Application of Openair package in R programming and PCA: unveiling air quality dynamics and meteorological influences

Air pollution in urban areas poses severe environmental and public health challenges requiring systematic monitoring. This study analyzes 2023 CAAQMS data from Nagpur-a rapidly growing Tier-2 Indian city-to examine interactions among eight major air pollutants (PM₁₀, PM_2.5, SO₂, CO, O₃, NO₂, NH₃, benzene) and four meteorological parameters (temperature, humidity, wind speed, rainfall). Key findings reveal: (1) AQI reached 492 (Severe category) in winter (February), with significant improvement during monsoon months (AQI < 100); (2) PM₁₀- PM_2.5 (r = 0.955) and CO-benzene (r = 0.889) show strong positive correlations, indicating common combustion sources; (3) Ventilation Coefficient varies from 668 m²/s (January) to 1385 m²/s (May), implying winter emission reductions need to be ~ 3.7 × more aggressive than summer to achieve equivalent ambient concentration targets; (4) No statistically significant weekend effect exists for any pollutant (all p > 0.1), suggesting continuous source contributions; (5) PCA with varimax rotation identifies two components explaining 73.1% of variance: anthropogenic combustion (PM, NO₂) and photochemical processes (O₃, temperature). Exceedance analysis shows PM_2.5 and PM₁₀ exceeded CPCB standards on 27-29 days in winter months. Policy implications include seasonally variable emission reduction targets, co-benefit strategies targeting combustion sources, and resource reallocation to winter months when dispersion is poorest. This study provides the first comprehensive annual air quality baseline for Nagpur, demonstrating that Tier-2 cities require tailored, seasonally aware pollution management strategies distinct from megacity approaches.