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Kinetics of activated sludge protein extraction by thermal alkaline treatment
Journal of Environmental Chemical Engineering 5 (2017) 5352–5357
Contents lists available at ScienceDirect
Journal of Environmental Chemical Engineering journal homepage: www.elsevier.com/locate/jece
Research Paper
Kinetics of activated sludge protein extraction by thermal alkaline treatment a,⁎
b
T
a
Yulin Xiang , Yukun Xiang , Lipeng Wang a b
College of Chemistry and Chemical Engineering, Yulin University, Yulin 719000 Shaanxi Province, China Yanshou No.1 Middle School, Harbin 150700 Heilongjiang Province, China
A R T I C L E I N F O
A B S T R A C T
Keywords: Activated sludge Protein Extraction kinetics Response surface methodology Alkaline thermal hydrolysis
In order to explore an effective method to enhance application of activated sludge, kinetic model to describe extraction process of sludge protein was investigated based on experimental results. Relative molecular mass of sludge protein was tested using sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE). The results showed that the extraction mechanism of sludge protein under thermal alkaline hydrolysis condition was in line with first-order continuous reaction kinetics. The kinetic model was established to explain relationships among first-order rate constant, pH value, and temperature. The optimum conditions were sludge retention time of 21d, extraction time of 2h, pH of 12, and temperature of 130 °C. The extraction yield of sludge protein was 69% under the optimized conditions. Relatively molecular mass of sludge protein was between 26.478 kDa and 430.86 kDa, and the protein could be used as an excellent foaming agent.
1. Introduction In wastewater treatment plants, a large amount of waste activated sludge is produced each year. The estimated production of waste activated sludge in the China, USA and Europe is 4, 8 and 2 billion tons year−1. It is projected that these values will still increase in the nearly future [1]. The hazardous substances in sludge will bring to humankind not only environmental pollution, but also unexpected disasters once the control system loses effectiveness [2]. Therefore, the treatment of waste activated sludge has been become a major problem, and there is a need to devise sustainable methods to manage waste activated sludge. Waste activated sludge is mainly composed of extracellular polymeric substances (EPS), cations as well as some other fine particles [3]. Recently, waste activated sludge has been identified as a renewable resource to produce various value-added products such as protein, biofuel, biosolids, biopesticides and short chain fatty acids [4,5]. Among them, sludge protein has shown a great potential as low cost biological nutrient [6]. Sludge cell wall is hard to degrade [7]. Thus, the key of sludge protein extraction is to choose an appropriate method to degrade sludge cell wall. In order to improve the disintegration performance of sludge cell wall, thermal pretreatment [8], ultrasonic pretreatment [9] and microwave irradiation [10] etc. have been reported by several researchers. The combination of several pretreatment methods, such as microwave-alkaline [11], and thermo-alkaline [12], has caused extensive concern. Thermal alkaline pretreatment is a well-known method for the ⁎
break-up of microbial cells to extract the intracellular organic matters and it is one of the most powerful sludge disintegration methods [13]. In the process, the sludge disintegration was accelerated by thermoalkaline pretreatment, and sludge protein could be recovered from aqueous phase of waste activated sludge [14]. Among frequently-used alkali reagents, Ca(OH)2 is considered to be one of the best alkali reagents due to its high efficiency and low-cost [15]. One of the characteristics about sludge is high moisture content. In this situation, Ca (OH)2 can be produced through a reaction between CaO and sludge moisture, and the reaction is exothermic. Sludge could be dehydrated and sterilized to some degree during the early period of CaO action, then there were a series of reactions between Ca(OH)2 and sludge. Finally, sludge disintegration was fulfilled. In addition, CaO cost is lower than that of Ca(OH)2. Consequently, it is far better to treat sludge with CaO instead of Ca(OH)2. Studies on the kinetics and mechanism of the disintegration of waste activated sludge, however, are still being continued because of their scientific and practical importance. Therefore, with CaO as hydrolysis agent, kinetic models during the sludge protein extraction process were investigated in this study. 2. Materials and methods 2.1. Sample preparation and reactor requirements The activated sludge samples were collected from the Yuyang wastewater treatment plant in Yulin, China. The influent received by
Corresponding author. E-mail address: [email protected] (Y. Xiang).
http://dx.doi.org/10.1016/j.jece.2017.09.062 Received 23 March 2017; Received in revised form 11 September 2017; Accepted 29 September 2017 Available online 07 October 2017 2213-3437/ © 2017 Published by Elsevier Ltd.
Journal of Environmental Chemical Engineering 5 (2017) 5352–5357
Y. Xiang et al.
Table 1 Main components in activated sludge. Sludge source
Tanggu
SCOD (mg L−1)
380 ± 16.8
TCOD (mg L−1)
11560 ± 58.3
TSS (mg L−1)
VSS (mg L−1)
15960 ± 110.8
the wastewater treatment plant is 100% municipal wastewater. The sludge retention time (SRT) of system was 7～28d. The pH values of sludge samples were in the range of 7.8-9.8. The main components are illustrated in Table 1. The experiments were performed in a reactor, whose effective volume was 1L, working pressure was 9.8 MPa, and operating temperature was 300 °C. CaO: analytic grade was used.
