Water Quality Research Articles

Combined Effects of Magnetized Irrigation and Water Source on Italian Lettuce (Lactuca sativa L. var. ramosa Hort.) Growth and Gene Expression

Agricultural water scarcity has become a global issue. Optimizing irrigation water quality and effectively utilizing non-conventional water resources are essential strategies to alleviate pressure on agricultural water use and achieve sustainable development. This study employed Italian lettuce as the test crop to explore the effects of magnetization treatment (M) at a magnetic field strength of 0.2 T and various irrigation water sources (T) on its growth. The following six treatments were established: fresh water irrigation (M0T1), recycled water irrigation (M0T2), saline water irrigation (M0T3), magnetized fresh water irrigation (M1T1), magnetized recycled water irrigation (M1T2), and magnetized saline water irrigation (M1T3). The results showed that the magnetization treatment increased the electrical conductivity (EC), power of hydrogen (pH), and dissolved oxygen (DO) of the three water sources compared to the non-magnetized treatment. Furthermore, magnetized irrigation with fresh water, recycled water, and saline water increased the contents of nitrogen (N), potassium (K), calcium (Ca), and magnesium (Mg) in lettuce. It also led to increases in the contents of soluble proteins (by 9.27% to 22.25%), soluble sugars (by 13.45% to 20.50%), and vitamin C (VitC) (by 4.18% to 19.33%) in lettuce. Additionally, it enhanced the above-ground fresh weight of lettuce (by 9.36% to 8.81%) and water productivity (WPc) (by 5.85% to 10.40%), while reducing water consumption. Among these treatments, magnetized fresh water irrigation was the most effective in improving quality, fresh weight, and WPc, followed by magnetized recycled water. Gene expression analysis revealed that differentially expressed genes (DEGs) were primarily enriched in metabolic pathways such as the MAPK signaling pathway—plant, phytohormone signaling, and cysteine and methionine metabolism. In summary, magnetized irrigation significantly enhanced DO levels in irrigation water, along with the fresh weight, quality, and WPc of lettuce, demonstrating its effectiveness as an efficient method for agricultural irrigation.

Domestic groundwater wells in Appalachia show evidence of low-dose, complex mixtures of legacy pollutants.

Lack of water quality data for private drinking water sources prevents robust evaluation of exposure risk for communities co-located with historically contaminated sites and ongoing industrial activity. Areas of the Appalachian region of the United States (i.e., Pennsylvania, Ohio and West Virginia) contain extensive hydraulic fracturing activity, as well as other extractive and industrial technologies, in close proximity to communities reliant on private drinking water sources, creating concern over potential groundwater contamination. In this study, we characterized volatile organic compound (VOC) occurrence at 307 private groundwater well sites within Pennsylvania, Ohio, and West Virginia. The majority (97%) of water samples contained at least one VOC, while the average number of VOCs detected at a given site was 5 ± 3. The majority of individual VOC concentrations fell below applicable U.S. Environmental Protection Agency (EPA) Maximum Contamination Levels (MCLs), except for chloroform (MCL of 80 μg L-1; n = 1 at 98 μg L-1), 1,2-dibromoethane (MCL of 0.05 μg L-1; n = 3 ranging from 0.05 to 0.35 μg L-1), and 1,2-dibromo-3-chloropropane (MCL of 0.2 μg L-1; n = 7 ranging from 0.20 to 0.58 μg L-1). To evaluate well susceptibility to VOCs from industrial activity, distance to hydraulic fracturing site was used to assess correlations with contaminant occurrences. Proximity to closest hydraulic fracturing well-site revealed no statistically significant linear relationships with either individual VOC concentrations, or frequency of VOC detections. Evaluation of other known industrial contamination sites (e.g., US EPA Superfund sites) revealed elevated levels of three VOCs (chloroform, toluene, benzene) in groundwaters within 10 km of those Superfund sites in West Virginia and Ohio, illuminating possible point source influence. Lack of correlation between VOC concentrations and proximity to specific point sources indicates complex geochemical processes governing trace VOC contamination of private drinking water sources. While individual concentrations of VOCs fell well below recommended human health levels, the low dose exposure to multiple VOCs occurring in drinking supplies for Appalachian communities was noted, highlighting the importance of groundwater well monitoring.

