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Ecological intensification by integrating biogas production into nutrient cycling: Modeling the case of Agroecological Symbiosis


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There is growing demand to produce both food and renewable energy in a sustainable manner, while avoiding competition between food and energy production. In our study, we investigated the potential of harnessing biogas production into nutrient recycling in an integrated system of organic food production and food processing. We used the case of Agroecological Symbiosis (AES) at Palopuro, which is a combination of three farms, a biogas plant, and a bakery, as a case to explore how biogas production using feedstocks from the farms can be used to improve nutrient cycling, and to calculate how much energy could be produced from the within-system feedstocks. The current system (CS) used in organic farms, and the integrated farm and food processing AES system, were analyzed using Substance Flow analysis. In the AES, annual nitrogen (N) and phosphorus (P) surpluses were projected to be reduced from 95 kg ha−1 to 36 kg ha−1 and from 3.4 kg ha−1 to −0.5 kg ha−1 respectively, compared to the CS. Biogas produced from green manure leys as the major feedstock, produced 2809 MWh a−1. This was 70% more than the energy consumed (1650 MWh a−1) in the systemand thus the AES system turned out to be a net energy producer. Results demonstrated the potential of biogas production to enhance the transition to bioenergy, nutrient recycling, and crop productivity in renewable localized farming and food systems.
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Agricultural Systems
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Ecological intensification by integrating biogas production into nutrient
cycling: Modeling the case of Agroecological Symbiosis
Kari Koppelmäki
, Tuure Parviainen
, Elina Virkkunen
, Erika Winquist
, Rogier P.O. Schulte
Juha Helenius
Agroecology, Department of Agricultural Sciences, University of Helsinki, P.O. Box 27, FI-00014, Finland
The Farming Systems Ecology, Wageningen University & Research, PO Box 430, Wageningen, AK 6700, The Netherlands
Natural Resources Institute Finland, Kirkkoahontie 115 D, Linnantaus 87910, Finland
Natural Resources Institute Finland, Vuorimiehentie 2, Espoo 02150, Finland
Biological nitrogen fixation
Localized agrifood system
Nutrient losses
Organic farming
Renewable energy
Sustainable intensification
There is growing demand to produce both food and renewable energy in a sustainable manner, while avoiding
competition between food and energy production. In our study, we investigated the potential of harnessing
biogas production into nutrient recycling in an integrated system of organic food production and food proces-
sing. We used the case of Agroecological Symbiosis (AES) at Palopuro, which is a combination of three farms, a
biogas plant, and a bakery, as a case to explore how biogas production using feedstocks from the farms can be
used to improve nutrient cycling, and to calculate how much energy could be produced from the within-system
feedstocks. The current system (CS) used in organic farms, and the integrated farm and food processing AES
system, were analyzed using Substance Flow analysis. In the AES, annual nitrogen (N) and phosphorus (P)
surpluses were projected to be reduced from 95 kg ha
to 36 kg ha
and from 3.4 kg ha
to −0.5 kg ha
respectively, compared to the CS. Biogas produced from green manure leys as the major feedstock, produced
2809 MWh a
. This was 70% more than the energy consumed (1650 MWh a
) in the systemand thus the AES
system turned out to be a net energy producer. Results demonstrated the potential of biogas production to
enhance the transition to bioenergy, nutrient recycling, and crop productivity in renewable localized farming
and food systems.
1. Introduction
There is a growing demand for ecological intensification in food
production. Food must be produced in greater quantities and agri-
culture is concurrently expected to supply other ecosystem services
(Schulte et al., 2014;Tittonell, 2014). Furthermore, there is now dual
pressure to produce renewable energy and meet European Union tar-
gets (European Commission, 2014), and to recycle nutrients (European
Commission, 2015). At present, agriculture and the food system as a
whole, are de-localized and highly dependent on fossil fuels and mi-
neral fertilizers as net inputs. This has caused many negative environ-
mental impacts (Whatmore, 1995;Kummu et al., 2012;IPES-Food,
2016). Sustainably produced biomasses are proposed to have significant
potential to replace fossil fuels and facilitate the transition to the pro-
duction of renewable energy in a circular economy (Haas et al., 2015).
One challenge across the Global North is that farms have specialized
into either livestock or crop farms, fertilizer use has intensified, and
spatial separation of crop and livestock production systems has in-
creased. This situation works against the objective of recycling plant
nutrients (Buckwell and Nadeu, 2016), and has led to a lack of manure
for use in crop farms located in areas without livestock. In response,
most farms have relied on mineral fertilizers. Contrastingly, organic
crop farms have had to rely on green manure or commercial organic
fertilizers. A lack of leys in stockless conventional farms and a lack of
opportunities to spread manure or other organic fertilizers has resulted
in negative environmental impacts, such as diminishing soil carbon
contents and substantial nutrient excesses, in the areas with spatial
separation of crop and livestock production (Uusitalo et al., 2007;
Heikkinen et al., 2013;Maillard and Angers, 2014).
The challenge arising from the spatial separation of animal pro-
duction and crop production is even more apparent on organic farms,
because they have to rely on green manure leys instead of using mineral
fertilizers. In green manuring, the timing of N mineralization does not
meet with the peak demand of the crop plants (Berry et al., 2002). Also,
Received 16 May 2018; Received in revised form 19 December 2018; Accepted 19 December 2018
Corresponding author at: Agroecology, Department of Agricultural Sciences, University of Helsinki, P.O. Box 27, FI-00014, Finland
E-mail address: (K. Koppelmäki).
Agricultural Systems 170 (2019) 39–48
Available online 28 December 2018
0308-521X/ © 2018 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license
the common practise in Nordic conditions of terminating green manure
leys by ploughing them in late autumn creates risks for losses of N and
other nutrients from the green manure as the nutrients are released
from the decomposing biomass too early (Uusi-Kämppä and Jauhiainen,
2010). For these reasons there is a need to develop alternative strategies
to increase N use efficiency in stockless organic farming (Berry et al.,
2002;Möller, 2009;Borgen et al., 2012).
These challenges and opportunities have created a need for finding
new ways to integrate food production and renewable energy produc-
tion in a sustainable manner. One approach is to use green manuring
leys, that are not competing with food production, for combined energy
and organic fertilizer production.
Stinner et al. (2008),Tuomisto and Helenius (2008),Siegmeier et al.
(2015), and Blumenstein et al. (2018) all suggest the use of green
manure leys as a feedstock in biogas production in organic farming. As
an added benefit, nutrients can be more efficiently reallocated in time
and space if these leys are harvested for digestion in biogas plants,
instead of tilled in the soil. This increases nutrient use efficiency and
returns higher yields, thereby potentially increasing productivity in the
farming system (Möller, 2009;Möller and Müller, 2012).
A further innovation was described by Koppelmäki et al. (2016).
They proposed Agroecological Symbiosis (AES); as a food system ap-
plication of the more generic idea of industrial symbiosis (Chertow,
2000), to further enhance nutrient recycling and to make full use of the
bioenergy produced within the system. AES is a food production and
processing symbiosis of farms and food processors. In addition, as a
localized food system model, AES is expected to have cultural and
socio-economic benefits (Koppelmäki et al., 2016), which are not dealt
with in this article. The first AES is actively forming in the village of
Palopuro in southern Finland. In this AES, a dry-digestion biogas unit
produces energy from green manure leys together with manure.
However, the knowledge gap regarding potential trade-offs between
energy gains and changes in food production, nutrient cycles and
among other soil functions remains. There is a need to ensure that the
production system is optimized to minimize trade-offs and maximize
synergies between food and energy production.
In our study, we explore how agricultural biomasses that are not
competing with food production can be utilized in producing renewable
energy and enhancing nutrient recycling in food production and pro-
cessing in an AES context. The aim of our paper is to explore the po-
tential of closing nutrient loops and increasing energy self-sufficiency in
food production through AES. We use Palopuro AES as a case and carry
out an ex-ante assessment of a biophysical system in terms of (1)
agricultural and food products produced and sold, (2) nutrients pro-
duced within, imported to, and exported from, (3) energy requirements,
energy sources, and salable energy of the AES.
2. Materials and methods
2.1. Case description
In this study, we used Palopuro Agroecological Symbiosis (http:// as the pilot case of an energy-
positive, circular food production system. Palopuro AES is located in
Southern Finland, approximately 50 km north of Helsinki, in the village
of Palopuro near the town of Hyvinkää (60°37′50″N, 024°51′35″E).
