Marzio Invernizzi, Francesca Tagliaferri, Selena Sironi, Gianni Tinarelli, Laura Capelli
{"title":"模拟意外火灾中污染物的扩散,重点是源表征。","authors":"Marzio Invernizzi, Francesca Tagliaferri, Selena Sironi, Gianni Tinarelli, Laura Capelli","doi":"10.5696/2156-9614-11.30.210612","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Storage tanks in oil and gas processing facilities contain large volumes of flammable compounds. Once the fuel-air mixture is ignited, it may break out into a large fire or explosion. The growing interest in monitoring air quality and assessing health risks makes the evaluation of the consequences of a fire an important issue. Atmospheric dispersion models, which allow for simulation of the spatial distribution of pollutants, represent an increasingly widespread tool for this type of evaluations.</p><p><strong>Objectives: </strong>The present study discusses the set up and results of a modeling study relevant to a hypothesized fire in an oil refinery.</p><p><strong>Methods: </strong>After choosing the most suitable dispersion models, i.e. the Lagrangian model SPRAY and the puff model CALPUFF, estimation of the required input data is discussed, focusing on the source variables, which represent the most uncertain input data. The results of the simulations were compared to regulatory limits to effectively evaluate the environmental consequences. Finally, a sensitivity analysis was employed to identify the most influential variables.</p><p><strong>Results: </strong>The simulation results revealed that ground concentration values were far below the cited long-term limits. However, the most interesting outcome is that depending on the dispersion model and the source type modeled, different results may be obtained. In addition, the sensitivity study indicates that the source area is the most critical variable, since it determines a significantly different behavior depending on the modeled source types, producing, in some cases, variability in the pollutant ground concentrations on selected receptors up to +/- 60%.</p><p><strong>Conclusions: </strong>Depending on the selected model and the algorithms available to describe the physics of emission, the results showed a different sensitivity to the input variables. Although this can be explained from a mathematical point of view, the problem remains of choosing case by case the option that best approximates the real behavior of the incidental source under investigation.</p><p><strong>Competing interests: </strong>The authors declare no competing financial interests.</p>","PeriodicalId":52138,"journal":{"name":"Journal of Health and Pollution","volume":null,"pages":null},"PeriodicalIF":2.4000,"publicationDate":"2021-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8276722/pdf/","citationCount":"2","resultStr":"{\"title\":\"Simulating Pollutant Dispersion from Accidental Fires with a Focus on Source Characterization.\",\"authors\":\"Marzio Invernizzi, Francesca Tagliaferri, Selena Sironi, Gianni Tinarelli, Laura Capelli\",\"doi\":\"10.5696/2156-9614-11.30.210612\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Storage tanks in oil and gas processing facilities contain large volumes of flammable compounds. Once the fuel-air mixture is ignited, it may break out into a large fire or explosion. The growing interest in monitoring air quality and assessing health risks makes the evaluation of the consequences of a fire an important issue. Atmospheric dispersion models, which allow for simulation of the spatial distribution of pollutants, represent an increasingly widespread tool for this type of evaluations.</p><p><strong>Objectives: </strong>The present study discusses the set up and results of a modeling study relevant to a hypothesized fire in an oil refinery.</p><p><strong>Methods: </strong>After choosing the most suitable dispersion models, i.e. the Lagrangian model SPRAY and the puff model CALPUFF, estimation of the required input data is discussed, focusing on the source variables, which represent the most uncertain input data. The results of the simulations were compared to regulatory limits to effectively evaluate the environmental consequences. Finally, a sensitivity analysis was employed to identify the most influential variables.</p><p><strong>Results: </strong>The simulation results revealed that ground concentration values were far below the cited long-term limits. However, the most interesting outcome is that depending on the dispersion model and the source type modeled, different results may be obtained. In addition, the sensitivity study indicates that the source area is the most critical variable, since it determines a significantly different behavior depending on the modeled source types, producing, in some cases, variability in the pollutant ground concentrations on selected receptors up to +/- 60%.</p><p><strong>Conclusions: </strong>Depending on the selected model and the algorithms available to describe the physics of emission, the results showed a different sensitivity to the input variables. Although this can be explained from a mathematical point of view, the problem remains of choosing case by case the option that best approximates the real behavior of the incidental source under investigation.</p><p><strong>Competing interests: </strong>The authors declare no competing financial interests.</p>\",\"PeriodicalId\":52138,\"journal\":{\"name\":\"Journal of Health and Pollution\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2021-06-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8276722/pdf/\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Health and Pollution\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5696/2156-9614-11.30.210612\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2021/6/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q1\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Health and Pollution","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5696/2156-9614-11.30.210612","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2021/6/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"Medicine","Score":null,"Total":0}
Simulating Pollutant Dispersion from Accidental Fires with a Focus on Source Characterization.
Background: Storage tanks in oil and gas processing facilities contain large volumes of flammable compounds. Once the fuel-air mixture is ignited, it may break out into a large fire or explosion. The growing interest in monitoring air quality and assessing health risks makes the evaluation of the consequences of a fire an important issue. Atmospheric dispersion models, which allow for simulation of the spatial distribution of pollutants, represent an increasingly widespread tool for this type of evaluations.
Objectives: The present study discusses the set up and results of a modeling study relevant to a hypothesized fire in an oil refinery.
Methods: After choosing the most suitable dispersion models, i.e. the Lagrangian model SPRAY and the puff model CALPUFF, estimation of the required input data is discussed, focusing on the source variables, which represent the most uncertain input data. The results of the simulations were compared to regulatory limits to effectively evaluate the environmental consequences. Finally, a sensitivity analysis was employed to identify the most influential variables.
Results: The simulation results revealed that ground concentration values were far below the cited long-term limits. However, the most interesting outcome is that depending on the dispersion model and the source type modeled, different results may be obtained. In addition, the sensitivity study indicates that the source area is the most critical variable, since it determines a significantly different behavior depending on the modeled source types, producing, in some cases, variability in the pollutant ground concentrations on selected receptors up to +/- 60%.
Conclusions: Depending on the selected model and the algorithms available to describe the physics of emission, the results showed a different sensitivity to the input variables. Although this can be explained from a mathematical point of view, the problem remains of choosing case by case the option that best approximates the real behavior of the incidental source under investigation.
Competing interests: The authors declare no competing financial interests.
期刊介绍:
The Journal of Health and Pollution (JH&P) was initiated with funding from the European Union and World Bank and continues to be a Platinum Open Access Journal. There are no publication or viewing charges. That is, there are no charges to readers or authors. Upon peer-review and acceptance, all articles are made available online. The high-ranking editorial board is comprised of active members who participate in JH&P submissions and editorial policies. The Journal of Health and Pollution welcomes manuscripts based on original research as well as findings from re-interpretation and examination of existing data. JH&P focuses on point source pollution, related health impacts, environmental control and remediation technology. JH&P also has an interest in ambient and indoor pollution. Pollutants of particular interest include heavy metals, pesticides, radionuclides, dioxins, polychlorinated biphenyls (PCBs), polycyclic aromatic hydrocarbons (PAHs), volatile organic compounds (VOCs), air particulates (PM10 and PM2.5), and other severe and persistent toxins. JH&P emphasizes work relating directly to low and middle-income countries, however relevant work relating to high-income countries will be considered on a case-by-case basis.