To investigate the protein extraction yield of sludge hydrolysis process, a series of experiments were performed under different reaction conditions. During the experiment, firstly, the sludge sample was added into the reactor, then calcium oxide was gradually added into the reactor until a certain pH value (10, 11, 12, 13) was obtained; Secondly, the mixtures were heated until a certain temperature (110, 120, 130, 140 °C) for a certain time (1 to 5 h) before the power was cut off; Thirdly, the mixtures were cooled with cold water to room temperature (23 ± 2 °C) before the mixtures were removed from the reactor; Fourthly, the mixtures were centrifuged (3000 r/min for 15 min) to separate particulate and soluble fractions; Fifthly, total nitrogen measurements by Kjeldahl method was undertaken for indirect protein determination of filtrate (GB/T5009.5-2003) [16]. Protein extraction yield was determined by Eq. (1):
m1 × c1 × 100% m0 × c0
87.0409 ± 0.5
Protein content(%) wet basis
dry basis
4.5 ± 0.3
33.3 ± 0.6
Under thermal alkaline condition, protein in aqueous phase was continuously hydrolyzed to small molecules. For this process, the following pseudo-components were of particular interest, protein, peptone, peptides, oligopeptide, amino acid, degradation products of amino acid [6]. In order to simplify the reaction model, the following assumptions were made based on the research method of Ma et al. [19]:
2.2. Experimental procedure
Y=
11400 ± 90.5
Moisture content(%)
• The protein concentration in reaction materials was identified as the • •
initial reaction concentration (The concentration can be determined using the Kjeldahl nitrogen determination method); The initial protein concentration in aqueous phase was zero; The protein concentration in filtrate was identified as the concentration of reaction intermediates (The concentration can be determined by the semi-micro Kjeldahl nitrogen determination method). The total amount of various intermediates was protein amount.
Based on the assumptions above, the sludge protein extraction process was considered as first-order continuous reaction. For the first-order continuous reaction, it could be expressed as follow: k1
(1)
k2
Insoluble protein (C0) → soluble protein, peptides, amino acid (C1) →end products (urea, H2O, CO2) generated from amino acid (C2). The total volume of protein remained changeless in the experimental process. The equations of reaction rates can be expressed as follows:
Where Y is protein extraction yield, mo and m1 is mass of the sludge sample and filtrate, g, respectively; co and c1 is protein content of the sludge sample and filtrate, %, respectively. 2.3. SDS-PAGE method
dC0 = −k1 C0 dt
(2)
SDS-PAGE was performed based on the modified method of Laemmli [17]. Concentration of separating gel was 12%, and concentration of stacking gel was 4%. Standard proteins come from Shanghai Institute of Biochemistry, Chinese Academy of Sciences. The composition and relative molecular mass of the standard proteins are as follows: Bovine serum albumin (Mr. 66200), Rabbit actin (Mr. 43000), Rabbit phosphorylase B (Mr. 97400), Bovine carbonic anhydrase (Mr. 31000), Trypsin inhibitor (Mr. 20100), Egg white lysozyme (Mr. 14400). The protein solutions were centrifuged at 3000 rpm for 10 min. Sludge protein solution (2.5 mg/mL) was mixed 1:1 with Lammeli buffer (25% glycerol, 0.01% bromophenol blue, 2% SDS, 62.5 mM TrisHCl, pH 6.8) to a final concentration of 1 mg/mL. Electrophoresis buffer contained 0.2 M glycine, 0.1% SDS, and 20 mM Tris-HCl at pH 8.3. SDSPAGE was run with 4 °C running buffer at room temperature. Protein solutions were loaded onto gels and run at 100 V for 40 min using a Mini-Protean III cell (Bio-Rad) and PowerPac Basic power supply. Gels were stained using a colloidal blue stain kit followed by destaining for 3 to 5 h. Protein molecular weights were analyzed using the software GelPro analyzer (version 6.3).
dC1 = k1 C0 − k2 C1 dt
(3)
dC2 = k2 C1 dt
(4)
Based on the Laplace transformation, the above equations are transformed as follows:
C0 = CA0 e−k1 t C1 =
k1 CA0 (e−k2 t − e−k1 t ) k1 − k2
k2 k1 C2 = CA0 ⎡1 − e−k1 t − e−k2 t ⎤ ⎥ ⎢ k2 − k1 k1 − k2 ⎦ ⎣
(5)
(6)
(7)
Where Cj (j = 0, 1, 2)is the protein concentration in the sludge solution at j time, g/L; CA0 is the initial concentration of sludge protein, g/L; k1 is the first-order rate constant at the first stage, h−1, and k2 is the firstorder rate constant at the second stage, h−1; and t is reaction time, h.
2.4. Analysis of reaction kinetics mechanism
3. Results and discussion
Sludge protein extraction process included two stages: sludge cell disintegration and intracellular matter release. Chemical reaction essence of the process was cleavage of amide bond [18]:
3.1. Determination of the k1 and k2 During the reaction process, the intermediate concentration (C1) 5353
Journal of Environmental Chemical Engineering 5 (2017) 5352–5357
Y. Xiang et al.
Fig. 1. The intermediate concent (C1) and non-linear fitting curves (SRT = 18d, pH = 10, pH = 11, pH = 12 and pH = 13).
could be accurately measured according to the Kjeldahl method, then the values of k1 and k2 could be determined by non-linear fitting method based on Eq. (6). The values of k1 and k2 were obtained by using Origin software and non-linear fitting method (see Fig. 1 and Table 1). According to Table 1, the values of k1 and k2, and the ratio of rate constants (k1/k2) gradually increased with the increase of temperature and pH. The protein theoretical maximum in the solution increased with the increase of the ratio of k1/k2. In other words, with the ratio growing, the degradation rate of sludge microbial cells increased, leading to the more release of intracellular protein. Under high temperature and high pH conditions, the release rate of protein was higher than the degradation rate of amino acid. The trend is similar to the findings of Cui et al. [6]. However, sensory quality of sludge protein would decline when pH was more than 12 and temperature was more than 130 °C.