Palopuro AES consists of the following operations: an organic cereal
farm, an organic vegetable farm, an organic hennery, a bakery, and a
biogas plant (Fig. 1). An investment decision to build a biogas plant was
made at the time of the study. From the beginning, the bakery has
participated in planning the AES and formulating a construction plan,
but the investment had not yet been realized at the time of our study.
Hence, our study comprises of an ex-ante assessment of the AES system,
as compared to the current system (CS). A full description of the Pa-
lopuro AES can be found in the Supplementary Material (S1).
The biogas plant serves as the heart of energy production and
nutrient flows (Fig. 1). By far, silage from green manure leys of the
farms will be the most important feedstock for the plant, representing
71% of the total feedstock quantity. The use of grass biomass as a
feedstock in biogas production follows the ideas previously presented
by Möller et al. (2008),Stinner et al. (2008), and Tuomisto and
Helenius (2008). Other feedstocks include chicken manure from the
hennery and manure from horse stables. Unlike the other feedstocks,
horse manure is not recycled within, but imported to the AES from
stables located nearby. Receiving horse manure is a service provided by
the AES to small horse stables in the neighbourhood, as these often do
not have their own fields for manure spreading.
Through the anaerobic digestion of the biomasses, recycled within
the AES alone, the AES becomes a net energy producer (Koppelmäki
et al., 2016). The biogas can be directly used by the AES in on-farm
processes, such as grain drying, and as fuel for the ovens in the bakery.
The rest of the biogas will be upgraded to biomethane for use as fuel for
the needs of the AES itself, and for sale at a gas station to be built next
to the plant.
The nutrient-rich digestate will be used as organic fertilizer on the
farm fields. The majority of the fields at Palopuro AES have been
managed under organic certification since 2010. Currently, the crop
rotations follow commonly used practices of stockless organic farms in
southern Finland. A five-year crop rotation consists of two years of
perennial green manure leys, followed by autumn- or spring-sown
cereals, then a pulse crop and, finally, spring-sown cereal with under-
sown grass seeds to establish the subsequent green manure leys. N
fertilization relies on the green manure leys and commercial organic
fertilizers are used in part of the fields. Horse manure is used as a soil
conditioner. In an operating AES, the green manure leys are replaced by
dual-purpose leys: this serves as the biological N input into the system,
but also converts green manuring leys into mobile organic fertilizers.
2.2. Food production and nutrient flow analyses
In this study, we modeled a current scenario (CS), which represents
the typical organic farming system based on current agricultural ac-
tivities of the farms participating in Palopuro AES. This scenario was
compared to the AES Scenario (AES), the functions of which were de-
signed in the completed research and development (R&D) project
(Helenius et al., 2017). The farm's arable land and hennery were sys-
tems boundaries for the CS. Arable land also included the vegetable
farm's fields, which consisted of one ha of vegetables and two ha of
green manure leys. For the AES model, boundaries were the symbiosis'
farm fields and operations including the biogas plant, which will begin
operating in autumn 2018, and the bakery, which is in the planning
stage (Fig. 1).
N and P flows were calculated, and a comparison was made between
CS and AES. Nutrient flows were illustrated using STAN 2.5.1302
substance flow analysis software. The data for arable land were com-
piled from cultivation notes (available arable land and fertilization use)
taken at farms of the Palopuro AES and from the literature. Energy use
and grain consumption data for the bakery were compiled from
Samsara Ltd., which has made plans to move its operations to become
part of Palopuro AES. The biogas plant operations were designed based
on the results of the R&D project, which was conducted in 2015–2017
(Helenius et al., 2017), and on results reported from biogas literature.
For the CS, the area of green manure leys followed the common
practices of organic crop farms in the region, which meant that 40% of
the crop rotation was allocated to green manuring. For the AES, the
area of green manure leys was set to meet the demand of the biogas
plant together with the other fallows, which were not included in the
crop rotation. Crop rotation was optimized to the demands of the AES
framework, as applied to Palopuro AES. This means that, in addition to
supplying enough feed for the henhouse, the fields should also produce
enough baking-quality grain for the bakery and enough feed in the form
of silage for the biogas plant.
K. Koppelmäki et al. Agricultural Systems 170 (2019) 39–48
The area of other fallows, nature management fields, and buffer
zones was set to be the same as in the farm's current crop rotation,
comprising approximately 8% of the total farm area. In the AES model,
the biomass harvested from buffer zones was used for biogas produc-
tion. In the CS model, the grass cut from the buffer zones was not used
for agricultural purposes. In the AES model, the use of harvest from the
buffer zones added 0.5% to the N and 0.6% to the P flows. In addition, a
part of the nature management fields was harvested to meet the de-
mand for grass biomass in biogas production. Nature management
fields and buffer zones are both common agricultural land uses in
Finland covering approximately 9% of the total agricultural land area in
the study region during 2017 (Natural Resources Institute Finland,
2018a). This is because they are subsidized by the agri-environmental
support system. According to regulations, harvest biomass from these
fields is allowed (Ministry of Agriculture and Forestry, 2014).
The total farmland was 385 ha in both scenarios, but allocations to
the various crops and land uses varied (Table 1). The crop yields
(Table 1) were average organic crop yields in the region (CS) (Natural
Resources Institute Finland, 2018a) or adjusted (AES) as follows: in the
AES model, biomass from the green manure leys is harvested for
anaerobic digestion in the biogas plant. The digestate is recycled to non-
leguminous crops. Based on published research (Möller et al., 2008;
Stinner et al., 2008;Möller and Müller, 2012), the digestate had
10–28% better fertilizer value in terms of crop response than the same
biomass used as green manure. An added benefit is that, while green
manure is used in the same field parcel in which it was grown, recycling
in the form of digestate allows for re-allocation of nutrients based on
optimization between the parcels.
To estimate the achievable yield increases resulting from the ad-
vantages described earlier, we calculated how much readily available
soluble N (nitrite NO
, nitrate NO
, and ammonium NH
) for
plants the digestate from biogas production would include. This was
based on the nutrient value of the feeds used. After that, we assumed
that the soluble N in the digestate would be used to fertilize non-le-
guminous crops in the crop rotation, thus increasing yields. Based on
these calculations, we estimated that 30 kg of soluble N ha
(total N
150 kg ha
), available for non-leguminous crops in the AES model,
increased cereal yields by 40%, compared to the traditional organic
farming practice in CS. The 40% yield increase is factored in the
modeling. This is based on N-rate yield response modeling by Valkama
et al. (2013). This model was a meta-regression with both Mitscherlich-
type exponential and quadratic fit. It was based on various Finnish N
fertilizer experiments for low-yielding spring cereals in 1940–2014 at
17 sites in Finland. The nutrient content of the digestate (Table 2) was
derived from the nutrient contents of the feedstocks used multiplied by
a solubility factor of 1.2 (Möller and Müller, 2012) to obtain the defi-
nitive soluble N value for the digestate. Grass biomass value was based
on average values for silage obtained from National Feed tables
(Natural Resources Institute Finland, 2018b). The value for horse
manure was based on results from Luostarinen et al. (2017). The N
content of the hen manure was taken from Luostarinen et al. (2017).
Because of gaseous N losses from the manure, N content could not be
calculated from the input-output balance. P content of the hen manure
was calculated from the input-output balance by subtracting the P
content of the produced eggs and the disposed hens from all the P in-
puts to the hennery. Other parameters and explanations for nutrient
flow analyses are given in Table 3.
2.3. Energy consumption and production
Data on energy use were collected from the farms and, for the biogas
production and the bakery in the AES model, we used data collected in
the R&D project, where the functions of symbiosis were planned
(Helenius et al., 2017). The energy consumption data included the
Fig. 1. System boundaries of the modeled case as (a) the current system and (b) as a system converted to agroecological symbiosis (AES). The AES adds not just a
biogas plant, but also a food processing unit to the system.
Table 1
Field use and yields
in the CS and AES models.
Field use Area
(ha) CS
(ha) AES
kg ha
Yield kg ha
in AES
Rye 40 40 1900 2660
Oat 42 32 2100 2940
Barley 25 25 2300 3220
Wheat 35 70 2000 2800
Pea 20 20 1800 1800
Pea-oat intercrop 51 57 2100 2100
Green manure leys 142 111 20,000 20,000
Nature management fields 20 20 15,000 15,000
Buffer zones (not in crop
9 9 10,000 10,000
Vegetables 1 1 12,000 12,000
Total area 385 385
The crop yields in the CS model are based on average organic crop yields in
the region (Natural Resources Institute Finland, 2018a) while the higher yield is
factored in the AES model.
