Jul 2026· Genetics and Molecular Research· 0 citations
Abstract
Background: Particulate matter is a major ambient air pollutant with important implications for respiratory, cardiovascular and population health. Local evidence on long-term PM2.5 and PM10 trends is needed for air quality surveillance and public health planning in smaller coastal urban settings such as Puducherry. Objectives: To assess annual, monthly and seasonal trends of 24-hour average PM2.5 and PM10 concentrations in Puducherry from 2021 to 2025, and to quantify exceedance of World Health Organization (WHO) guideline values and Indian National Ambient Air Quality Standards (NAAQS). Methods: A cross-sectional time-series analysis was conducted using daily 24-hour average PM2.5 and PM10 observations from the Jawahar Nagar, Puducherry monitoring dataset for 1 January 2021 to 31 December 2025. Seasons were classified as winter (January-February), summer (March-May), monsoon (June-September) and post-monsoon (October-December). Descriptive statistics, annual and seasonal comparisons, exceedance analysis, Spearman correlation and Kruskal-Wallis tests were used. Missing observations were excluded by available-case analysis. Results: Of 1,826 calendar days, valid observations were available for 1,762 PM2.5 days and 1,753 PM10 days. Annual mean PM2.5 ranged from 20.20 ± 13.89 µg/m³ in 2021 to 26.60 ± 19.09 µg/m³ in 2025. Annual mean PM10 ranged from 41.88 ± 19.17 µg/m³ in 2024 to 51.97 ± 21.64 µg/m³ in 2023. All annual means were below Indian annual NAAQS values for PM2.5 and PM10, but daily WHO 2021 guideline exceedance was frequent. PM2.5 exceeded the WHO 24-hour guideline on 52.9% to 68.2% of valid days across years, whereas PM10 exceeded it on 36.1% to 59.2% of valid days. Seasonal variation was significant for both PM2.5 and PM10 (both p<0.001), with winter and post-monsoon generally showing higher concentrations and monsoon showing lower concentrations. PM2.5 and PM10 were strongly correlated overall (Spearman ρ=0.870, p<0.001). Conclusion: Puducherry showed moderate annual particulate concentrations by Indian annual standards, but substantial daily exceedance of WHO guideline values and clear seasonal peaks. Continuous monitoring, season-specific mitigation and source-oriented control strategies are warranted.
Elevated ambient particulate matter levels have become a critical urban sustainability concern in India, endangering health and well‐being (UN SDG 3) of a vast section of the population. We present an exploratory seasonal analysis (ESA) of the ambient PM
2.5
and PM
10
concentrations, for nine Indian cities, using daily archival records from the Central Control Room for Air Quality Management (CAQM) for 2023. The ESA results revealed distinct seasonality in both PMs, varying as post‐monsoon (most polluted) > winter > summer > monsoon (cleanest). The National Capital Region (NCR: Delhi, Gurugram, Noida) appeared the most vulnerable to PM pollution, with Delhi as the most polluted among the nine cities, while Varanasi, the cleanest. Jaipur and Ahmedabad revealed concerns over windblown dust in summer, elevating the PM
10
risks. Seasonal PM
2.5
/PM
10
ratios indicated that besides fuel combustion in general, there is need for more location‐specific air quality control mechanisms, addressing local sources. For each city, about 9%–10% of the days appeared as “outlier”, representing sudden high spikes in PM levels. Both PMs exceeded the WHO health safety thresholds for about 90%–95% of days, even during monsoon, while for 99–100% of the days in winter and post‐monsoon times indicating year‐round public health concerns. Hierarchical Clustering (HCA) offered a spatio‐temporal (city‐season) PM
2.5
‐vulnerability ranking scheme comprising of four statistically distinguishable clusters: Cluster 1 (148.67 ± 17.94 µg.m
−3
) > Cluster 3 (79.469 ± 1.51 µg.m
−3
) > Cluster 4 (59.90 ± 6.31 µg.m
−3
) > Cluster 2 (32.64 ± 7.24 µg.m
−3
). Cluster 1 represented the NCR cities for post‐monsoon and winter, while cluster 2 included all nine cities for monsoon and summer. Overall, HCA outputs could help setting up a joint action plan, bringing together various city municipal bodies to address the PM pollution. Applying Multiple Linear Regression (MLR) to the HCA clusters individually, revealed significant (
p
< 0.05) statistical associations between meteorological parameters and PM2.5 concentrations in HCA clusters 1 (R
2
: 0.76) and 3 (R
2
: 0.67), while significantly lower for clusters 4 (R
2
: 0.52), and negligible for Cluster 2 (R
2
: 0.39). In Cluster 1 and 3, relative humidity and rainfall (monsoon season) exhibited strong inverse statistical relationships with PM
2.5
levels, consistent with potential scavenging and wet deposition processes to reduce the PM
2.5
risks, which was aggravated during post‐monsoon and winter. The latter occurred due to atmospheric stagnation (low wind speed, low solar radiance, cooler temperatures) that trapped the PM
2.5
near the ground. Meteorological influences, however, were minimal for HCA cluster 2 (R
2
: 0.39), indicating importances of other factors (e.g., built‐up types and geometry; emission sources types, vegetation type and density) that need to be researched further. In the final sections, we reflect on a future vision about reimagining the urban transport sector, aligning policies with UN SDGs 7 (clean energy), 9 (infrastructure, and innovation) 16 (institution building) and 17 (forging multi‐sectoral partnerships) to address the particulate pollution crises.
