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A novel test method for evaluating the methane gas permeability of biogas storage membrane
Renewable Energy 60 (2013) 572e577
Contents lists available at SciVerse ScienceDirect
Renewable Energy journal homepage: www.elsevier.com/locate/renene
A novel test method for evaluating the methane gas permeability of biogas storage membrane Zifu Li*, Fubin Yin, Haoyuan Li, Xiaoxi Wang, Jing Lian School of Civil and Environmental Engineering, University of Science and Technology Beijing, No. 30 Xueyuan Road, Haidian District, Beijing 100083, PR China
a r t i c l e i n f o
a b s t r a c t
Article history: Received 18 October 2012 Accepted 9 June 2013 Available online 2 July 2013
In China, although an increasing number of biogas storage have been created from different kinds of membranes in biogas plants, the issue of leakage assessment continues to be ignored. In this study, a novel test method for the evaluation and determination of the methane permeability of biogas storage membrane is developed and presented based on experiences from the food packing industry. Two test pressures in gradients of differential pressures were selected based on the permeability principle and characteristics of methane. The test method was developed to detect and quantify the methane permeability of the membrane in the biogas plant, and it was proven to be simple, accurate, stable, and highly sensitive through testing experiments. Using the developed test method, seven different kinds of membrane products, from local and international companies currently in the market were selected and tested. The test data were analyzed using the SPSS software to evaluate and measure the permeability of the different kinds of biogas membrane storage. The results show a high precision within a 95% confidence interval, and the different membranes exhibited significant differences in the daily volume of the methane permeability of the membranes, except two kinds of membranes. The permeability capacity of the seven tested membrane scan be evaluated according to the membrane permeability. Ó 2013 Elsevier Ltd. All rights reserved.
Keywords: Biogas storage membrane Novel test method Methane permeability
1. Introduction The rapid development of applications for polymer materials has led to the increasingly extensive use of polymer materials in daily life. Polymer materials utilize their gas tightness as one of the main performance indices for certain cases. For example, the performances of certain items, such as inflatable over water emergency equipment, inner tubes of tires, food packaging, and inflatable containers, among others, are closely related to air tightness [1]. Permeability is an important parameter for understanding membrane characteristics and for selecting a suitable membrane material for different applications [2]. As a novel material, membrane material has extensive applications not only in buildings and architecture but also in the storage process of biogas plants [3]. Biogas holders are an essential part of anaerobic digestion systemsthat provide a biogas storage buffer and a constant system pressure. However, ordinary biogas gasholders have issues that need to be resolved [4,5], such as the large
* Corresponding author. Tel./fax: þ86 010 6233 4378. E-mail addresses: [email protected], [email protected] (Z. Li). 0960-1481/$ e see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.renene.2013.06.010
dead weight and the instabilities in the output pressure of common fixed volume storage. The flexible system of membrane material is preferred to solve such problems [6,7]. Biogas storage membrane is used in special storage places that require gas tightness of a higher standard compared to ordinary architectural membrane, particularly methane gas tightness. In many practical projects, the double-layer membrane biogas storage and the anaerobic digester with storage-integrated process systems are the two primary kinds of biogas storage systems. The doublelayer membrane biogas storage system is often applied in traditional storage units, and it is an independent membrane system with 3/4 sphere-shaped or horizontal cylinder types (Fig. 1A). On the other hand, in the anaerobic digester with storage-integrated process system, the membrane storage portion is commonly coneshaped or hemisphere-shaped and it is laid on top of the digestion tank (Fig. 1B). Biogas is typically composed of a gas mixture that contains methane (50e70%, v/v), hydrogen sulfide (approximately 3000 ppm), and sometimes ammonia (in ppm range), with carbon dioxide acting as the balance [8]. No studies on product performance standards and testing method standards, particularly for biogas storage membranes, have
Z. Li et al. / Renewable Energy 60 (2013) 572e577
573
Table 1 Differential pressure and equal pressure comparison. Item
Differential pressure
Equal pressure
Test principle Test accuracy Representative test methods Instrument operability Selectivity of test gas
Gas permeability Similarity Vacuum method Easy No
Sensor method Complex Yes (O2/CO2)
Fig. 1. Biogas storage membrane in practical project.
been reported in both Chinese and foreign literature, although some well-known membrane material manufacturers, such as Germany’s Mehler and AgriKomp, use their own individual corporate standards. However, all the methods mentioned above require a suitable standard gas mixture for calibration during experiments, but calibration standard samples are difficult to obtain. Thus, more convenient and reliable techniques for the evaluation of gas permeation through biogas storage membranes are necessary. This study aims to develop a convenient and accurate measuring technique for the permeability measurement of membrane materials. Therefore, this study introduces a novel method for determining the methane permeability of biogas storage membrane. 1.1. Permeability test principle The permeability test refers to the specific detection of the gas permeability of materials with a certain gas barrier [9]. These applied materials are mostly polymers or multi-layer composite materials made from polymer that are widely used in food, medicine, chemicals, electronics, the military, and other areas of product packaging [10,11]. The barrier properties of packaging materials play a very important role in food and pharmaceutical packaging. Thus, Chinese authorities launched several test method standards for packing material permeability, including the “Plastics Film Determination of Gas Transmission” GB/T1038-1970, which was published in 1970, and the “Plastics Film and Sheeting Determination of Gas Transmission” GB/ T1038-2000, which was launched in 2000.Other related standards include the ASTM D1434, ISO 2556, ISO 15105-1, JIS K7126-A, and YBB 00082003. Permeating gas causes pressure change, volume change, or concentration change depending on the test. The membrane permeability test methods are classified into pressure, volume, and concentration methods. Other methods include the gas chromatography and thermal conductivity methods. Among these methods, the pressure method, which consists of differential pressure and equal pressure methods, is the most widely used [12]. Differential pressure method is vacuum method. In this method, permeation chamber is divided into two independent parts by membrane. Evacuate the two parts and then fill one side with test gas, while keep the other side vacuum state. Hence under the gradient of differential pressure the test gas permeates from the high-pressure side to the low-pressure side. By measuring the pressure in the low-pressure side we can get various barrier
parameters of the tested membrane[13].In the equal pressure method, the permeable chamber is divided into two independent airflow systems by membrane, with one side being the flowing testing gas (e.g. pure oxygen) and the other side being the flowing dry nitrogen gas. The pressure of the two sides is equal. Under the function of oxygen concentration difference, oxygen transmits through the membrane and is diverted into the sensor by nitrogen gas. Oxygen permeability can be calculated with the oxygen quantity in nitrogen gas with the measurement of a sensor[14]. With the support of the theory of membrane technology, the vacuum method as means of physical testing with a clear principle is used as a basic method and is mainly applied in scientific testing institutions. The sensor method has emerged with the continuous growth and improvement of the oxygen detectors technology. An advantage of the sensor method is that it can shorten its testing time relative to that of the vacuum test method, making it widely applicable in commercial detection [10]. The differential pressure and the equal pressure methods have different testing axioms and conditions, but as two basic methods in gas permeability test areas, they both have vital positions in barrier property and permeability tests [15]. The comparison of the differential pressure and equal pressure methods is shown in Table 1. The outstanding advantages of the equal pressure method were observed in the container oxygen permeability, but the equal pressure method is not as effective as the differential pressure method on the commonality of the testing gas[16]. The differential pressure method has many advantages in terms of detection because it has no selectivity in the test gas, it is low cost, and it has a high test success rate [17,18]. However, the gas purity in the test environment is the most significant advantage of the differential pressure method. Consequently, after considering the application, the environment aspect, the use of the biogas storage membrane, and the advantages of the differential pressure and equal pressure methods, the differential pressure method was found to be the more effective method for determining the methane permeability of the biogas storage membrane.