K. Koppelmäki et al. Agricultural Systems 170 (2019) 39–48
electricity and heating needed for agricultural operations, the energy
needed for bread baking in the bakery, fuels for the machinery, and the
biogas plant's own energy consumption. All the energy consumption
data are expressed in Megawatt hours (MWh). The energy production
data consisted of the biogas production described earlier. The bio-
methane potential (BMP) of the various biomasses was derived from the
literature and is expressed as normal cubic meters (Nm
). The BMP
value for silage, 298 Nm
total solids, was based on values
(229–353 Nm
for various herbaceous grasses) reported by
Seppälä et al. (2009) and the values (292–320 Nm
) reported
by Wahid et al. (2015) for grass-clover mixtures. We determined the
BMP for horse manure as 120 Nm
total solids based on va-
lues (88–196 Nm
) reported by Mönch-Tegeder et al. (2013)
and we used the value 324 Nm
total solids for chicken
manure, based on results by Kafle and Chen (2016). We assumed that
the whole biomethane potential was realized over a digestion time of
three months.
2.4. Uncertainties and sensitivity analysis
The uncertainty of various factors was determined by classifying
them into three different uncertainty levels (10, 20, and 30%)
(Supplementary Table 1). The classification was based on ranges used
by Antikainen et al. (2005). To account for the variability in flows
depending on management decisions and the availability of, for ex-
ample, horse manure imported from neighboring farms, we relied on
personal communication with the operators of Palopuro AES. After
assigning uncertainty levels to each factor, data reconciliation was
performed using the STAN data calculation tool for uncertainty re-
conciliation (Cencic and Rechberger, 2008).
The sensitivity of results of the models' outputs to variation to input
parameters was tested by changing the parameter values one-by-one
Table 2
Nutrient content, biomethane production, and the quantities of feeds used in
biogas production. The nutrient values are based on average values in the
National feed tables (Natural Resources Institute Finland, 2018b) and bio-
methane production (CH
) is calculated based on biomethane po-
tential values reported by Seppälä et al. (2009),Wahid et al. (2015),Mönch-
Tegeder et al. (2013), and Kafle and Chen (2016).
Silage Horse
Feed FM tn a
2450 800 185 3435 2804
DM % 0.32 0.30 0.31 0.31 0.29
Feed DM tn a
823 270 57 1150 813
TN kg tn
FM 7.0 3.4 14.02 6.8 8.4
TN tn a
18.1 2.7 2.59 23.5 23.5
SN kg tn
FM 1.1 0.5 3.47 1.1 1.6
SN tn a
2.7 0.4 0.6 3.7 4.5
TP kg tn
FM 0.7 0.8 6.3 1.0 1.0
TP kg a
1.8 0.6 1.2 3.6 3.6
233,632 28,800 18,508 280,940
Explanations: dry matter (DM), fresh matter (FM), Total nitrogen (TN), Soluble
nitrogen (SN), Total phosphorous (TP).
To determine the digestate's soluble nitrogen content, we used a solubility
factor of 1.2 based on the review study by Möller and Müller (2012).
Table 3
Explanation of nutrient flows.
Flow number Flow Explanation Reference
1 Nitrogen
Nitrogen deposition to the arable land of AES. Derived from the nitrogen deposition
to the area of the Hyvinkää municipality in 2016.
SYKE, 2018
2 Nitrogen fixation Biological nitrogen fixation (BNF) according to a formula described by Anglade
et al., 2015. The values used for BNF were: Green manure leys 222 kg ha
20,000 tn a
FM*), Nature management fields 183 kg ha
(Yield 15,000 tn a
FM), Peas 71 kg ha
(yield 1800 kg ha
), and pea-oat intercrop 25 kg ha
yield 525 kg ha
Anglade et al. (2015)
3 Digestate Combined nutrient content of feeds (Table 2) subtracted from the estimated nitrogen
loss during storage (6%).
Paavola and Rintala (2008)
4 Crop sales Cropping area multiplied by average organic crop yields in region multiplied by
yield increase 40% for digestate-fertilized crops (explained in the text). Nitrogen and
phosphorus content of the crops based on the literature.
Natural Resources Institute Finland (2018a)
5 Green manure
Harvested silage to biogas production. Silage nutrient content was based on the
nutrient value of late-harvested red-clover/timothy silage.
Natural Resources Institute Finland (2018b)
6 Flour Demand for the bakery (personal communication). Nitrogen and phosphorus content
based on the literature.
Personal communication with Zukale, P. (2016) and
Antikainen et al. (2005)
7 Feed Demand for the hennery (personal communication). Nitrogen and phosphorus
content based on the literature.
Personal communication with Latostenmaa V. (2017)
and Natural Resources Institute Finland (2018b)
8 Bread Same as flow 6.
9 Horse manure Feedstock to the biogas plant as an input to the system. Nutrient content based on
the literature.
Luostarinen et al. (2017)
10 Organice
Organic fertilizers utilized on the farms in the CS model. Cultivation notes
11 Chicken manure Manure produced by the hennery. Nitrogen content based on the literature and
phosphorus content calculated by subtracting the phosphorus content of the
produced eggs and the disposed hens from all the phosphorus inputs to the hennery.
Luostarinen et al. (2017)
12 Chicken feed The quantity of concentrate used in the hennery. Nutrient values were obtained from
the concentrate manufacturer.
Personal communication with Latostenmaa V. (2017)
and Hemmilä T. (2017)
13 Ready-to-lay
Ready-to-lay hens into the henhouse Anal. Methods (2014)
14 Eggs Average egg production per chicken per year multiplied by the number of hens in the
hennery (5600)
Aro (1998)
15 Hens Hens out Anal. Methods (2014)
16 Losses Nitrogen leaching and gaseous losses from the arable land were calculated by
subtracting outputs (flows 4 and 7) from inputs (flows 1,2,9,10). Phosphorus losses
due to erosion and leaching were based on the literature
Tattari et al. (2017)
17 Losses Nitrogen losses from the biogas production to be 6% during storage Paavola and Rintala (2008)
18 Losses Nitrogen losses from the hennery = Inputs Outputs
* FM = Fresh matter.
K. Koppelmäki et al. Agricultural Systems 170 (2019) 39–48
while keeping other variables equal. After this we reran the calculation.
To observe the sensitivity of the calculated nutrient surpluses from
arable land, we changed the original values within the uncertainty
ranges. To observe the sensitivity of energy production, we changed the
feed dry matter (DM) content ± 10%, and to observe BMP sensitivity,
we used the minimum and maximum value ranges from the literature,
as explained earlier.
3. Results
3.1. Nutrient flows
Compared to CS, circulating the grass biomass and manure through
the biogas plant in the AES increased the mobile N input to the arable
land, which resulted in increased crop production and reduced nutrient
losses from the system (Table 4). Nitrogen and P surpluses were reduced
by 36 kg ha
(1–70 kg ha
) and 3.9 kg ha
(2.8–5.1 kg ha
), re-
spectively, compared to CS. Also, the smaller area for green manure leys
reduced the biological nitrogen fixation (BNF) resulting in smaller N
By far, the most substantial N input to both systems was BNF from
the atmosphere (Fig. 2). In the AES model, BNF was 30% smaller than
in the CS model. The BNF quantity resulted in the greatest uncertainty
in N surplus (Table 5). The most substantial P input was derived from
the hennery (Fig. 3). This was due to net imports of chicken feed con-
centrate, as the exported eggs only contained 21% of the P imported in
the feeds. Also, horse manure contributed a substantial quantity of P to
the system, resulting in 43% of the total P imports. In the CS model, the
majority of P was imported in the form of organic fertilizers (Table 4),
which were no longer used in the AES model. In both models, crop sales
formed the largest N and P exports.
3.2. Energy production
The AES produced 2809 MWh gross energy from the green manure
leys, fallows, and manures (Table 6). Silage harvest from the bioenergy-
green manure leys was the most important feedstock to biogas produc-
tion. This produced approximately 83% of the total energy while con-
tributing only 71% to the total quantity of feedstock materials used in
biogas production. The share of horse manure in the feedstock was 23%,
but its contribution to produced energy was only 10%. The operations of
the AES consumed ca. 59% of the quantity of produced energy.
Energy production from the biogas plant was very sensitive to feed-
stock quality (Table 7). Energy produced was increased when the horse
manure was replaced by silage with a higher biomethane potential.
