Dielectric characterization of biodegradable wastes during pyrolysis

1  Dielectric characterization of biodegradable wastes 1 during pyrolysis 2 D. Beneroso1, A. Albero-Ortiz2, J. Monzó-Cabrera2, A. Díaz-Morcillo2, A. 3 Arenillas1, J.A. Menéndez1* 4 1Instituto Nacional del Carbón, CSIC, Apartado 73, 33080 Oviedo, Spain 5 2Department of Communication and Information Technologies, Technical 6 University of Cartagena, Cartagena, Spain 7 Corresponding author: Tel.: +34 985 119090 8 E-mail address: [email protected] 9 10 Abstract 11 The lack of dielectric properties data has often been named as one of the 12 reasons that has hampered the simulation of microwave processing of 13 biomass feedstock and process design. In this work, the dielectric behavior 14 of an organic fraction from municipal solid wastes during pyrolysis has been 15 monitored as a function of temperature. Furthermore, the effect of the 16 addition of a microwave absorbent material (carbonaceous char) to the raw 17 biowaste upon the dielectric properties has been investigated for the first 18 time. 19 The efficiency of the conversion of microwave energy to heat, measured by 20 means of the tan δ parameter, is shown in this study to be nearly 20 times 21 higher when the absorbent char is added to the reaction bulk at room 22 temperature and this gap is even greater in the 600 – 800 ºC range. 23 Nevertheless, the results suggest that the addition of increasing amounts of 24 microwave absorbent (up to ca. 40%) impairs microwave penetration, which 25 gives rise to a less homogeneous heating of the bulk. There is therefore an 26 optimum proportion that balances heat conversion and penetration depth. 27 The results of this study lend support to the use of char as a means to 28 induce thermochemical treatments by microwaves and reduce energy 29 consumption in the process. 30 31 Keywords: Dielectric properties, Microwave pyrolysis, Biomass pyrolysis, 32 Microwave heating modeling, Microwave absorbent 33 34 2  1. Introduction 1 On average, every one of the more than 500 million people living in the 2 European Union (EU) throws away around half a ton of household rubbish a 3 year. This is on top of the huge amount of waste generated from activities 4 such as manufacturing (360 million tons) and construction (900 million 5 tons), while the supply of water and the production of useful energy 6 generate another 95 million tons. Altogether, the EU produces up to 3 7 billion tons of waste every year [1]. A significant proportion of waste going 8 to landfill is organic material, (i.e. derived from both biomass and petroleum 9 sources). Thermochemical conversion processes, involving pyrolysis and 10 gasification, can convert this waste at source into potentially useful 11 chemical feedstocks and fuels after the removal of the more readily 12 recyclable materials, such as metals, glass, etc. 13 14 A number of processes are now under development or are at the 15 demonstration stage, whose aim is to provide more cost-effective, 16 environmentally and socially acceptable alternatives to incineration plants. 17 One of these new technologies is microwave pyrolysis based on dielectric 18 heating. This process benefits from the main advantages of using 19 microwaves, such as rapid, volumetric and selective heating, and avoids the 20 need to shred the feedstock and to pre-dry the samples, resulting in a 21 substantial reduction in the costs associated with these steps [2-5]. In spite 22 of these advantages, this technology has not yet reached industrial scale 23 3  owing to the lack of economic analyses on a large scale and the absence of 1 sufficient data to quantify the dielectric properties of the input feedstocks. 2 3 The property that determines the dielectric response of material under the 4 influence of an electric field is the relative complex permittivity, ε*, which is 5 expressed as a function of a real component known as the dielectric constant 6 (which represents the ability of dielectrics to store electrical energy) and an 7 imaginary component known as the dielectric loss factor (which represents 8 the ability of a material to absorb the electric energy): 9 10 11 12 where and ε’ and ε’’ are the dielectric constant and the dielectric loss 13 factor relative to the corresponding dielectric properties of free space. 