Mycoremediation is classified as an inexpensive, environmentally friendly, and effective technique to reduce wastewater. Leiotrametes menziesii BRB 73 was one of the White Rot Fungi (WRF) that has the potential to degrade dyes. Suitable environmental conditions can optimize dye decolorization results. This study aims to investigate optimal environmental conditions such as time incubation, concentration of dyes, pH, CuSO4, and glucose concentration against decolorization of a mixture of direct dyes and enzyme activity (laccase and MnP). The mixture of commercial direct dyes used contains direct turquoise (DT), direct orange (DO), and direct yellow (DY) dyes. Decolorization was measured using a spectrophotometer at 400-700 nm. Laccase and MnP assay using ABTS and 2.6 DMP as substrate, respectively. The highest decolorization by Leiotrametes menziesii BRB 73 was produced at 54.3% at 96 hours and increased to 67% at a dye concentration of 500 mg.L-1. Meanwhile, the highest laccase and MnP activities were 215 U.L-1 and 39 U.L-1, respectively. pH range was quite wide, ranging from pH 5.5-9, supported by stable MnP activity from pH 3-7. CuSO4 inducers were not required for the decolorization of these dyes. Decolorization was optimal at the addition of 1% glucose, while enzyme activities were 0.5% glucose. Decolorization of dyes by Leiotrametes menziesii BRB 73 was indicated through degradation pathways involving laccase and MnP enzymes. This isolate has a high tolerance to dye concentrations, a wide pH range, and low carbon requirements. Thus, it was recommended as a mycoremediation agent.

Improper disposal of landfill leachate, a highly polluted wastewater, can harm living beings and the ecosystem. Of all the treatment technologies available, electrochemical techniques have the most advantages in terms of ease of use, affordability, and the ability to degrade various contaminants found in landfill leachate effectively. Though there are a sufficient number of research articles regarding the electrochemical treatment of leachate, it has many research gaps, such as a study on the mechanism of radicle generation, pollutant degradation, study on different electrodes with various pollutants concentrations, application of green catalysts, byproduct formation assessment, energy recovery, etc. This review article explores the applications of electrooxidation techniques for the treatment of landfill leachate. Key aspects discussed include the (i) fundamental concepts in electrochemical treatment and its mechanism, (ii) factors affecting the electrochemical treatment efficiency, (iii) the applicability of leachate treatment with different electrochemical methods, (iv) recent advances, (v) merits, and demerits and (vi) proposal of future scope and the studies needed. The integration of electrooxidation with other treatment processes and the challenges hindering widespread adoption are also addressed. Overall, electrooxidation demonstrates promise as an effective and sustainable method for managing landfill leachate. Consequently, this article directs chacurrent and future research efforts toward optimizing the leachate treatment through electrooxidation techniques.

Heavy metal (HM) pollution has been a significant issue for the environment and public health. Unmonitored industrial effluents are a major source of HM pollution. However, metallotolerant bacteria thriving in such environments could be potentially useful for bioremediation purposes. In this study, Bacillus cereus IEI-01 was isolated from water samples of Badshahpur Lake, Gurugram, showcasing resilience to HM exposure and thriving under optimal conditions at 37°C and pH 7.0. Morphological and biochemical characterization showed its Gram-positive rod shape and metabolic versatility, including glucose fermentation and nitrate reduction capabilities. Molecular analysis further affirmed its close relation to the Bacillus cereus strain. Dynamic bacterial growth patterns were observed, with typical sigmoidal curves indicating significant growth over 72 h. When exposed to various HMs, the strain IEI-01 exhibited differential tolerance and promoting patterns, with cadmium (Cd) and lead (Pb) compared to other metals. Over 72 h, the strain exhibited substantial removal rates ranging from 60.64% to 87.43% for Cd and 41.87% to 52.62% for Pb. The concentration-dependent bio-removal efficiency of IEI-01 in Cd-spiked cultures displayed a declining trend with increasing concentrations, with removal rates ranging from 80.23% to 60.72% over the same period. These findings highlight the potential of Bacillus cereus IEI-01 for HM bioremediation, particularly at lower concentrations. Its efficacy in removing Cd and Pb from contaminated environments suggests promising applications in environmental cleanup efforts.