Machine Learning Based Inversion of Water Quality Parameters in Typical Reach of Rural Wetland by Unmanned Aerial Vehicle Images

Rural wetlands are complex landscapes where rivers, croplands, and villages coexist, making water quality monitoring crucial for the well-being of nearby residents. UAV-based imagery has proven effective in capturing detailed features of water bodies, making it a popular tool for water quality assessments. However, few studies have specifically focused on drone-based water quality monitoring in rural wetlands and their seasonal variations. In this study, Xiangfudang Rural Wetland Park, Jiaxin City, Zhejiang Province, China, was taken as the study area to evaluate water quality parameters, including total nitrogen (TN), total phosphors (TP), chemical oxygen demand (COD), and turbidity degree (TUB). We assessed these parameters across summer and winter seasons using UAV multispectral imagery and field sample data. Four machine learning algorithms were evaluated and compared for the inversion of the water quality parameters, based on the situ sample survey data and UAV multispectral images. The results show that ANN algorithm yielded the best results for estimating TN, COD, and TUB, with validation R2 of 0.78, 0.76, and 0.57, respectively; CatBoost performed best in TP estimation, with validation R2 and RMSE values of 0.72 and 0.05 mg/L. Based on spatial estimation results, the average COD concentration in the water body was 16.05 ± 9.87 mg/L in summer, higher than it was in winter (13.02 ± 8.22 mg/L). Additionally, mean TUB values were 18.39 Nephelometric Turbidity Units (NTU) in summer and 20.03 NTU in winter. This study demonstrates the novelty and effectiveness of using UAV multispectral imagery for water quality monitoring in rural wetlands, providing critical insights into seasonal water quality variations in these areas.

Uncovering the Anthropogenic Influences on Water Quality: A Case of Lake Victoria Shores, Entebbe, Uganda

Lakes serve as vital ecosystems, providing freshwater resources and habitats for diverse species. However, human activities, particularly around lakeshores, have led to significant environmental degradation, including heavy metal contamination. Lake Victoria, the second-largest freshwater lake globally, has been severely impacted by pollution from industrial, agricultural, and urban sources. This research aims at examining the influence of the anthropogenic activities on the water quality of Lake Victoria. Specifically, the study tried to determine the activities undertaken at the Lake shores of Lake Victoria; determined the physico-chemical parameters of the water from the shores and the heavy metal concentration in the water samples obtained from the shores of Lake Victoria. This study utilized a cross-sectional and experimental research designs to assess water quality and anthropogenic influences around Lake Victoria. A total of 150 residents from selected communities were surveyed using a semi-structured questionnaire to gather demographic information, perceptions of water quality and the activities carried out within the shores of Lake Victoria. Water samples were collected from multiple sites along the lake shores for analysis of heavy metals using the Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Water quality parameters were determined In-situ using a multi-parameter water testing kit and Hanna instrument. Results showed that the anthropogenic activities that could have contributed to water degradation include: fishing, transport, agriculture and construction among others. Apart from pH which was outside the permissible limits, all the other water parameters were within the WHO permissible limits. Considering the heavy metal concentration, all the sampled sites apart from one inlet, had the concentrations above the WHO permissible levels an indication of significant heavy metal contamination in the Lake Victoria shores. These findings highlight the urgent need for targeted pollution control measures and regular monitoring to mitigate further environmental degradation. Effective interventions, including stricter regulations and sustainable land use practices within the Victoria shores are essential for safeguarding the lake's ecosystem and the health of surrounding communities.

Ecological Assessment of Phytoplankton Diversity and Water Quality to Ensure the Sustainability of the Ecosystem in Lake Maybalyk, Astana, Kazakhstan

