Utilizing machine learning for reactive material selection and width design in permeable reactive barrier (PRB).

Permeable reactive barrier (PRB) is an important groundwater treatment technology. However, selecting the optimal reactive material and estimating the width remain critical and challenging problems in PRB design. Machine learning (ML) has advantages in predicting evolution and tracing contaminants in temporal and spatial distribution. In this study, ML was developed to design PRB, and its feasibility was validated through experiments and a case study. ML algorithm showed a good prediction about the Freundlich equilibrium parameter (R2 0.94 for KF, R2 0.96 for n). After SHapley Additive exPlanation (SHAP) analysis, redefining the range of the significant impact factors (initial concentration and pH) can further improve the prediction accuracy (R2 0.99 for KF, R2 0.99 for n). To mitigate model bias and ensure comprehensiveness, evaluation index with expert opinions was used to determine the optimal material from candidate materials. Meanwhile, the ML algorithm was also applied to predict the width of the mass transport zone in the adsorption column. This procedure showed excellent accuracy with R2 and root-mean-square-error (RMSE) of 0.98 and 1.2, respectively. Compared with the traditional width design methodology, ML can enhance design efficiency and save experiment time. The novel approach is based on traditional design principles, and the limitations and challenges are highlighted. After further expanding the data set and optimizing the algorithm, the accuracy of ML can make up for the existing limitations and obtain wider applications.

Comparison of effects of multiple oxidants with an ultrasonic system under unified system conditions for bisphenol A degradation.

Bisphenol A (BPA) as a trace contaminant has been reported, due to widespread use in the plastics industry. This study applied the 35 kHz ultrasound (US) to activate four different common oxidants (H2O2, HSO5-, S2O82-, and IO4-) for BPA degradation. With increasing initial concentration of oxidants, the degradation rate of BPA increased. The synergy index confirmed that a synergistic relationship between US and oxidants. This study also examined the impact of pH and temperature. The results showed that the kinetic constants of US, US-H2O2, US-HSO5- and US-IO4-decreased when the pH increased from 6 to 11. The optimal pH for US-S2O82- was 8. Notably, increasing temperature decreased the performance of US, US-H2O2, and US-IO4- systems, while it could increase the degradation of BPA in US-S2O82- and US-HSO5-. The activation energy for BPA decomposition using the US-IO4- system was the lowest, at 0.453nullkJnullmol-1, and the synergy index was the highest at 2.22. Additionally, the ΔG# value was found to be 2.11 + 0.29T when the temperature ranged from 25 °C to 45 °C. The main oxidation contribution is achieved by hydroxyl radicals in scavenger test. The mechanism of activation of US-oxidant is heat and electron transfer. In the case of the US-IO4- system, the economic analysis yielded 271 kwh m-3, which was approximately 2.4 times lower than that of the US process.

Zero-valent iron based materials selection for permeable reactive barrier using machine learning.

The zero-valent iron (ZVI) based reactive materials are potential remediation reagents in permeable reactive barriers (PRB). Considering that reactive materials is the essential to determining the long-term stability of PRB and the emergence of a large number of new iron-based materials. Here, we present a new approach using machine learning to screen PRB reactive materials, which proposes to improve the efficiency and practicality of selection of ZVI-based materials. To compensate for the insufficient amount of existing machine learning source data and the real-world implementation, machine learning combines evaluation index (EI) and reactive material experimental evaluations. XGboost model is applied to estimate the kinetic data and SHAP is used to improve the accuracy of model. Batch and column tests were conducted to investigate the geochemical characteristics of groundwater. The study find that specific surface area is a fundamental factor correlated with the kinetic constants of ZVI-based materials, according to SHAP analysis. Reclassifying the data with specific surface area significantly improved prediction accuracy (reducing RMSE from 1.84 to 0.6). Experimental evaluation results showed that ZVI had 3.2 times higher anaerobic corrosion reaction kinetic constants and 3.8 times lower selectivity than AC-ZVI. Mechanistic studies revealed the transformation pathways and endpoint products of iron compounds. Overall, this study is a successful initial attempt to use machine learning for selecting reactive materials.

Does environmental regulation lessen health risks? Evidence from Chinese cities.

Introduction: Atmospheric pollution is a severe problem confronting the world today, endangering not only natural ecosystem equilibrium but also human life and health. As a result, governments have enacted environmental regulations to minimize pollutant emissions, enhance air quality and protect public health. In this setting, it is critical to explore the health implications of environmental regulation. Methods: Based on city panel data from 2009 to 2020, the influence of environmental regulatory intensity on health risks in China is examined in this study. Results: It is discovered that enhanced environmental regulation significantly reduces health risks in cities, with each 1-unit increase in the degree of environmental regulation lowering the total number of local premature deaths from stroke, ischemic heart disease, and lung cancer by approximately 15.4%, a finding that remains true after multiple robustness tests. Furthermore, advances in science and technology are shown to boost the health benefits from environmental regulation. We also discover that inland cities, southern cities, and non-low-carbon pilot cities benefit more from environmental regulation. Discussion: The results of this research can serve as a theoretical and empirical foundation for comprehending the social welfare consequences of environmental regulation and for guiding environmental regulation decision-making.

