Insights on the solubilization products after combined alkaline and ultrasonic pre-treatment of sewage sludge

This work provides insights on the solubilization products after a simultaneous combination of alkaline and ultrasonic (ALK + ULS) pre-treatment of sewage sludge. Soluble chemical oxygen demand (SCOD) increased from 1200 to 11,000 mg/L after such treatment. Organics with molecular weight around 5.6 kDa were solubilized because of the synergistic effect of ultrasound and alkali. Organics with molecular weight larger than 300 kDa increased from 7.8% to 60%, 16% and 42.3% after ULS, ALK and ALK + ULS treatment, respectively. Excitation emission matrix fluorescence spectroscopy analysis identified soluble microbial product-like and humic acid-like matters as the main solubilization products. Sludge anaerobic biodegradability was significantly enhanced with the simultaneous application of ALK + ULS pre-treatment. ALK + ULS pre-treatment resulted in 37.8% biodegradability increase compared to the untreated sludge. This value was higher compared to the biodegradability increase induced by individual ALK pre-treatment (5.7%) or individual ULS pre-treatment (20.7%) under the same conditions applied.     

Insights on the solubilization products after combined alkaline and ultrasonic pre-treatment of sewage sludge

This work provides insights on the solubilization products after a simultaneous combination of alkaline and ultrasonic (ALK + ULS) pre-treatment of sewage sludge. Soluble chemical oxygen demand (SCOD) increased from 1200 to 11,000 mg/L after such treatment. Organics with molecular weight around 5.6 kDa were solubilized because of the synergistic effect of ultrasound and alkali. Organics with molecular weight larger than 300 kDa increased from 7.8% to 60%, 16% and 42.3% after ULS, ALK and ALK + ULS treatment, respectively. Excitation emission matrix fluorescence spectroscopy analysis identified soluble microbial product-like and humic acid-like matters as the main solubilization products. Sludge anaerobic biodegradability was significantly enhanced with the simultaneous application of ALK + ULS pre-treatment. ALK + ULS pre-treatment resulted in 37.8% biodegradability increase compared to the untreated sludge. This value was higher compared to the biodegradability increase induced by individual ALK pre-treatment (5.7%) or individual ULS pre-treatment (20.7%) under the same conditions applied.     

Unraveling the size distributions of surface properties for purple soil and yellow soil

Soils contain diverse colloidal particles whose properties are pertinent to ecological and human health, whereas few investigations systematically analyze the surface properties of these particles. The objective of this study was to elucidate the surface properties of particles within targeted size ranges(i.e. 10, 1–10, 0.5–1, 0.2–0.5 and 0.2 μm) for a purple soil(Entisol) and a yellow soil(Ultisol) using the combined determination method. The mineralogy of corresponding particle-size fractions was determined by X-ray diffraction.We found that up to 80% of the specific surface area and 85% of the surface charge of the entire soil came from colloidal-sized particles( 1 μm), and almost half of the specific surface area and surface charge came from the smallest particles( 0.2 μm). Vermiculite,illite, montmorillonite and mica dominated in the colloidal-sized particles, of which the smallest particles had the highest proportion of vermiculite and montmorillonite. For a given size fraction, the purple soil had a larger specific surface area, stronger electrostatic field, and higher surface charge than the yellow soil due to differences in mineralogy.Likewise, the differences in surface properties among the various particle-size fractions can also be ascribed to mineralogy. Our results indicated that soil surface properties were essentially determined by the colloidal-sized particles, and the 0.2 μm nanoparticles made the largest contribution to soil properties. The composition of clay minerals within the diverse particle-size fractions could fully explain the size distributions of surface properties.     

CFRP筋增强钢纤维混凝土梁受剪承载力试验与分析∗

对 CFRP 箍筋和纵筋增强钢纤维混凝土梁的受剪承载力进行研究,通过 6 根梁的加载试验研究了剪跨比、配箍率和箍筋种类对受剪承载力的影响。考虑 CFRP 纵筋与混凝土的粘结性能,建立了 CFRP 筋增强钢纤维梁受剪承载力计算方法。结果表明：①CFRP 筋增强钢纤维混凝土梁受剪承载力高,破坏前斜裂缝宽度大,破坏有明显预兆;②钢纤维可有效减小斜截面开裂后前期的 CFRP 箍筋应力,有利于箍筋强度发挥,CFRP 箍筋的极限应变可取为 0.004;③CFRP 纵筋发挥强度高,需注意锚固长度和设计使用应力,防止滑移拔出和销栓破断;④给出的受剪承载力计算方法具有较高的计算精度高。     

兰州市城区河道表层沉积物重金属污染及磁学参数相关关系研究

以兰州市城区8条河流的表层沉积物为研究载体,通过Hakanson潜在生态风险指数法、地质累积指数法及富集因子评价法等3种污染评价指标以及环境磁学方法对As、Co、Cr、Cu、Ni、Pb、V、Zn共8种重金属元素污染特征进行分析.结果显示,①元素As、Co、Ni、V在8条河流中均表现为轻微生态危害;元素Cr、Pb、Zn在...     

