Urban population exposure forecast system to predict NO2 impact by a building-resolving multi-scale model approach.
Saved in:
| Title: | Urban population exposure forecast system to predict NO2 impact by a building-resolving multi-scale model approach. |
|---|---|
| Authors: | Veratti, Giorgio1 (AUTHOR) giorgio.veratti@unimore.it, Bigi, Alessandro1 (AUTHOR), Lupascu, Aurelia2 (AUTHOR), Butler, Tim M.2 (AUTHOR), Ghermandi, Grazia1 (AUTHOR) |
| Source: | Atmospheric Environment. Sep2021, Vol. 261, pN.PAG-N.PAG. 1p. |
| Subject Terms: | *Urban density, City dwellers, Multiscale modeling, Population forecasting, City traffic, Hybrid systems |
| Geographic Terms: | Modena (Italy) |
| Company/Entity: | European Environment Agency , World Meteorological Organization |
| Abstract: | Operational forecasting systems based on chemical transport models (CTMs) nowadays generally produce concentration maps with a resolution in the order of 2–5 km, very rarely exceeding the sub-kilometre scale. The main reason for this restriction is the prohibitive computing cost that a simulation covering an entire country would have if set-up with a resolution in the order of meters. In this paper a hybrid forecast system, relying on the WRF-Chem model coupled with the PMSS Lagrangian modelling suite, has been developed and applied for each day of February 2019, to predict hourly NO 2 and NO x concentrations with a spatial resolution of 4 m, for the urban area of Modena (a city located in the central Po Valley). Simulated meteorological fields (temperature, wind speed and direction) were assessed at three urban stations, compliant with WMO standards, and modelled concentrations were compared with measurements at two urban air quality stations located at background and traffic sites. Results show that meteorological variables are well captured by the hybrid system and statistical performances are in line with the benchmark values suggested by the European Environmental Agency and with similar case studies focusing on the same area. Modelled NO 2 and NO x concentrations, notwithstanding a slight underestimation mainly evident at urban traffic stations for NO x , present a large agreement with related observations. The NO 2 Model Quality Objective, as defined by Fairmode guidelines, was met for both the urban stations and the other statistical indexes considered in the evaluation fulfilled the acceptance criteria for dispersion modelling in urban environment, for both NO 2 and NO x concentrations. In the second section of the study, the population exposure to forecasted NO 2 concentrations has been evaluated adopting a generic model of dynamic population activity. The population was distributed at hourly time steps in specific urban micro-environments at the same resolution of the concentration maps (4 m) and the short-term exposure has been computed as the product between the population density in each model cell and related surface NO 2 concentrations. An infiltration factor was also applied to estimate indoor concentrations. The hybrid system was shown to be particularly suited for assessing short-term peak exposure in areas influenced by traffic emissions. On the other hand, due to the limited time spent by the population within traffic related environments, the long-term population exposure calculated by the hybrid system tends to be similar to the WRF-Chem stand-alone estimate. • Development of an hybrid Eulerian-Lagrangian forecasting system. • A comparison between the hybrid system and a standard CTM is presented. • The population exposure to forecasted NO 2 concentrations was assessed. • NO 2 exposure estimate based on dynamic population activity. [ABSTRACT FROM AUTHOR] |
| Copyright of Atmospheric Environment is the property of Pergamon Press - An Imprint of Elsevier Science 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: | GreenFILE |
| FullText | Text: Availability: 0 |
|---|---|
| Header | DbId: 8gh DbLabel: GreenFILE An: 151629875 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Urban population exposure forecast system to predict NO2 impact by a building-resolving multi-scale model approach. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Veratti%2C+Giorgio%22">Veratti, Giorgio</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> giorgio.veratti@unimore.it</i><br /><searchLink fieldCode="AR" term="%22Bigi%2C+Alessandro%22">Bigi, Alessandro</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Lupascu%2C+Aurelia%22">Lupascu, Aurelia</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Butler%2C+Tim+M%2E%22">Butler, Tim M.