Surface Water Pollution Research Articles

Emerging pollutant in surface water bodies: a review on monitoring, analysis, mitigation measures and removal technologies of micro-plastics.

Water bodies play a crucial role in supporting life, maintaining the environment, and preserving the ecology for the people of India. However, in recent decades, human activities have led to various alterations in aquatic environments, resulting in environmental degradation through pollution. The safety of utilizing surface water sources for drinking and other purposes has come under intense scrutiny due to rapid population growth and industrial expansion. Surface water pollution due to micro-plastics (MPs) (plastics < 5mm in size) is one of the emerging pollutants in metropolitan cities of developing countries because of its utmost resilience and synthetic nature. Recent studies on the surface water bodies (river, pond, Lake etc.) portrait the correlation between the MPs level with different parameters of pollution such as specific conductivity, total phosphate, and biological oxygen demand. Fibers represent the predominant form of MPs discovered in surface water bodies, exhibiting fluctuations across seasons. Consequently, present study prioritizes understanding the adaptation, prevalence, attributes, fluctuations, and spatial dispersion of MPs in both sediment and surface water environments. Furthermore, the study aims to identify existing gaps in the current understanding and underscore opportunities for future investigation. From the present study, it has been reported that, the concentration of MPs in the range of 0.2-45.2 items/L at the Xisha Islands in the south China sea, whereas in India it was found in the range of 96 items/L in water samples and 259 items/kg in sediment samples. This would certainly assist the urban planners in achieving sustainable development goals to mitigate the increasing amount of emergent pollutant load.

Making waves: How to clean surface water with photogranules

Global surface waters are in a bad ecological and chemical state, which has detrimental effects on entire ecosystems. To prevent further deterioration of ecosystems and ecosystem services, it is vital to minimize environmental pollution and come up with ways to keep surface water healthy and clean. Recently, photogranules have emerged as a promising platform for wastewater treatment to remove organic matter and nutrients with reduced or eliminated mechanical aeration, while also facilitating CO2 capture and production of various bioproducts. Photogranules are microbial aggregates of microalgae, cyanobacteria, and other non-phototrophic organisms that form dense spheroidic granules. Photogranules settle fast and can be easily retained in the treatment system, which allows increased amounts of water and wastewater to be treated. So far, photogranules have only been tested on various “high-strength” wastewaters but they might be an excellent choice for treatment of large volumes of polluted surface water as well. Here, we propose and tested for the first time photogranules on their effectiveness to remove nutrients from polluted surface water at unprecedented low concentrations (3.2 mg/L of nitrogen and 0.12 mg/L of phosphorous) and low hydraulic retention time (HRT = 1.5 h). Photogranules can successfully remove nitrogen (<0.6 mg/L, ∼80 % removal) and phosphorous (<0.01 mg/L, 90–95 % removal) to low levels in sequencing batch operation even without the need for pH control. Subjecting photogranules to surface water treatment conditions drastically changed their morphology. While, under “high-strength” conditions the photogranules were spherical, dense and defined, under polluted surface water conditions photogranules increased their surface area by forming fingers. However, this did not compromise their excellent settling properties. Finally, we discuss the future perspectives of photogranular technology for surface water treatment.

Causes and Impacts of Water Pollution on Various water bodies in the State of Rajasthan, India: A Review

Water quality and water resources make an impression on the social, economic and political advancement of society. With the rapid growth of urbanization and industrialization linked with economic and social needs, the pollution of water has reached a level of no return. Water is defined as harmful for human and aquatic lives when it is become contaminated by unexpected substances such as heavy metals, agricultural and industrial chemicals, hydrocarbon fuels, radioactive materials, sewage, pharmaceutical drugs, and biologic agents such as bacteria, parasites, and viruses. This water is considered polluted or contaminated (Bagul et al. 2015), The problem of water pollution becomes more hazardous in a region where availability of water is critically less like the state of Rajasthan (Coyte et al. 2019). The situation of surface water pollution in arid and semi-arid areas of state is alarming. We know that every living being needs water for their survival. All living being intake water directly or indirectly from various water resources. Intake of polluted water would be harmful for them. Transport of bio-accumulative pollutants to food chain makes the situation more grievous. So, it is the need of the hour to examine the magnitude and range of water pollution in the water bodies, especially in the state like Rajasthan. In the present scenario we can’t prevent water to being polluted totally but the scaling down of pollution is imperative. It is high time to take some steps to educate and spread awareness to the people regarding this alarming issue.

