Bioresource Technology 151 (2014) 106–112
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Bioresource Technology journal homepage: www.elsevier.com/locate/biortech
Study on anaerobic treatment of hazardous steel-mill waste rolling oil (SmWRO) for multi-benefit disposal route Huanhuan Ma a, Zifu Li a,⇑, Fubin Yin a, William Kao b, Yi Yin a, Xiaofeng Bai a a b
School of Civil and Environment Engineering, University of Science and Technology Beijing, Beijing 100083, China Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
h i g h l i g h t s BMP test of steel-mill waste rolling oil (SmWRO) was conducted. Both temperature and ISR showed significant effect on methane yield. ISR of 1.5 and 2 at 35 °C and 1.5 at 55 °C were suggested with the highest biogas yield. Linear regression of substrate VS load against gas production could predict gas yield coefficient. Gompertz model best fitted the experimental data, while Exponential model not suitable.
a r t i c l e
i n f o
Article history: Received 25 July 2013 Received in revised form 11 October 2013 Accepted 15 October 2013 Available online 22 October 2013 Keywords: Steel-mill waste rolling oil (SmWRO) Anaerobic digestion Inoculum to substrate ratio (ISR) Temperature Gompertz model
a b s t r a c t Steel-mill waste rolling oil (SmWRO) is considered as hazardous substance with high treatment and disposal fees. Anaerobic process could not only transform the hazardous substance into activated sludge, but also generate valuable biogas. This study aimed at studying the biochemical methane potential of SmWRO under inoculum to substrate VS ratios (ISRs) of 0.25, 0.5, 1, 1.5, 2 and 3 using septic tank sludge as inoculum in mesophilic and thermophilic conditions, with blank tests for control. Specific biogas yield (mL/g VSadded), net biogas yield (mL/g VSremoved) and VS removal were analyzed. The ANOVA results indicated great influence of ISR and temperature on studied parameters. ISR of 1.5 at 55 °C and ISR of 1.5 and 2 at 35 °C were suggested with the highest specific biogas yield (262–265 and 303 mL/g VSadded). Kinetic analysis showed that Gompertz model fit the experimental data best with the least RMSE and largest R2. Ó 2013 Elsevier Ltd. All rights reserved.
1. Introduction A great amount of rolling oil is used as lubricant and oxidative protective coating during rolling, cutting, lapping, etc., in sheet metal processing and sheet steel manufacturing. Rolling oil hydrolyzes, oxidizes and accumulates particulate (dust and iron particles) during operation and needs to be replaced. Hence large amount of waste rolling oil is produced, here referred as steel-mill waste rolling oil (SmWRO). The characteristics of SmWRO vary greatly with the original composition of the oil and the process conditions from which it is derived. Due to its oleo chemical content and variety of chemical additives, it will cause serious environmental problem if untreated or improperly treated before disposal. Normally, it is treated as hazardous materials in China
⇑ Corresponding author. Tel./fax: +86 1062334378. E-mail address: [email protected] (Z. Li). 0960-8524/$ - see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.biortech.2013.10.051
(EPAC, 2008) and the disposal price is very high if treated by special companies. Anaerobic digestion (AD), as a traditional stabilization technology for disposing organic wastes, has received growing worldwide interest in recent years as a result of the increasing cost of fossil fuels and global warming (Xie et al., 2011). Through anaerobic treatment, SmWRO can be transformed into harmless activated sludge with biogas as by-product. In recent years, biochemical methane potential (BMP) tests have been commonly carried out to assess the biodegradability and methane production potential of different organic wastes from various sources (Raposo et al., 2011; González-Fernández and García-Encina, 2009). BMP tests are usually conducted in closed jars or bottles under appropriate temperature in batch mode. To accelerate the start-up rate of digestion, usually there is a need to add certain quantity of inoculum, which contains the microbes, especially methanogens that is necessary for biochemical conversion. The amount of inoculum is expressed as inoculum to substrate ratio (ISR), which often has complex impact on biogas production depending on the characteristics of organic wastes and inoculum (Li and Xiao, 2012; Lopes et al., 2004; Neves et al., 2004).
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AD process, especially the hydrolysis of organic matter is generally assumed to follow first-order kinetics. As a matter of fact, to reach full digestion, the entire degradation process includes three reaction phases: lag phase, exponential phase and steady phase (Li et al., 2011). The duration of the lag phase is also an important factor in determining the efficiency of AD and can be calculated with a modified Gompertz model, which fit the experimental data well (Kafle and Kim, 2013; Li et al., 2011; Xie et al., 2011). Whereas El-Mashad (2013) found that the Cone model best described methane production from the co-digestion of switchgrass and spirulina platensis algae, and the Gompertz model failed to predict the lag phase accurately under the studied conditions. According to Pitt et al. (1999), interpretation of gas production model parameters may be difficult in some cases, especially among comparison of different feedstocks. To the best of our knowledge, no previous studies have examined the AD of SmWRO; therefore, this study mainly aims at: (1) estimating the BMP and gas production rate of SmWRO under different ISRs in both mesophilic and thermophilic temperatures, (2) determining the ideal ISR in each temperature to achieve maximum methane production based on ANOVA, (3) studying the kinetics of SmWRO AD to serve better for future pilot test. 2. Methods 2.1. Analysis and calculation methods Total solid (TS) and Volatile solid (VS) were determined according to standard gravimetric methods 2540B and 2540E (APHA, 1989). It should be mentioned that for this special substrate, the measured TS content was actually a mixture of solid and oil (MSO). Total organic carbon (TOC) and total nitrogen (TN) were determined by a modified Kjedahl determination (CCAS, 1985). Oil content was tested using the reported petroleum ether extraction method (Jiang and Dong, 2008). pH was measured by a pHmeter (Mettle-Toledo Delta 320). Biogas production was read directly through the measuring cylinder and then adjusted to volume at standard temperature (0 °C) and pressure (1 atm) (STP).
V STP ¼
V T 273 ð760 PW Þ ð273 þ TÞ 760
ð1Þ
where, VSTP means the volume of gas calculated at standard temperature and pressure (mL), T is the temperature of the collected fermentation gas (°C), VT is the volume of gas measured at temperature T (mL) and PW means the saturated water vapor pressure at temperature T (mm Hg). Biogas production was read on daily basis. Biogas composition was analyzed every day during the first two weeks and then every two or three days by a portable gas analyzer (Geotech-Biogas check), which was calibrated using standard mixed gas prior to usage. Daily methane content was determined by linearly interpolating the measured methane contents (El-Mashad, 2013).
CX CN CM CX ¼ XN MX
ð2Þ
where, X means the day after day N and before day M after inoculation; CN and CM mean the measured methane contents at day N and M; CX means the calculated methane content at day X. 2.2. Characteristics and features of the substrate and inoculum The SmWRO sample used in this study was taken from a cold rolling steel-mill located at Xiamen city, southeast China. The original rolling oil before being mixed with lots of water in cold rolling process is water miscible, consisting of synthetic ester (30–
40%), refined fat (50–60%), refined mineral oil (1–10%) and other additives and agents. Prior to starting the experiment, the sample was preserved in a refrigerator that could provide a constant temperature of 4 °C for 4 days. This storage had no observable effect on the composition (Faisal and Unno, 2001). The TS and VS of the samples before and after storage were tested in triplicate, which showed little difference. Fresh sludge obtained from an ordinary septic-tank, which was treating domestic wastewater from residential area on the campus of our university, was used as inoculum. The inoculum was just taken out from the tank the day before inoculation to ensure high methanogenic activity and then was separately placed in a mesophilic and thermophilic water bath. Analysis of main features and compositions of the substrate and inoculum was conducted before the experiment (Table 1). The substrate contained about 53.6% of oil, counting for 80% of total organic matter. Total organic matter was computed by multiplying TOC by 1.724 (Guo et al., 2012). All measurements were performed in triplicate and the result was expressed as means with standard deviation.
