Treatment Trends and Combined Methods in Removing Pharmaceuticals and Personal Care Products from Wastewater-A Review

Behavior space-temporal of biofilters based on hazelnut shells/sawdust treating pharmaceutical and personal care products from domestic wastewater

Nature-based solutions (NBS) such as biofiltration are an efficient, eco-friendly, and economical alternative for wastewater treatment under decentralized contexts. However, the influence on removing emerging contaminants (pharmaceuticals and personal care products or PPCPs), considering different typologies and seasonality fate, has been little studied. In this work, four lab-scale biofiltration typologies (BM: Biofilter + microorganisms, BEM: Biofilter + earthworms + microorganisms, BH: Biofilter + microorganisms + plants + earthworms or Biofilter hybrid, BPM: Biofilter + plants + microorganisms) were monitored seasonally (April-December, 250 days), being fed with rural domestic wastewater. Zantedeschia aethiopica (L.) and Eisenia foetida Savigny were used as biotic components, interacting with organic support components (hazelnut shells and sawdust) for removal of organic matter, nutrients, and 4 PPCPs (caffeine, ibuprofen, losartan, and triclosan). The mass balance of PPCPs was carried out considering the input (influent), output (effluent), support (soil), and plant (root and stem/leaf). The results showed that the different evaluated typologies removed close to 100 % COD, up to 89 % NH4+-N, and up to 99 % coliforms. Meanwhile, caffeine, ibuprofen, losartan, and triclosan were removed between 34 and 100 %. Seasonality or biofiltration typology was non-significantly influential (p > 0.05). However, biofilter hybrid and the warm season were the most efficient for removing organic matter, nutrients, coliforms, and PPCPs. The PPCPs' fate was plants/substrate/effluent with values up to 36, 95, and 64 %, respectively. The effluent was caffeine's main fate. Substrate was the main fate of ibuprofen, losartan, and triclosan. Plants uptake caffeine as a carbon source.

Ecotoxicity mitigation and biodegradability enhancement during sulfamethazine removal by a pilot-scale rotating advanced oxidation contactor equipped with TiO2-zeolite composite sheets

This study investigated the ecotoxicity mitigation, biodegradability enhancement performance, and underlying mechanisms in treating sulfamethazine (SMT) using a pilot-scale rotating advanced oxidation contactor (RAOC) equipped with TiO2-zeolite composite sheets, which adsorbed and photocatalytically decomposed SMT and hydrophobic degradation intermediates. For the ecotoxicity evaluation, the green microalga Scenedesmus obliquus was cultured with treated SMT solution. The 96-h growth inhibition ratio was initially 53.3% but then dropped to nearly 0 after 96 h of RAOC treatment under ultraviolet irradiation, which showed that RAOC treatment effectively eliminated ecotoxicity. Both theoretical predictions using ECOSAR and experimental validation showed that 4-amino-2,6-dimethylpyrimidine, an intermediate with higher toxicity than SMT, contributed to the increased toxic effect as SMT removal neared completion. We also found that the specific content of chlorophyll a (0.55%-0.90% g-chlorophyll/g-biomass) was sensitive to toxic stress caused by SMT and the intermediates, whereas that of chlorophyll b (0.42%-0.58%) did not show a substantial correlation. Comprehensive analyses of the 5-day biochemical oxygen demand (BOD5) and total organic carbon (TOC) in the treated solution showed consistent improvement in biodegradability throughout the treatment. This also suggested efficient degradation and mitigation of the toxic effects of SMT and its degradation intermediates on microbes. Furthermore, comparison with TiO2 sheets showed that TiO2-zeolite composite sheets were superior in terms of both SMT removal and ecotoxicity mitigation.

A machine learning framework to predict PPCP removal through various wastewater and water reuse treatment trains

The persistence of pharmaceuticals and personal care products (PPCPs) through wastewater treatment and resulting contamination of aquatic environments and drinking water is a pervasive concern, necessitating means of identifying effective treatment strategies for PPCP removal. In this study, we employed machine learning (ML) models to classify 149 PPCPs based on their chemical properties and predict their removal via wastewater and water reuse treatment trains. We evaluated two distinct clustering approaches: C1 (clustering based on the most efficient individual treatment process) and C2 (clustering based on the removal pattern of PPCPs across treatments). For this, we grouped PPCPs based on their relative abundances by comparing peak areas measured via non-target profiling using ultra-performance liquid chromatography-tandem mass spectrometry through two field-scale treatment trains. The resulting clusters were then classified using Abraham descriptors and log K ow as input to the three ML models: support vector machines (SVM), logistic regression, and random forest (RF). SVM achieved the highest accuracy, 79.1%, in predicting PPCP removal. Notably, a 58-75% overlap was observed between the ML clusters of PPCPs and the Abraham descriptor and log K ow clusters of PPCPs, indicating the potential of using Abraham descriptors and log K ow to predict the fate of PPCPs through various treatment trains. Given the myriad of PPCPs of concern, this approach can supplement information gathered from experimental testing to help optimize the design of wastewater and water reuse treatment trains for PPCP removal.