</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ghermandi%2C+Grazia%22">Ghermandi, Grazia</searchLink><relatesTo>1</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Atmospheric+Environment%22">Atmospheric Environment</searchLink>. Sep2021, Vol. 261, pN.PAG-N.PAG. 1p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Urban+density%22">Urban density</searchLink><br /><searchLink fieldCode="DE" term="%22City+dwellers%22">City dwellers</searchLink><br /><searchLink fieldCode="DE" term="%22Multiscale+modeling%22">Multiscale modeling</searchLink><br /><searchLink fieldCode="DE" term="%22Population+forecasting%22">Population forecasting</searchLink><br /><searchLink fieldCode="DE" term="%22City+traffic%22">City traffic</searchLink><br /><searchLink fieldCode="DE" term="%22Hybrid+systems%22">Hybrid systems</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Modena+%28Italy%29%22">Modena (Italy)</searchLink> – Name: SubjectCompany Label: Company/Entity Group: Su Data: <searchLink fieldCode="DE" term="%22European+Environment+Agency%22">European Environment Agency</searchLink> <br /><searchLink fieldCode="DE" term="%22World+Meteorological+Organization%22">World Meteorological Organization</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Operational forecasting systems based on chemical transport models (CTMs) nowadays generally produce concentration maps with a resolution in the order of 2–5 km, very rarely exceeding the sub-kilometre scale. The main reason for this restriction is the prohibitive computing cost that a simulation covering an entire country would have if set-up with a resolution in the order of meters. In this paper a hybrid forecast system, relying on the WRF-Chem model coupled with the PMSS Lagrangian modelling suite, has been developed and applied for each day of February 2019, to predict hourly NO 2 and NO x concentrations with a spatial resolution of 4 m, for the urban area of Modena (a city located in the central Po Valley). Simulated meteorological fields (temperature, wind speed and direction) were assessed at three urban stations, compliant with WMO standards, and modelled concentrations were compared with measurements at two urban air quality stations located at background and traffic sites. Results show that meteorological variables are well captured by the hybrid system and statistical performances are in line with the benchmark values suggested by the European Environmental Agency and with similar case studies focusing on the same area. Modelled NO 2 and NO x concentrations, notwithstanding a slight underestimation mainly evident at urban traffic stations for NO x , present a large agreement with related observations. The NO 2 Model Quality Objective, as defined by Fairmode guidelines, was met for both the urban stations and the other statistical indexes considered in the evaluation fulfilled the acceptance criteria for dispersion modelling in urban environment, for both NO 2 and NO x concentrations. In the second section of the study, the population exposure to forecasted NO 2 concentrations has been evaluated adopting a generic model of dynamic population activity. The population was distributed at hourly time steps in specific urban micro-environments at the same resolution of the concentration maps (4 m) and the short-term exposure has been computed as the product between the population density in each model cell and related surface NO 2 concentrations. An infiltration factor was also applied to estimate indoor concentrations. The hybrid system was shown to be particularly suited for assessing short-term peak exposure in areas influenced by traffic emissions. On the other hand, due to the limited time spent by the population within traffic related environments, the long-term population exposure calculated by the hybrid system tends to be similar to the WRF-Chem stand-alone estimate. • Development of an hybrid Eulerian-Lagrangian forecasting system. • A comparison between the hybrid system and a standard CTM is presented. • The population exposure to forecasted NO 2 concentrations was assessed. • NO 2 exposure estimate based on dynamic population activity. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Atmospheric Environment is the property of Pergamon Press - An Imprint of Elsevier Science 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.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=8gh&AN=151629875 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1016/j.atmosenv.2021.118566 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 1 StartPage: N.PAG Subjects: – SubjectFull: Urban density Type: general – SubjectFull: City dwellers Type: general – SubjectFull: Multiscale modeling Type: general – SubjectFull: Population forecasting Type: general – SubjectFull: City traffic Type: general – SubjectFull: Hybrid systems Type: general – SubjectFull: Modena (Italy) Type: general – SubjectFull: European Environment Agency Type: general – SubjectFull: World Meteorological Organization Type: general Titles: – TitleFull: Urban population exposure forecast system to predict NO2 impact by a building-resolving multi-scale model approach. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Veratti, Giorgio – PersonEntity: Name: NameFull: Bigi, Alessandro – PersonEntity: Name: NameFull: Lupascu, Aurelia – PersonEntity: Name: NameFull: Butler, Tim M. – PersonEntity: Name: NameFull: Ghermandi, Grazia IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 09 Text: Sep2021 Type: published Y: 2021 Identifiers: – Type: issn-print Value: 13522310 Numbering: – Type: volume Value: 261 Titles: – TitleFull: Atmospheric Environment Type: main |
| ResultId | 1 |
