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1.
Environ Sci Technol ; 57(46): 17940-17949, 2023 Nov 21.
Article in English | MEDLINE | ID: mdl-37624988

ABSTRACT

The utilization of steel slag for CO2 sequestration is an effective way to reduce carbon emissions. The reactivity of steel slag in CO2 sequestration depends mainly on material and process parameters. However, there are many puzzles in regard to practical applications due to the different evaluations of process parameters and the lack of investigation of material parameters. In this study, 318 samples were collected to investigate the interactive influence of 12 factors on the carbonation reactivity of steel slag by machine learning with SHapley Additive exPlanations (SHAP). Multilayer perceptron (MLP), random forest, and support vector regression models were built to predict the slurry-phase CO2 sequestration of steel slag. The MLP model performed well in terms of prediction ability and generalization with comprehensive interpretability. The SHAP results showed that the impact of the process parameters was greater than that of the material parameters. Interestingly, the iron ore phase of steel slag was revealed to have a positive effect on steel slag carbonation by SHAP analysis. Combined with previous literature, the carbonation mechanism of steel slag was proposed. Quantitative analysis based on SHAP indicated that steel slag had good carbonation reactivity when the mass fractions of "CaO + MgO", "SiO2 + Al2O3", "Fe2O3", and "MnO" varied from 50-55%, 10-15%, 30-35%, and <5%, respectively.


Subject(s)
Carbon Dioxide , Industrial Waste , Industrial Waste/analysis , Carbon Dioxide/analysis , Steel , Silicon Dioxide , Carbonates , Machine Learning
2.
J Hazard Mater ; 408: 124411, 2021 04 15.
Article in English | MEDLINE | ID: mdl-33189467

ABSTRACT

As an emerging contaminant in water, antibiotic resistant bacteria are threatening the public health gravely. In this study, sulfidated ZVI was used to activate persulfate, for antibiotic resistant E. coli and antibiotic resistant genes removal. Impressively, 7 log of antibiotic resistant E. coli was inactivated within 30 min, in sulfidated ZVI activated persulfate system (S/Fe = 0.05). Electron paramagnetic resonance and free radical quenching experiments suggested that sulfidation treatment did not change the specie of radicals. SO4•-and HO• were the main reactive oxygen species for the removal of antibiotic resistant E. coli and genes. Investigation on the activation mechanism of persulfate indicated that persulfate decomposition was mainly attributed to heterogeneous activation. More importantly, in-situ characterization (ATR-FTIR) indicated that the main charge transfer complex was formed on the surface of sulfidated ZVI, which would predominantly mediate the generation of SO4•- and HO•. Finally, the proposed system was evaluated in modeling water and secondary effluent. Results revealed that only 2.86 log and 0.84 log of antibiotic resistant E. coli were inactivated in the presence of NOM (10 mg/L) and HCO3- (84 mg/L), respectively. Besides, sulfidated ZVI activated persulfate system could be pH-dependent in actual wastewater treatment.


Subject(s)
Iron , Water Pollutants, Chemical , Anti-Bacterial Agents/pharmacology , Escherichia coli/genetics , Oxidation-Reduction , Oxidative Stress
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