This study investigated the spatiotemporal variability of fine particulate matter (PM2.5) in Addis Ababa, Ethiopia and assessed its associated health risks and economic burden using data from January 2022 to December 2023. Hourly PM2.5 concentrations were collected through a hybrid monitoring network comprising seven low-cost sensors and two Beta Attenuation Monitors (BAM). Spatiotemporal analysis was performed using Python, and health risks were assessed by estimating the Hazard Quotient (HQ) and Excess Lifetime Cancer Risk (ELCR). The economic burden attributable to PM2.5 exposure was assessed by monetizing disease-specific Disability-Adjusted Life Years (DALYs) using a locally adapted Value of Statistical Life (VSL) approach. Over the two-year periods, mean PM2.5 concentrations ranged from 15 to 33 μg/m3 across monitoring sites, with an overall a citywide average of 27 μg/m3, exceeding the World Health Organization (WHO) Air Quality Guideline (AQG) of 5 μg/m3 by more than fivefold. Seasonal analysis revealed elevated PM2.5 concentrations during the wet season (Kiremt), while diurnal patterns showed peaks of 38 µg/m3 at 7:00 AM. The HQ values for all age groups exceeded the acceptable threshold of 1, indicating non-carcinogenic health risks. ELCR estimates calculated using a slope factor of 0.008 exceeded the risk threshold (1 ×10-4), whereas estimates based on the slope factor of 0.0012 remained within the acceptable limits, highlighting the sensitivity of cancer risk estimates to the toxicity parameter applied. The economic burden attributable to PM2.5 exposure was estimated at USD 652.95 million over the two-year study period, contributing an external cost share to national GDP of 0.25% in 2022 and 0.25% in 2023. Cardiovascular diseases, particularly ischemic heart disease (IHD), accounted for the largest share of economic losses, significantly exceeding acute respiratory infections and PM2.5 related cancers. These findings provide evidence to support targeted policies aimed at reducing PM2.5 related cancers combined.
The Paal Dua area of Manado City is an urban area characterized by intensive traffic and commercial activities that may contribute to elevated particulate matter concentrations in ambient air. This study aimed to determine and analyze Total Suspended Particulate (TSP), PM10, and PM2.5 concentrations at three sampling sites with different environmental characteristics and to evaluate their compliance with ambient air quality standards specified in Government Regulation No. 22 of 2021, Annex VII. Measurements were conducted for 24 hours at each site using a High Volume Air Sampler (HVAS) and the gravimetric method, following SNI 7119.3:2017 for TSP, SNI 7119.15:2016 for PM10, and SNI 7119.14:2016 for PM2.5. Although all methods employ the same gravimetric principle, they differ in particle-size-selective inlet specifications. TSP concentrations ranged from 6.19 to 24.46 µg/m³, PM10 from 1.38 to 10.89 µg/m³, and PM2.5 from 0.24 to 3.83 µg/m³. The highest TSP and PM10 concentrations were observed at Site 1, near a road and market area, while PM2.5 concentration at Site 3 exceeded that at Site 2. This spatial difference was presumably associated with prevailing wind direction and surrounding building configuration, although meteorological and statistical analyses are required for confirmation. All measured particulate concentrations were below ambient air quality standards during August 2025. These results represent conditions during the sampling period and cannot be generalized to the entire Paal Dua area. Periodic monitoring with broader spatial and temporal coverage is recommended. The study provides information on particulate matter distribution across locations with different emission sources and urban configurations.
