Search engine for discovering works of Art, research articles, and books related to Art and Culture
ShareThis
Javascript must be enabled to continue!

Co-Occurrence and Correlation Trends of PM₁₀, PM₂.₅, and O₃ in Bangalore City: Diurnal, Seasonal, and Inter-Annual Coupling and Its Implications

View through CrossRef
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.
Title: Co-Occurrence and Correlation Trends of PM₁₀, PM₂.₅, and O₃ in Bangalore City: Diurnal, Seasonal, and Inter-Annual Coupling and Its Implications
Description:
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.
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.

Related Results

Status of air quality in Rajshahi metropolitan area, Bangladesh
Status of air quality in Rajshahi metropolitan area, Bangladesh
Rajshahi is well-known as a model city for clean air in Bangladesh but in recent time air pollution is increasing in metropolitan areas. This study aims to examine the concentratio...
Atmospheric Monitoring of PM₂.₅, PM₁₀₋₂.₅, PM₁₀, Arsenic and Carbonaceous Aerosol at Wainuiomata
Atmospheric Monitoring of PM₂.₅, PM₁₀₋₂.₅, PM₁₀, Arsenic and Carbonaceous Aerosol at Wainuiomata
<p>Air pollution is harming our health and that of our children and parents. Air pollution causes many harmful effects, ranging from premature death, to headaches, coughing a...
Air pollution dynamics in arid urban-industrial zones for environmental engineering management
Air pollution dynamics in arid urban-industrial zones for environmental engineering management
Air pollution assessment in arid and rapidly urbanizing regions is challenged by complex source interactions, strong meteorological influences, and limited monitoring infrastructur...
Mapping and analysis of topography of Bangalore metropolitan region
Mapping and analysis of topography of Bangalore metropolitan region
Bangalore was built by Magadi Kempegowda at 1537. Bangalore ruled by various kingdom in 1758- Hyder Ali, in 1799- British overthrew Tippu sultan, in 1881- Mysore wodeyar, After the...
Air Pollution and Public Health: A Multi-City Assessment of PM₂.₅ Exposure in Punjab, Pakistan
Air Pollution and Public Health: A Multi-City Assessment of PM₂.₅ Exposure in Punjab, Pakistan
Particulate matter, particularly PM₂.₅ continues to be a critical determinant of the global disease burden, underscoring the scale of exposure and the multifaceted processes throug...
Altitude distribution of fine particulate matters PM₁ PM₂.₅ and PM₁₀ in Bangkok
Altitude distribution of fine particulate matters PM₁ PM₂.₅ and PM₁₀ in Bangkok
Fine particulate matter particles with a diameter less than 1 micron (PM1), less than 2.5 micron (PM₂.₅) and less than 10 micron (PM₂.₅) have been measured in different height 1.5 ...
Study on Urban Thermal Environment based on Diurnal Temperature Range
Study on Urban Thermal Environment based on Diurnal Temperature Range
&lt;p&gt;Diurnal temperature range (includes land surface temperature diurnal range and near surface air temperature diurnal range) is an important meteorological parameter...
Macroeconomic and Social Precursors of Suicide Rates in the Philippines: A Quantitative Analysis (Preprint)
Macroeconomic and Social Precursors of Suicide Rates in the Philippines: A Quantitative Analysis (Preprint)
BACKGROUND Suicide is a complex, serious and multifaceted public health issue that poses significant challenges to societies worldwide. In fact, it represen...

Back to Top