Spatial and Temporal Analysis of Surface Water Pollution Indices Using Statistical Methods

Spatial and Temporal Analysis of Surface Water Pollution Indices Using Statistical Methods

Interpretable Time Series Models for Wastewater Modeling in Combined Sewer Overflows

Climate change poses increasingly complex challenges to our society. Extreme weather events such as floods, wild fires or droughts are becoming more frequent, spontaneous and dificult to foresee or counteract. In this work we specifically address the problem of sewage water polluting surface water bodies after spilling over from rain tanks as a consequence of heavy rain events. We investigate to what extent state-of-the-art interpretable time series models can help predict such critical water level points, so that the excess can promptly be redistributed across the sewage network. Our results indicate that modern time series models can contribute to better waste water management and prevention of environmental pollution from sewer systems. All the code and experiments can be found in our repository:https://github.com/TeodorChiaburu/RIWWERTimeSeries.

Examining drinking water quality: analysis of physico-chemical properties and bacterial contamination with health implications for Shangla district, KhyberPakhtunkhwa, Pakistan.

A comprehensive understanding of water quality is essential for assessing the complex relationship between surface water and sources of pollution. Primarily, surface water pollution is linked to human and animal waste discharges. This study aimed to investigate the physico-chemical characteristics of drinking water under both dry and wet conditions, assess the extent of bacterial contamination in samples collected from various locations in District Shangla, and evaluate potential health risks associated with consuming contaminated water within local communities. For this purpose, 120 groundwater and surface water samples were randomly collected from various sources such as storage tanks, user sites, streams, ponds and rivers in the study area. The results revealed that in Bisham, lakes had the highest fecal coliform levels among seven tested sources, followed by protected wells, reservoirs, downstream sources, springs, rivers, and ditches; while in Alpuri, nearly 80% of samples from five sources contained fecal coliform bacteria. Similarly, it was observed that the turbidity level, total dissolved solids, electrical conductivity, biological oxygen demand, and dissolved oxygen in the surface drinking water sources of Bisham were significantly higher than those in the surface drinking water sources of Alpuri. Furthermore, the results showed that in the Alpuri region, 14% of the population suffers from dysentery, 27% from diarrhea, 22% from cholera, 13% from hepatitis A, and 16% and 8% from typhoid and kidney problems, respectively, while in the Bisham area, 24% of residents are affected by diarrhea, 17% by cholera and typhoid, 15% by hepatitis A, 14% by dysentery, and 13% by kidney problems. These findings underscore the urgent need for improved water quality management practices and public health interventions to mitigate the risks associated with contaminated drinking water. It is recommended to implement regular water quality monitoring programs, enhance sanitation infrastructure, and raise awareness among local communities about the importance of safe drinking water practices to safeguard public health.

Fine-resolution estimation for urban surface water pollution susceptibility with multi-modal earth observation data

The sustainability and suitability of water resources are of great importance for maintaining urban populations. The landscapes and environment around urban waters have always been the main focus of maintaining water quality for sustainable water supplies. Early-stage field investigations recognized the influence of land use/land cover (LULC) on water quality. To extend the research scope in spatial and temporal dimensions, remote sensing techniques have been utilized to discover the relationships between LULC and water quality. However, these remote sensing datasets generally had a medium spatial resolution, making them unable to support the fine-detailed land classifications that are critical to explore the water quality in an urban area. Moreover, although more details regarding the land surface are available from the currently-generated high-resolution and very-high-resolution remote sensing images, this land surface information is too complex for the state-of-the-art deep learning approaches and benchmark datasets. This manuscript reports our efforts on developing a framework to explore the fine-resolution relationship between surface water pollution and LULC. To address the cost of computing time and limitations of well-labelled datasets, we employ a foundation model-enhanced approach for water extraction and water-surrounded LULC classification. We propose an estimator of surface water pollution susceptibility to main pollutants based on the surrounding LULCs. Selecting the Future City of Beijing as the study area, based on very-high-resolution remote sensing images, the experiment proved that our proposed approach could effectively map the susceptibility of surface water pollution caused by its surrounding land use and land cover. To our knowledge, the relationship of LULCs and water quality have not been investigated using 0.5 m spatial resolution data. We hope our work can provide a prospective fine-detailed water quality analysis in the community of water environment of remote sensing.

