CETvol87
DOI: 10.3303/CET2187050
Paper Received: 26 August 2020; Revised: 16 March 2021; Accepted: 6 April 2021
Please cite this article as: Catalano F., Bianchi B., Berardi A., Leone A., Tamborrino A., 2021, Experimental Trials and Dynamical Simulation of
the Potential Biogas Production in a Frozen Food Industry, Chemical Engineering Transactions, 87, 295-300 DOI:10.3303/CET2187050
CHEMICAL ENGINEERING TRANSACTIONS
VOL. 87, 2021
A publication of
The Italian Association
of Chemical Engineering
Online at www.cetjournal.it
Guest Editors: Laura Piazza, Mauro Moresi, Francesco Donsì
Copyright © 2021, AIDIC Servizi S.r.l.
ISBN 978-88-95608-85-3; ISSN 2283-9216
Experimental Trials and Dynamical Simulation of the Potential
Biogas Production in a Frozen Food Industry
Filippo Catalanoa, Biagio Bianchib, Antonio Berardic, Alessandro Leoneb, Antonia
Tamborrinob,*
a Department of Biosciences and Territory, University of Molise, C.da Fonte Lappone – Pesche (IS), Italy
b Department of Agricultural and Environmental Science, University of Bari Aldo Moro, Via Amendola, 156/, Bari, Italy
c Dipartimento di Science Agrarie, Alimenti, Risorse Naturali e Ingegneria (DAFNE), Università degli Studi di Foggia, via
Napoli, 25 – 71122 Foggia – Italy
antonia.tamborrino@uniba.it
Food industry determines the production of huge quantities of by-products, solid and waste. Identifying an
ecological and economically viable solution for the management and disposal of horticultural wastes helps
reducing the environmental impact of this kind of industries. In this paper a biogas production potential was
obtained during one year of hourly data observation in a frozen food industry through dynamical simulation.
This provides useful data for the correct management of an anaerobic digestion plant using the horticultural
wastes coming from the production lines.The experimental analysis was carried out in an Italian cooperative
firm, that process and market canned foods and frozen foods. Material flows were analysed especially
considering the production of wastes. From the quantitative point of view, the hourly, daily, monthly, and
annual flows of the single by-products of the studied processing cycle were determined. A dynamical
simulation tool was developed to determine an optimized waste management procedure for biogas production.
Design criteria was obtained for a biomass treatment to recover the organic substance for biogas production.
1. Introduction
Anaerobic Digestion (AD) is a biological process that transforms organic matter into biogas in the absence of
oxygen, i.e. a mixture consisting mainly of methane and carbon dioxide (Fan et al., 2018). The methane
content varies between about 50 and 75%, depending on the type of starting organic substance and the
conditions in which the digestion process takes place (Gunaseelan, 2004).
In most biogas plants, various mixtures of raw materials are used simultaneously to stabilize the process and
optimize the production of biogas. This technique is called co-digestion.
The typical raw material for biogas plants can come from vegetables and/or animals (Mane et al., 2015):
• animal waste (manure, slurry, dung)
• agricultural residues and by-products
• organic waste from food and agri-food industries
• food residues from catering services
• sewage sludge from waste water treatment plants
• dedicated energy crops (e.g. corn, sugar beet, grass)
In particular, there are various food industries that produce high quantities of by-products suitable for AD,
especially horticultural wastes: in some cases, AD helps reducing the environmental impact of this kind of
industries (Scarlat et al., 2018).
In this paper the possible reuse of wastes from horticultural products, processed in a frozen food industry
located in Molise (Italy), was evaluated. Main aim is to show how, through dynamical simulation, it is possible
to overcome some problems, raised by the high variability of the waste feeding rate and materials potential,
when studying the feasibility of AD plant in this context. To this aim biogas production potential was obtained
during one year of hourly data observation in the studied industry through dynamical simulation (Perone et al.,
.2017; Catalano et al., 2020).
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2. Materials and Methods
In the studied food industry there are 3 production lines:
1) Leafy vegetables: spinach, chard, chicory and turnip greens (cubes, small plates or 2.5 kg bags)
2) Grilled and frozen zucchini, peppers, etc.
3) Minestrone: different types of vegetables are produced in rounds and cubes of various sizes (zucchini,
carrots, celery, cabbage, leeks, potatoes, broccoli, cauliflower, asparagus).
All these processes produce a great amount of by-products, requiring their disposal. One of the most
appropriate methods for the type of available by-products is that of anaerobic digestion aimed at the combined
production of heat and electricity for self-consumption in the firm.
The sizing of an anaerobic digestion plant aimed at producing biogas must be carried out by evaluating the
availability of biomass, whose chemical-physical characteristics change considerably according to the type of
available product. The determination of the biogas potential is made on the content of dry matter (total solids)
and on the content of organic matter (volatile solids). Moreover, the organic substance has a degradability
value that depends on its composition. For example, the protein, lipid and carbohydrate fractions are more or
less degradable and, for each family of organic compounds, a yield in biogas and methane can be estimated.
It follows that the biomasses must have a fairly uniform flow throughout the year and the digester must be
regularly fed with quantity and quality such as to respect the required hydraulic retention times, i.e. the number
of days that the family of organic compounds remains and are optimally degraded in the digester itself.
In the studied plant different types of horticultural products are frozen and the total amount processed for one
year is shown in Table 1. Methane (average) potential was recovered from different sources (BMU, 2012; Yan
et al., 2017; Li et al., 2013; Mane et al., 2015; Garcia et al., 2019).
