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Industrial point source CO(2) emission strength estimation with aircraft measurements and dispersion modelling
CO(2) remains the greenhouse gas that contributes most to anthropogenic global warming, and the evaluation of its emissions is of major interest to both research and regulatory purposes. Emission inventories generally provide quite reliable estimates of CO(2) emissions. However, because of intrinsic...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5823952/ https://www.ncbi.nlm.nih.gov/pubmed/29470656 http://dx.doi.org/10.1007/s10661-018-6531-8 |
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author | Carotenuto, Federico Gualtieri, Giovanni Miglietta, Franco Riccio, Angelo Toscano, Piero Wohlfahrt, Georg Gioli, Beniamino |
author_facet | Carotenuto, Federico Gualtieri, Giovanni Miglietta, Franco Riccio, Angelo Toscano, Piero Wohlfahrt, Georg Gioli, Beniamino |
author_sort | Carotenuto, Federico |
collection | PubMed |
description | CO(2) remains the greenhouse gas that contributes most to anthropogenic global warming, and the evaluation of its emissions is of major interest to both research and regulatory purposes. Emission inventories generally provide quite reliable estimates of CO(2) emissions. However, because of intrinsic uncertainties associated with these estimates, it is of great importance to validate emission inventories against independent estimates. This paper describes an integrated approach combining aircraft measurements and a puff dispersion modelling framework by considering a CO(2) industrial point source, located in Biganos, France. CO(2) density measurements were obtained by applying the mass balance method, while CO(2) emission estimates were derived by implementing the CALMET/CALPUFF model chain. For the latter, three meteorological initializations were used: (i) WRF-modelled outputs initialized by ECMWF reanalyses; (ii) WRF-modelled outputs initialized by CFSR reanalyses and (iii) local in situ observations. Governmental inventorial data were used as reference for all applications. The strengths and weaknesses of the different approaches and how they affect emission estimation uncertainty were investigated. The mass balance based on aircraft measurements was quite succesful in capturing the point source emission strength (at worst with a 16% bias), while the accuracy of the dispersion modelling, markedly when using ECMWF initialization through the WRF model, was only slightly lower (estimation with an 18% bias). The analysis will help in highlighting some methodological best practices that can be used as guidelines for future experiments. |
format | Online Article Text |
id | pubmed-5823952 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-58239522018-02-28 Industrial point source CO(2) emission strength estimation with aircraft measurements and dispersion modelling Carotenuto, Federico Gualtieri, Giovanni Miglietta, Franco Riccio, Angelo Toscano, Piero Wohlfahrt, Georg Gioli, Beniamino Environ Monit Assess Article CO(2) remains the greenhouse gas that contributes most to anthropogenic global warming, and the evaluation of its emissions is of major interest to both research and regulatory purposes. Emission inventories generally provide quite reliable estimates of CO(2) emissions. However, because of intrinsic uncertainties associated with these estimates, it is of great importance to validate emission inventories against independent estimates. This paper describes an integrated approach combining aircraft measurements and a puff dispersion modelling framework by considering a CO(2) industrial point source, located in Biganos, France. CO(2) density measurements were obtained by applying the mass balance method, while CO(2) emission estimates were derived by implementing the CALMET/CALPUFF model chain. For the latter, three meteorological initializations were used: (i) WRF-modelled outputs initialized by ECMWF reanalyses; (ii) WRF-modelled outputs initialized by CFSR reanalyses and (iii) local in situ observations. Governmental inventorial data were used as reference for all applications. The strengths and weaknesses of the different approaches and how they affect emission estimation uncertainty were investigated. The mass balance based on aircraft measurements was quite succesful in capturing the point source emission strength (at worst with a 16% bias), while the accuracy of the dispersion modelling, markedly when using ECMWF initialization through the WRF model, was only slightly lower (estimation with an 18% bias). The analysis will help in highlighting some methodological best practices that can be used as guidelines for future experiments. Springer International Publishing 2018-02-22 2018 /pmc/articles/PMC5823952/ /pubmed/29470656 http://dx.doi.org/10.1007/s10661-018-6531-8 Text en © The Author(s) 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Article Carotenuto, Federico Gualtieri, Giovanni Miglietta, Franco Riccio, Angelo Toscano, Piero Wohlfahrt, Georg Gioli, Beniamino Industrial point source CO(2) emission strength estimation with aircraft measurements and dispersion modelling |
title | Industrial point source CO(2) emission strength estimation with aircraft measurements and dispersion modelling |
title_full | Industrial point source CO(2) emission strength estimation with aircraft measurements and dispersion modelling |
title_fullStr | Industrial point source CO(2) emission strength estimation with aircraft measurements and dispersion modelling |
title_full_unstemmed | Industrial point source CO(2) emission strength estimation with aircraft measurements and dispersion modelling |
title_short | Industrial point source CO(2) emission strength estimation with aircraft measurements and dispersion modelling |
title_sort | industrial point source co(2) emission strength estimation with aircraft measurements and dispersion modelling |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5823952/ https://www.ncbi.nlm.nih.gov/pubmed/29470656 http://dx.doi.org/10.1007/s10661-018-6531-8 |
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