Search Results (89)

The effectiveness of manmade wetlands with four different macrophyte species (Arundo donax, Typha latifolia, Pistia stratiotes, and Eichhornia crassipes) in treating wastewater from the paper recycling industry, located in the Hattar Industrial Estate in Haripur, is reported. The findings show that each plant species has distinct pollutant removal capacities, which contribute to the overall treatment effectiveness of the system. Notably, Arundo donax performed exceptionally well in lowering chemical oxygen demand (COD) from 1013 mg/L to 119.66 mg/L and nitrate levels from 79.66 mg/L to 10.66 mg/L. In contrast, T. latifolia was successful in reducing biochemical oxygen demand (BOD) from 436 mg/L to 55 mg/L and total solids from 837.66 mg/L to 242.66 mg/L. The P. stratiotes species have high phosphate removal capacity, lowering values from 134.66 mg/L to 25.66 mg/L. RSM revealed that time, Arundo donax, and wetlands significantly enhance pollutant removal, while specific plant–treatment combinations yield variable efficiencies, highlighting synergistic effects crucial for optimal performance. Furthermore, all plant species have shown competency in removing heavy metals from effluent. This study’s findings highlight the potential of artificial wetlands as a natural and eco-friendly alternative for treating complex industrial wastewater, promoting the development of sustainable wastewater treatment methods in industrial settings. Full article

The comprehensive utilization of hazardous waste may introduce heavy metals, organic pollutants, etc., into products, resulting in secondary pollution. The environmental risk assessment method for hazardous waste resource utilization products is an important technical means of environmental management. We have established a standardized method for hazard identification, exposure evaluation and risk characterization. This study selects waste sulfuric acid generated in the integrated circuit industry as the object and investigates the use of waste sulfuric acid to react with aluminum hydroxide to produce liquid aluminum sulfate flocculant, as well as the environmental risks brought to practitioners and the potential relevant population in the sewage treatment process. By analyzing sulfuric acid and aluminum hydroxide, toxic substances such as nitrate ions, fluorides, As, Pb, Cr, Hg, Cd, etc., were identified. Through exposure scenario analysis, the exposure levels of occupational and non-occupational populations were determined. Based on the dose–response relationship data in the IRIS database of the United States and the carcinogenic and non-carcinogenic data of skin contact routes, it was suggested that chromium and its compounds were the main contributors to carcinogenic risk, and cadmium, its compounds, and mercuric chloride were the contributors to the non-carcinogenic risk. The total carcinogenic risk to human health in occupational populations was 5.31 × 10⁻⁵, and the total non-carcinogenic risk was 8.80 × 10⁻¹. The total carcinogenic risk to human health in non-occupational populations was 1.73 × 10⁻¹⁵, and the total non-carcinogenic risk was 1.23 × 10⁻¹¹. Based on this research, it is clear that the production of liquid aluminum sulfate flocculants from waste sulfuric acid generated in the integrated circuit industry has a low impact on occupational and other populations during use, and the environmental risks generated by this product are acceptable even under the most dangerous conditions. Full article

The Yamuna River, among India’s most polluted waterways, is burdened by industrial, agricultural, and domestic discharges containing complex organic and inorganic contaminants. This study introduces a novel, integrated approach combining comprehensive pollutant profiling by liquid chromatography–mass spectrometry (LC-MS) with bioremediation using laboratory-validated native algal consortia. Water samples from a severely polluted Delhi stretch revealed alarming levels of heavy metals (e.g., lead: 47.33 mg/L) and over 550 organic pollutants, including polychlorinated biphenyls, dioxins, carcinogens, and neurotoxins. Two consortia, each assembled from indigenous algal strains, were evaluated under controlled conditions against both pollutant-rich water and non-polluted controls. Consortium 1 (Scenedesmus, Chlorococcum, Oocystis) outperformed Consortium 2 (Chlorella, Klebsormidium, Monoraphidium), achieving up to 87.07% reduction in lead and >95% removal of nitrate and phosphate, alongside substantial decreases in chemical and biological oxygen demand. By integrating high-resolution chemical analytics with native microbial remediation, this work provides the first demonstration of simultaneous removal of diverse pollutant classes in Yamuna water. The findings establish native algal consortia as cost-effective, sustainable bioremediation tools and underscore LC-MS as a critical method for holistic aquatic pollution assessment. Full article

