Water, Air, & Soil Pollution最新文献

Monitoring and predicting the environmental quality of watersheds is essential for understanding and managing water pollution. Current prediction models often suffer from limitations, including the need for excessive information, complex architectures, and extensive computational resources. To address these challenges, this paper proposes a water pollution prediction system using artificial neural network trained by the back-propagation algorithm with a 2–6-2 structure. The model was developed using chemical oxygen demand and NH₄⁺ concentration data collected from the catchment areas of Kaihua and Anji counties in Zhejiang Province between November 2020 and October 2021. The average relative errors of the neural network training for chemical oxygen demand and NH₄⁺ were -4.59% and -2.65%, the correlation coefficients were 100% and 98%, and the root-mean-square errors were 7.83% and 0.14%, which confirmed the effectiveness of the back-propagation neural network training. The average relative errors between the predicted and observed values of chemical oxygen demand and NH₄⁺ by the neural network were -4.46% and 2.34%, respectively, with correlation coefficients of 100% and 88%, coefficient of determination of 0.94, and root-mean-square errors of 7.72% and 0.11%, which indicated that the predicted values of the back-propagation neural network on the quality of the water were highly significant correlated with the measured values. This study highlights the potential of artificial neural network models to offer efficient, accurate, and computationally streamlined solutions for water pollution monitoring.

The accelerating pace of global industrialization has intensified the prevalence of heavy metals in various environments, presenting a substantial threat to human health. This comprehensive review synthesizes findings from existing studies on human health risk assessments at heavy metal contaminated sites, mainly spanning 2013–2023. It reveals a concentrated focus on specific heavy metals, predominantly Pb, Cd, Cu, Zn, Cr, Ni, and As, and common exposure pathways, such as soil ingestion, dermal contact, and inhalation. This trend may inadvertently overshadow other significant contaminants and exposure routes, indicating a research bias towards certain metals and pathways. We observe a lack of justification in selecting these metals and pathways in existing research, which raises concerns about potential oversight of other significant contaminants and exposure pathways. This review also sheds light on the varying health risks of different site types, with higher risks observed in e-waste-related areas, mines, landfills, and waste incinerators. By conducting an in-depth analysis of existing literature, this review illuminates the imperative to evolve current risk assessment methods to more accurately mirror the complex and variable nature of environmental contaminants. The findings suggest a need for more diversified and comprehensive approaches in selecting pollutants and exposure pathways in heavy metal risk assessments, aiming to protect vulnerable populations better and inform future research and policy decisions.

Agro-waste biomass of Cajanus cajan leaves were used for the synthesis of bioadsorbent iron activated pigeon pea leave (Fe-ACP) at 500 °C in muffle furnace and used for the abatement of fluoride from water. Characterization of bioadsorbent was done by using pH_PZC, Scanning Electron Microscopy, Energy-dispersive X-ray, X-Ray Diffraction, and Fourier Transform Infrared Spectroscopy. Study was also conducted by varying the adsorbent doses, initial concentrations of fluoride, contact time intervals, pH of solution, temperature of the solution and in presence different competing ions. The result clearly indicated that at optimum adsorbent dose of 3 g/L the maximum removal of fluoride was achieved within 150 min of contact time. The fluoride removal efficiency got increased with increase in temperature from 25 °C to 55 °C. The Langmuir isotherm (R² = 0.997) and pseudo-second-order kinetic model (R² = 0.991) were found to be the best fit model to explain the mechanism of fluoride adsorption on Fe-ACP. The adsorption process was observed to be endothermic and spontaneous in nature as evidenced by thermodynamics studies. Through ANOVA analysis, the significant influence (p < 0.001) of contact time, biochar dose, initial fluoride concentrations, pH, and temperature were observed on the fluoride adsorption process. Presence of similar charge of competing ions (nitrate and phosphate) significantly impacted on the efficiency of Fe-ACP bioadsorbent for fluoride adsorption. Regeneration studies showed that Fe-ACP bio-adsorbent can be utilized up to four cycles. The experimental results proved that the Fe-ACP bio-adsorbent has excellent ability to reduce the level of fluoride from water up to 4 cycles after regeneration.

The current study investigated the distribution and health risk assessment of heavy metals present in the sediment samples Cauvery River. During the monsoon season, the sediment samples were collected at 13 sampling sites along the Cauvery River. The findings of the present study revealed elevated concentrations of metals, including Cr, Zn, Cu, Co, Pb, As, Cd, and Hg. A robust statistical relationship was identified among the sampling locations of all the elements under analysis (P < 0.05). Moreover, investigations into the pollution load index and geo-accumulation index revealed that the distribution of heavy metals during the monsoon flood had moderate to higher effects. However, it can be observed from the average values of PER (720) and PLI (> 1) that the sediments of the Cauvery River possess a considerably high level of toxicity. Based on the results, the sediment samples from the Cauvery River basin exhibited significant levels of Cd and Hg, whereas other metals were comparatively less severe.

