Uncertainty propagation of meteorological and emission data in modeling pollutant dispersion in the atmosphere
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| Natura: | Artículo científico |
| Lingua: | en |
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Universidad Nacional de Colombia
2014
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| _version_ | 1876447329796489216 |
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| author | S. Diez |
| author_facet | S. Diez |
| contents | Uncertainty propagation of meteorological and emission data in modeling pollutant dispersion in the atmosphere S. Diez E. Barra F. Crespo J. Britch Ingeniería PM10 Uncertainty Variability Monte Carlo Variability is true heterogeneity existing within a population that cannot be reduced or eliminated by more or better determi natio ns. Uncertainty represents ignorance about poorly characterized phenomena, but it can be reduced by collecting more data. The aim of this paper was to study the impact of the variability and uncertainty of the main variables, i.e., emissions and meteorolog y, of the PM10 concentration caused by a point source located at Malagueño (Córdoba, Argentina). To perform this analysis , a scheme was developed using the USEPA Industrial Source Complex model algorithms with a Monte Carlo methodology. Using a simulation with one hundred thousand iterations, the concentration distribution was obtained and show ed that the uncertainty in wind direction had the greatest impact on the estimates. 2014 artículo científico 0120-5609 https://www.redalyc.org/articulo.oa?id=64331837009 en http://www.redalyc.org/revista.oa?id=643 Ingeniería e Investigación application/pdf Universidad Nacional de Colombia Ingeniería e Investigación (Colombia) Num.2 Vol.34 |
| format | Artículo científico |
| id | redalyc_64331837009 |
| institution | Redalyc |
| language | en |
| publishDate | 2014 |
| publisher | Universidad Nacional de Colombia |
| spellingShingle | Uncertainty propagation of meteorological and emission data in modeling pollutant dispersion in the atmosphere S. Diez Ingeniería PM10 Uncertainty Variability Monte Carlo Uncertainty propagation of meteorological and emission data in modeling pollutant dispersion in the atmosphere S. Diez E. Barra F. Crespo J. Britch Ingeniería PM10 Uncertainty Variability Monte Carlo Variability is true heterogeneity existing within a population that cannot be reduced or eliminated by more or better determi natio ns. Uncertainty represents ignorance about poorly characterized phenomena, but it can be reduced by collecting more data. The aim of this paper was to study the impact of the variability and uncertainty of the main variables, i.e., emissions and meteorolog y, of the PM10 concentration caused by a point source located at Malagueño (Córdoba, Argentina). To perform this analysis , a scheme was developed using the USEPA Industrial Source Complex model algorithms with a Monte Carlo methodology. Using a simulation with one hundred thousand iterations, the concentration distribution was obtained and show ed that the uncertainty in wind direction had the greatest impact on the estimates. 2014 artículo científico 0120-5609 https://www.redalyc.org/articulo.oa?id=64331837009 en http://www.redalyc.org/revista.oa?id=643 Ingeniería e Investigación application/pdf Universidad Nacional de Colombia Ingeniería e Investigación (Colombia) Num.2 Vol.34 |
| title | Uncertainty propagation of meteorological and emission data in modeling pollutant dispersion in the atmosphere |
| topic | Ingeniería PM10 Uncertainty Variability Monte Carlo |
| url | https://www.redalyc.org/articulo.oa?id=64331837009 |