Decomposition of metal-organic complexes and metal recovery in wastewater: A systematic review and meta-synthesis

Metals are rarely found as free ions in natural and anthropogenic environments, but they are often associated with organic matter and minerals. Under the context of circular economy, metals should be recycled, yet they are difficult to extract for their complex forms in real situations. Based on the protocols of review methodology and the analysis of VOS viewer, there are few reviews on the properties of metal-organic complexes, decomplexation methods, the effect of coexisting ions, the pH influence, and metal recovery methods for the increasingly complicated metal-organic complexes wastewater. Conventional treatment methods such as flocculation, adsorption, biological degradation, and ion exchange fail to decompose metal-organic complexes completely without causing secondary pollution in wastewater. To enhance comprehension of the behavior and morphology exhibited by metal-organic complexes within aqueous solutions, we presented the molecular structure and properties of metal-organic complexes, the decomplexation mechanisms that encompassed both radical and non-radical oxidizing species, including hydroxyl radical (OH), sulfate radical (SO˙4-), superoxide radical (O˙2-), hydrogen peroxide (H2O2), ozone (O3), and singlet oxygen (1O2). More importantly, we reviewed novel aspects that have not been covered by previous reviews considering the impact of operational parameters and coexisting ions. Finally, the potential avenues and challenges were proposed for future research.

Development of a Green Polymeric Membrane for Sodium Diclofenac Removal from Aqueous Solutions

Water-soluble polymers provide an alternative to organic solvent requirements in membrane manufacture, aiming at accomplishing the Green Chemistry principles. Poly(vinyl alcohol) (PVA) is a biodegradable and non-toxic polymer renowned for its solubility in water. However, PVA is little explored in membrane processes due to its hydrophilicity, which reduces its stability and performance. Crosslinking procedures through an esterification reaction with carboxylic acids can address this concern. For this, experimental design methodology and statistical analysis were employed to achieve the optimal crosslinking conditions of PVA with citric acid as a crosslinker, aiming at the best permeate production and sodium diclofenac (DCF) removal from water. The membranes were produced following an experimental design and characterized using multiple techniques to understand the effect of crosslinking on the membrane performance. Characterization and filtration results demonstrated that crosslinking regulates the membranes' properties, and the optimized conditions (crosslinking at 110 °C for 110 min) produced a membrane able to remove 44% DCF from water with a permeate production of 2.2 L m^-2 h^-1 at 3 bar, comparable to commercial loose nanofiltration membranes. This study contributes to a more profound knowledge of green membranes to make water treatment a sustainable practice in the near future.

Membranes in Water Reclamation: Treatment, Reuse and Concentrate Management

In this article, an extensive examination is provided on the possible uses of membranes and hybrid processes in wastewater treatment. While membrane technologies face certain constraints, such as membrane fouling and scaling, the incomplete elimination of emerging contaminants, elevated expenses, energy usage, and brine disposal, there are approaches that can address these challenges. Methods such as pretreating the feed water, utilizing hybrid membrane systems and hybrid dual-membrane systems, and employing other innovative membrane-based treatment techniques can enhance the efficacy of membrane processes and advance sustainability.

Green Synthesis of Hydrogel-Based Adsorbent Material for the Effective Removal of Diclofenac Sodium from Wastewater

The removal of pharmaceutical contaminants from wastewater has gained considerable attention in recent years, particularly in the advancements of hydrogel-based adsorbents as a green solution for their ease of use, ease of modification, biodegradability, non-toxicity, environmental friendliness, and cost-effectiveness. This study focuses on the design of an efficient adsorbent hydrogel based on 1% chitosan, 40% polyethylene glycol 4000 (PEG4000), and 4% xanthan gum (referred to as CPX) for the removal of diclofenac sodium (DCF) from water. The interaction between positively charged chitosan and negatively charged xanthan gum and PEG4000 leads to strengthening of the hydrogel structure. The obtained CPX hydrogel, prepared by a green, simple, easy, low-cost, and ecological method, has a higher viscosity due to the three-dimensional polymer network and mechanical stability. The physical, chemical, rheological, and pharmacotechnical parameters of the synthesized hydrogel were determined. Swelling analysis demonstrated that the new synthetized hydrogel is not pH-dependent. The obtained adsorbent hydrogel reached the adsorption capacity (172.41 mg/g) at the highest adsorbent amount (200 mg) after 350 min. In addition, the adsorption kinetics were calculated using a pseudo first-order model and Langmuir and Freundlich isotherm parameters. The results demonstrate that CPX hydrogel can be used as an efficient option to remove DCF as a pharmaceutical contaminant from wastewater.