Exploration of microbial flora in red mud ponds is a topic of economic importance. In this study, we report two bacterial strains isolated from red mud ponds of Utkal Alumina, Odisha India. These strains were identified to be Brevundimonas sp. and Pseudomonas sp. through 16S rDNA analysis which showed more than 99% similarities with their respective clades. The LD50 values showed metal resistance to As, Cr, Cu, and Pb in a range of 2-8 mM. Both the strains showed a high tolerance towards arsenic and lead but a low tolerance towards chromium and copper salts. The bioaccumulation of copper was found to be the maximum and that of arsenic was the minimum. To find out the underlying genetic mechanism of the metal tolerance, a degenerate PCR approach was made to find out the genes responsible for the metal efflux or transformation. Two putative arsB genes could be identified from these two strains. Phylogenetic analysis of deduced amino acid sequences showed similarities with the amino acid sequences of arsB genes of Pseudomonas strains and formed monophyletic clades with their arsB proteins. These strains thus harbor potential genetic mechanisms for metal tolerance. Determination of whole operons and their cloning is the future aspect of the study. Moreover, these bacterial strains have a high potential to accumulate copper and can be used in studies related to biomining of copper.

The rapid increase in heavy metal accumulation within soil ecosystems has become a significant concern due to various anthropogenic activities such as industrial processes, agricultural practices, and urbanization. These activities have led to elevated levels of heavy metals like lead, cadmium, mercury, and arsenic in the soil, which, when surpassing permissible limits, pose severe toxicological risks to both human health and plant life. Once heavy metals are introduced into the soil, they can be readily absorbed by plants, subsequently entering the food chain and affecting the metabolic activities of humans and animals consuming these contaminated plants. Although trace amounts of heavy metals are naturally present in the soil, their concentration beyond safe thresholds can lead to deleterious effects, including disruption of enzymatic functions, damage to cellular structures, and interference with essential biological processes. Studies have highlighted that children living in urban and industrial areas are particularly vulnerable to heavy metal exposure, which can result in cognitive impairments, developmental delays, and various other health issues. Furthermore, long-term exposure to these metals can lead to chronic diseases such as cancer, kidney dysfunction, and cardiovascular disorders. Given the escalating threat posed by soil metal contamination, it is imperative to implement stringent management practices aimed at maintaining soil chemistry within safe limits. These practices may include the remediation of contaminated sites, the adoption of sustainable agricultural methods, regular monitoring of soil quality, and the use of phytoremediation techniques to mitigate the impact of heavy metals. Ensuring the safe production of food requires a comprehensive understanding of soil dynamics and the integration of innovative strategies to prevent and control heavy metal pollution. Consequently, addressing this environmental challenge is crucial for safeguarding public health, preserving ecological balance, and promoting sustainable development.

This study aims to develop a comprehensive flood hazard map for effective hazard management in the Noa river basin, located in Assam, India, through the integration of Geographic Information System (GIS) tools and a Maximum Entropy (MaxEnt) model. The MaxEnt machine learning algorithm was employed, utilizing eight selected geographic and environmental parameters as predictors to generate the flood hazard map. The accuracy of the generated map was evaluated using the Area Under the Curve (AUC) metric. Key findings of the study identified elevation and slope as critical parameters in the assessment of flood risk. Results revealed that the flood hazard map produced by the MaxEnt model achieved an AUC value of 0.85, indicating high predictive accuracy. The research underscores the significance of flood hazard maps as essential tools for policymakers, enabling the identification of areas vulnerable to severe environmental and economic damage. By providing a reliable and precise assessment of flood-prone zones, this study contributes valuable insights for the formulation of effective flood management strategies and mitigation measures. The implementation of such hazard maps is crucial in enhancing preparedness and resilience against flooding events, ultimately safeguarding lives, property, and infrastructure in the Noa River basin.

