Water quality assessment in two lakes of Panchkula, Haryana, using GIS: case study on seasonal and depth wise variations

Quantitative microbial risk assessment of gastrointestinal illness due to recreational exposure to E. coli and enterococci on the southern coasts of the Caspian Sea

Background

Gastrointestinal illness refers to a broad range of diseases that affect the digestive system, including infections caused by bacteria, viruses, and parasites. Quantitative Microbial Risk Assessment (QMRA) is a powerful tool used to evaluate the risks associated with microbial pathogens in various environments. The main objective of this study was to conduct a quantitative assessment of gastrointestinal illnesses that occur as a result of exposure to E. coli and enterococci during recreational activities on the southern coasts of the Caspian Sea.

Methods

Samples were collected from the recreational beaches along the border line of the Caspian Sea. The samples were analyzed for the presence and enumeration of E. coli and enterococci using the microplate method and membrane filtration techniques. Then, the annual and daily infection risks were computed using the Monte Carlo simulation approach.

Results

The results revealed that the risk of daily and annual infections on the coasts of Babolsar was higher than that on the coasts of Sari. Also, in the recreational waters of these beaches, the risk of infection by enterococci was higher than that posed by E. coli. In Babolsar, the average annual infection risk caused by E. coli and enterococci was 0.365 and 1 for children and 0.181 and 0.986 for adults. Also, in Sari, the average annual infection risk caused by E. coli and enterococci was 0.060 and 0.908 for children and 0.027 and 0.815 for adults. In addition, children were more likely than adults to become infected.

Conclusion

In light of the study's findings, due to the entry of untreated urban wastewater into the southern part of the Caspian Sea (northern Iran) and the high risk of infectious diseases for children, more control and health measures are necessary for children's swimming.

Identification of prevalent leachate percolation of municipal solid waste landfill: a case study in India

Landfill leachate forms when waste-inherent water and percolated rainfall transfer are highly toxic, corrosive, acidic, and full of environmental pollutants. The release of leachate from municipal solid waste (MSW) landfill sites poses a severe hazard to human health and aquatic life. This study examined the impact of leachate from Delhi's Ghazipur landfill on the nearby groundwater quality. Analysis of leachate samples was done to determine various parameters such as total dissolved solids (TDS), hardness, alkalinity, electrical conductivity, pH, BOD5, COD, nitrate, sulphate, chloride and iron, and presence of coliform bacteria. Significant dissolved elements (22,690-34,525 mg/L) were observed in the samples, indicated by the high conductivity value (1156-1405 mho/cm). However, a stable pH range (6.90-7.80) of leachate samples was observed due to high alkalinity concentrations between 2123 and 3256 mg/L. The inverse distance weighing (IDW) interpolation tool from QGIS 3.22.7 developed spatial interpolated models for each parameter across the Ghazipur area. The IDW interpolated graphs of various parameters over the whole study area confirmed these contaminations. In addition, leachate and groundwater samples were physio-chemically analyzed, and temporal fluctuation in landfill waste has also been studied. The temporal fluctuation results showed that when heat is produced, transmitted, and lost throughout the waste system, the maximum temperature position fluctuates over time. The findings of this study highlight the critical importance of landfill management in reducing groundwater contamination from MSW leachate.

Evaluating lake water quality with a GIS-based MCDA integrated approach: a case in Konya/Karapınar

Considering water quality is an essential requirement in terms of environmental planning and management. To protect and manage water resources effectively, it is necessary to develop an analytical decision-support system. In this study, a systematic approach was suggested to evaluate the lake water quality. The methodology includes the prediction of the values in different locations of the lakes from experimental data through inverse distance weighting (IDW) method, creation of maps by using Geographic Information System (GIS) integrated with analytic hierarchy process (AHP) from multi-criteria decision analysis (MCDA), reclassification into five class, combining the time-related spatial data into a single map to predict the whole lake water quality from the data of sampling points, and finally overlapping the final maps with topography/geology and land use. The proposed approach was verified and presented as case study for Meke and Acigol Lakes in Konya/Turkey which were affected by human and natural factors although they have ecological, hydromorphological, and socio-economic importance. In the proposed approach, categorizing water quality parameters as "hardness and minerals," "substrates and nutrients," "solids content," "metals," and "oil-grease" groups was helpful for AHP with the determined group weights of 0.484, 0.310, 0.029, and 0.046, respectively. Assigning weights within each group and then assigning weights between groups resulted in creating accurate final map. The proposed approach is flexible and applicable to any lake water quality data; even with a limited number of data, the whole lake water quality maps could be created for assessment.