Microalgae in planktonic communities are the main producers of biomass in lake ecosystems; however, their stability is influenced by many environmental factors. This study aims to assess the ecological state of Lake Maybalyk, located in Astana (Kazakhstan), based on the study of the taxonomic diversity and structure of phytoplankton, zooplankton, and the physico-chemical properties of the water. From 2019 to 2021, samples were taken for phytoplankton analysis, hydrochemical analysis of the water, zooplankton, and saprobiological analysis of the algocenosis. The study also investigated the main morphometric parameters of the lake, as well as the composition of hydrobionts, such as zooplankton, zoobenthos, and ichthyofauna. The analysis of phytoplankton revealed the presence of 97 species and intraspecific taxa of microalgae, with 71 types of microalgal indicators indicating water saprobity. The planktonic algoflora in Lake Maybalyk is predominantly composed of diatoms (Bacillariophyta) and green algae (Chlorophyta), which play a vital role in oxygen production and the food chain within the reservoir. Based on the Pantle–Buck saprobity index (2.15–2.5), the water quality in Lake Maybalyk is classified as moderately polluted. The assessment of the water quality, considering the number and composition of indicator phytoplankton species, places Lake Maybalyk in class III (β-mesosaprobic). The hydrochemical indicators align with the hydrobiological indicators, confirming the water quality as class III. The trophic status of the reservoir, during the study period, can be described as average. The obtained data on both the hydrobiological and hydrochemical indicators correlate, suggesting satisfactory water quality and the ability of the reservoir to purify itself. This study contributes to the sustainable management of water resources, by providing essential data on the ecological state of Lake Maybalyk. The results underscore the importance of continuous biomonitoring, with microalgae as indicators of water quality, which is crucial for developing effective ecosystem conservation strategies.

Water quality evaluation by WQI and ICOs for the rivers of Joya de los Sachas and Francisco de Orellana

A monitoring program enabled the evaluation of water quality and the simulation of the pollution dynamics of the rivers in the Joya de los Sachas and Francisco de Orellana cantons in Ecuador. For this assessment one used the WQI (water quality index) and the pollution indices ICOMO (organics contamination), ICOSUS (suspended solids), ICOMI (mineralization), ICOTRO (trophy system), and ICOpH (pH Index). The mathematical model operates with several input parameters, including dissolved oxygen, fecal coliforms, the biochemical oxygen demand (BOD5), turbidity, total solids, total phosphorus, pH, total nitrogen, suspended solids, alkalinity, conductivity, temperature, and the concentrations of nitrates, nitrites, and phosphates. WQI values were obtained from ICO pollution indices. The pollution of the Sacha area is significant, WQI = 0.292, which represents an advanced degree of pollution, since increased BOD values correspond to a high load of organic pollutants. They can originate from household, agricultural, industrial, and soil erosion waste. Likewise, the Sacha River has an ICOSUS = 0.16, which renders water treatment difficult, without impacting human health. Calculated WQI values reveal that the water quality of the Sacha, Basura and Coca rivers is low, being highly contaminated. In contrast, the Huamayacu, Jivino Rojo, Jivino Negro, and Jivino Blanco rivers are commonly polluted.

Assessing groundwater quality in the northwestern coastal area of Sri Lanka using multivariate statistical techniques

The objective of the present study was to assess groundwater quality in the northwestern coastal region of Sri Lanka by analyzing hydrogeochemical data using multivariate techniques. The study examined the relationship between water quality and sources influencing groundwater quality and proposed useful statistical tools for water resource management. Descriptive, comparative, correlation, factor analysis (FA), and discriminant analysis (DA) were among the techniques used. The water quality in terms of electrical conductivity (EC), total dissolved solids (TDS), and dissolved nitrate and phosphate concentrations of the northwestern coastal area, where different aquifer conditions prevailed, were compared, and differences in the mean concentrations of the above parameters were identified. The study also employed ridge regression and support vector machines (SVM) to predict nitrate levels and validate the results using a 70:30 train/test split. The analysis found that the mean concentrations of EC, TDS, and HCO3- are higher in the sandy aquifer area, while Fe2+ and PO43- are higher in the regolith aquifer area. EC, TDS, PO43-, and HCO3- in the hard-rock aquifer area exceed permissible limits. Factor analysis identified four factors contributing to pollution, and a linear discriminant model classified all observations with 99.9% accuracy. The water quality index for Kalpitiya, Vanathavillu, and Katana-Negombo areas was 68.1, 99.2, and 287.9, respectively, while the World Health Organization (WHO) cutoff was 50. The use of multivariate statistical techniques demonstrated the value of analyzing hydrogeochemical data to gain valuable insights into the complex interplay of factors affecting groundwater quality. The SVM model, using a linear kernel, was identified as the best model to predict nitrate levels. A combination of statistical analyses reveals that, with the exclusion of a few wells, the groundwater in the study area is polluted and inappropriate for human consumption or culinary purposes. Nonetheless, the inhabitants persist in utilizing it as their primary source of drinking water. This study reveals the combination of statistical analyses is useful for the management of groundwater resources.

