International Journal of Environmental Science and Technology最新文献

The discharge of untreated textile wastewater poses a significant threat to the environment due to its high color intensity and organic load. Developing cost-effective and efficient treatment strategies is therefore essential to support water reuse and reduce environmental impact. This study investigated the potential of two electrochemical-based processes: electrocoagulation and electrochemical peroxidation (ECP), as well as a hybrid process combining ECP with nanofiltration for the treatment and reuse of textile effluents. Experiments were carried out over 90 min using iron electrodes as anode and cathode, while the influence of operating parameters such as current density (100–400 A/m²), pH (2–11), and hydrogen peroxide dosage (0.1–0.4 mmol/L) was systematically examined. Treatment performance was assessed through color and chemical oxygen demand (COD) removal, alongside permeate flux for nanofiltration. The results demonstrated that ECP achieved the highest removal efficiencies, with 97.67% color removal and 70.33% COD reduction. When coupled with nanofiltration, the hybrid process further improved treatment efficiency under transmembrane pressures of 5 and 10 bar. Surface analyses of the anode using SEM and EDX showed minor deterioration after treatment, while the operational cost of the electrochemical processes was also calculated to assess their economic feasibility. Overall, the findings highlight the promise of electrochemical processes particularly the hybrid as effective and sustainable options for textile wastewater treatment.

Environmental impact assessments (EIAs) for railway projects in Korea remain largely qualitative and rely on standardized guidelines, which limit their capacity to reflect site-specific and temporal environmental variations. This study introduces a digitalized framework for assessing air quality and noise in railway Environmental impact assessments (EIAs) through the integration of drone and LiDAR technologies. The Osong railway test track was selected as a demonstration site, where time-series measurements of particulate matter and noise were conducted under varying altitudes, distances, and structural configurations. A high-resolution digital twin of the site was developed using photogrammetry and three-dimensional (3D) point cloud data. The analysis revealed significant correlations between Particle matter (PM) concentrations and microclimatic factors such as humidity and wind speed, and the drone-based noise data exhibited strong consistency with conventional ground measurements. These results confirm that the proposed drone–LiDAR approach enhances the spatiotemporal accuracy and reproducibility of environmental observations. The study concludes that this framework can substantially improve the objectivity and scalability of railway Environmental impact assessments (EIAs) and can be extended to other linear infrastructure projects to support sustainable environmental management.

Water pollution caused by dye-containing wastewater represents a major global environmental challenge. While various green synthesis approaches have been explored for the removal of Methylene Blue (MB), there remains a critical need to enhance their efficiency through proper process optimization and the exploration of novel eco-friendly materials. In this study, Cascabela thevetia leaves (CTL) were investigated as a low-cost, sustainable biosorbent for MB dye removal from wastewater. CTL powder was characterized using Fourier Transform Infrared (FTIR) spectroscopy, Scanning Electron Microscopy (SEM), and X-ray Diffraction (XRD). To optimize adsorption efficiency, the study employed both machine learning (ML) techniques and response surface methodology (RSM) to evaluate the effects of key variables, including solution pH, contact time, and initial dye concentration. The optimal conditions identified were: 0.1 g of adsorbent, 10 mg/L dye concentration, 50 min contact time, and pH 11. The adsorption process was best described by the Freundlich isotherm model (R² = 0.997), and kinetic analysis indicated that a pseudo-second-order model accurately represented the adsorption behavior. Thermodynamic parameters (ΔG°, ΔH°, ΔS°) confirmed the process to be spontaneous and exothermic. Notably, the CTL powder demonstrated excellent recyclability with no significant loss in adsorption capacity over multiple cycles. This is the first study to integrate machine learning optimization with conventional adsorption modeling for MB dye removal using CTL powder. This approach not only improves prediction accuracy but also advances the development of cost-effective, sustainable solutions for dye-contaminated wastewater treatment. Moreover, the study addresses existing research gaps at the intersection of adsorption science and data-driven process optimization, setting the stage for future innovations in environmental remediation.

