Industrial Waste Discharge Research Articles

Source apportionment, source-specific health risks, and control factors of heavy metals in water bodies of a typical karst basin in southwestern China.

Studying the apportionment of source-specific health risks and control factors for heavy metal pollution in karst regions is crucial for prevention and management. A typical karst basin was chosen in this study to investigate the pollution characteristics of heavy metals, source-specific health risks, and control factors. The results indicate that during the rainy season, As, Cd, and Pb, as well as As during the dry season, were the primary elements responsible for water pollution in the watershed. Comparative analyses showed that the absolute principal component-multiple linear regression (APCS-MLR) model better identifies and quantifies the sources of heavy metals in karst basin waters. The analysis of health risks revealed that during the dry season, heavy metals in the basin posed a moderate cancer risk to adults (10-4 < total cancer risk (TCR) < 10-3), whereas during the rainy season, these heavy metals posed a non-cancer risk (total hazard index (THI) > 1) and a moderate to high cancer risk (10-4 < TCR < 10-2). The APCS-MLR model combined with the health risk analysis showed that Industrial waste discharge sources are the main contributors to the health of basin residents (29.39%-52.57%), making dry season As a non-cancer risk for basin residents, as well as rainy season As and Cd a non-cancer risk and a high cancer risk for basin residents. Therefore, reasonable planning for upstream industrial production should be developed, and priority should be given to monitoring and treating As and Cd pollution in water. Analyses also showed that input pathways, dilution effects, and hydrochemical characteristics may influence the spatial and temporal variability of heavy metals in the basin. The results provide essential information and significant reference for prioritising and managing the health risks associated with heavy metal pollution in water bodies in karst areas.

Assessment of Environmental Pollution in Mahadev Khola, Tarakeshwor Municipality

One of the Small tributaries of the Bishnumati River is Mahadev Khola. It originates from Ale Danda, and downstream, it gets mixed with the Bishnumati River flowing from Tokha. It is 8.9 km in length and its elevation is 2000. The river's physio-chemical and biological characteristics were analyzed to know the river's pollution status. Primary data were collected from field observation and water sample analysis tests, and the secondary data were collected from the Tarkeshwor Municipality. Data analysis was done through MS-Excel. pH, ammonia, phosphate, chloride, hardness, iron, BOD5, and conductivity increase from upstream to downstream, whereas DO decreases. Temperature, turbidity, TS, TSS, and TDS were higher at the middle point than the other two, and coliform was found in the middle and exit points. Among the three segments of the river, the quality of the source point was good in terms of standards for drinking water. The middle and exit points were in medium and lousy condition, respectively.The principal causes of deteriorating water quality in Mahadev Khola are mainly the free and direct discharges of household and industrial wastes into the river and excessive mining of sand from the river bed. Since the quality of the river is deteriorating day by day, it’s the responsibility of the local government and the people to take immediate action for its conservation.

Potential of ash from agricultural waste as substitute of commercial FeCl3 in primary treatment of landfill leachate

Due to the ever increasing global population, higher volumes of industrial waste discharges to landfill have caused major problems for the environment. This study investigated the performance of rice straw ash (RSA) as a natural coagulant under different conditions for the treatment of landfill leachates by coagulation-flocculation and microfiltration, with and without addition of FeCl3. The highest performing treatment conditions (RSA = 2.48 g/L, FeCl3 = 4.98 g/L, settling time = 54.75min) were achieved with the combined use of RSA and FeCl3 as coagulant and led to a sludge volume index of 41.65 mL/g, 51.27% COD removal and 76.48% total suspended solid removal. In contrast, FeCl3 alone achieved slightly better COD and total suspended solid removal rates, however it resulted in higher sludge volume index and sludge production. The combined use of RSA and FeCl3 reduced the consumption of these two coagulants by 78.76% and 46.69% respectively. Functional groups and thermal stability of the flocs showed that RSA + FeCl3 synergistically enhance the mechanisms of the coagulation-flocculation process, including adsorption by particle's bridging, charge neutralization and size of flocs. Combining the coagulants resulted in increased van der Waals forces and lower attractive forces of the inter-colloidal energy barrier in the leachate. Additionally, the highest and lowest heavy metals removal rates for treatment by microfiltration were found for Fe (92.15%) and Mg (7.63%), with a total heavy metals removal efficiency in the range of 6.08–90.78%. The findings of this study show that RSA can serve as a natural eco-friendly coagulant both alone and in combination with FeCl3 in the leachate treatment.

