Bogaert Patrick, Diélie Gwenaël, Briffault Axel, de Saint-Hubert Benoit, Verbanck Michel A
Earth & Life Institute, Université catholique de Louvain (UCLouvain), Belgium.
Department of Water Pollution Control, Université libre de Bruxelles (ULB), Belgium.
Heliyon. 2023 Feb 1;9(2):e13312. doi: 10.1016/j.heliyon.2023.e13312. eCollection 2023 Feb.
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 ( 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 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.
本文研究了布鲁塞尔首都大区（BCR）部分地区道路灰尘中重金属（HMs）浓度的空间分布，旨在确定影响这些浓度的最相关因素，并随后在所有路段绘制其分布图。为实现这一目标，在三年时间跨度内，于安德莱赫特市采集了128份道路灰尘样本，该市面积约占BCR地区的十分之一。使用电感耦合等离子体发射光谱仪（ICP - OES）测量了最细颗粒部分（ 微米）中镉、铬、铜、镍、铅和锌的浓度。同时，在所有路段收集了连续和分类值的代理变量。采用多元线性建模（MLR）方法，确定的最具影响力的代理变量是到BCR中心的距离、土地利用、道路等级和路边停车占用情况。然而，MLR模型的性能仍然有限，所有重金属的调整 值约为0.5。从回归残差的空间分析来看，可能一些有用的代理变量被忽略了。尽管这些模型在可靠预测特定位置的重金属浓度方面存在明显局限性，但在所有路段绘制的相应地图提供了有用的概述，并有助于设计合理的监测政策以及在道路灰尘污染物容易集中的地方适当实施缓解措施。需要进一步研究来证实这一点，但预计我们的模型在BCR大部分地区将表现良好。人们也认为我们的研究结果与其他城市道路灰尘污染建模相关。
