AIMC Topic: Drinking Water

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Machine learning-guided prediction of chlorinated/chloraminated disinfection by-product formation in drinking water treatment.

Water research
Chlorination and chloramination as common water disinfection methods are challenged by the unintended formations of hazardous disinfection by-products (DBPs). Accurately predicting DBP formation is essential for improving water treatment processes an...

Prediction of trihalomethane occurrence and cancer risk using interpretable machine learning and virtual data augmentation.

Journal of hazardous materials
Trihalomethanes (THMs) in drinking water are regulated for carcinogenic health risks. However, frequent water quality monitoring imposes significant resource burdens. This study proposes a framework integrating interpretable machine learning (ML) wit...

A Comprehensive Exploration of Groundwater Quality of Ambagarh Chowki Region, Chhattisgarh, India: Water Quality Index, Health Risk, and ANN Predictive Modeling.

Water environment research : a research publication of the Water Environment Federation
Access to safe and clean drinking water remains a critical global challenge, with groundwater as a primary source for billions of people. Further, toxic contaminants increasingly threaten groundwater quality, posing significant health risks. This stu...

Sustainable water allocation under climate change: Deep learning approaches to predict drinking water shortages.

Journal of environmental management
Addressing sustainable urban water supply has become one of the most critical challenges for modern megacities, particularly in arid and semi-arid regions where rapid urbanization and climate change converge to exacerbate resource scarcity. Tehran, a...

Enhancing drinking water safety: Real-time prediction of trihalomethanes in a water distribution system using machine learning and multisensory technology.

Ecotoxicology and environmental safety
Prolonged exposure to high concentrations of trihalomethanes (THMs) may generate human health risks due to their carcinogenic and mutagenic properties. Therefore, monitoring THMs in drinking water distribution systems (DWDS) is essential. This study ...

A machine learning approach to estimate domestic use of public and private water sources in the United States.

Water research
In the United States, people obtain water for household use from one of two sources. Public water systems, which are subject to rules and regulations under the Safe Drinking Water Act, or private sources such as domestic wells, which are not subject ...

ArsenicNet: An efficient way of arsenic skin disease detection using enriched fusion Xception model.

PloS one
Arsenic contamination of drinking water is a significant health risk. Countries such as Bangladesh's rural areas and regions are in the red alert zone because groundwater is the only primary source of drinking. Early detection of arsenic disease is c...

[SERUM THYROGLOBULIN LEVELS AND ESTIMATED IODINE INTAKE IN ADULTS EXPOSED TO IODINE‑DILUTED DESALINATED DRINKING WATER].

Harefuah
AIMS: The aim of this study was to describe thyroglobulin levels and iodine intake estimations in a convenience sample of Israeli adults without TD in the Ashkelon District, where SWRO desalination has become the major source of drinking water.

[Determination of trace and ultra-trace level bromate in water by large volume sample injection with enrichment column for on-line preconcentration coupled with ion chromatography].

Se pu = Chinese journal of chromatography
A method for the determination of trace and ultra-trace level bromate in water by ion chromatography with large volume sample injection for on-line preconcentration was established. A high capacity Dionex IonPac AG23 guard column was simply used as t...