Industrial Water Pollution Research Articles

Development of an input-output CGE model for collaborative management of water pollution reduction and carbon mitigation

Achieving the dual goals of improving water quality and reducing carbon emissions requires a systematic study of the combined effects of economic and environmental policies on industrial systems. A CGE-IWCR model is developed to examine the long-term evolution of industrial economic and environmental responses in the Yangtze River Economic Belt (YREB) under varying levels of carbon and water pollution taxes. The CGE-IWCE model offers several advantages: i) under the dual tax (carbon and water pollution tax) interventions, it can effectively forecast industrial CO2 and water pollution emissions driven by both macro and local factors from 2025 to 2060; ii) it quantitatively captures the interactions between various policy interventions, thereby providing guidance for comprehensive regional policy formulation. It is discovered that in the double-tax scenario, various combinations of carbon and water pollution taxes significantly impact direct carbon emissions and direct water pollution emissions, and from local consumption, imports, and exports in industrial sectors. Among them, the dual pressure of high carbon and water pollution taxes, which significantly raise production costs. In addition, increasing the carbon tax from 10 ¥/tonne to 50 ¥/tonne, the water pollution equivalent (WPE) reduction rate rises from 20.79% to 52.67% with the increase in the carbon tax from 2050 to 2060, when the water pollution tax is low. Between 2025 and 2060, the carbon tax plays a significant role in influencing the total industrial output change rate in YREB. from 2025 to 2060, the water pollution tax will play a more significant role in CO2 reduction in YREB’s industrial sector. The results will offer decision-making support for water pollution reduction and carbon mitigation in the YREB’s industrial sector, quantitatively identify the interactions between the dual taxes, and provide new insights for analyzing the impacts of pollution reduction and carbon mitigation policies.

Nuclear abnormalities and DNA damage indicate different genotoxic stress responses of marsh frogs (Pelophylax ridibundus, Pallas 1771) to industrial and agricultural water pollution in South Bulgaria.

Amphibians are continuously exposed to pollutants and anthropogenic stressors in their natural habitats, representing a significant challenge to their survival. This study aimed to quantify the extent of DNA damage caused by chronic industrial and agrochemical surface water pollution in wild populations of the marsh frog (Pelophylax ridibundus). The observed genotoxic effects on the marsh frog DNA, manifesting as abnormalities in erythrocyte nuclei, micronuclei, and DNA strand breaks, demonstrate a clear cause-and-effect relationship with surface water parameters, heavy metals, metalloids, and pesticides. The most prevalent nuclear abnormalities observed were notched and blebbed nuclei and nuclear buds, indicative of chromosomal instability. The significant correlation between cadmium, lead, and copper contamination and the increased frequency of DNA breakage in the marsh frogs from the industrial site indicates that heavy metal contamination has a higher genotoxic potential than pesticide contamination. These findings underscore the vulnerability of amphibians inhabiting heavy metal-contaminated wetlands to genotoxic stress due to their lower tolerance to environmental genotoxins. Therefore, using in situ assays to detect erythrocyte nuclear abnormalities and DNA damage in P. ridibundus could serve as a reliable indicator of environmental quality and provide early detection of anthropogenic pollution.

Industrial water pollution and farmer adaptation: Evidence from rice farming in Jiangsu, China

AbstractThe shift of industrial water pollution from urban to rural areas during industrialization can impact agricultural production and stimulate farmers’ adaptive behavior. As an illustration, this study examines the impact of industrial water pollution from manufacturing firms on rice production in Jiangsu, China. By combining data from the China Rural Fixed Point Survey with the China Environmental Statistics Database, we employ an extended translog production function to distinguish between the effects of industrial water pollution and farmers’ adaptation behaviors. Our results demonstrate that industrial chemical oxygen demand (COD) has a direct biological effect on paddy rice growth, reducing rice yields by 3.76 to 4.17 percent. This detrimental effect is most pronounced within a radius of 5 kg from the village center. Additionally, farmers increase their operating inputs to mitigate the adverse effects of industrial water pollution. These findings underscore the need for stringent environmental regulations and enhanced environmental education in rural areas to promote the sustainable development of both manufacturing industry and agriculture in developing countries.

On the Valorization of Olive Oil Pomace: A Sustainable Approach for Methylene Blue Removal from Aqueous Media.