ROOT ZONE TECHNOLOGY FOR WASTE WATER TREATMENT

In India, the primary cause of surface and ground water pollution is the discharge of untreated sewage, according to a 2007 study by the Central Pollution Control Board. In India, there is a significant delay between the generation and treatment of household wastewater. India's insufficient treatment capacity is not the only issue; there are also sewage treatment plants that exist, but they are not being maintained or operated. Because of poor design, inadequate maintenance, unreliable electricity supplies, absentee staff, and incompetent management, the majority of government-owned sewage treatment plants remain closed for the most part of the year. Usually, the wastewater produced in these places evaporates or percolates into the soil. Uncollected waste builds up in urban areas, releasing pollutants that seep into surface and groundwater and creating unsanitary conditions. Furthermore, industrialists prefer not to treat the waste produced and instead to dump it untreated into rivers in the areas where these treatment plants are located because the cost of treatment is so high.The Root Zone Treatment System (RZTS), sometimes referred to as the reed bed system or the constructed wetland system, is a sealed filter bed that is planted with vegetation that can grow in wetlands and is made up of a sand, gravel, and soil system, sometimes with a cohesive element. The wastewater flows through the filter bed, where biodegradation of the wastewater occurs, after the coarse and floating material has been removed. Complex physical, chemical, and biological processes that are the outcome of the interaction of wastewater, wetland plants, filter bed material, and microorganisms define the functional mechanisms in the soil matrix that are in charge of the mineralization of biodegradable matter.

Current expenditure and investment for water resources management. An analysis in the Ecuadorian manufacturing industry

INTRODUCTION. Environmental deterioration is a matter of great concern caused in part by industrial activities, where the main impacts are generated through emissions, solid waste and polluting wastewater. OBJECTIVE. To analyze the generation and treatment of wastewater resulting from industrial operations in terms of current expenditure and investment made by manufacturing industries in Ecuador. METHOD. The numerical data are cross-sectional, for which three levels of research were covered: descriptive, correlational and explanatory. The database of the environmental economic information module in companies (ENESEM) of the year 2020 was used. RESULTS. 53.2% of Ecuadorian manufacturing industries allocated resources in current expenditures to prevent surface water pollution by reducing the release of wastewater (including wastewater collection and treatment) and only 4.5% allocated resources in investment for the treatment of this water. DISCUSSION AND CONCLUSIONS. The activities that presented the highest level of correlation with current expenditure were wastewater treated, wastewater generated and the amount of water captured from natural sources. In this sense, manufacturing companies should focus their efforts on issues related to the generation and treatment of wastewater from their productive activities.

A "2-in-1" Bioanalytical System Based on Nanocomposite Conductive Polymers for Early Detection of Surface Water Pollution.

