LAUSR

Air pollution is one of the deadliest and most important concerns of our era, and it not only impacts our environment but also our health. The consequences of poor air quality are not limited to just our lungs or our heart but also our brain and resulting in increased mortality rate of many countries every year. There are many effluents/pollutants present in the air that are harmful and cause diseases in humans which eventually lead to an increase in morbidity and mortality. Therefore, there is a need to identify those factors and evaluate the effect of pollution caused by air on the health of humans which is a prerequisite for the implementation of policies in preventing pollution. In this study, we model and evaluate the harmful impact of pollution caused by air on the health of humans by using a multi-criteria decision-making approach (MCDM). We have proposed a novel coupled model of the double modified (criteria importance through intercriteria correlation) CRITIC—technique for order of preference by similarity to ideal solution (TOPSIS) method (DMCTM) to identify and evaluate the factors of air pollution and its effect on health which overcome the disadvantage of bias while collecting the subjective data in the traditional TOPSIS method. To get a clear view of the framework proposed, a case study is conducted based on the methodology proposed in which we find that Xinxiang is the most polluted city in China among the five studied cities with SO2 as the major contributor, and the city experienced more pollution levels in 2022 and least in 2016, whereas there is a slight fluctuation in life expectancy with air pollution in the years 2015 and 2023.