Health risk assessment and source apportionment of potentially toxic metal(loid)s in windowsill dust of a rapidly growing urban settlement, Iran

Comparison of dust and surface soil heavy metals and some element contents in erbil city as a sign of environmental pollution

The purpose of the study was to compare the levels of Heavy metals and some elements in the dust and soil close to the Lanaz oil refinery and the steel industry in Erbil-Iraq, as indicators of environmental contamination. Accordingly, ten different sites were investigated based on their distances from the pollution sources. Results of the study showed that dust was significantly more contaminated with elements than urban soil, particularly Pb, As, Hg, and Sb with t values (p < 0.01) of 2.170**, 2.104**, -0.985**, and -3.187** respectively. Significant variations between all of the distances under study were found via statistical analysis. The order of heavy metals and elements abundance was the same in both soil and dust as: Fe > Zn > Mn > Pb > Cr > Cu > Ni > As > Co > V > Sb > Se > Hg > Cd. Ni, Cr, and Zn concentrations in soil exceeded WHO limits. The contamination factor of dust and soil's Pb, As, Co, Cr, Mn, Zn, Cu, Fe, Ni, V, Se, and Sb contents showed very high pollution (CF > 6). Ni was the main contributor to soil pollution 250-1500 m away from pollution sources. The pollution load index (PLI) for dust and soils indicated deterioration of the site's quality in the distances from 250-750 and 250-500m respectively. Dust posed very strong Pb, As, and Zn health risks (RI ≥ 440) in 250 m from pollution sources, whereas, only Sb showed powerful health risks in soils from 250-1250 m.

Spatial distribution pattern and health risk of groundwater contamination by cadmium, manganese, lead and nitrate in groundwater of an arid area

Combining the results of base models to create a meta-model is one of the ensemble approaches known as stacking. In this study, stacking of five base learners, including eXtreme gradient boosting, random forest, feed-forward neural networks, generalized linear models with Lasso or Elastic Net regularization, and support vector machines, was used to study the spatial variation of Mn, Cd, Pb, and nitrate in Qom-Kahak Aquifers, Iran. The stacking strategy proved to be an effective substitute predictor for existing machine learning approaches due to its high accuracy and stability when compared to individual learners. Contrarily, there was not any best-performing base model for all of the involved parameters. For instance, in the case of cadmium, random forest produced the best results, with adjusted R2 and RMSE of 0.108 and 0.014, as opposed to 0.337 and 0.013 obtained by the stacking method. The Mn and Cd showed a tight link with phosphate by the redundancy analysis (RDA). This demonstrates the effect of phosphate fertilizers on agricultural operations. In order to analyze the causes of groundwater pollution, spatial methodologies can be used with multivariate analytic techniques, such as RDA, to help uncover hidden sources of contamination that would otherwise go undetected. Lead has a larger health risk than nitrate, according to the probabilistic health risk assessment, which found that 34.4% and 6.3% of the simulated values for children and adults, respectively, were higher than HQ = 1. Furthermore, cadmium exposure risk affected 84% of children and 47% of adults in the research area.

Assessment of potentially toxic elements in atmospheric dust and associated health risks in Zahedan City, Iran

