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Neural networks (NNs) have been used extensively in surface water prediction tasks due to computing algorithm improvements and data accumulation. An essential step in developing an NN is the hyperparameter selection. In practice, it is common to manually determine hyperparameters in the studies of NNs in water resources tasks. This may result in considerable randomness and require significant computation time; therefore, hyperparameter optimization (HPO) is essential. This study adopted five representatives of the HPO techniques in the surface water quality prediction tasks, including the grid sampling (GS), random search (RS), genetic algorithm (GA), Bayesian optimization (BO) based on the Gaussian process (GP), and the tree Parzen estimator (TPE). For the evaluation of these techniques, this study proposed a method: first, the optimal hyperparameter value sets achieved by GS were regarded as the benchmark; then, the other HPO techniques were evaluated and compared with the benchmark in convergence, optimization orientation, and consistency of the optimized values. The results indicated that the TPE-based BO algorithm was recommended because it yielded stable convergence, reasonable optimization orientation, and the highest consistency rates with the benchmark values. The optimization consistency rates via TPE for the hyperparameters hidden layers, hidden dimension, learning rate, and batch size were 86.7%, 73.3%, 73.3%, and 80.0%, respectively. Unlike the evaluation of HPO techniques directly based on the prediction performance of the optimized NN in a single HPO test, the proposed benchmark-based HPO evaluation approach is feasible and robust.

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Catalytic denitrification over Pd-based catalysts under mild conditions has received significant attention as an emerging technology. However, the Pd particle size effect has been much less systematically investigated. Herein, carbon-supported Pd nanoparticles (NPs) with particle sizes ranging from 2.1 to 22.1 nm were synthesized and characterized using high-resolution transmission electron microscopy (HR-TEM), X-ray diffraction (XRD), CO-chemisorption, and X-ray photoelectron spectroscopy (XPS). Catalytic nitrite reduction experiments were conducted in a semi-batch reactor at room temperature. The results showed that the highest mass catalytic activity of 603.6 mg gPd−1min−1was obtained at the Pd size of 2.7 nm. The turnover frequency (TOF) and the N2selectivity increased gradually with the increasing Pd NP size. Considering both the mass catalytic activity and N2selectivity, the Pd catalyst with a size of approximately 5 nm had a better comprehensive performance. Mechanism studies showed that the enhanced TOF of larger Pd NPs could be ascribed to the formation of more β-hydride, which has a higher reducing activity than α-hydride. Compared with the terraces, the edges and corners of Pd NPs are the major active sites where ammonia is generated, most likely because of their low-coordination and electron-deficient properties. This indicated that the NO2−catalytic reduction is a size sensitive reaction in terms of both activity and selectivity, and may provide new insight into tailoring Pd NP size of Pd-based catalysts to improve catalytic activity and selectivity for nitrate and nitrite reduction in water.

Micro–nano bubble (MNB) aeration is an emerging technology that considerably enhances the aeration efficiency of wastewater. This study evaluates, for the first time, aerosolization at the water–air interface during MNB aeration. Our results show that the concentration of culturable mixed microorganisms (i.e., bacteria, fungi, and intestinal bacteria) in the in situ MNB generation (MNBs-G) phase is 2170 CFU/m3, 1.38 and 1.58-fold higher than those in medium-bubble aeration (MBA; 1568 CFU/m3) and small-bubble aeration (SBA; 1376 CFU/m3) aerosols, respectively. Conversely, the concentration of culturable mixed microorganisms in the MNB persistent dissolved oxygen (MNBs-O) phase is only 914 CFU/m3. Microbiological analysis shows a lower abundance of bacterial pathogens in MNBs-G (34.12%) and MNBs-O (34.02%) phases than in MBA (39.63%) and SBA (38.87%) aerosols. Acinetobacter is prevalent in MNBs-G (14.76%) and MNBs-O (8.22%) aerosols, whereas Bacillus and Arcobacter are prevalent in MBA (23.96%) and SBA (6.92%) aerosols, respectively. The total concentrations of chemicals [i.e., total organic carbon, water-soluble ions, and metal(loid)s] in aerosols formed via MNB aeration (205.98–373.74 μg/m3) are lower than those in MBA and SBA (398.69–594.92 μg/m3). Compared to MBA and SBA, the MNBs-G phase exhibits higher emissions of 12 elements in aerosols (i.e., NO3–, NO2–, Ca2+, Na+, K+, Mg2+, Zn, Cd, Fe, Mn, As, and Cr), whereas the MNBs-O phase generally shows lower emissions. These findings highlight the potential of optimized MNB aeration technology in considerably mitigating aerosol emissions and thereby advancing environmental sustainability in wastewater treatment.

An innovative treatment method by the combination of NaOH and nitrite is proposed for controlling hydrogen sulfide and methane in gravity sewers and overcome the drawbacks of the conventional single chemical treatment. Four reactors simulating gravity sewers were set up to assess the effectiveness of the proposed method. Findings demonstrated hydrogen sulfide and methane reductions of about 96.01% and 91.49%, respectively, by the combined addition of NaOH and nitrite. The consumption of NaNO2decreased by 42.90%, and the consumption rate of NaOH also showed a downward trend. Compared with a single application of NaNO2, the C/N ratio of wastewater was increased to about 0.61 mg COD/mg N. The greenhouse effect of intermediate N2O and residual methane was about 48.80 gCO2/m3, which is far lower than that of methane without control (260 gCO2/m3). Biofilm was destroyed to prevent it from entering the sewage by the chemical additives, which reduced the biomass and inhibited the recovery of biofilm activity to prolong the control time. The sulfide production rate and sulfate reduction rate were reduced by 92.32% and 85.28%, respectively. Compared with conventional control methods, the cost of this new method was only 3.92 × 10−3$/m3, which is potentially a cost-effective strategy for sulfide and methane control in gravity sewers.

AbstractThe infrared (IR) and Raman spectra of propylene carbonate (PC) containing various concentrations of LiClO4have been measured and analyzed. The difference in spectra of PC with and without LiClO4was attributed to the interaction of the PC molecules and lithium ions. This interaction occurs mainly on the carbonyl oxygen atom of the PC molecule. The ring deformation, symmetric ring deformation, carbonyl stretching and stretching of ring oxygens for PC are sensitive to this interaction. The solvation number of Li+is also calculated. On the other hand, the structure of the ClO−4is also affected by PC molecule, forming the solvent separated ion pairs.

The thermodynamic parameters of interaction of HCl with D-xylose in water were determined from electromotive force measurements from 278.15 to 318.15 K. The correlation between the pair interaction Gibbs free energy parameters for HCl-sugar (gHCl-S) and the mean number (n(e-OH)) of equatorial hydroxy groups in sugar molecules was found to be gHCl-S/J kg mol-2= (41.2 ± 2.1) + (16.88 ± 0.52)n(e-OH). Refractive indices of aqueous D-xylose solutions were measured and used to evaluate the polarizability of D-xylose molecule in water. Several theoretical models were used to calculate the salting constant of D-xylose. The results show that the calculated values are reasonably in agreement with the experimental ones.Key words: thermodynamics, HCl, D-xylose, interaction parameter, salting constant.

The concept of mean asociation number (MAN) has been proposed to describe the association state of an electrolyte. Both the mean spherical approximation (MSA) and the generalized mean spherical approximation (GMSA) are used to calculate the MAN. The theoretical results obtained are compared to the experiment results from an ultraviolet spectroscopic study of PbCl2-H2O-C2H5OH solutions and also to the predictions of the Bjerrum theory as given by Friedman.