Heavy metal-contained wastewater in China: Discharge, management and treatment
Q Li, G Liu, L Qi, H Wang, Z Ye, Q Zhao - Science of the Total Environment, 2022 - Elsevier
A large amount of heavy metal-contained wastewater (HMW) was discharged during
Chinese industry development, which has caused many environmental problems. This study …
Chinese industry development, which has caused many environmental problems. This study …
A review on biofiltration techniques: recent advancements in the removal of volatile organic compounds and heavy metals in the treatment of polluted water
R Pachaiappan, L Cornejo-Ponce, R Rajendran… - …, 2022 - Taylor & Francis
Good quality of water determines the healthy life of living beings on this earth. The
cleanliness of water was interrupted by the pollutants emerging out of several human …
cleanliness of water was interrupted by the pollutants emerging out of several human …
Competitive sorption of Cd, Cr, Cu, Ni, Pb and Zn from stormwater runoff by five low-cost sorbents; Effects of co-contaminants, humic acid, salinity and pH
For a comprehensive estimation of metals removal by sorbents in stormwater systems, it is
essential to evaluate the impacts of co-contaminants. However, most studies consider only …
essential to evaluate the impacts of co-contaminants. However, most studies consider only …
Navigating the molecular landscape of environmental science and heavy metal removal: A simulation-based approach
Heavy metals pose a significant threat to ecosystems and human health because of their
toxic properties and their ability to bioaccumulate in living organisms. Traditional removal …
toxic properties and their ability to bioaccumulate in living organisms. Traditional removal …
Mathematical modeling and machine learning-based optimization for enhancing biofiltration efficiency of volatile organic compounds
Biofiltration is a method of pollution management that utilizes a bioreactor containing live
material to absorb and destroy pollutants biologically. In this paper, we investigate …
material to absorb and destroy pollutants biologically. In this paper, we investigate …
[HTML][HTML] Predicting the performance of green stormwater infrastructure using multivariate long short-term memory (LSTM) neural network
The expected performance of Green Stormwater Infrastructure (GSI) is typically quantified
through numerical models based on hydrologic parameters and physics-based equations …
through numerical models based on hydrologic parameters and physics-based equations …
Utilizing machine learning to evaluate heavy metal pollution in the world's largest mangrove forest
The world's largest mangrove forest (Sundarbans) is facing an imminent threat from heavy
metal pollution, posing grave ecological and human health risks. Develo** an accurate …
metal pollution, posing grave ecological and human health risks. Develo** an accurate …
Metal bioleaching from printed circuit boards by bio-Fenton process: Optimization and prediction by response surface methodology and artificial intelligence models
Recycling printed circuit boards (PCBs) in the e-waste stream is essential for ecological
protection and metal recycling for a circular economy. Efficient metal recovery from PCBs is …
protection and metal recycling for a circular economy. Efficient metal recovery from PCBs is …
Using Random Forest, a machine learning approach to predict nitrogen, phosphorus, and sediment event mean concentrations in urban runoff
Estimating pollutant loads from developed watersheds is vitally important to reduce nonpoint
source pollution from urban areas, as a key tool in meeting water quality goals is the …
source pollution from urban areas, as a key tool in meeting water quality goals is the …
Machine learning for heavy metal removal from water: recent advances and challenges
Research on the removal of heavy metals (HMs) from contaminated waters, aiming at
ensuring the safety of water bodies, has shifted from direct experimental tests to machine …
ensuring the safety of water bodies, has shifted from direct experimental tests to machine …