Table 2 Results of variance analysis.
3.2.1. Analysis of k1 by RSM According to Table 1, k1 was influenced by temperature and pH. In order to determine the relationships between k1 and pH, and temperature, the equation about their relationships is proposed by the multiple linear regression method, as follow:
Degree of freedom (DF)
Mean square sum (MS)
F
P
Regression Surplus Sum total
SRe = 0.7343 SSu = 0.005307 SSt = 0.7385
5 10 15
0.1454 0.000531 –
276.21 –
< 0.001
Item
Degree of freedom (DF)
Mean square sum (MS)
F
P(Prob > F)
pH T pH2 pH × T T2
1 1 1 1 1
0.0667 0.0090 0.0539 0.0308 0.0027
126.74 17.53 106.14 61.20 5.27
P P P P P
< < < < <
0.001(21.05) 0.01(10.02) 0.001 0.001 0.025
was significant under the confidence level of α=0.05. The significance of these coefficients decreased in a sequence of pH > pH2 > pH × T > T > T2. Consequently, k1 was influenced by pH and T as well as the interaction between the two factors. The relationships are shown in Fig. 2. As shown in Fig. 2, k1 increased with the increase of pH and T. Under the conditions of T ＜ 120 °C and pH ＜ 11, the curves in Fig. 2b were comparatively sparse, which implied that k1 changed relatively slowly. The conditions were not favorable for sludge hydrolysis. Conversely, under the conditions of T > 120 °Cand pH > 11, the curves in Fig. 2b showed comparatively dense, k1 changed quickly. The conditions were favorable for cell disintegration and protein extraction.
(8)
Where βi (i = 0～5) is regression coefficient. The regression model about k1 is as follow:
k1 = 12.074 − 1.6277pH − 6.2859 × 10−2T + 5.8095 × 10−2pH 2 + 3.5252 × 10−3pH × T + 1.2933 × 10−4T 2
Square sum (S)
Table 3 Results of variance analysis.
3.2. Analysis of k1, k2 and C∞ by response surface methodology (RSM)
k1 = β0 + β1 pH + β2 T + β3 pH 2 + β4 pH × T + β5 T 2
Item
(9)
Table 2 shows the results of variance analysis for the regression equation. According to Table 2, the results showed that the regression equation were of high significance. Table 3 shows the results of variance analysis for the equation coefficients. In accordance with Table 3, each item of the regression equation
3.2.2. Analysis of k2 by RSM According to Table 1, k2 was effected by temperature and pH. In order to determine the relationships between k2 and pH, and temperature, the equation about their relationships is obtained by the 5354
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Fig. 2. The interference of pH and temperature on k1(a: Response surface curve; b: Contour plot).
Table 4 Results of analysis of variance.
Table 5 Results of analysis of variance.
Item
Sum of square (S)
Degree of freedom (DF)
Mean square sum (MS)
F
P
Item
Sum of square(S)
Degree of freedom (DF)
Mean square sum (MS)
F
P
Regression Surplus Sum total
SRe = 0.004311 SSu = 0.0001596 SSt = 0.004471
5 10 15
0.0085 1.6 × 10−5 –
53.97 –
< 0.001
Regression Surplus Sum total
SRe = 6.866 SSu = 0.07124 SSt = 6.9367
5 10 15
1.374 0.007145 –
192.1897 –
< 0.001
Correlation coefficient: R = 0.9820.
Correlation coefficient:R = 0.9948.
The response results are shown in Fig. 4. According to Fig. 4, C∞ increased with the increase of pH and temperature. It can be seen that the curves near to pH in Fig. 4b were denser, which implied that the influence of pH on C∞ was greater than that of temperature. In conclusion, an increase in pH was more favorable for sludge protein extraction.
multiple linear regression method, as follow:
10−2
10−3pH
10−4T +
k2 = −6.9769 × + 3.8861 × + 7.1854 × 7.3812 × 10−4pH 2 − 8.427 × 10−5pH × T + 5.1437 × 10−6T 2
(10)
Table 4 shows the results of variance analysis for Eq. (10). According to Table 4, the results showed that Eq. (10) was of high significance. The response results are shown in Fig. 3. As shown in Fig. 3, k2 gradually increased with the increase of pH and temperature. the curves in Fig. 3b showed a relatively uniform distribution, which indicated that k2 changed slowly with the increase of pH and temperature.
