Exposure to potentially toxic trace elements (PTTEs) in inhalable particulate matter (PM) is associated with an increased risk of developing cardiorespiratory diseases. Therefore, in multi-source polluted urban contexts, a spatially-resolved evaluation of health risks associated with exposure to PTTEs in PM is essential to identify critical risk areas. In this study, a very-low volume device for high spatial resolution sampling and analysis of PM was employed in Terni (Central Italy) in a wide and dense network (23 sampling sites, about 1 km between each other) during a 15-month monitoring campaign. The soluble and insoluble fraction of 33 elements in PM was analysed through a chemical fractionation procedure that increased the selectivity of the elements as source tracers. Total carcinogenic risk (CR) and non-carcinogenic risk (NCR) for adults and children due to concentrations of PTTEs in PM were calculated and quantitative source-specific risk apportionment was carried out by applying Positive Matrix Factorization (PMF) to the spatially-resolved concentrations of the chemically fractionated elements. PMF analysis identified 5 factors: steel plant, biomass burning, brake dust, soil dust and road dust. Steel plant showed the greatest risk contribution. Total CR and NCR, and source-specific risk contributions at the 23 sites were interpolated using the ordinary kriging (OK) method and mapped to geo-reference the health risks of the identified sources in the whole study area. This also allowed risk estimation in areas not directly measured and the assessment of the risk contribution of individual sources at each point of the study area. This innovative experimental approach is an effective tool to localize the health risks of spatially disaggregated sources of PTTEs and it may allow for better planning of control strategies and mitigation measures to reduce airborne pollutant concentrations in urban settings polluted by multiple sources.
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http://dx.doi.org/10.1016/j.chemosphere.2022.135871 | DOI Listing |
Huan Jing Ke Xue
January 2025
Shaanxi Environmental Monitoring Center, Xi'an 710006, China.
To identify the spatial distribution patterns and assess the ecological risks associated with soil heavy metal pollution in the southern region of Hunan Province, a total of 362 surface soil samples were collected from the studied area. This study employed multivariate statistics and geographic information systems (GIS) to investigate the spatial distribution pattern of soil metals (Cd, Hg, As, Pb, Zn, Ni, Mn, Tl, and Sb). Furthermore, the pollution sources and source-specific ecological risk of heavy metals were quantified by combining the positive matrix factorization (PMF) model and the comprehensive ecological risk index model.
View Article and Find Full Text PDFJ Hazard Mater
December 2024
Guangdong Laboratory for Lingnan Modern Agriculture, Guangdong Provincial Key Laboratory of Agricultural & Rural Pollution Abatement and Environmental Safety, College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, China; School of Environmental Science and Engineering, Sun Yat-sen University, Guangzhou 510006, China.
This study quantified heavy metal (HM) pollution risks in mining site soils to provide targeted solutions for environmental remediation. Focusing on As waste mine sites in Yunnan, we utilised multiple indices and a positive matrix factorisation model to assess and quantify ecological health risks. Our ecological risk assessment distinguished between environmental and biological factors.
View Article and Find Full Text PDFJ Hazard Mater
November 2024
School of Energy and Environmental Engineering, Beijing Key Laboratory of Resource-Oriented Treatment of Industrial Pollutants, University of Science and Technology Beijing, Beijing 100083, China. Electronic address:
China is the largest producer and consumer of antibiotics, a nationwide study on the contamination of antibiotics in China is urgently needed, and source apportionment towards risks associated with antibiotics is now attracting increasing attention. In this study, based on eight antibiotics at 666 sampling sites, spatial variations and probabilistic risks (human health and ecological risk) of antibiotics in eight river basins in China were analyzed. Source-specific health and ecological risk associated with antibiotics in a typical basin was apportioned quantitatively.
View Article and Find Full Text PDFSci Rep
November 2024
College of Ecology and Environment, Baotou Teachers' College, Baotou, 014000, China.
In order to determine the priority control elements and sources of heavy metal(loid)s (HMs) pollution in park dust, this study collected dust samples from 25 parks in the urban area of Mianyang City and measured the contents of 10 HMs. Based on Monte Carlo simulation, the probabilistic pollution levels and ecological-health risks of HMs were assessed. We found that the average contents of Zn, Co, Pb, and Cr were much higher than their background values in local soil and were influenced by artificial activities.
View Article and Find Full Text PDFJ Hazard Mater
December 2024
Postgraduate Program in Water Resources and Environmental Engineering, Federal University of Paraná, Curitiba, Paraná, Brazil; Department of Environmental Engineering, Federal University of Paraná, Curitiba, Paraná, Brazil; Department of Chemical Engineering, Federal University of Paraná, Curitiba, Paraná, Brazil. Electronic address:
The influence of specific local land-use activities (continuously redistributing elements across environments) and environmental conditions (altering the chemical composition of airborne particulate matter) on the intrinsic health risk of PM exposure is sparsely reported. To fill this gap, we employed a novel integrated approach to address the influence of short-term changes in source-specific PM composition on the exposure-response risk, while controlling for weather conditions. We combine receptor-based source apportionment with conditional logistic regression in a space-time-stratified case-crossover design.
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