2.3. Experimental set-up The experiment was carried out in a multi-batch reactor system that allowed better comparability and homogenization among different flasks (Fig. 1). Two such set-ups were applied simultaneously for mesophilic (35 ± 1 °C) and thermophilic (55 ± 1 °C) fermentation. Chynoweth et al. (1993) suggested an ISR (on VS basis) of 2 in AD, while Owen et al. (1979) proposed an ISR of about 1. For this study, batch anaerobic digestion of SmWRO with anaerobic sludge as inoculum were studied at six different ISRs (0.25, 0.5, 1, 1.5, 2 and 3), expressed as R1, R2, R3, R4, R5 and R6 respectively. Within the range of these ISRs, all the carbon-to-nitrogen ratios (C/N) of the mixture were between 19 and 25, which were within the optimal range for AD (Kayhanian and Tchobanoglous, 1992). This was achieved by keeping a constant inoculum addition (6 g VS) and varying the substrate amount from 24 to 2 g VS, as shown in Table 2. After adding the required amount of substrate and inoculum, all the 1 L fermentation flasks were filled with distilled water to achieve an effective working volume of 0.7 L. Then they were placed separately in mesophilic and thermophilic water bath, numbered as M1–M6 and T1–T6. The biogas generated was collected through a gas-guide tube inserted into the digester headspace to allow venting of the biogas into a graduated cylinder by water displacement. In addition, blank tests of inoculum under both temperatures were carried out as controls, i.e. number M0 and T0. There were no additional elements or buffer agents added to the fermentation flasks in the process, except for strict control of the temperature and sealed environment. The flasks were shaken manually for 30 s once a day in order to avoid local acidification and achieve better mixing of microorganisms and substrate. The VS content of fermentation residues was analyzed when gas production almost ceased. Table 1 Initial characteristics of the waste oil and inoculum sludge. Characteristics
Substrate
Inoculum
Total solids (wt.% as received) Volatile solids (wt.% dry basis) Total organic carbon (wt.% dry basis) Total nitrogen (wt.% dry basis) Oil (wt.% as received) Total organic matter (wt.% as received) pH
77.0 ± 0.9 80.9 ± 1.9 50.9 ± 1.1 1.95 ± 0.1 53.6 ± 1.2 67.6 ± 1.2 6.75 ± 0.25
8.7 ± 0.5 85.7 ± 1.1 55.1 ± 1.2 3.1 ± 0.2 – 8.2 ± 0.3 7.05 ± 7.25
Values are expressed as mean (standard deviation). TS of substrate means the mixture content of solid and oil (MSO).
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Fig. 1. Experimental set-up.
Table 2 Experimental parameters for the batch AD test of different ISRs. Number
R0 R1 R2 R3 R4 R5 R6
(M0, (M1, (M2, (M3, (M4, (M5, (M6,
Inoculum
T0) T1) T2) T3) T4) T5) T6)
Substrate
ISR (VS basis)
VS (g)
Concentration (g VS L1)
VS (g)
Concentration (g VS L1)
6.00 6.00 6.00 6.00 6.00 6.00 6.00
8.57 8.57 8.57 8.57 8.57 8.57 8.57
0.00 24.00 12.00 6.00 4.00 3.00 2.00
0.00 34.29 17.14 8.57 5.71 4.29 2.86
2.4. Statistical analysis The effect of temperature and ISR on specific gas yield, average methane content and VS removal was studied based on two-factor analysis of variance without repeated trials (ANOVA) in Excel software 2007. To conduct pairwise comparison and decide whether two or more measured parameters were significantly different or not, the Least Significant Difference (LSD) was calculated at a = 0.05 (LSD0.05) and at a = 0.01 (LSD0.01) as follows (Little and Hills, 1978):
rffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 2 MSE LSDa ¼ ta n
2.5.2. Model evaluation Three indicators were employed to compare the studied models. The correlation index (R2) and root mean square error (EMSE), derived from statistical analysis, were quantified to describe the accuracy of the models (Kafle and Kim, 2013). The difference (Dif.%) between specific methane yield (B) and ultimate methane yield (B0) was also calculated to provide more information on the regression results. All the kinetic analysis was based on Matlab software R2011. 3. Results and discussions
ð3Þ
where ta is the t value chosen for degree of freedom for error at significance level a, MSE means the mean square for error, n is the sample size for the studied parameter.
2.5. Study on anaerobic digestion kinetics 2.5.1. The equations of selected models Exponential (Veeken and Hamelers, 1999), Gompertz (Zwietering et al., 1990) and Cone (Pitt et al., 1999) model were selected to fit the experimental data and the equations are:
BðtÞ ¼ B0 ð1 expðktÞ Þ e Rm BðtÞ ¼ B0 exp exp ðk tÞ þ 1 B0 B0 BðtÞ ¼ n 1 þ ðktÞ
1/0 0.25 0.5 1.0 1.5 2.0 3.0
ð4Þ ð5Þ ð6Þ
where, B(t) is cumulative methane yield at day t (mL/g VSadded), B0 is ultimate methane yield, i.e., methane potential (mL/g VSadded), k is methane production rate constant (day1), t is the digestion time (days), e is exp (1) = 2.718282, Rm is the maximum methane production rate (mL/g VSadded day), k is the lag phase (days) and n is shape factor (dimensionless).
3.1. Gas production and yield The daily biogas production (after subtracting the corresponding biogas volume produced from the inoculum) at different ISRs in mesophilic and thermophilic conditions were respectively shown in Fig. 2A and B. It should be mentioned that the biogas production increased with the decrease of ISR due to higher substrate VS loading, except for R1. After 40 days of digestion, final biogas production of 1054, 2061, 1312, 1048, 797 and 430 mL were achieved for M1– M6, and the time needed to produce 90% of the final biogas production were 32, 28, 26, 25, 23 and 19 days; And for T1–T6, final biogas production were accordingly 1404, 2278, 1386, 1215, 864 and 503 mL, and the time needed to produce 90% of the final biogas production were 26, 25, 25, 23, 23 and 19 days. It can be seen that there were two biogas yield peaks for most of the tests. The first gas yield peak appeared at the second or third day after inoculation, while the time to reach the second gas yield peak was longer at lower ISRs in both mesophilic and thermophilic conditions, except for R1, which failed to reach high gas yield. The second biogas production peaks were 34, 142, 82, 68, 51 and 26 mL/day for M1–M6 at day 22, 24, 23, 20, 15 and 16 respectively; and second biogas production peaks were 61, 141, 78, 80, 57 and 29 mL/day for T1–T6 at day 16, 17, 21, 18, 15 and 15 respectively. So thermophilic fermentation showed no obvious effect on increasing the peak biogas yield, but surely reduced the time to reach it. The biogas production of R3–R6 almost ceased since day 33 in mesophilic digestion and day 29 in thermophilic digestion, as a result of shortage for soluble biodegradable organic matters.
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M1
M2
M3
M4
M5
M6
180 130 80 30 (20)
1
3
5
7
9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39
Cumulative biogas yield (mL/g VSadded)
Daily biogas production (mL)
230
350.0 300.0 250.0 200.0 150.0 100.0 50.0 0.0
M1
1
3
5
7
Time (day)
M2
M3
M4
M5
M6
9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 Time (day)
(A)
Daily biogas production (mL)
230
T1
T2
T3
T4
T5
T6
180 130 80 30
Cumulative biogas yield (mL/g VSadded)
(A)
350.0 300.0 250.0 200.0 150.0 100.0 50.0 0.0
T1
1 (20)
1
3
5
7
3
5
7
9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39
T2
T6
Cumulative methane yield (mL/g VSadded)
M1
M2
M3
M4
M5
M6
200.0 150.0 100.0 50.0 0.0 1
3
5
7
9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 Time (day)
(C) 250.0 Cumulative methane yield (mL/g VSadded)
Cumulative biogas and methane yield can be determined by dividing the cumulative biogas and methane production by the VS content initially added in each ISR, as plotted in Fig. 3. It was apparent that R1 under both temperatures failed to reach a cumulative biogas yield of above 100 mL/g VSadded. It might have been caused by the relative high substrate VS loading (34.29 g/L) and the microbes could not successfully adapt to the environment. Both cumulative biogas and methane were much higher for M4 and M5 than the other tests in mesophilic conditions. For thermophilic digestion, the cumulative gas yield decreased when ISR was raised to T5 and T6. The reason may be that more energy and organic materials were consumed by cellular growth and maintenance (anabolism) under such high ISR. The ANOVA test showed that there was no significant difference between R4 and R5 experiment (p > 0.05) under both temperatures. Conducting linear regression of substrate VS loading against final gas production under different ISRs, the slope of the line expresses the average gas yield coefficient (Ym, mL/g VSadded) in the range of stated VS loading (Raposo et al., 2006). The final biogas and methane production in both temperatures were plotted with the substrate VS load of 2, 3, 4 and 6 g (VS loading of 2.86, 4.29, 5.71 and 8.57 g/L), shown in Fig. 4. The result showed that the average biogas and methane yield coefficients at mesophilic conditions were 213.0 and 151.3 mL/g VSadded; and a little bit higher at thermophilic conditions as 216.4 and 163.9 mL/g VSadded. This suggests that the effect of increasing substrate VS load on increasing specific gas yield was more significant in thermophilic digestion than in mesophilic digestion. The average methane yield coefficient obtained by Raposo et al. (2006), when conducting mesophilic AD of maize with anaerobic sludge from WWTP as inoculum at ISRs of 3, 2, 1.5 and 1 (substrate VS loading of 5, 7.5, 10 and 15 g/L, respectively), was 211 mL/g VSadded, about 1.4 times that of this experiment. So the average gas yield coefficient may be different even under the same ISR, depending on the characteristics of the substrate and inoculum used. In this study, the relative lower substrate VS loading might reduce the microbial activity.
