Concentrations and Health Implications of PM2.5, PM10, and Gaseous Pollutants in Communities near Ibom Power Company, Ikot Abasi, Nigeria

Air Quality Based on Particulate Matter Concentrations (TSP, PM10, and PM2.5) in Paal Dua, Manado City

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.

Assessment and Modelling of Particulate Matter (PM2.5 and PM10) Concentration around North Central Region of Nigeria

Air Pollution has become one of the most conspicuous pollutants around the globe today, for which Particulate Matter (PM2.5 and PM10) is inclusive, having the highest air pollutant index (API) value contrasted with the other criteria contaminations. Long-term exposure to these pollutants may lead to a marked reduction in life expectancy due to increase in cardiopulmonary and lung disease mortality. This study provides baseline data on Particulate Matter (PM2.5 and PM10) concentration in the region and models it to indirect data using the average direct satellite captured data sourced 24 Hours from NASA through NASRDA software. A number of anthropogenic activities increase the concentration of PM2.5 and PM10 in the North Central Region of Nigeria, which are linked to health issues in the area. PM2.5 and PM10 are fine atmospheric particles and coarse particles, respectively that contribute to the low life expectancy of less than 60 years in Nigeria. The absence of Particulate Matter monitoring stations and inadequate equipment in the Country for timely prediction of its status for information that permits the regulatory authority and local community to take prudent steps and lessen the effect of particulate contamination, calls for the use of forecast models that would readily ensure data availability. This study applies the Multiple Linear Regression (MLR) model to predict Particulate Matter (PM2.5 and PM10) concentration and Air Quality Index prediction in Six States and the Federal Capital Territory which has two main seasons (Dry and Wet) in 2020, 2021 and 2022. The meteorological variables (of temperature) for the average of 12 Months was used to model the concentration. The Air Quality Index was calculated with the indirect data and it showed a percentile difference of about 5% between direct and indirect Particulate Matter concentration. The highest AQI for PM10 concentration for the direct data across the locations were 103µg/m3, 101 µg/m3 and 103 µg/m3 for 2020, 2021 and 2022 respectively while the lowest were 79 µg/m3, 82 µg/m3 and 83 µg/m3 for the same 2020, 2021 and 2022 respectively. For PM2.5 concentration, the AQI for the direct data across the locations were 51µg/m3, 53 µg/m3 and 53 µg/m3 in 2020, 2021 and 2022 respectively while the lowest were 32 µg/m3, 45 µg/m3 and 27 µg/m3 for 2020, 2021 and 2022 respectively. The highest AQI for PM10 concentration for the indirect data across the locations were 113µg/m3, 111 µg/m3 and 113 µg/m3 in 2020, 2021 and 2022 respectively while the lowest were 89 µg/m3, 92 µg/m3 and 93 µg/m3 in 2020, 2021 and 2022 respectively. The highest AQI for PM2.5 concentration indirect data across the locations were 53µg/m3, 53 µg/m3 and 52 µg/m3 in 2020, 2021 and 2022 respectively while the lowest were 45 µg/m3, 41 µg/m3 and 39 µg/m3 in 2020, 2021 and 2022 respectively. The AQIs with highest concentration for all the years exceeded the WHO World Annual Standard of 24 Hours for both PM2.5 and PM10 which is <50 µg/m3 and <100 µg/m3 respectively. This result is unhealthy for such locations and is a contributing factor to cases of cardiopulmonary and lung disease mortality around the region. The performance indicators used are Root Mean Square Error (RMSE) and the value of coefficient determination (R2). The error in the model was evaluated based on RMSE and the accuracy was assessed using R2. The increasing values of R2 and decreasing RMSE indicated that the Particulate Matter (PM2.5 and PM10) is very well explained by the input variable in the model being developed. It’s either RMSE was decreasing or increasing and R2 increasing or decreasing for each location. The indicator showed that the calculated indirect AQI and concentration can be relied on across the locations in the absence of direct data from Polar Satellites.

Health impacts of PM2.5 exposure at moderate concentrations (below 35 µg/m3)

Assessment of PM2.5 exposure and respiratory health risks for vulnerable populations in urban underpass: a predictive MLR approach in Chiang Mai, Thailand

Characteristics, Sources, and Health Risks of PM2.5-Bound Heavy Metals in School Environments: A Comparative Study of Two Cities in South China.

The results highlighting the need for continued source control in school environments, with special attention to nonexhaust traffic emissions and industrial combustion, highlight the need for continued source control in school environments.

Spatiotemporal Variation of PM2.5 Concentration and Health Impacts in Addis Ababa, Ethiopia: Trends and Patterns

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.