Comprehensive evaluation of an advanced street canyon air pollution model.


Journal

Journal of the Air & Waste Management Association (1995)
ISSN: 2162-2906
Titre abrégé: J Air Waste Manag Assoc
Pays: United States
ID NLM: 9503111

Informations de publication

Date de publication:
02 2021
Historique:
pubmed: 1 8 2020
medline: 25 11 2021
entrez: 1 8 2020
Statut: ppublish

Résumé

A street canyon pollution dispersion model is described which accounts for a wide range of canyon geometries including deep and/or asymmetric canyons. The model uses up to six component sources to represent different effects of street canyons on the dispersion of road traffic emissions. The final concentration is a weighted sum of the component concentrations dependent on output point location; canyon geometry; and wind direction relative to canyon orientation. Conventional approaches to modeling pollution in street canyons, such as the "Operational Street Pollution Model" (OSPM), do not account for canyons with high aspect ratios, pavements, and building porosity, so are not applicable for all urban morphologies. The new model has been implemented within the widely used, street-level resolution ADMS-Urban air quality model, which is used for air quality assessment and forecasting in cities such as Hong Kong where high-rise buildings form deep and complex street canyons. The new model is evaluated in relation to measured pollutant concentration data from the "Optimisation of modelling methods for traffic pollution in streets" (TRAPOS) project and routine measurements from 42 monitoring sites in London. Comparisons have been made between modeling using the new canyon model; a simpler approach to canyon modeling based on the OSPM formulation; and without any inclusion of canyon effects. The TRAPOS dataset has been used to highlight the model's ability to replicate the dependence of concentration on wind speed and direction, and also to show improved model performance for the prediction of high concentration values, which is particularly important for model applications such as planning and assessment. The London dataset, in which the street canyons are less well defined, has also been used to demonstrate improved model performance for this advanced approach compared to the simpler methods, by categorizing the measurement locations according to site type (background, near-road, and strong canyon).

Identifiants

pubmed: 32735484
doi: 10.1080/10962247.2020.1803158
doi:

Substances chimiques

Air Pollutants 0
Vehicle Emissions 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

247-267

Auteurs

Christina Hood (C)

Cambridge Environmental Research Consultants , Cambridge, UK.

Jenny Stocker (J)

Cambridge Environmental Research Consultants , Cambridge, UK.

Martin Seaton (M)

Cambridge Environmental Research Consultants , Cambridge, UK.

Kate Johnson (K)

Cambridge Environmental Research Consultants , Cambridge, UK.

James O'Neill (J)

Cambridge Environmental Research Consultants , Cambridge, UK.

Lewis Thorne (L)

Department of Chemical Engineering and Biotechnology, University of Cambridge , Cambridge, UK.

David Carruthers (D)

Cambridge Environmental Research Consultants , Cambridge, UK.

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Classifications MeSH