Water Quality Analysis of a 300 Mvar Large-Scale Dual Internal Water Cooling Synchronous Condenser External Cooling System and Exploration of Optimal Water Treatment Agent Dosage at Different Temperatures

The external cooling water system of a 300 Mvar dual internal water cooling synchronous condenser at a certain ultra-high voltage converter station continued to exhibit significant scaling and corrosion, even with regular addition of scale and corrosion inhibitors. To solve this problem, the external cooling water of the synchronous condenser was sampled and tested periodically, with the main test items including conductivity, pH value, turbidity, hardness, alkalinity, and other water quality parameters directly related to corrosion and scaling. The trends of these parameters over time were also analyzed. The results showed that as the operation time increased, the cooling water became concentrated during multiple circulation cycles, and the various dissolved or suspended substances underwent a certain degree of enrichment. However, the addition of scale and corrosion inhibitors did not dynamically adjust according to the changes in water quality, and there was always an excessive dosage. Thus, using the external cooling water as the experimental sample, static scale inhibition tests and rotating coupon corrosion tests were conducted to evaluate the scale and corrosion inhibition performance of the commercial AS-582 scale and corrosion inhibitor used at this ultra-high voltage converter station under different conditions. Considering the more obvious corrosive tendency of this water sample, the focus was on testing its corrosion inhibition performance. When the dosage was 600 ppm, the scale inhibition effect was optimal, with an inhibition rate of 92.15%. The corrosion inhibition effect of this scale and the corrosion inhibitor were significantly related to water temperature. At 25 °C, when the dosage was 500 ppm, the corrosion inhibition effect was optimal, with an inhibition rate of 86.79%. However, when the temperature increased to 40 °C, the corrosion inhibition effect under each dosage was significantly worse, unable to meet the requirements, and the use of other corrosion inhibitors in combination was necessary. This work will provide a reference for the scientific use of scale and corrosion inhibitors.

Intensive white shrimp (Litopenaeus vannamei) culture integrated with green mussel (Perna viridis), seaweed (Gracilariopsis bailiniae), and tilapia (Oreochromis mossambicus): impacts on water quality and growth of the shrimp

The production of Litopenaeus vannamei has significantly intensified, and integrated multi-trophic aquaculture (IMTA) has emerged as an effective farming technique to sustain the shrimp industry. Integrated aquaculture reduces pollution while increasing aquaculture production. This production system could give both ecological and economic benefits. Its contribution to the reduced amount of nutrients from intensive shrimp farming effluents and to the improvement of water quality conditions and growth of white shrimp are significant. This study aimed to evaluate the impacts on water quality and growth performance of shrimp (L. vannamei) at the same time assess the viability of rearing shrimps integrated with either green mussel, Perna viridis (GM alone), GM+seaweed (Gracilariopsis bailiniae), GM+tilapia (Oreochromis mossambicus), or GM+seaweed+tilapia. Shrimps were cultured outdoors for 60 days in a recirculating system at an average water exchange rate of 6 L hr-1. Shrimps were stocked at 400 shrimp m-3 in shrimp tank while seaweed (2kg m-2), green mussels (50 individuals per meter line), and tilapia (350 grams m-3) were cultivated separately in plastic baskets inside the biofiltration tank. Shrimp effluents were recirculated from the shrimp tank to the biofiltration tank. After 60 days of culture, results showed that shrimps without integration had the lowest average body weight (ABW), survival, weight gain, specific growth rate (SGR), biomass gain, and high feed conversion ratio (FCR) compared to shrimps with integration. This experiment confirmed that shrimp can be cultured intensively with either green mussel (GM alone), GM+ seaweed, GM+tilapia, or GM+seaweed+tilapia without adversely affecting the water quality and its growth performance and could even result in better yield than the shrimp cultured without integration. This research demonstrated the benefits of integrated aquaculture and could be further verified using large-scale culture.