Biosorption potential of Purpureocillium lilacinum biomass for chromium (VI) removal: isolation, characterization, and significance of growth limiting factors

Chromium (VI) is known to be harmful element that commonly found industrial waste, mining activities, and wastewater discharges from various industries. When released into the environment, Cr (VI) can contaminate soil, water, and air, posing a serious threat to living organisms. Aiming to Cr decontamination, this work was framed to isolate the fungal species having high Cr tolerance capacity and to exploit as bio-sorbent for the removal of Cr (VI) from aqueous solutions by biosorption. Among the fungal species isolated from the Cr (VI) contaminated soil sample, the filamentous fungus of Ophiocordycipitaceae family, Purpureocillium lilacinum was identified using molecular sequencing technique, showed maximum tolerance against Cr (VI) with a tolerance index of 1.19 ± 0.23. Further, Plackett Burman Design was applied to investigate for ascertaining the significance of different carbon and nitrogen sources on P. lilacinus growth, as well as the influence of environmental factors, such as pH, temperature, and Cr (VI) concentration. The results explicated that glucose was the most preferred carbon source for P. lilacinus, while yeast extract was the most preferred for nitrogen source. The optimum pH value and temperature were found to be 6.0 and 26 °C, respectively. In addition, P. lilacinus isolate was identified to survive in high concentrations of Cr (VI), indicating its potential for employing effective bioremediation of chromium-contaminated site.

Characteristics of Zinc Adsorption onto Biochars Derived from Different Feedstocks

Human activities such as the discharge of urban sewage, garbage, and industrial waste have seriously affected the quality of groundwater sources for human consumption. The potential for using biochar as a reactive medium in a permeable reactive barrier (PRB) was explored for Zn-contaminated groundwater treatment in this study. Four different types of biochar produced from wood, coconut shell, rice straw, and fruit shell were used. The production temperature of these biochars were 600 °C, 550 °C, 500 °C, and 500 °C, respectively. The samples were coded with the initials of the biochar source and the production temperature as WD600, CS550, RS500, and FS500. The results of various batch adsorption studies show that equilibrium solution pH has a great effect on the maximum adsorption capacity in the pH range of 2–7. The adsorption of Zn on biochars follows the Freundlich model and fits well with the pseudo-second-order model. The fixed-bed column test data were well fitted to the Dose–Response model. The adsorption capacities of WD600, CS550, RS500, and FS500 were 24.91, 15.87, 9.25, and 46.71 mg/g, respectively. The removal rate of FS500 can reach a maximum of 98.87%. FS500 is considered to be a potential reaction medium for treating Zn-contaminated groundwater in a PRB system. This work provides a new option for converting biomass waste into an adsorbent for zinc in wastewater. The results of this study are expected to provide a solid theoretical basis for the further application of biochar in groundwater pollution remediation.

Investigating the Impact of Environmental Toxicology of Heavy Metals in Fish: A Study of Rivers of Pakistan

The global concern of heavy metal toxicity has affected all nations, as the discharge of agricultural runoff and untreated industrial waste into water bodies, including rivers, leads to environmental toxicology. This increased level of heavy metals poses risks not only for marine life but also to those who consume them. While fish is an important protein source, consuming contaminated fish containing high levels of heavy metals can have severe adverse effects on human health. Therefore, it is crucial to address these pollution sources effectively in Pakistan, where a significant portion of the population relies on agriculture and fishing for their living. The country's rapid industrialization and urbanization have substantially increased pollutants in its rivers and other water bodies. The current body of research has indicated that the elevated levels of heavy metals in the ecosystem, including the Indus River, pose a significant threat to the local ecosystem and the well-being of marine life. Heavy metal pollution in Pakistani rivers originates from multiple sources, such as industrial effluents, agricultural runoff, and municipal waste. The unregulated discharge of industrial waste into rivers is a major contributor to heavy metal pollution in Pakistani rivers. Moreover, the excessive and uncontrolled use of fertilizers and pesticides in agriculture equally contributes to the contamination of rivers with heavy metals. The current study is a review article, which provides a comprehensive explanation of how environmental toxicology affects the ecosystem, especially concerning the rivers of Pakistan.