4. Discussion
Our study showed that biogas production based on utilizing bio-
masses available within the farming system has the potential to increase
primary production in farming, reduce nutrient losses, and produce
renewable energy in excess while enhancing nutrient recycling.
4.1. Increased nutrient use efficiency
Reduced N and P surpluses and increased nutrient use efficiency
were consequences of increased crop production from arable land,
which led to greater outputs from the system. In the AES model, the
biogas plant plays a key role in nutrient recycling and in increased
system-level plant nutrient use efficiency by allowing for spatial and
temporal nutrient re-allocation in the crop rotation without importing
new nutrient inputs from outside of the system.
The projected cereal yield increase was 40% for the AES model
compared to average yields on organic farms without livestock in
Southern Finland. The digestate from biogas production enabled an
increased quantity of soluble N to be available for crops in spring, thus
enhancing crop growth. The positive effect on cereal yields attained by
using digestate as a fertilizer is supported by findings from other stu-
dies, though the reported effects have been smaller; 10% by Stinner
et al. (2008) and 14% by Brozyna et al. (2013). Farmers have reported a
20–25% yield increase and increased protein content for cereals in a
survey conducted in Germany (Blumenstein et al., 2015). In the AES
model, the assumption of a yield increase was based on modeling re-
sults from metadata by Valkama et al. (2013): these indicated sub-
stantial yield responses when original yields were low, as is the case in
stockless organic farming in Finland. Similar yield responses (37–38%)
were achieved in a study by Blumenstein et al. (2018), where the im-
pact of integrated biogas production was modeled on yields in stockless
organic farming. However, the 40% yield increase presents the poten-
tial achievable yield increase in situations when no other factors, such
as unfavourable weather conditions or weed competition, limit the
yield response. We used the ± 20% sensitivity range for the yield re-
sponse to the digestate to account for situations where agricultural
yields vary depending on many factors not included in the modeling.
In both the AES and CS, nutrient imports into the system were
equivalent with the exception of BNF, which was substantially influ-
enced by the reduced field area needed for green manuring due to
enhanced nutrient use efficiency. As a result, the nitrogen surplus was
reduced by 38% in the AES model compared to CS. This reduction was
further augmented by increased crop yields per hectare and per system.
Nitrogen losses were reduced, but further specification of these N losses
to air or water was not included in this study. Dahlin et al. (2011)
compared how harvesting the green manure vs. mulching affects N
recycling in field experiments. They suggested that harvesting the green
manure leys' biomass is likely to reduce both gaseous losses to the at-
mosphere and nutrient leaching compared to conventional mulching
where grass mulch is left on the ground.
In our study, we assumed that BNFs from green manure leys were
equal in both models. However, biomass harvesting can result in in-
creased BNF. Hatch et al. (2007) found that clover leys increased BNF
Table 4
Nitrogen and phosphorous balances and nutrient use efficiency (Beatty et al., 2016) for arable land in the CS and AES models. Uncertainty range in parentheses. Units
are in elemental nutrients kg
Input 118 ( ± 24.3) 136 ( ± 23.9) 7.1 ( ± 1.0) 8.9 ( ± 0.8)
BNF 96 ( ± 20.2) 77 ( ± 14.3)
Manure/organic fertilizers/ 18 ( ± 3.0) 7.1 ( ± 1.0)
Digestate 55 ( ± 8.6) 8.9 ( ± 0.8)
Nitrogen deposition 3 ( ± 1.0) 3 ( ± 1.0)
Output 23 ( ± 2.9) 76 ( ± 10.2) 3.7 ( ± 0.7) 9.4 ( ± 1.3)
Surplus 95 ( ± 20.2) 59 ( ± 14.2) 3.4 ( ± 1.4) −0.5 ( ± 0.2)
Nutrient use efficiency 0.2 0.24 0.52 0.58
Surplus kg tn
harvest 89 44 3.20 −0.40
K. Koppelmäki et al. Agricultural Systems 170 (2019) 39–48
by 9–61 kg ha
compared to treatments where clover was mulched
and left on the ground. Stinner et al. (2008) reported that reduced soil
N availability was compensated for by enhanced BNF, resulting in equal
pea yields. However, biomass harvest has not always enhanced BNF, as
Dahlin and Stenberg (2010) have reported. According to Dahlin et al.
(2011), only 14% of the N from the aboveground biomass is recycled
back into grass growth when used as green manure.
In the AES model, the P balance was slightly negative (−0.5 kg P
), whereas a surplus of 3.4 kg P ha
in the CS was near the
average balance of 4 kg P ha
in Finland (OECD, 2018). As with N, this
caused by larger yields in the AES model, which resulted in increased P
exports from the system. Phosphorus exported out of the system, in-
cluding erosion, was replaced by imports in the form of horse manure
and concentrate feed for hens (Fig.3).
In our study, the hennery contributed 34% (CS) and 57% (AES) of
total P imports to the system, in the form of feed concentrate, but only
14% (CS) and 10% (AES) of the total P exports, in the form of eggs.
Most of the P in the chicken feed is excreted in the manure. This results
Fig. 2. Nitrogen flows (tn a
) in the AES and CS models. The width of the arrow is proportional to the flow rate. Blue arrows illustrate imports into and exports out
of the system, red arrows illustrate the losses from the system, and black arrows are flows within the system. Explanations of the flows are provided in Table 3. (For
interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
K. Koppelmäki et al. Agricultural Systems 170 (2019) 39–48
in a potential risk for P accumulation in soils where manure is used
continuously. Such an outcome was reported in Finland by Uusitalo
et al. (2007), who observed greater P balances resulting in increased P
contents in the soils of livestock farms compared to arable crop farms.
In light of the slightly negative P balance in the AES model, imports
are needed to compensate for the exports to maintain soil fertility. As an
Table 5
Sensitivity to change in model parameters to the model outcomes of nitrogen and phosphorous surpluses.
Sensitivity scenario Nitrogen surplus CS Nitrogen surplus AES Phosphorus surplus CS Phosphorus surplus AES
kg ha
kg ha
kg ha
kg ha
Green manure ley biomass +20% 16.0 12.5
Green manure ley biomass −20% −16.0 −12.5
Crop yields (cereals) +20% −2.7 −2.0 −0.5 −0.4
Crop yields (cereals) −20% 2.7 2.0 0.5 0.4
Fig. 3. Phosphorus flows (tn a
) in the AES and CS models. The width of the arrow is proportional to the flow rate. Green arrows illustrate imports into and exports
out of the system, red arrows illustrate the losses from the system, and black arrows are flows within the system. Explanations of the flows are given in Table 3. (For
interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
K. Koppelmäki et al. Agricultural Systems 170 (2019) 39–48
outcome of decades of mineral fertilization at rates exceeding plant
uptake, current P levels in Finnish farmland soils are high and yield
losses are not expected in short term, even if negative P balances are
maintained (Ylivainio et al., 2014).
The AES is not a fully closed system, because certain nutrients are
imported into and certain nutrients are exported out of the system in
the form of crop sales. Nitrogen required in crop production can be
supplied by BNF, but with P the interpretation of a desirable level of
self-sufficiency depends on the intrinsic or historic soil P level.
4.2. From energy consumer to energy producer
The AES model converted the studied production system from an
energy consumer to a net energy producer by taking advantage of
available biomasses within the system that were not used in food pro-
duction. Seventy percent more biogas was produced than was con-
sumed in total by the farm operations, bakery, and biogas plant (plant's
own energy needs).
In the AES model, biomasses from within the system boundaries,
which included the green manure leys and chicken manure, produced
energy equal to 7.29 MWh ha
in the AES field area. The biomethane
potential of horse manure is substantially lower than that of silage and
chicken manure (Seppälä et al., 2009;Mönch-Tegeder et al., 2013;
Wahid et al., 2015;Kafle and Chen, 2016). In terms of energy pro-
duction, horse manure was not an important feedstock and could be
replaced by crop residues such a straw. However, horse farms often lack
fields for manure spreading, which means they may be willing to pay
biogas companies for manure management.
4.3. Sensitivity analyses
Results were sensitive to certain input factors in both models.
Changes in grass biomass produced ha
substantially affected N
balances as the formula for calculating BNF was based on the quantity
of biomass produced. Biogas production was most sensitive to the
quality of green manure leys, which were used as feedstock in biogas
4.4. Applicability and limitations of the study
Our study explored how integrating biogas production into a cereal
production system affected nutrient flows and energy self-sufficiency in
an integrated system of organic farming and food processing. Our study
focused on one AES case located in southern Finland. The results con-
firm previous findings that nutrient recycling from green manuring
through a biogas plant is productive in stockless organic farming. The
introduction of dry biogas production into a stockless organic crop
rotation therefore allows for the arable area allocated to green man-
uring crops to be reduced, which further negates undue competition
between fuel and food competition.
