Survey on the resolution and accuracy of input data validity for SWAT-based hydrological models.

This review was conducted to highlight the most influential factors and specify the trends reducing uncertainty and increasing the accuracy of soil and water assessment tool (SWAT)-based hydrological models. Although the resolution of input data on the results of SWAT-based hydrological models has been extensively determined. There is still a gap in providing comprehensive review framework to be emerged for identifying the impact of the data resolution and accuracy.

Machine learning predictive insight of water pollution and groundwater quality in the Eastern Province of Saudi Arabia.

This study presents an innovative approach for predicting water and groundwater quality indices (WQI and GWQI) in the Eastern Province of Saudi Arabia, addressing critical challenges of scarcity and pollution in arid regions. Recent literature highlights the increasing attention towards WQI based on water pollution index (WPI) and GWQI as essential tools for simplifying complex hydrogeological data, thereby facilitating effective groundwater management and protection. Unlike previous works, the present research introduces a novel hybrid method that integrates non-parametric kernel Gaussian learning (GPR), adaptive neuro-fuzzy inference system (ANFIS), and decision tree (DT) algorithms.

Tracking the impact of heavy metals on human health and ecological environments in complex coastal aquifers using improved machine learning optimization.

The rising heavy metal (HM) pollution in coastal aquifers in rapidly urbanizing areas such as Dammam leads to significant risks to public health and environmental sustainability, challenging compliance with Environmental Protection Agency (EPA) guidelines, World Health Organization (WHO) standards, and Sustainable Development Goals (SDGs) related to clean water and life on land. This study developed the predictive-based monitoring of HM concentrations, including cadmium (Cd), chromium (Cr), and mercury (Hg) in the coastal aquifers of Dammam, influenced by industrial, agricultural, and urban activities. For this purpose, dynamic system identification and machine learning (ML) models integrated with three ensemble techniques, namely, simple averaging (SAE), weighted averaging (WAE), and neuro-ensemble (N-ESB), were employed to enhance the accuracy, reliability, and efficiency of environmental monitoring systems.

Observed and future shifts in climate zone of Borneo based on CMIP6 models.

Climate change has significantly altered the characteristics of climate zones, posing considerable challenges to ecosystems and biodiversity, particularly in Borneo, known for its high species density per unit area. This study aimed to classify the region into homogeneous climate groups based on long-term average behavior. The most effective parameters from the high-resolution daily gridded Princeton climate datasets spanning 65 years (1950-2014) were utilized, including rainfall, relative humidity (RH), temperatures (Tavg, Tmin, Tmax, and diurnal temperature range (DTR)), along with elevation data at 0.

The role of environmental trace element toxicants on autism: A medical biogeochemistry perspective.

Since genetic factors alone cannot explain most cases of Autism, the environmental factors are worth investigating as they play an essential role in the development of some cases of Autism. This research is a review paper that aims to clarify the role of the macro elements (MEs), Trace elements (TEs) and ultra-trace elements (UTEs) on human health if they are greater or less than the normal range. Aluminium (Al), cadmium Cd), lead (Pb), chromium (Cr), zinc (Zn), copper (Cu), nickel (Ni), arsenic (As), mercury (Hg), manganese (Mn), and iron (Fe) have been reviewed.

Gas Phase Toluene Adsorption Using Date Palm-Tree Branches Based Activated Carbon.

Activated carbon that has been widely used for several environmental applications is typically produced from carbon-based raw materials including agricultural by-products. To that end, extensive date palm-tree farming across the globe with millions of palm trees, also results in various types of agricultural waste including date palm-tree branches (DPB) during the regular trimming phase of palm-trees. Furthermore, air pollution also remains a serious concern in many global regions, requiring the application of appropriate treatment technologies to mitigate the respective negative effects on human health and environment.

Predicting risk and loss of disability-adjusted life years (DALY) from selected disinfection byproducts in multiple water supply sources in Saudi Arabia.

Disinfection byproducts (DBPs) in drinking water is an issue in many countries. Many DBPs are possible or probable human carcinogens while few DBPs pose cyto- and genotoxic effects to the mammalian cells. The populations are likely to consume DBPs with drinking water throughout their lifetimes.

Human exposure and risk of trihalomethanes during continuous showering events.

Exposure to disinfection byproducts (DBPs) in municipal water mainly occurs through ingestion, inhalation during showering, house cleaning and dermal permeation. While showering, the air-phase DBPs [e.g.

Reduction of DBPs in synthetic water by indoor techniques and its implications on exposure and health risk.

Disinfection byproducts (DBPs) in municipal supply water have been a concern. Many DBPs have been characterized as possible and probable human carcinogens, which can pose elevated cancer risks through lifetime exposure to municipal supply water. Few DBPs are regulated in many countries to control human exposure and risk from DBPs.