A methodology for optimising feed composition for anaerobic co-digestion of agro-industrial wastes

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<ul><li><p>os</p><p>omp</p><p>Organic wasteBatch assayLinear programming</p><p>forlinetraterdend bssay</p><p>(16.4 L CH4/kg COD d) was obtained by a mixture containing 88% pig manure, 4% sh waste and 8% bio-</p><p>f organith 120t reprereatme</p><p>2007; Weiland, 2000), and there is an increasing interest, mainlyin Europe, in using this technology for bioenergy production. Onthe other hand, it is well known that organic waste anaerobicdigestion produces a new semi-liquid waste: digestate, whichcan be used in agriculture after doing a stabilisation or compostprocess.</p><p>Co-digestion is dened as the anaerobic treatment of a mixtureof at least two different waste types with the aim of improving the</p><p>1993; Chen et al., 2008; Hansen et al., 1998).Alkalinity is necessary to avoid decreasing pH due to accumula-</p><p>tion of volatile fatty acids when applying a high organic load.Anaerobic digesters work in a wide variety of alkalinity valuesdepending on the substrate to be degraded. These values rangefrom 2000 to 18000 mg CaCO3/L (Cuetos et al., 2008; Gelegeniset al., 2007a; Murto et al., 2004; Mshandete et al., 2004).</p><p>Moller et al. (2004) studied the specic methane productivity ofdifferent types of manure in batch tests. The specic methanepotentials measured were 148 41, 356 28 and 275 36 L CH4/kg VS (volatile solids) for cattle, pig fattener and sow manure,</p><p>* Corresponding author. Tel.: +34 981563100x16016; fax: +34 981528050.</p><p>Bioresource Technology 101 (2010) 11531158</p><p>Contents lists availab</p><p>T</p><p>elsE-mail address: juanantonio.alvarez@usc.es (J.A. lvarez).2006). The idea of co-digestion offers several possible ecological,technological and economical advantages, so it can improveorganic waste treatment through anaerobic digestion. Anaerobicco-digestion can increase CH4 production of manure digesters by50200%, depending on the operating conditions and the co-sub-strates used (Amon et al., 2006; Callaghan et al., 1999; Ferreiraet al., 2007; Murto et al., 2004; Soldano et al., 2007). Currently,there is a increasing number of full-scale co-digestion plants treat-ing manure and industrial organic wastes, mainly in Denmark andGermany (Angelidaki and Ellegaard, 2003; Raven and Gregersen,</p><p>ents, C:N ratio, pH, inhibitors/toxic compounds, biodegradable or-ganic matter and dry matter (Hartmann et al., 2003). Optimumvalues of C:N and COD:N ratios of 20 and 70, respectively, havebeen suggested for the stable performance of anaerobic digestion(Burton and Turner, 2003; Chen et al., 2008). However, lower val-ues of C:N ratios (between six and nine) have been reported assuitable for the anaerobic digestion of nitrogen-rich waste(Mshandete et al., 2004). Threshold limits of free ammonia and to-tal ammonia of 1.1 and 4 g N/L, respectively, in swine and cattlemanure digestion have been reported (Angelidaki and Ahring,1. Introduction</p><p>Although anaerobic digestion oestablished technology in Europe, wing about 4 million tons per year, i27.5% of all of the biological waste t0960-8524/$ - see front matter 2009 Elsevier Ltd. Adoi:10.1016/j.biortech.2009.09.061diesel waste.Linear programming was proved to be a powerful, useful and easy-to-use tool to estimate methane</p><p>production in co-digestion units where different substrates can be fed. 2009 Elsevier Ltd. All rights reserved.</p><p>ic solid wastes is anfull-scale plants treat-sents on average, onlynt processes (De Baere,</p><p>efciency of the anaerobic digestion process. Therefore, it is veryimportant to establish the best blend in order to maximise meth-ane production, avoid inhibition processes and make protablebiogas plants.