Modelling of corrosion rate in the drinking water distribution network using Design Expert 13 software

This study is focused on the modelling of the composite effect of corrosion factors using Design Expert 13 software on the corrosion rate in the water distribution network of Patna (Bihar), India. A total of nine variables, including pH, temperature, total dissolved solid (TDS), alkalinity, calcium hardness, chloride, sulphate, dissolved oxygen (DO) and time, were considered for modelling. The physicochemical parameters were determined through regular monitoring of water samples. The corrosion rate was determined by the direct monitoring of water distribution pipes using adjustments of seven GI coupons for 45, 90, 135, 180, 225, 270 and 315 days. Modelling was performed for various corrosion factors using the low-level and high-level experimental ranges. Nine of the corrosion factors, i.e. pH, temperature, TDS, alkalinity, calcium hardness, chloride, sulphate, DO and time, were considered in this study. The data used for low-level and high-level range were 7.28, 23, 430, 115, 24, 18, 10.94, 3.5 and 0 and 7.86, 28, 704, 284, 180, 98, 38.7, 6.8 and 315, respectively. Using the Box-Behnken design (BBD), 160 runs were conducted, including ten replicates at the central point of each block. The results of ANOVA indicate that the values of R², adjusted R² and predicted R² are 0.9714, 0.9507 and 0.8941, respectively. The value of R² (0.9714) was close to 1, which indicates a good fit. The adequate precision was found to be 30.8442, indicating a good signal. The coefficient of variance discusses reproducibility, and in this case, it was 9.90%. On the basis of the ANOVA result, the quadratic model is well-fitted and can be accepted as a suitable model. A total of seven parameters, such as chloride, sulphate, hardness, alkalinity, pH, calcium and hardness, were used for the design of the experimental corrosion rate (CR). Corrosion rate as observed by direct monitoring of the water distribution system was 1.37, 3.08, 1.90, 1.38, 1.09, 2.05 and 1.45 MPY for 45, 90, 135, 180, 225, 270 and 315 days, respectively. These individual CR versus synthetic aqueous solutions were used to validate the interaction of the response surface. It was observed that the trend of individual corrosion rates in synthetic aqueous solutions and the interaction of composite variables with corrosion rates in a quadratic model of response surfaces were clearly correlated.

Impact of leachate on quality of ground water around Chunga Landfill, Lusaka, Zambia and possible health risks

We report the characteristics and possible impact of leachate on quality of groundwater in the Chunga Landfill area of Lusaka, Zambia. Water and leachate samples were collected within and around the landfill for analysis. The pH, biological oxygen demand (BOD), chemical oxygen demand (COD), nitrates, sulphates, chlorides for the leachate and groundwater samples were (6.6 ± 0.1 to 8.7 ± 0.0), (1.7 ± 0.3 to 1,569.6 ± 4.9 mg/L), (4.0 ± 0.0 to 10,378.5 ± 59.2 mg/L), (8.0 ± 0.0 to 37.7 ± 0.4 mg/L), (11.7 ± 0.0 to 273.1 ± 1.7 mg/L), (43.0 ± 1.2 to 974.2 ± 0.8 mg/L) respectively. Heavy metal concentration ranges were cadmium (0.004 ± 0.000 to 1.149 ± 0.021 mg/L, chromium (0.007 ± 0.000 to 2.699 ± 0.039 mg/L), copper (0.013 ± 0.002 to 0.246 ± 0.005 mg/L), lead (0.062 ± 0.005 to 2.591 ± 0.065 mg/L) and zinc (0.008 ± 0.001 to 2.032 ± 0.017 mg/L). The pH of the leachate (8.5 ± 0.0 to 8.7 ± 0.0) meant the landfill was in the methane fermentation phase. An indexing approach was used with the leachate pollution index (LPI) of 30.173, heavy metal pollution index (HPI) of 3,938.92. The heavy metal index (HMI) for copper, lead, chromium, cadmium and zinc were found to be 0.92, 1,124.19, 47.20, 994.17 and 1.48 respectively. Principal component analysis (PCA) showed that anthropogenic activities contributed to pollution with high loading values. Ash from continuous burning of the waste may provide alkalinity which reduces leachate BOD and COD. Results showed that the landfill has outgrown the designed cells capacity as not all leachate was collected by the under-drainage. Results also showed that lack of adequate landfill cover significantly increases rainfall infiltration thereby increasing volumes of leachate produced with a, hence potential for underground water contamination and a human health and environmental problem.

Quality assessment and prediction of municipal drinking water using water quality index and artificial neural network: A case study of Wuhan, central China, from 2013 to 2019

The sanitary security of drinking water is closely related to human health, but its quality assessment mainly focused on limited types of indicators and relatively restricted time span. The current study was aimed to evaluate the long-term spatial-temporal distribution of municipal drinking water quality and explore the origin of water contamination based on multiple water indicators of 137 finished water samples and 863 tap water samples from Wuhan city, China. Water quality indexes (WQIs) were calculated to integrate the measured indicators. WQIs of the finished water samples ranged from 0.24 to 0.92, with the qualification rate and excellent rate of 100 % and 96.4 %, respectively, while those of the tap water samples ranged from 0.09 to 3.20, with the qualification rate of 99.9 %, and excellent rate of 95.5 %. Artificial neural network model was constructed based on the time series of WQIs from 2013 to 2019 to predict the water quality thereafter. The predicted WQIs of finished and tap water in 2020 and 2021 qualified on the whole, with the excellent rate of 87.5 % and 92.9 %, respectively. Except for three samples exceeding the limits of free chlorine residual, chloroform and fluoride, respectively, the majority of indicators reached the threshold values for drinking. Our study suggested that municipal drinking water quality in Wuhan was generally stable and in line with the national hygiene standards. Moreover, principal component analysis illustrated that the main potential sources of drinking water contamination were inorganic salts and organic matters, followed by pollution from distribution systems, the use of aluminum-containing coagulants and turbidity involved in water treatment, which need more attention.