Currently, industrial water pollution represents a significant global challenge, with the potential to adversely impact human health and the integrity of ecosystems. The continuous increase in global consumption has resulted in an exponential rise in the use of dyes, which have become one of the major water pollutants, causing significant environmental impacts. In order to address these concerns, a number of wastewater treatment methods have been developed, with a particular focus on physicochemical approaches, such as adsorption. The objective of this study is to investigate the potential of a bio-based material derived from olive oil pomace (OOP) as an environmentally friendly bio-adsorbent for the removal of methylene blue (MB), a cationic dye commonly found in textile effluents. The biobased material was initially characterized by determining the point of zero charge (pHpzc) and using scanning electron microscopy (SEM), X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FTIR). Subsequently, a comprehensive analysis was conducted, evaluating the impact of specific physicochemical parameters on MB adsorption, which included a thorough examination of the kinetic and thermodynamic aspects. The adsorption process was characterized using Langmuir, Freundlich, Brunauer-Emmett-Teller (BET), and Dubinin Radushkevich (D-R) isotherms. The results suggest that the equilibrium of adsorption is achieved within ca. 200 min, following pseudo-second-order kinetics. The optimal conditions, including adsorbent mass, temperature, bulk pH, and dye concentration, yielded a maximum adsorption capacity of ca. 93% (i.e., 428 mg g-1) for a pomace concentration of 450 mg L-1. The results suggest a monolayer adsorption process with preferential electrostatic interactions between the dye and the pomace adsorbent. This is supported by the application of Langmuir, BET, Freundlich, and D-R isotherm models. The thermodynamic analysis indicates that the adsorption process is spontaneous and exothermic. This work presents a sustainable solution for mitigating MB contamination in wastewater streams while simultaneously valorizing OOP, an agricultural by-product that presents risks to human health and the environment. In conclusion, this approach offers an innovative ecological alternative to synthetic adsorbents.

Racial and ethnic disparities in health risk from industrial surface water pollution in the United States, 2011–2021

Industrial chemical pollution is released into surface water at a large scale annually in the United States. However, geographic variation and racial disparities in potential exposure are poorly understood at a national scale. Using county-level Risk-Screening Environmental Indicators data for 2011–2021 and American Community Survey data, this study analyzes the spatial and temporal distribution of health risk from modeled water releases using a Gamma hurdle model. Several racial disparities in presence of risk and amount of risk were identified, particular for Black or African American and Asian populations. At least 200 million U.S. residents live in a county where health risk from this pollution is present. Exposure reduction in high-risk areas may improve health for the broader population while also reducing inequities.

Photocatalytic nanohybrid UV-light-driven PVDF/GO-NiFe@SiO2 membrane coupled with bentonite adsorption and ozonation process for a sustainable textile wastewater treatment

The textile industries face significant environmental challenges due to the presence of complex pollutant dyes in its wastewater, making it one of the world's major sources of industrial water pollution. Numerous studies have been employed to overcome this problem, including physical, chemical, and biological treatments. However, most of those methods still suffered to achieve higher dye removal performance. This study provides new insight regarding textile wastewater treatment containing indigo red as the main colorant by carrying out a hybrid process combining bentonite adsorption, ozonation, and photocatalytic membrane filtration. For the membrane, we propose a modified polyvinylidene fluoride (PVDF) membrane incorporated with graphene oxide (GO) and nickel-iron doped silica (NiFe@SiO2) photocatalyst, which is named PVDF/GO-NiFe@SiO2 membrane. The membrane was employed under different sets of filtrations (dark and under ultraviolet irradiation) to treat natural dye wastewater from textile industry effluent. Further improvement was achieved when UV light irradiation was subjected to the process. This sequential adsorption-ozonation-membrane process under UV exposure exhibited improved dye removal from 55.11 % to 97.22 %. The results show that the proposed hybrid process successfully improved the membranes' antifouling behavior, thus boosting the membranes' performance and durability. From a broader perspective, our work promotes new insights for the integration of other physical, chemical, and biological treatment methods to improve the performance and durability of membrane-based processes, particularly for dye wastewater treatment.