Assessment of genotoxicity biomarkers in neotropical fish species from streams of the Ivinhema River basin located in sugarcane cultivation areas

The Ivinhema River basin has experienced the greatest expansion of sugarcane cultivation in the state of Mato Grosso do Sul, Brazil. Theassessment of water quality through physical and chemical parameters and ecotoxicological studies, employing both bioindicators collected in situ and laboratory tests, provides more robust results for this region. In this context, the objective of this study was to analyze the composition and structure of the landscape around the sampling sites located in three streams (Vitória, Rosário, and Piravevê) belonging to the Ivinhema River basin to evaluate the impacts of sugarcane cultivation expansion on water quality and genotoxicity biomarkers in situ and ex situ using native fish species. Inthe sampling sites in the Rosário and Vitória streams, sugarcane is the main land use, while in the Piravevê stream, pasture areas represent the main land use. The acidic pH observed in the Vitória and Rosário streams seems to be related to the application of fertilizers and the fertigation in the sugarcane crop. Two species of detritivorous and five of omnivorous fishes were collected. A higher frequency of genotoxic damage was identified in detritivorous fish species. In the genotoxicity tests with Astyanax lacustris, the most frequent nuclear alteration induced by the water samples from all sampling sites was nuclear invagination. Our results indicated that the expansion of the sugarcane ridge in the Ivinhema River basin may cause negative impacts on the aquatic environment and native biota. These results contribute to the generation of data and information that can be used for public hearing requests that aim to discuss and review many aspects of legislation regarding agricultural activities around streams, as well as the need for restoration and management programs in these areas in order to conserve biodiversity.

Delineation and Mapping of Groundwater Quality Assessment in Salem District, Tamil Nadu, India using GIS Techniques

Groundwater is a crucial natural resource with significant economic importance, supporting industrial activities, irrigation, and drinking water supplies. However, its extensive use for these purposes depletes water tables, which diminishes its future availability and leads to increased salinity, stream depletion, and land subsidence. A study was conducted to evaluate and map groundwater quality across different blocks in Salem district viz., Salem, Gangavalli, Thalaivasal, Attur, Pethanaickenpalayam, Valappady, Ayothiyapattinam, Yercaud, Panamarathupatty, Veerapandi, Edappadi, Sankari, Kadayampatti, Kolathur, Konganapuram, Magudanchavadi, Mecheri, Nangavalli, Omalur, and Tharamangalam. Sampling was conducted in February 2024, during which a total of 200 samples were collected and examined for pH, electrical conductivity, cations like Ca2+, Mg2+, Na+ and K+, anions like CO32-, HCO3-, SO42-, and Cl-. Based on the ionic concentration, the water quality parameters are derived such as Sodium Adsorption Ratio(SAR) and Residual Sodium Carbonate (RSC). The pH and EC values were ranged from 7.08 to 8.58 and 0.74 to 2.75 dS/m, respectively. The residual sodium carbonate (RSC) concentration ranged from -7.3 to 10.1 meq/L, while the sodium adsorption ratio (SAR) ranged from 0.7 to 9.7 meq/L. According to the CSSRI, Karnal Water Quality Classification, approximately 66.5 % of the samples fit into the good quality category, approximately 13% of the samples fit into the alkaline water category, and 20% of the samples fit into the saline water category in the Salem district. Using this classification, thematic maps depicting groundwater quality in the Salem district were generated with ArcGIS software. The study concludes that the majority of the samples are classified as good-quality water, while saline and alkali water emerge as the next major concern. Using this saline water for irrigation can change the soil's physical properties and lower agricultural productivity. Thus, it's crucial to apply soil amendments like gypsum and provide proper drainage to avoid long-term soil damage.

Water quality estimates using machine learning techniques in an experimental watershed

ABSTRACT Estimation of the water quality parameters is important to enhance time and cost-effectiveness to that of the conventional approach. This study is aimed to identify the best machine learning (ML) approach to predict concentrations of biochemical oxygen demand (BOD), nitrate, and phosphate. Four ML techniques including decision tree, random forest, gradient boosting, and XGBoost were compared to estimate the water quality parameters based on biophysical (i.e., population, basin area, river slope, water level, and stream flow) and physicochemical properties (i.e., conductivity, turbidity, pH, temperature, and dissolved oxygen) as input parameters. The data were split into training and test sets, and the model performances were evaluated using coefficient of determination (R2), Nash–Sutcliffe efficiency coefficient (NSE), and root mean squared error (RMSE). The mean squared error (MSE) was used as the optimization target. The robust fivefold cross-validation, along with hyperparameter tuning, achieved R2 values of 0.76, 0.67, and 0.71 for phosphate, nitrate, and BOD, and NSE values of 0.73, 0.67, and 0.66, respectively. XGBoost yielded the lowest RMSE across all parameters, showcasing superior performance when considering all metrics performed. In conclusion, ML techniques, particularly with a robust cross-validation technique and hyperparameter optimization, showed good results in water quality parameter prediction.

