Environmental Geochemistry and Health最新文献

This study investigates the photocatalytic degradation of Moxifloxacin (MOX), a fluoroquinolone antibiotic, using a synthesized photocatalyst composed of g-C₃N₄/Ti₃C₂/Sm₂O₃ (GTS). The photocatalyst was prepared by a simple Co-precipitation and characterized using various analytical techniques. The FE-SEM results revealed a cluster-like morphology with average particle sizes from 20 to 40 nm. The Tauc-plot analysis yields a band gap of 2.8 eV, indicating that the material is responsive to visible-light irradiation. AFM analysis determined the catalyst's average surface roughness to be 127.1 nm. The degradation efficiency of GTS was assessed, yielding an impressive 99.50% degradation rate after 300 min under optimal conditions (pH = 6.8, catalyst dosage = 10 mg, and Moxifloxacin concentration = 10 ppm). Notably, GTS exhibited enhanced photocatalytic activity under visible light. These findings suggest that the GTS photocatalyst is highly effective in degrading MOX antibiotics under visible light, highlighting its potential for practical applications in eliminating fluoroquinolone antibiotics.

Arsenic accumulation is becoming a major pollutant fueled by natural and anthropogenic activities. Arsenic contamination degrades the soil fertility and make it unsuitable for plants growth. Various physical and chemical solutions can be used to decontaminate the soil but these solutions have many limitations. Rhizoremediation along biochar, a potential strategy to treat the arsenic contaminated soil and biochar also improves the soil nutrient content. Therefore, this research focused on mitigating arsenic toxicity via the arsenic-tolerant Acinetobacter in combination with biochar. Arsenic tolerant bacteria was isolated from arsenic contaminated soil and identified as Acinetobacter. Biochar was prepared from the wood shaving of Cedrus deodara. A pot experiment was designed to check the rhizoremediation potential of biochar and Acinetobacter in the rhizosphere of Spinach. It is the first study to evaluate the potential of Acinetobacter and the biochar on the nutritional and arsenic accumulation in spinach. The collection of soil samples for the isolation of bacterial strains was done from the arsenic-affected site and the preparation of biochar was done using the wood shaving of Cedrus deodara. A pot experiment was conducted to figure out the potential of isolated bacterial strains and biochar individually as well as synergistically. The co-application of Acinetobacter and biochar improved spinach's morphological (shoot length 22%, root length 24%), physiological (chlorophyll 22%) and biochemical (proline 24%, soluble sugar 30%) attributes in arsenic contaminated soil. Both biochar and Acinetobacter also increase enzymatic and non-enzymatic content in plant. Arsenic content of soil decreased by 43% in root and 47% in shoot with co-application of biochar and Acinetobacter. Rhizoremediation potential of Acinetobacter and biochar in the plant rhizosphere to reduce the arsenic content considered to be a promising strategy for heavy metal remediation in soil.

Excess uranium (U) in the shallow aquifers of Punjab, India, has become a significant public health concern for the population dependent on groundwater for drinking and irrigation purposes. Although prior investigations have statistically established the control of geogenic and anthropogenic factors on U enrichment, a comprehensive and high-resolution spatial distribution of the extent of contamination remains lacking. To address this gap, we employed the Random Forest (RF) machine-learning classifier to model 1,852 data points of groundwater U concentrations compiled from different districts of Punjab. Spatial prediction and mapping were performed using spatially continuous predictor variables pertaining to meteorological, topographical, geological, soil, and other relevant parameters. A highly accurate prediction map of the occurrence probability of U surpassing the WHO drinking water limit of 30 µg L^-1 at a 250 m spatial resolution, with an accuracy of 85% for test data and 87% for validation data, was generated. The predicted U hazard was strongly influenced by potential evapotranspiration, elevation, and aquifer thickness, with a moderate to low influence from soil physical and chemical properties. Based on the predicted hazard map, the probability of U contamination was higher in the south and southwestern districts (Malwa region) than in other regions of Punjab, comprising approximately 1.7 million hectares (~ 35%) of the state's total area. This study represents the first attempt to spatially predict the occurrence of high groundwater U levels, providing valuable insights for government agencies and policymakers to make informed decisions and manage groundwater sustainably.

