Assessment of Population Exposure to Coarse and Fine Particulate Matter in the Urban Areas of Chennai, India

Effect of PM2.5 on burden of mortality from non-communicable diseases in northern Thailand

Background

Particulate pollution, especially PM2.5from biomass burning, affects public and human health in northern Thailand during the dry season. Therefore, PM2.5exposure increases non-communicable disease incidence and mortality. This study examined the relationship between PM2.5and NCD mortality, including heart disease, hypertension, chronic lung disease, stroke, and diabetes, in northern Thailand during 2017-2021.

Methods

The analysis utilized accurate PM2.5data from the MERRA2 reanalysis, along with ground-based PM2.5measurements from the Pollution Control Department and mortality data from the Division of Non-Communicable Disease, Thailand. The cross-correlation and spearman coefficient were utilized for the time-lag, and direction of the relationship between PM2.5and mortality from NCDs, respectively. The Hazard Quotient (HQ) was used to quantify the health risk of PM2.5to people in northern Thailand.

Results

High PM2.5 risk was observed in March, with peak PM2.5concentration reaching 100 µg/m3, with maximum HQ values of 1.78 ± 0.13 to 4.25 ± 0.35 and 1.45 ± 0.11 to 3.46 ± 0.29 for males and females, respectively. Hypertension significantly correlated with PM2.5levels, followed by chronic lung disease and diabetes. The cross-correlation analysis showed a strong relationship between hypertansion mortality and PM2.5at a two-year time lag in Chiang Mai (0.73) (CI [-0.43-0.98], p-value of 0.0270) and a modest relationship with chronic lung disease at Lampang (0.33) (a four-year time lag). The results from spearman correlation analysis showed that PM2.5concentrations were associated with diabetes mortality in Chiang Mai, with a coefficient of 0.9 (CI [0.09-0.99], p-value of 0.03704). Lampang and Phayao had significant associations between PM2.5 and heart disease, with coefficients of 0.97 (CI [0.66-0.99], p-value of 0.0048) and 0.90 (CI [0.09-0.99], p-value of 0.0374), respectively, whereas Phrae had a high coefficient of 0.99 on stroke.

A spatial approach to assessing PM2.5 exposure level of a brickmaking community in South Africa

Globally, particulate matter with an aerodynamic diameter of 2.5 µm or less poses a significant threat to human health. The first step in quantifying human health impacts caused by exposure to PM2.5 pollution is exposure assessment. Population-weighted exposure level (PWEL) estimation is one of the methods that provides a more precise exposure assessment since it incorporates the spatiotemporal distribution of population with the pollution concentration estimate. In this study, PM2.5 exposure levels in the local communities around brickmaking industries were investigated, using the population census data of the study area and 1-year data from nine PM2.5 monitoring stations installed in and around the brickmaking industries. The observed PM2.5 data was spatially interpolated using inverse distance weight (IDW). Data on PM2.5 levels across the study area were classified based on the World Health Organization interim target (IT) guidelines and the South African National ambient air quality standard (NAAQS). An annual PM2.5 population weighted exposure level of 27.6 µg/m3 was estimated for the study area. However, seasonal exposure levels of 28.9, 37.6, 26.5, and 20.7 µg/m3 were estimated for the autumn, winter, spring, and summer seasons, respectively. This implies that local communities around the brick kiln in the Vhembe District are exposed to high levels of PM2.5, especially in winter. The PM2.5 levels in the brickmaking industries as well as its other sources in the Vhembe District, therefore, need to be lowered. Findings from population exposure level to pollutants can provide valuable data for formulating policies and recommendations on exposure reduction and public health protection.Implications: PM2.5 concentration in any given environment has high spatial and temporal variability due to the presence of diffused sources in the environment. Using ambient air concentrations to directly estimate population exposure without taking into consideration the disproportionate spatial and temporal distribution of the pollutant and the population may not yield accurate results on human exposure levels. It is, therefore, important to assess the aggregated PM2.5 exposure of a populace within a given area. This study therefore examines the PM2.5 population-weighted-exposure level of the host communities of the brickmaking industry in Vhembe District, South Africa.

Toxic External Exposure Leading to Ocular Surface Injury

The surface of the eye is directly exposed to the external environment, protected only by a thin tear film, and may therefore be damaged by contact with ambient particulate matter, liquids, aerosols, or vapors. In the workplace or home, the eye is subject to accidental or incidental exposure to cleaning products and pesticides. Organic matter may enter the eye and cause infection. Ocular surface damage can trigger a range of symptoms such as itch, discharge, hyperemia, photophobia, blurred vision, and foreign body sensation. Toxin exposure can be assessed clinically in multiple ways, including via measurement of tear production, slit-lamp examination, corneal staining, and conjunctival staining. At the cellular level, environmental toxins can cause oxidative damage, apoptosis of corneal and conjunctival cells, cell senescence, and impaired motility. Outcomes range from transient and reversible with complete healing to severe and sight-compromising structural changes. Classically, evaluation of tolerance and safety was carried out using live animal testing; however, new in vitro and computer-based, in silico modes are superseding the gold standard Draize test. This review examines how environmental features such as pollutants, temperature, and seasonality affect the ocular surface. Chemical burns to the eye are considered, and approaches to protect the ocular surface are detailed.

Effects of Population Weighting on PM10 Concentration Estimation

Particulate matter with an aerodynamic diameter of 10 μm or less (PM₁₀) pollution poses a considerable threat to human health, and the first step in quantifying health impacts of human exposure to PM₁₀ pollution is exposure assessment. Population-weighted exposure level (PWEL) estimation is one of the methods that provide a more refined exposure assessment as it includes the spatiotemporal distribution of the population into the pollution concentration estimation. This study assessed the population weighting effects on the estimated PM₁₀ concentrations in Malaysia for years 2000, 2008, and 2013. Estimated PM₁₀ annual mean concentrations with a spatial resolution of 5 kilometres retrieved from satellite data and population count obtained from the Gridded Population of the World version 4 (GPWv4) from the Centre for International Earth Science Information Network (CIESIN) were overlaid to generate the PWEL of PM₁₀ for each state. The calculated PWEL of PM₁₀ concentrations were then classified based on the World Health Organization (WHO) and the national Air Quality Guidelines (AQG) and interim targets (IT) for comparison. Results revealed that the annual mean PM₁₀ concentrations in Malaysia ranged from 31 to 73 µg/m³ but became generally lower, ranging from 20 to 72 µg/m³ after population weighting, suggesting that the PM₁₀ population exposure in Malaysia might have been overestimated. PWEL of PM₁₀ distribution showed that the majority of the population lived in areas that complied with the national AQG, but were vulnerable to exposure level 3 according to the WHO AQG and IT, indicating that the population was nevertheless potentially exposed to significant health effects from long-term exposure to PM₁₀ pollution.