</p><p>The main issue for co-digestion process lies in balancing severalparameters in the co-substrate mixture: macro- and micronutri-Keywords:Anaerobic co-digestion</p><p>The highest biodegradation potential (321 L CH4/kg COD) was reached with a mixture composed of 84%pig manure, 5% sh waste and 11% biodiesel waste, while the highest methane production rateA methodology for optimising feed compof agro-industrial wastes</p><p>J.A. lvarez *, L. Otero, J.M. LemaDepartment of Chemical Engineering, School of Engineering, University of Santiago de C</p><p>a r t i c l e i n f o</p><p>Article history:Received 9 June 2009Received in revised form 17 September 2009Accepted 18 September 2009Available online 14 October 2009</p><p>a b s t r a c t</p><p>An optimisation protocolwastes was carried out. Amaximising the total subs(L CH4/kg substrate d). In omanure, tuna sh waste astudies in discontinuous a</p><p>Bioresource</p><p>journal homepage: www.ll rights reserved.ition for anaerobic co-digestion</p><p>ostela, Ra Lope Gmez de Marzoa, 15782 Santiago de Compostela, Spain</p><p>maximising methane production by anaerobic co-digestion of severalar programming method was utilised to set up different blends aimed atbiodegradation potential (L CH4/kg substrate) or the biokinetic potential</p><p>r to validate the process, three agro-industrial wastes were considered: pigiodiesel waste, and the results obtained were validated by experimentals.</p><p>le at ScienceDirect</p><p>echnology</p><p>evier .com/locate /bior tech</p></li><li><p>Although there is a sufcient methodology for determining bio-methanation potential, most of the approaches used to date are</p><p>for storage until characterisation and triturated until homogenised.Biodiesel waste (BW) was sampled from a biodiesel factory. It con-</p><p>echtained mainly glycerine (glycerol) produced in the transesterica-tion of triglycerides with methanol and sodium hydroxide togenerate biodiesel (methyl esters).</p><p>Granular biomass from a pilot hybrid reactor (UASB-FA) treat-ing wine waste and from an IC reactor treating brewery wastewa-ter was used as inoculum in the biodegradation assays andbiokinetic assays, respectively. During biodegradation assays,anaerobic hybrid reactor was washed and its biomass was lost,so a similar granular inoculum had to be used to carry out bioki-netic assays and the IC reactor biomass was selected. The specicmethanogenic activities of each inoculum were 0.15 and0.10 g CH4-COD/g SSV d, respectively.</p><p>2.2. Analytical methods</p><p>Standard methods (1995) were applied for pH measurementsand for determination of COD, TS, VS, TKN-N, NH4 N and TA (totalalkalinity). Biogas composition (N2, CH4, CO2 and H2S percentage)was analysed by gas chromatography (HP, 5890 Series II) equippedwith a thermal conductivity detector (Molina et al., 2008). Volatilefatty acids (VFA) were determined by gas chromatography (HP,5890A) equipped with a ame ionisation detector (Molina et al.,2008). Samples were previously centrifuged (5 min, 3500 rpm),and the supernatant ltrated through 0.45-lm cellulose lters. To-based on experimental studies concerning the behaviour of differ-ent feedings with different properties of raw waste.</p><p>The aim of this work is to develop a methodology useful fordetermining the most adequate ratios of different co-substratesthat provide an optimised biodegradation potential or biokineticmethane potential.</p><p>For this propose, a linear programming optimisation methodbased on determining restrictions (minimum and maximum val-ues) on several characteristics of the mixture has been developed.In order to validate the methodology, three types of wastes withquite different characteristics (pig manure, sh waste and biodieselwaste) were considered as co-substrates.