This study provides a wide radiological investigation of surface soils in the North and South Industrial Zones of Erbil City, Iraq by measuring radon (²²²Rn) and gamma dose rates. For this purpose, 50 soil samples were studied by employing CR-39 detectors for radon concentration and portable Geiger-Muller survey meter for gamma dose rates. The mean values of measured radon concentrations were 129.83 ± 51.18 Bq/m³ in the North Zone and 95.10 ± 34.01 Bq m^-3 in the South Zone; approximately half (50%) and nearly one-third (35%) of sites exceeded the WHO reference level of 100 Bq m^-3, respectively. Mean radiological hazard indices like PAEC, AED, ELCR and doses to organs were also higher in North Zone. Absorbed dose rates of gamma radiation varied from 0.09 to 0.22 μSv h^-1 and were related to the amount of radon, suggesting contribution from geological and also industrial sources. Monte Carlo simulations (50 000 iterations) showed a high probability (70.97-82.51%) of exceeding the ICRP public dose criterion for members of the public, namely, 1 mSv y^-1 in North Zone, whereas there was a lower but significant probability (26.22-30.48%) for South Zone. The high risk areas or hot spots were identified by the spatial analysis integrating kriging interpolation. Findings reflect the importance of surveillance and radiation protection in industrial areas to minimize potential public health hazards.

Organophosphate flame retardants (OPFRs) and phthalate esters (PAEs) are widely used flame retardants and plasticisers; however, baseline data on their occurrence in India remain limited. This study investigated 15 OPFRs and 6 PAEs in playground soils along an urban-rural gradient in Nagpur, central India, to assess occurrence, spatial distribution, and potential sources. Total concentrations of twelve OPFRs (Σ₁₂OPFRs) ranged from 40.9 to 2,740 ng/g (mean: 339 ± 435 ng/g), while six PAEs (Σ₆PAEs) varied from 35.0 to 2,550 ng/g (mean: 320 ± 394 ng/g). Σ₁₂OPFR concentrations were significantly higher in rural transects than in urban areas (p < 0.05). OPFR profiles were dominated by alkyl OPFRs (57%), followed by aryl (32%) and chlorinated OPFRs (11%), with tris-n-butyl phosphate (TnBP) as the most abundant compound (31%) and significantly enriched in rural soils (p < 0.05). PAEs were dominated by di-(2-ethylhexyl) phthalate (DEHP; 76%), followed by di-n-butyl phthalate (DnBP; 15%). Principal component analysis resolved five components, identifying polymeric and consumer product sources (TDCIPP, TICIPP, TPhP, TIPrP), industrial and petrochemical inputs (TpCP), plasticizer- and agriculture-related sources (DEHP, TnBP), and diffuse atmospheric, polymeric, and traffic-related contributions (DEP, TEP, DMP, TMP). Human health risk assessment indicated a negligible risk, with maximum hazard index values of 3.49 × 10^-3 for children and 8.91 × 10^-4 for adults, and incremental lifetime cancer risk values ranging from 3.33 × 10^-9 to 4.79 × 10^-8, all of which fall within the United States Environmental Protection Agency's acceptable limits. Elevated OPFRs levels in rural areas highlight concerns related to long-range atmospheric transport and diffuse pollution hotspots locally.

