Digital twins, a nascent yet potent computer technology, can substantially advance
sustainable ocean management by mitigating overfishing and habitat degradation …

Water quality deterioration in drinking water systems (ie, system failure) causing serious
outbreaks have frequently been happening around the world. These failures can be …

Marine oil spill response is a time sensitive and complex task, in which the management of
oily wastewater generated from response operations could be a bottleneck limiting the …

Monitoring emerging disinfection byproducts (DBPs) is challenging for many small water
distribution networks (SWDNs), and machine learning-based predictive modeling could be …

This study employs fuzzy regression and fuzzy multivariate clustering techniques to analyze
arsenic-polluted water samples originating from acid rock drainage in waste rock dumps …

Abstract Water/wastewater ((waste) water) disinfection, as a critical process during drinking
water or wastewater treatment, can simultaneously inactivate pathogens and remove …

The absence of nationwide distribution data regarding heavy metal emissions into the
atmosphere poses a significant constraint in environmental research and public health …

A quantitative understanding of spilled oil transport in a nearshore environment is
challenging due to the complex physicochemical processes in aqueous conditions. The …

Applying machine learning (ML) and fuzzy inference systems (FIS) requires large datasets to
obtain more accurate predictions. However, in the cases of oil spills on ground …

Over the past two decades, oil spills have been one of the most serious ecological disasters,
causing massive damage to the aquatic and terrestrial ecosystems as well as the socio …