Four-year Spatiotemporal Distribution & Analysis of PM<sub>2.5</sub> and its Precursor Air Pollutant SO<sub>2</sub>, NO<sub>2</sub> & NH<sub>3</sub> and their Impact on LST in Bengaluru City, India
Gourav Suthar, R P Singhal, Sumit Khandelwal, Nivedita Kaul, Versha Parmar, Ajit Pratap Singh
Abstract
Abstract Bengaluru is one of the most populated cities in India. The rise in urbanization has caused an increase in air pollutant concentrations and land surface temperature. The present study explored the four-year (2019-2022) seasonal relationship between PM 2.5 and its precursor’s air pollutants SO 2 , NO 2 , NH 3 , and meteorological parameters (WS, WD, RH, SR). Another relationship was explored to find the combined impact of air pollutants (PM 2.5 SO 2 , NO 2 , NH 3 ) and meteorological parameters on LST. Results from correlation analysis show that PM 2.5 is strongly and very strongly correlated with NH 3 during 2022 and moderately correlated with SO 2 in 2021 and NO 2 in 2022, respectively, during both seasons. LST is positively associated with air pollutants except for PM 2.5 in 2020 and NO 2 in 2022. The multiple linear regression analysis shows that PM 2.5 strongly correlates with its precursors and meteorological parameter in both summers (0.66 to 0.74) and winters (0.59 to 0.93). Similarly, LST is strongly associated with all four air pollutants and meteorological parameters in summer (0.66 to 0.81) and winter from 0.60 to 0.79 from 2019 to 2021. The result shows that multiple parameters are responsible for the formation of secondary PM 2.5 and change in LST.