Fatty acid composition of selected fish species farmed in Biofloc system

Bangladesh is well known for the abundant range of fish. Though fish consumption and variety are very high in Bangladesh, the biodiversity has been alarmingly declining in recent years due to a number of factors including the country's rapid population growth, industrial water pollution, natural disasters, sea intrusion, salinity, overexploitation of fisheries, use of harmful gear, and dewatering of waterbodies. Given that 60% of Bangladesh's rural poor are functionally landless, lack of access to land and water for agricultural production, and rely, in part, on shared resources like fish for their livelihoods and food, the loss of fish biodiversity could pose a special challenge for them. Considering all of this, biofloc technology ensures safe food and higher productivity in high-density fish farming in a limited area by being sustainable and ageless. In order to satisfy the demands, more creative and effective techniques for growing and harvesting fish have been created as the fishing business has developed. Present study analyses the fatty acid profile of two commonly consumed fish species Oreochromis niloticus (Tilapia) and Systomus sarana (Shorputi). These fishes were farmed in biofloc system. They were fed commercial feeds and organic feed. Later the the fatty acid profile of both groups were measured. The organic feed group showed higher level of PUFA, omega 3 & 6 fatty acid. Through biofloc technology it is possible to produce fish species with high nutritional level using minimum land and water resources. Sustainable food system can be developed through more research in Bangladesh. Bioresearch Commu. 10(2): 1592-1596, 2024 (July)

Can Market-Based Environmental Regulation Inhibit the Industrial Water Pollution?

Can Market-Based Environmental Regulation Inhibit the Industrial Water Pollution?

Integrating machine learning and electrochemistry: A hybrid SA-DE-RF approach for optimizing electrode composition in water treatment

The imperative to address the burgeoning challenge of industrial water pollution has catalyzed the pursuit of sophisticated treatment methodologies capable of neutralizing non-biodegradable contaminants. This investigation focuses on the optimization of Ti/SnO2-Sb-Ni anode composition, leveraging a synergistic hybrid machine learning strategy that integrates Simulated Annealing (SA), Differential Evolution (DE), and Random Forest (RF) algorithms. This triad of algorithms is meticulously applied to ascertain the optimal doping concentrations of antimony (Sb) and nickel (Ni), pivotal in maximizing the efficacy of electrochemical oxidation processes. Our findings elucidate that the meticulously optimized Ti/SnO2-Sb-Ni anode, with a specific doping ratio of 100:3.74:5.36, engenders a degradation efficiency of benzoic acid (BA) that approximates completeness within a constrained temporal framework of 60 minutes. The RF regression model, exemplifying a robust R² value of 0.9565 and an RMSE of 0.0576, surpasses its counterparts in prognostication accuracy, underscoring its preeminence in electrode composition optimization for the amelioration of electrochemical water treatment matrices. The convergence of SA, DE, and RF methodologies not only refines the predictive fidelity of the degradation kinetics but also extricates the optimization process from the conventional constraints, thereby enhancing the scalability and precision of the model. This research advances the frontiers of electrochemical oxidation and etches a pioneering niche for the amalgamation of machine learning within environmental engineering paradigms. The hybrid algorithmic scaffolding proffered herein is suggested as a robust and versatile framework, propelling forward the discourse on the remediation of polluted water bodies and offering a springboard for future investigative endeavors.

Numerical Simulation of the Solute Migration Regulated by Vertical Cutoff Wall based on FEFLOW

Cutoff wall has been widely used in desalination of coastal aquifers in many coastal regions and remediation of industrial waste water pollution. In recent years, the excessive exploitation of resources in the coastal brine distribution area leads to the salinization of deep soil. At the same time, the mine water pollution caused by improper discharge of industrial waste water into the abandoned mining area is a new form of pollution in Shandong, China. However, due to the complex geological conditions of abandoned mining areas, loose collapse of overlying strata in roadway and gob layer, it is difficult to prevent and control groundwater pollution in deep gob layer. It is a major difficulty in practical engineering to evaluate the cutoff interception performance of vertical cutoff wall on the pollution of gob layer in such mining areas and optimize cutoff interception measures. In this paper, a typical polluted abandoned mining area in Shandong, China is taken as an example, and COD is used as the main simulation factor for numerical simulation. The numerical simulation results show that in the process of groundwater pollution control, the cutoff wall with appropriate thickness and hydraulic conductivity can effectively block the diffusion of solute. The horizontal transport of solute can be significantly weakened when the thickness of the cutoff wall is 90 cm and the hydraulic conductivity is 1.0×10-4 m/d. Compared with increasing the thickness, reducing the hydraulic conductivity of the cutoff wall is more effective in controlling the migration of solute in the site. When the hydraulic conductivity is reduced by an order of magnitude, the diffusion range of solute is reduced by 19.74% compared to before. Therefore, priority should be given to reducing the hydraulic conductivity of the cutoff wall in order to optimize its influence on pollutant migration.