Intelligent learning algorithms integrated with feature engineering for sustainable groundwater salinization modelling: Eastern Province of Saudi Arabia

Groundwater (GW) salinization refers to the natural or human-induced process of GW acquiring a higher level of salt content. While geological factors or proximity to the ocean can naturally cause this phenomenon, it can also be attributed to activities like irrigation, changes in land use, and the discharge of industrial or municipal waste. The following research employs the use of various feature extraction methods coupled with novel chemometrics approaches informed by machine learning (ML) techniques including; Gaussian Process Regression (GPR), Support Vector Regression (SVR), Regression tree (RT) and Robust linear regression (RLR). Based on the feature selection methods, the models were classified into three different combinations. The intelligent learning algorithms equally depict higher PCC values ranging from 0.935 to 1.00 in the training and 0.779 to 0.999 in the validation stage respectively, which depicts a higher relation between the experimental and simulated values. The performance results indicate that GPR-Comb-3 showed the highest performance in both the training and validation stages respectively. It is worth mentioning that even the RLR technique equally depicts exceptional prediction skills in both the training and validation steps. In conclusion, the outcomes of the current research depict the significance of these techniques in evaluating GW salinization.

Phycoremediation potential and agar yield of red macroalgae (Gracilaria corticata) against HEDP (hydroxyethylidene diphosphonic acid) and CAPB (cocoamidopropyl betaine) detergents and the heavy metal pollutants.

The discharge of raw industrial, agricultural, and domestic wastes leads to an increase in heavy metal (HM) burden and detergents in aquatic environs, which can have destructive effects on aquatic organisms. Agarophyte Gracilaria corticata, a major component of seaweed flora of the southern coast of Iran (Bushehr) that contains agar and red pigments, is one of the economically valuable red marine algae. Agar is one of the important polysaccharides with high economic value, widely used in pharmaceutical, medicinal, and cosmetic product manufacturing industries. The aim of this work was to investigate the effect of 5 HMs and two common surfactants in household and industrial detergents on the agar yield, appearance color, and the red algae's phycoremediation potential against HMs. The metal ions were Zn(II), Cu(II), Ni(II), Mn(II), and Cr(VI), and the surfactants were HEDP and CAPB. The analysis results of samples cultured for 60 days in seawater and polluted environments showed that G. corticata can accumulate copper and nickel. In the presence of detergents without HMs, the amount of extracted agar significantly increased compared to the control sample with no change in algae color. But with increasing concentration of HMs, the amount of agar in seaweed samples decreased significantly, and the algae discolored from red to dark green or yellowish-green color (signs of death in the algae). These results show that increasing of HM pollution and detergents can lead to toxicological effects and reduce the species diversity of red seaweeds in the future.

Internal Defense System of Mytilus galloprovincialis (Lamarck, 1819): Ecological Role of Hemocytes as Biomarkers for Thiacloprid and Benzo[a]Pyrene Pollution.

The introduction of pollutants, such as thiacloprid and benzo[a]pyrene (B[a]P), into the waters of urbanized coastal and estuarine areas through fossil fuel spills, domestic and industrial waste discharges, atmospheric inputs, and continental runoff poses a major threat to the fauna and flora of the aquatic environment and can have a significant impact on the internal defense system of invertebrates such as mussels. Using monoclonal and polyclonal anti-Toll-like receptor 2 (TLR2) and anti-inducible nitric oxide synthetase (iNOS) antibodies for the first time, this work aims to examine hemocytes in the mantle and gills of M. galloprovincialis as biomarkers of thiacloprid and B[a]P pollution and analyze their potential synergistic effect. To pursue this objective, samples were exposed to the pollutants, both individually and simultaneously. Subsequently, oxidative stress biomarkers were evaluated by enzymatic analysis, while tissue changes and the number of hemocytes in the different contaminated groups were assessed via histomorphological and immunohistochemical analyses. Our findings revealed that in comparison to a single exposure, the two pollutants together significantly elevated oxidative stress. Moreover, our data may potentially enhance knowledge on how TLR2 and iNOS work as part of the internal defense system of bivalves. This would help in creating new technologies and strategies, such as biosensors, that are more suitable for managing water pollution, and garnering new details on the condition of the marine ecosystem.

