Background: Rapid urban growth has turned air pollution into a stubborn public-health problem across Indian cities, and Bangalore is no exception. What stays poorly mapped is how particulate matter (PM₁₀ and PM₂.₅) and ground-level ozone (O₃) rise and fall together. The coupling across the day, the seasons, and successive years matters for any evidence-based control strategy, yet few studies have quantified it for Bangalore city.

Methods: Hourly PM₁₀, PM₂.₅, and O₃ records were drawn from six of the thirteen Continuous Ambient Air Quality Monitoring Stations (CAAQMS) operated by the Central Pollution Control Board (CPCB) and the Karnataka State Pollution Control Board (KSPCB) across Bangalore, spanning 25 June 2018 to 31 December 2023. Quality-controlled daily averages were sorted into diurnal, seasonal (monsoon, post-monsoon, winter, summer), and yearly windows. Descriptive statistics, Chi-square tests of independence, and Pearson lag correlations (±96 intervals at 15-minute resolution, i.e. ±96 × 15 min = ±24 h) were computed in Python and R 4.0.5.

Results: PM₁₀ topped out at 77.84 µg/m³ in 2022 and PM₂.₅ at 34.36 µg/m³; both indicates the lowest annual means during COVID-19 lockdown period and 2020. Winter carried the heaviest particulate load (PM₁₀: 88.82 µg/m³; PM₂.₅: 40.32 µg/m³), while O₃ peaked in summer (36.09 µg/m³). Every Chi-square test returned p < 0.001. Independence between PM and O₃ was rejected in each temporal segment. Lag correlations peaked near +50 fifteen-minute intervals (≈ +12.5 h; O₃–PM₁₀: r = 0.191; O₃–PM₂.₅: r = 0.207), a roughly half-day delay in the ozone response to precursor emissions.

Conclusions: PM and O₃ in Bangalore are coupled statistically and through shared precursor chemistry. The coupling bears directly on forecasting, exposure assessment, and joint emission control. Real-time CAAQMS data should feed dynamic interventions, especially during winter inversions and summer photochemical episodes.