Investigating the Impact of Meteorological Parameters on PM2.5 Concentrations and Air Quality Index Using Regression Analysis

2025-09-15T09:56:06+08:00

Air pollution from fine particulate matter (PM2.5) poses a serious health risk in rapidly urbanizing areas like Bhopal, India. This study investigates the influence of meteorological factors temperature, humidity, rainfall, and wind speed on PM2.5 concentrations and the Air Quality Index (AQI) from January 2022 to December 2023. PM2.5 levels ranged from 1.0 µg/m³ to 938.0 µg/m³, with an average AQI of 119, indicating moderate pollution. Correlation analysis indicated that higher temperatures were sometimes associated with elevated PM2.5 episodes due to enhanced photochemical activity, but regression analysis revealed an overall negative association, suggesting stronger atmospheric dispersion at higher temperatures. Wind speed consistently reduced PM2.5, while humidity and rainfall supported pollutant removal. Regression models explained 18.1% of PM2.5 and 29.7% of AQI variability. Ridge regression reinforced the dominant influence of temperature and humidity. AQI was modelled alongside PM2.5 to align with its practical role in public communication and policy, despite being largely driven by PM2.5. These findings highlight the role of meteorological conditions in shaping urban air quality and emphasize the need for targeted interventions during stagnant, high-pressure episodes. By focusing on Bhopal, this study contributes valuable city-specific knowledge to the broader discourse on air pollution in rapidly developing regions of India. The study reinforces the need to incorporate meteorological forecasting into urban air quality management strategies.

Is Climate Change Fuel to Increase Intense Tropical Cyclones in the North Indian Ocean?

2025-09-01T10:51:40+08:00

In recent years, severe cyclonic storm (SCS) activity is increased in the North Indian Ocean (NIO), particularly in the central Arabian Sea and Bay of Bengal. In the present study investigate the role of climate change on increasing intense severe cyclonic storms (Cat 4 & 5) at each 2.5° × 2.5° grid boxes in the NIO. Inter-governmental on Climate Change (IPCC) AR4 Model data sets for cyclone genesis parameters, sea surface temperature (SST) from Hadley Centre, cyclone tracks from Indian Meteorological Department and Joint Typhoon Warning Center during 1891–2010 is used. The study reveals stimulating results that the frequency of SCS increased during 1970–2010 (19) compared with 1891–1969 (12) at north of 15° N lat, but south of 15° N it is reversed in the Arabian Sea (AS) during southwest monsoon season(JJAS). In the Bay of Bengal (BoB) the scenario is reversed when compared with the Arabian Sea and the frequency of SCS was decreased in climate change environment. Strong latitudinal shift and increase the frequency of SCS is observed in the Arabian Sea during climate change scenario (1970–2010), but such phenomena is not noticed in the BoB. The main reason is reduction in vertical wind shear (easterly shear) along with increase in SSTs. To find out the relationship between the frequency of SCS and cyclone genesis parameters I did statistical tests, they also showed good results.

Journal of Atmospheric Science Research

Investigating the Impact of Meteorological Parameters on PM2.5 Concentrations and Air Quality Index Using Regression Analysis

Is Climate Change Fuel to Increase Intense Tropical Cyclones in the North Indian Ocean?