BIOCHEMICAL HYDROGEN POTENTIAL TEST OF
THE ORGANIC FRACTION OF MUNICIPAL SOLID
WASTE IN PILOT SCALE REACTORS
Isabella Pecorini
1, Francesco Baldi
2, Elena Albini
2, Giovanni Galoppi
1, Giovanni
Ferrara
1, Reanto Iannelli
31 DIEF, Department of Industrial Engineering, University of Florence, via Santa Marta 3, 50139 Florence, Italy 2 PIN s.c.r.l., Servizi didattici e scientifici per l’Università di Firenze, Piazza G. Ciardi 25, 59100 Prato, Italy 3 DESTEC – Derpartment of Energy, Systems, Territory and Construction engineering, University of Pisa, Largo Lucio Lazzarino, 56122 Pisa, Italy
ABSTRACT: In this paper a new biochemical hydrogen potential test set-up was presented. The test was performed in pilot scale reactors (working volume 3 l, total volume 6 l) using automatic pH control by means of NaOH 2M solution addition. This configuration is an optimal solution when the investigated substrate is highly heterogeneous such as the case of the organic fraction of municipal solid waste. Due to the automatic addition of NaOH solution, pH was stable all over the tests around the set value of 5.5. Experimental data were well fitted by the kinetic model of Gompertz with determination coefficients higher than 0.997.
Keywords: Biochemical Hydrogen Potential, Organic Fraction of Municipal Solid Waste, Pilot scale reactor, automatic pH control
1. INTRODUCTION
The increasing interest in anaerobic digestion of biodegradable residues has moved the scientific community towards further development of the process. For instance, bio-hydrogen production during the fermentative phase is regarded as a key topic by many researchers. Hydrogen is considered to be the fuel of the future owing to its high energy content and environmentally friendly production. Such benefits are further promoted if hydrogen is produced through the biochemical conversion of biodegradable wastes (Ghimire et al., 2015). Several substrates have been tested for hydrogen production (Ghimire e al., 2015) and, among them, the organic fraction of municipal solid waste (OFMSW) seems to be a promising feedstock due to its biodegradability characteristics and availability (Cappai et al., 2014).
In order to have a rapid, low cost and valuable response of hydrogen production of a substrate, Biochemical Hydrogen Potential (BHP) tests are used in literature (Alibardi and Cossu, 2015, Alibardi and Cossu, 2016, Cappai et al., 2014, Chinellato et al., 2013). BHP tests consist in batch reactors where a certain amount of substrate is incubated with an inoculum under anaerobic fermentative conditions. Batch tests are mostly preferred when time and costs are a constraint due to their simplicity and less time-consuming procedure in comparison with more complex and high-priced continuous reactor experiments. BHP assays evaluate the specific amount of hydrogen that can be potentially produced when a certain substrate or waste is biodegraded under fermentative conditions and it is
usually expressed as NlH2/kgTVSsub. In particular, BHP tests play a fundamental role as previous experimental tests to assess the potential, adequacy and viability of the fermentative treatment of such wastes of interest.
In this paper a new set-up and methodology of the test is presented. Tests are performed in pilot scale stainless steel reactors, each one with a total volume of 6 liters and with automatic pH control. This configuration is a scale up of the system. Indeed, BHP tests are generally performed in vessels of smaller volume (0.5-1 l: Akhlagi et al., 2017, Alibardi and Cossu, 2015, Alibardi and Cossu, 2016). In this way a greater amount of substrate can be subjected to the test. This feature is particularly important when substrates are highly heterogeneous such as the case of OFMSW.
2. MATERIALS AND METHODS
2.1 Inoculum and substrates characterization
Activated sludge collected from the aerobic unit of a municipal wastewater treatment plant was used as inoculum (Akhlagi et al., 2017, Cappai et al., 2014, De Gioannis et al., 2017). The sample was heat treated at 80°C for 30 minutes prior to fermentation tests with the aim of selecting only HPB while inhibiting hydrogenotrophic methanogens (Alibardi and Cossu, 2015). The treatment was performed in 250 ml beakers placed in a static oven (UM200, Memmert GmbH, Germany). The temperature of the medium was continuously measured with a digital tip thermometer (T1, Testo S.p.A., Italy). Treatment time started when the temperature of the medium reached 80°C. After 30 minutes, the inocula were removed from the oven and cooled down to ambient air temperature. Tests were carried out when the inoculum temperature reached mesophilic conditions.
Two samples of OFMSW (OFMSW1 and OFMSW2) collected in two different Tuscan municipalities (Italy) by means of a curbside collection system were used as substrates. In order to obtain a slurry with a total solid content suitable to wet fermentation, samples were treated in a food processor, sifted with a strainer (3 mm diameter) and mixed with tap water (Pecorini et al., 2016).