T5
(B) 250.0
T1
T2
T3
T4
T5
T6
200.0 150.0 100.0 50.0 0.0 1
3
5
7
9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 Time (day)
(D) Fig. 3. Variation of cumulative gas yield (mL/g VSadded) with time at different ISRs in both mesophilic and thermophilic conditions: (A) Cumulative biogas yield in mesophilic condition; (B) Cumulative biogas yield in thermophilic condition; (C) Cumulative methane yield in mesophilic condition; (D) Cumulative methane yield in thermophilic condition.
1600 Specific gas production (mL)
Fig. 2. Variation of daily biogas production (mL) with time at different ISRs in both mesophilic (A) and thermophilic conditions (B).
T4
9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 Time (day)
Time (day)
(B)
T3
Biogas-M
Biogas-T
Methane-M
Methane-T
y = 216.44x + 180.65 R² = 0.8902 (Biogas-T) y = 213.01x + 98.26 R² = 0.9381 (Biogas-M)
1400 1200
y = 163.94x + 54.316 R² = 0.8873 (Methane-T)
1000
y = 151.34x + 24.237 R² = 0.9259 (Methane-M)
800 600 400 200 0 1.00
2.00
3.00 4.00 5.00 Substrate VS load (gVS)
6.00
7.00
Fig. 4. Final gas production volume (mL) at each of the applied substrate VS load (2–6 g VS, R6–R3) and the linear regression result.
3.2. Pairwise comparisons of the parameters Final methane production at the end of digestion time were 251, 1336, 881, 713, 516, 256 mL (mesophilic) and 368, 1514,
966, 844, 562, 302 mL (thermophilic), calculated based on daily biogas production and daily methane content. Average methane content was determined by dividing final biogas production by
H. Ma et al. / Bioresource Technology 151 (2014) 106–112
final methane production. Thus specific biogas and methane yield can be worked out (Table 3). The fermentation of R1 was considered to have failed and thus not discussed in the following test, with specific methane yield of 10.5 mL/g VSadded (mesophilic, Fig. 3C) and 15.3 mL/g VSadded (thermophilic, Fig. 3D) much lower than the other tests. Judging from Table 3, both specific biogas yield and specific methane yield showed the trend of first increasing and then decreasing, as ISR changing from 0.5 to 3 (R2–R6), regardless of temperature. Therefore, the authors conducted a quadratic polynomial fitting and the result was shown in Fig. 5. In the range of ISRs stated, specific biogas yield at thermophilic conditions was higher than at mesophilic conditions, as well as specific methane yield. However, the correlation coefficients for specific biogas yield and specific methane yield were only 0.91 and 0.87 at thermophilic conditions. Whereas, the correlation coefficients were both 0.98 at mesophilic conditions, indicating that the binomial model describes the experimental results well for mesophilic digestion and can be used to estimate the specific gas yield under specific ISR. As shown in Fig. 5, it is possible to reach high specific gas yield at ISRs of 1.5–2 at mesophilic conditions. It can be seen in Table 3 that specific biogas yield between R4 and R5 in both temperatures showed little difference (3.7 and 15.5), but was significantly different among all the other ISRs (LSD0.05 = 18.7 and LSD0.01 = 32.8). Specific methane yield at mesophilic conditions showed similar rules, and only the difference between R4 and R5 was not significant (LSD0.05 = 12.1 and LSD0.01 = 21.3). However, very significant difference appeared for specific methane yield between any two ISRs at thermophilic conditions (with the highest specific methane yield of 211.2 mL/g VSadded at R4). This may be explained by the significant difference of average methane content at thermophilic conditions (LSD0.05 = 1.4 and LSD0.01 = 2.4). Although the difference of average methane content between R4 and R5 was also significant in mesophilic digestion, the difference of specific methane yield could be reduced by the very tiny difference of specific biogas yield between R4 and R5. Besides, temperature displayed very significant effect on specific methane yield (LSD0.05 = 7.6 and LSD0.01 = 13.5), as well as on specific biogas yield (LSD0.05 = 11.8 and LSD0.01 = 20.8). According to Yang (2007) and Bushwell equation (Symons and Bushwell, 1933), the methane content was related to the chemical components of the waste: the theoretical methane yield of fat was about 1.6–2.1 times of protein and 2.4–2.8 times of carbohydrate. Thus the high content of oil in this substrate might have contributed to the higher value of methane percentage (especially for R3, R4 and R5), compared to the methane content of about 52% from the blank assay. H2S volume content was always in the range of 10–1000 ppm for all tests. Thus biogas generated from SmWRO digestion has the potential to be a source of high quality bioenergy.
350.0 Specific gas yield (mL/g VSadded)
110
Biogas-M
Methane-M
Biogas-T
Methane-T
300.0 y = -69.893x2 + 283.28x + 23.921 R² = 0.9119 (Biogas-T) y = -46.31x2 + 180.45x + 90.804 R² = 0.9886 (Biogas-M)
250.0 200.0
y = -58.87x2 + 226.95x - 7.2067 R² = 0.8714 (Methane-T) y = -36.57x2 + 134.86x + 52.285 R² = 0.9808 (Methane-M)
150.0 100.0 50.0 0.0 0.00
0.50
1.00 1.50 2.00 2.50 Inoculum to substrate ratio (on VS basis)
3.00
3.50
Fig. 5. Specific gas yield (mL/g VSadded) at each of the ISR (0.5–3, R2–R6) and the quadratic polynomial regression result.
Table 3 also describes the VS removal rate under different experiment conditions. VS removal rate at thermophilic conditions were a little higher than that at mesophilic conditions at R4 and R6 respectively, and significantly higher (LSD0.05 = 3.3 and LSD0.01 = 5.8) at the other ISRs. It demonstrates high biodegradability of the substrate at higher temperature, due to higher organic hydrolysis rate or more suitable environment for microbes. In addition, net methane yield per gram of VS removed (mL/g VSremoved) was calculated based on VS removal rate to assess the biodegradability of the substrate. As Table 3 showed, both net biogas yield and net methane yield at mesophilic digestion were of no significant differences among R3, R4 and R5. For thermophilic digestion, both net biogas yield and net methane yield of R4 were significantly higher than under other ISRs. 3.3. Kinetic study results Table 4 summarizes the results of kinetic study using Exponential, Gompertz and Cone model respectively. The ultimate methane yield estimated by Exponential model was much higher than the specific methane yield under each ISR, indicating that the model is not suitable for describing the experimental data. However, it is found that the value of RMSE and the difference of specific methane yield and methane potential, were getting smaller when the ISR was raised, in both temperatures. It may be due to that the Exponential model does not take the lag phase of AD process into consideration. When the ISR increases, it can speed up the fermentation process more quickly. As a result, the lag phase shortens and experimental data tends to accord with Exponential model. The description of experimental data by Cone model was much better than Exponential model, with average difference of 16.727%, average RMSE of 7.722 and R2 above 0.980. The Gompertz model proved to be the best to fit the experimental data with the lowest value of average difference (Dif. 9.697%)
Table 3 Results of statistical analysis based on ANOVA. Parameters Specific biogas yield (mL/g VSadded) Net biogas yield (mL/g VSremoved) Specific methane yield (mL/g VSadded) Net methane yield (mL/g VSremoved) Average methane content (%) VS removal rate (%) a b
Mesophilic Thermophilic Mesophilic Thermophilic Mesophilic Thermophilic Mesophilic Thermophilic Mesophilic Thermophilic Mesophilic Thermophilic
R2
R3
R4
R5
R6
LSD0.05
LSD0.01
171.8 189.9 380.7 381.4 111.4 126.2 246.8 253.5 64.8 66.5 45.1 49.8
218.7 231.0 449.6 392.5 146.8 161.1 301.8 273.7 67.1 69.7 48.6 58.9
262.1 303.8 477.0 524.7 178.2 211.2 324.4 364.8 68.0 69.5 54.9 57.9
265.8 288.3 446.1 455.6 172.3 187.5 289.1 296.3 64.8 65.0 59.6 63.3
215.1 251.5 381.1 439.2 128.2 151.3 227.1 264.2 59.6 60.2 56.4 57.3
11.8a 18.7b 43.4a 68.6b 7.6a 12.1b 26.5a 41.9b 0.8a 1.4b 3.3a 5.2b
20.8a 32.8b 76.3a 120.7b 13.5a 21.3b 46.6a 73.7b 1.5a 2.4b 5.8a 9.2b
Means the LSD value for pairwise comparisons of studied parameters between mesophilic and thermophilic conditions under the same ISR. Means the LSD value for pairwise comparisons of studied parameters between different ISRs under the same temperature.