Acute exposure of Cr and Cu induces oxidative stress, genotoxicity and histopathological alterations in snakehead fish Channa punctatus

Aim: This study aimed to investigate the oxidative stress, genotoxicity and histopathology after sub-lethal exposure of chromium (Cr6+) and copper (Cu+2) to common food fish Channa punctatus. Metal exposure to fishes of River Ganga is a very common phenomenon due to their ubiquitous nature and through discharge of domestic and industrial waste into the river water. Methodology: An in-vitro experiment was performed to study ill effects of metallic stressors on fish. Fishes were divided into seven groups. Group I served as control, Group II, III, IV as 1/20th ,1/10th and 1/5th of 96 hr-LC50 of Cr6+. Group V, VI and VII were similarly treated with Cu at 1/20th, 1/10th and 1/5th of 96 hr LC50 of Cu+2, respectively. All the treatments were done for 15, 30 and 45 days of exposure period. Genotoxicity was evaluated by micronuclei (MN) induction. Enzymatic and non-enzymatic oxidative stress markers, including reactive oxygen species (ROS), superoxide dismutase (SOD), catalase (CAT), glutathione (GSH), glutathione reductase (GR), and glutathione peroxidase (GPx) were evaluated. Histopathological studies of liver and kidney tissue were also performed. Results: Stress biomarkers were more profound in fishes of chromium treated groups in comparison to copper. Particularly, SOD and CAT showed a significant hike in the activity levels. ROS levels in blood cells increased significantly (p &lt; 0.05) in all the treated groups (Group II, III, and IV) in a dose dependent manner as compared with control (Group I). There was significant induction in micronuclei (MN) frequency in all the treated groups for both the metals. The highest frequency of MN induction was recorded in Group IV after 96 hr of the exposure period.Significant histological alterations were observed in liver and kidney of treated fish, changes were more pronounced in chromium treated fish than copper. Interpretation: Acute exposure of chromium and copper induces ROS and generates oxidative stress mediated genotoxicity and histopathological perturbations in the prime organs of fish.Cr and Cu induces the changes in the production and accumulation of enzymatic antioxidant system for the regulation and scavenging of ROS induced by Cr and Cu. Key words: Channa punctatus, Genotoxicity, Histology, Heavy metals, Micronuclei, Oxidative stress

Coal gasification fine slag based multifunctional nanoporous silica microspheres for synergistic adsorption of Pb(II) and Congo red

The discharge of large-scale industrial solid waste and wastewater has caused severe damage to environmental health. In this study, the adsorption behaviors of Pb(II) and Congo Red (CR) dye in single and binary aqueous systems were investigated using novel functionalized nanoporous glass microspheres (NGM). The NGM material was fabricated from coal gasification fine slag (CGFS) by a simple treatment and characterized using TG, BET, XRD, TEM, FT-IR, and XPS to analyze its physicochemical properties. The adsorption experiments showed that the adsorption amounts of DMA-NGM for Pb(II) and CR were 302.39 mg/g and 342.74 mg/g for the single systems, and 372.73 mg/g and 412.93 mg/g for the binary systems, respectively. The increased adsorption capacity was attributed to the synergistic effect of electrostatic attraction and chelation. Furthermore, the pseudo-second-order model and Elovich model could reasonably describe the adsorption of Pb(II) and CR on DMA-NGM. Pb(II) adsorption on DMA-NGM was monolayer adsorption and CR adsorption was multilayer adsorption. In summary, the results demonstrate the potential of efficient and environmentally friendly adsorbents for the resource recovery of CGFS and the processing of printing and dyeing wastewater.

Multi-benthic size approach to unveil different environmental conditions in a Mediterranean harbor area (Ancona, Adriatic Sea, Italy).

