Environmental Quality Management最新文献

High chromium content in tannery waste is a significant environmental concern because of its remarkable ecological hazards. However, while the potential of bacteria for bioremediation has been widely explored, research on fungal bioremediation remains relatively limited and underexplored. This study aimed to identify and examine chromium-resistant fungi to determine their role in reducing chromium levels and observe their capability to help in remediation processes for cleaning up contaminated sites. Nine samples were collected from chromium-contaminated tannery waste in Jhaowchar, Hemayetpur, Savar, Dhaka. These isolates were provisionally identified based on morphological traits. Then, subcultures of those isolates yielded four pure isolates. Finally, molecular identification was performed using PCR and sequence analysis, and the results were identified as Penicillium citrinum, P. janthinellum, Fusarium oxysporum, and Trichoderma harzianum. Subsequently, the chromium tolerance capacity of these isolates was evaluated after 72 h of incubation at 30°C. They all exhibited successful growth at concentrations of 500 and 1000 mg/L. At 1300 mg/L, P. janthinellum and T. harzianum developed while the others did not. At 1500 mg/L, only T. harzianum demonstrated growth. None of the fungal isolates could grow at 2000 mg/L. Notably, T. harzianum exhibited superior chromium tolerance at 1500 mg/L. The Cr (VI) reduction capacity of the four fungal isolates was quantitatively assessed using the diphenylcarbazide (DPC) method, with all isolates demonstrating approximately 95% reduction of 10 mg/L Cr (VI) to the less toxic Cr (III). For hexavalent chromium removal, contaminated soil containing 50 mg/L of Cr (VI) treated with all selected fungal isolates showed complete disappearance of Cr (VI) after incubation for 7 days. Therefore, these isolates can be employed in an economical and eco-friendly manner to detoxify chromium and are promising for the removal of Cr (VI) contamination.

Pharmaceutical wastewater is characterized by complex and recalcitrant organic compounds that pose serious environmental and ecological risks. The current study investigates the effectiveness of a novel sequential process integrating electrocoagulation (EC) with Fenton (F) and electro-Fenton (EF) oxidation for the treatment of real pharmaceutical effluent, with performance evaluated in terms of chemical oxygen demand (COD) removal. The EC process was optimized by adjusting current density (up to 200 mA), pH, and external coagulant dosage, achieving a maximum COD removal of 42%. The addition of external chemical coagulants, such as polyaluminum chloride (PAC), alum, ferric chloride, and aluminum chloride improved pollutant removal efficiency compared to the electrochemical process alone. Under acidic conditions (pH = 3), the EF process using hydrogen peroxide (250–1000 mg/L) and ferrous sulfate (30–120 mg/L) achieved a maximum COD reduction of 65%, while the conventional Fenton process resulted in 45% removal. Sequential coupling of EC and EF under optimized conditions yielded a COD removal of 85%, and the combination of EC followed by PAC and EF achieved the highest COD reduction of 92%. The results clearly demonstrate the synergistic effect of the EC–PAC–EF process in degrading refractory organic pollutants from pharmaceutical wastewater and hence highlight the potential of hybrid electrochemical treatment as an efficient and sustainable solution.

Fish market wastewater has high content of organic pollutants that quickly decompose crustacean and fish residues. This study investigates the performance of sediment microbial fuel cell (SMFC) and plant microbial fuel cell (PMFC) systems where mint plants are used to improve the microbial activity and electricity generation. Over 42 days, both systems were monitored for voltage output, power density, and removal of COD, BOD, oil and grease, and TSS. PMFC delivered a higher peak voltage (181.5 mV) and maximum power density of 25.6 mW/m² that was superior to SMFC which delivered 12.8 mW/m² and whose voltage decreased after 840 h. Pollutant removal was also superior in PMFC, oil and grease pollutant removal decreased from 2710 to 59 mg/L as compared to 90 mg/L in SMFC. Both systems achieved similar reductions in TSS to below 50 mg/L. Overall, PMFC was shown to be more efficient in wastewater treatment and the bioelectricity production, which promotes its prospects of sustainable wastewater management.

