Environmental Geochemistry and Health最新文献

This study provides a detailed size-resolved analysis of atmospheric particulate matter (PM) collected in two contrasting European capitals, Oslo and Budapest, during summer and winter campaigns. Using 13-stage cascade impactors, we assessed the mass size distributions of over 30 elements and analyzed arsenic (As) compounds to identify their sources and potential health risks. Advanced data analyses, including Kaplan-Meier estimation for censored data, Atmospheric Particle Size Distribution (APSD) analysis, and Enrichment Factor (EF) calculations, revealed distinct behaviors among the elements. We observed a clear separation of sources based on particle size. Crustal elements such as aluminum (Al), iron (Fe), and calcium (Ca) were primarily found in the coarse mode (greater than 2.5 µm), originating from natural soil and resuspended road dust. In contrast, anthropogenic tracers like sulfur (S), As, cadmium (Cd), and lead (Pb) were concentrated in the accumulation mode (approximately 0.1-1.0 µm), which is characteristic of high-temperature combustion and secondary aerosol formation. A significant finding of our study was the predominance of inorganic arsenic (As_inorg) over organic species [dimethylarsinic acid (DMA) and trimethylarsine oxide (TMAO)] across all campaigns. As_inorg consistently peaked in the fine fraction and closely tracked the distribution of total As, indicating a substantial potential for deep respiratory deposition. Source apportionment analysis revealed notable seasonal and geographical differences. In Oslo, there was an accumulation-mode enrichment of vanadium (V) and nickel (Ni), indicating that shipping emissions were a major source of pollution. In Budapest, winter pollution was influenced by distinct local factors: potassium (K) shifted to the accumulation mode, pointing to biomass burning, while Pb exhibited a significant increase in the coarse mode, suggesting the resuspension of legacy soil contamination. These findings highlight the importance of size-resolved speciation for accurate source identification and health risk assessment in urban environments.

Reliable geochemical baselines are largely absent for northern Ghana, limiting efforts to distinguish natural element variability from human-induced contamination. This study addresses that gap by evaluating soil geochemical compositions in the Bongo and Talensi districts, where limited prior characterization has hindered accurate environmental assessment. Using an integrated geostatistical and machine-learning framework, regional background and baseline values were established to support environmental monitoring, land-use planning, and resource management. Three complementary geostatistical approaches; Iterative (3σ), Frequency Distribution, and Concentration-Area (C-A), were combined with clustering and regression-based learning to delineate geochemical zones and identify key elemental drivers. Machine-learning analysis identified Cd, Sb, Ge, and Ag as the main predictors distinguishing the Bongo and Talensi geochemical provinces. The Bongo province, underlain by felsic granitoids, is dominated by silicate weathering and low trace-metal variability, whereas Talensi reflects metavolcanic and hydrothermally influenced soils with localized metal enrichment. Chromium (Cr) exhibited the highest mean concentration (276.6 mg/kg), exceeding international soil-quality limits, while Cu (7.9 mg/kg), Pb (4.8 mg/kg), and Zn (26.2 mg/kg) remained within safe thresholds. The enrichment of Cr and related baseline ratios indicate that trace-metal variations arise chiefly from natural bedrock composition. The results provide reliable geochemical baselines essential for contamination assessment, environmental regulation, and mineral exploration. This study delivers the first integrated geostatistical-machine-learning framework for northern Ghana, offering a practical tool for sustainable land-use and resource-management decision-making.

Mining activities are not only sources of potentially toxic element (PTE) pollution, but are also closely associated with natural radioisotopes. This study combined uranium radioisotopes to better understand the behavior of mine-derived PTEs in lake sediments. We collected surface sediments near an abandoned mine in Lake Daecheong, South Korea, and determined the concentration distribution of PTEs (Pb, Zn, Cu, Cr, Ni, As, Cd, and Hg) and uranium radioisotopes (²³⁵U and ²³⁸U) using an inductively coupled plasma mass spectrometer and a gamma spectrometer, respectively. The mean Zn, Cu, Ni, and Cd concentrations in the tributary near the mine were significantly higher than those of other PTEs, and their distributions tended to decrease downstream. The mean concentrations and distributions of ²³⁵U and ²³⁸U showed a consistent trend similar to that of PTEs. PTE pollution was extremely high only in sites downstream of the tributary directly affected by the mine. Zn, Cu, Ni, Cd, ²³⁵U, and ²³⁸U were closely related and were the most important factors controlling PTE origin. Consequently, the surface sediments were dominated by mine-derived PTEs (Zn, Cu, Ni, and Cd), suggesting a close relationship between the locations and PTE concentrations, highlighting mines as sources. Moreover, uranium radioisotopes were highly correlated with mine-derived PTEs, which will help improve our understanding of PTE behavior. Therefore, uranium radioisotopes can be used as tracers to assess the origin of PTEs from mining activities.

