2 (ODIAC). The proposed method will also work ideally for new and upcoming satellite observations systems such as OCO-3, CO2M and GOSAT-GW. Highlights: A new methodology to derive source-specific NOx -to-CO2 emission ratios. The method is applied for TROPOMI and OCO-2 satellite observations. The mean emission ratio of (2.6 ± 0.6) × 10 −3 is obtained for Matimba Power Station. The annual CO2 emissions for Matimba are ~60 kt/d. The emission estimates are consistent with existing inventories such as ODIAC.