Analyzing nitrogen oxides to carbon dioxide emission ratios from space: A case study of Matimba Power Station in South Africa
We describe a new methodology for deriving source-specific emission ratios of nitrogen oxides (NOx) 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...
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Published in | Atmospheric Environment: X Vol. 10; p. 100110 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
Elsevier Ltd
01.04.2021
Elsevier |
Subjects | |
Online Access | Get full text |
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Summary: | We describe a new methodology for deriving source-specific emission ratios of nitrogen oxides (NOx) 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 NOx-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 NOx-to-CO2 emission ratio of 2.6×10−3 and standard deviation of 0.6×10−3 (or 23%). When applied to NOx 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.
•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. |
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ISSN: | 2590-1621 2590-1621 |
DOI: | 10.1016/j.aeaoa.2021.100110 |