生物制药污水处理中自动控制系统运行的分析

污水处理中,自动控制系统的运行方式关系到污水处理是否达标的关键,尤其是在运行细节中,运行控制考虑得不周全,往往会影响到污水处理的效果。生物制药污水处理中,设备在运行细节控制方法中的有效解决,保证了出水稳定可靠。     

Mineral nutrient imbalance, DNA lesion and DNA-protein crosslink involved in growth retardation of Vicia faba L. seedlings exposed to lanthanum ions

Effects of mineral nutrient imbalance, DNA lesion and DNA-protein crosslink on growth of Vicia faba L. seedlings hydroponically cultivated in concentrations of extraneous lanthanum (La) for 20 days were investigated in the present experiment. The results showed that contents of La, Cu or K elements in roots generally changed synchronously with those in leaves, while Ca, Fe, Zn, Mg, Mn or P in the roots altered inversely to those in the leaves. Thus, the extraneous La led to redistribution and imbalance of mineral nutrient elements in the roots and leaves. DNA lesion and DNA-protein crosslink were investigated by single cell gel electrophoresis (SCGE) and sodium dodecyl sulfate/potassium (SDS/K⁺) precipitation methods, respectively. The results demonstrated that the increasing La induced DNA break and DNA-protein crosslinks (DPCs) in the seedlings. These results suggested that mineral nutrient imbalance, DNA lesion and DNA-protein crosslink were involved in the growth retardation and growth alteration of the seedlings, which may help to understand the mechanisms of rare earth elements (REEs) on plant growth.     

Preparation of birnessite-supported Pt nanoparticles and their application in catalytic oxidation of formaldehyde

Flaky and nanospherical birnessite and birnessite-supported Pt catalysts were successfully prepared and characterized by means of X-ray diffraction (XRD), transmission electron microscopy (TEM), energy dispersive spectroscopy (EDS) and N₂ adsorption-desorption. Effects of the birnessite morphology and Pt reduction method on the catalytic activity for the complete oxidation of formaldehyde (HCHO) were investigated. It was found that flaky birnessite exhibited higher catalytic activity than nanospherical birnessite. The promoting effect of Pt on the birnessite catalyst indicated that the reduction method of the Pt precursor greatly influenced the catalytic performance. Flaky birnessite-supported Pt nanoparticles reduced by KBH₄ showed the highest catalytic activity and could completely oxidize HCHO into CO₂ and H₂O at 50℃, whereas the sample reduced using H₂-plasma showed lower activity for HCHO oxidation. The differences in catalytic activity of these materials were jointly attributed to the effects of pore structure, surface active sites exposed to HCHO and the dispersion of Pt nanoparticles.     

Removal of sulfamethazine antibiotics by aerobic sludge and an isolated Achromobacter sp. S-3

Removal characteristics of sulfamethazine (SMZ) by sludge and a bacterial strain using an aerobic sequence batch reactor (ASBR) were studied. Operating conditions were optimized by varying the reaction time and sludge retention time (SRT). An Achromobacter sp. (S-3) with the ability to remove SMZ was isolated from the ASBR. The effects of different operating parameters (pH and temperature) on the biodegradation of SMZ by S-3 were determined. The results indicate that, between 0.5 and 4 hr, reaction time of the ASBR had a significant effect on the SMZ removal efficiency in the system. The SMZ removal efficiency also increased from 45% to 80% when SRT was prolonged from 5 to 25 days, although longer SRT had no impact on SMZ removal. The SMZ adsorption rate decreased with increasing temperature, which fitted Freundlich isotherm well. The removal of SMZ in the ASBR was due to the combined effects of adsorption and degradation, and degradation played a leading role.     

A hybrid Wavelet-CNN-LSTM deep learning model for short-term urban water demand forecasting

● A novel deep learning framework for short-term water demand forecasting. ● Model prediction accuracy outperforms other traditional deep learning models. ● Wavelet multi-resolution analysis automatically extracts key water demand features. ● An analysis is performed to explain the improved mechanism of the proposed method. Short-term water demand forecasting provides guidance on real-time water allocation in the water supply network, which help water utilities reduce energy cost and avoid potential accidents. Although a variety of methods have been proposed to improve forecast accuracy, it is still difficult for statistical models to learn the periodic patterns due to the chaotic nature of the water demand data with high temporal resolution. To overcome this issue from the perspective of improving data predictability, we proposed a hybrid Wavelet-CNN-LSTM model, that combines time-frequency decomposition characteristics of Wavelet Multi-Resolution Analysis (MRA) and implement it into an advanced deep learning model, CNN-LSTM. Four models - ANN, Conv1D, LSTM, GRUN - are used to compare with Wavelet-CNN-LSTM, and the results show that Wavelet-CNN-LSTM outperforms the other models both in single-step and multi-steps prediction. Besides, further mechanistic analysis revealed that MRA produce significant effect on improving model accuracy.