Phytochemical Screening of Seaweed Flour (Eucheuma cottonii) Using Various Organic Solvents and Its Application in Tilapia Feed (Oreochromis niloticus)

This study aims to qualitatively analyze the bioactive compounds in Eucheuma cottonii seaweed flour extract and its application in commercial feed for tilapia (Oreochromis niloticus). The methodology employed is experimental and consists of two phases. Phase 1 involves the extraction of E. cottonii flour using three different organic solvents with varying polarity (ethanol, ethyl acetate, and a combination of ethanol + ethyl acetate). The testing parameters include qualitative phytochemical tests for alkaloids, steroids/triterpenoids, saponins, flavonoids, and tannins. Phase 2 consists of the application of the extract to tilapia over a 30-day rearing period with four treatments: control/commercial feed (P0), commercial feed + ethanol extract (P1), commercial feed + ethyl acetate extract (P2), and commercial feed + combined ethanol and ethyl acetate extract (P3). The parameters tested include absolute weight, specific growth rate, survival rate, and water quality. Phytochemical and water quality data are presented in table format. Meanwhile, growth and survival data are analyzed using ANOVA, followed by Duncan’s test for significant differences. The results of the researches carried out, it can be concluded that the phytochemical analysis of E. cottonii extract in ethanol and the ethanol + ethyl acetate combination yielded similar compounds: alkaloids, steroids/triterpenoids, and flavonoids. The ethyl acetate extract contained triterpenoids and flavonoids. Both saponins and tannins returned negative results across all organic solvent treatments. All treatments with the addition of E. cottonii seaweed extract in various organic solvents demonstrated better growth in tilapia compared to the control treatment.

Effects of mangrove leaf litter on the water quality, growth, and survival of tiger shrimp (Penaeus monodon Fabricius, 1798) post-larvae

Effects of mangrove leaf litter on the water quality, growth, and survival of tiger shrimp (Penaeus monodon Fabricius, 1798) post-larvae

Plasma Tailoring of NH2-MIL-53 with Enhanced Fluorescence Emission for Simultaneous Detection of Multiple Heavy Metals in Water.

Indium, copper, and mercury are important raw materials in the electronics industry and often coexist in factory wastewater. Therefore, the development of a highly sensitive and selective method for the simultaneous detection of these heavy metal ions is of great significance for water quality monitoring and environmental protection. Herein, we report a NH2-MIL-53 fluorescent probe for the simultaneous detection of trace In3+, Cu2+, and Hg2+ in water. After a low-temperature NH3 plasma tailoring treatment for grafting electron-donor amine groups, the obtained NH2-MIL-53-M exhibited enhanced fluorescence emission intensity (∼6 times) coupled with selective adsorption of In3+, Cu2+, and Hg2+. This quenched the NH2-MIL-53-M fluorescence and allowed to significantly increase the selectivity and sensitivity for detection of In3+, Cu2+, and Hg2+. The fluorescence quenching constant (Ksv) values were 2.23 × 105, 1.00 × 105, and 2.74 × 104 M-1, while the limit of detection (LODs) values were 0.06, 0.14, and 0.53 μM, for In3+, Cu2+, and Hg2+, respectively. The concentrations of In3+, Cu2+, and Hg2+ in real environmental samples could be determined by addition of appropriate masking agents, and the recoveries were within the range of 94-110%. This study not only supplied a strategy for constructing a highly sensitive and selective fluorescent probe but also established a platform for simultaneous detection of multiple heavy metal ions in water.