111
Gas yield (mL/g VSadded)
Measured methane yield (M4) Measured methane yield (M5)
200.0
Predicted methane yield (M4) Predicted methane yield (M5)
150.0 100.0
M4: R2=0.988 Dif(%)=6.9 M5: R2=0.988 Dif(%)=6.3
50.0 0.0 0
10
20 Time (day)
30
40
(A)
Gas yield (mL/g VSadded)
Where B is specific methane yield (mL/g VSadded), B0 is ultimate methane yield, i.e., methane potential (mL/g VSadded), k is methane production rate constant (day1), t is the digestion time (days), Rm is the maximum methane production rate (mL/g VSadded day), k is the lag phase (days), and n is shape factor (dimensionless). Dif. means the difference between the ultimate and specific methane yield, %. – means there is no result fitting with the model, i.e. the model does not fit the experimental data at all.
175.149 0.086 1.859 0.980 6.853 13.620 213.740 0.064 2.626 0.985 8.761 12.290 230.026 0.064 3.098 0.989 8.652 8.182 204.608 0.052 2.223 0.982 7.773 21.274 150.952 0.054 2.626 0.978 7.188 16.396 146.254 0.080 2.127 0.979 6.316 12.367 197.761 0.056 3.264 0.989 7.813 9.871 192.647 0.033 2.003 0.956 8.432 42.185 Cone
B0 k n R2 RMSE Dif. (%)
184.631 0.046 2.733 0.980 7.968 20.475
192.581 0.062 2.911 0.986 7.971 10.549
157.603 8.277 1.215 0.989 4.868 4.003 200.810 9.665 4.549 0.988 7.281 6.642 221.588 11.905 5.745 0.990 7.650 4.685 180.566 6.978 4.482 0.986 6.505 10.792 140.625 5.887 5.378 0.980 6.395 10.256 134.368 7.031 2.215 0.987 4.748 4.615 191.564 9.290 6.996 0.988 7.320 6.956 152.190 4.116 5.948 0.962 7.670 26.816 Gompertz
B0 Rm k (days) R2 RMSE Dif. (%)
172.554 6.308 6.928 0.981 7.307 14.909
183.851 9.106 5.459 0.988 7.003 6.302
151.294
181.025 0.057 0.969 8.783 16.424 348.076 0.023 0.951 15.619 46.141 426.456 0.020 0.943 19.634 50.474 – – – – – – – – – – 163.895 0.048 0.959 8.992 21.799 – – – – – – – – – – Exponential
B0 k R2 RMSE Dif. (%)
– – – – –
377.030 0.018 0.946 15.442 54.310
187.472
R5 R4
211.206 161.079
R3 R2
126.202 128.167 178.239 146.827 111.378 B
Thermophilic
R6 R5 R4 R3 R2
Mesophilic Parameters Model
Table 4 Estimated parameters, R2, RMSE and Dif. (%) of different kinetic models.
172.265
R6
H. Ma et al. / Bioresource Technology 151 (2014) 106–112
Measured methane yield (T4) Measured methane yield (T5)
250.0
Predicted methane yield (T4) Predicted methane yield (T5)
200.0 150.0 T4: R2=0.990 Dif(%)=4.6 T5: R2=0.988 Dif(%)=6.6
100.0 50.0 0.0 0
10
20 Time (day)
30
40
(B) Fig. 6. Plot of specific methane yield and ultimate methane yield with statistical indicators for ISRs of R4 and R5: (A) mesophilic, (B) thermophilic.
and RMSE (6.674). The lag phase for R2–R6 was 5.9, 6.9, 6.9, 5.4, 2.2 days respectively in mesophilic system and 5.3, 4.4, 5.7, 4.5, 1.2 days in thermophilic system. It is apparent that the lag phase was shorter in thermophilic than in mesophilic system, suggesting higher digestion speed and shorter digestion time at higher temperature. It should be mentioned that the fitness of different kinetic models can be very changeable, depending on the specific feedstock, inoculum and experimental conditions (El-Mashad, 2013; Pitt et al., 1999). It can also be seen from Table 4 that methane potential predicted at thermophilic temperature was higher than that predicted at mesophilic temperature, indicating that the substrate was more degradable under higher temperature. Besides, the result of R4 and R5 in both temperatures showed higher methane potential than other tests, with lower average difference. The measured biogas yield, measured methane yield, predicted biogas yield and predicted methane yield were plotted with time for R4 and R5 in both temperatures, shown in Fig. 6. The R2 value fell within the range of 0.988–0.990 and the average difference value (Dif.%) fell within the range of 4.6–6.9, also seen in Fig. 6. 4. Conclusion BMP test conducted in this study suggested a potential method to treat SmWRO through mesophilic or thermophilic anaerobic digestion and the significance for practical application. Thermophilic digestion showed higher specific gas yield and potential than mesophilic digestion, shorter lag phase as well. Strong correlation between ISR and gas yield was detected and ISR of 1.5 at 55 °C and ISR of 1.5 and 2 at 35 °C were suggested. Kinetic study showed that the Gompertz model can describe the experimental data properly. Acknowledgement The authors would like to express their thanks for the support from Fujian Kaijing Iron and Steel Development Co., Ltd., KCS Group.
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References APHA, AWWA, WPCF, 1989. Standard Methods for the Examination of Water and Wastewater, 17th ed., Washington, DC. CCAS, Chengdu Biological Research Institute of Chinese Academy of Sciences, 1985. Routine analysis of Anaerobic Digestion, first ed. Beijing Science and Technology Press, Beijing. Chynoweth, D.P., Turick, C.E., Owens, J.M., Jerger, D.E., Peck, M.W., 1993. Biochemical methane potential of biomass and waste feedstocks. Biomass Bioenergy 5, 95–111. El-Mashad, H.M., 2013. Kinetics of methane production from the codigestion of switchgrass and spirulina platensis algae. Bioresour. Technol. 132, 305–312. EPAC, Environmental Protection Administration of China, 2008. National Category of Hazardous Wastes, Beijing. Faisal, M., Unno, H., 2001. Kinetic analysis of palm oil mill wastewater treatment by a modified anaerobic baffled reactor. Biochem. Eng. J. 9, 25–31. Guo, X., Gu, J., Gao, H., Qin, Q., Chen, Z., Shao, L., Chen, L., Li, H., Zhang, W., Chen, S., Liu, J., 2012. Effects of Cu on metabolisms and enzyme activities of microbial communities in the process of composting. Bioresour. Technol. 108, 140–148. González-Fernández, C., García-Encina, P.A., 2009. Impact of substrate to inoculum ratio in anaerobic digestion of swine slurry. Biomass Bioenergy 22, 1065–1069. Jiang, Y., Zhao, P., Dong, T.Y., Dong, J.G., 2008. Determination methods for oil concentration in the oily sludge. Environ. Sci. Manage. 33, 115–117, In Chinese, with English abstract. Kafle, G.K., Kim, S.H., 2013. Anaerobic treatment of apple waste with swine manure for biogas production: batch and continuous operation. Appl. Energy 103, 61– 72. Kayhanian, M., Tchobanoglous, G., 1992. Computation of C/N ratios for various organic fractions. BioCycle 33, 58–60. Li, C.L., Champagne, P., Anderson, B.C., 2011. Evaluating and modeling biogas production from municipal fat, oil, and grease and synthetic kitchen waste in anaerobic co-digestion. Bioresour. Technol. 102, 9471–9480.