The case study further demonstrates that food production and pro-
cessing can be made energy-positive through its own bioenergy, with a
dramatic climate change mitigation benefit through the replacement of
fossil energy. This requires re-localizing to the scale required for AES.
The results cannot be directly applied to other AES, as the concept re-
quires situated system designs.
The green manure leys in the AES model have an important func-
tion: their purpose is even more multi-functional than typical in organic
crop farming. On organic farms, green manure leys are traditionally
used for BNF, soil conditioning, and weed suppression. In the AES
model, the leys maintain these functions while also serving as feedstock
for biogas production and for the production of recyclable digestate,
allowing for more efficient use of BNF and nutrient reallocation within
the system to better meet crop nutrient demand.
Based on the results of our study, net energy production is sig-
nificant in areas not used in food production. If the fallows available in
all of Finland were farmed for biogas feedstock with the same pro-
ductivity as in this study, they would produce over 4 TWh a
of en-
ergy. As a comparison, the motor fuel oil consumption in Finland's
agriculture and horticulture sector was 2.45 TWh a
in 2016 (Official
Statistics of Finland, 2016).
In Finland, the proportion of perennial green manure leys is larger
than in organic crop farms in other Northern European countries or in
Central Europe. In terms of energy production, this makes the im-
plementation of the AES system described in this study specifically re-
levant to Finland, and more challenging in these other areas.
The results are applicable in stockless organic crop farms. However,
both organic and conventional farms typically have fallow land in ad-
dition to cash crops or rotational green manure leys. This is a typical
situation in Finland, where 11% of agricultural land was fallows in
2017 (Natural Resources Institute Finland, 2018a), creating a sub-
stantial potential resource for biogas production. However, yield in-
creases as described in our study would not apply to conventional
systems, as there, the digestate would be replacing mineral fertilizers.
This would require re-parameterization of our model for non-organic
4.5. Further research questions
The feasibility of the AES mode-of-action needs to be studied for a
range of food products in variable production conditions at various
spatial and organizational scales. In addition to food and energy pro-
duction and nutrient recycling, impacts on soil functions, such soil
carbon content, on greenhouse gas emissions, and on biodiversity
should also be studied at the farm level and at a regional scale.
In our case study, the integration of food processing and primary
production at the farm did not influence nutrient flows, because there
were no losses from the bread-baking process. Other types of food
processing, such as dairy processing, meat processing, or vegetable
Table 6
Gross energy production and consumption in the AES model.
Energy produced, and current energy use
MWh a
Produced energy 2809
Silage 2336
Horse manure 288
Chicken manure 185
Consumed gross energy
Biogas plant 390
Cereal farm 625
Machinery 250
Grain drying 250
Electricity 125
Hennery 275
Vegetable farm 10
Bakery 350
Energy surplus 1159
Consumed electricity was converted to needed primary energy using a
factor of 0.4 (Boyce, 2001)
Table 7
The effect of increasing and decreasing various parameters in the energy
production. Silage biomethane potential min. and max. Values described ear-
MWh a
Silage DM content +10% 234
Silage DM content - 10% −234
Silage biomethane potential max. value 432
Silage biomethane potential min. value −541
Replacing 300 tn of horse manure by silage 179
K. Koppelmäki et al. Agricultural Systems 170 (2019) 39–48
cleaning and peeling processes, could potentially provide additional
waste biomasses that could be utilized in energy production and sub-
sequently recycled back into food production. However, it is notable
that with a redesign for AES, a bread system can be converted from an
energy consumer to an energy producer, from primary production to
In more intensive farming systems, the risk for trade-offs in various
farmland functions increases. For example, there might not be as much
available grass biomass that could be utilized in biogas production
without competing with the conventional food production. However,
especially in warmer climates, a longer growing season means a greater
potential for cover crops to produce substantial biomasses, which can
function as an alternative feedstock in biogas production without
competing with other farmland functions.
In this study, results were based on modeling. The Palopuro AES
case needs to be evaluated by direct measurements and ex-post assess-
ments once fully functional. Field experiments examining the fertilizing
effect of digestate have been conducted with digested slurries or other
slurries combined with energy crops or crop residues (Stinner et al.,
2008;Möller, 2009;Benke et al., 2017). To our knowledge, no other
available studies have explored the fertilizing effect of digestates with
as high of a dry matter content as the digestate from the dry-fermen-
tation type of biogas plant modeled in our case study.
5. Conclusions
Agroecological Symbiosis serves as an adaptive model in meeting
the challenge of nutrient recycling and the transition to renewable
energy for ecologically intensified localized food systems. Such utili-
zation of the multiple beneficial functions of leys helps diversify rota-
tions in, especially, specialized arable farms. AES systems may turn
food production and processing to an energy-positive sector, while re-
ducing environmental loading. Our study demonstrated the impacts of
biogas production on nutrient flows and energy production. However,
other environmental impacts, including soil organic matter changes and
greenhouse gas emissions, should be studied in the future. Also, the N
value of digestates should be studied with plot experiments. Further
studies concerning variable production conditions, including other
types of food production systems, are needed to gain full understanding
of the potential of an AES for sustainable food production.
We would like to thank the Ministry of the Environment in Finland
for funding the Palopuro AES project. The authors also wish to thank all
the participants in the Palopuro AES project: especially Markus Eerola
from Knehtilä Farm, Virva Latostenmaa from Mäntymäen luomu ltd,
Peter Zukale from Samsara ltd, and Jukka Kivelä from the University of
Helsinki. We are also grateful for two anonymous reviewers who gave
their comments.
This work received funding from the Finnish Ministry of the
Environment's Programme (RAKI2) to promote the recycling of nu-
trients and improve the ecological status of the Archipelago Sea [grant
number YM52/481/2015].
Appendix A. Supplementary data
Supplementary data to this article can be found online at https://
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... The literature review revealed that the largest concentration of technology was related to biomass for nutrient cycling and biomass to energy. This highlighted the assertion that biomass and nutrient flows related to livestock are key to circular food systems (Koppelmäki et al., 2019) and the importance of manure management technologies for Table 3 Year 1 costs and Benefits of on-farm investments in Cuenca Santa Lucia by technology across farm, regional, and national scales. ...
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An increasing global population is putting stress on the food system. On-farm technologies to close resource loops will play a role in increasing food production without stressing natural resources. What are these applied on-farm circular technologies and what impact do they have on the food system? This paper develops a framework for defining the potential of on-farm circular technologies for benefits across multiple spatial scales. It then applies the framework to Uruguay to examine what economic and environmental benefits on-farm circular technologies, namely biomass for nutrient cycling (manure management) and on-farm water cycling, can have at multiple spatial scales – on-farm, regionally and nationally. Using data from a government program in Uruguay's most important watershed, the work shows that investments in on-farm manure management technologies yield economic and sustainability benefits that are unequally distributed across scales. It demonstrates that famers only receive a small percentage (16% on average) of the total benefits yielded by manure management and on-farm water cycling technologies, while most benefits (84% on average) occur at regional level. The analysis by technology demonstrates that the benefits of technologies also depend on how they are combined. For example, installing only a waste management pool on-farm increases the GHG emissions, while installing a waste management pool combined with a separator decreases the GHG emissions and magnifies the benefits of reduced water pollution. These findings raise questions regarding whether these technologies should be subsidized since most benefits occur beyond the farm level to the benefit of society. This has implications for how governments and private actors co-finance on-farm technologies to make farming practices more circular and sustainable.
... Especially in stockless organic crop farming, green manure and annual legumes are a substantial resource, as up to 60% of the cultivated area is used for the cultivation of nitrogen fixing plants. The use of green manure grass as the main feedstock in biogas production was demonstrated by Koppelmäki et al. [7]. This approach has several benefits. ...
... This approach has several benefits. The multifunctional use of biomass where nitrogen fixing crops are part of the crop rotation can positively impact farming systems, resulting in enhanced nutrient cycling, carbon sequestration, and crop growth without competition between food and energy production [7][8][9][10][11][12]. During anaerobic digestion, part of the organic nitrogen in green biomass is converted into ammonium nitrogen, which is more easily available when used as fertiliser [9]. ...
