Performance analysis of machine learning algorithms for the prediction of disinfection byproducts formation during chlorination: Effect of background water characteristics.

This study investigated the comparison of the nonlinear machine learning algorithms and linear regression models to predict the formation of trihalomethanes (THM4), haloacetic acids (HAA5 and HAA9), and haloacetonitriles (HAN4 and HAN6) under uniform formation conditions in chlorinated waters. A wide range of water sources including wastewater effluent organic matters (EfOM), laboratory grown algal organic matters (AOM) samples from different algal species, and raw/treated/isolated natural organic matter (NOM) samples were selected to investigate background water effect on the model performance. Models for THM4, HAA5, HAA9, HAN4 and HAN6 formation were developed for all water sources combined (including NOM, AOM, and EfOM-impacted waters) and for NOM separately.

Predicting full-scale performance of adsorbents for per- and polyfluoroalkyl substances adsorption: The role of rapid small-scale column tests.

Per- and polyfluoroalkyl substances (PFAS) pose persistent environmental and health challenges, requiring the development of effective removal strategies. Rapid Small-Scale Column Tests (RSSCTs) provide a cost-effective approach to evaluating the performance of adsorbents for PFAS removal. Current literature emphasized that the chain length of PFAS tails and the functional groups of PFAS heads play a crucial role in breakthrough behavior, with shorter chains and carboxylate PFAS leading to earlier breakthroughs.

Statistical modeling for iodinated trihalomethanes: Preformed chloramination versus prechlorination followed by ammonia addition.

Developing predictive models for iodo-trihalomethane (I-THM) formation in water is needed and valuable to minimize extensive and costly analysis. The main objective of this study was to develop a statistical model for the formation of six types of I-THMs under uniform formation conditions. Prediction of I-THM formation in two different water sources (natural organic matter [NOM] and algal organic matter [AOM]) were comprehensively evaluated during both preformed chloramination and prechlorination followed by ammonia addition conditions.

Comparative study on electro-regeneration of antibiotic-laden activated carbons in reverse osmosis concentrate.

Electro-regeneration is emerging as a new technique to regenerate spent carbon adsorbents through an electrochemical process. In this study, sequential adsorption and electro-regeneration of ciprofloxacin (CIP)-laden carbon were investigated using both pristine and iron (Fe)-doped F400 activated carbon in distilled, deionized (DI) water and reverse osmosis (RO) concentrate water. The impact of reactor flow rate and sequential adsorption/electro-regeneration cycles on the regeneration efficiency were also evaluated.

Enhancing the selective ciprofloxacin adsorption in urine matrices through the metal-doping of carbon sorbents.

Pharmaceuticals excreted after administration can pollute water sources given their ineffective removal in conventional wastewater treatment plant. Among the techniques used during tertiary wastewater treatment, adsorption is an effective and cost-efficient method for removing antibiotics. This study aimed to investigate the adsorption of ciprofloxacin (CIP) on metal-doped granular activated carbon (GAC) and evaluate the impact of urine on CIP adsorption for pristine, pre-oxidized, and metal-doped GAC.

Emerging investigator series: microplastic sources, fate, toxicity, detection, and interactions with micropollutants in aquatic ecosystems - a review of reviews.

Hundreds of review studies have been published focusing on microplastics (MPs) and their environmental impacts. With the microbiota colonization of MPs being firmly established, MPs became an important carrier for contaminants to step inside the food web all the way up to humans. Thus, the continuous feed of MPs into the ecosystem has sparked a multitude of scientific concerns about their toxicity, characterization, and interactions with microorganisms and other contaminants.

Adsorption modeling of organic compounds (OCs) by carbon nanotubes (CNTs): role of OC and CNT properties on the linear solvation energy relationship.

This study evaluated a comprehensive database for the adsorption of polar and nonpolar organic compounds (OCs) by carbon nanotubes (CNTs) and to use the linear solvation energy relationship (LSER) technique for developing predictive adsorption models of OCs by multi-walled carbon nanotubes (MWCNTs) and single-walled carbon nanotubes (SWCNTs). The results showed that coefficient of determinations (R) values for all compounds are higher variability in the 200 g/mol molecular weight cutoff (74-99%). When the molecular weight cutoff of all OCs is higher than 200 g/mol, the trend of their R values is decreased (less than 70%).

Predictive modeling of haloacetonitriles under uniform formation conditions.