</p><p>2. Methods</p><p>2.1. Waste and inoculum origin and collection</p><p>Pig manure (PM) was taken from a sewer of a 150-pig fattenerand sow farm, which collects both faeces and urine. It was stored at4 C until characterisation. PM samples were homogenised andsieved to 2 mm. Fish waste (FW) from a canning industry consistedof heads, tails, sh bones and viscera of tuna sh. FW was frozenrespectively. The manure specic methane potential has been im-proved by co-digestion with other substrates: sewage sludge (Mur-to et al., 2004), fruit and vegetable waste (Ferreira et al., 2007),energy crops (Lehtomki et al., 2007), glycerine (Amon et al.,2006) and the organic fraction of municipal solid waste (Hartmannand Ahring, 2005).</p><p>Waste biomethanation potential depends on the concentrationof the three main organic components: proteins, lipids and carbo-hydrates, and a substrate characterisation is required to predictmethane production (Gelegenis et al., 2007a,b; Maya-Altamiraet al., 2008; Neves et al., 2008; Shanmugam and Horan, 2009).</p><p>1154 J.A. lvarez et al. / Bioresource Ttal lipid content was determined using a Standard Soxhlet method(Standard methods, 1995). Proteins were calculated from organicnitrogen composition. Carbohydrates were estimated as theremaining fraction of VS or COD after proteins and lipids weredetermined.</p><p>2.3. Linear programming</p><p>Computational software used to solve linear programmingproblems is actually a strength technological alternative whichfacilitates feasibility studies. Specically, ExcelTM Solver is an ade-quate tool of relatively easy initial programming and versatile pos-terior usage to apply for different problems solution. So, solvermethod from ExcelTM was chosen as linear programming tool in thiswork.</p><p>The reported method consists of maximising an objective func-tion, taking into account several restrictions that need to be ful-lled. Two different objective functions have been considered:the total substrate biodegradation potential (L CH4/kg wet weight(WW) of the substrate); taking into account substrate transforma-tion efciency and the biokinetic potential (L CH4/kg WW d); tak-ing into account kinetic capacity of the anaerobic process. Thetheoretical biodegradation potential value was calculated fromthe COD content of the different wastes using a factor of350 L CH4/kg COD removed (Angelidaki and Sanders, 2004). Thetheoretical biokinetic potential was calculated by considering thefollowing values: 35 L CH4/kg lipid d; 42 L CH4/kg protein d and27 L CH4/kg carbohydrate d (Neves et al., 2008).</p><p>Minimum and maximum values of the following parameterswere considered as the restrictions on the system: COD/N ratio(calculated as COD/TKN-N); NH4 N concentration, calculated byassuming a full protein digestion (0.124 g N/g protein) (Angelidakiand Sanders, 2004; Gelegenis et al., 2007a); lipid concentration; to-tal alkalinity; liquid fraction; COD/SO24 ratio; chloride.</p><p>As a result of each optimisation, which corresponds to a partic-ular set of restrictions, the program gives the fraction of each sub-strate to be used in the blend to obtain the maximumbiodegradation and biokinetic potential.</p><p>The organic loading rate value was also considered as a restric-tion when the biokinetic potential was determined.</p><p>Restriction values of total alkalinity, liquid fraction, COD/SO24ratio and chloride were maintained constant in all cases. Their val-ues were the following: total alkalinity: between 3 and 20 g CaCO3;liquid fraction: between 85% and 100%; COD/SO24 ratio: higherthan 15; chloride: lower than 3 g/L.</p><p>The following minor restrictions must be stipulated to developproper solver programming: the sum of the substrate fraction inthe blend must be equal to 100 and each fraction must be higherthan 0.</p><p>Summarising, the parts of linear programming method used inthis work are the following:</p><p>1. Input proposed restrictions.2. Calculate theoretical restrictions values according substrate</p><p>characterisation.3. Calculate fractions of each waste to set up the blend, which</p><p>have to full proposed restrictions and maximised methaneproduction (total biodegradation or kinetic transformation).