Harbors are hubs of human activity and are subject to the continuous discharge and release of industrial, agricultural, and municipal waste and contaminants. Benthic organisms are largely known to reflect environmental conditions they live in. Despite meio- and macrofauna interacting within the benthic system, they are ecologically distinct components of the benthos and as such may not necessarily respond to environmental conditions and/or disturbances in the same way. However, in a few field studies the spatial patterns of meio- and macrofauna have been simultaneously compared. In the present study, we assess the response and patterns in the abundance, diversity, and distribution of the two benthic size classes to the different environmental conditions they live in (i.e., sediment concentrations of selected trace metals and polycyclic aromatic hydrocarbons (PAHs); organic matter contents and grain size) characterizing the Ancona Harbor (Adriatic Sea). Meio- and macrofauna provided partially similar types of information depending on the indices used (univariate measures or community structure/species composition) and the different 'response-to-stress'. The community structure (i.e., taxa composition) of both benthic size components clearly showed differences among sampling stations located from inside to outside the harbor, reflecting the marked environmental heterogeneity and disturbance typically characterizing these systems. Notwithstanding, the univariate measures (i.e., meio- and macrofauna total abundance, diversity indices and equitability) didn't show similar spatial patterns. Meiofauna were likely to be more sensitive to the effects of environmental features and contaminants than macrofauna. Overall, trace metals and PAHs affected the community composition of the two benthic components, but only the meiofauna abundance and diversity were related to the environmental variables considered (i.e., quantity and quality of organic matter). Our results pinpoint the importance of studying both meio- and macrofauna communities, which could provide greater insight into the processes affecting the investigated area and reveal different aspects of the benthic ecosystems in response to harbor conditions.

Effect of Barrages and Anthropogenic Activities on Ecological Integrity of the Ganga River: A Review on Current Issues and Restoration Efforts

The Ganga River, a lifeline for millions of people in the Indian subcontinent, is facing significant environmental challenges due to the construction of barrages and various anthropogenic activities along its course. This review paper examines the effects of barrages and human interventions on the ecological integrity of the Ganga and explores current issues surrounding its deteriorating ecosystem. Furthermore, it discusses the restoration efforts undertaken to mitigate the ecological impacts and restore the river's health. The construction of dams and barrages can aggravate the situation in the context of the Ganga, which is already suffering from the discharge of industrial and agricultural wastes. The construction of various dams, barrages, and hydroelectric projects is affecting the water flow of the Ganga. These affect the water flow, resulting in the accumulation of solid waste on the river bed. Barrages not only affect the water flow but also restrict the migration of aquatic fauna. This affects the hydrological balance of the Ganga as well as the survival and existence of several fish species. This review provides a comprehensive analysis of the effects of barrages and anthropogenic activities on Ganga's ecological integrity, sheds light on the current issues plaguing the river, and highlights the ongoing restoration efforts. By understanding the complex interplay between human activities and ecosystem dynamics, stakeholders can work towards safeguarding Ganga's ecological health and ensuring its sustainable future.

Life cycle assessment of a typical lead smelting process in China

The production of lead smelting in China has led to dangerous environmental contamination, which poses a continuous threat to human health and the ecosystem. To evaluate the specific environmental effects of lead smelting, a life cycle assessment (LCA) was conducted using Simapro 9.0 software in this study. A typical industrial area dominated by the lead smelting industry was chosen as the field data source, and more than 90% of the lead escape routes were found to produce water-quenched slag and zinc hypoxide during fuming. Furthermore, this work clarified the fates of the associated element elements and the key nodes of pollution. In addition, the ReCiPe H method was used to calculate normalized results with uncertainty information, revealing that marine ecotoxicity had the most significant impact, followed sequentially by freshwater ecotoxicity, human toxicity, human noncarcinogenicity, and terrestrial ecotoxicity. The processing plant played a significant role in environmental contamination according to a contribution analysis. Specifically, the purchased crude lead and the concentrated crude lead should be given close attention because they made the largest contributions to the pollution of each environment. According to a sensitivity analysis, improving the smelting efficiencies of heavy metals during smelting and reducing the direct discharge of industrial waste could effectively solve environmental problems.