2.2 Experimental set-up
The tests were performed in pilot scale stainless steel reactors with a total volume of 6 l and a working volume of 3 l (Figure 1).
Specific hydrogen production (SHP) was determined as the cumulated hydrogen production divided by the TVS content contained in each batch. In The ratio between volatile solids of inoculum and volatile solids of substrate was 0.75 gTVSIN/gTVSsub. pH is controlled by the automatic addition of a NaOH 2M solution. This configuration has been already used in several works instead of using an initial buffer solution (Cappai et al., 2014, De Gioannis et al., 2017, Akhlagi et al., 2017).
Figure 2 shows the experimental measurement chain and the data acquisition system.
Continuous mixing inside the reactors was ensured by mixing blades connected to electric gearmotors (COAX MR 615 30 Q 1/256) that regulated the rotational speed. Warm water heated by a thermostatic bath passed through each reactor cladding in order to keep the temperature constant at mesophilic conditions (37.0 ± 0.1 °C). On the caps of the reactors, relief valves and check valves were installed for the pressure control inside them. The reactors were equipped with sensors and components for measuring the main parameters. A pH probe equipped with PT100 (Mettler Toledo InPro4260i, 0-14 pH) and a conductivity probe (Mettler Toledo InPro7100i) were installed inside each reactor and were connected to a transmitter (MT M300) to obtain the values of pH, temperature, conductivity and redox, and to convert them into current signals (4-20 mA). The volume of the produced gas during the tests was measured by using volumetric counters connected to the upper side of the reactors through a 3-way valve. Each counter was composed by two concentric cylinders partially filled with water: when the gas entered from the reactor to the external side of the counter, the water rose through the internal cylinder up to reach a level defined by the an electrode. Then, an impulse was given to the 3-way valve in order to connect the counter with a 10 l multilayer foil bag (Supel TM, Merck KGaA, Germany) that collects the gas. Once a minimum water level was reached, the valve reconnect the counters to the reactors end the gas restarted to enter into them. Each impulse was related to a gas volume of 0.07 l. In order to convert gas volume data at normal conditions, ambient pressure and temperature were measured by a pressure transducer (Delta Ohm HD 9908T BARO, 800-1100 mbar, ±0.25% F.S.) and a T-type thermocouple, respectively.
All signals coming from all reactors were acquired by using a National Instruments cRIO 9030 and were processed by a software specifically developed in Labview®. Due to the long duration of the tests, the software acquired the signals every 4 seconds for the real-time visualization, whereas the processed data were recorded every 5 minutes. The acquisition system and the software was used also to control the rotation of a peristaltic pump that dosed a NaOH 2M solution addition to regulate the pH. In particular, the solution was automatically added when the pH decreased under 5.5 in order to keep this value in the range 5.5-5.6 all through the tests. The communication between the acquisition device and the pump occurred via a serial RS232 connection. The same pump was used to dose the NaOH solution in all three reactors.
In order to determine hydrogen production, the hydrogen content of the gas was analysed using a gas chromatograph (3000 Micro GC, INFICON, Switzerland) equipped with a thermal conductivity detector. Hydrogen, Nitrogen, oxygen and methane gas passed through a Molsieve column (30 μm /320 μm / 10 m) using argon as gas carrier at a temperature of 50°C. Carbon dioxide and hydrogen sulphide passed through a PLOTQ column (10 μm /320 μm / 8 m) using helium as gas carrier at temperature of 55°C.
After set-up, the reactors were flushed with N2 gas to ensure anaerobic conditions and to drive off air from the reactor headspace.
Figure 2. Experimental measurement chain and the data acquisition system.
2.3 Kinetic model
The mean cumulative hydrogen production curves were obtained over the course of the batch experiments and analysed using the modified Gompertz equation (Eq. 1, Van Ginkel et al., 2005):
H (t)=H
maxexp
{
−
exp
[
r∙ e
H
max(
λ−t )+1
]
}
(1)where:
H(t): specific hydrogen production at time t (NlH2/kgTVSsub); Hmax: total amount of hydrogen produced (NlH2/kgTVSsub); r: maximum hydrogen production rate (NlH2/kgTVSsub h) λ: length of the lag phase (h).
The time needed to attain 95% of the maximum hydrogen yield (t95), was obtained from the Gompertz equation as follows (Cappai et al., 2014, Eq. (4)):
(2) Constants were estimated by minimizing the sum square of errors between the experimental data and model results. The estimations were carried out by using the solver function of Microsoft Excel version 2016.