Supercritical CO2 extrusion foaming of highly open-cell poly(lactic acid) foam with superior oil adsorption performance

Addressing marine oil spills and industrial water pollution necessitates the development of eco-efficient oil-absorbing materials. With increasing concern for the environment, there is a consensus to decrease the use of petroleum-based polymers. Herein, lightweight poly(lactic acid) (PLA) blend foams with varying thermoplastic polyurethane (TPU) content were fabricated via a solvent-free, eco-friendly supercritical carbon dioxide (scCO2) extrusion foaming technology. The incorporation of TPU significantly enhanced the crystallization rate of PLA, with the semi-crystallization time of PT30 and PT50 blends at 105 °C exhibiting a reduction of 77.2 % and 47.9 %, respectively, compared to neat PLA. The resulting foams exhibited an open-cell structure with excellent selective oil adsorption capabilities. Notably, the PT30 foam achieved a remarkable maximum expansion ratio of 36.0, while the PT50 foam attained the highest open-cell content of 96.2 %. The PT50 foam demonstrated an outstanding adsorption capacity, spanning from 4.7 to 18.8 g/g for diverse oils and solvents, with rapid adsorption kinetics, reaching 94.9 % of the equilibrium adsorption capacity for CCl4 within just 1 min. Furthermore, the PT50 foam retained 95.2 % of its adsorption capacity for CCl4 over 10 adsorption-desorption cycles. This study presents a scalable and sustainable approach for large-scale production of high-performance, bio-based foams, facilitating efficient oil-water separation.

Zeolite prepared from high-calcium ladle furnace slag and fly ash for Pb2+ removal

The stockpiling of industrial solid waste and lead (Pb) pollution have become a worldwide problem, which can be potentially solved by using solid waste such as ladle furnace slag (LFS) and fly ash (FA) to prepare Pb adsorbents. In this paper, zeolites prepared from untreated high-calcium LFS and FA were used to remove Pb2+ by adsorption. The optimal adsorption conditions were an adsorbent dose of 1 g/L, pH 5, a contact time of 180 min, and an initial Pb2+ concentration of 300 mg/L. The zeolites prepared from high-calcium solid waste had a Pb2+ adsorption capacity of 292.8 mg/g and an adsorption efficiency of 97.6 %. Adsorption mainly occurred via the ion exchange of Pb2+ with Ca2+ and Na+, as well as the complexation of Pb2+. The pseudo-second-order kinetic model and the Langmuir model were used to analyze adsorption kinetics and isotherm data, supporting the occurrence of chemisorption and monolayer adsorption. Regeneration experiments demonstrated that the zeolite synthesized in this study exhibited good repeatability and cost-effectiveness. The zeolites derived from LFS and FA-based geopolymers removed Pb2+ from wastewater, offering new perspectives on utilizing high-calcium industrial waste and advancing geopolymer-based adsorbents for sustainable industrial solid waste management and water pollution treatment strategies.

Unlocking solutions for cleaner waters: The Industrial Wastewater Quality Index in Egypt and beyond

AbstractThis research study conducted in Egypt focuses on addressing the issue of industrial water pollution and promoting sustainable water and environmental management practices. The study introduces a novel tool called the Industrial Wastewater Quality Index (IWQI) and utilizes two assessment methods to evaluate the extent of water pollution caused by industrial effluents. The IWQI takes into consideration both the environmental limits specified by Egyptian legislation and industry‐specific parameters, effectively condensing extensive water quality data into simplified categories. The IWQI model proves to be a dependable instrument for assessing the overall quality of groundwater intended for industrial use. It incorporates multiple water quality indices and employs multivariate statistical analysis techniques to determine the contribution of each parameter to industrial water quality. This comprehensive analysis enhances the reliability of the model, making it a valuable point of reference for similar locations worldwide, particularly those sharing similar climatic conditions. The outcomes of this study provide valuable insights for policymakers and stakeholders involved in regulating and mitigating industrial water pollution in Egypt. The findings also have relevance to other countries facing similar challenges, highlighting the importance of developing effective techniques for investigating pollution sources, monitoring water quality, and forecasting future trends. The study underscores the necessity of implementing proactive measures to address industrial water pollution and protect water resources and ecosystems. By emphasizing these aspects, the study emphasizes the importance of promoting sustainable water and environmental management practices. Overall, the IWQI and the study's findings contribute to the development of strategies to manage and control industrial water pollution and can guide policymakers and stakeholders in Egypt and other countries facing similar challenges.