Urban agriculture is growing in popularity, but toxic metals and metalloids in garden soil raise concerns about human health risks associated with gardening. Gardeners might be exposed to toxic elements because they directly handle the garden soil and grow edible produce in it. This study examined community gardens in the City of St. Louis, Missouri, US and surrounding municipalities, areas with a history of soil contamination by metals, particularly Pb. To improve the current understanding of soil contamination patterns in garden soil and implications for exposure to metals/metalloids, the study (1) measured total metal/metalloid concentrations (Pb, As, Cd, Cu, Co, Ni, Mo, Ca, Mg, Fe, and Zn) in soil from twenty gardens, (2) tested in-vitro Pb bioaccessibility in soil samples, and (3) administered surveys to gardeners. Overall, our measurements suggest that Pb is a metal of concern in St. Louis community gardens. While soil in 21% of sampled plots contained Pb concentrations above recommended thresholds for gardens, Pb bioaccessibility was low (< 5.4% of the total soil concentration), suggesting that the Pb bioavailability in the case of accidental ingestion of soil particles was limited. Total metal/metalloid concentrations in soil varied spatially across plots within gardens, highlighting the importance of sampling multiple plots. Pb and As concentrations were positively correlated with garden age. Survey results revealed the common gardening habits, the type of produce grown in urban gardens, and exposure parameters. These findings contribute to improving the design of soil sampling, providing insights for exposure assessment, and informing contamination mitigation measures.

Pollution from potentially toxic elements (PTEs) in farmland soil poses significant risks to food safety and human health. Accurately identifying and assessing the health risks of PTEs in farmland soil is crucial. In this study, we apply the pollution index to evaluate soil pollution levels, employ positive matrix factorization- principal component analysis to identify pollution sources, and quantify health risks through four exposure pathways associated with walnut kernel consumption. The results revealed that mercury (Hg) and cadmium exhibited the highest soil enrichment factor and very high contamination (pollution index > 6). Agricultural activities (6.6%), industrial production (6.2%), coal combustion (12.7%), and natural sources (74.5%) were identified as the major sources of these pollutants. Notably, the hazard index for adults (1.05) exceeded the recommended value, while the total cancer risk (TCR) index for children (2.84E-03) was lower than that for adults (2.04E-03), indicating that there are non-carcinogenic health risks, and the cumulative carcinogenic risk value of residents is not within the acceptable range. It is worth highlighting that Hg emerged as a priority pollutant originating from agricultural activities, with a higher bioconcentration factor observed in walnut kernels (0.511). Additionally, coal combustion contributed 31.3-35.3% to the total cancer risk, emerging as the second-largest contributor after natural sources. Furthermore, a significant correlation was observed between diagenetic elements and the enrichment of PTEs, emphasizing the importance of characterizing the content and composition of diagenetic elements in specific polluted areas to enhance our understanding of PTE sources. This study highlights the accumulation of PTEs in Baiyin City's environment, which presents significant challenges to long-term sustainability, particularly in regions severely affected by environmental degradation. Therefore, urgent measures are required to mitigate PTEs pollution and safeguard both farmland and public health.

Heavy metal (HMs) contamination of soil and its adverse impacts are a global concern. However, limited studies have investigated the spatial and seasonal variability of soil HMs in the Tasik Chini area. This study aimed to assess the distribution, source, and contamination of ten particular heavy metalic elements (Cr, Cu, Co, Ni, Cd, Ba, Pb, Mn, As, and Zn) in the surface soil of the Chini Lake. A total of 60 soil samples were collected from 10 sites during wet and dry seasons, and analyzed using Inductively Coupled Plasma Mass Spectrometry (ICP-MS). The degree of pollution was assessed using the CF and PLI, while PCA, CA, and correlation analysis provided insights into the prevalence and sources of HMs. Based on the findings, a notable mean concentration of HMs was measured in Ni (6.78 ± 8.37 ppb), Mn (11.51 ± 21.08 ppb), and Pb (3.23 ± 2.68 ppb), compared to background values of 16 μg/g, 460 μg/g, and 31 μg/g, respectively. Pollution indices revealed moderate contamination levels for Cd, Co, and Pb, especially in mining and agricultural areas. PCA indicates a variance of 50.27% with a strong relationship between As, Cu, Cd, Mn, Zn, Ba, and Pb, suggesting a common originating source of mining and agriculture activities. CA analysis highlights the higher contamination level in the mining area and downstream in the agricultural area among the sampling station groups. According to the results, human-made sources, including mining waste and agricultural chemicals, are the primary contributors of Cd, Pb, Cu, Zn, and As, whereas Ni, Cr, and Mn were mostly derived from natural geogenic backgrounds. This study concludes that seasonal inputs from mining and agriculture have a substantial impact on soil HMs contamination. Further studies are needed on ecological and socio-economic implications, including long-term monitoring, to support effective mitigation and management.