3.3. Effect of SRT on k1, k2 and C∞ SRT of the sampling system was 7, 14, 21, 28d, respectively. pH was 12, temperature was 130 °C, and extraction time was 2 h. Table 6 shows the effect of SRT on k1, k2 and C∞. k1, k2 and C∞ increased with an increase in SRT from 7 to 21d and decreased when the SRT increased to 28d. At 21 days of SRT, k1 was 0.6635 h−1, k2 was 0.13547 h−1, and C∞ was 4.0983 g/L, and the condition was favorable for the protein extraction. The tendency was also consistent with that of Li [20]. With the running time prolonging, on the one hand, the protein concentration of extracellular was significantly increased, which was beneficial to extracting protein; On the other hand, as the dead bacteria began to accumulate in the system, bacteria propagation would be inhibited, and sludge activity decreased [21]. Consequently, a higher running time exceeding the SRT of 21d had negative effects on bacteria propagation and sludge activity, resulting in a decrease of the extraction rate of sludge protein.
3.2.3. Analysis of C∞ by RSM According to Table 1, the theoretical maximum (C∞) of protein in solution was influenced by pH and temperature. In order to determine the relationships between C∞ and pH, and temperature, the equation about their relationships is obtained by the multiple linear regression method, as follow:
C∞ = −4.6359 − 9.5494 × 10−1pH + 1.3813 × 10−1T + 9.1496 × 10−2pH 2 − 5.4083 × 10−3pH × T + 1.7196 × 10−4T 2 (11) Table 5 shows the results of variance analysis for Eq. (11). It can be seen from Table 5 that Eq. (11) was of high significance.
Fig. 3. The interference of pH and temperature on k2 (a: Response surface curve; b: Contour plot).
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Fig. 4. The interference of pH and temperature on C∞ (a: Response surface curve; b: Contour plot).
According to previous work [22], the size of protein between 20 kDa and 450 kDa had excellent foaming properties, and the protein could be used to produce foam concrete and foam fire extinguishing agent.
Table 6 Effect of SRT on k1, k2 and C∞. SRT(d)
k1 (h−1)
k2 (h−1)
C∞(g/L)
7 14 21 28
0.25843 0.40913 0.6635 0.6546
0.12366 0.12415 0.13647 0.13291
3.1380 3.7576 4.0983 4.0115
4. Conclusions The extraction mechanism of the sludge protein under thermal alkaline conditions was in line with first-order continuous reaction kinetics. The influences of pH and temperature on the reaction rate constants and theoretical maximum of protein were analyzed using response surface methodology. The contour plots showed that the change rates of the rate constant at the second stage and protein theoretical maximum were uniform, while the rate constant at the first stage gradually increased with the increase of temperature and pH. In detail, the rate constant at the first stage increased significantly under pH above 11 and the temperature above 120 °C, which indicated that the conditions were favorable for the disintegration of sludge microbial cells and protein release. When the sludge retention time of the sampling system was 21d, extraction time was 2h, pH was 12, and temperature was 130 °C, the protein extraction yield could reach 69%. The size of the sludge protein was between 26.478 kDa and 430.86 kDa, and the protein can be used as an excellent foaming agent.
Correlation coefficient:R ＞ 0.98.
Acknowledgments The work is supported by the Scientific Research Starting Foundation for High-level Professionals in Yulin University of China (No. 12GK04), and the Key Laboratory Project Foundation of Shaanxi Provincial Education Department in China (17JS144). Fig. 5. Protein light intensity analysis.
References
In general, the time at which the sludge concentration begins to fall is the system's SRT [20]. In this study, the sludge concentration reached a maximum when the running time was 36 d, but now, the degradation rate of organic matter from the sludge was significantly lower than that of 21 d. It can be seen that the two results about SRT are significantly different. If sludge reduction and protein extraction are considered at the same time, the determination of SRT still needs further investigation. The main purpose of this paper is to achieve higher protein yield, consequently, the most suitable SRT in the sludge hydrolysis system is 21 days.
[1] Roel J.W. Meulepas, Graciela Gonzalez-Gil, Fitfety Melese Teshager, Ayoma Witharana, Pascal E. Saikaly, Piet N.L. Lens, Anaerobic bioleaching of metals from waste activated sludge, Sci. Total Environ. 514 (2015) 60–67. [2] E.W. Low, H.A. Chase, Reducing production of excess biomass during wastewater treatment, Water Resour. 33 (5) (1999) 119–1132. [3] D.H. Li, J.J. Ganczarczyk, Structure of activated sludge flocs, Biotechnol. Bioeng. 35 (1) (1990) 57–65. [4] Y. Liu, X. Li, X. Kang, Y. Yuan, M. Du, Short chain fatty acids accumulation and microbial community succession during ultrasonic-pretreated sludge anaerobic fermentation process: effect of alkaline adjustment, Int. Biodeterior. Biodegrad. 94 (2014) 128–133. [5] M.Z. Alam, A. Fakhru'l-Razi, A.H. Molla, Biosolids accumulation and biodegradation of domestic wastewater treatment plant sludge by developed liquid state bioconversion process using a batch fermenter, Water Res. 37 (2003) 3569–3578. [6] J. Cui, A. Dong, W. Zhang, F. Miao, Experimental investigation of extracting protein by alkaline thermal sludge hydrolysis from sludge, Chin. J. Environ. Eng. 3 (10) (2009) 1889–1892. [7] S.S. Chishti, S.N. Hasnain, M.A. Khan, Studies on the recovery of sludge protein, Water Res. 26 (2) (1992) 241–248. [8] S. Sahinkaya, M.F. Sevimli, Sono-thermal pretreatment of waste activated sludge before anaerobic digestion, Ultrason. Sonochem. 20 (2013) 587–594. [9] S. Sahinkaya, M.F. Sevimli, Effects and modeling of ultrasonic waste-activated sludge disintegration, Water Environ. J. 27 (2013) 238–246. [10] Q. Yang, J. Yi, K. Luo, X. Jing, X. Li, Y. Liu, G. Zeng, Improving disintegration and
