Estimating the toxicities of organic chemicals in activated sludge process

Inhibition of aged microplastics and leachates on methane production from anaerobic digestion of sludge and identification of key components

Large amounts of microplastics (MPs) accumulate in the sludge anaerobic digestion system after being treated by the wastewater treatment plants, inevitably leading to aging and chemicals leaching. However, no information is available about the effects of aged MPs and leachates on the anaerobic digestion of sludge. In this study, the effects of different aged MPs ((polyethylene (PE), polyethylene terephthalate (PET), polyvinyl chloride (PVC), and polylactic acid (PLA)) and leachates on anaerobic methanogenesis of sludge were investigated. PLA-related treatments caused no adverse effects on anaerobic digestion. While PE-, PET-, and PVC-related treatments significantly inhibited methane production with an order of leachates (26.4-42.4 %) > MPs (16.1-22.9 %) > aged MPs (2.4-11.8 %). For different leachates, PET leachate caused the strongest inhibitory effects. The same order was found for the methane potential and hydrolysis coefficient. These results suggest that the inhibition of MPs on methanogenesis is mainly caused by the leachates. Based on biochemical and microbial community analysis, the primary mechanism is that the leachates induce oxidative stress, damaging microbial cells and reducing microbial activity, consequently inhibiting methanogenesis. Furthermore, via effect-directed analysis, methyl benzoate (MB), dimethyl phthalate (DMP), and 2,4-Di-tert-butylphenol (DTBP) were identified as key components in the PET-leachate inhibiting anaerobic methanogenesis.

Electrical selection for planktonic sludge microbial community function and assembly

Electrostimulated hydrolysis acidification (eHA) has been used as an efficient biological pre-treatment of refractory industrial wastewater. However, the effects of electrostimulation on the function and assembly of planktonic anaerobic sludge microbial communities are poorly understood. Using 16S rRNA gene and metagenomic sequencing, we investigated planktonic sludge microbial community structure, composition, function, assembly, and microbial interactions in response to electrostimulation. Compared with a conventional hydrolysis acidification (HA) reactor, the planktonic sludge microbial communities selected by electrostimulation promoted biotransformation of the azo dye Alizarin Yellow R. The taxonomic and functional structure and composition were significantly shifted upon electrostimulation with azo dyes degraders (e.g. Acinetobacter and Dechloromonas) and electroactive bacteria (e.g. Pseudomonas) being enriched. More microbial interactions between fermenters and decolorizing and electroactive bacteria, as well as fewer interactions between different fermenters evolved in the eHA microbial communities. Moreover, the decolorizing bacteria were linked to the higher abundance of genes encoding for azo- and nitro-reductases and redox mediator (e.g. ubiquinone) biosynthesis involved in the transformation of azo dye. Microbial community assembly was more driven by deterministic processes upon electrostimulation. This study offers new insights into the effects of electrostimulation on planktonic sludge microbial community function and assembly, and provides a promising strategy for the manipulation of anaerobic sludge microbiomes in HA engineering systems.

Pharmaceutical and anticorrosive substance removal by woodchip column reactor: removal process and effects of operational parameters

Urban stormwater has recently been considered a potential water resource to augment urban water supplies; however, the existence of emerging contaminants limits urban stormwater utilization. This study aims to use woodchip bioreactors, which are natural and inexpensive, to remove emerging contaminants from artificial stormwater, with a focus on the contaminant removal processes in the woodchip bioreactor and on the effects of operational parameters on the system performance. Seven commonly detected emerging contaminants - acetaminophen (ACE), caffeine (CAFF), carbamazepine (CBZ), ibuprofen (IBU), sulfathiazole (SFZ), benzotriazole (BT) and 5-methyl-1H-benzotriazole (5-MeBT) - were studied. The results showed that the removal efficiency and removal processes are heavily dependent on the compound. ACE and CAFF have the highest removal efficiencies (≥80%), and sorption and biodegradation are both crucial for their removal. However, IBU exhibits very limited sorption and biodegradation and hence has the worst removal (≤15%). The removal efficiencies of the other compounds (SFZ, CBZ, BT and 5-MeBT) range from ∼30 to 60%, and sorption is likely the main removal process. The effects of several operational parameters, including woodchip type, operation time, season and flow rate, on the removal rate of emerging contaminants were also explored. The results of this study showed that the woodchip column system, which is capable of sorption and biodegradation, represents a promising treatment process for removing emerging contaminants from urban stormwater.

Assessment of Pharmaceuticals, Personal Care Products, and Hormones in Wastewater Treatment Plants Receiving Inflows from Health Facilities in North West Province, South Africa

The presence of 17 pharmaceutical and personal care products (PPCPs) belonging to various therapeutic categories was investigated in two hospital wastewater treatment plants (WWTPs) in North West Province, South Africa. The compounds were extracted from wastewater samples by solid-phase extraction and analysed by liquid chromatography-tandem mass spectrometry. The results showed that ofloxacin, chloramphenicol, and bezafibrate were generally below the limit of quantification (LOQ) in the analysed samples. Acetaminophen and ibuprofen were the dominant pharmaceuticals in the influent streams with corresponding concentrations ranging from 21 to 119 μg/L and 0.3 to 63 μg/L, respectively. Both WWTPs were shown to have the capability to remove some of the target PPCPs, including acetaminophen (76-98%), tetracycline (15-93%), ibuprofen (44-99%), and triclocarban (13-98%). The monitoring of the target PPCPs in both influent and effluent samples of the investigated WWTPs revealed that the discharge of inadequately treated effluents could be contributing to the possible increase in the concentrations of these contaminants in the receiving environmental compartments. Further studies must be focused on the broader characterisation of these matrices in order to assess the potential ecological impacts of this waste disposal practice.