Biological Assessment of Anthropogenic Impacts in Buguma Creek, Rivers State, Nigeria

The objective of this research was to assess the anthropogenic impact on plankton and macrobenthic fauna composition, abundance, distribution, and diversity of four communities in Buguma creek. The Phytoplankton, zooplankton, and benthic fauna samples were collected quantitatively monthly from each of the four sampling stations between January and June 2020 using standard sampling methods. Margalef (D), Shannon Wienner (H), and Evenness indices were used to determine species richness and diversity respectively using the PAST statistical package. This study revealed that artisanal refinery activities, sand mining/dredging, and discharge of industrial, domestic, human, and animal wastes have adversely affected the aquatic biota (plankton and macrobenthic fauna) in Buguma creek. The effects of these activities have remarkable spatial manifestations; with the more perturbed especially station 2, having a lower number of species and abundance. The preponderance of indicator species is a confirmation while the community structure gave an insight into the negative impact of these activities individually and cumulatively. The brunt of these activities rests more on the macrobenthic fauna; probably due to their unique characteristics and position in the aquatic environment. The result indicated that Buguma creek had been polluted seriously to a large extent. Keywords: Aquatic biota, Bioindicator, Anthropogenic, Artisanal refinery, Diversity

Neural Network Analysis as a Base of the Future System of Water–Environmental Regulation

The article considers neural-network methods and technologies, which are relatively new even for many researchers and experts, as applied to water–environmental regulation. The efficiency of neural networks in this line of studies is due to their self-training, and the ensuing ability to reveal complex nonlinear relationships between the characteristics under control by data processing instruments, consisting of interrelated neurons. The methodology of artificial neural networks and the features of their functioning are described. Training and methodological examples are given to illustrate their potential use. A practical problem, considered as an example of ANN application, is the potential for improving the efficiency of identification of large enterprises polluting natural water among many water users in an industrial region. This is made with the use of data on the concentrations of some priority water-polluting metals at the hydrochemical gages in the Iset river near Ekaterinburg City. The neural-network analysis is shown to detect relationships between individual water quality characteristics at nearby gages. This allowed the conclusion that there exist close logistic economic relationships between water users, which help revealing water pollutants by the water footprint produced by plants working in the same branch. It is also shown that the use of ANN opens new ways for determining the contribution of industrial waste discharges to the level of water pollution by substances of dual genesis (natural and technogenic). The reliability of the conclusions is confirmed by the possibility to use the data on a given hydrochemical gage to satisfactorily predict water quality at a gage further downstream.

Evaluating the influence of environmental variables on fish abundance and distribution in the Singhiya River of Morang District, eastern Nepal

Monitoring the impact of fishing pressure on the Singhiya River is critical for resource development and sustainability, and the present situation is alarming and causing critical concern among the public. This study aimed to identify fish community trends over time and space in the river, and to investigate the impact of environmental variables on fish abundance and dispersion. Monthly fish sampling was performed from October 2020 to September 2021 from the 5th to 10th of each month. We used three cast nets of various mesh sizes (0.5, 2, &amp; 4 cm) and monofilament gill nets with mesh sizes of 6, 8, &amp; 10 cm. A total of 7,593 fish were collected, representing 61 species from seven orders, 20 families, and 37 genera. Similarity percentage (SIMPER) analysis revealed 78.8% similarity among six stations, with the primary contributing species: Puntius chola (28.2%), Puntius sophore (13.5%), Pethia ticto (5.33%), Chagunius chagunio (3.76%), Barbonymus gonionotus (3.69%), Puntius terio (3.46%), Opsarius shacra (2.2%), and Opsarius bendelisis (2.1%). Analysis of variance (ANOVA) on canonical correspondence analysis revealed that four of the seven selected environmental variables had significant relationship with the fish assemblage such as water parameters velocity, temperature, pH, and hardness. Overfishing and direct discharge of industrial waste into water resources may be the primary causes for the decline in fish diversity in Singhiya River.