14 15 An estimation of these properties is essential for the effective design and 16 scaling up of microwave heating processes to ensure an accurate prediction 17 of the absorbed power density; i.e. the rate at which the electromagnetic 18 energy is converted to heat in the material. Dielectric properties may vary 19 with composition, frequency, temperature and even material density [6] 20 and, therefore, it is essential to characterize their variation in relation to 21 those parameters. 22 23 4  Several studies have attempted to characterize the dielectric properties of 1 coal [7] and some kinds of biomass [8, 9] since it is known that the dielectric 2 loss of these materials at low temperatures is negligible, making them 3 transparent to microwaves. However, when the substrates are subjected to 4 higher temperatures (i.e. temperatures higher than 600 ºC), the structures 5 become essentially char, which is known to be a high microwave absorbing 6 material due to the Maxwell-Wagner effect which causes a very high 7 displacement of π-electrons on carbonized structures [10]. It is for this 8 reason that different microwave receptor materials are added to biomass 9 during microwave pyrolysis, so that a high enough temperature is reached 10 to induce pyrolysis [11, 12]. However, most published studies are focused 11 solely on the dependence of dielectric properties upon frequency radiation at 12 room temperature [13-16] and ignore the need for a comprehensive study of 13 the whole microwave pyrolysis process. In other words, an in-depth and 14 extensive study of the dependence of dielectric properties on temperature is 15 needed to obtain a better understanding of the dielectric response of organic 16 substrates during microwave pyrolysis and of mixed organic substrates 17 when used with microwave susceptors. 18 This paper investigates the microwave absorption capability of a 19 biodegradable waste and its mixture with microwave absorbent char on the 20 basis of their dielectric properties, from room temperature up to 800 ºC at 21 the commonly used frequency of 2.45 GHz. 22 23 2. Materials and Methods 24 5  2.1 Biowaste preparation and characterization 1 The biodegradable waste used for this study was an organic fraction from a 2 municipal solid waste, obtained from a landfill in Seville (Spain). The waste 3 was dried, partially cleaned of inerts such as glass or metals and size-4 reduced to 1-3 mm. This fraction has been labelled as MSWd. The pre-5 treatment of this organic residue allows a good homogeneity of this fraction. 6 Actually, this fraction has been used in other studies to produce synthesis 7 gas by means of microwave-induced pyrolysis and the composition of the gas 8 was quite homogeneous when repeating the tests [17]. 9 In order to assess the effect of adding char as microwave absorber to the 10 biowaste upon the dielectric response, a carbonaceous solid char was 11 prepared by subjecting the biowaste sample to a temperature of 800 ºC in an 12 electric furnace for 1 h in an oxygen-free atmosphere. This has been labelled 13 Char-MSWd. The mixtures of char:biowaste were prepared in weight ratios 14 of 0.3:1 and 0.6:1. These two mixture ratios were considered on the basis of 15 keeping the amount of char as low as possible to induce the microwave 16 pyrolysis. In previous studies [17], we used 0.3:1 ratio; thus, we have used 17 this same ratio in this work. Furthermore, a larger amount (0.6:1 ratio) was 18 considered to study the effect of adding char to feedstock as microwave 19 absorbent. 20 The moisture, ash content and volatile matter data of the residues were 21 obtained on a LECO TGA-601 device. To perform the ultimate analysis, a 22 LECO-CHNS-932 micro-analyzer and a LECO-TF-900 furnace were used. 23 The micro-analyzer provided data on the carbon, hydrogen, nitrogen, and 24 6  sulfur percentage composition. The oxygen content was determined using 1 the LECO-TF-900 furnace. The results of proximate and ultimate analyses 2 of the MSWd and char-derived samples are presented in Table 1. 3 4 Table 1. Proximate and ultimate analyses of the MSWd and Char-MSWd fractions 5 Residue Municipal solid waste Char from municipal solid waste Label MSWd Char-MSWd Moisture 2.8 3.3 Asha 27.7 66.6 Proximate analysis (wt.