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This study focuses on the feasibility of the dry anaerobic digestion of solid agricultural biomass for efficient renewable-energy production and nutrient recycling. Methane production and the amount of nitrogen in the digestates were measured in pilot- and farm-scale leach-bed reactors. In the pilot scale, with a digestion time of 133 days, the methane production of a mixture of whole crop fava bean and horse manure corresponded to 94% and 116%, respectively, of the methane potentials of the solid substrates. The mono-digestion of fava beans resulted in relatively low methane production (production/potential ratios of 59% and 57%). In two full-scale experiments, the methane production of mixtures of clover-grass silage, chicken manure, and horse manure corresponded to 108% and 100% of their respective methane potentials with digestion times of 117 and 185 days. In co-digestion, the production/potential ratios were similar in the pilot and farm experiments. High nitrogen loss was observed in the farm scale when the digestate was stored in a stack covered with a tarpaulin during summertime. Thus, although the technology seems promising, attention needs to be paid to management practices to minimise nitrogen losses and greenhouse gas emissions.
... Advances in agroecology are especially known for agrifood system design (Gliessman 2020), but little understood and studied in agricultural systems based on an integration of the circular bioeconomy through waste inclusion and by-products valorisation for crop protection and fertilization, water reuse, bioenergy and biomaterials productions (Koppelmäki et al. 2019). ...
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Background and aims One of the major challenges of modern agriculture is to transform agricultural systems to support food security under global change. The reduction of the agricultural carbon footprint requires the development of agroecological practices and eco-friendly processes for biomass and by-products transformation. The push towards decarbonization of several industrial sector brings about new demand for bio-based products and can constitute an opportunity for crop diversification and by-products valorisation for crop fertilization and protection. This evolution leads to the study of novel agricultural systems centered around the concept of circular bioeconomy and the development of transdisciplinary approaches combining agroecology and bioeconomy to create more resilient. But what are these approaches and which steps must be taken to transform agricultural systems toward the ultimate goal of sustainability? Methods This opinion paper synthesizes such recent advances and contemporary understanding of agroecology and bioeconomy synergies by focusing on 1) the agroecological solutions for the bioeconomy: the ecological role of crop diversification, 2) the main eco-technologies of waste recycling and biomass transformation for agroecological development, 3) a holistic approach of combinations of agroecology and bioeconomy for sustainable agricultural systems. Results This combination is based on the association of functional low- and high-tech innovations that require life cycle analysis and a multi-assessment in cropping and farming systems to decrease their energy consumption and greenhouse gas emissions. Conclusion The combination of agroecology and circular bioeconomy constitutes an important lever to mobilize in order to improve ecosystem services at the soil–plant-atmosphere interface and farming sustainability at the territorial scale.
... Typically, integrating legumes into maize-based cropping systems serves as an alternative to inorganic fertilizers, contributing to biodiversity conservation [67]. These practices have been shown to contribute to weed and pest control, improve soil fertility, support pollination and nutrient cycling [33], and reduce water loss rates, facilitating the adaptation of food crop cultivation to prevailing climatic conditions [7,24,56]. In the realm of AEI, individual farming practices and the development of farmers' knowledge play a crucial role in addressing ecological, social, and economic conditions, as well as adapting food crop production to climate change [43]. ...
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In response to the increasing impacts of climatic stressors on human populations, climatic scholars have emphasized the need for alternative approaches to adapt food crop production to climate change and sustain the livelihoods of smallholder farmers. Inspired by agro-ecological intensification (AEI) practices of smallholder farmers, this study contributes to climate change adaptation debates in Sub-Saharan Africa by providing a context-specific exploration of everyday traditional soil and water management practices employed by smallholder farmers in adapting food crop production to climate change. The study employed a qualitative research design, conducted household case studies, focus group discussions, key informant interviews, and a review of secondary data. We show that smallholder farmers employ diverse range of agronomic practices, with a particular emphasis on traditional soil and water management techniques. Such as the preparation and application of organic manure and compost, ridges formation, crop rotation, and cover cropping. These agronomic practices were complemented by the application of limited inorganic fertilizers and applied across different types of farms; compound and bush farms, valley fields, and gardens to adapt production to climate change. We argue that smallholder farmers are more inclined towards adopting AEI as a means of climate change adaptation due to their strong reliance on traditional farming methods, that draws heavily on local resources, indigenous knowledge as relatively affordable practices. Therefore, we emphasize the importance of incorporating an Endogenous Development (ED) approach in promoting AEI as part of climate change adaptation planning, particularly in rural Ghana and other Sub-Saharan African regions facing similar conditions.
... As highlighted by Romera et al. (2020), studies in industrial ecology have already considered the inclusion of economic firms which could help lowering input and logistical costs and should be included in a territorial network. Here, it will be relevant to consider not only the agricultural sector in a food system transition but to see how to build a coordinated network at the local level, which could articulate relationships between farmers and other actors in the territory while achieving cultural and socio-economic benefits in a so-called AES (Agroecological Symbiosis) (Koppelmäki et al., 2019). The FAAB project mentioned earlier in section 3.6. ...
... Ordinarily, legumes may be integrated into maize-based cropping systems as an alternative to chemical fertilizers in a step towards sustaining biodiversity [83]. These have been found to contribute towards weed and pest control, enhancing soil fertility, pollination, and nutrient cycling [39]; and are capable of reducing the rate of water loss for adapting food crop cultivation to the climatic conditions [27,7,68]. AEI emphasizes that individual farming practices, including the knowledge-based development of farmers towards addressing ecological, social and economic conditions [52] in adapting to climate change. ...
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Globally, following the rising impacts of climatic stressors on humanity, climate change scholars have argued for alternative approaches towards adapting food crop production to climate change in sustaining smallholder farmers’ livelihood. This study used qualitative methods of data collection and analysis. Inspired by generational farming practices of smallholder farmers, drawing on their Agro ecological Intensification (AEI) practices, we contribute to climate change adaptation debates in Sub-Saharan Africa. We explore traditional AEI practices of smallholder farmers and their potential of adapting food crop production to climate change in the age of technology. We explored the link between smallholder farmers self-initiated soil and water management practices and AEI and discussed the implications for adapting food crop production to climate change via AEI practices. The study realized that smallholder farmers engaged in varied agronomic practices including the preparation and application of organic manure and compost ridging, crop rotation and cover cropping. Farmers applied multiple practices across different farms; compound and bush farms, valley fields, and gardens. Although these practices bear a resemblance to AEI in the form of improve soil fertility, health and water retention, we realized that smallholder farmers complemented self-initiated AEI practices with the application of chemical fertilizers to adapt food crop production to climate change. In sustaining food production, we argue that although AEI practices offer potential for sustaining soil and water, a concerted effort in the form of a climate change adaptation planning policy is imperative to ensure holistic adoption of AEI by smallholder farmers.
... In an attempt of bringing together the use of renewable energy and a farm-scale production strategy, we propose to apply the concept of Agroecological 13 th International Conference on Life Cycle Assessment of Food 2022 (LCA Foods 2022) On The role of emerging economies in global food security 12-14 October 2022, Lima, Peru (hybrid conference) 2 Symbiosis (AES) to alternative protein production. AES system aims resilient agricultural techniques and circular economy by locating food and bioenergy producers and processors in proximity, allowing efficient material and energy integration (Koppelmäki et al. 2019). In AES, an anaerobic digester produces biogas as a renewable energy source from crop residues, cover crops, and clover-grass leys incorporated into the crop rotations, as well as from manure and biowaste from neighbouring food processing plants and communities. ...