3.4. SDS-PAGE analysis SRT of the sampling system was 21d, under such conditions: extraction time 2 h, pH 12, and temperature 130 °C, the protein extraction yield could reach 69%. Fig. 5 shows light intensity analysis of the sludge protein. As seen from Fig. 5, SDS-PAGE analysis suggested that the size of the sludge protein was between 26.478 kDa and 430.86 kDa. 5356
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method extraction protocol for protein quantification in activated sludge, Bioresour. Technol. 99 (16) (2008) 7464–7471. B.X. Fu, H.D. Sapirstein, Procedure for isolating monomeric proteins and polymeric glutenin of wheat flour, Cereal Chem. 73 (1) (1996) 143–152. Q. Zhou, Y. Gao, Environmental Engineering Microbiology, Advanced Education Press, Beijing, 2000, pp. 26–29. H. Ma, Q. Li, S. Li, Kinetics study on pulsed ultrasound-assisted extraction of protein and polysaccharide from defatted rice bran, J. Agric. Mach. 42 (11) (2011) 135–138. S. Li, Y. Liu, C. Cui, J. Huang, Effect of SRT on kinetics of polluted substance removal by sludge system in MBR, Chin. J. Environ. Eng. 1 (5) (2007) 105–108. Y. Miron, G. Zeeman, J.B. Van Lier, G. Lettinga, The role of sludge retention time in the hydrolysis and acidification of lipids, carbohydrates and proteins during digestion of primary sludge in CSTR systems, Water Res. 34 (2000) 1705–1713. Y. Xiang, L. Wang, Y. Jiao, Feasibility research on the performance improvement of sludge protein solution by 60Co γ ray synergia H2O2, Chem. Ind. Eng. Progr. 34 (2) (2015) 561–564.
Contents lists available at ScienceDirect
Journal of Environmental Chemical Engineering journal homepage: www.elsevier.com/locate/jece
Research Paper
Kinetics of activated sludge protein extraction by thermal alkaline treatment a,⁎
b
T
a
Yulin Xiang , Yukun Xiang , Lipeng Wang a b
College of Chemistry and Chemical Engineering, Yulin University, Yulin 719000 Shaanxi Province, China Yanshou No.1 Middle School, Harbin 150700 Heilongjiang Province, China
A R T I C L E I N F O
A B S T R A C T
Keywords: Activated sludge Protein Extraction kinetics Response surface methodology Alkaline thermal hydrolysis
In order to explore an effective method to enhance application of activated sludge, kinetic model to describe extraction process of sludge protein was investigated based on experimental results. Relative molecular mass of sludge protein was tested using sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE). The results showed that the extraction mechanism of sludge protein under thermal alkaline hydrolysis condition was in line with first-order continuous reaction kinetics. The kinetic model was established to explain relationships among first-order rate constant, pH value, and temperature. The optimum conditions were sludge retention time of 21d, extraction time of 2h, pH of 12, and temperature of 130 °C. The extraction yield of sludge protein was 69% under the optimized conditions. Relatively molecular mass of sludge protein was between 26.478 kDa and 430.86 kDa, and the protein could be used as an excellent foaming agent.
1. Introduction In wastewater treatment plants, a large amount of waste activated sludge is produced each year. The estimated production of waste activated sludge in the China, USA and Europe is 4, 8 and 2 billion tons year−1. It is projected that these values will still increase in the nearly future [1]. The hazardous substances in sludge will bring to humankind not only environmental pollution, but also unexpected disasters once the control system loses effectiveness [2]. Therefore, the treatment of waste activated sludge has been become a major problem, and there is a need to devise sustainable methods to manage waste activated sludge. Waste activated sludge is mainly composed of extracellular polymeric substances (EPS), cations as well as some other fine particles [3]. Recently, waste activated sludge has been identified as a renewable resource to produce various value-added products such as protein, biofuel, biosolids, biopesticides and short chain fatty acids [4,5]. Among them, sludge protein has shown a great potential as low cost biological nutrient [6]. Sludge cell wall is hard to degrade [7]. Thus, the key of sludge protein extraction is to choose an appropriate method to degrade sludge cell wall. In order to improve the disintegration performance of sludge cell wall, thermal pretreatment [8], ultrasonic pretreatment [9] and microwave irradiation [10] etc. have been reported by several researchers. The combination of several pretreatment methods, such as microwave-alkaline [11], and thermo-alkaline [12], has caused extensive concern. Thermal alkaline pretreatment is a well-known method for the ⁎
break-up of microbial cells to extract the intracellular organic matters and it is one of the most powerful sludge disintegration methods [13]. In the process, the sludge disintegration was accelerated by thermoalkaline pretreatment, and sludge protein could be recovered from aqueous phase of waste activated sludge [14]. Among frequently-used alkali reagents, Ca(OH)2 is considered to be one of the best alkali reagents due to its high efficiency and low-cost [15]. One of the characteristics about sludge is high moisture content. In this situation, Ca (OH)2 can be produced through a reaction between CaO and sludge moisture, and the reaction is exothermic. Sludge could be dehydrated and sterilized to some degree during the early period of CaO action, then there were a series of reactions between Ca(OH)2 and sludge. Finally, sludge disintegration was fulfilled. In addition, CaO cost is lower than that of Ca(OH)2. Consequently, it is far better to treat sludge with CaO instead of Ca(OH)2. Studies on the kinetics and mechanism of the disintegration of waste activated sludge, however, are still being continued because of their scientific and practical importance. Therefore, with CaO as hydrolysis agent, kinetic models during the sludge protein extraction process were investigated in this study. 2. Materials and methods 2.1. Sample preparation and reactor requirements The activated sludge samples were collected from the Yuyang wastewater treatment plant in Yulin, China. The influent received by
Corresponding author. E-mail address: [email protected] (Y. Xiang).
