Urban air quality: What is the optimal place to reduce transport emissions?
File(s)
Accepted version
Author(s)
Li, Tianyang
Fellini, Sofia
van Reeuwijk, Maarten
Type
Journal Article
Abstract
We develop a linear model based on a complex network approach that predicts the effect of emission changes on air pollution exposure in urban street networks
including NO–NO2–O3-chemisty. The operational air quality model SIRANE is used to create a weighted adjacency matrix A describing the relation between
emissions of a passive scalar inside streets and the resulting concentrations in the street network. A case study in South Kensington (London) is used, and the ad jacency matrix A0 is determined for one wind speed and eight different wind directions. The physics of the underlying problem is used to infer A for different wind
speeds. Good agreement between SIRANE predictions and the model is observed for all but the lowest wind speed, despite non-linearities in SIRANE’s model
formulation. An indicator for exposure in the street is developed, and it is shown that the out-degree of the exposure matrix E represents the effect of a change in
emissions on the exposure reduction in all streets in the network. The approach is then extended to NO–NO2–O3-chemisty, which introduces a non-linearity. It is
shown that a linearised model agrees well with the fully nonlinear SIRANE predictions. The model shows that roads with large height-to-width ratios are the first in
which emissions should be reduced in order to maximise exposure reduction.
including NO–NO2–O3-chemisty. The operational air quality model SIRANE is used to create a weighted adjacency matrix A describing the relation between
emissions of a passive scalar inside streets and the resulting concentrations in the street network. A case study in South Kensington (London) is used, and the ad jacency matrix A0 is determined for one wind speed and eight different wind directions. The physics of the underlying problem is used to infer A for different wind
speeds. Good agreement between SIRANE predictions and the model is observed for all but the lowest wind speed, despite non-linearities in SIRANE’s model
formulation. An indicator for exposure in the street is developed, and it is shown that the out-degree of the exposure matrix E represents the effect of a change in
emissions on the exposure reduction in all streets in the network. The approach is then extended to NO–NO2–O3-chemisty, which introduces a non-linearity. It is
shown that a linearised model agrees well with the fully nonlinear SIRANE predictions. The model shows that roads with large height-to-width ratios are the first in
which emissions should be reduced in order to maximise exposure reduction.
Date Issued
2023-01
Date Acceptance
2022-10-13
Citation
Atmospheric Environment, 2023, 292, pp.1-12
ISSN
1352-2310
Publisher
Elsevier BV
Start Page
1
End Page
12
Journal / Book Title
Atmospheric Environment
Volume
292
Copyright Statement
Copyright © Elsevier Ltd. All rights reserved. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/
Identifier
http://dx.doi.org/10.1016/j.atmosenv.2022.119432
Publication Status
Published
Article Number
119432
Date Publish Online
2022-10-17