Assessment of drinking water quality on public health at Alappuzha district, southern Kerala, India

Kumari

et al. 2023

Environ Sci Pollut Res

The current investigation primarily concerns groundwater potability and irrigational value in the urban area of Patna.Hydrogeochemical processes in uence human health by controlling the quality of groundwater. In this research, we evaluated the interplay between several measures of groundwater quality, the various possible causes of groundwater pollution, and the resulting health risks. Twenty groundwater samples were taken from various locations and examined to determine the water quality. Groundwater and associated geochemical processes in the study area were analyzed using statistical methods, geochemical modelling, and graphical representations. The average EC of the groundwater in the examined area was 728.13 ± 331.84 µS/cm, with a range of around 300-1700 µS/cm. Positive loadings were seen for Total Dissolved Solid (TDS), Electrical Conductivity (EC), Calcium (Ca 2+ ), Magnesium (Mg 2+ ), Sodium (Na + ), Chloride (Cl − ), and Sulphate (SO 4 2− ) in principal component analysis (PCA), demonstrating that these variables accounted for 61.78% of the total variance. In the groundwater samples, the following main cations are the most prevalent such as Na + > Ca 2+ > Mg 2+ > K + , while the dominant anions are HCO 3 − > Cl − > SO 4 2− . The elevated HCO 3 − and Na + ions indicate that carbonate mineral dissolution might affect the study area. The result demonstrated that there are 70% of samples fall into the Na-Cl-SO 4 type, 15% of samples fall into mixed Ca-Na-HCO 3 type, and 5% of samples that fall into the mixed Ca-Mg-Cl type and Na-HCO 3 type, and no samples that fall into the Ca-Cl type. The ndings make it abundantly evident that the primary groundwater salinity is far higher than the secondary salinity produced because of the weathering of the bedrock. The presence of the NaHCO 3 kind of water is suggestive of shallow meteoric water, which may have originated from the river Ganga that is located nearby. The interactions between water and rock could have naturally resulted in the creation of these clusters inside the aquifer matrix. The results show that a multivariate statistical analysis, graphical plots, and geochemical modelling successfully identify the parameters controlling groundwater quality.

Section: Health Risk Assessmentmentioning

confidence: 99%

Assessing the geochemical processes controlling groundwater quality and their possible effect on human health in Patna, Bihar

Kumari

et al. 2023

Environ Sci Pollut Res

“…In those areas, such information may be used to target waste reduction and recycle efforts. These algorithms may assist municipalities in planning and implementing waste reduction and recycling programs precisely adapted to the individual needs of their communities, by determining generation volumes, quantities, or areas with significant waste [9].…”

Section: Heavy Waste Generation Area Predictionmentioning

confidence: 99%

“…The non-linear autoregressive exogenous model (NARX) is a type of neural network specifically designed for modelling non-linear time-series data. It incorporates recurrent feedback connections from other layers within the network, allowing it to capture complex patterns and relationships [9]. In this study, we utilized the NARX model as a baseline to evaluate the performance of our proposed method.…”

Section: Prediction Of Waste Generation Using Narx Modelmentioning

confidence: 99%

Municipal Solid Waste Management: A Review of Machine Learning Applications

Pillai,

M L,

et al. 2023

E3S Web Conf.

This study comprises of an analysis of various Machine Learning (ML) algorithms for municipal solid waste management to enhance waste management procedures and reduce the adverse environmental effects. The increasing population has resulted in substantial environmental hazards due to increased waste generation. Therefore, an effective waste management system with much more efficient and innovative waste management techniques is required to reduce the adverse effects that would occur due to the generation of massive waste. This study reviews various ML algorithms to automate and optimize garbage generation, collection, transportation, treatment, and disposal. To deliver and predict effective and precise waste generation, segregation, and collection forecasts, the system integrates multiple ML methods including decision trees (DT), k-nearest neighbours (KNN), support vector machines (SVM), random forests (RF), and clustering algorithms.

“…Water is used in drinking, bathing, cleaning, and food preparation, and it can be a medium for the presence and  ISSN: 2252-8806 transmission of pathogens, microorganisms, and chemical contaminants. Therefore, ingestion of contaminated water can lead to serious waterborne illnesses and even death [8]. From the stated facts, routine monitoring and evaluation of water alkalinity, especially for potable water is important.…”

Section: Introductionmentioning

confidence: 99%

“…A standard method for determining alkalinity is the titration of the sample with a standard acid solution using a pH indicator solution [8]. In seawater and natural terrestrial waters, the alkalinity can be analyzed using a spectrophotometric technique using a bromocresol green indicator.…”

Section: Introductionmentioning

confidence: 99%

RGB-based colorimetric method for the analysis of water alkalinity using Cordyline fruticosa extracts as visual indicator

Parungao,

Reyes

2024

IJPHS

Leaf extracts of Cordyline fruticosa was used as a natural visual indicator for a digital image-based analytical procedure for the measurement of water alkalinity. A smartphone and ImageJ were used to capture and process the images, respectively. This work sought to develop and evaluate a greener strategy of using of Cordyline fruticosa leaf extract as natural indicator, in a digital image-based colorometric set-up using smartphone. Under optimized conditions, the linear working range was from 40 to 160 ppm of CaCO3, with a calibration sensitivity of 5 x 10-3 ppm and a coefficient of correlation (r2) = 0.998. The limit of detection and quantification were 39 ppm and 117 ppm, respectively. A 10,000 ppm CaCO3 solution was tested using the proposed method and the results statistically agree with the results obtained from titrimetric methods. The study presented a simple analytical procedure that can be develop and apply for the assessment of pollution that could pose serious human and environmental health hazards.