This work proposes an approach to the formation of receptor elements for the rapid diagnosis of the state of surface waters according to two indicators: the biochemical oxygen demand (BOD) index and toxicity. Associations among microorganisms based on the bacteria P. yeei and yeast S. cerevisiae, as well as associations of the yeasts O. polymorpha and B. adeninivorans, were formed to evaluate these indicators, respectively. The use of nanocomposite electrically conductive materials based on carbon nanotubes, biocompatible natural polymers-chitosan and bovine serum albumin cross-linked with ferrocenecarboxaldehyde, neutral red, safranin, and phenosafranin-has made it possible to expand the analytical capabilities of receptor systems. Redox polymers were studied by IR spectroscopy and Raman spectroscopy, the contents of electroactive components were determined by atomic absorption spectroscopy, and electrochemical properties were studied by electrochemical impedance and cyclic voltammetry methods. Based on the proposed kinetic approach to modeling individual stages of bioelectrochemical processes, the chitosan-neutral red/CNT composite was chosen to immobilize the yeast association between O. polymorpha (ks = 370 ± 20 L/g × s) and B. adeninivorans (320 ± 30 L/g × s), and a bovine serum albumin (BSA)-neutral composite was chosen to immobilize the association between the yeast S. cerevisiae (ks = 130 ± 10 L/g × s) and the bacteria P. yeei red/CNT (170 ± 30 L/g × s). After optimizing the composition of the receptor systems, it was shown that the use of nanocomposite materials together with associations among microorganisms makes it possible to determine BOD with high sensitivity (with a lower limit of 0.6 mg/dm3) and detect the presence of a wide range of toxicants of both organic and inorganic origin. Both receptor elements were tested on water samples, showing a high correlation between the results of biosensor analysis of BOD and toxicity and the results of standard analytical methods. The results obtained show broad prospects for creating sensitive and portable bioelectrochemical sensors for the early warning of environmentally hazardous situations based on associations among microorganisms and nanocomposite materials.

The adsorption effect of aquaculture residual feed on heavy metals and its impact on microbial metabolism of feed

BackgroundIntensive and large-scale aquaculture has a high biological density, and a large amount of artificial feed must be provided. As a result, residual feed would be discharged into natural water bodies with water exchange. Due to heavy metal pollution in surface water, residual feed may adsorb heavy metals in the water, affecting the subsequent microbial degradation of feed and the restoration of the water environment. The combined ecological impacts of these two types of pollution urgently need to be explored.ResultsThis study explored the adsorption effect of residual feed on heavy metals and its impact on microbial degradation of residual feed. The results showed that both the insoluble component (mainly fiber, ash, and ether extract, abbreviated as FAE) and soluble component (soluble protein and starch) of the feed had adsorption effects on heavy metals. As the salinity increased, the adsorption capacity of Cu2+ and Cd2+ decreased, while the adsorption effect on Pb2+ was not changed significantly. The adsorption of heavy metals by residual feed could affect the biological degradation of residual feed. The residual feed could adsorb heavy metals and bacterial cells simultaneously, forming FAE-B(bacteria)-S(starch)-Pr(protein)-metal adsorption complex. This adsorption effect could reduce the negative impact of heavy metals on microbial degradation of residual feed. The simulated degradation experiments in actual water bodies also confirmed this. However, the accumulation of heavy metals in residual feed may bring negative effects, such as being consumed by aquatic organisms and entering the food chain.ConclusionsThe results of this study provide a basis for the collection and centralized treatment of residual feed in aquaculture, as well as the control and remediation of residual feed pollution in natural water bodies.Graphical

A Review About the Occurrence and Effectiveness of Conventional and Advanced Treatment Technologies of Persistent Organic Pollutants in Surface Water

A Review About the Occurrence and Effectiveness of Conventional and Advanced Treatment Technologies of Persistent Organic Pollutants in Surface Water

Water Quality Assessment Using the Water Quality Index, and Geographic Information Systems in Nador Canal, Morocco

In recent decades, water pollution has emerged as a significant concern, posing a threat to both humans and natural ecosystems. This study aimed to assess the spatial variations in water quality in the Nador Canal, Morocco using the water quality index combined with multivariate statistical techniques and geographic information systems (GIS). The parameters examined were then compared to the maximum permissible limit values recommended by Moroccan surface water standards and the World Health Organization. The results indicated that the WQI of Nador Canal is generally suitable for irrigation and unsuitable for drinking. It indicated that the quality of surface water in the Nador Canal is affected by organic pollutants, and this is evidenced by low levels of dissolved oxygen, the levels of elements were high, especially chlorine and sodium, in addition to a high concentration of ammonia, nitrate, and phosphate in some of the stations studied. Principal component analysis (PCA) results revealed that PC1–PC3 collectively accounted for 73% of the variation in surface water quality within the study area. The cluster analysis also proves that the water quality is relatively polluted. Potential contributing factors to surface water pollution include changes in the hydrological regime, household waste discharges, and agricultural activities. These findings furnish essential insights into water quality, particularly its suitability for irrigation, and contribute to enhancing the water quality management system of the Nador Canal in the Gharb region of Morocco.

