Prediction of air pollutants concentrations from multiple sources using AERMOD coupled with WRF prognostic model.
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| Title: | Prediction of air pollutants concentrations from multiple sources using AERMOD coupled with WRF prognostic model. |
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| Authors: | Afzali, Afsaneh1,2 afzali_afsaneh@yahoo.com, Rashid, M.2 rashidyusof.kl@utm.my, Afzali, Mahboubeh3,4 afzali.mahboubeh@gmail.com, Younesi, Vahid5,6 vahid.unesi@aut.ac.ir |
| Source: | Journal of Cleaner Production. Nov2017, Vol. 166, p1216-1225. 10p. |
| Subjects: | Environmental protection, Air pollutants, Air quality management, Weather forecasting, Climate change |
| Geographic Terms: | Malaysia |
| Abstract: | The investigation of pollutants concentrations affected by the multiple sources is essential for air quality management. In this study, the spatial variations of SO 2 , NO 2 and PM 10 emitted from multiple industrial sources in Pasir Gudang industrial area, Johor, Malaysia were predicted using American Meteorological Society/Environmental Protection Regulatory Model (AERMOD) air dispersion model coupled with Weather Research and Forecasting (WRF). The WRF model was applied to simulate the hourly surface and upper air meteorological variables for the period of two weeks. The output parameters from WRF such as temperature, wind speed and wind direction were also statistically evaluated in the study. The results of comparing the wind roses from the observed and simulated data in Pasir Gudang station showed the difficulty of prognostic WRF model in predicting wind direction in Malaysia located in a coastal site. The results showed that the maximum ground level concentration of SO 2 , NO 2 and PM 10 simulated through AERMOD-WRF in the industrial area was 36.2, 59.8 and 5.4 μg/m 3 , respectively. The evaluation of AERMOD through the Quantile-Quantile (Q-Q) plots showed that most of the predicted and observed pair points are lying close to the one-to-one line indicating that there is a good agreement between predicted and observed concentrations in the study. The findings of this study can facilitate and assist the local government authorities and policy makers in managing the urban air quality. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Cleaner Production is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 125116935 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Prediction of air pollutants concentrations from multiple sources using AERMOD coupled with WRF prognostic model. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Afzali%2C+Afsaneh%22">Afzali, Afsaneh</searchLink><relatesTo>1,2</relatesTo><i> afzali_afsaneh@yahoo.com</i><br /><searchLink fieldCode="AR" term="%22Rashid%2C+M%2E%22">Rashid, M.</searchLink><relatesTo>2</relatesTo><i> rashidyusof.kl@utm.my</i><br /><searchLink fieldCode="AR" term="%22Afzali%2C+Mahboubeh%22">Afzali, Mahboubeh</searchLink><relatesTo>3,4</relatesTo><i> afzali.mahboubeh@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Younesi%2C+Vahid%22">Younesi, Vahid</searchLink><relatesTo>5,6</relatesTo><i> vahid.unesi@aut.ac.ir</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Journal+of+Cleaner+Production%22">Journal of Cleaner Production</searchLink>. Nov2017, Vol. 166, p1216-1225. 10p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Environmental+protection%22">Environmental protection</searchLink><br /><searchLink fieldCode="DE" term="%22Air+pollutants%22">Air pollutants</searchLink><br /><searchLink fieldCode="DE" term="%22Air+quality+management%22">Air quality management</searchLink><br /><searchLink fieldCode="DE" term="%22Weather+forecasting%22">Weather forecasting</searchLink><br /><searchLink fieldCode="DE" term="%22Climate+change%22">Climate change</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Malaysia%22">Malaysia</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The investigation of pollutants concentrations affected by the multiple sources is essential for air quality management. In this study, the spatial variations of SO 2 , NO 2 and PM 10 emitted from multiple industrial sources in Pasir Gudang industrial area, Johor, Malaysia were predicted using American Meteorological Society/Environmental Protection Regulatory Model (AERMOD) air dispersion model coupled with Weather Research and Forecasting (WRF). The WRF model was applied to simulate the hourly surface and upper air meteorological variables for the period of two weeks. The output parameters from WRF such as temperature, wind speed and wind direction were also statistically evaluated in the study. The results of comparing the wind roses from the observed and simulated data in Pasir Gudang station showed the difficulty of prognostic WRF model in predicting wind direction in Malaysia located in a coastal site. The results showed that the maximum ground level concentration of SO 2 , NO 2 and PM 10 simulated through AERMOD-WRF in the industrial area was 36.2, 59.8 and 5.4 μg/m 3 , respectively. The evaluation of AERMOD through the Quantile-Quantile (Q-Q) plots showed that most of the predicted and observed pair points are lying close to the one-to-one line indicating that there is a good agreement between predicted and observed concentrations in the study. The findings of this study can facilitate and assist the local government authorities and policy makers in managing the urban air quality. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Journal of Cleaner Production is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1016/j.jclepro.2017.07.196 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 10 StartPage: 1216 Subjects: – SubjectFull: Environmental protection Type: general – SubjectFull: Air pollutants Type: general – SubjectFull: Air quality management Type: general – SubjectFull: Weather forecasting Type: general – SubjectFull: Climate change Type: general – SubjectFull: Malaysia Type: general Titles: – TitleFull: Prediction of air pollutants concentrations from multiple sources using AERMOD coupled with WRF prognostic model. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Afzali, Afsaneh – PersonEntity: Name: NameFull: Rashid, M. – PersonEntity: Name: NameFull: Afzali, Mahboubeh – PersonEntity: Name: NameFull: Younesi, Vahid IsPartOfRelationships: – BibEntity: Dates: – D: 10 M: 11 Text: Nov2017 Type: published Y: 2017 Identifiers: – Type: issn-print Value: 09596526 Numbering: – Type: volume Value: 166 Titles: – TitleFull: Journal of Cleaner Production Type: main |
| ResultId | 1 |
