Urbanization has been one of the defining global trends of the 21st century. As people flock to cities in search of economic opportunities and a better quality of life, urban areas are becoming increasingly crowded and polluted. One of the most pressing challenges associated with urbanization is the rise in air pollution, which has detrimental effects on population health. In this article, we will delve into the complex relationship between urban air pollution and population health, exploring how machine learning techniques can be leveraged to evaluate and understand this critical issue. Air pollution is a major environmental problem that affects people worldwide. While it is a concern in both urban and rural areas, urban air pollution poses unique challenges due to the concentration of population and industrial activities. The primary contributors to urban air pollution include vehicular emissions, industrial processes, construction activities, and the combustion of fossil fuels for heating and energy production.
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Journal of Environmental Analytical Chemistry received 1781 citations as per Google Scholar report