Neural Network Analysis as a Base of the Future System of Water–Environmental Regulation

The article considers neural-network methods and technologies, which are relatively new even for many researchers and experts, as applied to water–environmental regulation. The efficiency of neural networks in this line of studies is due to their self-training, and the ensuing ability to reveal complex nonlinear relationships between the characteristics under control by data processing instruments, consisting of interrelated neurons. The methodology of artificial neural networks and the features of their functioning are described. Training and methodological examples are given to illustrate their potential use. A practical problem, considered as an example of ANN application, is the potential for improving the efficiency of identification of large enterprises polluting natural water among many water users in an industrial region. This is made with the use of data on the concentrations of some priority water-polluting metals at the hydrochemical gages in the Iset river near Ekaterinburg City. The neural-network analysis is shown to detect relationships between individual water quality characteristics at nearby gages. This allowed the conclusion that there exist close logistic economic relationships between water users, which help revealing water pollutants by the water footprint produced by plants working in the same branch. It is also shown that the use of ANN opens new ways for determining the contribution of industrial waste discharges to the level of water pollution by substances of dual genesis (natural and technogenic). The reliability of the conclusions is confirmed by the possibility to use the data on a given hydrochemical gage to satisfactorily predict water quality at a gage further downstream.

Seasonal assessment of heavy metal contamination of groundwater in two major dumpsites in Sierra Leone

Consumption of water contaminated with heavy metals has serious health consequences and these include hypertension, kidney disease, cancer, anaemia, brain damage, etc. However, groundwater pollution with heavy metals may occur naturally or anthropogenically as a result of water-rock interaction, dumpsite leachate, agricultural activities, or sewage percolation. Therefore, the apportionment of the specific sources of heavy metals to groundwater is vital to prevent and control its pollution to groundwater. The present work assessed thirty-four (34) groundwater samples from the vicinity of the Granvillebrook and Kingtom dumpsites, Freetown, Sierra Leone. The objective of the research was achieved by integrating geospatial, indexical, and multivariate statistical methods. The results showed that heavy metals such as Cu, Cr, Fe, and Mn exceeded the permissible levels in the majority of the groundwaters. As and Pb were below the detection level of the instrument in all the groundwaters analyzed. Seasonal variations revealed that the concentration of heavy metals is relatively higher in the dry season due to the effect of dilution. The heavy metal evaluation index and degree of contamination analyses respectively showed that 16.7 and 41.6% of the groundwaters in the Granvillebrook dumpsite are highly polluted by heavy metals. All the groundwater samples in the Kingtom dumpsites except well KW17 are unaffected by heavy metals. The principal component analysis showed that fuel combustion, brake abrasion, and discharge of municipal and industrial waste from the dumpsites are some of the anthropogenic sources that impact groundwater pollution in the study areas. The findings of this research revealed the urgent need to develop strategies to control and mitigate the occurrences of heavy metals and thus serve as a base for future research in the study areas.

Assessment of the Impact of Industrial Wastewater on the Water Quality of Rivers around the Bole Lemi Industrial Park (BLIP), Ethiopia

The discharge of industrial waste into water bodies without significant treatment can be a source of water pollution. This study was conducted to assess the impact of industrial wastewater on the water quality in rivers around the Bole Lemi Industrial Park (BLIP). Data were collected from six sampling stations in midstream, downstream, and upstream locations between May and June 2021. In situ (pH, electrical conductivity [EC], total suspended solids [TSS], and temperature) and ex situ (chemical oxygen demand [COD], total nitrogen [TN], total dissolved solids [TDS], total phosphorus [TP], and biological oxygen demand [BOD]) determinations of water quality were conducted. The quality of the water samples was examined using the weighted arithmetic water quality index (WQI) method. A statistical analysis showed that there are significant differences in the water quality parameters among the sampling stations along the river. The results showed different levels of temperature, EC, pH, TSS, TDS, COD, BOD, TN, and TP. The pH values were higher than the pH ranges (6.5–8.5) of USEPA, EU, CES, and WHO at two sampling stations. The results of the WQI showed that the analyzed water samples were in the “unsuitable for consumption” water quality category. These results will be useful for the city administration of Addis Ababa in crafting strategies for the protection and sustainable management of the Bole Lemi River.