Across the United States (U.S.), many communities experience disproportionate exposure to environmental health hazards due to their proximity to coal-fired power plants and associated coal ash disposal sites. These facilities release toxic heavy metals such as arsenic, mercury, and lead into the surrounding environment, posing serious public health risks. Although prior research has documented adverse health effects of coal-fired power plants, few studies have specifically examined the relationship between cancer incidence and proximity to coal ash impoundments, as well as exposure to elevated concentrations of toxic constituents in coal ash. Using complementary contingency table analyses, bivariate spatial association techniques, and spatial regression methods, this study finds consistent evidence that counties containing or adjacent to coal ash impoundments exhibit significantly higher cancer incidence rates compared to more distant counties, even after adjusting for potential confounders. Incidence rates for both total cancer and lung cancer were significantly associated with smoking, drinking, and physical inactivity, corroborating prior research on these behavioral risk factors. The lung cancer model further revealed significant positive associations between cancer incidence and PM₂.₅, arsenic concentrations, and airborne cancer risk scores, highlighting specific environmental risk factors for the disease. These findings strengthen the evidence linking coal ash exposure to adverse health outcomes and underscore the urgent need for robust enforcement and compliance measures to protect communities from coal ash contamination.

In arid Rajasthan, groundwater is the primary water source for domestic and agricultural needs across the state's hydrogeological spectrum. However, pervasive chemical has been reported locally, and long-term statewide groundwater quality trends remain poorly characterized. This study presents a comprehensive 21-year spatiotemporal analysis of groundwater quality across Rajasthan, India, focusing on irrigation compatibility, human health risk, and regional hydrochemical evolution. Mann-Kendall, Modified Mann-Kendall and Sen's slope tests were used to identify temporal trends in 12 key parameters (EC, major ions, nitrate, fluoride). Irrigation suitability was assessed using standard indices (SAR, RSC, Na%, KR, MH, PI, PS), and non-carcinogenic health risks were quantified via hazard indices for nitrate and fluoride ingestion. Hierarchical cluster analysis was applied to delineate evolving hydrochemical zones. Temporal analysis reveals statistically significant deterioration in salinity, sodicity, nitrate, and sulfate concentrations, particularly in the arid northwest and agriculturally intensive east. Key irrigation indices such as RSC (~ 269 mg/L), SAR (~ 43.8), and KR (> 2.5) consistently exceeded permissible limits, rendering most groundwater marginal to unsuitable for crop use. Concurrently, hazard index values for nitrate and fluoride ingestion averaged 2.35 (adults) and 2.99 (children), indicating chronic health risks in over various districts. Hierarchical cluster analysis delineated distinct hydrochemical zones, salinity-dominated west, nitrate-enriched agricultural belts, and fluoride-affected hard-rock terrains with increasing divergence over time. The emergence of complex contamination profiles underscores an accelerating groundwater quality crisis, demanding region-specific interventions. This integrated, multi-dimensional assessment provides critical insights for sustainable water management and policy planning in semi-arid and arid landscapes undergoing hydrochemical stress.

Per- and polyfluoroalkyl substances (PFAS) have aroused increasing concern in diverse environmental media owing to their ubiquitous occurrence. Understanding the relationships between various PFAS and relevant geographical areas necessitates an analysis of their spatiotemporal distribution and potential risk across different water systems. This study systematically analyzed the monitoring data of twelve PFAS in wastewater, surface water, and groundwater over the past two decades. The results indicated that wastewater treatment plants were a critical node for PFAS entering the environment, and their effluents led to similar PFAS distributions in surface and groundwater. Among the three water environments, perfluorobutyric acid, perfluorobutane sulfonate, and perfluorooctanoic acid (PFOA) exhibited consistently higher average concentrations. Of these, PFBA displayed the highest cross-media mean concentration, reaching 4666.92 ng/L. Linear mixed effects models revealed that concentrations of most PFAS have exhibited an increasing trend over time in wastewater, surface water, and groundwater. However, perfluoroundecanoic acid and perfluorododecanoic acid in wastewater treatment plant influent, and PFOS in surface water, trended downward. PFAS concentrations exhibited spatial heterogeneity, with higher levels in coastal areas, particularly in Jiangsu and Shandong Provinces. PFAS profiles varied by city, dominated by PFOA and short-chain PFAS, and related to fluorine chemical plant distribution. PFOS and PFOA had the lowest predicted no-effect concentrations (1330 and 3730 ng/L), indicating "medium" to "high" ecological risks in cities like Fuxin and Zibo. Under high drinking water exposure, these two compounds may pose adverse effects on human health. This study provided a basis for the control and management of regional PFAS pollution. It was suggested to develop a cross-media, multi-level monitoring and assessment system targeting key PFAS compounds.

