AI Article Synopsis

  • Meteorological conditions play a crucial role in influencing air quality, particularly in pollution-heavy urban areas like Asansol, West Bengal.
  • This study examines how various meteorological factors (like temperature, humidity, rainfall, and wind speed) relate to key air pollutants (such as PM, NO, and SO) from January 2019 to December 2023, revealing an overall decrease in pollutant levels.
  • Findings indicate that temperature and rainfall significantly affect pollutant concentrations, with negative correlations observed for most conditions, while the research improves predictions of air quality by factoring in seasonal changes and meteorological influences.

Article Abstract

Meteorological conditions significantly impact ambient air quality in urban environments. This study focuses on Asansol, known as the "Coal City" and the "Industrial Heart of West Bengal," a notable hotspot for air pollution. Despite its significance, limited research has addressed the influence of meteorological factors on key air pollutants in this urban area. From January 2019 to December 2023, this investigation explores the relationships between meteorological parameters (including atmospheric temperature, relative humidity, rainfall, wind speed) and the concentrations of crucial air pollutants (PM, PM, NO, SO). Temporal trends in air pollutant concentrations are also analysed. The Spearman correlation method is used to establish associations between pollutant concentrations and meteorological variables, while multiple linear regression (MLR) models are employed to assess meteorological factors and potential impact on pollutant concentrations. The analysis reveals a decreasing trend in pollutant concentrations in Asansol. Temperature exhibits negative correlations with all pollutants in all seasons except for a positive correlation during the monsoon. Rainfall consistently displays significant negative correlations with pollutants in all seasons. Relative humidity is negatively correlated with pollutants in all seasons, and wind speed, except during the post-monsoon season, shows negative correlations with all pollutants. Linear models excel in predicting particulate matter concentrations but perform poorly in predicting gaseous contaminants. Accounting for seasonal fluctuations and meteorological parameters, this research enhances the accuracy of air pollution forecasting, contributing to a better understanding of air quality dynamics in Asansol and similar urban areas.

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Source
http://dx.doi.org/10.1007/s11356-024-33608-zDOI Listing

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