http://dx.doi.org/10.1016/j.jece.2017.09.062 Received 23 March 2017; Received in revised form 11 September 2017; Accepted 29 September 2017 Available online 07 October 2017 2213-3437/ © 2017 Published by Elsevier Ltd.
Journal of Environmental Chemical Engineering 5 (2017) 5352–5357
Y. Xiang et al.
Table 1 Main components in activated sludge. Sludge source
Tanggu
SCOD (mg L−1)
380 ± 16.8
TCOD (mg L−1)
11560 ± 58.3
TSS (mg L−1)
VSS (mg L−1)
15960 ± 110.8
the wastewater treatment plant is 100% municipal wastewater. The sludge retention time (SRT) of system was 7～28d. The pH values of sludge samples were in the range of 7.8-9.8. The main components are illustrated in Table 1. The experiments were performed in a reactor, whose effective volume was 1L, working pressure was 9.8 MPa, and operating temperature was 300 °C. CaO: analytic grade was used.
To investigate the protein extraction yield of sludge hydrolysis process, a series of experiments were performed under different reaction conditions. During the experiment, firstly, the sludge sample was added into the reactor, then calcium oxide was gradually added into the reactor until a certain pH value (10, 11, 12, 13) was obtained; Secondly, the mixtures were heated until a certain temperature (110, 120, 130, 140 °C) for a certain time (1 to 5 h) before the power was cut off; Thirdly, the mixtures were cooled with cold water to room temperature (23 ± 2 °C) before the mixtures were removed from the reactor; Fourthly, the mixtures were centrifuged (3000 r/min for 15 min) to separate particulate and soluble fractions; Fifthly, total nitrogen measurements by Kjeldahl method was undertaken for indirect protein determination of filtrate (GB/T5009.5-2003) [16]. Protein extraction yield was determined by Eq. (1):
m1 × c1 × 100% m0 × c0
87.0409 ± 0.5
Protein content(%) wet basis
dry basis
4.5 ± 0.3
33.3 ± 0.6
Under thermal alkaline condition, protein in aqueous phase was continuously hydrolyzed to small molecules. For this process, the following pseudo-components were of particular interest, protein, peptone, peptides, oligopeptide, amino acid, degradation products of amino acid [6]. In order to simplify the reaction model, the following assumptions were made based on the research method of Ma et al. [19]:
2.2. Experimental procedure
Y=
11400 ± 90.5
Moisture content(%)
• The protein concentration in reaction materials was identified as the • •
initial reaction concentration (The concentration can be determined using the Kjeldahl nitrogen determination method); The initial protein concentration in aqueous phase was zero; The protein concentration in filtrate was identified as the concentration of reaction intermediates (The concentration can be determined by the semi-micro Kjeldahl nitrogen determination method). The total amount of various intermediates was protein amount.
Based on the assumptions above, the sludge protein extraction process was considered as first-order continuous reaction. For the first-order continuous reaction, it could be expressed as follow: k1
(1)
k2
Insoluble protein (C0) → soluble protein, peptides, amino acid (C1) →end products (urea, H2O, CO2) generated from amino acid (C2). The total volume of protein remained changeless in the experimental process. The equations of reaction rates can be expressed as follows:
Where Y is protein extraction yield, mo and m1 is mass of the sludge sample and filtrate, g, respectively; co and c1 is protein content of the sludge sample and filtrate, %, respectively. 2.3. SDS-PAGE method
dC0 = −k1 C0 dt
(2)
SDS-PAGE was performed based on the modified method of Laemmli [17]. Concentration of separating gel was 12%, and concentration of stacking gel was 4%. Standard proteins come from Shanghai Institute of Biochemistry, Chinese Academy of Sciences. The composition and relative molecular mass of the standard proteins are as follows: Bovine serum albumin (Mr. 66200), Rabbit actin (Mr. 43000), Rabbit phosphorylase B (Mr. 97400), Bovine carbonic anhydrase (Mr. 31000), Trypsin inhibitor (Mr. 20100), Egg white lysozyme (Mr. 14400). The protein solutions were centrifuged at 3000 rpm for 10 min. Sludge protein solution (2.5 mg/mL) was mixed 1:1 with Lammeli buffer (25% glycerol, 0.01% bromophenol blue, 2% SDS, 62.5 mM TrisHCl, pH 6.8) to a final concentration of 1 mg/mL. Electrophoresis buffer contained 0.2 M glycine, 0.1% SDS, and 20 mM Tris-HCl at pH 8.3. SDSPAGE was run with 4 °C running buffer at room temperature. Protein solutions were loaded onto gels and run at 100 V for 40 min using a Mini-Protean III cell (Bio-Rad) and PowerPac Basic power supply. Gels were stained using a colloidal blue stain kit followed by destaining for 3 to 5 h. Protein molecular weights were analyzed using the software GelPro analyzer (version 6.3).