%) Volatile mattera 61.1 1.7 C 45.1 30.7 H 5.4 0.1 N 2.1 1.0 S 0.4 0.7 Ultimate analysis (wt.%) O 19.3 0.9 6 2.2 Measurement of dielectric properties 7 An inverse methodology to obtain the permittivity of the different biowastes 8 was used (Fig. 1) [18]. This technique is one of the most appropriate; other 9 techniques such as standard coaxial probes may lead to lower precision 10 since air bubbles below the coaxial probe can result in lower values of 11 permittivity; resonant-cavity technique is typically used for low-loss 12 materials (which is not our case) and identifying the resonant frequency and 13 quality factor (intrinsic parameters of this technique) would have been 14 difficult due to the high absorption of the materials. First, each sample (see 15 Sample R in Fig. 1) was introduced and uniformly compacted into a quartz 16 tube (i.d. 5 mm, height 43 mm; MSWd bulk density: 166 kg/m3; char bulk 17 7  density: 353 kg/m3) and heated up to a specific temperature in an oxygen-1 free atmosphere by a GALLUR convection oven. The samples were subjected 2 to 25, 50, 100, 200, 300, 400, 500, 600, 700, 800 and 1000 ºC before being 3 very quickly placed (maximum 3 s) in the middle of a WR-340 waveguide 4 where the scattering parameters (i.e., S11, S12, S21 and S22) were measured 5 by means of a RHODE & SCHWARZ, model ZVA67 vector network analyzer 6 set to a frequency of 2.45 GHz. S-parameters describe the response of an N-7 port network to voltage signals at each port. The first number in the 8 subscript refers to the responding port, while the second number refers to 9 the incident port. Thus S21 means the response at port 2 due to a signal at 10 port 1. Afterwards, the measurement system was modeled (Sample S in Fig. 11 1) by using CST Microwave Studio (CST MWS) commercial software and, by 12 inverse techniques, the value of the complex permittivity of each sample at 13 the corresponding temperature was obtained. That is to say, an optimization 14 method (a genetic algorithm combined with a gradient descent optimization 15 method) [18] was applied to the model to obtain a simulated material that 16 would induce the same scattering parameters as those previously measured. 17 As initial values for the corresponding optimization method, the 18 permittivity of the materials was measured in a portable DIMAS 19 dielectrometer, model DIELKITV/DIELKITC at room temperature. The 20 errors during measurements are included in the Supplementary Material. 21 Furthermore, to minimize the uncertainty of the sample cooling on the 22 permittivity measurements during the sample transfer from the oven to the 23 waveguide, the cooling curve was previously estimated and can be found in 24 8  the Supplementary Material. This curve allows establishing the operating 1 temperature of the oven in order to reach the nominal temperature into the 2 waveguide. 3 4 FIGURE 1 5 6 2.3 Loss tangent calculation 7 The loss tangent is an important dielectric property which is directly related 8 to the ability of a specific material to convert electromagnetic energy into 9 heat at a given temperature and frequency. This property is defined as: 10 11 12 13 Furthermore, the relationship between the dielectric properties of biowaste 14 and char was investigated for the two material mixtures over the selected 15 temperature range. The dielectric properties of a mixture of two different 16 materials can be modeled by using different equations such as the Landau, 17 Lifshitz and Looyenga equation (Equation 3), as reported in [19]: 18 19 20 21 where is the volumetric fraction of the material MSWd, which was 22 calculated from its density, and and are the permittivity of 23 the biomass and char fractions, respectively. The accuracy of this model was 24 9  tested using the experimental data obtained over the temperature range 1 selected. 2 3 2.4 Skin depth calculation 4 The skin depth, also known as penetration depth (Ds), is defined as the 5 distance from the surface into the materials at which the travelling 6 electromagnetic wave power drops to e-1 from its value at the surface. The 7 skin depth can be calculated using Equation 4 [20]: 8 9 10 11 where is the microwave wavelength in free space. The skin depth is an 12 important parameter since the use of microwaves as a heating medium 13 usually involves scaling-up limitations due to the difficulty of properly 14 dispersing the microwaves as the material increases in volume [21]. 