Conference Paper
Rationale and objective of the work: Brazil was the third-largest producer (36.5 million tons) of fresh cow milk in 2020 (FAO, 2022). However, the Brazilian raising of ruminant animals’ management showed an increase of 107% in air pollution from 1990 (1 kilo-DALY) to 2018 (2 kilo-DALY) due to particulate matter (PM) related emissions (UN, 2022). Thus, the goals of this research were to evaluate the human health damages of PM emitted from two confined milk production systems in Brazil through the Life Cycle Assessment (LCA) (ISO, 2006); and to analyze the sensitivity of results against different characterization models application. Approach and methodology: Two systems of confined milk production were evaluated. The first one was a compost barn system located at Angatuba city in São Paulo state, where the cows are confined, and sawdust is constantly inserted as bedding (bulky material) for the cows and mixed with manure to produce biofertilizer. The second one was a confined system located at Campos Gerais in Paraná state, with biogas and biofertilizer generation during the manure treatment. Mathematical models assisted the air emissions quantification of fossil CO2, fossil and biogenic CH4, N2O, and NO2. Both systems were analyzed from cradle-to-farm for 1 kg of Fat and Protein Corrected Milk (FPCM) as functional unit. The openLCA v. 1.10.3 software supported the systems modeling, and ecoinvent v. 3.7 provided the background datasets needed. The Life Cycle Impact Assessment (LCIA) step was developed exclusively for the PM formation category using four characterization models with Brazilian coverage: (1) UNEP and SETAC (2016), which is the global recommendation from the life cycle initiative; (2) Van Zem et al. (2016), which provided Characterization Factors (CF) to the world and to Brazil; (3) Fantke et al. (2017, 2019), which provided regionalized CF for 126 Brazilian cities, and; (4) Oberschelp et al. (2020), with CF to the world, to Brazil, and regionalized to Brazilian states. Main results and discussion: The confined system showed lower emissions of NH3 (69%) and NOx (35%) concerning the compost barn and higher emissions of PM2.5 (109%), and SO2 (106%). Then, using the CF provided by Van Zelm et al. (2016) to the global average, the compost barn showed an impact of 2.7×10-7 DALY/kg FPCM, and the confined system was 28% lower. Using the Brazilian CF of Van Zelm et al. (2016), the compost barn impact was 2.4×10-8 DALY/kg FPCM, and the confined system resulted in 20% higher damages. The NH3 emissions were the hotspot in the compost barn for global and national CF. However, to the confined system, the hotspot varied with the LCIA regionalization level. Results indicated the PM2.5 as the hotspot for the global approach and the SO2 for the national one. However, using the Oberschelp et al. (2020)’s CF, the compost barn resulted in 1.8×10-8, 4.9×10-8, and 4.6×10-7 DALY/ kg FPCM for global, national, and state levels, respectively. These results were 45%, 54%, and 85% lower for the confined system. These three geographical coverages indicated the NH3 emissions as the hotspot for both systems. Using the Fantke et al. (2017, 2019)’s proposed CF values showed that the compost barn impact was 7.5×10-9 DALY/kg FPCM, and the confined system presented an impact 242% higher. To this model, the NH3, SO2, and NOx emissions did not account for impacts due to the lack of specific CF. Thus, the hotspots analysis was not a viable step on this model use. Finally, the CF recommended by UNEP and SETAC (2016) resulted in 1×10-7 DALY/kg FPCM for compost barn, which was 16% lower than the confined impact. The confined system presented higher emissions of NOx for the high population density archetype, mainly due to background processes, and higher emissions of PM2.5 and SO2 compared to compost barn. NH3 and PM2.5 were found as the hotspots in the compost barn, while only PM2.5 was highlighted in the confined system. It is worth mentioning that the analyzed milk production systems are not comparable given the need for more harmonization in the inventory data quality. However, it is interesting to note that the variation in the characterization models significantly altered the results of both systems, changing the hotspots analysis and the magnitude of impacts on human health. Conclusion: For the PM formation category, regionalized CF values are recommended. Fantke et al. (2017, 2019) provided the finer territorial scope among the used models and CF for different archetypes. However, this model showed a limitation due to the lack of factors for PM precursor emissions. Thus, regarding the total PM impacts of the systems and geographic scope, the state-level model provided by Oberschelp et al. (2020) showed more consistency for application. The selection of the LCIA method should be made with caution, considering the LCA scope and the level of regionalization of the models available and required to attend to the LCA goal.
... Organic substances have rarely been the subject of investigation in classic cases of industrial symbiosis. However, the concept may also be extended to agri-food chains and energy systems (Koppelmäki et al., 2019;Onu and Mbohwa, 2021). ...
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Industrial symbiosis is an eco-innovative system concept that is based on a circular economy and industrial ecology ideas. This process comprises the movement of materials, energy, and skills across enterprises located within eco-industrial parks, and strives to provide economic, environmental, and social competitive advantages for all the involved parties. Considering that the agri-food system creates a vast quantity of by-products along the supply chain, it is a sector that has huge potential within material and energy recovery systems and fits well into eco-industrial parks. The current study is a literature review that aims to evaluate the interest exhibited so far by scientific research in the topic of industrial symbiosis in the agri-food sector and to highlight the primary analytical techniques that have been used for this topic. Using the paradigm of multiple correspondence analysis, a content analysis was conducted from which the major themes of the researched phenomena emerged. The results indicate that the topic areas are unrelated and somewhat distant from each other. The analysed case studies have revealed that the authors had neglected the communicative and collaborative elements among stakeholders, and instead focused on the potential use of some tools and approaches. Furthermore, it has been hypothesised that the hiding of information within a supply chain prevents industrial symbiosis procedures from being implemented. This research suggests the necessity of creating communication and cooperation platforms among stakeholders, which would promote the introduction of new techniques and tools for the development of circular production systems.
... There are examples of regenerative farming systems around the globe that demonstrate that achieving multiple regenerative objectives and having viable business models is possible (e.g. Khumairoh et al., 2018;Koppelmäki et al., 2019). Currently the majority of Dutch farmers, however, prioritize economic profitability over environmental and social objectives of food production (Kik et al., 2021). ...
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CONTEXT Regenerative agriculture is a farming approach that uses soil health as the entry point to contribute to multiple objectives, such as improved nutrient cycling and climate regulation. To reach these objectives farmers can apply different practices. The objectives and practices, however, are not equally relevant or applicable for every farming system and local context. OBJECTIVE The main objective of this paper, therefore, was to find out how tailor-made solutions towards regenerative agriculture can be identified and evaluated as such that they result in meaning-full advice for farmers. METHODS In this study a well-established modelling framework to redesign farming systems was applied to three typical but diverse Dutch farming systems. The modelling framework combined the models Soil Navigator and FarmDESIGN to simultaneously assess five soil functions at field-level and general sustainability indicators (e.g. greenhouse gas emissions) at farm-level. We applied the modelling framework to an arable farm on clay soil, a dairy farm on peat soil, and a mixed farm on sand soil. We subsequently explored a multitude of tailor-made solutions composed of combinations of practices for these farming systems, each showing solutions that contributed in varying degrees towards the objectives of regenerative agriculture. RESULTS AND CONCLUSION In total, we created 4000 alternative solutions per case-study farm. For all farming systems, environmental performance was improved in the solutions dominated by the use of regenerative practices. For example, for the arable, the dairy, and the mixed case-study farm, greenhouse gas emissions were reduced by 50% (from 4 to 2 Mg CO2 eq. ha⁻¹), 6% (from 30 to 28 Mg CO2 eq. ha⁻¹), and 23% (from 21 to 16 Mg CO2 eq. ha⁻¹), respectively, while maintaining soil functionality at high capacity for four out of the five soil functions. This overall improvement in environmental performance due to the application of regenerative practices, also resulted in reduced farm profitability for all case-study farms by on average 50%. We discuss that a mechanism to incentivize farmers for their tailor-made contribution to regenerative agriculture is for stakeholders to shift focus from solely primary productivity to also other ecosystem services. SIGNIFICANCE This study contributes to the wider implementation of regenerative agriculture, by showing which regenerative objectives and farming practices can contribute to the transition towards regenerative agriculture in contrasting contexts. The modelling framework that is used, can underpin regenerative management for farmers and other stakeholders to help, for example, the valorization of multiple regenerative objectives in business models.
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In temperate regions, legume-based green manures are a key element of organic rotations. However, specialized farms lack sufficient mobile organic fertilizers. To gain a better understanding of the N flows and the nitrogen (N) and phosphorus (P) fertilizer value of different clover-grass-based fertilizers (biogas digestate, compost, silage and fresh clover-grass obtained from clover-grass ley biomass), we assessed their fertilizer value. Nitrogen and P offtake by the ryegrass was used to assess the short-term effects. The data were completed using model calculations to assess the field-to-field N-transfer efficiencies and the overall N-transfer efficiencies. The greatest plant N offtake was achieved with digestates (64%) and the lowest from the compost (6%) and solid farmyard manure (14%). The mineralization rate was positively related to the NH4⁺–N/total N ratio (P < 0.01, r² = 0.82). The model calculations indicate that the overall short-term N-transfer efficiencies are driven by the field-to-field N-transfer efficiency and the field-to-crop transfer efficiency. However, in the long term, model calculations indicate that a high field-to-field N-transfer efficiency is the key strategic approach when aiming to achieve cropping systems with a high overall long-term N-transfer efficiency. Consequently, the results showed that aerobic decomposition (composting) significantly lowered field-to-field as well as field-to-crop N-transfer rates. The relative P use efficiency strongly differed among the fertilizers. In particular, freshly cut clover-grass and solid manure increased P availability and led to an increase of plant P offtake that was higher than the amount of P supplied.
