Industries in Delhi: Air pollution versus respiratory morbidities
| Autor: | Sk Mohibul, Neha Parveen, Nazreen Khanam, Lubna Siddiqui, Safikul Islam, Nawaj Sarif |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Pollutant
021110 strategic defence & security studies Environmental Engineering General Chemical Engineering 0211 other engineering and technologies Air pollution 02 engineering and technology 010501 environmental sciences medicine.disease_cause complex mixtures 01 natural sciences Human health Industrialisation Air pollutants Environmental health medicine Environmental Chemistry Environmental science Negative correlation Safety Risk Reliability and Quality 0105 earth and related environmental sciences |
| Zdroj: | Process Safety and Environmental Protection. 152:495-512 |
| ISSN: | 0957-5820 |
| DOI: | 10.1016/j.psep.2021.06.027 |
| Popis: | Industrialization has been contributing to the economic development of countries all over the globe but on the other side of the coin, it is also causing deterioration of the environment as well as human health. Air pollution in industrial areas has emerged as a hasten issue in recent years due to its aggravated effects on health and wellbeing. The objectives of the study are to analyze the concentrations of air pollutants (PM10, PM2.5, NO2 & CO) in industrial areas of Delhi and to assess the association among meteorological variables, air pollutants, and respiratory diseases of industrial workers and their family members. To map these pollutants concentration, Kriging and Inverse Distance Weighted (IDW) interpolation techniques were employed. The results showed that several industrial areas were cloaked with all these four pollutants in varied ranges and different seasons. The increase in the number of registered and operating industries in Delhi, and the consequential rise in the air pollutants' concentrations followed the quadratic polynomial trend. Spearman’s rho correlation technique revealed that the respiratory disease entries of workers and their families depicted a statistically strong negative correlation with temperature, rainfall, and wind speeds while a strong positive association with PM2.5, NO2, and CO. |
| Databáze: | OpenAIRE |
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