Li, J., Ding, Y.F., Xiao, Q., 2012. Research advances in effects of inoculum on biogas yields during anaerobic degradation. Environ. Sci. Manage. 37, 76–80, In Chinese, with English abstract. Little, T.M., Hills, F.J., 1978. Agricultural experimentation: design and analysis. John Wiley and Sons Inc., New York. Lopes, W.S., Leite, V.D., Prasad, S., 2004. Influence of inoculum on performance of anaerobic reactors for treating municipal solid waste. Bioresour. Technol. 94, 261–266. Neves, L., Oliveira, R., Alves, M.M., 2004. Influence of inoculum activity on the biomethanization of a kitchen waste under different waste/inoculum ratios. Process Biochem. 39, 2019–2024. Owen, W.F., Stuckey, D.C., Healy, J.B., Young, L.Y., McCarty, P.L., 1979. Bioassay for monitoring biochemical methane potential and anaerobic toxicity. Water Res. 13, 485–492. Pitt, R.E., Cross, T.L., Pell, A.N., Schofield, P., Doane, P.H., 1999. Use of in vitro gas production models in ruminal kinetics. Math. Biosci. 159, 145–163. Raposo, F., Fernández-Cegrí, V., De la Rubia, M.A., Borja, R.F., 2011. Biochemical methane potential (BMP) of solid organic substrates: evaluation of anaerobic biodegradability using data from an international interlaboratory study. J. Chem. Technol. Biotechnol. 86, 1088–1098. Raposo, F., Banks, C.J., Siegert, I., Heaven, S., Borja, R., 2006. Influence of inoculum to substrate ration on the biochemical methane of maize in batch tests. Process Biochem. 41, 1444–1450. Symons, G.E., Bushwell, A.M., 1933. The methane fermentation of carbohydrate. JACS 55, 2028–2039. Veeken, A., Hamelers, B., 1999. Effect of temperature on hydrolysis rates of selected biowaste components. Bioresour. Technol. 69, 249–254. Xie, S., Lawlor, P.G., Frost, J.P., Hu, Z., Zhan, X., 2011. Effect of pig manure to grass silage ratio on methane production in batch anaerobic co-digestion of concentrated pig manure and grass silage. Bioresour. Technol. 102, 5728–5733. Yang, J.S., 2007. Disposal and recycling of solid waste. THU Press, Beijing. Zwietering, M.H., Jongenburger, L., Rombouts, F.M., van’t Riet, K., 1990. Modeling the bacterial growth curve. Appl. Environ. Microbiol. 56, 1875–1881.
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Bioresource Technology journal homepage: www.elsevier.com/locate/biortech
Study on anaerobic treatment of hazardous steel-mill waste rolling oil (SmWRO) for multi-benefit disposal route Huanhuan Ma a, Zifu Li a,⇑, Fubin Yin a, William Kao b, Yi Yin a, Xiaofeng Bai a a b
School of Civil and Environment Engineering, University of Science and Technology Beijing, Beijing 100083, China Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
h i g h l i g h t s BMP test of steel-mill waste rolling oil (SmWRO) was conducted. Both temperature and ISR showed significant effect on methane yield. ISR of 1.5 and 2 at 35 °C and 1.5 at 55 °C were suggested with the highest biogas yield. Linear regression of substrate VS load against gas production could predict gas yield coefficient. Gompertz model best fitted the experimental data, while Exponential model not suitable.
a r t i c l e
i n f o
Article history: Received 25 July 2013 Received in revised form 11 October 2013 Accepted 15 October 2013 Available online 22 October 2013 Keywords: Steel-mill waste rolling oil (SmWRO) Anaerobic digestion Inoculum to substrate ratio (ISR) Temperature Gompertz model
a b s t r a c t Steel-mill waste rolling oil (SmWRO) is considered as hazardous substance with high treatment and disposal fees. Anaerobic process could not only transform the hazardous substance into activated sludge, but also generate valuable biogas. This study aimed at studying the biochemical methane potential of SmWRO under inoculum to substrate VS ratios (ISRs) of 0.25, 0.5, 1, 1.5, 2 and 3 using septic tank sludge as inoculum in mesophilic and thermophilic conditions, with blank tests for control. Specific biogas yield (mL/g VSadded), net biogas yield (mL/g VSremoved) and VS removal were analyzed. The ANOVA results indicated great influence of ISR and temperature on studied parameters. ISR of 1.5 at 55 °C and ISR of 1.5 and 2 at 35 °C were suggested with the highest specific biogas yield (262–265 and 303 mL/g VSadded). Kinetic analysis showed that Gompertz model fit the experimental data best with the least RMSE and largest R2. Ó 2013 Elsevier Ltd. All rights reserved.
1. Introduction A great amount of rolling oil is used as lubricant and oxidative protective coating during rolling, cutting, lapping, etc., in sheet metal processing and sheet steel manufacturing. Rolling oil hydrolyzes, oxidizes and accumulates particulate (dust and iron particles) during operation and needs to be replaced. Hence large amount of waste rolling oil is produced, here referred as steel-mill waste rolling oil (SmWRO). The characteristics of SmWRO vary greatly with the original composition of the oil and the process conditions from which it is derived. Due to its oleo chemical content and variety of chemical additives, it will cause serious environmental problem if untreated or improperly treated before disposal. Normally, it is treated as hazardous materials in China
⇑ Corresponding author. Tel./fax: +86 1062334378. E-mail address: [email protected] (Z. Li). 0960-8524/$ - see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.biortech.2013.10.051
(EPAC, 2008) and the disposal price is very high if treated by special companies. Anaerobic digestion (AD), as a traditional stabilization technology for disposing organic wastes, has received growing worldwide interest in recent years as a result of the increasing cost of fossil fuels and global warming (Xie et al., 2011). Through anaerobic treatment, SmWRO can be transformed into harmless activated sludge with biogas as by-product. In recent years, biochemical methane potential (BMP) tests have been commonly carried out to assess the biodegradability and methane production potential of different organic wastes from various sources (Raposo et al., 2011; González-Fernández and García-Encina, 2009). BMP tests are usually conducted in closed jars or bottles under appropriate temperature in batch mode. To accelerate the start-up rate of digestion, usually there is a need to add certain quantity of inoculum, which contains the microbes, especially methanogens that is necessary for biochemical conversion. The amount of inoculum is expressed as inoculum to substrate ratio (ISR), which often has complex impact on biogas production depending on the characteristics of organic wastes and inoculum (Li and Xiao, 2012; Lopes et al., 2004; Neves et al., 2004).
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AD process, especially the hydrolysis of organic matter is generally assumed to follow first-order kinetics. As a matter of fact, to reach full digestion, the entire degradation process includes three reaction phases: lag phase, exponential phase and steady phase (Li et al., 2011). The duration of the lag phase is also an important factor in determining the efficiency of AD and can be calculated with a modified Gompertz model, which fit the experimental data well (Kafle and Kim, 2013; Li et al., 2011; Xie et al., 2011). Whereas El-Mashad (2013) found that the Cone model best described methane production from the co-digestion of switchgrass and spirulina platensis algae, and the Gompertz model failed to predict the lag phase accurately under the studied conditions. According to Pitt et al. (1999), interpretation of gas production model parameters may be difficult in some cases, especially among comparison of different feedstocks. To the best of our knowledge, no previous studies have examined the AD of SmWRO; therefore, this study mainly aims at: (1) estimating the BMP and gas production rate of SmWRO under different ISRs in both mesophilic and thermophilic temperatures, (2) determining the ideal ISR in each temperature to achieve maximum methane production based on ANOVA, (3) studying the kinetics of SmWRO AD to serve better for future pilot test. 2. Methods 2.1. Analysis and calculation methods Total solid (TS) and Volatile solid (VS) were determined according to standard gravimetric methods 2540B and 2540E (APHA, 1989). It should be mentioned that for this special substrate, the measured TS content was actually a mixture of solid and oil (MSO). Total organic carbon (TOC) and total nitrogen (TN) were determined by a modified Kjedahl determination (CCAS, 1985). Oil content was tested using the reported petroleum ether extraction method (Jiang and Dong, 2008). pH was measured by a pHmeter (Mettle-Toledo Delta 320). Biogas production was read directly through the measuring cylinder and then adjusted to volume at standard temperature (0 °C) and pressure (1 atm) (STP).