Biotechnological Approach to Treat Textile Dyeing Effluents: A Critical Review Analysing the Practical Applications

Although the textile industry is one of the significant contributors to the global economy, approximately 10% of the annual global dye production, amounting to 7 × 106 tonnes and spanning a spectrum of 10,000 different dye variants, is wasted in the dyeing process and subsequently released into the environment. Following the dyeing and processing stages, this waste contributes to environmental pollution, making the textile industry account for 20% of the overall industrial water pollution worldwide. Traditional treatment of effluents is burdensome for the majority of textile units that are micro-scale enterprises. A significant challenge is that there isn't a single, commercially viable way to efficiently treat wastewater from textile industries. Scholars from several disciplines are working together to investigate novel approaches that are assiduously directed at addressing environmental issues by minimising waste, thereby promoting sustainability, circular economy, and industrial symbiosis. This study aims to address the challenges associated with the treatment process of textile dye-related effluents by conducting a comprehensive analysis of recent research on treatment processes and advancements and exploration of biotechnological treatment methods that are focused on achieving the reuse of treated water. The review covers different processes, traditional, current and emerging techniques, and it emphasises their use in practical situations. Also, the efficiency, specificity, and environmental friendliness of different biotechnological approaches are discussed offering a comparison of their benefits and drawbacks. A holistic remediation approach is advocated by harmonizing both conventional and non-conventional treatment methods for a more comprehensive solution.

The driving factors and spatial evolution of industrial water pollution governance efficiency in the Yangtze River Delta urban agglomeration in China.

In order to explore the effective path to improve the efficiency of industrial water pollution governance efficiency (WGE), this study takes 27 prefecture-level cities in the Yangtze River Delta urban agglomeration in China as the research object, measures WGE through the improved SBM model, and tests the impact of WGE drivers using the spatial Durbin model (SDM). The study found that environmental pollution governance investment (EPGI) is positively correlated with WGE, and industrial agglomeration status (IAS) has inhibitory effects on the improvement of WGE. By testing IAS2, it was determined that the impact of IAS on WGE has a "U"-shaped relationship. The direct impact of EPGI on WGE is 0.5016, and the indirect impact on WGE is 0.6428; the direct impact of IAS on WGE is -0.3036, and the indirect impact on WGE is -0.5158. Among the other tested impact drivers, per capita GDP (PCG), industrial structure (IS), and level of technological innovation (TIL) are positively correlated with the dependent variable WGE, while energy consumption intensity (ECI), environmental regulation intensity (ERI), and degree of openness to foreign investment (FIR) are negatively correlated with the dependent variable WGE. In addition to the impact of the aforementioned main drivers, IAS and EPGI, these six drivers also largely influence and determine the final impact on WGE.

Plasmonic photocatalytic nanocomposite of in-situ synthesized MnO2 nanoparticles on cellulosic fabric with structural color

The textile industry produces 20 % of the industrial water pollution containing toxic substances mostly dyes. Reducing material consumption and developing more efficient and scalable textile waste-water treatment methods such as photocatalytic degradation is essential. In this work, manganese dioxide nanoparticles (MnO2 NPs) were synthesized on the cotton fabric via a facile in-situ process. The preparation process was optimized for the highest photocatalytic activity under sunlight and color change originating from the plasmonic structural color of the nanoparticles. This promotes the photocatalytic activity by delocalization of the hot electrons while demonstrating the best washing and light fastness by using the least chemicals, and energy in a short time. In this way, the fabric was colored without any dye and possessed robust photocatalytic activity. Further, no dye-containing waste-water is made, and also accomplished to degrade dyes in a few hours under sunlight which is substantial for sustainable development. The treated fabrics indicated favorable mechanical properties, enhanced thermal stability, and perfect biocompatibility.