Considering the diminishing nature of fossil fuels, their associated air pollution, and major contribution to global warming, renewable energy resources have attracted the attention of researchers and government policymakers around the world. This is mainly because they are clean, locally available, environmentally friendly, and ensure our future energy demands. Despite their current expensive cost, they will eventually become economically viable. Nonetheless, the type of renewable energy resources and feasible extractable amounts of renewable energy from such resources are region specific. This study investigates five climatic zones of a vast country like Iran and provides suitability of various renewable energy resources (i.e., solar, wind, geothermal, hydro, and biomass) for each region. Ranking of their suitability is determined using five main criteria of technical, pecuniary, environmental, social, and reliability. Opinions from experts have also been used to identify sub-criteria that are relevant to each of the main criteria. The criteria were weighed using the fuzzy best–worst method and evaluation and ranking of different energy production resources for each region, were carried out using the FTOPSIS, FVIKOR, and FCOPRAS methods, all of which belong to multi-criteria decision-making field. The results of this research and investigation rank solar energy as the first option for the four climatic regions of Iran, where sunlight is available throughout the year, and wind energy as the first option only for its “temperate and humid summer, temperate winter” region. The weighing criteria of the obtained results were validated via ChatGPT of OpenAI.

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Hexavalent chromium (Cr(VI)) poses a significant environmental challenge because of its high toxicity, non-biodegradability, and mutagenic effects. This study investigates the potential of a chemically modified spent mushroom substrate (SMS), an agricultural byproduct from mushroom cultivation, as an adsorbent. This study employed the SMS in batch experiments to evaluate its potential for removing Cr(VI) by varying the adsorbent dose, pH, contact time, chromium concentration, and temperature. The adsorbent was prepared through washing, sonication, chemical activation using HCl and NaOH, and subsequent neutralization. Fourier-transform infrared (FTIR) analysis confirmed the presence of various functional groups. X-ray diffraction (XRD) analysis revealed a decrease in crystallinity post-activation, indicating a less dense atomic spacing. Scanning electron microscopy-energy dispersive X-ray spectroscopy (SEM–EDS) showed that the surface of HCl-activated SMS had a higher number of well-defined pores than NaOH-activated SMS and unactivated SMS. Brunauer–Emmett–Teller (BET) analysis confirmed these findings, with surface areas of 77.02 m²/g (HCl-activated), 22.60 m²/g (NaOH-activated), and 14.22 m²/g (unactivated). HCl-activated SMS exhibited the highest adsorption efficiency and maximum capacity, reaching 12.68 mg/g. The adsorption process followed the Freundlich isotherm model and Pseudo-second-order kinetics. These findings highlight the potential of chemically activated SMS as an adsorbent for the remediation of Cr(VI)-contaminated wastewater.

Construction and demolition waste (CDW) are commonly disposed of in unlined landfills or inappropriately at irregular sites. Civil construction materials may contain hazardous substances that, if solubilized or leached, can negatively impact the environment and human health. Understanding the leaching behavior of CDW is essential for assessing its environmental performance and ensuring its safe reintegration into the construction supply chain. This study aimed to investigate the impact of paint presence on the leachate contamination potential. The method involved the UNE-EN 12457-3 compliance leaching test and column percolation tests conducted under both saturated and unsaturated conditions, using columns filled with CDW, with and without paint. The samples, regardless of the presence of the paint layer, were classified as non-hazardous according to the criteria established by the European Council. The results indicate that the presence of paint mainly influenced the apparent color, turbidity, and concentrations of Na⁺ and K⁺ in the leachate. Although various heavy metals are used in paints, especially as pigments, the presence of paint in CDW did not significantly influence the release of these metals into the leachate. The CDW leachates, regardless of the presence of paint, exhibited potential for groundwater contamination due to elevated levels of sulphate and total dissolved solids. Notably, CDW also demonstrated the capacity to remove Zn and Fe and CDW without paint was found to reduce water turbidity.

The Capibaribe and Ipojuca Rivers drain vital watersheds in the state of Pernambuco, northeastern Brazil, but are influenced by intense anthropogenic activities, particularly because they flow through municipalities in the region known as the Textile Triangle. To evaluate the spatial distributions, contamination levels, and sources of trace elements, surface sediments were collected from the two rivers and the concentrations of seven trace elements (As, Cr, Cu, Co, Ni, Pb, and Zn) were determined. Contamination levels were assessed using five indices: enrichment factor (EF), geoaccumulation index (I_geo), contamination factor (CF), pollution load index (PLI), and combined pollution index (CPI). For the Capibaribe River, Pb was considered to originate from natural sources, with the remaining trace elements presenting contamination levels ranging from low to moderate, primarily due to inputs associated with textile industry effluents and agricultural activities. For the Ipojuca River, Ni was derived from natural sources, while Cr, Cu, Pb, and Zn, at levels ranging from moderate to high, were from anthropogenic origins, especially sewage discharges. Multivariate statistical analysis was employed to distinguish the primary sources of trace element contamination, which was shown to increase in urban areas. Potential sources of contamination in both rivers also included contributions from vehicle emissions and rainwater leachate. These findings provide a comprehensive understanding of substantial contamination by trace elements and the impact of human activities in these watersheds, serving as a guide for the development of preventive and remediation policies aimed at minimizing risks to living species.

