Articles | Volume 20, issue 20
https://doi.org/10.5194/acp-20-11855-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-20-11855-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Errors in top-down estimates of emissions using a known source
Wayne M. Angevine
CORRESPONDING AUTHOR
Cooperative Institute for Research in Environmental Sciences (CIRES),
University of Colorado, Boulder, Colorado, USA
NOAA Chemical Sciences Laboratory, Boulder, Colorado USA
Jeff Peischl
Cooperative Institute for Research in Environmental Sciences (CIRES),
University of Colorado, Boulder, Colorado, USA
NOAA Chemical Sciences Laboratory, Boulder, Colorado USA
Alice Crawford
Atmospheric Sciences Modeling Division, Air Resources Laboratory,
NOAA, College Park, MD, USA
Christopher P. Loughner
Atmospheric Sciences Modeling Division, Air Resources Laboratory,
NOAA, College Park, MD, USA
Cooperative Institute for Satellite Earth System Studies (CISESS)/Earth System Science Interdisciplinary Center (ESSIC), University of
Maryland, College Park, MD, USA
Ilana B. Pollack
Department of Atmospheric Science, Colorado State University, Ft. Collins, Colorado USA
Chelsea R. Thompson
Cooperative Institute for Research in Environmental Sciences (CIRES),
University of Colorado, Boulder, Colorado, USA
NOAA Chemical Sciences Laboratory, Boulder, Colorado USA
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Cited
11 citations as recorded by crossref.
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- A top-down estimation of subnational CO2 budget using a global high-resolution inverse model with data from regional surface networks L. Nayagam et al. 10.1088/1748-9326/ad0f74
- Assessing the bias and uncertainties in the aircraft mass balance technique for the determination of carbon dioxide emission rates K. Hajny et al. 10.1525/elementa.2022.00135
- Synthesis of Satellite and Surface Measurements, Model Results, and FRAPPÉ Study Findings to Assess the Impacts of Oil and Gas Emissions Reductions on Maximum Ozone in the Denver Metro and Northern Front Range Region in Colorado P. Reddy 10.1029/2023EA002917
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- Quantifying methane emissions from the global scale down to point sources using satellite observations of atmospheric methane D. Jacob et al. 10.5194/acp-22-9617-2022
- Nonlinear impacts of urban built environment on freight emissions T. Peng et al. 10.1016/j.trd.2024.104358
- Estimation of power plant SO2 emissions using the HYSPLIT dispersion model and airborne observations with plume rise ensemble runs T. Chai et al. 10.5194/acp-23-12907-2023
11 citations as recorded by crossref.
- Evaluation of simulated CO2 power plant plumes from six high-resolution atmospheric transport models D. Brunner et al. 10.5194/acp-23-2699-2023
- Passive-tracer modelling at super-resolution with Weather Research and Forecasting – Advanced Research WRF (WRF-ARW) to assess mass-balance schemes S. Fathi et al. 10.5194/gmd-16-5069-2023
- A top-down estimation of subnational CO2 budget using a global high-resolution inverse model with data from regional surface networks L. Nayagam et al. 10.1088/1748-9326/ad0f74
- Assessing the bias and uncertainties in the aircraft mass balance technique for the determination of carbon dioxide emission rates K. Hajny et al. 10.1525/elementa.2022.00135
- Synthesis of Satellite and Surface Measurements, Model Results, and FRAPPÉ Study Findings to Assess the Impacts of Oil and Gas Emissions Reductions on Maximum Ozone in the Denver Metro and Northern Front Range Region in Colorado P. Reddy 10.1029/2023EA002917
- Evaluating the impact of storage-and-release on aircraft-based mass-balance methodology using a regional air-quality model S. Fathi et al. 10.5194/acp-21-15461-2021
- Impacts of Spatial Resolution and XCO2 Precision on Satellite Capability for CO2 Plumes Detection Z. Li et al. 10.3390/s24061881
- Vertical distribution of tropospheric ozone and its sources of precursors over Beijing: Results from ∼ 20 years of ozonesonde measurements based on clustering analysis Y. Zeng et al. 10.1016/j.atmosres.2023.106610
- Quantifying methane emissions from the global scale down to point sources using satellite observations of atmospheric methane D. Jacob et al. 10.5194/acp-22-9617-2022
- Nonlinear impacts of urban built environment on freight emissions T. Peng et al. 10.1016/j.trd.2024.104358
- Estimation of power plant SO2 emissions using the HYSPLIT dispersion model and airborne observations with plume rise ensemble runs T. Chai et al. 10.5194/acp-23-12907-2023
Latest update: 20 Nov 2024
Short summary
Emissions of air pollutants must be known for a wide variety of applications. Different methods of estimating emissions often disagree substantially. In this study, we apply standard methods to a well-known source, a power plant. We explore the uncertainty implied by the different answers that come from the different methods, different samples taken over several years, and different pollutants. We find that the overall uncertainty of emissions estimates is about 30 %.
Emissions of air pollutants must be known for a wide variety of applications. Different methods...
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