1.2. Permeability test pressure The permeability test pressure refers to the differential pressure on both sides of the sample. In generally, the differential pressure on both sides of biogas storage membrane is approximately a 4 m water column in the
Table 2 The methane permeability at the two typical test pressures. Sample
M1 M2 M3
Test pressure ¼ 0.1 MPa
Test pressure ¼ 0.04 MPa
Permeability (cm3/m3$day$0.1 MPa)
Relative errors
161.53 240.97 177.27
1.10% 0.92% 2.30%
163.19 238.91 165.38
165.28 248.71 170.33
0.09% 1.35% 1.72%
1.19% 2.27% 0.58%
Permeability (cm3/m3$day$0.04 MPa)
Relative errors
309.19 408.82 409.82
6.31% 0.00% 3.75%
343.26 389.68 425.41
337.56 427.92 415.37
4.02% 4.68% 0.75%
2.29% 4.68% 4.50%
574
Z. Li et al. / Renewable Energy 60 (2013) 572e577
methane permeability of the three parallel samples were observed, and the average relative error was not in the permitted scope. Thus, the test pressure was set to 0.1 MPa to avoid test errors caused by the obvious change in test data. 2. Materials and methods 2.1. Materials
Fig. 2. The general structure of membrane. Table 3 The characteristic parameters of membranes. Source (domestic/ imported)
Membrane
Support cloth
Type of coating
Weight (g/m2)
Temperature resistance
Imported
M1 M2 M3 M4 M5 M6 M7
PES PES PES PES PES PES PES
PVC PVC PVC PVC PVC PVC PVC
1500 1200 900 1000 800 1100 900
30 30 30 30 30 30 30
Domestic
C C C C C C C
to to to to to to to
70 70 70 70 70 70 70
C C C C C C C
biogas plant, and thus, the test pressure of the experiments was set at 4 m water column (0.04 MPa).On the other hand, according to other testing standards on gas permeability [13], the test pressure of the experiments was set to 10 m water column (0.1 MPa). Two test pressure values (0.04 MPa and 0.1 MPa) were selected for the experiment to investigate the test pressures that influence the methane permeability of the membranes. The membrane permeability can be calculated as follows [13,17], the results are shown in Table 2, and each sample was tested in triplicates.
Qg ¼
dp V T 24 0 dt S p0 T ðp1 p2 Þ
(1)
where Qg is the permeability (cm3/m2$d$0.1 MPa), V is the volume of the lower chamber (cm3), S is the surface area of the membrane exposed to the gas (cm2), p0 is the pressure under standard conditions (0.1 MPa), (p1 p2) is the pressure difference across the membrane (MPa), where p1 and p2 are the upstream and downstream pressures, respectively, T0 is the temperature under standard conditions (273.15 K), T is the absolute temperature (K), and dp/dt is the rate of the downstream pressure increase (MPa/h). As can be seen in Table 2, three kinds of membranes were tested under the same environment but with varying test pressure. At a test pressure of 0.1 MPa, no obvious changes in the methane permeability of the three parallel samples were observed, and the average relative error was in the permitted scope (relative errors < 5%). On other hand, at a test pressure of 0.04 MPa, remarkable changes in the
A membrane material is generally composed of several layers, including the surface layer, bottom coating, and the base fabric. The base fabric is chemically a polymer with required thickness and width, and it is produced via a specific process where composite materials are bonded together (Fig. 2). The brands of the membranes used for the experiments included German Mehler, German AgriKomp, German Heytex, and Shanghai Shenda-Kobond. The composition of a membrane plays a key role in the determination of its permeability properties [19]. The parameters of the membranes are given in Table 3, and numbers M1eM7 represent the seven kinds of membranes, respectively. The nitrogen (N2) and methane (CH4) used in this study were highly pure (99.99%). 2.2. Apparatus and membrane performance test Fig. 3 shows the experimental setup for the apparatus and membrane performance test. Two custom made steel chambers were used to calculate the gas permeability. The diffusion cell was divided into an upper chamber and a lower chamber by using a membrane. The upper chamber contained feed gas, and the lower one contained permeating gas. Two accurate microprocessor-controlled manometers were used to measure the pressure of the feed and permeate chambers during the permeability tests. The 38.48 cm3 is the permeating section area of the test chamber, i.e., the 38.48 cm3 of the membrane surface was in contact to the permeating gas. Prior to the measurements, a stream of pure nitrogen was purged through the test system to remove any possible residual gases from previous experiments. The entire system was isothermally maintained at test temperature, which was measured using a thermocouple (accuracy of 0.1 C) with direct contact to the chamber surface. After injecting the feed gas, at least about 21 h was allowed to pass to allow the system to reach thermal stability steady state conditions and pure test environment. The entire system was vacuumed about 10 h to below 27 kPa to meet the national standard definition. The feed gas was charged from a cylinder to the cell upstream side and then maintained at a constant pressure of 0.1 MPa. Gas permeability was calculated with respect to the rate of increase in pressure of the permeate chamber. Various
Fig. 3. The experimental setup for gas permeability test.