15 16 3. Results and Discussion 17 The measured dielectric properties of the MSWd and Char-MSWd fractions 18 are shown in Fig. 2 (a) and (b), respectively, versus the increase in 19 temperature. As can be seen, the dielectric properties depend greatly on the 20 temperature during pyrolysis, particularly at high temperatures. 21 FIGURE 2 22 The dielectric constant and loss factor for MSWd show a nearly constant 23 value from room temperature up to 500 °C, corresponding to the pyrolysis 24 16  4. Conclusion 1 The dielectric properties of an organic fraction from a municipal solid waste 2 were determined at 2.45 GHz from room temperature to 800 ºC. The 3 dielectric properties of the biowaste remained constant during pyrolysis up 4 to 400 ºC; then there was a sharp increase in both the dielectric constant 5 and loss factor, owing to the release of volatiles and honeycomb-like carbon 6 structures with a high delocalised electron density. Furthermore, the 7 addition of char as microwave absorbent to the feedstock proved to be an 8 effective way to reduce the energy consumption of the pyrolysis process, 9 because it provided the bulk with a high tan δ at room temperature, 10 although it reduced the penetration depth, which resulted in a more 11 heterogeneous heating when a high concentration of char was used. 12 The dielectric characterization addressed in this paper could serve as a 13 starting point for the design of suitable equipment to perform the 14 microwave-induced pyrolysis at industrial scale with the appropriate 15 simulation software. 16 17 Acknowledgments 18 The research leading to these results has received funding from the 19 European Union’s Seventh Framework Programme for research, 20 technological development and demonstration under grant agreement n° 21 311815 (SYNPOL project). D. B. also acknowledges the financial support 22 received from PCTI and FICYT of the Government of the Principado de 23 Asturias. 24 17  References 1 2 [1]EuropeanCommission,Beingwisewithwaste:theEU’sapproachtowaste3 management,in,2010.4 [2]D.Beneroso,J.M.Bermúdez,A.Arenillas,J.A.Menéndez,Integratedmicrowave5 drying,pyrolysisandgasificationforvalorisationoforganicwastestosyngas,Fuel,1326 (2014)20‐26.7 [3]V.L.Budarin,P.S.Shuttleworth,J.R.Dodson,A.J.Hunt,B.Lanigan,R.Marriott,K.J.8 Milkowski,A.J.Wilson,S.W.Breeden,J.Fan,E.H.K.Sin,J.H.Clark,Useofgreen9 chemicaltechnologiesinanintegratedbiorefinery,Energy&EnvironmentalScience,410 (2011)471‐479.11 [4]F.Motasemi,M.T.Afzal,Areviewonthemicrowave‐assistedpyrolysistechnique,12 RenewableandSustainableEnergyReviews,28(2013)317‐330.13 [5]D.Beneroso,J.Bermúdez,A.Arenillas,J.Menéndez,MicrowavePyrolysisof14 OrganicWastesforSyngas‐DerivedBiopolymersProduction,in:ProductionofBiofuels15 andChemicalswithMicrowave,Springer,2015,pp.99‐127.16 [6]J.B.Salsman,TechniqueforMeasuringtheDielectricPropertiesofMineralsasa17 FunctionofTemperatureandDensityatMicrowaveHeatingFrequencies,MRSOnline18 ProceedingsLibrary,189(1990)null‐null.19 [7]Z.Peng,J.‐Y.Hwang,B.‐G.Kim,J.Mouris,R.Hutcheon,MicrowaveAbsorption20 CapabilityofHighVolatileBituminousCoalduringPyrolysis,Energy&Fuels,26(2012)21 5146‐5151.22 [8]F.Motasemi,M.T.Afzal,A.A.Salema,Microwavedielectriccharacterizationofhay23 duringpyrolysis,IndustrialCropsandProducts,61(2014)492‐498.24 [9]F.Motasemi,M.T.Afzal,A.A.Salema,J.Mouris,R.M.Hutcheon,Microwave25 dielectriccharacterizationofswitchgrassforbioenergyandbiofuel,Fuel,124(2014)26 151‐157.27 [10]J.A.Menéndez,A.Arenillas,B.Fidalgo,Y.Fernández,L.Zubizarreta,E.G.Calvo,28 J.M.Bermúdez,Microwaveheatingprocessesinvolvingcarbonmaterials,Fuel29 ProcessingTechnology,91(2010)1‐8.30 [11]D.Beneroso,J.M.Bermúdez,A.Arenillas,J.A.Menéndez,Microwavepyrolysisof31 microalgaeforhighsyngasproduction,BioresourceTechnology,144(2013)240‐246.32 [12]D.Beneroso,J.M.Bermúdez,A.Arenillas,J.A.Menéndez,Influenceofthe33 microwaveabsorbentandmoisturecontentonthemicrowavepyrolysisofanorganic34 municipalsolidwaste,JournalofAnalyticalandAppliedPyrolysis,105(2014)234‐240.35 [13]A.A.Salema,Y.K.Yeow,K.Ishaque,F.N.Ani,M.T.Afzal,A.Hassan,Dielectric36 propertiesandmicrowaveheatingofoilpalmbiomassandbiochar,IndustrialCrops37 andProducts,50(2013)366‐374.38 [14]R.Omar,A.Idris,R.Yunus,K.Khalid,M.I.AidaIsma,Characterizationofempty39 fruitbunchformicrowave‐assistedpyrolysis,Fuel,90(2011)1536‐1544.40 [15]S.Ramasamy,B.Moghtaderi,DielectricpropertiesoftypicalAustralianwood‐41 basedbiomassmaterialsatmicrowavefrequency,Energy&Fuels,24(2010)4534‐42 4548.43 [16]A.A.Salema,M.T.Afzal,Numericalsimulationofheatingbehaviourinbiomassbed44 andpelletsundermultimodemicrowavesystem,InternationalJournalofThermal45 Sciences,91(2015)12‐24.46 18  [17]D.Beneroso,J.M.Bermúdez,A.Arenillas,J.A.Menéndez,Comparingthe1 compositionofthesynthesis‐gasobtainedfromthepyrolysisofdifferentorganic2 residuesforapotentialuseinthesynthesisofbioplastics,JournalofAnalyticaland3 AppliedPyrolysis,111(2015)55‐63.4 [18]M.E.Requena‐Perez,A.Albero‐Ortiz,J.Monzo‐Cabrera,A.Diaz‐Morcillo,5 Combineduseofgeneticalgorithmsandgradientdescentoptmizationmethodsfor6 accurateinversepermittivitymeasurement,MicrowaveTheoryandTechniques,IEEE7 Transactionson,54(2006)615‐624.8 [19]D.C.Dube,StudyofLandau‐Lifshitz‐Looyenga'sformulafordielectriccorrelation9 betweenpowderandbulk,JournalofPhysicsD:AppliedPhysics,3(1970)1648.10 [20]J.P.Robinson,S.W.Kingman,E.H.Lester,C.Yi,Microwaveremediationof11 hydrocarbon‐contaminatedsoils–Scale‐upusingbatchreactors,Separationand12 PurificationTechnology,96(2012)12‐19.13 [21]J.Doucet,J.‐P.Laviolette,S.Farag,J.Chaouki,DistributedMicrowavePyrolysisof14 DomesticWaste,WasteandBiomassValorization,5(2014)1‐10.15 [22]M.Tripathi,J.N.Sahu,P.Ganesan,T.K.Dey,Effectoftemperatureondielectric16 propertiesandpenetrationdepthofoilpalmshell(OPS)andOPScharsynthesizedby17 microwavepyrolysisofOPS,Fuel,153(2015)257‐266.18 [23]Y.Fernández,A.Arenillas,J.Á.Menéndez,MicrowaveHeatingAppliedtoPyrolysis,19 AdvancesinInductionandMicrowaveHeatingofMineralandOrganicMaterials,20 StanisławGrundas(Ed.),ISBN:978‐953‐307‐522‐8,InTech,InTech,2011.21 [24]J.P.Robinson,C.E.Snape,S.W.Kingman,Developinghighpowermicrowave22 processingasaneffectivetechnologyforthethermo‐chemicalconversionof23 biodegradablemunicipalwaste,in:TechnologyREsearchandInnovationFundProject24 Report,UniversityofNottingham,2010.25 [25]H.H.Sait,A.A.Salema,MicrowavedielectriccharacterizationofSaudiArabiandate26 palmbiomassduringpyrolysisandatindustrialfrequencies,Fuel,161(2015)239‐247.27 28 29 30 31 32 33 19  1 Figure captions 2 3 Figure 1. Inverse methodology for determining the dielectric properties 4 based on the procedure described in [18] 5 6 20  1 Figure 2. Dielectric properties of the (a) MSWd fraction (b) Char-MSWd 2 fraction during pyrolysis. 3 4 5 21  1 Figure 3. Evolution of tan δ during pyrolysis for the (a) MSWd and (b) 2 Char-MSWd fractions. 3 4 22  1 Figure 4. Dielectric constant of the mixtures 2 3 23  1 Figure 5. Loss factor of the mixtures 2 3 24  1 Figure 6. Evolution of tan δ during pyrolysis for the different char/biowaste 2 mixtures. tan δ from MSWd fraction is also depicted as a means of 3 comparison 4 5 25  1 Figure 7. Microwave skin depth for the mixtures of MSWd with Char-2 MSWd during pyrolysis 3 4 32  1 Mixture Char:MSWd (0.6:1) 2 0100 200 300 400 500 600 700 800 0 20 40 60 80 100 120 140 Temperature (ºC) ε ´ ε ´ vs Temperature Material 3 ε ´ ε ´+U ε ´ ε ´-U ε ´ 3 0100 200 300 400 500 600 700 80 0 0 20 40 60 80 100 120 140 Temperature (ºC) ε ´´ ε ´´ vs Temperature Material 3 ε ´´ ε ´´+U ε ´´ ε ´´-U ε ´´ 4 33  0100 200 300 400 500 600 700 800 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 Temperature (ºC) tanδ tanδ vs Temperature Material 3 tanδ tanδ+Utanδ tanδ-Utanδ 1 34  1 Char sample 2 3 0100 200 300 400 500 600 700 80 0 0 20 40 60 80 100 120 140 Temperature (ºC) ε´ ε´ vs Temperature Material 4 ε´ ε´+Uε´ ε´-Uε´ 4 0100 200 300 400 500 600 700 80 0 4 5 6 7 8 9 10 11 12 13 Temperature (ºC) ε´´ ε´´ vs Temperature Material 4 ε´´ ε´´+Uε´´ ε´´-Uε´´ 5 35  0100 200 300 400 500 600 700 80 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 Temperature (ºC) tan δ tan δ vs Temperature Material 4 1 2 36  1 Cooling down curve 2 50 100 150 200 250 300 350 400 450 500 0 200 400 600 800 1000 1200 Time (s) Temperature (C) Cooling curve Interpolated. Max descent: 22.47 C/s Measured 3 4 5