Forest fires, one of the largest natural disasters, have had negative consequences for centuries. Today, these damages continue due to various negligences or climate influences. In large cities, this danger brings along significant problems. This study focuses on the Izmir region, a metropolitan city in Türkiye, where the ecosystem and biodiversity are damaged by fire every year. In order to prevent these fires, it is necessary to identify areas with high fire potential and develop fire management strategies there. In this context, the aim of the study is to obtain a comprehensive fire risk map in GIS and routes for early fire detection with the help of UAVs. The risk map was created by combining 14 maps, including topographic, meteorological, human-induced, historical fire data, and vegetation data. As a result of the findings, single and multi-center routes were obtained using K-Means and LCP methods with UAVs divided into three categories of high, medium and low cost in high fire risk points. It has been found that more efficient results are achieved with a multi-center approach and medium-cost UAVs. This holistic approach proposed within the scope of forest fire management helps develop more effective strategies.

Textile industries contribute significantly to the global economy; however, they pose a serious environmental threat due to the discharge of undesired dye runoff and intensely colored effluent. This study evaluates and compares various textile wastewater treatment strategies, including biological, physical, and integrated systems. Out of fourteen bacterial isolates, a newly isolated strain, Staphylococcus auricularis TWD11, and a bacterial consortium, TWDcon, exhibited the highest decolorization efficiencies. The optimized parameters yielded decolorization rates of 83.50 ± 0.51% and 68.02 ± 0.10%, respectively. When ionizing irradiation was applied, increasing the dosage from 4 to 20 kGy raised the decolorization rate from 43.91 ± 6.48 to 79.51 ± 0.01% via gamma irradiation, while electron beam irradiation enhanced the decolorization potential from 54.03 ± 1.04 to 93.09 ± 1.01%. In terms of efficiency, safety, reusability, and economic feasibility, complementary integrated systems were studied. In the suggested system, undiluted effluent was exposed to electron beam irradiation (4 kGy) during the primary stage, followed by a secondary biological treatment using optimized Staphylococcus auricularis TWD11, and finally passing through a tertiary treatment process in which wastewater traversed a low-cost multi-media filter. Integrated system treatment achieved decreases in chemical oxygen demand, biological oxygen demand, total suspended solids, total dissolved solids, and color by 96%, 93%, 97.80%, 81.70%, and 99.20%, respectively. Post-treatment, degradation metabolites were examined using ultraviolet–visible spectroscopy, fourier transform infrared spectroscopy, high-performance liquid chromatography, and toxicity assessment. Complementary integration systems provide a sustainable, efficient, and safe biotechnological solution for textile effluent remediation.

Soil–plant interactions are essential for understanding adaptive responses to abiotic stressors such as salinity and metal(loid)s contamination. This study analyzed plant behavior of the recretohalophyte Limonium daveaui Erben when cultivated in saline and in gossan mine soils, both with and without organic–inorganic amendments. Analysis included soil physicochemical and biological parameters, multielemental composition of plant tissues, and the cationic profile of salts excreted by foliar salt glands. All plants grown in unamended gossan soil died, whereas amendment addition substantially improved both gossan and saline Fluvisol properties, raising pH in gossan soil, reducing salinity, increasing nutrient availability, generally stimulating microbial enzymatic activity, thereby allowing normal plant development. In amended gossan soil, plants accumulated high concentrations of As and Pb and moderate levels of other potentially hazardous elements (PHE) in roots and shoots without visible toxicity symptoms. Transfer coefficients revealed low PHE translocation but high biological absorption, indicating efficient uptake. Microscopic analyses showed the presence of the typical Limonium salt glands on both leaf surfaces through which plants excreted salts with macroelements but not As and Pb. The findings indicate that plant's primary tolerance strategy is based on accumulation of metal(loi)s in roots, rather than exclusion or excretion through foliar salt glands.