Z. Li et al. / Renewable Energy 60 (2013) 572e577 Table 4 Results of the experiment with test pressure of 0.1 MPa.
Table 6 ANOVA results.
Membrane
Permeability (cm3/m3$day$0.1 MPa)
Average value
Relative errors
M1 M2 M3 M4 M5 M6 M7
250.35 186.17 164.47 484.18 269.79 162.73 180.65
244.75 191.03 160.78 486.54 275.72 165.14 176.70
2.29% 2.54% 2.30% 0.49% 2.15% 1.46% 2.24%
240.27 195.65 157.02 489.30 280.35 164.41 176.65
243.63 191.27 160.83 486.13 276.02 168.29 172.79
575
1.83% 2.42% 2.34% 0.57% 1.68% 0.44% 0.03%
Sum of Squares 0.46% 0.13% 0.03% 0.08% 0.11% 1.91% 2.21%
permeability parameters of the tested membrane were obtained by monitoring and measuring the pressure in the lower chamber. For each experiment of this kind, the membrane permeability can be calculated using formula (1). 2.3. The method of data analysis In scientific research, test and experimental data are needed to analyze, in order to identify the influences on the test results under different test conditions. Is there a significant variation among the sample data? Which factors have greater effects? What is the best combination of factors that can lead to optimal results? And is there an interaction effect among the impact factors? Analysis of Variance of Statistical Package for Social Sciences (SPSS) is an effective statistical method to resolve the questions above. It is used for survey authoring and deployment, statistical analysis, text analytics, data mining, collaboration and deployment, that plays a tremendous role in the areas of social sciences and the natural science. In this research, the kind of different membranes is the single factor that has an influence on the result, so the significant variation among the test data was evaluated using One-way analysis of variance (ANOVA). A significance value (Sig.) < 0.05 was considered statistically significant. And the difference of the permeabilities among the membranes was analysis by Multi-way ANOVA. 3. Results and discussions Previous studies have indicated that Mehler and AgriKomp Company of Germany have their own corporate standards. Other studies also mentioned other testing standards that involve a test environment [10,16], where the gas permeability is 23 C and has 0% relative humidity. Thus, in this study, the permeability test of the known membrane was processed under the same conditions. The results are shown in Table 4, and every sample was tested in triplicates. The results of the experiment were analyzed using one-way ANOVA of the SPSS statistics software. In analysis of variance, One-way ANOVA is the simplest analysis method that in terms of the comparison among population means [20]. And only single factor is taken into consideration, while multiple factors and the interactions are considered in Multi-way ANOVA. If the hypothesis
Between (Combined) groups Linear term Within groups
df Mean square
F
Sig.
240,845.694 6 40,140.949 2319.015 0.000 2139.787 1 2139.787 123.619 0.000 Deviation 238,705.908 5 47,741.182 2758.094 0.000 242.333 14 17.309
is denied after test results that means there is a significant variance among the index value in different levels, and the factors have great effects on the results [21]. The null hypothesis that requires testing states that the permeabilities of all the membranes have no differences (as shown in Table 5). The descriptive results in Table 5 show the mean, standard deviation, standard error, and the minimum and maximum of the permeability. All the test results are within the scope of 95% confidence interval for the mean, and the relative errors were less than 2.6%, indicating that the method has good repeatability and high precision. ANOVA results are shown in Table 6,where the degree of freedom (df) was 14 within groups and 6 between groups, with significance (Sig.) ¼ 0 < 0.05. Thus, the null hypothesis is denied because the permeabilities of all membranes significantly varied. The results of multiple comparisons by Duncan are shown in Table 7. The results indicate that only membranes M3 and M6 were in the same subset, with a significance (Sig.) ¼ 0.219 > 0.05, indicating that the permeabilities of membranes M3 and M6 did not significantly vary. However, the permeabilities of the other membranes significantly varied. The daily volume of the methane permeability of all kinds of membranes can be calculated using formula (1) and the data in Table 8. The results analyzed using the univariate multi-way ANOVA of SPSS are shown in Table 9, where variables A and B represent the surface area of membrane and the daily volume of permeability, respectively. As can be seen in Table 9, factor B had F ¼ 22.268 and Sig. ¼ 0 < 0.05, illustrating that the daily volume of the permeabilities of different membranes significantly varied and had a large range. In practical use, thus, it is necessary to evaluate the permeability of each membrane in advance before making selection, due to the significant variation of the permeability. As can be seen in Table 10, after the post hoc tests of factor B, seven kinds of membranes were classified into three subsets. The differences in the permeabilities of the various membranes became less as the value of Sig. further exceeded 0.05. Subset 1 includes membranes M3, M6, M7, M2, and M1. The probability of mean comparison was Sig. ¼ 0.136 > 0.05, indicating that the mean of daily volumes of the permeabilities of the membranes did not have significant differences. Subset 2 includes membranes M2, M1 and M5, which shows similar results as subset 1.Subset 3 includes only membrane M4, which is classified into subset 3 separately because of the significant differences in the
Table 5 Descriptive results. Membrane
N
Mean
Std. deviation
Std. error
95% Confidence interval for mean Lower bound
Upper bound
M1 M2 M3 M4 M5 M6 M7
3 3 3 3 3 3 3
244.7500 191.0300 160.7733 486.5367 275.3867 165.1433 176.6967
5.13248 4.74455 3.72532 2.58411 5.30841 2.85162 3.93021
2.96324 2.73927 2.15082 1.49194 3.06481 1.64638 2.26911
232.0002 179.2439 151.5191 480.1174 262.1998 158.0595 166.9335
257.4998 202.8161 170.0275 492.9560 288.5735 172.2271 186.4598
Minimum
Maximum
240.27 186.17 157.02 484.18 269.79 162.73 172.79
250.35 195.65 164.47 489.30 280.35 168.29 180.65
576
Z. Li et al. / Renewable Energy 60 (2013) 572e577
Table 7 Subset of multiple comparisons. Membrane
Subset for alpha ¼ 0.05a
N
1 Duncan
M3 M6 M7 M2 M1 M5 M4 Sig.