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Long-term data from a network of intensively monitored research catchments in Finland was analysed. We studied temporal (1981–2010) and spatial variability in nitrogen (N) and phosphorus (P), from 1987 losses, both from agricultural and forestry land. Based on trend analysis, total nitrogen (TN) concentrations increased in two of the four agricultural sites and in most of the forested sites. In agricultural catchments, the total phosphorus (TP) trends were decreasing in two of the four catchments studied. Dissolved P (DRP) concentrations increased in two catchments and decreased in one. The increase in DRP concentration can be a result of reducing erosion by increased non-plough cultivation and direct sowing. In forested catchments, the TP trends in 1987–2011 were significantly decreasing in three of the six catchments, while DRP concentrations decreased significantly in all sites. At the same time, P fertilisation in Finnish forests has decreased significantly, thus contributing to these changes. The mean annual specific loss for agricultural land was on average 15.5 kg ha⁻¹ year⁻¹ for N and 1.1 kg ha⁻¹ year⁻¹ for P. In the national scale, total TN loading from agriculture varied between 34,000–37,000 t year⁻¹ and total P loading 2400–2700 t year⁻¹. These new load estimates are of the same order than those reported earlier, emphasising the need for more efforts with wide-ranging and carefully targeted implementation of water protection measures.
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A comprehensive understanding of plant metabolism could provide a direct mechanism for improving nitrogen use efficiency (NUE) in crops. One of the major barriers to achieving this outcome is our poor understanding of the complex metabolic networks, physiological factors, and signaling mechanisms that affect NUE in agricultural settings. However, an exciting collection of computational and experimental approaches has begun to elucidate whole-plant nitrogen usage and provides an avenue for connecting nitrogen-related phenotypes to genes. Herein, we describe how metabolomics, computational models of metabolism, and flux balance analysis have been harnessed to advance our understanding of plant nitrogen metabolism. We introduce a model describing the complex flow of nitrogen through crops in a real-world agricultural setting and describe how experimental metabolomics data, such as isotope labeling rates and analyses of nutrient uptake, can be used to refine these models. In summary, the metabolomics/computational approach offers an exciting mechanism for understanding NUE that may ultimately lead to more effective crop management and engineered plants with higher yields.
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This report explores the potential for a shift to occur from current food systems, characterized by industrial modes of agriculture, to systems based around diversified agroecological farming. It asks what the impacts on food systems would be if diversity, rather than uniformity, were the key imperative. The ecological benefits of such a shift have been widely documented. The key question in this report, is how can food systems based around diversified agroecological farming succeed where current systems are failing, namely in reconciling concerns such as food security, environmental protection, nutritional adequacy and social equity. As this report shows, there is much promise in the emerging evidence.
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There is a lack of literature reporting the methane potential of several livestock manures under the same anaerobic digestion conditions (same inoculum, temperature, time, and size of the digester). To the best of our knowledge, no previous study has reported biochemical methane potential (BMP) predicting models developed and evaluated by solely using at least five different livestock manure tests results. The goal of this study was to evaluate the BMP of five different livestock manures (dairy manure (DM), horse manure (HM), goat manure (GM), chicken manure (CM) and swine manure (SM)) and to predict the BMP using different statistical models. Nutrients of the digested different manures were also monitored. The BMP tests were conducted under mesophilic temperatures with a manure loading factor of 3.5 g volatile solids (VS)/L and a feed to inoculum ratio (F/I) of 0.5. Single variable and multiple variable regression models were developed using manure total carbohydrate (TC), crude protein (CP), total fat (TF), lignin (LIG) and acid detergent fiber (ADF), and measured BMP data. Three different kinetic models (first order kinetic model, modified Gompertz model and Chen and Hashimoto model) were evaluated for BMP predictions. The BMPs of DM, HM, GM, CM and SM were measured to be 204, 155, 159, 259, and 323 mL/g VS, respectively and the VS removals were calculated to be 58.6%, 52.9%, 46.4%, 81.4%, 81.4%, respectively. The technical digestion time (T80–90, time required to produce 80–90% of total biogas production) for DM, HM, GM, CM and SM was calculated to be in the ranges of 19–28, 27–37, 31–44, 13–18, 12–17 days, respectively. The effluents from the HM showed the lowest nitrogen, phosphorus and potassium concentrations. The effluents from the CM digesters showed highest nitrogen and phosphorus concentrations and digested SM showed highest potassium concentration. Based on the results of the regression analysis, the model using the variable of LIG showed the best (R2 = 0.851, p = 0.026) for BMP prediction among the single variable models, and the model including variables of TC and TF showed the best prediction for BMPs (R2 = 0.913, p = 0.068–0.075) comparing with other two-variable models, while the model including variables of CP, LIG and ADF performed the best in BMP prediction (R2 = 0.999, p = 0.009–0.017) if three-variable models were compared. Among the three kinetic models used, the first order kinetic model fitted the measured BMPs data best (R2 = 0.996–0.998, rRMSE = 0.171–0.381) and deviations between measured and the first order kinetic model predicted BMPs were less than 3.0%.
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Rising global energy needs and limited fossil fuel reserves have led to increased use of renewable energies. In Germany, this has entailed massive exploitation of agricultural biomass for biogas generation, associated with unsustainable farming practices. Organic agriculture not only reduces negative environmental impacts, organic farmers were also prime movers in anaerobic digestion (AD) in Germany. This study's aim was to identify the structure, development, and characteristics of biogas production associated with organic farming systems in order to estimate further development, as well as energetic and associated agronomic potentials. Surveys were conducted among organic farms with AD technology. 144 biogas plants could be included in the analysis. Total installed electrical capacity was 30.8 MWel, accounting for only 0.8% of the total installed electrical capacity in the German biogas sector. Recently, larger plant types (>250 kWel) with increased use of (also purchased) energy crops have emerged. Farmers noticed increases in yields (22% on average) and quality of cash crops in arable farming through integrated biogas production. In conclusion, although the share of AD in organic farming is relatively small it can provide various complementary socio-ecological benefits such as the enhancement of food output through digestate fertilization without additional need for land, while simultaneously reducing greenhouse gas emissions from livestock manures and soils. However, to achieve this OPEN ACCESS Sustainability 2015, 7 10710 eco-functional intensification, AD systems and their management have to be well adapted to farm size and production focus and based primarily on residue biomass.
Organic agriculture is often criticized for its lower productivity compared to conventional farming, while biogas production on organic farms is confronted with many structural constraints additionally impeding its profitability. However, integrated anaerobic digestion seems to induce multiple benefits for the respective organic farm system, such as reduced environmental impacts, improved nutrient efficiency, and stabilized or increased yields. In order to measure these effects within entire farm systems, systemic evaluation approaches are needed. Consequently, in this study we modelled twelve different livestock-keeping (LS) and stockless (noLS) organic farm prototypes comprising of arable farming, dairy cattle, grassland, and biogas production in a farm system assessment. The aim was to evaluate the impact of integrated anaerobic digestion (+ AD) on agronomic, economic, and risk aspects by applying stochastic optimization. While the absolute amount of readily available nitrogen as well as cash crop yields increase for both LS + AD and noLS + AD farm models, especially noLS farm types benefit from the novel availability of a mobile nitrogen (N) fertilizer (biogas digestate) to meet cash crop N demands. Integrated AD may increase profitability of arable farming and reduce its risk potential by displaying first order stochastic dominance. In addition, this diversification strategy may reduce the overall production risk of organic farms. By providing renewable energy as well as increasing food outputs and economic stability, the integration of AD in organic farms may serve as an example for the often postulated aim of a sustainable or eco-functional intensification of organic agricultural systems to face the challenge of productivity increases.
The Gas Turbine Engineering Handbook has been the standard for engineers involved in the design, selection, and operation of gas turbines. This revision includes new case histories, the latest techniques, and new designs to comply with recently passed legislation. By keeping the book up to date with new, emerging topics, Boyce ensures that this book will remain the standard and most widely used book in this field.The new Third Edition of the Gas Turbine Engineering Hand Book updates the book to cover the new generation of Advanced gas Turbines. It examines the benefit and some of the major problems that have been encountered by these new turbines. The book keeps abreast of the environmental changes and the industries answer to these new regulations. A new chapter on case histories has been added to enable the engineer in the field to keep abreast of problems that are being encountered and the solutions that have resulted in solving them.