Groundwater represents a critical global resource, increasingly threatened by overexploitation and pollution from contaminants such as arsenic (As), fluoride (F), nitrates (NO₃⁻), and heavy metals in arid to semi-arid regions like Mexico. Traditional Water Quality Indices ($WQIs$), while useful, suffer from subjectivity in assigning weights, which can lead to misinterpretations. This study addresses these limitations by developing a novel, objective Groundwater Quality Index ($GWQI$) through the seamless integration of Machine Learning (ML) models. Utilizing a database of 775 wells from the Mexican National Water Commission (CONAGUA), Principal Component Analysis (PCA) was applied to achieve significant dimensionality reduction. We successfully reduced the required monitoring parameters from 13 to only three key indicators: total dissolved solids (TDSs), chromium (Cr), and manganese (Mn). This reduction allows for an 87% decrease in the number of indicators, maximizing efficiency and generating potential savings in monitoring resources without compromising water quality prediction accuracy. Six $WQI$ methods and six ML models were evaluated for quality prediction. The Unified Water Quality Index (${WQI}_u$) demonstrated the best performance among the $WQIs$ evaluated and exhibited the highest correlation (R² = 0.85) with the traditional $WQI$ based on WHO criteria. Furthermore, the ML Support Vector Machine with polynomial kernel (svmPoly) model achieved the maximum predictive accuracy for ${WQI}_u$ (R² = 0.822). This robust $GWQI$-ML approach establishes an accurate, objective, and efficient tool for large-scale groundwater quality monitoring across Mexico, facilitating informed decision-making for sustainable water management and enhanced public health protection. Full article

As a typical heavy metal pollutant, cadmium (Cd) poses significant threats to ecosystems and human health. Giant duckweed (Spirodela polyrhiza), a small aquatic plant characterized by rapid growth and efficient heavy metal accumulation, holds great promise for phytoremediation. However, the mechanisms by which S. polyrhiza enriches Cd—particularly the contributions of its surface-associated microbiota—remain poorly understood. In this study, S. polyrhiza fronds were exposed to 0, 1, and 10 μM Cd, and we observed a concentration-dependent increase in the abundance of epiphytic microorganisms on the frond surfaces. High-throughput 16S rRNA gene sequencing revealed that Cd stress significantly altered the diversity of the frond-epiphytic bacterial community. Notably, the relative abundances of the genera Herbaspirillum, Enterobacter, and Pantoea increased significantly with rising Cd concentrations. Functional prediction using PICRUSt2 indicated enrichment under Cd stress of specific traits—such as the nitrate/nitrite transporter NarK, signal transduction mechanisms, and ion channel proteins—suggesting these taxa may actively participate in Cd uptake and tolerance. Together, our results reveal a synergistic S. polyrhiza–microbiome response to Cd and identify taxa/functions as targets and biomarkers for microbe-augmented remediation. Full article

Riverbank height plays a potentially important role in hydrological dynamics and pollutant transport, yet its influence on long-term water quality trends remains insufficiently documented. This study explores possible relationships between riverbank height variations and the Global Pollution Index ($I_{GP}^{*}$) in the Timiș River, Romania, over eleven (11) years (2013–2023). A dataset of 17 physicochemical parameters—including BOD₅, COD-Cr, dissolved oxygen, nutrients (N and P species), heavy metals (As, Cr, Cu, and Zn), detergents, and phenols—was used to tentatively assess ecological status. The results suggest that, despite a maximum riverbank elevation change of ~11 cm between 2020 and 2025, $I_{GP}^{*}$ values remained within a relatively narrow range (1.98–2.56, mean 2.19), pointing to persistent but moderate anthropogenic pressure. The highest index value (2.56, in 2016) coincided with a transient pollution event, whereas subsequent years stabilized around 2.0–2.3, which may reflect chronic diffuse pollution. Correlation analysis revealed strong associations between BOD₅ and conductivity (r = 0.76, linked to organic loads), COD-Cr and heavy metals (r = 0.79, suggestive of industrial influence), and total nitrogen and nitrate (r = 0.97, related to agricultural inputs), appear to outline distinct source-related signatures. This study offers preliminary evidence that even modest riverbank fluctuations may influence hydrodynamics and the fate of pollutants, while basin-scale water quality seems to remain largely governed by diffuse pollution sources. By integrating long-term geomorphological monitoring with multi-parameter water quality data into a composite index ($I_{GP}^{*}$), our work sketches a potentially innovative framework for diagnosing pollution drivers. The findings underscore the importance of incorporating riverbank morphology into EU Water Framework Directive monitoring, alongside GIS, IoT, and machine learning tools, could contribute to more adaptive river basin management. Full article

