Cargando…
Identifying proxies and mapping heavy metals concentrations in city road dusts: A case study in the Brussels-Capital Region, Belgium
This paper investigates the spatial distribution of heavy metals (HMs) concentrations in road dusts over a part of the Brussels-Capital Region (BCR), with the aim of identifying the most relevant factors impacting these concentrations and subsequently mapping them over all road segments. For this go...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9900355/ https://www.ncbi.nlm.nih.gov/pubmed/36755603 http://dx.doi.org/10.1016/j.heliyon.2023.e13312 |
_version_ | 1784882830166196224 |
---|---|
author | Bogaert, Patrick Diélie, Gwenaël Briffault, Axel de Saint-Hubert, Benoit Verbanck, Michel A. |
author_facet | Bogaert, Patrick Diélie, Gwenaël Briffault, Axel de Saint-Hubert, Benoit Verbanck, Michel A. |
author_sort | Bogaert, Patrick |
collection | PubMed |
description | This paper investigates the spatial distribution of heavy metals (HMs) concentrations in road dusts over a part of the Brussels-Capital Region (BCR), with the aim of identifying the most relevant factors impacting these concentrations and subsequently mapping them over all road segments. For this goal, a set of 128 samples of road dusts was collected over a three years time span in the Anderlecht municipality, that covers about a tenth of the BCR area. The concentrations of Cd, Cr, Cu, Ni, Pb and Zn have been measured in the finest fraction ([Formula: see text] μm) using ICP-OES. In parallel, continuous and categorical-valued proxies have been collected over all road segments. Using a multivariate linear modeling (MLR) approach, the most influential proxies that have been identified are the distance to the center of the BCR, land use, road hierarchy and roadside parking occupation. The performance of the MLR models remains however limited, with adjusted [Formula: see text] values around 0.5 for all HMs. From a spatial analysis of the regression residuals, it is likely that some useful proxies could have been overlooked. Although these models have clear limitations for reliably predicting HMs concentrations at specific locations, the corresponding maps drawn over all road segments provide a useful overview and help designing sound monitoring policies as well appropriate implementation of mitigation measures at places where road dust pollutants tend to concentrate. Further studies are needed to confirm this, but it is expected that our models will perform reasonably well over a large part of the BCR. It is believed too that our findings are relevant for modeling road dusts pollution in other cities as well. |
format | Online Article Text |
id | pubmed-9900355 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-99003552023-02-07 Identifying proxies and mapping heavy metals concentrations in city road dusts: A case study in the Brussels-Capital Region, Belgium Bogaert, Patrick Diélie, Gwenaël Briffault, Axel de Saint-Hubert, Benoit Verbanck, Michel A. Heliyon Research Article This paper investigates the spatial distribution of heavy metals (HMs) concentrations in road dusts over a part of the Brussels-Capital Region (BCR), with the aim of identifying the most relevant factors impacting these concentrations and subsequently mapping them over all road segments. For this goal, a set of 128 samples of road dusts was collected over a three years time span in the Anderlecht municipality, that covers about a tenth of the BCR area. The concentrations of Cd, Cr, Cu, Ni, Pb and Zn have been measured in the finest fraction ([Formula: see text] μm) using ICP-OES. In parallel, continuous and categorical-valued proxies have been collected over all road segments. Using a multivariate linear modeling (MLR) approach, the most influential proxies that have been identified are the distance to the center of the BCR, land use, road hierarchy and roadside parking occupation. The performance of the MLR models remains however limited, with adjusted [Formula: see text] values around 0.5 for all HMs. From a spatial analysis of the regression residuals, it is likely that some useful proxies could have been overlooked. Although these models have clear limitations for reliably predicting HMs concentrations at specific locations, the corresponding maps drawn over all road segments provide a useful overview and help designing sound monitoring policies as well appropriate implementation of mitigation measures at places where road dust pollutants tend to concentrate. Further studies are needed to confirm this, but it is expected that our models will perform reasonably well over a large part of the BCR. It is believed too that our findings are relevant for modeling road dusts pollution in other cities as well. Elsevier 2023-02-01 /pmc/articles/PMC9900355/ /pubmed/36755603 http://dx.doi.org/10.1016/j.heliyon.2023.e13312 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research Article Bogaert, Patrick Diélie, Gwenaël Briffault, Axel de Saint-Hubert, Benoit Verbanck, Michel A. Identifying proxies and mapping heavy metals concentrations in city road dusts: A case study in the Brussels-Capital Region, Belgium |
title | Identifying proxies and mapping heavy metals concentrations in city road dusts: A case study in the Brussels-Capital Region, Belgium |
title_full | Identifying proxies and mapping heavy metals concentrations in city road dusts: A case study in the Brussels-Capital Region, Belgium |
title_fullStr | Identifying proxies and mapping heavy metals concentrations in city road dusts: A case study in the Brussels-Capital Region, Belgium |
title_full_unstemmed | Identifying proxies and mapping heavy metals concentrations in city road dusts: A case study in the Brussels-Capital Region, Belgium |
title_short | Identifying proxies and mapping heavy metals concentrations in city road dusts: A case study in the Brussels-Capital Region, Belgium |
title_sort | identifying proxies and mapping heavy metals concentrations in city road dusts: a case study in the brussels-capital region, belgium |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9900355/ https://www.ncbi.nlm.nih.gov/pubmed/36755603 http://dx.doi.org/10.1016/j.heliyon.2023.e13312 |
work_keys_str_mv | AT bogaertpatrick identifyingproxiesandmappingheavymetalsconcentrationsincityroaddustsacasestudyinthebrusselscapitalregionbelgium AT dieliegwenael identifyingproxiesandmappingheavymetalsconcentrationsincityroaddustsacasestudyinthebrusselscapitalregionbelgium AT briffaultaxel identifyingproxiesandmappingheavymetalsconcentrationsincityroaddustsacasestudyinthebrusselscapitalregionbelgium AT desainthubertbenoit identifyingproxiesandmappingheavymetalsconcentrationsincityroaddustsacasestudyinthebrusselscapitalregionbelgium AT verbanckmichela identifyingproxiesandmappingheavymetalsconcentrationsincityroaddustsacasestudyinthebrusselscapitalregionbelgium |