Goa’s iron ore mining industry has generated over 7.7 million tonnes of iron ore tailings (IOTs) in the past two decades. These IOTs pose a significant environmental threat due to heavy metal contamination, dust generation, and acid mine drainage. While some IOTs are used for backfilling, the majority are stored in tailings storage facilities (TSFs), posing long-term risks to surrounding water resources, ecosystems, and land use. Large-scale utilization technologies are crucial for sustainable IOT management. This study investigates the feasibility of incorporating IOTs in construction block production, aiming for high-volume waste consumption and improved resource efficiency. This approach offers a potential pathway to remediate the environmental impact of IOTs. The proposed method replaces 85% of the cement content with a cementitious material comprising 65% Ground Granulated Blast Furnace Slag (GGBS), 10% Fly Ash, and 10% Lime. It also utilizes IOTs entirely as a substitute for sand, with ceramic waste partially replacing coarse aggregates. While partial substitution of coarse aggregates with ceramic waste was attempted, it decreased workability. The optimal mix design, achieving the highest compressive strength, utilizes 15% cement, 65% GGBS, 10% Fly Ash and Lime, and 100% IOTs as fine aggregate with 100% basaltic aggregates. This formulation successfully demonstrates the potential use of IOTs in manufacturing construction blocks that reach compressive strengths of 10.91 N.mm-² and 15.92 N.mm-² at 7 and 28 days, respectively, satisfying the IS 2185-Part 1 (2005) code requirement. The block density was 2.20 g.cm-³. This research demonstrates the potential to convert a significant environmental challenge into a sustainable solution. By utilizing IOTs in construction block production, we can effectively achieve waste remediation; and create resource-efficient and eco-friendly building materials, offering substantial dual benefits for Goa’s environment and construction sector.

The uncontrolled production of waste is a daily phenomenon that is experienced by most global communities, and the situation worsens due to the lack of effective waste management procedures. Solid waste such as sawdust is primarily produced by the forestry industry and although it is utilized by certain countries as briquettes to make fire or as an absorbent to clean fluid spillage as well as a component of ceilings, most of the sawdust along the Lagos Lagoon in Nigeria is left unattended as waste, contributing to environmental pollution. Cellulose, composed of glucose units is a structural component of sawdust and when saccharified the resulting glucose can be fermented into renewable substances such as bio-ethanol. The cellulose degradation process can be performed with a cellulase enzyme such as available in the fungus Aspergillus niger and during the current investigation, this enzyme system was used to bio-convert the cellulose component of sawdust from ten different trees along the Lagoon into glucose. To increase the cellulase action all sawdust materials were delignified before cellulase action with the main aim of determining the optimum pH value for maximum degradation of the various sawdust materials. The pH-related saccharification profile of each type of sawdust was constructed as well as the relative percentage of saccharification and it was concluded that all the materials were optimum degraded at acidic pH-values which varied between pH 5.0 and pH 6.0 that are like optimum pH-values reported for the other types of cellulose materials.

Forward Osmosis is a suitable pretreatment process for reverse osmosis for secondary-treated sewage reuse and secondary-treated industrial effluents. In this study, the FO process is investigated for concentrating synthetic secondary treated tannery effluents using 24 g.L-1 and 38 g.L-1 of NaCl solution as draw solution. Results showed that 38 g.L-1 NaCl solution when used, provided higher flux and lower flux decline ratio as compared to 24 g.L-1 NaCl solution. The solute rejection by FO membrane was more in FO experiments using 38 g.L-1 NaCl solution as DS as compared to 24 g.L-1 NaCl solution. Contact angle, Fourier transform infrared spectroscopy, and scanning electronic microscopy tests on pristine and chemically cleaned membranes indicated the change in membrane structure and the presence of foulants on the membrane surface, indicating insufficient chemical cleaning. Findings signify implications on the concentration of DS and the cleaning method adopted for concentrating treated tannery effluent efficaciously using the FO process.

Natural disasters are natural activities that can disrupt various aspects. Natural disasters cannot be avoided, but the impact of natural disasters can be minimized through mitigation. This can be known through event history to determine an area’s vulnerability to natural disasters. This research aims to determine regional natural disaster vulnerability by calculating the natural disaster index. The data used in this research refers to data from the 2021 PODES data collection, which contains the intensity of natural disasters and casualties according to the type of natural disaster in Indonesia in 2020. The method used for the calculation is the weighted index method. The results of this research produced 5 clusters based on the level of natural disaster vulnerability according to sub-district/village. The top five provinces in Indonesia that have the highest natural disaster-prone areas are Aceh, North Sumatra, West Java, East Java, and Central Sulawesi. Research shows that sub-districts/villages in Indonesia are known according to their level of vulnerability to natural disasters. These results can be used as a reference for the government to carry out mitigation so that accelerated development in the local area can continue.