To mitigate dust pollution generated during various stages of construction activities and reduce the environmental and health hazards posed by airborne dust, this study utilized hydroxyethyl cellulose, glycerol, and isomeric tridecyl alcohol polyoxyethylene ether as raw materials to formulate a composite chemical dust suppressant. The properties of the dust suppressant were characterized through analysis. Employing single-factor experiments, the optimal proportions of the binder, water-retaining agent, and surfactant for the composite dust suppressant were determined. Subsequently, a response surface model was established, and, after analysis and optimization, the optimal mass ratios of each component in the composite dust suppressant were obtained. Under optimal ratios, the physicochemical properties and wind erosion resistance of the composite dust suppressant were analyzed. Finally, the practical application of the suppressant was validated through on-site trials at a construction site. This study revealed that the optimal formulation for the dust suppressant was as follows: 0.2% hydroxyethyl cellulose, 2.097% glycerol, 0.693% isomeric tridecyl alcohol polyoxyethylene ether, and the remainder was pure water. The suppressant is non-toxic, non-corrosive, environmentally friendly, and exhibits excellent moisture retention and bonding properties compared to water. The research findings provide valuable insights for addressing dust pollution issues on construction sites.

Due to the complicated transport and reactive behavior of organic contamination in groundwater, the development of mathematical models to aid field remediation planning and implementation attracts increasing attentions. In this study, the approach coupling response surface methodology (RSM), artificial neural networks (ANN), and kinetic models was implemented to model the degradation effects of nano-zero-valent iron (nZVI) activated persulfate (PS) systems on benzene, a common organic pollutant in groundwater. The proposed model was applied to optimize the process parameters in order to help predict the effects of multiple factors on benzene degradation rate. Meanwhile, the chemical oxidation kinetics was developed based on batch experiments under the optimized reaction conditions to predict the temporal degradation of benzene. The results indicated that benzene (0.25 mmol) would be theoretically completely oxidized in 1.45 mM PS with the PS/nZVI molar ratio of 4:1 at pH 3.9°C and 21.9 C. The RSM model predicted well the effects of the four factors on benzene degradation rate (R2 = 0.948), and the ANN with a hidden layer structure of [8-8] performed better compared to the RSM (R2 = 0.980). In addition, the involved benzene degradation systems fit well with the Type-2 and Type-3 pseudo-second order (PSO) kinetic models with R2 > 0.999. It suggested that the proposed statistical and kinetic-based modeling approach is promising support for predicting the chemical oxidation performance of organic contaminants in groundwater under the influence of multiple factors.

There are numerous combinations of biomass, plastic, and co-pyrolysis conditions. The presence of synergies, which make pyrolyzate distribution more complex, has been supported by research. In this study, the potential of response surface methodology (RSM) to predict the pyrolyzate yields affected by synergies during co-pyrolysis (500-700 °C) of cellulose and polyethylene was investigated, beyond gas, oil, and char yields. The results indicated that co-pyrolysis promoted liquid and C5-28 hydrocarbon production with increasing temperature. The quadratic model could predict the total gas, CO, CO2, and liquid yields, including the synergy. The cubic model could predict the levoglucosan and C5-28 hydrocarbon yields due to various synergies under different conditions. The linear model was suitable for the char yield distribution without interaction. Thus, this study reveals that RSM has a significant potential to predict pyrolyzate yields, enabling co-pyrolysis condition setting to maximize the desired product recovery with the fewest experiments.

Recently, efficient extraction of natural products from traditional Chinese medicines (TCMs) by green solvents is deemed an essential area of green technology and attracts extensive attentions. In this work, a green protocol for simultaneous ultrasonic-extraction of the native compounds with different polarities of TCMs by using a hybrid ionic liquids (HILs)-water system was reported for the first time. As a case study, three superior ILs (1-ethyl-3-methylimidazolium tetrafluoroborate ([EMIM][BF4]), 1-ethyl-3-methylimidazolium acetate ([EMIM][OAc]), and 1-allyl-3-methylimidazolium chloride ([AMIM]Cl)) were chosen as the compositions of the HILs system, and the TCMs Suhuang antitussive capsule (SH) containing different-polarity lignans was selected. Primarily, an ultra-performance liquid chromatography coupled to triple quadrupole tandem mass spectrometry (UPLC-QqQ-MS/MS) method in the multiple reaction monitoring (MRM) mode was established for qualitative and quantitative analysis of 18 lignans. After majorization by uniform design experiment, the HILs prepared with [AMIM]Cl, [EMIM][BF4], and [EMIM][OAc] at a volume ratio of 1:5:5 could simultaneously extract multi-polarity lignans compared to single IL. Subsequently, the conditions of ultrasonic extraction employing with HILs and traditional organic solvent were optimized by the response surface methodology, respectively. The results indicated that the extract efficiency of the HILs system for target compounds was significantly improved compared with the traditional organic solvent-extraction, i.e. the content of total lignans in ethanol system was up to 47 mg/g, while that in the HILs system was up to 69 mg/g, with an increasing of 47%. Additionally, 1H-NMR and 13C-NMR spectra were used to characterize the hydrogen-bond interactions in the HILs-lignan mixtures. Extraction with the HILs in TCMs is a new application schema of ILs, which not only avoids the use of volatile toxic organic solvents, but also shows the potential to be comprehensively applied for the extraction of bioactive compounds from TCMs.

The main objective of this study is to investigate the application of Photo-Fenton process to treat landfill leachate with minimum energy consumption and maximum COD removal efficiencies, simultaneously. Accordingly, an operational assessment of Photo-Fenton process was conducted in terms of variables, namely oxidation pH, [H2O2]/[Fe2+] molar ratio, and Fe2+ dosage. The Central Composite Design (CCD) based on Response Surface Methodology (RSM) was applied for statistical analysis and optimization of target parameters. To assess the rate of energy consumption in Photo-Fenton process, the EEM parameter (Electric Energy consumed per organic Mass removed) was introduced, and the same Fenton experiments were performed to compare the results. Applying UV light in the Fenton process (i.e. Photo-Fenton process) increased COD removal efficiencies up to 10%. The results showed that the Photo-Fenton treatment is capable of removing COD by over 80% of the initial COD (i.e. 17,200 mg/L of AradKooh landfill leachate), applying 195-265 mM iron concentration, [H2O2]/[Fe2+] molar ratio of 15.50-20.55, and the oxidation pH value of 3.75-5.55 (other conditions were oxidation time of 30 min, coagulation pH of 8, and coagulation time of 25 min). The regeneration of Fe(II) from Fe(III) by UV light irradiation resulted in a larger degradation of COD than that of conventional Fenton process, and also reduced the amount of iron catalyst consumption (approximately 25% reduction observed). Furthermore, the cost of energy in Photo-Fenton process could be covered considering lower amounts of sludge generated than conventional Fenton treatment (note that the cost evaluations in current paper were based on batch studies and should be confirmed on full-scale system).