ISSN (0970-2083)

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Case Report Open Access



Air pollution is one of the most serious forms of environmental pollutions posing huge threat to human life. Air pollution is increasingly becoming a global concern and is believed to be one of the causes of death in the world today. Developing countries, like India are struggling between the focus on economic development and curbing air pollution emissions. Bengaluru is one of India’s fastest growing metropolises although benefiting economically due to its rapid development has along with rapidly deteriorating air quality. Several epidemiological studies and clinical evidence have linked both the short and long-term exposures of air pollution on various health issues such as respiratory disorders, lung cancer, heart disease and even damage the brain and nerves. In the present study an attempt has been made to present the air quality status and its prediction at the four selected locations of Bengaluru using multiple linear regression modeling. These predictions of the pollutant concentration are able to improve decision making and also provide appropriate solutions. This study examines the performance of multiple-linear regression in order to achieve an efficient model to estimate the concentration of oxides of sulphur and nitrogen and respirable suspended Particulate Matter (PM10) contents in the ambient air and represent air pollution trend at various industrial, residential, commercial and sensitive locations of Bengaluru over the period 2011-2019. From the model it was observed that the concentration of sulfur dioxide was lower than the other air contaminants whereas the concentration of nitrogen dioxide predominant than the other pollutants.

Indira BC*, Maya Naik, Guruprasad M Hugar

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