</p><p>2.4. Batch assay methodology</p><p>Batch assays were carried out in 500-mL glass asks with coiledbutyl rubber stoppers. All tests were performed in triplicate assaysunder the following operating conditions: 35 C, mixing at 120 rpmand 5 g VSS/L of inoculum. Substrate feed was composed by adding</p><p>nology 101 (2010) 1153115810 mL of the optimised blend, the substrate concentration varyingfrom 4 to 9 g TCOD/L. Control assays with only inoculum and withboth inoculum and PM were also performed.</p></li><li><p>Anaerobic conditions were maintained by using an anaerobicbasal medium composed of cysteine (0.5 g/L) and NaHCO3 (5 g/L),at a pH of 7.07.2. Before ushing the liquid and headspace withN2, 1.2 mL of Na2S (20 g/L) was added to each assay as a reducingagent (Molina et al., 2008). An initial liquid volume of 385 mL wasused in all assays. A pressure transducer was used to measure the</p><p>pressure increase. The biogas was sampled regularly, and its com-position was determined by gas chromatography.</p><p>2.5. Calculations</p><p>Batch assay methane production was plotted as CH4-COD (g)against time (d). Firstly, moles of methane were calculated bythe ideal gas law:</p><p>Table 1PM, FW and BW characterisation.</p><p>Parameter Pigmanure</p><p>Fishwaste</p><p>Biodieselwaste</p><p>Liquid fraction (%) 98.3 63.1 100pH 6.9 nd ndSoluble fraction conductivity (mS/</p><p>cm)29.5 140.4 45.5</p><p>Density (kg WWa/L) 1.0 1.1 1.0TS (g TS/kg WW) 17.3 369 0VS (g SV/kg WW) 11.7 270 0COD (g O2/kg WW) 28.9 409.6 1390Soluble COD (g O2/kg WW) 15.3 nd 1390TKN-N (g N/kg WW) 3.3 33.6 0.2NH4 N (g N/kg WW) 3.1 0.7 0Total alkalinity (g CaCO3/L) 7.7 0.3 32Chloride (g/kg WW) 0.5 34.9 ndSulphate (g/kg WW) 0.04 0.7 ndVFA-COD (g VFA-COD/kg WW) 12.2 0 0Proteins (g prot.b/kg WW) 1.1 205.8 1.2Lipids (g lip.c/kg WW) 1.5 28 77.3Carbohydrates (g ch.d/kg WW) 9.2 36.2 921.5e</p><p>COD/N ratio 8.9 12.2 7315</p><p>a Wet weight.b Proteins.c Lipids.d Carbohydrates.e Carbohydrates were determined by the COD balance; nd: not determined.</p><p>Table 2Percentage of each waste on blends A, B and C, determined by linear programmingand theoretical biodegradation potential of each blend.</p><p>Blend Main inputrestrictionsa</p><p>Fullledrestrictionvalues</p><p>Wastepercentage(%WW b)</p><p>Theoreticalbiodegradationpotential c</p><p>(L CH4/kg WW)</p><p>A 50 &lt; COD/N &lt; 100 50.6 Manure: 91 530.2 &lt; NH4 N &lt; 3.5 3.0 Fish waste: 00.5 &lt; Lip &lt; 8.3 8.3 Biodiesel waste: 9</p><p>B 50 &lt; COD/N &lt; 100 100 Manure: 82 950.2 &lt; NH4 N &lt; 3.5 2.7 Fish waste: 00.5 &lt; Lip &lt; 15 15.0 Biodiesel waste: 18</p><p>C 50 &lt; COD/N &lt; 90 90 Manure: 74 1200.2 &lt; NH4 N &lt; 3.5 3.5 Fish waste: 40.5 &lt; Lip &lt; 20 19.2 Biodiesel waste: 22</p><p>a NH4 N and lip (lipids) in g/L.b Wet weight.c Determined by linear programming method based on total biodegradation</p><p>potential.</p><p>Table 3the c</p><p>prod</p><p>LCH4</p><p></p><p>J.A. lvarez et al. / Bioresource Technology 101 (2010) 11531158 1155Experimental and theoretical specic methane production of mixtures A, B, C and of</p><p>Assay ExperimentalCH4-COD (g/L)</p><p>TheoreticalCH4-COD (g/L)</p><p>Experimental methane</p><p>(LCH4/kg WW) (</p><p>Blend A 2.9 3.9 37.6 2Blend B 0.5 7.1 6.8Blend C 0.8 8.9 11.3</p><p>PM 4.7 7.0 6.7 230.4</p><p>a Obtained by linear programming.CH4moles PT XCH4 VgasR T 273 ;</p><p>where PT is the total pressure measured by the transducer (mmHg);XCH4 is the methane molar fraction; Vgas is the headspace volume(mL); R is the ideal gas constant (62,364 mmHgmL/mol K); and Tis the assay temperature (C). CH4-COD (g) can be calculated bymultiplying the moles of CH4 by 64 (g DQO/CH4 mol).</p><p>The experimental specic methane potential at standard tem-perature and pressure conditions was calculated by dividing theCH4 volume produced by the waste quantity at the beginning ofthe assay in wet weight and the COD bases (STP L CH4/kg WW orSTP L CH4/kg COD). The theoretical specic methane...</p></li></ul>


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