Table 1. Substrates and inoculum characterization. Values are expressed by averages and standard deviations (n = 3). Sample TS (% w/w) TVS (% w/w) pH Inoculum 2.1 ± 0.2 1.5 ± 0.1 7.1 ± 0.0 OFMSW1 5.7 ± 0.1 4.3 ± 0.1 3.7 ± 0.2 OFMSW2 5.6 ± 0.1 5.1 ± 0.1 3.8 ± 0.1 3. RESULTS
Specific cumulative hydrogen productions and the kinetic parameters derived from fitting the experimental data with the Gompertz equation (Eq. (2)) are reported in Table 2. SHP curves are expressed in terms of NlH2/kgTVSsub and depicted in Figure 1. In this figure, experimental data are shown as single points while solid lines represent Gompertz model curves. In order to avoid visual misunderstandings, experimental data are represented every hour. Dashed lines represent NaOH solution consumption during the experiment.
Figure 3. Mean SHP curves. Points indicate experimental results; solid lines Gompertz model trends; dashed lines NaOH solution consumption.
Table 2. Substrates and inoculum characterization. Values are expressed by averages and standard deviations (n = 3). Sample (NlH SHP 2/kgTVSsub) Hmax (NlH2/kgTVSsub) R (NlH2/kgTVSsub h) λ (h) t95 (h) R2 OFMSW1 35.1 35.4 5.2 4.3 14.3 0.999 OFMSW2 82.3 83.3 6.1 3.2 23.1 0.997
During all fermentation assays no methane was detected. Thermal pretreatment of inoculum was therefore efficient in the inhibition of hydrogenotrophic methanogens.
SHP from OFMSW (35.1 – 82.3 NlH2/kgTVSsub) were comparable to findings of previous works. Alibardi and Cossu (2015) highlighted results in the range of 25-85 NlH2/kgTVSsub while Alibardi and Cossu (2016) found 78-135 NlH2/kgTVSsub for different organic waste mixtures.
The addition of NaOH solution was able to control pH all over the test. pH was stable around 5.5 ± 0.1 for both experiments. The total amount of NaOH solution added during the tests was 34 and 48 ml respectively for OFMSW1 and OFMSW2. As it can be highlighted from Figure 3, NaOH consumption and hydrogen production observed three phases during the test. The first 3-4 hours represented the lag phase (λ, table 2). It is an acclimatisation phase where bacteria still do not produce hydrogen and NaOH solution is not consumed. The second stage was characterized by a noticeable production of hydrogen and consumption of NaOH solution. In this phase acidogenic bacteria convert the products from the initial hydrolytic stage into hydrogen, carbon dioxide, acetates and volatile fatty acids (Khan et al., 2016). The production of acids is linked to a decrease of pH and subsequently a consumption of NaOH solution to keep pH constant to the set value. In this phase, the trend highlighted the maximum hydrogen production rate (r, Table 2) that it was found to be 5.2 and 6.1 NlH2/kgTVSsub h respectively for OFMSW1 and OFMSW2. After that, when bacteria finished to degrade the easily degradable organic matter, hydrogen and volatile fatty acids production decreased together with the consumption of the alkali solution. As it can be seen from both experiments, a correlation was found between hydrogen production and NaOH solution: the more hydrogen was generated, the more alkali solution was consumed. This finding is probably attributable to the composition of the OFMSWs. As such, OFMSW1 was probably characterized by a higher content of carbohydrates and easily degradable matter than OFMSW2 that resulted in a higher generation of hydrogen and consumption of NaOH solution.
Concerning the kinetics, Gompertz model fitted well the experimental data with high coefficients of determination for both assays (R2 > 0.997). The maximum hydrogen production rate for OFMSW was in the range of previous literature data. Cappai et al., 2014 reported maximum hydrogen production rates in the range of 2.4 – 16.6 NlH2/kgTVSsub h depending on pH and inoculum pretreatment, while De Gioannis et al., 2017 found a maximum hydrogen production rate of 3.9 NlH2/kg TVSsub h. In the matter of t95, the time required to attain 95% of the maximum hydrogen yield was 14.3 and 23.1 h respectively for OFMSW1 and OFMSW2. These results were concurrent with previous works (Cappai et al. 2014, t95 = 9.1 – 32.2 h; De Gioannis et al., 2017: t95 = 26.4 h).
Experimental data were well fitted by the kinetic model of Gompertz with determination coefficients higher than 0.997.
AKNOWLEDGEMENTS
The research was supported by the MIUR-Regione Toscana DGRT 1208/2012 and MIUR-MISE-Regione Toscana DGRT 758/2013 PAR FAS 2007-2013 in sub-programme FAR-FAS 2014 (Linea d’Azione 1.1).
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