Metal–Organic Framework Fe-BTC as Heterogeneous Catalyst for Electro-Fenton Treatment of Tetracycline

This study explores the use of the iron-containing metal–organic framework (MOF), Basolite®F300, as a heterogeneous catalyst for electrochemically-driven Fenton processes. Electrochemical advanced oxidation processes (EAOPs) have shown promise on the abatement of recalcitrant organic pollutants such as pharmaceuticals. Tetracyclines (TC) are a frequently used class of antibiotics that are now polluting surface water and groundwater sources worldwide. Acknowledging the fast capability of EAOPs to treat persistent pharmaceutical pollutants, we propose an electrochemical Fenton treatment process that is catalyzed by the use of a commercially available MOF material to degrade TC. The efficiency of H2O2 generation in the IrO2/carbon felt setup is highlighted. However, electrochemical oxidation with H2O2 production (ECO-H2O2) alone is not enough to achieve complete TC removal, attributed to the formation of weak oxidant species. Incorporating Basolite®F300 in the heterogeneous electro-Fenton (HEF) process results in complete TC removal within 40 min, showcasing its efficacy. Additionally, this study explores the effect of varying MOF concentrations, indicating optimal removal rates at 100 mg L−1 due to a balance of kinetics and limitation of active sites of the catalysts. Furthermore, the impact of the applied current on TC removal is investigated, revealing a proportional relationship between current and removal rates. The analysis of energy efficiency emphasizes 50 mA as the optimal current, however, balancing removal efficiency with electrical energy consumption. This work highlights the potential of Basolite®F300 as an effective catalyst in the HEF process for pollutant abatement, providing valuable insights into optimizing electrified water treatment applications with MOF nanomaterials to treat organic pollutants.

Unveiling the Dynamics of Cryptosporidium in Urban Surface Water: A Quantitative Microbial Risk Assessment and Insights into Climatic and Seasonal Influences

In response to global urbanization and economic development, urban surface water pollution has become a universal challenge and particularly affects densely populated megacities, and Dhaka is no exception. The discharge of 98% of untreated domestic sewage and massive volumes of industrial wastewater from over 7000 industries escalate surface water crises. This study investigates microbial and fecal contamination with particular emphasis on Cryptosporidium in surface water, known for causing waterborne diseases, such as cryptosporidiosis. Findings reveal high Cryptosporidium oocyst concentrations and fecal contamination in various water bodies in Dhaka City. Among the investigated water bodies, the Buriganga River exhibits the highest Cryptosporidium oocyst concentration (46%), while the Balu River, Turag River, Shitalakkhya River, Dhanmondi Lake, Gulshan Lake, Banani Lake, Ramna Lake, and Crescent Lake also present high levels of oocyst concentrations ranging from 21–40%. This study also calculated infection risks and found that the infection risk of swimming is highest during the wet season and is (3.9 ± 2.2 (95% CI: 3.0–5.0)) × 10−2 per swimming event, whereas it is approximately (2.4 ± 1.9 (95% CI: 1.6–3.3)) × 10−2 during the dry season. Annual diving risks are approximately (1.2 ± 0.6 (95% CI: 0.9–1.4)) × 10−2, indicating considerably high risks. Most of the sampling sites generally show significantly higher risks than other study areas like the Mymensingh and Kushtia Districts. In light of these results, we strongly recommend immediate measures to address water quality issues and mitigate the risks associated with Cryptosporidium contamination in Dhaka’s surface water.

