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Abstract
A high level of fine particulate matter (PM2.5) has become one of the greatest threats to human health. Based on multi-source remote sensing data, the pollutant population exposure model, accompanied by the Theil–Sen Median and Mann–Kendall methods, was used to analyze the spatio-temporal patterns of global population exposure risk of PM2.5 from 2000 to 2016. The population distribution patterns of high-risk exposure areas have been accurately identified; the variation trend and stability of global population exposure risk of PM2.5 have also been analyzed. According to the results, the average concentration of PM2.5 is correlated with the total population. The average concentration of PM2.5 for countries from high to low are Asia (14.7 μg/m3), Africa (8.1 μg/m3), Europe (8.03 μg/m3), South America (5.69 μg/m3), North America (4.41 μg/m3), and Oceania (1.27 μg/m3). In addition, the global average population exposure risk of PM2.5 is decreasing annually. Specifically, China, India, Southeast Asia, and other regions have higher exposure risks. Less developed mountainous regions, cold regions, deserts and tropical rainforest regions have lower exposure risks. Moreover, Oceania, North America, South America and other regions have relatively stable exposure, whereas areas with relatively unstable exposure risk of PM2.5 are mainly concentrated in Asia, India, and eastern China, followed by Southeast Asia, Europe, and Africa. Furthermore, Asia has the largest population of all the continents, followed by Africa and Europe. Countries with increased populations are mainly distributed in Africa, whereas the countries with a declining population are mainly distributed in Europe. Based on this, it is important to identify the relationship between PM2.5 concentration and population exposure risk to improve human settlements and environmental risk assessment.
Highlights
Due to the continuous growth of the global manufacturing scale and population, energy extraction, processing, and consumption are exponentially increasing
Based on multi-source remote sensing data, the pollutant population exposure model, accompanied by the Theil–Sen Median and Mann–Kendall methods were used to analyze the spatio-temporal patterns of global population exposure risk of PM2.5 from 2000 to 2016
It was found that the total population has a certain relationship with PM2.5 concentration and exposure risk
Summary
Due to the continuous growth of the global manufacturing scale and population, energy extraction, processing, and consumption are exponentially increasing. Air pollution has become a global challenge to human health, production, and life. The World Health Organization has emphasized that air pollution is one of the main environmental risks affecting human health. PM2.5 (or particulate matter with an aerodynamic diameter ≤2.5 μm) is a solid particulate matter with an equivalent diameter less than or equal to 2.5 μm in aerodynamics [1]. It is the main form of air pollution and the leading cause of global non-communicable diseases [2]. Air pollution exposure refers to the state or process in which individual residents are exposed to air pollution by direct contact with air pollutants [3]. Scientific and accurate exposure assessment is a prerequisite for the risk prevention and control of PM2.5
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