3 3 3 3 3 3 3
2
3
4
5
6
160.7733 165.1433 176.6967 191.0300 244.7500 275.3867 0.219
1.000
1.000
1.000
486.5367 1.000
1.000
Means for groups in homogeneous subsets are displayed. a Uses harmonic mean sample size ¼ 6.000.
Table 8 The methane permeability of membrane biogas storage. Membrane permeability (m3/day$0.04 MPa)
Parameters of membrane biogas storage 3
V (m )
D (m)
Surface area (m2)
M1
M2
M3
M4
M5
M6
M7
100 500 1000 1500 2000 2500
6.7 11.0 12.9 14.8 16.4 17.6
140.95 379.94 522.53 687.79 844.53 972.65
0.862 2.325 3.197 4.208 5.167 5.951
0.675 1.821 2.504 3.296 4.047 4.661
0.567 1.527 2.100 2.764 3.394 3.909
1.714 4.621 6.356 8.366 10.272 11.831
0.961 2.590 3.563 4.689 5.758 6.632
0.582 1.569 2.157 2.840 3.487 4.016
0.625 1.685 2.317 3.050 3.745 4.313
Table 9 Tests of between-subjects effects. Dependent variable: daily volume of permeability Source
Type III sum of square
df
Mean square
F
Sig.a
Corrected model Intercept The surface area of membrane (A) The daily volume of permeability (B) Error Total Corrected total
226.279a 540.826 121.411
11 1 5
20.571 540.826 24.282
26.208 689.045 30.937
0.000 0.000 0.000
104.868
6
17.478
22.268
0.000
23.547 790.652 249.825
30 42 41
0.785
a
4. Conclusions
R2 ¼ 0.906 (adjusted R2 ¼ 0.871).
Table 10 Post hoc tests B. StudenteNewmaneKeulsa,b Membrane
N
M3 M6 M7 M2 M1 M5 M4 Sig.
6 6 6 6 6 6 6
Subset 1 2.3768 2.4418 2.6225 2.8340 3.6183
0.1360
2
3
2.8340 3.6183 4.0322 0.0650
Means for group in homogeneous subsets are displayed. Based on Type III sum of squares. The error term is the mean square (error) ¼ 0.785. a Uses harmonic mean sample size ¼ 6.000. b Alpha ¼ 0.05.
mean of daily volumes of the permeabilities between membrane M4 and the other membranes. This method provides an appropriate way to seek a solution to evaluate membranes in practical biogas storage, with this method, different kinds of membranes can be purposely classified into various grades via the results data of SPSS, in order to select the optimal membrane which has a better performance of tightness. The differences in the permeabilities of the various membranes could be because no uniform test method can objectively and accurately evaluate or measure the permeability of different membranes. Therefore, unifying the test methods of permeability in the membrane industry and devising a uniform industry standard are necessary.
7.1933 1.0000
(1) The proposed method was tested using several commonly used membranes, and good repeatability of test results and high precision within a 95% confidence interval were obtained. The methane leakage of the gas holder in the biogas project can be evaluated quantitatively using the proposed method. (2) The permeability test data were analyzed using SPSS. The results indicate that the permeabilities among the membranes had significant differences. Based on these differences, seven kinds of membranes were classified into three subsets. (3) The proposed method was found to be a valuable tool for detecting and quantifying the methane permeability of membrane biogas storage in a biogas plant. Moreover, the proposed method is simple, convenient, precise, and highly sensitive. Thus, the proposed method can play an active role in promoting the development of a uniform determination method for methane permeability in China and its corresponding industry standards, and it can also accelerate the development of biogas membranes. Acknowledgments Authors thank the support of China Key Projects in the National Science & Technology (gs1) Pillar Program (Project no. 2008BADC4B10)
Z. Li et al. / Renewable Energy 60 (2013) 572e577
and International cooperation project of Ministry of Science and Technology China (gs2) (Project no. 2013DFG92620). References [1] Wang BQ, Zhou WK, Zhu ZK. Research the permeability of the rubber and other film materials. Special Purpose Rubber Products 1986;1:22e7. [2] Liu XY, Pawliszyn J. Determination of membrane permeability without calibration using solid-phase microextraction (SPME). Journal of Membrane Science 2006;268:65e73. [3] Li ZF, Lian J, Yin FB, Liu X, Wang XX. Application and development of biogas storage membrane. China Biogas 2010;28:27e30. [4] Ofori-Boateng C, Kwofie EM. Water scrubbing: a better option for biogas purification for effective storage. World Applied Science Journal 2009;5: 122e5. [5] Zhang DT. An analysis of domestic biogas storage installations in China. Journal of Biomass 1989;20:61e7. [6] Zhang JL. Design analysis and test research on double layer membrane marsh gas stores system. Shang Hai: Shanghaijiao Tong University; 2010. [7] Kapdi SS, Vijay VK, Rajesh SK, Prasad R. Biogas scrubbing, compression and storage: perspective and prospectus in Indian context. Renewable Energy 2005;30:1195e202. [8] Makaruk A, Miltner M, Harasek M. Membrane biogas upgrading processes for the production of natural gas substitute. Separation and Purification Technology 2010;74:83e92.