Zahedan City is situated in the Sistan basin, a highly active dust source region that poses significant risks to human and ecological health due to potentially toxic elements (PTEs) present in atmospheric dust. In this study, we investigated the concentration, sources, and human health risk assessment of PTEs in 88 monthly atmospheric dust samples collected between December 2020 and October 2021 using inductively coupled plasma mass spectrometry. The results showed that the concentrations of PTEs in atmospheric dust followed the descending order of Mn > Zn > Ba > Sr > Cr > V > Ni > Cu > Pb > Co > As > Mo > Cd. The calculated enrichment factors revealed significant enrichment for As > Zn, moderate enrichment Pb > Ni, deficiency to minimal enrichment for Cr > Mn > Fe > Sr > Cd > V > Cu > Ba > Co, and no enrichment for Mo. Arsenic was found to be the major contributor to the potential ecological risk index, accounting for 55% of the total risk. The widespread utilization of arsenic-based pesticides in the surrounding agricultural lands may be a significant contributor to the severe arsenic pollution in the region. The winter season exhibited the highest monthly mean concentrations of Zn and Pb possibly due to temperature inversions trapping local anthropogenic pollutants near the Earth's surface. Cluster analysis revealed a strong correlation between Ni-Cr-Fe-V-Mn-Al, which shows mainly the geogenic source for these elements. The predominant exposure route for non-carcinogenic risk to humans was ingestion. The hazard index (HI) values for the heavy metals studied decreased in the following order: Cr > As > Pb > Ni > Zn > Cu > Cd, for both children and adults. The HI values indicated that there was no possible non-carcinogenic risk associated with exposure to these heavy metals in Zahedan's atmospheric dust. The result of the inhalation cancer risk assessment suggested that while the potential risks of cancer for As, Cd, Cr, and Ni were below the safe level, the levels of Chromium were close enough to the threshold to warrant further investigation and monitoring.

Effects of Road Dust Particle Size on Mineralogy, Chemical Bulk Content, Pollution and Health Risk Analyses

Because of the rising environmental and health concerns associated with atmospheric pollution caused by potentially toxic elements (PTEs), several road dust studies have been performed across the world in recent decades. This paper illustrates the effects of particle size on the PTE contents, mineralogical composition, environmental pollution and health risk assessments in road dust from Barcelona (Spain). The samples were sieved into five size fractions ranging from <45 to 500-800 µm. Although the major mineral contents (tectosilicates, phyllosilicates, and carbonates) were profuse in all fractions, the identified inhalable PTE particles (e.g., Fe, Cr, Cu, Zn, Ni, and REE), with size < 10 µm, were more pervasive in the finest fraction (<45 μm). This is consistent with the concentrations measured: the finest fractions were richer in PTEs than the coarser ones, resulting in a direct correlation with the enrichment factor (EFx), geo-accumulation (Igeo), and non-carcinogenic (HI) and carcinogenic (CRI) values. Igeo and EFx values can be appropriate tracers for some common elements (e.g., Zn, Sb, Sn, Cu, and Cr), but they do not seem adequate for anthropogenic particles accumulated at concentrations similar to the geogenic background. Overall, the HI and CRI values obtained in Barcelona were acceptable, reflecting no serious health impacts in the study area, except for Cr. Our results suggest that fine dust particles are a more suitable fraction to conduct pollution and health risk assessments than coarser ones, although the EFx, Igeo, HI, and CRI threshold values should be redefined in the future to include all emergent pollutants as well. In summary, monitoring programs should include at least the road dust evaluation of <45 µm particles, which can be performed with a simple sieving method, which is both time- and cost-effective.

Pollution Profiles, Source Identification and Health Risk Assessment of Heavy Metals in Soil near a Non-Ferrous Metal Smelting Plant

Heavy metal pollution related to non-ferrous metal smelting may pose a significant threat to human health. This study analyzed 58 surface soils collected from a representative non-ferrous metal smelting area to screen potentially hazardous heavy metals and evaluate their health risk in the studied area. The findings demonstrated that human activity had contributed to the pollution degrees of Cu, Cd, As, Zn, and Pb in the surrounding area of a non-ferrous metal smelting plant (NMSP). Cu, Cd, As, Zn, Pb, Ni, and Co pollution within the NMSP was serious. Combining the spatial distribution and Spearman correlations with principal component analysis (PCA), the primary sources of Cd, As, Pb, and Zn in surrounding areas were related to non-ferrous metal smelting and transportation activities. High non-cancer (THI = 4.76) and cancer risks (TCR = 2.99 × 10^-4) were found for adults in the NMSP. Moreover, heavy metals in the surrounding areas posed a potential cancer risk to children (TCR = 3.62 × 10^-6) and adults (TCR = 1.27 × 10^-5). The significant contributions of As, Pb, and Cd to health risks requires special attention. The construction of a heavy metal pollution management system will benefit from the current study for the non-ferrous metal smelting industry.