V STP ¼
V T 273 ð760 PW Þ ð273 þ TÞ 760
ð1Þ
where, VSTP means the volume of gas calculated at standard temperature and pressure (mL), T is the temperature of the collected fermentation gas (°C), VT is the volume of gas measured at temperature T (mL) and PW means the saturated water vapor pressure at temperature T (mm Hg). Biogas production was read on daily basis. Biogas composition was analyzed every day during the first two weeks and then every two or three days by a portable gas analyzer (Geotech-Biogas check), which was calibrated using standard mixed gas prior to usage. Daily methane content was determined by linearly interpolating the measured methane contents (El-Mashad, 2013).
CX CN CM CX ¼ XN MX
ð2Þ
where, X means the day after day N and before day M after inoculation; CN and CM mean the measured methane contents at day N and M; CX means the calculated methane content at day X. 2.2. Characteristics and features of the substrate and inoculum The SmWRO sample used in this study was taken from a cold rolling steel-mill located at Xiamen city, southeast China. The original rolling oil before being mixed with lots of water in cold rolling process is water miscible, consisting of synthetic ester (30–
40%), refined fat (50–60%), refined mineral oil (1–10%) and other additives and agents. Prior to starting the experiment, the sample was preserved in a refrigerator that could provide a constant temperature of 4 °C for 4 days. This storage had no observable effect on the composition (Faisal and Unno, 2001). The TS and VS of the samples before and after storage were tested in triplicate, which showed little difference. Fresh sludge obtained from an ordinary septic-tank, which was treating domestic wastewater from residential area on the campus of our university, was used as inoculum. The inoculum was just taken out from the tank the day before inoculation to ensure high methanogenic activity and then was separately placed in a mesophilic and thermophilic water bath. Analysis of main features and compositions of the substrate and inoculum was conducted before the experiment (Table 1). The substrate contained about 53.6% of oil, counting for 80% of total organic matter. Total organic matter was computed by multiplying TOC by 1.724 (Guo et al., 2012). All measurements were performed in triplicate and the result was expressed as means with standard deviation.
2.3. Experimental set-up The experiment was carried out in a multi-batch reactor system that allowed better comparability and homogenization among different flasks (Fig. 1). Two such set-ups were applied simultaneously for mesophilic (35 ± 1 °C) and thermophilic (55 ± 1 °C) fermentation. Chynoweth et al. (1993) suggested an ISR (on VS basis) of 2 in AD, while Owen et al. (1979) proposed an ISR of about 1. For this study, batch anaerobic digestion of SmWRO with anaerobic sludge as inoculum were studied at six different ISRs (0.25, 0.5, 1, 1.5, 2 and 3), expressed as R1, R2, R3, R4, R5 and R6 respectively. Within the range of these ISRs, all the carbon-to-nitrogen ratios (C/N) of the mixture were between 19 and 25, which were within the optimal range for AD (Kayhanian and Tchobanoglous, 1992). This was achieved by keeping a constant inoculum addition (6 g VS) and varying the substrate amount from 24 to 2 g VS, as shown in Table 2. After adding the required amount of substrate and inoculum, all the 1 L fermentation flasks were filled with distilled water to achieve an effective working volume of 0.7 L. Then they were placed separately in mesophilic and thermophilic water bath, numbered as M1–M6 and T1–T6. The biogas generated was collected through a gas-guide tube inserted into the digester headspace to allow venting of the biogas into a graduated cylinder by water displacement. In addition, blank tests of inoculum under both temperatures were carried out as controls, i.e. number M0 and T0. There were no additional elements or buffer agents added to the fermentation flasks in the process, except for strict control of the temperature and sealed environment. The flasks were shaken manually for 30 s once a day in order to avoid local acidification and achieve better mixing of microorganisms and substrate. The VS content of fermentation residues was analyzed when gas production almost ceased. Table 1 Initial characteristics of the waste oil and inoculum sludge. Characteristics
Substrate
Inoculum
Total solids (wt.% as received) Volatile solids (wt.% dry basis) Total organic carbon (wt.% dry basis) Total nitrogen (wt.% dry basis) Oil (wt.% as received) Total organic matter (wt.% as received) pH
77.0 ± 0.9 80.9 ± 1.9 50.9 ± 1.1 1.95 ± 0.1 53.6 ± 1.2 67.6 ± 1.2 6.75 ± 0.25
8.7 ± 0.5 85.7 ± 1.1 55.1 ± 1.2 3.1 ± 0.2 – 8.2 ± 0.3 7.05 ± 7.25
Values are expressed as mean (standard deviation). TS of substrate means the mixture content of solid and oil (MSO).
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Fig. 1. Experimental set-up.
Table 2 Experimental parameters for the batch AD test of different ISRs. Number
R0 R1 R2 R3 R4 R5 R6
(M0, (M1, (M2, (M3, (M4, (M5, (M6,
Inoculum
T0) T1) T2) T3) T4) T5) T6)
Substrate
ISR (VS basis)
VS (g)
Concentration (g VS L1)
VS (g)
Concentration (g VS L1)
6.00 6.00 6.00 6.00 6.00 6.00 6.00
8.57 8.57 8.57 8.57 8.57 8.57 8.57
0.00 24.00 12.00 6.00 4.00 3.00 2.00
0.00 34.29 17.14 8.57 5.71 4.29 2.86
2.4. Statistical analysis The effect of temperature and ISR on specific gas yield, average methane content and VS removal was studied based on two-factor analysis of variance without repeated trials (ANOVA) in Excel software 2007. To conduct pairwise comparison and decide whether two or more measured parameters were significantly different or not, the Least Significant Difference (LSD) was calculated at a = 0.05 (LSD0.05) and at a = 0.01 (LSD0.01) as follows (Little and Hills, 1978):
rffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 2 MSE LSDa ¼ ta n
2.5.2. Model evaluation Three indicators were employed to compare the studied models. The correlation index (R2) and root mean square error (EMSE), derived from statistical analysis, were quantified to describe the accuracy of the models (Kafle and Kim, 2013). The difference (Dif.%) between specific methane yield (B) and ultimate methane yield (B0) was also calculated to provide more information on the regression results. All the kinetic analysis was based on Matlab software R2011. 3. Results and discussions
ð3Þ
where ta is the t value chosen for degree of freedom for error at significance level a, MSE means the mean square for error, n is the sample size for the studied parameter.
2.5. Study on anaerobic digestion kinetics 2.5.1. The equations of selected models Exponential (Veeken and Hamelers, 1999), Gompertz (Zwietering et al., 1990) and Cone (Pitt et al., 1999) model were selected to fit the experimental data and the equations are:
BðtÞ ¼ B0 ð1 expðktÞ Þ e Rm BðtÞ ¼ B0 exp exp ðk tÞ þ 1 B0 B0 BðtÞ ¼ n 1 þ ðktÞ
1/0 0.25 0.5 1.0 1.5 2.0 3.0
ð4Þ ð5Þ ð6Þ
where, B(t) is cumulative methane yield at day t (mL/g VSadded), B0 is ultimate methane yield, i.e., methane potential (mL/g VSadded), k is methane production rate constant (day1), t is the digestion time (days), e is exp (1) = 2.718282, Rm is the maximum methane production rate (mL/g VSadded day), k is the lag phase (days) and n is shape factor (dimensionless).
3.1. Gas production and yield The daily biogas production (after subtracting the corresponding biogas volume produced from the inoculum) at different ISRs in mesophilic and thermophilic conditions were respectively shown in Fig. 2A and B. It should be mentioned that the biogas production increased with the decrease of ISR due to higher substrate VS loading, except for R1. After 40 days of digestion, final biogas production of 1054, 2061, 1312, 1048, 797 and 430 mL were achieved for M1– M6, and the time needed to produce 90% of the final biogas production were 32, 28, 26, 25, 23 and 19 days; And for T1–T6, final biogas production were accordingly 1404, 2278, 1386, 1215, 864 and 503 mL, and the time needed to produce 90% of the final biogas production were 26, 25, 25, 23, 23 and 19 days. It can be seen that there were two biogas yield peaks for most of the tests. The first gas yield peak appeared at the second or third day after inoculation, while the time to reach the second gas yield peak was longer at lower ISRs in both mesophilic and thermophilic conditions, except for R1, which failed to reach high gas yield. The second biogas production peaks were 34, 142, 82, 68, 51 and 26 mL/day for M1–M6 at day 22, 24, 23, 20, 15 and 16 respectively; and second biogas production peaks were 61, 141, 78, 80, 57 and 29 mL/day for T1–T6 at day 16, 17, 21, 18, 15 and 15 respectively. So thermophilic fermentation showed no obvious effect on increasing the peak biogas yield, but surely reduced the time to reach it. The biogas production of R3–R6 almost ceased since day 33 in mesophilic digestion and day 29 in thermophilic digestion, as a result of shortage for soluble biodegradable organic matters.