This study uses industrial wastewater from an aluminum factory to evaluate the phycoremediation efficiency of two green microalgal strains, Dictyosphaerium sp. and Tetradesmus obliquus. The industrial wastewater contained high levels of pollutants, including COD, ammonium, nitrate, phosphate, and heavy metal ions (Al³⁺, Cu²⁺, Cr³⁺, Zn²⁺, Mn²⁺, Cd²⁺). Four biomass conditions were tested: free-living cells (active living cells), immobilized cells (entrapped within alginate), dried biomass (non-living dried cells), and acid-treated dried biomass (chemically modified for enhanced adsorption). Both strains demonstrated significant pollutant removal, with living biomass (free and immobilized) achieving the highest nutrient and organic pollutant removal, and non-living biomass (dried and acid-treated) being more efficient for rapid heavy metal removal. Tetradesmus obliquus showed superior performance across most parameters, while Dictyosphaerium sp. exhibited the highest aluminum removal (99.4%, reducing Al from 481.2 mg/L to 10.2 mg/L). These findings highlight the potential of microalgae-based approaches and support species-specific strategies for cost-effective and sustainable phycoremediation of industrial wastewater. Full article

Rare earth element (REE) mining exerts profound impacts on aquatic ecosystems, yet the microbial community responses and water quality under such stress remain underexplored. In this study, the surface (0.2 m) and subsurface (1.0 m) water along a spatial transect from proximal to distal points was investigated in a REE-mining area of Ganzhou, China. Physicochemical analyses revealed pronounced gradients of nitrogen (e.g., NH₄⁺−N, NO₃⁻−N), heavy metals (e.g., Mn, Zn, Pb), and REEs (e.g., La, Nd, Ce), with higher accumulation near mining sources and partial attenuation downstream. Dissolved oxygen and redox potential indicated mildly reducing conditions at contaminated points, potentially promoting denitrification and altering nitrogen cycling. Metagenomic sequencing showed significant shifts in microbial community composition, with enrichment of metal- and nitrogen-tolerant taxa, and key denitrifiers (e.g., Acidovorax, Bradyrhizobium, Rhodanobacter), particularly at upstream polluted points. KEGG-based gene annotation highlighted dynamic nitrogen transformations mediated by multiple pathways, including nitrification, denitrification, dissimilatory nitrate reduction to ammonium, and nitrogen fixation. Notably, genes associated with nitrite and nitrate reduction (e.g., nir, nar, nrf) were enriched near mining sources, indicating enhanced nitrogen conversion potential, while downstream activation of nitrogen-fixing genes suggested partial ecosystem recovery. Meanwhile, some microbial such as Variovorax carried metal tolerant genes (e.g., ars, chr, cnr). These findings demonstrate that REE and heavy metal contamination restructure microbial networks, modulate nitrogen cycling, and create localized ecological stress gradients. This study provides a comprehensive assessment of mining-related water pollution, microbial responses, and ecological risks, offering valuable insights for monitoring, restoration, and sustainable management of REE-impacted aquatic environments. Full article

Heavy metals, nitrogen, and phosphorus play a significant role in the marine ecosystem and human health. In this work, the concentrations of heavy metals, inorganic nitrogen, and phosphorus were determined to assess the distribution characteristics, risk levels, and possible sources in seawater from Taizhou Bay. The concentration ranges of Cu, Pb, Zn, Cd, Hg, As, ammonia, nitrate, nitrite, and phosphate were 1.87–3.65 μg/L, 0.10–0.95 μg/L, 2.98–16.80 μg/L, 0.07–0.38 μg/L, 0.011–0.043 μg/L, 0.93–2.06 μg/L, 0.011–0.608 mg-N/L, 0.012–0.722 mg-N/L, 0.001–0.022 mg-N/L, and 0.004–0.044 mg-P/L, respectively. The ecological risks were evaluated by the single factor index, Nemerow pollution index, and risk quotient. The results indicated that Taizhou Bay is not currently facing ecological risk related to heavy metals, nitrogen, and phosphorus, but the RQ values emphasized the urgency of strengthening continuous monitoring of As, Cu, and Zn. The results of Pearson’s correlation indicated that salinity and chemical oxygen demand had a significant impact on nitrogen and phosphorus but little impact on heavy metals. Principal component analysis was then applied to analyze the probable origins of heavy metals and inorganic pollutants, suggesting that these pollutants were mainly derived from human activities along the bay. Full article