The objective of this study was to develop models to predict the formation of HANs under uniform formation conditions (UFC) in chlorinated, choraminated, and perchlorinated/chloraminated waters of different origins. Model equations were developed using multiple linear regression analysis to predict the formation of dichloroacetonitrile (DCAN), HAN4 (trichloroacetonitrile [TCAN], DCAN, bromochloroacetonitrile [BCAN], and dibromoacetonitrile [DBAN]) and HAN6 (HAN4 plus monochloroacetonitrile, monobromoacetonitrile). The independent variables covered a wide range of values, and included ultraviolet absorbance,(UV) dissolved organic carbon (DOC), dissolved organic nitrogen (DON), specific UV absorbance at 254 (SUVA), bromide (Br), pH, oxidant dose, contact time, and temperature.

Adsorption kinetics and aggregation for three classes of carbonaceous adsorbents in the presence of natural organic matter.

In this study, adsorption kinetics of phenanthrene (PNT) and trichloroethylene (TCE) by a graphene nanosheet (GNS), a graphene oxide nanosheet (GO), a single-walled carbon nanotube (SWCNT), a multi-walled carbon nanotube (MWCNT), and two coal based activated carbons (ACs) (F400 and HD3000) were examined in distilled and deionized water (DDW) and under natural organic matter (NOM) preloading conditions. The results showed the times needed for the adsorption of PNT and TCE to reach apparent equilibrium (i.e.

Predictive models for adsorption of organic compounds by Graphene nanosheets: comparison with carbon nanotubes.

The Linear Solvation Energy Relationships (LSER) technique was applied in the present study for predicting models of organic compounds (OCs) adsorption by Graphene and Graphene oxide (GO), and the results were compared with those of multi-walled carbon nanotube (MWCNT) and single-walled carbon nanotube (SWCNT). Adsorption database of 38 OCs (28 aromatic and 10 aliphatic) for Graphene and 69 OCs (59 aromatic and 10 aliphatic) for GO were collected from the literature and our laboratory. The r of the LSER models on the adsorption of aromatic OCs by Graphene and GO at three different equilibrium concentrations gradually increased up to OC molecular weight of 400 g/mol, after which a declining trend was observed for GO, while there was no visible change for Graphene.

Adsorption of organic contaminants by graphene nanosheets: A review.

Graphene nanosheets (GNS) such as graphenes and graphene oxides (GOs) have been widely investigated as next-generation adsorbents in both water and wastewater treatment processes due to their unique physicochemical properties and their affinity towards different classes of organic contaminants (OCs). In the last five years, more than 40 articles investigating adsorption of different classes of OCs by graphene and GO were published in peer-reviewed journals. Adsorption mechanisms were controlled by molecular properties of OCs (e.

Removal of intra- and extracellular microcystin by submerged ultrafiltration (UF) membrane combined with coagulation/flocculation and powdered activated carbon (PAC) adsorption.

In this study, we investigated the performance of conventional (coagulation/flocculation→powdered activated carbon [PAC] adsorption) and advanced treatment (coagulation/flocculation→PAC adsorption→submerged ultrafiltration [UF] membrane) processes separately and sequentially for the removal of total (intra- and extracellular) microcystin. Results of the conventional treatment process demonstrated that coagulation/flocculation alone was not effective (up to 70%) for the removal of total microcystin, while the uptake of total microcystin was achieved up to 84% by PAC adsorption (PAC dose of 20mg/L). In addition, the adsorption kinetic mechanism of PAC was also examined using several kinetic models.

Adsorption of organic contaminants by graphene nanosheets, carbon nanotubes and granular activated carbons under natural organic matter preloading conditions.

The effect of NOM preloading on the adsorption of phenanthrene (PNT) and trichloroethylene (TCE) by pristine graphene nanosheets (GNS) and graphene oxide nanosheet (GO) was investigated and compared with those of a single-walled carbon nanotube (SWCNT), a multi-walled carbon nanotube (MWCNT), and two coal based granular activated carbons (GACs). PNT uptake was higher than TCE by all adsorbents on both mass and surface area bases. This was attributed to the hydrophobicity of PNT.

Linear solvation energy relationships (LSER) for adsorption of organic compounds by carbon nanotubes.

The objective of this paper was to create a comprehensive database for the adsorption of organic compounds by carbon nanotubes (CNTs) and to use the Linear Solvation Energy Relationship (LSER) technique for developing predictive adsorption models of organic compounds (OCs) by multi-walled carbon nanotubes (MWCNTs) and single-walled carbon nanotubes (SWCNTs). Adsorption data for 123 OCs by MWCNTs and 48 OCs by SWCNTs were compiled from the literature, including some experimental results obtained in our laboratory. The roles of selected OCs properties and CNT types were examined with LSER models.