Audrin Thomas, Apparicio Philippe, Séguin Anne-Marie
Institut National de la recherche scientifique, 385 rue Sherbrooke Est, Montréal H2X 1E3, Canada.
Transp Res D Transp Environ. 2022 May;106:103274. doi: 10.1016/j.trd.2022.103274. Epub 2022 Apr 27.
From an environmental equity perspective, the aim of this paper is twofold. First, we want to verify to what extent vulnerable population groups resided in areas exposed to high levels of aircraft noise before and during the COVID-19 pandemic (2019 and 2020) in the Montréal census metropolitan area. Second, we want to identify whether the use of an aircraft noise indicator rather than another generates significant variations in the results and consequently in terms of affected areas and populations. With the IMPACT web-application, we model aircraft noise contours from three cumulative ( , , ) and a single-event ( ) metrics. The model's input data are retrieved by a website for flight tracking. Next, four variables are extracted from the 2016 Statistics Canada census at a fine scale level (dissemination areas): that is, the percentages of low-income individuals, visible minorities, children under 15 years old, and individuals aged 65 and over. The results show a significant drop in population exposed to aircraft noise in 2020 compared to 2019. In addition, the estimates of populations impacted by aircraft noise differ from one indicator to the next. The logistic regression models indicate that the inequities are inconsistent between cumulative and single-event metrics.
从环境公平的角度来看，本文的目的有两个。首先，我们想验证在蒙特利尔人口普查大都市区，在新冠疫情之前及期间（2019年和2020年），弱势群体居住在飞机噪音高强度区域的程度。其次，我们想确定使用飞机噪音指标而非其他指标是否会导致结果出现显著差异，进而影响受影响的区域和人群。借助IMPACT网络应用程序，我们根据三个累积指标（ 、 、 ）和一个单事件指标（ ）对飞机噪音等值线进行建模。该模型的输入数据通过一个飞行跟踪网站获取。接下来，从加拿大统计局2016年人口普查的精细尺度层面（行政区）提取四个变量：即低收入个体、可见少数群体、15岁以下儿童以及65岁及以上个体的百分比。结果显示，与2019年相比，2020年暴露于飞机噪音中的人口显著减少。此外，受飞机噪音影响的人口估计因指标不同而有所差异。逻辑回归模型表明，累积指标和单事件指标之间的不公平情况并不一致。