Evaluation of pilot-scale drinking water treatment trains using a panel of bioassays

ABSTRACT Chemical water quality monitoring is increasingly complemented with bioassays. In this study, the performance of drinking water treatment technologies was evaluated with bioassays. CALUX reporter gene bioassays and the Ames fluctuation bioassay for mutagenicity were used to analyze the responses of raw feed water with and without a spiking mixture of organic contaminants in five different pilot-scale water treatment trains applying advanced oxidation processes, reverse osmosis and filtration with (biological) activated carbon for the preparation of drinking water. In general, CALUX responses in the spiked feed water were in the same range as in the unspiked feed water, indicating that spiking did not significantly elevate the activity measured in the feed water. This observation was in line with a calculation of the combined additive behavior of the spiking mixture using bioactivities of the spiked chemicals in analog bioassays from ToxCast. This calculation gave no indication of a measurable response in the bioassays to be expected by the spiking, except for oxidative stress. Responses in the Ames fluctuation assay in most feed water were in some cases increased by AOP and mostly removed by active concentrations. The bioassay responses demonstrate the removal of emerging chemicals with different mechanisms of action by different water treatment technologies.

Correction: Heavy metal concentrations and water quality assessment of different types of drinking water wells in the Erdenet Cu–Mo mining area

Correction: Heavy metal concentrations and water quality assessment of different types of drinking water wells in the Erdenet Cu–Mo mining area

Application of Multiple Linear Regression Models in Deriving Water Quality Criteria for Lead: Comparison of Metal Bioavailability Estimation Approaches

Application of Multiple Linear Regression Models in Deriving Water Quality Criteria for Lead: Comparison of Metal Bioavailability Estimation Approaches

Willingness to Pay for Improved Groundwater due to BMPs in PEI.

This study uses stated preference techniques to evaluate the willingness to pay for improved groundwater in PEI, which allows us to estimate the social cost of nitrogen in this region. 'Beneficial Management Practices' (BMPs) are often employed in PEI's agricultural sector, to improve crop yields but also reduce adverse environmental effects such as nitrogen leaching that can affect ground and surface waters. PEI residents were surveyed to estimate a dollar value of improved water quality due to reduced nitrogen leaching due to BMPs. From the responses to a double-bounded dichotomous choice survey, models using maximum likelihood estimation showed that residents of PEI were willing to pay roughly $230 per year to see a reduction in nitrogen of either 20% or 50%, which translated to $5-13 per kg of nitrogen reduced. However, excluding 'yeah-sayers' and protest votes suggests that WTP is lower for the 20% reduction and increases as nitrogen reduction increases. Thus, a social cost of $13/kg should be considered an upper bound in PEI. WTP values, as well as estimates of the social cost of nitrogen are similar to values in previous literature. We find that variables such as cell phone usage, belief that farmers should pay for BMPs, and spending on water filtration have a statistically significant impact on WTP. Other variables are significant in some model specifications, however many demographic variables such as employment status and education do not affect WTP.

Environmental Impact Assessment of Solid Waste Disposal on Groundwater Quality

<p class="CxSpFirst" style="text-align:justify;"><span style="font-family:"Times New Roman","serif";font-size:12.0pt;line-height:150%;text-autospace:none;">This study focuses on the impact of solid waste on groundwater quality in the region of Ramayanpatti, Tirunelveli. Tirunelveli city generates 100 tonnes of solid waste in a day. Solid waste has organic matter, inorganic matter, and moisture content which leaches dissolved organic matter, and heavy metals to the groundwater. Rainfall runoff carries all the dissolved contaminants from the solid waste and infiltrates into the groundwater. Groundwater quality is characterized at 30 locations around the dumping yard. Water Quality Index (WQI) is calculated using important characteristics such as pH, TDS, Calcium, Magnesium, Alkalinity, Sodium, Potassium, Chloride, Nitrate, and Sulphate by its relative weightage. The Spatial distribution of WQI is drawn.  Groundwater Quality is very poor in the surrounding region of solid waste dump yard and also in the areas of agriculture irrigated areas. Groundwater in other areas shall be used for domestic purposes except drinking with proper disinfection.</span></p><p class="CxSpMiddle" style="text-align:justify;"><span style="font-family:"Times New Roman","serif";font-size:12.0pt;line-height:150%;text-autospace:none;"><strong>Keywords:</strong> Solid waste, Groundwater Quality, Characterization, Water Quality Index, Groundwater use</span></p>