Abstract
Air pollution exposure has become ubiquitous and is increasingly detrimental to human health. Small Particulate matter (PM) is one of the most harmful forms of air pollution. It can easily infiltrate the lungs and trigger several respiratory diseases, especially in vulnerable populations such as children and elderly people. In this work, we start by leveraging a retrospective study of 416 children suffering from respiratory diseases. The study revealed that asthma prevalence was the most common among several respiratory diseases, and that most patients suffering from those diseases live in areas of high traffic, noise, and greenness. This paved the way to the construction of the MOREAIR dataset by combining feature abstraction and micro-level scale data collection. Unlike existing data sets, MOREAIR is rich in context-specific components, as it includes 52 temporal or geographical features, in addition to air-quality measurements. The use of Random Forest uncovered the most important features for the understanding of air-quality distribution in Moroccan urban areas. By linking the medical data and the MOREAIR dataset, we observed that the patients included in the medical study come mostly from neighborhoods that are characterized by either high average or high variations of pollution levels.
Highlights
Air pollution is the largest environmental risk to health
When it comes to the temporal behavior of air pollution, the statistics show that the concentrations of PM10 and PM2.5 are stable during the whole week for Neighborhood 1 and Neighborhood 4, while Neighborhood 3 shows a slight peak on Friday
A novel method was developed to construct the MOREAIR dataset. This method merges air-quality measurements, weather data, and all the direct or indirect impacting sources of pollution in Rabat, Morocco. In line with this objective, we start by leveraging a retrospective study of 416 children who were hospitalized for a moderate to severe respiratory disease at the Ibn Sina’s Children Hospital Center (CHUIS)
Summary
Air pollution is the largest environmental risk to health. According to the World. Several countries have begun providing access to outdoor air-quality data collected by monitoring agencies such as “Air Data” in the United States [15] and “Airparif” in France [16]. These datasets provide hourly measurements of air quality, they do not specify what produces that pollution, or the different factors responsible for it. In the case of Morocco, there are no publicly available datasets of continuous measurements of air quality, nor is there a resource highlighting the different pollution sources and impacting factors. We aim to tackle outdoor environmental factors and study the impact of pollution on children’s health. We investigate how air quality in Morocco varies over time and space
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