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M1
M2
M3
M4
M5
M6
180 130 80 30 (20)
1
3
5
7
9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39
Cumulative biogas yield (mL/g VSadded)
Daily biogas production (mL)
230
350.0 300.0 250.0 200.0 150.0 100.0 50.0 0.0
M1
1
3
5
7
Time (day)
M2
M3
M4
M5
M6
9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 Time (day)
(A)
Daily biogas production (mL)
230
T1
T2
T3
T4
T5
T6
180 130 80 30
Cumulative biogas yield (mL/g VSadded)
(A)
350.0 300.0 250.0 200.0 150.0 100.0 50.0 0.0
T1
1 (20)
1
3
5
7
3
5
7
9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39
T2
T6
Cumulative methane yield (mL/g VSadded)
M1
M2
M3
M4
M5
M6
200.0 150.0 100.0 50.0 0.0 1
3
5
7
9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 Time (day)
(C) 250.0 Cumulative methane yield (mL/g VSadded)
Cumulative biogas and methane yield can be determined by dividing the cumulative biogas and methane production by the VS content initially added in each ISR, as plotted in Fig. 3. It was apparent that R1 under both temperatures failed to reach a cumulative biogas yield of above 100 mL/g VSadded. It might have been caused by the relative high substrate VS loading (34.29 g/L) and the microbes could not successfully adapt to the environment. Both cumulative biogas and methane were much higher for M4 and M5 than the other tests in mesophilic conditions. For thermophilic digestion, the cumulative gas yield decreased when ISR was raised to T5 and T6. The reason may be that more energy and organic materials were consumed by cellular growth and maintenance (anabolism) under such high ISR. The ANOVA test showed that there was no significant difference between R4 and R5 experiment (p > 0.05) under both temperatures. Conducting linear regression of substrate VS loading against final gas production under different ISRs, the slope of the line expresses the average gas yield coefficient (Ym, mL/g VSadded) in the range of stated VS loading (Raposo et al., 2006). The final biogas and methane production in both temperatures were plotted with the substrate VS load of 2, 3, 4 and 6 g (VS loading of 2.86, 4.29, 5.71 and 8.57 g/L), shown in Fig. 4. The result showed that the average biogas and methane yield coefficients at mesophilic conditions were 213.0 and 151.3 mL/g VSadded; and a little bit higher at thermophilic conditions as 216.4 and 163.9 mL/g VSadded. This suggests that the effect of increasing substrate VS load on increasing specific gas yield was more significant in thermophilic digestion than in mesophilic digestion. The average methane yield coefficient obtained by Raposo et al. (2006), when conducting mesophilic AD of maize with anaerobic sludge from WWTP as inoculum at ISRs of 3, 2, 1.5 and 1 (substrate VS loading of 5, 7.5, 10 and 15 g/L, respectively), was 211 mL/g VSadded, about 1.4 times that of this experiment. So the average gas yield coefficient may be different even under the same ISR, depending on the characteristics of the substrate and inoculum used. In this study, the relative lower substrate VS loading might reduce the microbial activity.
T5
(B) 250.0
T1
T2
T3
T4
T5
T6
200.0 150.0 100.0 50.0 0.0 1
3
5
7
9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 Time (day)
(D) Fig. 3. Variation of cumulative gas yield (mL/g VSadded) with time at different ISRs in both mesophilic and thermophilic conditions: (A) Cumulative biogas yield in mesophilic condition; (B) Cumulative biogas yield in thermophilic condition; (C) Cumulative methane yield in mesophilic condition; (D) Cumulative methane yield in thermophilic condition.
1600 Specific gas production (mL)
Fig. 2. Variation of daily biogas production (mL) with time at different ISRs in both mesophilic (A) and thermophilic conditions (B).
T4
9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 Time (day)
Time (day)
(B)
T3
Biogas-M
Biogas-T
Methane-M
Methane-T
y = 216.44x + 180.65 R² = 0.8902 (Biogas-T) y = 213.01x + 98.26 R² = 0.9381 (Biogas-M)
1400 1200
y = 163.94x + 54.316 R² = 0.8873 (Methane-T)
1000
y = 151.34x + 24.237 R² = 0.9259 (Methane-M)
800 600 400 200 0 1.00
2.00
3.00 4.00 5.00 Substrate VS load (gVS)
6.00
7.00
Fig. 4. Final gas production volume (mL) at each of the applied substrate VS load (2–6 g VS, R6–R3) and the linear regression result.
3.2. Pairwise comparisons of the parameters Final methane production at the end of digestion time were 251, 1336, 881, 713, 516, 256 mL (mesophilic) and 368, 1514,
966, 844, 562, 302 mL (thermophilic), calculated based on daily biogas production and daily methane content. Average methane content was determined by dividing final biogas production by
H. Ma et al. / Bioresource Technology 151 (2014) 106–112
final methane production. Thus specific biogas and methane yield can be worked out (Table 3). The fermentation of R1 was considered to have failed and thus not discussed in the following test, with specific methane yield of 10.5 mL/g VSadded (mesophilic, Fig. 3C) and 15.3 mL/g VSadded (thermophilic, Fig. 3D) much lower than the other tests. Judging from Table 3, both specific biogas yield and specific methane yield showed the trend of first increasing and then decreasing, as ISR changing from 0.5 to 3 (R2–R6), regardless of temperature. Therefore, the authors conducted a quadratic polynomial fitting and the result was shown in Fig. 5. In the range of ISRs stated, specific biogas yield at thermophilic conditions was higher than at mesophilic conditions, as well as specific methane yield. However, the correlation coefficients for specific biogas yield and specific methane yield were only 0.91 and 0.87 at thermophilic conditions. Whereas, the correlation coefficients were both 0.98 at mesophilic conditions, indicating that the binomial model describes the experimental results well for mesophilic digestion and can be used to estimate the specific gas yield under specific ISR. As shown in Fig. 5, it is possible to reach high specific gas yield at ISRs of 1.5–2 at mesophilic conditions. It can be seen in Table 3 that specific biogas yield between R4 and R5 in both temperatures showed little difference (3.7 and 15.5), but was significantly different among all the other ISRs (LSD0.05 = 18.7 and LSD0.01 = 32.8). Specific methane yield at mesophilic conditions showed similar rules, and only the difference between R4 and R5 was not significant (LSD0.05 = 12.1 and LSD0.01 = 21.3). However, very significant difference appeared for specific methane yield between any two ISRs at thermophilic conditions (with the highest specific methane yield of 211.2 mL/g VSadded at R4). This may be explained by the significant difference of average methane content at thermophilic conditions (LSD0.05 = 1.4 and LSD0.01 = 2.4). Although the difference of average methane content between R4 and R5 was also significant in mesophilic digestion, the difference of specific methane yield could be reduced by the very tiny difference of specific biogas yield between R4 and R5. Besides, temperature displayed very significant effect on specific methane yield (LSD0.05 = 7.6 and LSD0.01 = 13.5), as well as on specific biogas yield (LSD0.05 = 11.8 and LSD0.01 = 20.8). According to Yang (2007) and Bushwell equation (Symons and Bushwell, 1933), the methane content was related to the chemical components of the waste: the theoretical methane yield of fat was about 1.6–2.1 times of protein and 2.4–2.8 times of carbohydrate. Thus the high content of oil in this substrate might have contributed to the higher value of methane percentage (especially for R3, R4 and R5), compared to the methane content of about 52% from the blank assay. H2S volume content was always in the range of 10–1000 ppm for all tests. Thus biogas generated from SmWRO digestion has the potential to be a source of high quality bioenergy.
350.0 Specific gas yield (mL/g VSadded)
110
Biogas-M
Methane-M
Biogas-T
Methane-T
300.0 y = -69.893x2 + 283.28x + 23.921 R² = 0.9119 (Biogas-T) y = -46.31x2 + 180.45x + 90.804 R² = 0.9886 (Biogas-M)
250.0 200.0
y = -58.87x2 + 226.95x - 7.2067 R² = 0.8714 (Methane-T) y = -36.57x2 + 134.86x + 52.285 R² = 0.9808 (Methane-M)
150.0 100.0 50.0 0.0 0.00
0.50
1.00 1.50 2.00 2.50 Inoculum to substrate ratio (on VS basis)
3.00
3.50
Fig. 5. Specific gas yield (mL/g VSadded) at each of the ISR (0.5–3, R2–R6) and the quadratic polynomial regression result.