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[9] Li Q, Cai L, Cai ChD. Design and construction of 3 MW centralized biogas plant combined with heat, power and fertilizer production. Renewable Energy Resources 2009;27:97e100. [10] Zhao J. Gas permeability test. Beverage & Fast Frozen Food Industry 2006;12: 32e3. [11] Houtman R. Material for membrane structures. Textile roofs. Berlin: Technical University; 2001. [12] Kang YF. Permeability test device research. Guang Dong. Guang Dong University of Technology; 2009. [13] GB/T 1083-2000. Plastics e film and sheeting e determination of gas transmission e differential-pressure method. [14] GB/T 19789-2005. Packaging material e test method for oxygen gas permeability characteristics of plastic film and sheeting e coulometric sensor. [15] Zhao J. Determine the oxygen permeability of packing material. China Packaging Industry 2005;11:70e1. [16] Hernandez RJ, Sekle SEM, Culter JD. Plastics packaging. Munich HANSER Publishers; 2000. [17] Su Y, Zhang M, Zhao J, Yao P. Effect of pressure difference on permeability test for plastic film. In: 23rd IAPRI symposium on packaging. Windsor: PIRA International; 2007. p. 41. [18] Pusch W, Mossa G. Influence of pressure and/or pressure differential on membrane permeability. Desalination 1997;24:39e53. [19] Felder RM, Huvard GS. In: Fava RA, editor. Methods of experimental physics. Part C, vol. 16. New York: Academic Press; 1980. [20] Howell DC. Statistical methods for psychology. Wadsworth Publishing; 2012. [21] Fisher RA. Statistical methods for research workers. Edinburgh, United Kingdom: Oliver & Boyd; 1925.
Contents lists available at SciVerse ScienceDirect
Renewable Energy journal homepage: www.elsevier.com/locate/renene
A novel test method for evaluating the methane gas permeability of biogas storage membrane Zifu Li*, Fubin Yin, Haoyuan Li, Xiaoxi Wang, Jing Lian School of Civil and Environmental Engineering, University of Science and Technology Beijing, No. 30 Xueyuan Road, Haidian District, Beijing 100083, PR China
a r t i c l e i n f o
a b s t r a c t
Article history: Received 18 October 2012 Accepted 9 June 2013 Available online 2 July 2013
In China, although an increasing number of biogas storage have been created from different kinds of membranes in biogas plants, the issue of leakage assessment continues to be ignored. In this study, a novel test method for the evaluation and determination of the methane permeability of biogas storage membrane is developed and presented based on experiences from the food packing industry. Two test pressures in gradients of differential pressures were selected based on the permeability principle and characteristics of methane. The test method was developed to detect and quantify the methane permeability of the membrane in the biogas plant, and it was proven to be simple, accurate, stable, and highly sensitive through testing experiments. Using the developed test method, seven different kinds of membrane products, from local and international companies currently in the market were selected and tested. The test data were analyzed using the SPSS software to evaluate and measure the permeability of the different kinds of biogas membrane storage. The results show a high precision within a 95% confidence interval, and the different membranes exhibited significant differences in the daily volume of the methane permeability of the membranes, except two kinds of membranes. The permeability capacity of the seven tested membrane scan be evaluated according to the membrane permeability. Ó 2013 Elsevier Ltd. All rights reserved.
Keywords: Biogas storage membrane Novel test method Methane permeability
1. Introduction The rapid development of applications for polymer materials has led to the increasingly extensive use of polymer materials in daily life. Polymer materials utilize their gas tightness as one of the main performance indices for certain cases. For example, the performances of certain items, such as inflatable over water emergency equipment, inner tubes of tires, food packaging, and inflatable containers, among others, are closely related to air tightness [1]. Permeability is an important parameter for understanding membrane characteristics and for selecting a suitable membrane material for different applications [2]. As a novel material, membrane material has extensive applications not only in buildings and architecture but also in the storage process of biogas plants [3]. Biogas holders are an essential part of anaerobic digestion systemsthat provide a biogas storage buffer and a constant system pressure. However, ordinary biogas gasholders have issues that need to be resolved [4,5], such as the large
* Corresponding author. Tel./fax: þ86 010 6233 4378. E-mail addresses: [email protected], [email protected] (Z. Li). 0960-1481/$ e see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.renene.2013.06.010
dead weight and the instabilities in the output pressure of common fixed volume storage. The flexible system of membrane material is preferred to solve such problems [6,7]. Biogas storage membrane is used in special storage places that require gas tightness of a higher standard compared to ordinary architectural membrane, particularly methane gas tightness. In many practical projects, the double-layer membrane biogas storage and the anaerobic digester with storage-integrated process systems are the two primary kinds of biogas storage systems. The doublelayer membrane biogas storage system is often applied in traditional storage units, and it is an independent membrane system with 3/4 sphere-shaped or horizontal cylinder types (Fig. 1A). On the other hand, in the anaerobic digester with storage-integrated process system, the membrane storage portion is commonly coneshaped or hemisphere-shaped and it is laid on top of the digestion tank (Fig. 1B). Biogas is typically composed of a gas mixture that contains methane (50e70%, v/v), hydrogen sulfide (approximately 3000 ppm), and sometimes ammonia (in ppm range), with carbon dioxide acting as the balance [8]. No studies on product performance standards and testing method standards, particularly for biogas storage membranes, have
Z. Li et al. / Renewable Energy 60 (2013) 572e577
573
Table 1 Differential pressure and equal pressure comparison. Item
Differential pressure
Equal pressure
Test principle Test accuracy Representative test methods Instrument operability Selectivity of test gas
Gas permeability Similarity Vacuum method Easy No
Sensor method Complex Yes (O2/CO2)
Fig. 1. Biogas storage membrane in practical project.
