The contribution of activity-based transport models to air quality modelling: A validation of the ALBATROSS–AURORA model chain
Saved in:
| Title: | The contribution of activity-based transport models to air quality modelling: A validation of the ALBATROSS–AURORA model chain |
|---|---|
| Authors: | Beckx, Carolien1 carolien.beckx@vito.be, Int Panis, Luc1,2, Van De Vel, Karen1, Arentze, Theo3, Lefebvre, Wouter1, Janssens, Davy2, Wets, Geert2 |
| Source: | Science of the Total Environment. Jun2009, Vol. 407 Issue 12, p3814-3822. 9p. |
| Subjects: | Air pollution, Mathematical models, Automobile emissions, Air quality research, Air pollution forecasting, Nitrogen dioxide, Emission exposure |
| Geographic Terms: | Netherlands |
| Abstract: | The potential advantages of using activity-based transport models for air quality purposes have been recognized for a long time but models that have been developed along these lines are still scarce. In this paper we demonstrate that an activity-based model provides useful information for predicting hourly ambient pollutant concentrations. For this purpose, the traffic emissions obtained in a previous application of the activity-based model ALBATROSS were used as input for the AURORA air quality model to predict hourly concentrations of NO2, PM10 and O3 in the Netherlands. Predicted concentrations were compared with measured concentrations at 37 monitoring stations from the Dutch air quality monitoring network. A statistical analysis was performed to evaluate model performance for different pollutants, locations and time periods. Results confirm that modelled and measured concentrations present the same geographical and temporal variation. The overall index of agreement for the prediction of hourly pollutant concentrations amounted to 0.64, 0.75 and 0.57 for NO2, O3 and PM10 respectively. Concerning the predictions for NO2, a major traffic pollutant, a more thorough analysis revealed that the ALBATROSS–AURORA model chain yielded better predictions near traffic locations than near background stations. Further, the model performed better in urban areas, on weekdays and during the day, consistent with the emission results obtained in a previous study. The results in this paper demonstrate the ability of the activity-based model to predict the contribution of traffic sources to local air pollution with sufficient accuracy and confirms the usefulness of activity-based transport models for air quality purposes. The fact that the ALBATROSS–AURORA chain provides reliable pollutant concentrations on hourly basis for the whole Netherlands instead of using only daily averages near traffic stations is a plus for future exposure studies aiming at more realistic exposure analyses and health impact assessments. [Copyright &y& Elsevier] |
| Copyright of Science of the Total Environment 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 |
|---|---|
| Header | DbId: egs DbLabel: Engineering Source An: 38318429 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: The contribution of activity-based transport models to air quality modelling: A validation of the ALBATROSS–AURORA model chain – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Beckx%2C+Carolien%22">Beckx, Carolien</searchLink><relatesTo>1</relatesTo><i> carolien.beckx@vito.be</i><br /><searchLink fieldCode="AR" term="%22Int+Panis%2C+Luc%22">Int Panis, Luc</searchLink><relatesTo>1,2</relatesTo><br /><searchLink fieldCode="AR" term="%22Van+De+Vel%2C+Karen%22">Van De Vel, Karen</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Arentze%2C+Theo%22">Arentze, Theo</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AR" term="%22Lefebvre%2C+Wouter%22">Lefebvre, Wouter</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Janssens%2C+Davy%22">Janssens, Davy</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Wets%2C+Geert%22">Wets, Geert</searchLink><relatesTo>2</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Science+of+the+Total+Environment%22">Science of the Total Environment</searchLink>. Jun2009, Vol. 407 Issue 12, p3814-3822. 9p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Air+pollution%22">Air pollution</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+models%22">Mathematical models</searchLink><br /><searchLink fieldCode="DE" term="%22Automobile+emissions%22">Automobile emissions</searchLink><br /><searchLink fieldCode="DE" term="%22Air+quality+research%22">Air quality research</searchLink><br /><searchLink fieldCode="DE" term="%22Air+pollution+forecasting%22">Air pollution forecasting</searchLink><br /><searchLink fieldCode="DE" term="%22Nitrogen+dioxide%22">Nitrogen dioxide</searchLink><br /><searchLink fieldCode="DE" term="%22Emission+exposure%22">Emission exposure</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Netherlands%22">Netherlands</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The potential advantages of using activity-based transport models for air quality purposes have been recognized for a long time but models that have been developed along these lines are still scarce. In this paper we demonstrate that an activity-based model provides useful information for predicting hourly ambient pollutant concentrations. For this purpose, the traffic emissions obtained in a previous application of the activity-based model ALBATROSS were used as input for the AURORA air quality model to predict hourly concentrations of NO2, PM10 and O3 in the Netherlands. Predicted concentrations were compared with measured concentrations at 37 monitoring stations from the Dutch air quality monitoring network. A statistical analysis was performed to evaluate model performance for different pollutants, locations and time periods. Results confirm that modelled and measured concentrations present the same geographical and temporal variation. The overall index of agreement for the prediction of hourly pollutant concentrations amounted to 0.64, 0.75 and 0.57 for NO2, O3 and PM10 respectively. Concerning the predictions for NO2, a major traffic pollutant, a more thorough analysis revealed that the ALBATROSS–AURORA model chain yielded better predictions near traffic locations than near background stations. Further, the model performed better in urban areas, on weekdays and during the day, consistent with the emission results obtained in a previous study. The results in this paper demonstrate the ability of the activity-based model to predict the contribution of traffic sources to local air pollution with sufficient accuracy and confirms the usefulness of activity-based transport models for air quality purposes. The fact that the ALBATROSS–AURORA chain provides reliable pollutant concentrations on hourly basis for the whole Netherlands instead of using only daily averages near traffic stations is a plus for future exposure studies aiming at more realistic exposure analyses and health impact assessments. [Copyright &y& Elsevier] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Science of the Total Environment 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.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=38318429 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1016/j.scitotenv.2009.03.015 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 9 StartPage: 3814 Subjects: – SubjectFull: Air pollution Type: general – SubjectFull: Mathematical models Type: general – SubjectFull: Automobile emissions Type: general – SubjectFull: Air quality research Type: general – SubjectFull: Air pollution forecasting Type: general – SubjectFull: Nitrogen dioxide Type: general – SubjectFull: Emission exposure Type: general – SubjectFull: Netherlands Type: general Titles: – TitleFull: The contribution of activity-based transport models to air quality modelling: A validation of the ALBATROSS–AURORA model chain Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Beckx, Carolien – PersonEntity: Name: NameFull: Int Panis, Luc – PersonEntity: Name: NameFull: Van De Vel, Karen – PersonEntity: Name: NameFull: Arentze, Theo – PersonEntity: Name: NameFull: Lefebvre, Wouter – PersonEntity: Name: NameFull: Janssens, Davy – PersonEntity: Name: NameFull: Wets, Geert IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: Jun2009 Type: published Y: 2009 Identifiers: – Type: issn-print Value: 00489697 Numbering: – Type: volume Value: 407 – Type: issue Value: 12 Titles: – TitleFull: Science of the Total Environment Type: main |
| ResultId | 1 |