Classification of Pollution Sources and Their Contributions to Surface Water Quality Using APCS-MLR and PMF Model in a Drinking Water Source Area in Southeastern China

Identifying the potential pollution sources of surface water pollutants is essential for the management and protection of regional water environments in drinking water source areas. In this study, absolute principal component score-multiple linear regression (APCS-MLR) and positive matrix factorization (PMF) models were applied to assess water quality and identify the potential pollution sources affecting the surface water quality of Xin’an River Basin. For this purpose, a 10-year (2011–2020) dataset of eight water quality indicators (including pH, EC, DO, COD, NH3-N, TN, TP, and FC) covering eight monitoring stations and 7248 monthly observations was used. The results indicated that Pukou section had the worst water quality among the eight monitoring stations, and TN was the most serious water quality index. Both the APCS-MLR and PMF models identified agricultural nonpoint source pollution, urban nonpoint source pollution and rural domestic pollution, and meteorological factors. The sum of these three sources was very close, accounting for 60% and 58%, respectively. The APCS-MLR results demonstrated that for EC, COD, and NH3-N, the major pollution sources were urban nonpoint sources and rural domestic pollution. The major contamination source of TN was agricultural nonpoint source pollution (30.4%). Meanwhile, the major pollution sources of pH, DO, TP, and FC were unidentified factors. The PMF model identified five potential sources, and pH and DO were affected by meteorological factors. NH3-N and TP were influenced mainly by agricultural nonpoint source pollution. Atmospheric deposition was the major pollution source (87.9%) of TN. FC was mostly derived from livestock and poultry breeding (88.3%). EC and COD were mostly affected by urban nonpoint sources and rural domestic pollution. Therefore, receptor models can help managers identify the major sources of pollution in watersheds, but the major factors affecting different pollutants need to be supplemented by other methods.

Health impact assessment of the surface water pollution in China

China suffers from severe surface water pollution. Health impact assessment could provide a novel and quantifiable metric for the health burden attributed to surface water pollution. This study establishes a health impact assessment method for surface water pollution based on classic frameworks, integrating the multi-pollutant city water quality index (CWQI), informative epidemiological findings, and benchmark public health information. A relative risk level assignment approach is proposed based on the CWQI, innovatively addressing the challenge in surface water-human exposure risk assessment. A case study assesses the surface water pollution-related health impact in 336 Chinese cities. The results show (1) between 2015 and 2022, total health impact decreased from 3980.42 thousand disability-adjusted life years (DALYs) (95 % Confidence Interval: 3242.67–4339.29) to 3260.10 thousand DALYs (95 % CI: 2475.88–3641.35), measured by total cancer. (2) The annual average health impacts of oesophageal, stomach, colorectal, gallbladder, and pancreatic cancers added up to 2621.20 thousand DALYs (95 % CI: 2095.58–3091.10), revealing the significant health impact of surface water pollution on digestive cancer. (3) In 2022, health impacts in the Beijing-Tianjin-Hebei and surroundings, the Yangtze River Delta, and the middle reaches of the Yangtze River added up to 1893.06 thousand DALYs (95 % CI: 1471.82–2097.88), showing a regional aggregating trend. (4) Surface water pollution control has been the primary driving factor to health impact improvement, contributing −3.49 % to the health impact change from 2015 to 2022. It is the first city-level health impact map for China's surface water pollution. The methods and findings will support the water management policymaking in China and other countries suffering from water pollution.

Ecological Monitoring of Pollution of Surface Waters of the Volga River Basin with Phenol and its Derivatives

The results of gas chromatographic control of the content of phenol and its derivatives in the surface waters of the Volga River basin are presented. The assessment of the water quality of the studied reservoir by categories of pollution at different times of the year was carried out. The results of environmental monitoring of the surface waters of the Volga River basin, taking into account the transformation of phenols into more toxic compounds, are discussed.