This review provides a critical and technically grounded assessment of continuous electrocoagulation processes (CEPs) for the treatment of industrial inorganic pollutants, emphasizing recent innovations, methodological developments, and practical outcomes. A comprehensive literature survey indicates that 53 studies published over the past 25 years have investigated CEPs for inorganic contaminant removal, with 36 focusing on standalone electrocoagulation systems and 17 exploring integrated CEPs approaches. Recent advancements in reactor design, such as enhanced internal mixing, optimized electrode geometry, and modular configurations, have significantly improved treatment efficiency, scalability, and operational stability. Evidence indicates that CEPs can achieve high removal efficiencies for a wide range of inorganic contaminants, including fluoride, arsenic, heavy metals (e.g., chromium, lead, nickel, iron), nitrates, and phosphates, particularly under optimized operating conditions. Compared to conventional treatment methods, CEPs offer several advantages, such as simplified operation, reduced chemical consumption, lower sludge generation, and compatibility with renewable energy sources and complementary processes like membrane filtration, flotation, and advanced oxidation. Despite these promising outcomes, industrial-scale implementation remains constrained by non-standardized reactor designs, variable operational parameters, electrode passivation, high energy requirements, and limited long-term field data. Furthermore, few studies have addressed the modeling and optimization of integrated CEPs systems, highlighting critical research gaps for process enhancement and reliable scale-up. In conclusion, CEPs emerge as a novel, adaptable, and potentially sustainable approach to industrial inorganic wastewater treatment. Its future deployment will rely on continued technological refinement, standardization, validation under real-world conditions, and alignment with regulatory and economic frameworks. Full article

The Sanqi–pine agroforestry (SPA) system is considered a sustainable agroforestry model. However, empirical studies that clearly elucidate the impact of Sanqi cultivation on soil fertility and the heavy metal content within the SPA system are still lacking. This study established monoculture Pinus armandii (MPA) and SPA systems to conduct a comparative analysis of dynamic changes in soil physicochemical properties and the heavy metal content of Sanqi and pine over one year (with semi-monthly sampling), followed by a comprehensive evaluation of soil fertility and heavy metal pollution. Following the land use conversion from MPA to SPA, there was a notable increase in soil moisture (SM), total nitrogen (TN), and nitrate nitrogen (NO₃⁻-N) levels within Sanqi soil. Conversely, total potassium (TK), ammonium nitrogen (NH₄⁺-N), plumbum (Pb), and chromium (Cr) levels experienced a significant reduction. In the case of pine soil, soil moisture (SM), pH levels, and ammonium nitrogen (NH₄⁺-N) content exhibited an increase. However, soil organic carbon (SOC), total phosphorus (TP), total potassium (TK), zinc (Zn), manganese (Mn), plumbum (Pb), and chromium (Cr) contents all significantly decreased. The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) demonstrated that Sanqi cultivation not only significantly enhanced soil fertility for Sanqi rather than pine but also reduced the heavy metal content in the soil of both Sanqi and pine within the SPA system. Furthermore, the Nemerow pollution index for both Sanqi and pine soils has decreased, transitioning the pollution status from relatively safe to safe. This suggests that the introduction of Sanqi promotes the sustainable development of the SPA system. Full article

Porous carbon-loaded MnO was prepared via a combination of the sol–gel method and the chemical blow molding method using polyvinylpyrrolidone (PVP) and manganese nitrate as starting materials. SEM, EDX, TEM, FTIR, XRD, XPS, nitrogen adsorption–desorption, and elemental analysis were used to assess its physical and chemical characteristics. Furthermore, the adsorption property of porous carbon-loaded MnO for hexavalent chromium (Cr(VI)) in polluted water was investigated in detail. The results demonstrated that large numbers of MnO nanoparticles were evenly mounted on the surfaces of carbon walls, with a uniform distribution of C, N, and O elements. The BET surface area was 46.728 m²/g, and the pore sizes of porous carbon ranged from 2 nm to 10 nm. Additionally, abundant surface functional groups were found in porous carbon-loaded MnO, a result consistent with XPS data and applicable to the adsorption of heavy metals from aqueous solutions containing Cr(VI). The Freundlich model fitted the adsorption isotherm well, and the pseudo−second−order model precisely matched the adsorption kinetics. According to the study results, the adsorption was multilayer, and the adsorption process involved an endothermic reaction. These results indicate that this is a feasible way to synthesize a high−efficiency adsorbent for the removal of harmful heavy−metal ions from wastewater. Full article