Removal of Reactive Black 5 from simulated textile effluents by an electrocoagulation process: optimization by response surface methodology

Abstract The textile industry creates one-fifth of the world's industrial water pollution, thus, the electrocoagulation (EC) process was proposed and investigated as an alternative eco-friendly treatment for water reuse. This study aimed to assess the removal efficiency of the Reactive Black 5 (RB5) from synthetic textile effluent by EC. Key operating parameters on EC process efficiency were optimized using response surface methodology (RSM). The main independent variables studied were the current density, EC time, concentration, and pH while the RB5 dye removal was studied as the dependent variable. The range of the studied parameters affecting the EC process ranged from 10 to 60 mA/cm2, 5 to 30 min, 4 to 10 pH and 10 to 40 ppm for current density, EC time, pH, and RB5 concentration, respectively. The optimal operating parameters turned out to be 5.5 pH, 47.5 mA/cm2, 23.75 min, 17.5 ppm, and the predicted RB5 dye removal was 96.33%. The experimental dye removal with optimum operating conditions was in good agreement with the predicted removal efficiency. Therefore, the experiment results revealed the high potential of the EC process to effectively treat textile industry effluents and the RB5 dye removal was successfully optimized using Response Surface Methodology (RSM).

Employment of polyacrylic acid beads in treatment of industrial water pollution with Pb (II) ions

The current study deals with the removal of Lead ions from its aqueous solution by using polyacrylic acid beads. The process variables have been studied where time of contact, pH of solution, temperature, initial concentration. The adsorption capacity reached a maximum value of 565 mg/gm. after 24 hours. The study proved the applicability of pseudo first order of Langmuir model comparing with Frundlich model using the same conditions. The adsorption isotherms correspond well with shape (S) and by Giles isotherms. The thermodynamic study showed that the adsorption is endothermic process from positive value of ΔHo , while the positive value of entropy refers to the increased regularity of adsorption.

Spatial correlation and coupling between industrial enterprise agglomeration and water pollutant discharge

Industrial wastewater discharge has become the main cause of water pollution in China. However, the spatial interaction mechanism between industrial structure and water pollution is still unclear. Accordingly, we evaluated and analyzed spatiotemporal changes of the agglomeration pattern of pollution-intensive industrial enterprises and the evolution of the water environmental pollution pattern, as well as the correlation between them. The study results show that the polluting industrial enterprises were located mainly along the Yangtze River and Taihu Lake Basin in southern Jiangsu in 2013 and 2018. However, we observed a spatial trend of pollution transfer to northern Jiangsu. The industrial water pollution discharge presents the distribution pattern of facing rivers, seas, lakes and cities. Papermaking and paper products industry are the leading factors of COD and NH3–N pollution, with explanatory power of 0.3666 and 0.6201 respectively. The spatial positive coupling effect between the concentration degree of polluting enterprises and the intensity of water environment pollution discharge is 94.95% of the region. The spatial agglomeration of polluting industrial enterprises is an important cause of water environment pollution. They promote and couple each other, proving the existence of “Pollution haven” and “Porter hypothesis".

Textile Waste Recycling: A Need for a Stringent Paradigm Shift

Despite the fact that textile waste is almost entirely recyclable, approximately 75% of it ends up in landfills worldwide. This has serious environmental and economic consequences. This review focuses on textile waste statistics, its contribution to pollution and recycling, as well as the benefits, barriers, types, and technologies of textile waste recycling. Textile production and textile waste generation have increased alarmingly as a result of fast fashion, which emphasizes low-cost production, frequent consumption, and short-term use of garments. This industry is distinguished by scarcity of resources, excessive consumption, and the generation of large amounts of waste. The frequency of consumer purchases is increasing, while the life span of clothing is drastically decreasing. Recycling does not occur as expected for a variety of reasons, so the environmental impact and economic losses from this waste grow over time. The textile industry currently contributes about 8% of the global carbon budget and 20% of industrial water pollution. Every year, $500 billion is lost to the system due to unused clothing and a lack of recycling. A paradigm shift is urgently required to implement an effective textile waste recycling system.