Population density, urbanization and industrialization are the rapidly increasing and it's causes severe damages to freshwater ecosystem. The present study aims to assess the quality of groundwater using integrated methods in the industrial zone of South India. The integrated assessment of groundwater using unsupervised machine learning method associated human health risk assessment are identified as research gap in the study region. We collected 55 samples based on groundwater availability, population density, and industrial activity in summer and winter seasons. The study found that calcium-chloride and mixed calcium-magnesium-chloride types of water are the dominating category in both seasons. The groundwater pollution index (GPI) and piper trilinear and gibbs diagram indicate that evaporation, water-rock interface, and other anthropogenic activities are the dominating factors in groundwater chemistry. Analysis using the entropy water quality index (EWQI) and human health risk estimation confirmed that nitrate is the key parameter affecting groundwater sustainability. Unsupervised machine learning techniques were applied to evaluate groundwater chemistry. The principal component analysis (PCA) results revealed that seasonal variation is influenced by mineral dissolution, rainwater recharge, and anthropogenic activities. The hierarchical cluster analysis (HCA) results shows that a tight cluster forms among pH, Na, K, NO3, and F, suggesting that processes such as agricultural inputs from fertilizer use, synthetic pesticides, and natural geochemical interactions control ion exchange. The k-means clustering yielded three clusters: low-salinity fresh water, moderately mineralized water undergoing geochemical alteration, and high-hardness water indicative of specific geogenic and anthropogenic influences in both seasons. Overall, the integrated assessment of groundwater revealed that the water-rock interface, evaporation, and synthetic fertilizer use in agricultural fields are significant factors controlling groundwater quality. The key findings of this study provides clear knowledge about the nature of groundwater, influencing factors and help to improve the water resources management strategies in investigation zone.

Groundwater is a critical water resource in arid and semi-arid coal-mining regions, where mining-induced disturbances can modify aquifer conditions and degrade water quality. In this paper, hydrochemical analysis, Self-Organizing Maps (SOM), correlation analysis, and the Objective Combined Weight Water Quality Index (OCWQI) were integrated to characterize groundwater hydrochemical features, assess groundwater quality in the Dahaize coal mine area, and identify the key factors controlling water quality. Based on the Piper trilinear diagram, two dominant hydrochemical facies were identified: Ca-HCO₃ and Na-Cl. Major-ion chemistry is mainly controlled by water-rock interaction, evaporation crystallization, cation exchange, and anthropogenic inputs. Groundwater quality in the Zhiluo Group is generally poorer than that in the other aquifers. SOM and correlation analyses suggest that Na⁺, SO₄^2- and F^- are among the key parameters influencing groundwater quality and support the rationality of the OCWQI weighting. Anthropogenic activities influence groundwater hydrochemistry: elevated SO₄^2- in deeper groundwater shows a correlation with mining-affected zones, whereas NO₃^- and NH₄⁺ in shallow groundwater show patterns consistent with inputs from agricultural fertilization and domestic wastewater. This study proposes a method for evaluating the rationality of indicator weights in water quality assessment, providing a reference for groundwater quality management in coal mining areas and offering insights into water quality evolution and pollution risks in arid regions.