Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Estimates of power plant NOx emissions and lifetimes from OMI NO2 satellite retrievals
https://orcid.org/0000-0003-4150-9922
Abstract Isolated power plants with well characterized emissions serve as an ideal test case of methods to estimate emissions using satellite data. In this study we evaluate the Exponentially-Modified Gaussian (EMG) method and the box model method based on mass balance for estimating known NOx emissions from satellite retrievals made by the Ozone Monitoring Instrument (OMI). We consider 29 power plants in the USA which have large NOx plumes that do not overlap with other sources and which have emissions data from the Continuous Emission Monitoring System (CEMS). This enables us to identify constraints required by the methods, such as which wind data to use and how to calculate background values. We found that the lifetimes estimated by the methods are too short to be representative of the chemical lifetime. Instead, we introduce a separate lifetime parameter to account for the discrepancy between estimates using real data and those that theory would predict. In terms of emissions, the EMG method required averages from multiple years to give accurate results, whereas the box model method gave accurate results for individual ozone seasons.
Graphical abstract Display Omitted
Highlights Accurate estimations of power plant NOx emissions can be made with OMI data. Exponentially-Modified Gaussian fit needs multi-annual OMI averages. Box Model fit requires seasonal OMI averages for accurate estimates. Lifetimes are dominated by a mixed lifetime that does not represent chemical lifetime. Continuous Emission Monitoring System (CEMS) provides an excellent emissions test bed.
Estimates of power plant NOx emissions and lifetimes from OMI NO2 satellite retrievals
https://orcid.org/0000-0003-4150-9922
Abstract Isolated power plants with well characterized emissions serve as an ideal test case of methods to estimate emissions using satellite data. In this study we evaluate the Exponentially-Modified Gaussian (EMG) method and the box model method based on mass balance for estimating known NOx emissions from satellite retrievals made by the Ozone Monitoring Instrument (OMI). We consider 29 power plants in the USA which have large NOx plumes that do not overlap with other sources and which have emissions data from the Continuous Emission Monitoring System (CEMS). This enables us to identify constraints required by the methods, such as which wind data to use and how to calculate background values. We found that the lifetimes estimated by the methods are too short to be representative of the chemical lifetime. Instead, we introduce a separate lifetime parameter to account for the discrepancy between estimates using real data and those that theory would predict. In terms of emissions, the EMG method required averages from multiple years to give accurate results, whereas the box model method gave accurate results for individual ozone seasons.
Graphical abstract Display Omitted
Highlights Accurate estimations of power plant NOx emissions can be made with OMI data. Exponentially-Modified Gaussian fit needs multi-annual OMI averages. Box Model fit requires seasonal OMI averages for accurate estimates. Lifetimes are dominated by a mixed lifetime that does not represent chemical lifetime. Continuous Emission Monitoring System (CEMS) provides an excellent emissions test bed.
Estimates of power plant NOx emissions and lifetimes from OMI NO2 satellite retrievals
https://orcid.org/0000-0003-4150-9922
Abstract Isolated power plants with well characterized emissions serve as an ideal test case of methods to estimate emissions using satellite data. In this study we evaluate the Exponentially-Modified Gaussian (EMG) method and the box model method based on mass balance for estimating known NOx emissions from satellite retrievals made by the Ozone Monitoring Instrument (OMI). We consider 29 power plants in the USA which have large NOx plumes that do not overlap with other sources and which have emissions data from the Continuous Emission Monitoring System (CEMS). This enables us to identify constraints required by the methods, such as which wind data to use and how to calculate background values. We found that the lifetimes estimated by the methods are too short to be representative of the chemical lifetime. Instead, we introduce a separate lifetime parameter to account for the discrepancy between estimates using real data and those that theory would predict. In terms of emissions, the EMG method required averages from multiple years to give accurate results, whereas the box model method gave accurate results for individual ozone seasons.
Graphical abstract Display Omitted
Highlights Accurate estimations of power plant NOx emissions can be made with OMI data. Exponentially-Modified Gaussian fit needs multi-annual OMI averages. Box Model fit requires seasonal OMI averages for accurate estimates. Lifetimes are dominated by a mixed lifetime that does not represent chemical lifetime. Continuous Emission Monitoring System (CEMS) provides an excellent emissions test bed.
Estimates of power plant NOx emissions and lifetimes from OMI NO2 satellite retrievals
de Foy, Benjamin (Autor:in) / Lu, Zifeng (Autor:in) / Streets, David G. (Autor:in) / Lamsal, Lok N. (Autor:in) / Duncan, Bryan N. (Autor:in)
Atmospheric Environment ; 116 ; 1-11
26.05.2015
11 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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