dC1 = k1 C0 − k2 C1 dt
(3)
dC2 = k2 C1 dt
(4)
Based on the Laplace transformation, the above equations are transformed as follows:
C0 = CA0 e−k1 t C1 =
k1 CA0 (e−k2 t − e−k1 t ) k1 − k2
k2 k1 C2 = CA0 ⎡1 − e−k1 t − e−k2 t ⎤ ⎥ ⎢ k2 − k1 k1 − k2 ⎦ ⎣
(5)
(6)
(7)
Where Cj (j = 0, 1, 2)is the protein concentration in the sludge solution at j time, g/L; CA0 is the initial concentration of sludge protein, g/L; k1 is the first-order rate constant at the first stage, h−1, and k2 is the firstorder rate constant at the second stage, h−1; and t is reaction time, h.
2.4. Analysis of reaction kinetics mechanism
3. Results and discussion
Sludge protein extraction process included two stages: sludge cell disintegration and intracellular matter release. Chemical reaction essence of the process was cleavage of amide bond [18]:
3.1. Determination of the k1 and k2 During the reaction process, the intermediate concentration (C1) 5353
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Fig. 1. The intermediate concent (C1) and non-linear fitting curves (SRT = 18d, pH = 10, pH = 11, pH = 12 and pH = 13).
could be accurately measured according to the Kjeldahl method, then the values of k1 and k2 could be determined by non-linear fitting method based on Eq. (6). The values of k1 and k2 were obtained by using Origin software and non-linear fitting method (see Fig. 1 and Table 1). According to Table 1, the values of k1 and k2, and the ratio of rate constants (k1/k2) gradually increased with the increase of temperature and pH. The protein theoretical maximum in the solution increased with the increase of the ratio of k1/k2. In other words, with the ratio growing, the degradation rate of sludge microbial cells increased, leading to the more release of intracellular protein. Under high temperature and high pH conditions, the release rate of protein was higher than the degradation rate of amino acid. The trend is similar to the findings of Cui et al. [6]. However, sensory quality of sludge protein would decline when pH was more than 12 and temperature was more than 130 °C.
Table 2 Results of variance analysis.
3.2.1. Analysis of k1 by RSM According to Table 1, k1 was influenced by temperature and pH. In order to determine the relationships between k1 and pH, and temperature, the equation about their relationships is proposed by the multiple linear regression method, as follow:
Degree of freedom (DF)
Mean square sum (MS)
F
P
Regression Surplus Sum total
SRe = 0.7343 SSu = 0.005307 SSt = 0.7385
5 10 15
0.1454 0.000531 –
276.21 –
< 0.001
Item
Degree of freedom (DF)
Mean square sum (MS)
F
P(Prob > F)
pH T pH2 pH × T T2
1 1 1 1 1
0.0667 0.0090 0.0539 0.0308 0.0027
126.74 17.53 106.14 61.20 5.27
P P P P P
< < < < <
0.001(21.05) 0.01(10.02) 0.001 0.001 0.025
was significant under the confidence level of α=0.05. The significance of these coefficients decreased in a sequence of pH > pH2 > pH × T > T > T2. Consequently, k1 was influenced by pH and T as well as the interaction between the two factors. The relationships are shown in Fig. 2. As shown in Fig. 2, k1 increased with the increase of pH and T. Under the conditions of T ＜ 120 °C and pH ＜ 11, the curves in Fig. 2b were comparatively sparse, which implied that k1 changed relatively slowly. The conditions were not favorable for sludge hydrolysis. Conversely, under the conditions of T > 120 °Cand pH > 11, the curves in Fig. 2b showed comparatively dense, k1 changed quickly. The conditions were favorable for cell disintegration and protein extraction.
(8)
Where βi (i = 0～5) is regression coefficient. The regression model about k1 is as follow:
k1 = 12.074 − 1.6277pH − 6.2859 × 10−2T + 5.8095 × 10−2pH 2 + 3.5252 × 10−3pH × T + 1.2933 × 10−4T 2
Square sum (S)
Table 3 Results of variance analysis.
3.2. Analysis of k1, k2 and C∞ by response surface methodology (RSM)
k1 = β0 + β1 pH + β2 T + β3 pH 2 + β4 pH × T + β5 T 2
Item
(9)
Table 2 shows the results of variance analysis for the regression equation. According to Table 2, the results showed that the regression equation were of high significance. Table 3 shows the results of variance analysis for the equation coefficients. In accordance with Table 3, each item of the regression equation
3.2.2. Analysis of k2 by RSM According to Table 1, k2 was effected by temperature and pH. In order to determine the relationships between k2 and pH, and temperature, the equation about their relationships is obtained by the 5354
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Fig. 2. The interference of pH and temperature on k1(a: Response surface curve; b: Contour plot).
Table 4 Results of analysis of variance.
Table 5 Results of analysis of variance.