Table 1: One-year production and waste, and biogas potential in terms of methane production
Product Raw materials
(kg)
Waste
(kg)
CH4 potential
(Nm3/kg)
CH4 production
(Nm3)
spinach 4,481,053 1,478,747 0.040 59,149
chard 1,506,317 406,705 0.040 16,268
turnip 236,826 71,048 0.040 2,841
broccoli 486,493 9,729 0.025 243
cauliflower 208,536 18,768 0.025 469
leek 119,473 2,389 0.025 59
curly endive 405,182 81,036 0.025 2,025
cabbage 128,876 10,567 0.025 264
zucchini 3,281,780 787,627 0.025 19,690
celery 98,510 1,970 0.010 19
potatoes 4,300,391 1,419,129 0.065 92,243
carrots 3,650,696 949,181 0.040 37,967
eggplant 580,405 139,297 0.025 3,482
TOTAL 19,484,538 5,376,193 - 234,719
A simple (static) analysis of these data leads to the wrong conclusion that the high amount waste useful for
AD is always and regularly available. This seems confirmed by a good methane production that can be
obtained from the waste, 234,719 Nm3 against an annual consumption of 1,188,000 Nm3, that is about the 20
% of the required gas. On the other hand, first of all we have to consider that there are about half of the
cultivars giving very few waste or small methane potential, such as turnip, broccoli, cauliflower, leek, curly
endive, cabbage, celery, and eggplant while the remaining cultivars allow to produce about the 96 % of the
total methane. Moreover, these last cultivars are unevenly distributed throughout the year: all these
considerations lead to the need of a more accurate analysis. This analysis was carried out calculating the
methane produced by a hypothetical AD plant with a weekly sampling, considering again the methane
potential shown in Table 1, through a dynamical analysis as outlined in Catalano et al., 2020. It was proposed
for the first time, and applied, in that case to overcome the problems find when selecting and dimensioning a
Combined Heat and Power (CHP) plant for the same industry.
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Figure 1: Scheme of the simulated waste treatment process. (blue blocks are existing processes, green blocks
are simulated processes)
To this aim the production scheduling was hourly acquired throughout next year, and the weekly methane
production was calculated simulating the presence of a tank to cumulate and equalize the waste flow rate. The
scheme of the simulated plant is shown in Figure 1. Each process uses mass balance equations as shown in
Catalano et al., 2020 (energy balance equations are not considered in this paper), and not repeated here for
the sake of brevity.
3. Results
Figures 2 and 3 show respectively the trend of the cumulative production (i.e. summing the wastes of all
cultivars for each observation interval) and the trend of the cumulative waste production. The result shown in
Figure 3 is from a simulation carried out with only the existing processes (blue blocks in Figure 1) so it
considers no equalization tank present in the plant.
Figure 2: Trend of the raw materials production rate for one year
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Figure 3: Trend of the waste production rate for one year
As regards raw materials even though we can highlight some variability in the production rate there are mainly
two periods characterized by different mean production rate: 60-70 (103 kg/h) during winter and spring, 150-
160 (103 kg/h) during summer and autumn. This variability could be easily addressed, but the great difference
in the yield of individual products leads to a much greater variability in the waste production rate (Figure 3).
In fact, it is clear the higher variability of the available waste especially during the period winter-spring. This
behaviour – high variability of raw materials and waste production rates - was already noticed in Catalano et
al. 2020 leading to develop a new modelling technique, that uses the dynamical simulation approach.
In the present case we have a similar problem, and the simulation was repeated considering the presence of
an equalization tank with a residence time of about one week as shown in the scheme in Figure 1. The result
is shown in Figure 4.
Figure 4: Simulated trend of the waste production for one year considering the use of an equalization tank
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The trend of biomass feeding the AD is much smoother than that of waste entering the equalization tank.
While it still changes more than required by a correctly operated AD process, the trend is slow enough (with a
cycle between 3 and 5 days) to allow including further biomass feeding the digestor, e.g. using the sludge
from the purification plant, or acquiring suitable biomass, e.g. manure from livestock farming, etc. This is even
more necessary as the specific methane potential varies with the processed cultivars leading to the trend of
weekly methane production shown in Figure 5.
Figure 5: Simulated weekly trend of the methane production considering the use of an equalization tank
We have to notice that the most efficiently processed wastes are mainly produced during summer and autumn
giving, on average, a higher methane production rate just during this period than in winter-spring.
4. Conclusions
In this paper a new modelling technique, based on the dynamical simulation approach, was used for the first
time to study the feasibility of a biogas production plant. This plant uses wastes produced processing raw
vegetables materials in a food freezing industry. The new approach, developed when selecting and
dimensioning a CHP plant, comes from the need of overcoming the problems raised by the high time
variability of the available waste amount and methane potential characteristics. In fact, it was shown that a
static analysis leads to wrong conclusions about the true available methane potential for the AD plant, while,
acquiring the waste production hourly, the variability can be dominated by introducing an equalization tank.
The trend of methane potential in the final configuration was calculated using the proposed approach and
suitable mass balance equations. This trend is smooth enough to give the chance of adding other biomass
materials, coming from other by-products of the firm and/or acquired from livestock farming, etc.
This analysis represents an aspect of strong innovation for the company as it allows to evaluate the possibility
of 'closing' the production cycle within the company itself through the direct recovery of by-products with
energy production. As final consideration just some economic aspects that will be deepened in another paper.
In any case, the economic evaluation must consider the production performance: process duration, biomass
conversion yields, electricity self-consumption, etc. must be estimated considering average values for 15
years and not only in the first years of plant operation, typically higher. In the business plan, manpower,
insurance, plant maintenance and extraordinary investments must be considered over the years to keep the
plant efficient.
Acknowledgments
The authors have contributed to the same extent to the present study.
3
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