Procambarus clarkii represents an invasive species of crayfish common in the rivers of the Iberian Peninsula, which replaced a previous invasive species of crayfish (Austropotamobius pallipes) and is now being replaced by a new invasive species (Pacifastacus leniusculus) in northern rivers. Leaving aside the ecological problems that these invasive species can cause, these organisms can be excellent candidates to act as environmental indicators in pollution processes that involves the interface water-sediment. In this work, the potential role of Procambarus clarkii as a bioindicator of pollution processes of mining origin is evaluated. Unlike previous research, which often focuses on snapshot assessments of contamination levels, our approach integrates historical data and continuous monitoring to provide a dynamic perspective on the impact of Hg and other metals on biotic and abiotic media over an extended period. A total of 330 crayfish were collected from 10 sites in Valdeazogues river, grouped by size, and analyzed for Hg, Pb, Cd, Cu, Zn, As, and Sb in abdominal muscle and hepatopancreas, with a complete characterization of sediment and water media. Crayfish data have shown that hepatopancreas and muscle present the highest average content of Zn (1,325 and 377 mg kg^-1, respectively) and Cu (1,297 and 179 mg kg^-1 respectively). Levels of Hg were higher in muscle (1.6 mg kg^-1) than hepatopancreas (1.0 mg kg^-1), with all muscle samples exceeding the EU maximum permissible level of 0.5 mg kg^-1 for food. The sensitivity of P. clarkii has been sufficient to identify different sources of Hg, Pb and Zn contamination in the drainage system, and even agricultural sources of Cd downstream of the mining district. This versatile capability can be of application to large mining areas in the south of the Iberian Peninsula, especially throughout the Iberian Pyrite Belt.

Chemical fertilizers and agrochemicals contain heavy metal impurities, positioning chemicalized agriculture as the second-largest source of heavy metal contamination after industrial activities. Rubber tree plantations, critical to industrial development, have been widely established in wet tropical countries, including Kerala, South India, for over a century. Despite the regular application of chemical fertilizers and agrochemicals in rubber plantation fields over extended periods, the issue of heavy metal contamination in these plantations remains largely unaddressed. We evaluated, using X-ray fluorescence (XRF) spectroscopy, the presence of chemical fertilizers and other agrochemical-associated heavy metal contaminants, including manganese, iron, chromium, nickel, copper, and zinc, in rubber plantations across various soil types and seasons. The findings revealed elevated heavy metal levels in the order of Fe > Mn > Cr > Zn > Ni > Cu. Most fields exhibited contamination exceeding background levels, with some surpassing WHO limits, indicating severe pollution. Pollution indices indicated moderate contamination that varied by soil type. Monte Carlo simulations have highlighted significant health risks, particularly from carcinogenic metals such as chromium and nickel, which warrant global attention and monitoring of chemicalized perennial tree-crop fields.

The Luanhe River Piedmont Alluvial Fan Complex, a critical industrial-agricultural zone in North China, faces severe groundwater contamination from anthropogenic sources. Hence, forty groundwater samples collected were analyzed by employing multivariate statistics, Piper trilinear diagram, Gibbs diagrams, and ion ratios. Additionally, principal component analysis (PCA) was used to identify the principal factors influencing groundwater, and health risk assessment (HRA) was conducted for nitrate (NO₃^-) and fluoride (F^-). The results revealed that the groundwater is generally weakly alkaline (mean pH = 7.52) and primarily classified as the HCO₃-Ca·Mg type (72% of samples). Among major ions, Ca²⁺ was the dominant cation (all samples), and HCO₃^- the dominant anion (75% of samples). Naturally, the hydrochemistry of groundwater is predominantly controlled by water-rock interaction, including carbonate dissolution and cation exchange. Anthropogenically, industrial and mining activities are the primary factors controlling this hydrochemistry, with agricultural activities being a key contributor to NO₃^-. Critically, the PCA extracted two principal components representing pollution (70.2% variance explained) and salinization (19.8% variance explained) factors. The HRA results demonstrated that NO₃^- poses a significant non-carcinogenic risk to local residents. In particular, infants were the most vulnerable group, with 15% of samples showing HQ ≥ 1, compared to 10% in children and 5% in adults. In contrast, the health risk from F^- was within acceptable limits (HQ < 1). Overall, these findings provide a critical scientific basis for the sustainable management and protection of groundwater resources in the similar Piedmont Alluvial Fan Complex.

Environmental exposure to toxic and essential metals can disrupt host immune function through mechanisms involving epigenetic, transcriptional, and post-transcriptional regulation. Although numerous studies have investigated these regulatory layers separately, integrative analyses across molecular levels in relation to metallome is missing. In this study, we performed a targeted multi-omics analysis of six immune-associated genes (NFKB1, CDKN2A, IGF2, H19, ESR1, and APOA5) and corresponding proteins in healthy residents from a long-term mining region (MRR, n = 46) and a non-mining region (NMR, n = 48). Transcriptome data were generated by mRNA sequencing, while DNA methylation data were obtained using targeted bisulfite sequencing by analyzing previously identified differentially methylated positions. Plasma protein levels were measured by enzyme-linked immunosorbent assay, and plasma metal concentrations were quantified using inductively coupled plasma mass spectrometry. We observed significantly higher plasma levels of NFKB1 and CDKN2A proteins, along with lower ESR1 transcript levels, in residents of the mining region compared to the non-mining region. NFKB1 protein levels were associated with both promoter methylation and residence in mining region, suggesting a regulatory cascade from DNA methylation to protein expression. IGF2 protein levels were higher in males and showed positive associations with age and the cumulative Z-score of essential metal mixture burden. Our results show that long-term residence in mining regions is associated with changes in NFKB1 at both the DNA methylation and protein levels, which may serve as a sensitive biomarker of metal exposure.