Goal-oriented placement of depolluting panels in urban areas - application to a Paris district

J. Waeytens, T. Hamada, R. Chakir, D. Lejri, F. Dugay
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Abstract

According to the World Health Organization, every year more than 4 million premature death world-wide are due to outdoor air pollution. Many sectors, e.g traffic, agriculture, industry, and housing, contribute to this. Herein, we focus on NO 2 pollution in urban areas caused by traffic. In fact, at Universit´e Gustave Eiffel, on the one hand, experimental works are in progress to develop operational depolluting panels based on ZnO photocatalysis [1]. On the other hand, to reduce air pollutant human exposure we propose a full numerical strategy from diagnosis — via the determination of critical highly polluted areas — to remediation via the smart placement of the depolluting panels in urban areas. Firstly, a city digital twin and computational fluid dynamics (CFD) are used to get detailed cartography of the NO 2 concentration at the district scale. From these numerical simulations, we retain high-concentration areas in the frequented zone as a quantity of interest. Then, a goal-oriented placement of depolluting panels is proposed to improve the selected quantities of interest using the adjoint framework. This work can be seen as an extension of previous works from the authors dealing with goal-oriented error estimation [2], goal-oriented model updating [3] and goal-oriented sensor placement [3, 4]. The proposed numerical strategy will be illustrated over a district in Paris. We consider two wind scenarios (directions and amplitudes), which are characteristic of the Paris region, and realistic NO 2 sources on each road provided by the regional air quality agency “Airparif”. First practical recommendations for depolluting panels deployment will be presented.
目标导向的在城市地区放置去污染面板-在巴黎地区的应用
根据世界卫生组织的数据,全球每年有超过400万人因室外空气污染而过早死亡。许多部门,如交通、农业、工业和住房,都有助于实现这一目标。在这里,我们关注的是城市地区由交通造成的二氧化氮污染。事实上,在Universit´e Gustave Eiffel,一方面,实验工作正在进行中,开发基于ZnO光催化的可操作的去污染面板[1]。另一方面,为了减少人类接触空气污染物,我们提出了一个完整的数字策略,从诊断-通过确定严重污染地区-到通过在城市地区智能放置去污染面板进行补救。首先,利用城市数字孪生模型和计算流体力学(CFD)技术,获得了区域尺度上二氧化氮浓度的详细制图;从这些数值模拟中,我们保留了频繁光顾区域的高浓度区域作为兴趣量。然后,利用伴随框架提出了目标导向的去污染面板放置,以改善感兴趣的选择数量。这项工作可以看作是作者先前处理面向目标的误差估计[2],面向目标的模型更新[3]和面向目标的传感器放置[3,4]的工作的扩展。提出的数字战略将在巴黎的一个地区进行说明。我们考虑了两种风的情景(方向和振幅),这是巴黎地区的特征,以及由地区空气质量机构“Airparif”提供的每条道路上的现实二氧化氮来源。本文将首先提出有关净化面板部署的实用建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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