Biochar, a porous carbonaceous material derived from the pyrolysis of biomass under oxygen-limited conditions, offers several advantages for environmental remediation, including a high specific surface area, ease of preparation, and abundant raw material sources. However, the application of pristine biochar is limited by its inherent physicochemical shortcomings, such as a lack of active functional groups and limited elemental compositions. To overcome these limitations, metal-modified biochars have garnered increasing attention. In particular, iron-manganese (Fe-Mn) modification significantly enhances the adsorption capacity, redox potential, and microbial activity of biochar, owing to the synergistic interactions between Fe and Mn. Iron-manganese-modified biochar (FM-BC) has demonstrated effective removal of heavy metals, organic matter, phosphate, and nitrate through mechanisms including mesoporous adsorption, redox reactions, complexation, electrostatic interactions, and precipitation. Moreover, FM-BC can improve soil physicochemical properties and support plant growth, highlighting its promising potential for broader environmental application. This review summarizes the preparation methods, environmental remediation mechanisms, and practical applications of FM-BC and discusses future directions in mechanism elucidation, biomass selection, and engineering implementation. Overall, FM-BC, with its tunable properties and multifunctional capabilities, emerges as a promising and efficient material for addressing complex environmental pollution challenges. Full article

The aim of the article is to highlight the increasing environmental burden on aquatic ecosystems in Slovakia due to continuous pollution from municipal, industrial and agricultural sources. Laboratory analyses have shown alarming exceedance of the limit values of contaminants, with nitrate nitrogen (NO₃⁻) reaching 5.8 mg/L compared to the set limit of 2.5 mg/L and phosphorus concentrations exceeding the permissible values by a factor of five, thereby escalating the risk of eutrophication and loss of ecological stability of the aquatic ecosystem. The accumulation of heavy metals is also a problem—lead (Pb) concentrations reach up to 9.7 μg/L, which exceeds the safe limit by a factor of ten. Despite the measures implemented, such as scum barriers, there is continuous contamination of the aquatic environment, with illegal waste dumps and uncontrolled runoff of agrochemicals playing a significant role. The research results underline the critical need for a more effective environmental policy and more rigorous monitoring of toxic substances in real time. These findings highlight not only the urgency of more effective environmental policy and stricter real-time monitoring of toxic substances, but also the necessity of integrating environmental logistics into the design of sustainable solutions. Logistical approaches including the optimization of waste collection, coordination of stakeholders and creation of infrastructural conditions can significantly contribute to reducing environmental burdens and ensure the continuity of environmental management in ecologically sensitive areas. Full article

Stormwater carries significant amounts of pollutants—including metals, microorganisms, organic micropollutants, and nutrients—from land surfaces into nearby water bodies, leading to water quality deterioration and threats to both human health and ecosystems. The removal of these contaminants is essential not only for environmental protection, but also to enable the reuse of treated water for various beneficial applications. Common treatment methods include bioretention systems, biofiltration, constructed wetlands, rain gardens, swales, and permeable pavements. To improve pollutant removal efficiency, adsorbent materials are often incorporated into the soil substrate of these treatment devices. However, most research on adsorbents has focused on their effectiveness against one or two specific pollutants and has been conducted under static, short-term laboratory conditions rather than dynamic, field-relevant scenarios. Column-based dynamic filtration type studies, which are more informative for field applications, are limited. In one study, a combination of two or more adsorbents with contrasting properties that matched the affinity preferences of the different pollutants to the substrate media removed 77–100% of several heavy metals that occur in real stormwater compared to 38–73% removal with only one adsorbent. In another study, polycyclic aromatic hydrocarbon removal with zeolite was only 30–50%, but increased to >99% with 0.3% granular activated carbon addition. Long-term dynamic column-based filtration experiments and field studies using real stormwater, which contains a wide range of pollutants, are recommended to better evaluate the performances of the combined adsorbent systems. Full article