Evaluation of anode materials in sonoelectrochemistry processes: Kinetic, mechanism, and cost estimation.

Eco-friendly pollutant treatment technology has a developing tendency in future. The combination of ultrasound (US) and electrochemical (EC) is a promising technology, because they are efficient, clean and environmentally friendly. In this study, the impacts of anode material have been investigated in US (300 kHz) and EC (10V) system. The results of all systems revealed that the kinetic constant decreased with increasing pH. The results are also shown that ΔG# > 0 and ΔH# > 0 during PCP degradation in EC or US-EC systems are non-spontaneous and endothermic reactions. Meanwhile, in the US-EC system, TiO2, Ti4O7, PbO2, SnSb, RuIr, and BDD, except for TiO2, all the anode materials showed a synergistic index (SI) of 106-197%, and the activation energies were 19.32, 33.4, 33.74, 32.84, 10.41, 36.44 kJ mol-1, respectively. In EC and US-EC systems, PCP can be completely mineralized by BDD anode within 30 min. TBA scavenger experiments verified that hydroxyl radicals were the main oxidant in each system using BDD and PbO2 anode. As a result of estimating the cost according to the anode material when removing PCP using the EC or US-EC system, BDD was the smallest in the two systems, 1.58 and 1.12 $ m-3, respectively. Finally, this study may serve as a reference for implementation of US-EC system in wastewater treatment.

Rare earth real wastewater treatment by pilot scale using new concept continuous treatment process.

Rare earth (RE) containing radioactive species and a variety of toxic pollutants The treatment of real wastewater is very important for environmental protection. In this study, a new concept of continuous process consisting of precipitation, adsorption, and oxidation was developed without the use of chemicals. In the sedimentation step, waste oyster shell(WOS) and a PE tube diffuser(PE250) containing Na2S (PECa/S), PECa/S were prepared, which were used to precipitate heavy metals with a removal efficiency of 97% or more. In the adsorption step, fluorine (F), arsenic (As), and thorium (Th) were precipitated and removed when heavy metals were removed using coal mine drainage sludge (CMDS) and an adsorbent (PUCMDS) made of polyurethane (PU). Running a semi and pilot scale continuous process using PECa/S, PUCMDS and O3/HC systems resulted in a semi and pilot scale operating period of 120 and 62 days, and 60.26, 797.84, 46.94, 78.62 g, and 7.120 kg and 266.35, 42556.8, 191.95, 3108.43 g and 629.84 kg for As, F, Th, Pb and CODcr has been removed respectively. In addition, the removal efficiencies of As, F, Th, Pb and CODcr were 99.75, 99.98, 93.60, 99.99, and 88.82%, respectively, when treating real RE wastewater using the pilot scale system. Without the use of agitated reactors and regulators, the new concept of continuous process can effectively treat RE real wastewater, and the quality of the process outlet has met the pollutant limits recommended by EPA and China for irrigation.

Evaluation of stabilizing material and stabilization efficiency through comparative study of toxic heavy metal transfer between corn and peanut grown in stabilized field soil.

Soil contaminated with toxic heavy metals (THMs) was stabilized by adding a combination of waste resources in 7.0 wt%, including coal-mine drainage sludge, waste cow bone, and steelmaking slag, in the ratio of 5:35:60. Subsequently, corn and peanut were cultivated in treated soil to investigate the effects of the waste resources on THM mobility in soil and translocation to plants. Sequential extraction procedures (SEP) was used to analyze mobile phase THMs which could be accumulated in the plants. SEP shows that mobile Pb, Cd, Cu, Zn, Ni, Cr, and As were reduced by 8.48%, 29.22%, 18.85%, 21.66%, 4.58%, 62.78%, and 20.01%, respectively. The bioaccumulation of THMs was clearly hindered by stabilization; however, the increment in the amount of immobile-phase THMs and change in the amount of translocated THMs was not proportional. The corn grains grown above the soil surface were compared with the peanut grains grown beneath the soil surface, and the results indicating that the efficiency of stabilization on THM translocation may not depend on the contact of grain to soil but the nature of plant. Interestingly, the results of bioaccumulation with and without stabilization showed that the movement of some THMs inside the plants was affected by stabilization.

Improving sono-activated persulfate oxidation using mechanical mixing in a 35-kHz ultrasonic reactor: Persulfate activation mechanism and its application.

This study investigated the degradation of ibuprofen (IBP), an activated persulfate (PS), when subjected to ultrasonic (US) irradiation and mechanical mixing (M). The effects of several critical factors were evaluated, including the effect of rpm on M, PS concentration, and initial pH, and that of temperature on IBP degradation kinetics and the PS activation mechanism. The resulting IBP oxidation rate constant was significantly higher at 400 rpm. As the PS load increased, the IBP oxidation rate constant increased. The value of the IBP reaction rate increased with decreasing pH; below pH 4.9, there was no significant difference in the IBP oxidation rate constant. The IBP oxidation activation energy when using the US/M-PS system was 18.84 kJ mol-1. In the US/M-PS system, PS activation was the primary effect of temperature at the interface during the explosion of cavitation bubbles. These encouraging results suggest that the US-PS/M process is a promising strategy for the treatment of IBP-based water pollutants.