Multivariate statistical methods for analysis of physicochemical and microbiological parameters of well water from the village M’Pody

The pollution of surface water and groundwater is a real public health problem that is currently receiving particular attention throughout the world. The use of water for food or hygiene purposes requires excellent physicochemical and microbiological quality. Well water is used for many purposes by the inhabitants of M’pody, a village in the Anyama district of Côte d’Ivoire. In this village, an epidemic of diarrhoea was detected in January 2020. This epidemic claimed sixty-nine (69) victims. This study aims to evaluate well water quality controls using the methods of principal component analysis (PCA), correspondence factorial analysis (CFA), analysis of variance (ANOVA) and self-organizing map (SOM) algorithm. The parameters studied were, turbidity (Tur), conductivity (Cond), hydrogen potential (pH), temperature (T), nitrate (NO3-\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$NO_{3^{-}}$$\\end{document}), nitrite (NO2-\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$NO_{2^{-}}$$\\end{document}), ammonium (NH4+\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$NH_{4^{+}}$$\\end{document}), phosphates (PO43-\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$PO_{4}^{3^{-}}$$\\end{document}), chlorides (Cl-)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$(Cl^{-})$$\\end{document}, total hydrotimetric degree (DHT), sulfates (SO42-\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$SO_{4}^{2^{-}}$$\\end{document}), bicarbonate (HCO3-\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$HCO_{3^{-}}$$\\end{document}), total alkalinity contents (TAC), escherichia coli (E.coli), thermotolerant coliforms (CTH) and enterococcus faecalis (E.faecalis). Data were collected from seventy-two (72) wells in the village during four campaigns in 2020. Physicochemical parameters were determined by electrochemical and spectrophotometric methods. Microbiological analysis was carried out using membrane filtration technique. Descriptive statistics revealed that Tur, Cond, pH and T parameters did not meet world health organization (WHO, 2017) standards. However, the parameters NO3-\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$NO_{3^{-}}$$\\end{document}, NO2-\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$NO_{2^{-}}$$\\end{document}, NH4+\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$NH_{4^{+}}$$\\end{document}, PO43-\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$PO_{4}^{3^{-}}$$\\end{document}, Cl-\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$Cl^{-}$$\\end{document}, DHT, TAC, SO42-\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$SO_{4}^{2^{-}}$$\\end{document} and HCO3-\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$HCO_{3^{-}}$$\\end{document} comply with WHO standards. The results of bacteriological analyzes confirm the presence in very significant numbers of indicators of faecal contamination (CTH, E.coli and E.faecalis) in all wells. The logical explanations for faecal pollution would come from the infiltration of septic tanks located near the wells and the run-off of waste water carrying human and animal faecal matter. The diarrhea epidemic would therefore be caused by the consumption of this polluted water. PCA, FCA and hierarchical cluster analysis (HCA) were jointly employed to identify the structure of wells and deduce the principal factors controlling the parameters of these well waters. ANOVA revealed the effect of human-induced activities as the main factors influencing the physicochemical and microbiological parameters of the studied well waters. Further studies should focus on multivariate statistical techniques for effective forecasting and monitoring of emerging pollution for improved water quality.

Rationalizing the selection of cleaning solution type through quantum chemical calculations

The surface water sources for water supply are contaminated with substances that cause water discoloration. These substances include soluble humic and fulvic acids, which are retained on the surface during ultrafiltration membrane treatment, forming a fouling layer that deteriorates membrane performance and reduces membrane productivity. These substances also form a mixed fouling layer with water-soluble metals and coagulants. This work proposes a theoretical justification for cleaning solutions capable of restoring the properties of ultrafiltration membranes. Quantum-chemical calculations and modeling were chosen as the method for prediction and justification. EDTA-Na, SDS, and sodium tripolyphosphate can wash away the fouling layer, but it is impossible to justify the use of mixtures of these substances theoretically. As the quantum-chemical analysis showed, each of these substances has a tendency to wash away the fouling layer. However, it is impossible to justify the use of mixtures of these substances from a theoretical point of view. The pollutants in surface waters have a complex organomineral composition. Considering this, optimal components and concentration ratios of reagents for ultrafiltration membrane cleaning cannot be determined using quantum-chemical prediction methods, so experimental studies of cleaning processes are necessary.