been reported in both Chinese and foreign literature, although some well-known membrane material manufacturers, such as Germany’s Mehler and AgriKomp, use their own individual corporate standards. However, all the methods mentioned above require a suitable standard gas mixture for calibration during experiments, but calibration standard samples are difficult to obtain. Thus, more convenient and reliable techniques for the evaluation of gas permeation through biogas storage membranes are necessary. This study aims to develop a convenient and accurate measuring technique for the permeability measurement of membrane materials. Therefore, this study introduces a novel method for determining the methane permeability of biogas storage membrane. 1.1. Permeability test principle The permeability test refers to the specific detection of the gas permeability of materials with a certain gas barrier [9]. These applied materials are mostly polymers or multi-layer composite materials made from polymer that are widely used in food, medicine, chemicals, electronics, the military, and other areas of product packaging [10,11]. The barrier properties of packaging materials play a very important role in food and pharmaceutical packaging. Thus, Chinese authorities launched several test method standards for packing material permeability, including the “Plastics Film Determination of Gas Transmission” GB/T1038-1970, which was published in 1970, and the “Plastics Film and Sheeting Determination of Gas Transmission” GB/ T1038-2000, which was launched in 2000.Other related standards include the ASTM D1434, ISO 2556, ISO 15105-1, JIS K7126-A, and YBB 00082003. Permeating gas causes pressure change, volume change, or concentration change depending on the test. The membrane permeability test methods are classified into pressure, volume, and concentration methods. Other methods include the gas chromatography and thermal conductivity methods. Among these methods, the pressure method, which consists of differential pressure and equal pressure methods, is the most widely used [12]. Differential pressure method is vacuum method. In this method, permeation chamber is divided into two independent parts by membrane. Evacuate the two parts and then fill one side with test gas, while keep the other side vacuum state. Hence under the gradient of differential pressure the test gas permeates from the high-pressure side to the low-pressure side. By measuring the pressure in the low-pressure side we can get various barrier
parameters of the tested membrane[13].In the equal pressure method, the permeable chamber is divided into two independent airflow systems by membrane, with one side being the flowing testing gas (e.g. pure oxygen) and the other side being the flowing dry nitrogen gas. The pressure of the two sides is equal. Under the function of oxygen concentration difference, oxygen transmits through the membrane and is diverted into the sensor by nitrogen gas. Oxygen permeability can be calculated with the oxygen quantity in nitrogen gas with the measurement of a sensor[14]. With the support of the theory of membrane technology, the vacuum method as means of physical testing with a clear principle is used as a basic method and is mainly applied in scientific testing institutions. The sensor method has emerged with the continuous growth and improvement of the oxygen detectors technology. An advantage of the sensor method is that it can shorten its testing time relative to that of the vacuum test method, making it widely applicable in commercial detection [10]. The differential pressure and the equal pressure methods have different testing axioms and conditions, but as two basic methods in gas permeability test areas, they both have vital positions in barrier property and permeability tests [15]. The comparison of the differential pressure and equal pressure methods is shown in Table 1. The outstanding advantages of the equal pressure method were observed in the container oxygen permeability, but the equal pressure method is not as effective as the differential pressure method on the commonality of the testing gas[16]. The differential pressure method has many advantages in terms of detection because it has no selectivity in the test gas, it is low cost, and it has a high test success rate [17,18]. However, the gas purity in the test environment is the most significant advantage of the differential pressure method. Consequently, after considering the application, the environment aspect, the use of the biogas storage membrane, and the advantages of the differential pressure and equal pressure methods, the differential pressure method was found to be the more effective method for determining the methane permeability of the biogas storage membrane.
1.2. Permeability test pressure The permeability test pressure refers to the differential pressure on both sides of the sample. In generally, the differential pressure on both sides of biogas storage membrane is approximately a 4 m water column in the
Table 2 The methane permeability at the two typical test pressures. Sample
M1 M2 M3
Test pressure ¼ 0.1 MPa
Test pressure ¼ 0.04 MPa
Permeability (cm3/m3$day$0.1 MPa)
Relative errors
161.53 240.97 177.27
1.10% 0.92% 2.30%
163.19 238.91 165.38
165.28 248.71 170.33
0.09% 1.35% 1.72%
1.19% 2.27% 0.58%
Permeability (cm3/m3$day$0.04 MPa)
Relative errors
309.19 408.82 409.82
6.31% 0.00% 3.75%
343.26 389.68 425.41
337.56 427.92 415.37
4.02% 4.68% 0.75%
2.29% 4.68% 4.50%
574
Z. Li et al. / Renewable Energy 60 (2013) 572e577
methane permeability of the three parallel samples were observed, and the average relative error was not in the permitted scope. Thus, the test pressure was set to 0.1 MPa to avoid test errors caused by the obvious change in test data. 2. Materials and methods 2.1. Materials
Fig. 2. The general structure of membrane. Table 3 The characteristic parameters of membranes. Source (domestic/ imported)
Membrane
Support cloth
Type of coating
Weight (g/m2)
Temperature resistance
Imported
M1 M2 M3 M4 M5 M6 M7
PES PES PES PES PES PES PES
PVC PVC PVC PVC PVC PVC PVC
1500 1200 900 1000 800 1100 900
30 30 30 30 30 30 30
Domestic
C C C C C C C
to to to to to to to
70 70 70 70 70 70 70
C C C C C C C
biogas plant, and thus, the test pressure of the experiments was set at 4 m water column (0.04 MPa).On the other hand, according to other testing standards on gas permeability [13], the test pressure of the experiments was set to 10 m water column (0.1 MPa). Two test pressure values (0.04 MPa and 0.1 MPa) were selected for the experiment to investigate the test pressures that influence the methane permeability of the membranes. The membrane permeability can be calculated as follows [13,17], the results are shown in Table 2, and each sample was tested in triplicates.
