Health risk assessment of the European inhabitants exposed to contaminated ambient particulate matter by potentially toxic elements

Broomandi, Parya; Rodríguez-Seijo, Andrés; Janatian, Nasime; Fathian, Aram; Tleuken, Aidana; Mohammadpour, Kaveh; Galán-Madruga, David; Jahanbakhshi, Ali; Kim, Jong Ryeol; Satyanaga, Alfrendo; Bagheri, Mehdi; Morawska, Lidia

doi:10.1016/j.envpol.2023.121232

Environmental Pollution

2023

DOI: 10.1016/j.envpol.2023.121232

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Health risk assessment of the European inhabitants exposed to contaminated ambient particulate matter by potentially toxic elements

Parya Broomandi

Andrés Rodríguez-Seijo

Nasime Janatian

et al.

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Cited by 12 publications

(1 citation statement)

References 77 publications

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“…For instance, Cardito et al ( 2023 ) employed the inverse distance weighting tool to analyze the spatial distribution of six air pollutants and evaluate the impact of COVID-19 lockdown regulations on air pollution in Campania, Italy. Similarly, Broomandi et al ( 2023 ) utilized the same interpolation algorithm to assess the health risks associated with metal-containing particulate matter in 158 European cities between 2013 and 2019, mapping the spatial correlation between potentially toxic elements and time. In another study, Kumar et al ( 2020 ) investigated the influence of traffic-related air pollutants and associated risks along major transport corridors in Delhi.…”

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confidence: 99%

Elucidating Best Geospatial Estimation Method Applied to Environmental Sciences

de Lourdes Berrios Cintrón,

Broomandi,

Cárdenas-Escudero

et al. 2023

Bull Environ Contam Toxicol

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The aim of this study is to assess and identify the most suitable geospatial interpolation algorithm for environmental sciences. The research focuses on evaluating six different interpolation methods using annual average PM10 concentrations as a reference dataset. The dataset includes measurements obtained from a target air quality network (scenery 1) and a sub-dataset derived from a partitive clustering technique (scenery 2). By comparing the performance of each interpolation algorithm using various indicators, the study aims to determine the most reliable method. The findings reveal that the kriging method demonstrates the highest performance within environmental sciences, with a spatial similarity of approximately 70% between the two scenery datasets. The performance indicators for the kriging method, including RMSE (root mean square error), MAE (mean absolute error), and MAPE (mean absolute percentage error), are measured at 3.2 µg/m3, 10.2 µg/m3, and 7.3%, respectively.This study addresses the existing gap in scientific knowledge regarding the comparison of geospatial interpolation techniques. The findings provide valuable insights for environmental managers and decision-makers, enabling them to implement effective control and mitigation strategies based on reliable geospatial information and data. In summary, this research evaluates and identifies the most suitable geospatial interpolation algorithm for environmental sciences, with the kriging method emerging as the most reliable option. The study’s findings contribute to the advancement of knowledge in the field and offer practical implications for environmental management and planning.

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mentioning

confidence: 99%

Elucidating Best Geospatial Estimation Method Applied to Environmental Sciences

de Lourdes Berrios Cintrón,

Broomandi,

Cárdenas-Escudero

et al. 2023

Bull Environ Contam Toxicol

Self Cite

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Research on characteristics and influencing factors of road dust emission in a southern city in China

Li,

Wang,

Liang

et al. 2024

Environ Monit Assess

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PM2.5 and PM10-related carcinogenic and non-carcinogenic risk assessment in Iran

Anbari,

Sicard,

Khaniabadi

et al. 2024

J Atmos Chem

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Health risk assessment of the European inhabitants exposed to contaminated ambient particulate matter by potentially toxic elements

Cited by 12 publications

References 77 publications

Elucidating Best Geospatial Estimation Method Applied to Environmental Sciences

Elucidating Best Geospatial Estimation Method Applied to Environmental Sciences

Research on characteristics and influencing factors of road dust emission in a southern city in China

PM2.5 and PM10-related carcinogenic and non-carcinogenic risk assessment in Iran

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