The study investigated the adsorption capacity of natural minerals such as limestone sand (LS), silica spongolite (SS), chalcedonite (CH), and dolomite (DO) for the removal of a model contaminant, the azo dye Reactive Red 120 (RR-120). The effects of adsorbent dose and solution pH on adsorption, as well as the adsorption kinetics and equilibrium adsorption, were investigated. The results showed that adsorption was dependent on the mass of the adsorbent and increased with increasing adsorbent dose. Adsorption was also dependent on the pH of the initial solution and was most efficient in an acidic media. Adsorption kinetic research results revealed that the adsorption of RR-120 on all four minerals followed the pseudo-second-order model and was controlled by film diffusion. The dye adsorbed fastest on limestone sand (k₂ = 0.021 g/µmol∙min) and slowest on dolomite (k₂ = 0.015 g/µmol∙min). The observed adsorption rate increases in the order of DO < CH < SS < LS. Under equilibrium conditions, Reactive Red 120 was adsorbed best on dolomite and least on limestone sand (LS < SS < CH < DO). The Langmuir adsorption capacities for RR-120 were found to be 4.7 μmol/g for LS, 5.2 μmol/g for SS, 7.0 μmol/g for CH, and 9.0 μmol/g for DO. The results indicate that selected natural minerals can be employed as alternatives to commercial adsorbents for the removal of Reactive Red 120 from water.

This study assessed spatiotemporal water quality, hydrogeochemical characteristics, and heavy metal contamination level of anthropogenically impacted an ancient artificial freshwater wetland, Bhojtal, India, which is crucial for drinking water supply and aquatic biodiversity. The study revealed significant (p < 0.05) seasonal variations in pH, magnesium, and dissolved oxygen levels exceeding permissible limits. Hydrogeochemical classification indicated Cl^‒-Ca²⁺/Mg²⁺ facies dominance post-monsoon. Entropy-based WQI results showed excellent water quality during the monsoon, which declined to good (67% samples) and medium (33% samples) post-monsoon. The trophic state index (TSI) indicated hyper-eutrophication, with values of 81.81 and 82.61. Heavy metals were within safe limits during the monsoon, but high cadmium and lead concentrations were found post-monsoon in the western (Karballa) and southeastern sides (Hallalpur) of the Bhojtal wetland. The study emphasizes the need for land use management to protect water quality, especially post-monsoon. The study signifies the anthropogenic impact on historically significant artificial freshwater wetlands regarding water quality, hydrogeochemistry, and heavy metal pollution, emphasizing the crucial role of effective land use management to sustain these freshwater wetlands for better human health and livelihood.

Water pollution is a growing concern, particularly hexavalent chromium, a toxic pollutant that poses serious environmental and health risks due to its persistence and bioaccumulation. In this study, zeolite A–X was synthesized using an ultrasonic-alkali fusion hydrothermal method, with coal fly ash serving as the source of silica and aluminum, to treat chromium-containing wastewater. The zeolite A–X was successfully synthesized at an alkali-to-ash ratio of 1.5, a hydrothermal temperature of 90 °C, and a hydrothermal time of 12 h. Batch adsorption experiments showed that zeolite A–X achieved optimal adsorption of Cr (VI) at 13.73 mg g⁻¹ under a pH of 3.

Due to the problems of high difficulty and cost of sludge treatment and disposal, the residual sludge with high water content was treated by lysis to realize the reduction. The sludge lysis was conducted by ultravio-sonication (UVS). The effects of wavelength and power of ultraviolet (UV), and sludge concentration and alkali treatment were investigated. The results found that the power of the UV impacted the sludge lysis degree (DD_COD) more strongly than the wavelength, which could increase the amount of TP, PO₄³⁻-P, TN, NH₄⁺-N, protein and polysaccharides in the supernatant but reduce the percentage of carbon, nitrogen and phosphorus. During the lysis by UV-ultrasound, DD_COD increased slightly as the sludge concentration increased, and alkali treatment was more conducive to the dissolution of substances. Under the conditions of ultrasonic power 400 W and frequency 40 kHz, UV power 16 W and wavelength 185 nm, sludge concentration 12,000 mg·L⁻¹, pH = 11 (alkali treatment), the contents of TP, PO₄³⁻-P, TN, NH₄⁺-N were 297.1 mg·L⁻¹, 183.9 mg·L⁻¹, 522.3 mg·L⁻¹, and 58.9 mg·L⁻¹, respectively, with DD_COD reaching up to 63.02%. The improvement of sludge lysis degree was conducive to the release of substances and the reduction the moisture content, which facilitated the subsequent sludge disposal and resource utilization.

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