Table 3 also describes the VS removal rate under different experiment conditions. VS removal rate at thermophilic conditions were a little higher than that at mesophilic conditions at R4 and R6 respectively, and significantly higher (LSD0.05 = 3.3 and LSD0.01 = 5.8) at the other ISRs. It demonstrates high biodegradability of the substrate at higher temperature, due to higher organic hydrolysis rate or more suitable environment for microbes. In addition, net methane yield per gram of VS removed (mL/g VSremoved) was calculated based on VS removal rate to assess the biodegradability of the substrate. As Table 3 showed, both net biogas yield and net methane yield at mesophilic digestion were of no significant differences among R3, R4 and R5. For thermophilic digestion, both net biogas yield and net methane yield of R4 were significantly higher than under other ISRs. 3.3. Kinetic study results Table 4 summarizes the results of kinetic study using Exponential, Gompertz and Cone model respectively. The ultimate methane yield estimated by Exponential model was much higher than the specific methane yield under each ISR, indicating that the model is not suitable for describing the experimental data. However, it is found that the value of RMSE and the difference of specific methane yield and methane potential, were getting smaller when the ISR was raised, in both temperatures. It may be due to that the Exponential model does not take the lag phase of AD process into consideration. When the ISR increases, it can speed up the fermentation process more quickly. As a result, the lag phase shortens and experimental data tends to accord with Exponential model. The description of experimental data by Cone model was much better than Exponential model, with average difference of 16.727%, average RMSE of 7.722 and R2 above 0.980. The Gompertz model proved to be the best to fit the experimental data with the lowest value of average difference (Dif. 9.697%)
Table 3 Results of statistical analysis based on ANOVA. Parameters Specific biogas yield (mL/g VSadded) Net biogas yield (mL/g VSremoved) Specific methane yield (mL/g VSadded) Net methane yield (mL/g VSremoved) Average methane content (%) VS removal rate (%) a b
Mesophilic Thermophilic Mesophilic Thermophilic Mesophilic Thermophilic Mesophilic Thermophilic Mesophilic Thermophilic Mesophilic Thermophilic
R2
R3
R4
R5
R6
LSD0.05
LSD0.01
171.8 189.9 380.7 381.4 111.4 126.2 246.8 253.5 64.8 66.5 45.1 49.8
218.7 231.0 449.6 392.5 146.8 161.1 301.8 273.7 67.1 69.7 48.6 58.9
262.1 303.8 477.0 524.7 178.2 211.2 324.4 364.8 68.0 69.5 54.9 57.9
265.8 288.3 446.1 455.6 172.3 187.5 289.1 296.3 64.8 65.0 59.6 63.3
215.1 251.5 381.1 439.2 128.2 151.3 227.1 264.2 59.6 60.2 56.4 57.3
11.8a 18.7b 43.4a 68.6b 7.6a 12.1b 26.5a 41.9b 0.8a 1.4b 3.3a 5.2b
20.8a 32.8b 76.3a 120.7b 13.5a 21.3b 46.6a 73.7b 1.5a 2.4b 5.8a 9.2b
Means the LSD value for pairwise comparisons of studied parameters between mesophilic and thermophilic conditions under the same ISR. Means the LSD value for pairwise comparisons of studied parameters between different ISRs under the same temperature.
111
Gas yield (mL/g VSadded)
Measured methane yield (M4) Measured methane yield (M5)
200.0
Predicted methane yield (M4) Predicted methane yield (M5)
150.0 100.0
M4: R2=0.988 Dif(%)=6.9 M5: R2=0.988 Dif(%)=6.3
50.0 0.0 0
10
20 Time (day)
30
40
(A)
Gas yield (mL/g VSadded)
Where B is specific methane yield (mL/g VSadded), B0 is ultimate methane yield, i.e., methane potential (mL/g VSadded), k is methane production rate constant (day1), t is the digestion time (days), Rm is the maximum methane production rate (mL/g VSadded day), k is the lag phase (days), and n is shape factor (dimensionless). Dif. means the difference between the ultimate and specific methane yield, %. – means there is no result fitting with the model, i.e. the model does not fit the experimental data at all.
175.149 0.086 1.859 0.980 6.853 13.620 213.740 0.064 2.626 0.985 8.761 12.290 230.026 0.064 3.098 0.989 8.652 8.182 204.608 0.052 2.223 0.982 7.773 21.274 150.952 0.054 2.626 0.978 7.188 16.396 146.254 0.080 2.127 0.979 6.316 12.367 197.761 0.056 3.264 0.989 7.813 9.871 192.647 0.033 2.003 0.956 8.432 42.185 Cone
B0 k n R2 RMSE Dif. (%)
184.631 0.046 2.733 0.980 7.968 20.475
192.581 0.062 2.911 0.986 7.971 10.549
157.603 8.277 1.215 0.989 4.868 4.003 200.810 9.665 4.549 0.988 7.281 6.642 221.588 11.905 5.745 0.990 7.650 4.685 180.566 6.978 4.482 0.986 6.505 10.792 140.625 5.887 5.378 0.980 6.395 10.256 134.368 7.031 2.215 0.987 4.748 4.615 191.564 9.290 6.996 0.988 7.320 6.956 152.190 4.116 5.948 0.962 7.670 26.816 Gompertz
B0 Rm k (days) R2 RMSE Dif. (%)
172.554 6.308 6.928 0.981 7.307 14.909
183.851 9.106 5.459 0.988 7.003 6.302
151.294
181.025 0.057 0.969 8.783 16.424 348.076 0.023 0.951 15.619 46.141 426.456 0.020 0.943 19.634 50.474 – – – – – – – – – – 163.895 0.048 0.959 8.992 21.799 – – – – – – – – – – Exponential
B0 k R2 RMSE Dif. (%)
– – – – –
377.030 0.018 0.946 15.442 54.310
187.472
R5 R4
211.206 161.079
R3 R2
126.202 128.167 178.239 146.827 111.378 B
Thermophilic
R6 R5 R4 R3 R2
Mesophilic Parameters Model
Table 4 Estimated parameters, R2, RMSE and Dif. (%) of different kinetic models.
172.265
R6
H. Ma et al. / Bioresource Technology 151 (2014) 106–112
Measured methane yield (T4) Measured methane yield (T5)
250.0
Predicted methane yield (T4) Predicted methane yield (T5)
200.0 150.0 T4: R2=0.990 Dif(%)=4.6 T5: R2=0.988 Dif(%)=6.6
100.0 50.0 0.0 0
10
20 Time (day)
30
40
(B) Fig. 6. Plot of specific methane yield and ultimate methane yield with statistical indicators for ISRs of R4 and R5: (A) mesophilic, (B) thermophilic.
and RMSE (6.674). The lag phase for R2–R6 was 5.9, 6.9, 6.9, 5.4, 2.2 days respectively in mesophilic system and 5.3, 4.4, 5.7, 4.5, 1.2 days in thermophilic system. It is apparent that the lag phase was shorter in thermophilic than in mesophilic system, suggesting higher digestion speed and shorter digestion time at higher temperature. It should be mentioned that the fitness of different kinetic models can be very changeable, depending on the specific feedstock, inoculum and experimental conditions (El-Mashad, 2013; Pitt et al., 1999). It can also be seen from Table 4 that methane potential predicted at thermophilic temperature was higher than that predicted at mesophilic temperature, indicating that the substrate was more degradable under higher temperature. Besides, the result of R4 and R5 in both temperatures showed higher methane potential than other tests, with lower average difference. The measured biogas yield, measured methane yield, predicted biogas yield and predicted methane yield were plotted with time for R4 and R5 in both temperatures, shown in Fig. 6. The R2 value fell within the range of 0.988–0.990 and the average difference value (Dif.%) fell within the range of 4.6–6.9, also seen in Fig. 6. 4. Conclusion BMP test conducted in this study suggested a potential method to treat SmWRO through mesophilic or thermophilic anaerobic digestion and the significance for practical application. Thermophilic digestion showed higher specific gas yield and potential than mesophilic digestion, shorter lag phase as well. Strong correlation between ISR and gas yield was detected and ISR of 1.5 at 55 °C and ISR of 1.5 and 2 at 35 °C were suggested. Kinetic study showed that the Gompertz model can describe the experimental data properly. Acknowledgement The authors would like to express their thanks for the support from Fujian Kaijing Iron and Steel Development Co., Ltd., KCS Group.
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