Deterministic Decision Support System for the Assessment of Cities Based on Air Quality Indicators: Decision Support System Using DBA

Deterministic Decision Support System for the Assessment of Cities Based on Air Quality Indicators: Decision Support System Using DBA

Rakesh Garg, Supriya Raheja
Copyright: © 2022 |Pages: 21
DOI: 10.4018/IJDSST.292448
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Abstract

A deterministic decision support system is developed for the assessment of various Indian cities based on the air quality parameters in this research. The present study shapes the assessment of cities as a multi-criteria decision-making (MCDM) problem due to the involvement of many indicators. To solve the present assessment problem the authors use an MCDM method, namely distance-based approach (DBA), that mainly works on the Euclidean distance calculation for each city from the optimal point and ranks the cities on the basis of their calculated distances. The city scoring minimum distance value is ranked at top position, and the city with the maximum distance value at the last position.
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Introduction

Air pollution has become the globally concerned environmental challenge which is disturbing the viable growth of many developing countries. It is among the top five global risk factors for mortality. IQAir 2019 (World Air Quality) report revealed that 21 worst polluted cities out of top 30 are only from India which proves the progressive deprivation in air quality of India due to the rapid evolution of resources and rapid growth of population in urban areas. Vehicular and industrial emissions, construction, road dust, and anthropogenic activities etc. (Wang et al., 2018) are the other factors which diminishes the air quality. Figure 1 demonstrates the major resources triggering air pollution in India (Wikipedia, 2019). Recent reports of the World Health Organization (WHO) stated that globally 90% of people are breathing in highly polluted air including both indoors and out-doors. However, more than 80% urban population is exposed to such a poor air quality which is even exceeding the WHO (2019) guideline limits.

Figure 1.

Major sources of Air Pollution

IJDSST.292448.f01

Over the last several decades, various studies and research have been concluding air pollution as an important risk factor to the individual’s health (Liu et al., 2018; Chakrabarti et al., 2019). Poor air quality is affecting everyone’s health either young or old, rich, or poor etc. According to reports, approximately 7 million premature deaths per year is caused due to both indoor and outdoor pollution. However, 4.2 million deaths are just because of outdoor pollution due to poor air quality. According to Recent Global Burden of Diseases (GBD) report India is amongst those countries who are surpassing the WHO guideline limits for air pollution. Not only among these countries, India and China are contributing more than 50% for this disease burden (Balakrishnan et al. 2019).

Number of studies reported that excessive contact to these harmful concentrations of pollutants may trigger many diseases like lung cancer, cardiopulmonary mortality, respiratory diseases and many more (Pope et al., 2002; Lepeule et al., 2014). PM2.5 beyond the limits may initiate lung cancer, whereas ozone beyond limits may trigger respiratory diseases (Jerret et al., 2009). The average value of PM2.5 is rapidly increasing in India (OECD, 2019). According to OECD (Organization for Economic Cooperation and Development) report, the increase in the value of PM2.5 may cause approx. 2000 person per million premature deaths in India by 2060.

Several studies have been reporting the other impacts of poor air quality on human life. Along with health (Liu et al., 2018; Chakrabarti et al., 2019), it may adversely impact on the agricultural land (Agarwal et al., 2003) and on the economy mainly for the developing nations (Lvovsky, 1998; Maji et al., 2017). Poor air quality caused around USD 30 billion economic loss in India.

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