Item
Sum of square (S)
Degree of freedom (DF)
Mean square sum (MS)
F
P
Item
Sum of square(S)
Degree of freedom (DF)
Mean square sum (MS)
F
P
Regression Surplus Sum total
SRe = 0.004311 SSu = 0.0001596 SSt = 0.004471
5 10 15
0.0085 1.6 × 10−5 –
53.97 –
< 0.001
Regression Surplus Sum total
SRe = 6.866 SSu = 0.07124 SSt = 6.9367
5 10 15
1.374 0.007145 –
192.1897 –
< 0.001
Correlation coefficient: R = 0.9820.
Correlation coefficient:R = 0.9948.
The response results are shown in Fig. 4. According to Fig. 4, C∞ increased with the increase of pH and temperature. It can be seen that the curves near to pH in Fig. 4b were denser, which implied that the influence of pH on C∞ was greater than that of temperature. In conclusion, an increase in pH was more favorable for sludge protein extraction.
multiple linear regression method, as follow:
10−2
10−3pH
10−4T +
k2 = −6.9769 × + 3.8861 × + 7.1854 × 7.3812 × 10−4pH 2 − 8.427 × 10−5pH × T + 5.1437 × 10−6T 2
(10)
Table 4 shows the results of variance analysis for Eq. (10). According to Table 4, the results showed that Eq. (10) was of high significance. The response results are shown in Fig. 3. As shown in Fig. 3, k2 gradually increased with the increase of pH and temperature. the curves in Fig. 3b showed a relatively uniform distribution, which indicated that k2 changed slowly with the increase of pH and temperature.
3.3. Effect of SRT on k1, k2 and C∞ SRT of the sampling system was 7, 14, 21, 28d, respectively. pH was 12, temperature was 130 °C, and extraction time was 2 h. Table 6 shows the effect of SRT on k1, k2 and C∞. k1, k2 and C∞ increased with an increase in SRT from 7 to 21d and decreased when the SRT increased to 28d. At 21 days of SRT, k1 was 0.6635 h−1, k2 was 0.13547 h−1, and C∞ was 4.0983 g/L, and the condition was favorable for the protein extraction. The tendency was also consistent with that of Li [20]. With the running time prolonging, on the one hand, the protein concentration of extracellular was significantly increased, which was beneficial to extracting protein; On the other hand, as the dead bacteria began to accumulate in the system, bacteria propagation would be inhibited, and sludge activity decreased [21]. Consequently, a higher running time exceeding the SRT of 21d had negative effects on bacteria propagation and sludge activity, resulting in a decrease of the extraction rate of sludge protein.
3.2.3. Analysis of C∞ by RSM According to Table 1, the theoretical maximum (C∞) of protein in solution was influenced by pH and temperature. In order to determine the relationships between C∞ and pH, and temperature, the equation about their relationships is obtained by the multiple linear regression method, as follow:
C∞ = −4.6359 − 9.5494 × 10−1pH + 1.3813 × 10−1T + 9.1496 × 10−2pH 2 − 5.4083 × 10−3pH × T + 1.7196 × 10−4T 2 (11) Table 5 shows the results of variance analysis for Eq. (11). It can be seen from Table 5 that Eq. (11) was of high significance.
Fig. 3. The interference of pH and temperature on k2 (a: Response surface curve; b: Contour plot).
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Fig. 4. The interference of pH and temperature on C∞ (a: Response surface curve; b: Contour plot).
According to previous work [22], the size of protein between 20 kDa and 450 kDa had excellent foaming properties, and the protein could be used to produce foam concrete and foam fire extinguishing agent.
Table 6 Effect of SRT on k1, k2 and C∞. SRT(d)
k1 (h−1)
k2 (h−1)
C∞(g/L)
7 14 21 28
0.25843 0.40913 0.6635 0.6546
0.12366 0.12415 0.13647 0.13291
3.1380 3.7576 4.0983 4.0115
4. Conclusions The extraction mechanism of the sludge protein under thermal alkaline conditions was in line with first-order continuous reaction kinetics. The influences of pH and temperature on the reaction rate constants and theoretical maximum of protein were analyzed using response surface methodology. The contour plots showed that the change rates of the rate constant at the second stage and protein theoretical maximum were uniform, while the rate constant at the first stage gradually increased with the increase of temperature and pH. In detail, the rate constant at the first stage increased significantly under pH above 11 and the temperature above 120 °C, which indicated that the conditions were favorable for the disintegration of sludge microbial cells and protein release. When the sludge retention time of the sampling system was 21d, extraction time was 2h, pH was 12, and temperature was 130 °C, the protein extraction yield could reach 69%. The size of the sludge protein was between 26.478 kDa and 430.86 kDa, and the protein can be used as an excellent foaming agent.
Correlation coefficient:R ＞ 0.98.
Acknowledgments The work is supported by the Scientific Research Starting Foundation for High-level Professionals in Yulin University of China (No. 12GK04), and the Key Laboratory Project Foundation of Shaanxi Provincial Education Department in China (17JS144). Fig. 5. Protein light intensity analysis.
References
In general, the time at which the sludge concentration begins to fall is the system's SRT [20]. In this study, the sludge concentration reached a maximum when the running time was 36 d, but now, the degradation rate of organic matter from the sludge was significantly lower than that of 21 d. It can be seen that the two results about SRT are significantly different. If sludge reduction and protein extraction are considered at the same time, the determination of SRT still needs further investigation. The main purpose of this paper is to achieve higher protein yield, consequently, the most suitable SRT in the sludge hydrolysis system is 21 days.
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