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Wang Z.,Beijing University of Chemical Technology | Zhang Q.,Beijing University of Chemical Technology | Yang L.,Aerospace Environmental Engineering Ltd Company | Lyu Y.,The Filter | Zhao S.,Beijing Xindayu Environmental Protection Engineering Co.

In this paper, the impacts of cleaning conditions on the cleaning efficiency of 0.1μm polyethersulfone (PES) membrane fouled by active sludge suspension from SBR were investigated systematically. The experiments were performed in dead-end microfiltration cell, using oxalic acid, chlorhydric acid, citric acid, sodium hypochlorite and sodium hydroxide as the chemical cleaning agents. The orthogonal method was applied to analyze the experimental data. The results showed that chemical cleaning could restore almost all of the permeate flux. However, its cleaning ability was reduced gradually with the increase of cleaning cycles, which results from the increasing accumulation of irreversible foulants onto the membrane surface or in the pores. The two-stage chemical cleaning procedure which uses sodium hypochlorite and citric acid sequentially is a more effective way. The sequence of cleaning conditions on average change rate of the cumulative permeate volume is pHsodium hypochlorite (22.4%)>pHcitric acid (20.3%)>Tsodium hypochlorite (16.4%)>Vcitric acid (14.4%)>Tcitric acid (13.2%)>Vsodium hypochlorite (11.2%)>tsodium hypochlorite (1.2%)>tcitric acid (0.9%). Higher temperature, more dosage volume, and strong basicity or acidity of the cleaning solution are beneficial to chemical cleaning operation. © 2013 Elsevier B.V. Source

Xu J.,Tianjin University | Xu J.,Tianjin University of Technology | Wang L.,Aerospace Environmental Engineering Ltd Company | Zhi Z.,Tianjin University | And 3 more authors.
Energy and Fuels

In this study, formic acid was selected as the catalyst to pretreat corn stover which is also a good substrate for biohydrogen and biogas production. The pretreatment effect and the acidogenic characteristic of hydrolysates were also evaluated. Using corn stover (8.00 g) mixed with 72.00 g of formic acid (2.5%) at temperature 190°C for reaction time 10 min, 17.36 ± 0.80 g/L glucose, 18.13 ± 0.83 g/L xylose, 5.45 ± 0.25 g/L arabinose, 3.88 ± 0.17 g/L acetic acid, and 1.96 ± 0.07 g/L furfural were obtained in the hydrolysate. The kinetic parameters of the Saeman model were determined to predict the percentage of xylan remaining in the substrate and the xylose in the liquid. Two kinds of specific hydrolysates (the highest yield of total sugar and highest yield of furfural) in the following acidogenic fermentation experiments were examined. The results indicated that both of the hydrolysates were shown to be butyric acid type fermentation and got the highest VFAs concentration of 6.3 ± 0.48 g/L. Diluted formic acid had good catalytic effects on the hydrolysis of corn stover. The hydrolysates obtained from the pretreatment process could be used as good substrates for acidogenic fermentation process. © 2015 American Chemical Society. Source

Zhao X.,Tianjin University | Wang L.,Aerospace Environmental Engineering Ltd Company | Lu X.,Tianjin University | Zhang S.,Tianjin University
Bioresource Technology

A Box-Behnken design of response surface method was used to optimize acetic acid-catalyzed hydrothermal pretreatment of corn stover, in respect to acid concentration (0.05-0.25%), treatment time (5-15. min) and reaction temperature (180-210. °C). Acidogenic fermentations with different initial pH and hydrolyzates were also measured to evaluate the optimal pretreatment conditions for maximizing acid production. The results showed that pretreatment with 0.25% acetic acid at 191. °C for 7.74. min was found to be the most optimal condition for pretreatment of corn stover under which the production of acids can reach the highest level. Acidogenic fermentation with the hydrolyzate of pretreatment at the optimal condition at the initial pH. = 5 was shown to be butyric acid type fermentation, producing 21.84. g acetic acid, 7.246. g propionic acid, 9.170 butyric acid and 1.035. g isovaleric acid from 100. g of corn stover in 900. g of water containing 2.25. g acetic acid. © 2014 Elsevier Ltd. Source

Wang Z.,Beijing University of Technology | Yang L.,Beijing University of Technology | Yang L.,Aerospace Environmental Engineering Ltd Company | Lyu Y.,The Filter | And 4 more authors.
Separation Science and Technology (Philadelphia)

The applicability of model predictive accuracy and the selection of suitable model parameters for the membrane flux prediction and prediction of the filtration characteristics of dead-end filtration systems were assessed. In determining the model predictive accuracy using model parameters, the selection of suitable model parameters is of great significance. A series of experiments were conducted. The relative deviations, average deviations, and root mean square between the experimental and predicted values were calculated to evaluate predictive accuracy. The results showed that the model parameter has changed nonlinearly with operating conditions. Particularly, in the membrane flux prediction model, the time-dependent character of the model parameter can result in a considerable error. However, model prediction accuracy can be improved indisputably and the model will get higher predictive accuracy than that of other predictive models if the constant membrane fouling index in the flux prediction model is either replaced by the average membrane fouling index or it takes a composite parameter with free combination of the initial membrane fouling index, meantime, minimum and the maximum of the model parameter. These results give us a possibility to see the panorama of the variation of the model parameters in different situations and an idea to establish the foundation for building mathematical models. ©, Taylor & Francis Group, LLC. Source

Si Z.,Tianjin University | Si Z.,Aerospace Environmental Engineering Ltd Company | Sun B.,Tianjin University | Li X.,Tianjin University
Chinese Journal of Environmental Engineering

In view of the air quality data shortage and high fluctuation, we combined grey model(GM (1, 1)) with artificial neural network to establish an integration model. Then, improved grey neural network model (IGNNM) was presented by improving this combination model. As raw data, the annual average value of PM10, SO2 and NO2 from 2001 to 2008 in Tianjin City was used to simulate. Meanwhile, the concentrations of PM10, SO2 and NO2 in 2009 to 2010 were forecasted to check the precision of this model. Finally, the air quality of Tianjin between 2011 and 2015 was predicted by using this proposed model. The results show that the model mentioned can be employed in air quality prediction as its less relative simulation error and higher reliability, compared with grey model and traditional grey neural network model. Source

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