Qg ¼
dp V T 24 0 dt S p0 T ðp1 p2 Þ
(1)
where Qg is the permeability (cm3/m2$d$0.1 MPa), V is the volume of the lower chamber (cm3), S is the surface area of the membrane exposed to the gas (cm2), p0 is the pressure under standard conditions (0.1 MPa), (p1 p2) is the pressure difference across the membrane (MPa), where p1 and p2 are the upstream and downstream pressures, respectively, T0 is the temperature under standard conditions (273.15 K), T is the absolute temperature (K), and dp/dt is the rate of the downstream pressure increase (MPa/h). As can be seen in Table 2, three kinds of membranes were tested under the same environment but with varying test pressure. At a test pressure of 0.1 MPa, no obvious changes in the methane permeability of the three parallel samples were observed, and the average relative error was in the permitted scope (relative errors < 5%). On other hand, at a test pressure of 0.04 MPa, remarkable changes in the
A membrane material is generally composed of several layers, including the surface layer, bottom coating, and the base fabric. The base fabric is chemically a polymer with required thickness and width, and it is produced via a specific process where composite materials are bonded together (Fig. 2). The brands of the membranes used for the experiments included German Mehler, German AgriKomp, German Heytex, and Shanghai Shenda-Kobond. The composition of a membrane plays a key role in the determination of its permeability properties [19]. The parameters of the membranes are given in Table 3, and numbers M1eM7 represent the seven kinds of membranes, respectively. The nitrogen (N2) and methane (CH4) used in this study were highly pure (99.99%). 2.2. Apparatus and membrane performance test Fig. 3 shows the experimental setup for the apparatus and membrane performance test. Two custom made steel chambers were used to calculate the gas permeability. The diffusion cell was divided into an upper chamber and a lower chamber by using a membrane. The upper chamber contained feed gas, and the lower one contained permeating gas. Two accurate microprocessor-controlled manometers were used to measure the pressure of the feed and permeate chambers during the permeability tests. The 38.48 cm3 is the permeating section area of the test chamber, i.e., the 38.48 cm3 of the membrane surface was in contact to the permeating gas. Prior to the measurements, a stream of pure nitrogen was purged through the test system to remove any possible residual gases from previous experiments. The entire system was isothermally maintained at test temperature, which was measured using a thermocouple (accuracy of 0.1 C) with direct contact to the chamber surface. After injecting the feed gas, at least about 21 h was allowed to pass to allow the system to reach thermal stability steady state conditions and pure test environment. The entire system was vacuumed about 10 h to below 27 kPa to meet the national standard definition. The feed gas was charged from a cylinder to the cell upstream side and then maintained at a constant pressure of 0.1 MPa. Gas permeability was calculated with respect to the rate of increase in pressure of the permeate chamber. Various
Fig. 3. The experimental setup for gas permeability test.
Z. Li et al. / Renewable Energy 60 (2013) 572e577 Table 4 Results of the experiment with test pressure of 0.1 MPa.
Table 6 ANOVA results.
Membrane
Permeability (cm3/m3$day$0.1 MPa)
Average value
Relative errors
M1 M2 M3 M4 M5 M6 M7
250.35 186.17 164.47 484.18 269.79 162.73 180.65
244.75 191.03 160.78 486.54 275.72 165.14 176.70
2.29% 2.54% 2.30% 0.49% 2.15% 1.46% 2.24%
240.27 195.65 157.02 489.30 280.35 164.41 176.65
243.63 191.27 160.83 486.13 276.02 168.29 172.79
575
1.83% 2.42% 2.34% 0.57% 1.68% 0.44% 0.03%
Sum of Squares 0.46% 0.13% 0.03% 0.08% 0.11% 1.91% 2.21%
permeability parameters of the tested membrane were obtained by monitoring and measuring the pressure in the lower chamber. For each experiment of this kind, the membrane permeability can be calculated using formula (1). 2.3. The method of data analysis In scientific research, test and experimental data are needed to analyze, in order to identify the influences on the test results under different test conditions. Is there a significant variation among the sample data? Which factors have greater effects? What is the best combination of factors that can lead to optimal results? And is there an interaction effect among the impact factors? Analysis of Variance of Statistical Package for Social Sciences (SPSS) is an effective statistical method to resolve the questions above. It is used for survey authoring and deployment, statistical analysis, text analytics, data mining, collaboration and deployment, that plays a tremendous role in the areas of social sciences and the natural science. In this research, the kind of different membranes is the single factor that has an influence on the result, so the significant variation among the test data was evaluated using One-way analysis of variance (ANOVA). A significance value (Sig.) < 0.05 was considered statistically significant. And the difference of the permeabilities among the membranes was analysis by Multi-way ANOVA. 3. Results and discussions Previous studies have indicated that Mehler and AgriKomp Company of Germany have their own corporate standards. Other studies also mentioned other testing standards that involve a test environment [10,16], where the gas permeability is 23 C and has 0% relative humidity. Thus, in this study, the permeability test of the known membrane was processed under the same conditions. The results are shown in Table 4, and every sample was tested in triplicates. The results of the experiment were analyzed using one-way ANOVA of the SPSS statistics software. In analysis of variance, One-way ANOVA is the simplest analysis method that in terms of the comparison among population means [20]. And only single factor is taken into consideration, while multiple factors and the interactions are considered in Multi-way ANOVA. If the hypothesis
Between (Combined) groups Linear term Within groups
df Mean square
F
Sig.
