Factors hindering the degradation of pharmaceuticals from human urine in an iron-activated persulfate system

This study investigated the degradation of clofibric acid(CFA),bezafibrate(BZF),and sulfamethoxazole(SMX)in synthetic human urine using a novel mesoporous iron powderactivated persulfate system(mFe-PS system),and identified the factors limiting their degradation in synthetic human urine.A kinetic model was established to expose the radical production in various reaction conditions,and experiments were conducted to verify the modeling results.In the phosphate-containing mFe-PS system,the 120 min removal efficiency of CFA decreased from 95.1%to 76.6%as the phosphate concentration increased from 0.32 to 6.45 mmol/L,but recovered to 90.5%when phosphate concentration increased to 16.10 mmol/L.Meanwhile,the increased concentration of phosphate from 0.32 to 16.10mmol/L reduced the BZF degradation efficacy from 91.5%to 79.0%,whereas SMX removal improved from 37.3%to 62.9%.The m Fe-PS system containing(bi)carbonate,from 4.20 to166.70 mmol/L,reduced CFA and BZF removal efficiencies from 100%to 76.8%and 80.4%,respectively,and SMX from 83.5%to 56.7%within a 120-min reaction time.In addition,alkaline conditions(pH≥8.0)inhibited CFA and BZF degradations,while nonacidic pH(pH≥7.0)remarkably inhibited SMX degradation.Results of the kinetic model indicated the formation of phosphate(H_(2)PO_(4)^(·)/HPO_(4)^(·-))and/or carbonate radicals(CO_(3)^(·-))could limit pharmaceutical removal.The transformation products(TPs)of the pharmaceuticals revealed more incompletely oxidized TPs occurred in the phosphate-and(bi)carbonate-containing m Fe-PS systems,and indicated that H_(2)PO_(4)^(·)/HPO_(4)^(·-)mainly degraded pharmaceuticals via a benzene ring-opening reaction while CO_(3)^(·-)preferentially oxidized pharmaceuticals via a hydroxylation reaction.

Application of permanganate in the oxidation of micropollutants:a mini review

As a green oxidant,permanganate has received considerable attention for the removal of micropollutants in drinking water treatment.To provide a better understanding of the oxidation of organic micropollutants with permanganate,the oxidation kinetics of 32 micropollutants were compiled.The pollutants include algal toxins,endocrine disrupting chemicals(EDCs),and pharmaceuticals.The oxidation kinetics of micropollutants by permanganate were found to be first order with respect to both contaminant and permanganate concentrations from which second-order rate constants(k″)were obtained.Permanganate oxidized the heterocyclic aromatics with vinyl moiety(i.e.,microcystins,carbamazepine,and dichlorvos)by the addition of double bonds.For the polycyclic aromatic hydrocarbons(PAHs)with alkyl groups,permanganate attacked the benzylic C-H through abstraction of hydrogen.The mechanism for the oxidation of phenolic EDCs by permanganate was a single electron transfer and aromatic ring cleavage.The presence of background matrices could enhance the oxidation of some phenolic EDCs by permanganate,including phenol,chlorinated phenols,bisphenol A,and trichlosan.The toxicity of dichlorvos solution increased after permanganate oxidation,and the estrogenic activity of bisphnol A/estrone increased significantly at the beginning of permanganate oxidation.Therefore,the toxicity of degradation products or intermediates should be determined in the permanganate oxidation processes to better evaluate the applicability of permanganate.The influence of background ions on the permanganate oxidation process is far from clear and should be elucidated in the future studies to better predict the performance of permanganate oxidation of micropollutants.Moreover,methods should be employed to catalyze the permanganate oxidation process to achieve better removal of micropollutants.

p-Norm Broad Learning for Negative Emotion Classification in Social Networks

Negative emotion classification refers to the automatic classification of negative emotion of texts in social networks.Most existing methods are based on deep learning models,facing challenges such as complex structures and too many hyperparameters.To meet these challenges,in this paper,we propose a method for negative emotion classification utilizing a Robustly Optimized BERT Pretraining Approach(RoBERTa)and p-norm Broad Learning(p-BL).Specifically,there are mainly three contributions in this paper.Firstly,we fine-tune the RoBERTa to adapt it to the task of negative emotion classification.Then,we employ the fine-tuned RoBERTa to extract features of original texts and generate sentence vectors.Secondly,we adopt p-BL to construct a classifier and then predict negative emotions of texts using the classifier.Compared with deep learning models,p-BL has advantages such as a simple structure that is only 3-layer and fewer parameters to be trained.Moreover,it can suppress the adverse effects of more outliers and noise in data by flexibly changing the value of p.Thirdly,we conduct extensive experiments on the public datasets,and the experimental results show that our proposed method outperforms the baseline methods on the tested datasets.

A “Seawater-in-Sludge” approach for capacitive biochar production via the alkaline and alkaline earth metals activation

Sewage sludge is a potential precursor for biochar production,but its effective utilization involves costly activation steps.To modify biochar properties while ensuring cost-effectiveness,we examined the feasibility of using seawater as an agent to activate biochar produced from sewage sludge.In our proof-of-concept study,seawater was proven to be an effective activation agent for biochar production,achieving a surface area of 480.3 m^(2)/g with hierarchical porosity distribution.Benefited from our design,the catalytic effect of seawater increased not only the surface area but also the graphitization degree of biochar when comparing the pyrolysis of sewage sludge without seawater.This leads to seawater activated biochar electrodes with lower resistance,higher capacitance of 113.9 F/g comparing with control groups without seawater.Leveraging the global increase in the salinity of groundwater,especially in coastal areas,these findings provide an opportunity for recovering a valuable carbon resource from sludge.