Access to safe drinking water is essential for public health, yet rapid urbanization in cities like Cuttack and Bhubaneswar in India is exacerbating groundwater contamination. Industrial discharge and inadequate infrastructure are contributing to water quality deterioration, which calls for the development of robust frameworks for assessment and management. This study aims to predict the water quality index (WQI), classify groundwater quality, and identify key contaminants using machine learning (ML) techniques. The preprocessing steps included removing outliers, handling missing values through imputation, and calculating WQI using weighted hydrochemical parameters. Five machine learning models were evaluated for performance: logistic regression, decision tree, support vector machine (SVM), naïve Bayes, and a feedforward neural network also known as a multilayer perceptron (MLP). The neural network model achieved the highest classification accuracy of 93%, followed by logistic regression at 89%. To further enhance performance, a custom stacking ensemble model named Neuro-StackNet was developed. This model integrates the neural network and logistic regression as base learners while using random forest as the meta-learner. Neuro-StackNet achieved an accuracy of 95% and effectively classified the water samples into three quality categories: Excellent, Good, and Poor. This study offers a scalable, data-driven framework for urban groundwater quality assessment. It can support policymakers in identifying contamination hotspots and planning targeted remediation strategies.

In this study, characteristics and anaerobic treatability of a resin wastewater were investigated. In addition to organic matter fractions (biochemical oxygen demand [BOD₅], chemical oxygen demand [COD], inert COD, total carbon, total organic and inorganic carbon, etc.), the amounts of various components (nitrogen and phosphorus forms) were measured. Also, the specific methanogenic activity (SMA) of the anaerobic sludge was determined. Subsequently, anaerobic toxicity tests (ATA) and biochemical methane potential tests (BMP) were conducted. Resin wastewater had a very high COD value (19,200 mg/L), with 696 mg/L of this being in an inert form. Wastewater had an acidic character (pH = 3.46). Nitrogen and phosphorus fractions were at low levels. The BOD₅/COD ratio was calculated as 0.48, which indicates that wastewater can be treated with biological processes. The anaerobic inoculum had a high SMA value (1.25 kg COD-CH₄/kg VSS), pointing to the high methanogenic potential of the anaerobic sludge sample. Based on the IC₅₀ values, wastewater contains significant toxic components (23.07% and 30.20% after 24 and 48 h, respectively). The BMP values for wastewater samples diluted at 12%, 24%, and 36% were 3778, 3056, and 2926 mL CH₄/L wastewater, respectively. These results showed that despite wastewater having a toxic character, it can be treated biologically after the acclimatization process. Also, wastewater has a huge methane potential. Therefore, in terms of sustainable treatment, energy recovery is possible.

The increasing generation of areca leaf waste biomass presents an opportunity for sustainable utilization in paper product manufacturing. This study aims to develop chemical-free paperboard products by converting areca leaf waste through an optimized hydrothermal-mechanical pulping process. The raw biomass was subjected to pulping under varying conditions of time, temperature, and solid-to-liquor ratio. Mechanical strength properties of the resulting paperboards were evaluated using TAPPI standard methods, while modeling and regression analysis were conducted via Minitab software to identify optimal processing parameters. Additionally, a life cycle assessment (LCA) using openLCA software was performed to evaluate the energy consumption and environmental impact of the pulping process. The optimized conditions produced greyboard, strawboard, and stencil backing sheets with tensile indexes of 18.34, 13.06, and 16.75 N/m/g; tear indexes of 7.53, 6.39, and 6.84 mN/m²/g; breaking lengths of 1867, 1332, and 1760 m; and burst indexes of 0.905, 0.56, and 1.00 kPa/m²/g, respectively. These properties conform to Indian Standard specifications (IS 2617:1967 and IS 3302:1965), demonstrating the feasibility of producing high-quality, chemical-free paperboard products without adhesives or additives. The LCA results confirmed that this process significantly reduces energy use and environmental impact compared to conventional methods. This research provides a sustainable approach to valorizing areca leaf waste, with potential applicability for blending with other non-wood pulps in the paper industry.