Full-scale bioreactor pretreatment of highly toxic wastewater from styrene and propylene oxide production

The wastewater originating from simultaneous production of styrene and propylene oxide (SPO) is classified as highly polluted with chemical oxygen demand level in the range 5965 to 9137mgL(-1)-as well as highly toxic. The dilution factor providing for a 10 percent toxic effect of wastewater samples in a test with Paramecium caudatum was 8.0-9.5. Biological approach for pretreatment and detoxification of the wastewater under full-scale bioreactor conditions was investigated. The number of suspended microorganisms and the clean up efficiency were increased up to 5.5-6.58×10(8)CFUmL(-1) and 88 percent, respectively during the bioreactor's operation. Isolates in the Citrobacter, Burkholderia, Pseudomonas, and Paracoccus genera were dominant in the mature suspended, as well as the immobilized microbial community of the bioreactor. The most dominant representatives were tested for their ability to biodegrade the major components of the SPO wastewater and evidence of their role in the treatment process was demonstrated. The investigated pretreatment process allowed the wastewater to be detoxified for conventional treatment with activated sludge and was closely related to the maturation of the bioreactor's microbial community.

Toxicant inhibition in activated sludge: fractionation of the physiological status of bacteria

In wastewater treatment plants the sensitivity of activated sludge to a toxicant depends on the toxicity test chosen, and thus the use of more than one test is suggested. The physiological status of bacteria in response to toxicants was analysed by flow cytometry to distinguish intact, permeabilised, active cells and cells disrupted. Results were compared with respirometry and bioluminescence bioassay (Vibrio fischeri). 3,5-Dichlorophenol (DCP) was used as reference xenobiotic. DCP has a strong effect on cellular integrity, causing an increase in permeabilised and disrupted cells. A reduction of 44-80% of intact cells with 6-30 mgDCP/L for 5h was found. Inhibition of active cells was 25-49%, at 6-30 mgDCP/L for 5h. The bioluminescence bioassay resulted oversensitive to DCP compared to tests based on activated sludge, while oxygen uptake rate was affected similarly to intact cells measured by flow cytometry. Landfill leachate was tested: a detrimental impact on both cellular integrity and enzymatic activity was observed. Reduction of intact cells and active cells was by 32% and 61% respectively after addition of 50% (v/v) of leachate for 5h. The flow cytometry analysis proposed here might be widely applicable in the monitoring of various toxicants and in other aquatic biosystems.

Predicting aqueous solubility of environmentally relevant compounds from molecular features: a simple but highly effective four-dimensional model based on Project to Latent Structures

The aqueous solubility (log S) of xenobiotic chemicals has been identified as a key characteristic in determining their bioaccessibility/bioavailability and their fate and transport in aquatic environments. We here explore and evaluate the use of a state-of-the-art data analysis technique (Project to Latent Structures, PLS) to estimate log S of environmentally relevant chemicals. A large number (n = 624) of molecular descriptors was computed for over 1400 organic chemicals, and then refined by a feature selection technique. Candidate predictor descriptors were fitted to data by means of PLS, which was optimized by an internal leave-one-out cross-validation technique and validated by an external data set. The final (best) PLS model with only four variables (AlogP, X1sol, Mv, and E) exhibited noteworthy stability and good predictive power. It was able to explain 91% of the data (n = 1400) variance with an average absolute error of 0.5 log units through the solubilities span over 12 orders of magnitude. The newly proposed model is transparent, easily portable from one user to another, and robust enough to accurately estimate log S of a wide range of emerging contaminants.

The toxicity of cadmium to three aquatic organisms (Photobacterium phosphoreum, Daphnia magna and Carassius auratus) under different pH levels

This study investigated the effect of pH on cadmium toxicity to three aquatic organisms: Photobacterium phosphoreum, Daphnia magna and Carassius auratus. The acute toxicity of Cd(2+) to P. phosphoreum and D. magna at five pH values (5.0, 6.0, 7.0, 8.0, and 9.0) was assessed by calculating EC50 values. We determined that Cd(2+) was least toxic under acidic conditions, and D. magna was more sensitive to the toxicity of Cd than P. phosphoreum. To evaluate Cd(2+)-induced hepatic oxidative stress in C. auratus at three pH levels (5.0, 7.25, 9.0), the activity of antioxidant enzymes (superoxide dismutase, catalase and glutathione peroxidase), the level of glutathione and the malondialdehyde content in the liver were measured. Oxidative damage was observed after 7d Cd exposure at pH 9.0. An important finding of the current research was that Cd(2+) was generally more toxic to the three test organisms in alkaline environments than in acidic environments.

QSAR Modeling is not "Push a Button and Find a Correlation": A Case Study of Toxicity of (Benzo-)triazoles on Algae

A case study of toxicity of (benzo)triazoles ((B)TAZs) to the algae Pseudokirchneriella subcapitata is used to discuss some problems and solutions in QSAR modeling, particularly in the environmental context. The relevance of data curation (not only of experimental data, but also of chemical structures and input formats for the calculation of molecular descriptors), the crucial points of QSAR model validation and the potential application for new chemicals (internal robustness, exclusion of chance correlation, external predictivity, applicability domain) are described, while developing MLR-OLS models based on molecular descriptors, calculated by various QSAR software tools (commercial DRAGON, free PaDEL-Descriptor and QSPR-THESAURUS). Additionally, the utility of consensus models is highlighted. This work summarizes a methodology for a rigorous statistical approach to obtain reliable QSAR predictions, also for a large number of (B)TAZs in the ECHA preregistration list of REACH (even if starting from limited experimental data availability), and has evidenced some ambiguities and discrepancies related to SMILES notations from different databases; furthermore it highlighted some general problems related to QSAR model generation and was useful in the implementation of the PaDEL-Descriptor software.