240,845.694 6 40,140.949 2319.015 0.000 2139.787 1 2139.787 123.619 0.000 Deviation 238,705.908 5 47,741.182 2758.094 0.000 242.333 14 17.309
is denied after test results that means there is a significant variance among the index value in different levels, and the factors have great effects on the results [21]. The null hypothesis that requires testing states that the permeabilities of all the membranes have no differences (as shown in Table 5). The descriptive results in Table 5 show the mean, standard deviation, standard error, and the minimum and maximum of the permeability. All the test results are within the scope of 95% confidence interval for the mean, and the relative errors were less than 2.6%, indicating that the method has good repeatability and high precision. ANOVA results are shown in Table 6,where the degree of freedom (df) was 14 within groups and 6 between groups, with significance (Sig.) ¼ 0 < 0.05. Thus, the null hypothesis is denied because the permeabilities of all membranes significantly varied. The results of multiple comparisons by Duncan are shown in Table 7. The results indicate that only membranes M3 and M6 were in the same subset, with a significance (Sig.) ¼ 0.219 > 0.05, indicating that the permeabilities of membranes M3 and M6 did not significantly vary. However, the permeabilities of the other membranes significantly varied. The daily volume of the methane permeability of all kinds of membranes can be calculated using formula (1) and the data in Table 8. The results analyzed using the univariate multi-way ANOVA of SPSS are shown in Table 9, where variables A and B represent the surface area of membrane and the daily volume of permeability, respectively. As can be seen in Table 9, factor B had F ¼ 22.268 and Sig. ¼ 0 < 0.05, illustrating that the daily volume of the permeabilities of different membranes significantly varied and had a large range. In practical use, thus, it is necessary to evaluate the permeability of each membrane in advance before making selection, due to the significant variation of the permeability. As can be seen in Table 10, after the post hoc tests of factor B, seven kinds of membranes were classified into three subsets. The differences in the permeabilities of the various membranes became less as the value of Sig. further exceeded 0.05. Subset 1 includes membranes M3, M6, M7, M2, and M1. The probability of mean comparison was Sig. ¼ 0.136 > 0.05, indicating that the mean of daily volumes of the permeabilities of the membranes did not have significant differences. Subset 2 includes membranes M2, M1 and M5, which shows similar results as subset 1.Subset 3 includes only membrane M4, which is classified into subset 3 separately because of the significant differences in the
Table 5 Descriptive results. Membrane
N
Mean
Std. deviation
Std. error
95% Confidence interval for mean Lower bound
Upper bound
M1 M2 M3 M4 M5 M6 M7
3 3 3 3 3 3 3
244.7500 191.0300 160.7733 486.5367 275.3867 165.1433 176.6967
5.13248 4.74455 3.72532 2.58411 5.30841 2.85162 3.93021
2.96324 2.73927 2.15082 1.49194 3.06481 1.64638 2.26911
232.0002 179.2439 151.5191 480.1174 262.1998 158.0595 166.9335
257.4998 202.8161 170.0275 492.9560 288.5735 172.2271 186.4598
Minimum
Maximum
240.27 186.17 157.02 484.18 269.79 162.73 172.79
250.35 195.65 164.47 489.30 280.35 168.29 180.65
576
Z. Li et al. / Renewable Energy 60 (2013) 572e577
Table 7 Subset of multiple comparisons. Membrane
Subset for alpha ¼ 0.05a
N
1 Duncan
M3 M6 M7 M2 M1 M5 M4 Sig.
3 3 3 3 3 3 3
2
3
4
5
6
160.7733 165.1433 176.6967 191.0300 244.7500 275.3867 0.219
1.000
1.000
1.000
486.5367 1.000
1.000
Means for groups in homogeneous subsets are displayed. a Uses harmonic mean sample size ¼ 6.000.
Table 8 The methane permeability of membrane biogas storage. Membrane permeability (m3/day$0.04 MPa)
Parameters of membrane biogas storage 3
V (m )
D (m)
Surface area (m2)
M1
M2
M3
M4
M5
M6
M7
100 500 1000 1500 2000 2500
6.7 11.0 12.9 14.8 16.4 17.6
140.95 379.94 522.53 687.79 844.53 972.65
0.862 2.325 3.197 4.208 5.167 5.951
0.675 1.821 2.504 3.296 4.047 4.661
0.567 1.527 2.100 2.764 3.394 3.909
1.714 4.621 6.356 8.366 10.272 11.831
0.961 2.590 3.563 4.689 5.758 6.632
0.582 1.569 2.157 2.840 3.487 4.016
0.625 1.685 2.317 3.050 3.745 4.313
Table 9 Tests of between-subjects effects. Dependent variable: daily volume of permeability Source
Type III sum of square
df
Mean square
F
Sig.a
Corrected model Intercept The surface area of membrane (A) The daily volume of permeability (B) Error Total Corrected total
226.279a 540.826 121.411
11 1 5
20.571 540.826 24.282
26.208 689.045 30.937
0.000 0.000 0.000
104.868
6
17.478
22.268
0.000
23.547 790.652 249.825
30 42 41
0.785
a
4. Conclusions
R2 ¼ 0.906 (adjusted R2 ¼ 0.871).
Table 10 Post hoc tests B. StudenteNewmaneKeulsa,b Membrane
N
M3 M6 M7 M2 M1 M5 M4 Sig.
6 6 6 6 6 6 6
Subset 1 2.3768 2.4418 2.6225 2.8340 3.6183
0.1360
2
3
2.8340 3.6183 4.0322 0.0650
Means for group in homogeneous subsets are displayed. Based on Type III sum of squares. The error term is the mean square (error) ¼ 0.785. a Uses harmonic mean sample size ¼ 6.000. b Alpha ¼ 0.05.
mean of daily volumes of the permeabilities between membrane M4 and the other membranes. This method provides an appropriate way to seek a solution to evaluate membranes in practical biogas storage, with this method, different kinds of membranes can be purposely classified into various grades via the results data of SPSS, in order to select the optimal membrane which has a better performance of tightness. The differences in the permeabilities of the various membranes could be because no uniform test method can objectively and accurately evaluate or measure the permeability of different membranes. Therefore, unifying the test methods of permeability in the membrane industry and devising a uniform industry standard are necessary.
7.1933 1.0000
(1) The proposed method was tested using several commonly used membranes, and good repeatability of test results and high precision within a 95% confidence interval were obtained. The methane leakage of the gas holder in the biogas project can be evaluated quantitatively using the proposed method. (2) The permeability test data were analyzed using SPSS. The results indicate that the permeabilities among the membranes had significant differences. Based on these differences, seven kinds of membranes were classified into three subsets. (3) The proposed method was found to be a valuable tool for detecting and quantifying the methane permeability of membrane biogas storage in a biogas plant. Moreover, the proposed method is simple, convenient, precise, and highly sensitive. Thus, the proposed method can play an active role in promoting the development of a uniform determination method for methane permeability in China and its corresponding industry standards, and it can also accelerate the development of biogas membranes. Acknowledgments Authors thank the support of China Key Projects in the National Science & Technology (gs1) Pillar Program (Project no. 2008BADC4B10)
Z. Li et al. / Renewable Energy 60 (2013) 572e577
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