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Research Paper

Model-based analysis of greenhouse gas emissionreduction potential through farm-scale digestion

Tine L.I. Vergote a,b, Wouter J.C. Vanrolleghem a,Caroline Van der Heyden a, Anke E.J. De Dobbelaere c, Jeroen Buysse b,Erik Meers a, Eveline I.P. Volcke a,*

a Department of Green Chemistry and Technology, Faculty of Bioscience Engineering, Ghent University, Coupure

Links 653, 9000, Ghent, Belgiumb Department of Agricultural Economics, Faculty of Bioscience Engineering, Ghent University, Coupure Links 653,

9000, Ghent, Belgiumc Inagro vzw, Research and Advice in Agriculture and Horticulture, Ieperseweg 87, Rumbeke-Beitem, 8800, Belgium

a r t i c l e i n f o

Article history:

Received 2 August 2018

Received in revised form

6 February 2019

Accepted 13 February 2019

Keywords:

Farm-scale anaerobic digestion

Dairy manure

ADM1

Model reduction

Hydrolysis

Greenhouse gas emissions

* Corresponding author. Coupure Links 653,E-mail address: Eveline.Volcke@UGent.be

https://doi.org/10.1016/j.biosystemseng.20191537-5110/© 2019 IAgrE. Published by Elsevie

An anaerobic digestion model was set up and applied to estimate desired methane pro-

duction in the form of biogas as well as unwanted methane emissions associated with

farm-scale digestion of manure. The generally accepted Anaerobic Digestion Model No. 1

was simplified assuming that hydrolysis is rate-limiting during anaerobic digestion of

manure, mainly consisting of non-readily biodegradable compounds. Simulations were

performed to demonstrate the effect of temperature and retention time on methane

emissions resulting from long-term manure and digestate storage. Moreover, the overall

carbon footprint of several manure management scenarios for Flemish dairy farms was

assessed based on model simulations and literature data. The scenarios assessed, differed

in the possible presence of a digester as well as in the manure collection and storage

method. A reduction in methane emissions was achieved for lower manure storage tem-

peratures (through external storage) and by decreasing the storedmanure volume and thus

the storage time before (controlled) anaerobic digestion. At the same time, feeding fresh

manure induced an increased methane production in the digester. The lowest carbon

footprint could be achieved on dairy farms with fresh manure collection by a manure

scraper, followed by controlled digestion and storage of the digestate in a gas-tight tank,

located outside. The controlled digestion must take place in a properly managed and

correctly dimensioned reactor as high digester methane losses and low digester retention

times increase the carbon footprint significantly.

© 2019 IAgrE. Published by Elsevier Ltd. All rights reserved.

9000, Ghent, Belgium.(E.I.P. Volcke).

.02.005r Ltd. All rights reserved.

Nomenclature

Note: For the values and units of parameters and variables, the

reader is referred to Supplementary information C.

a1 Parameter of double Arrhenius equation

a2 Parameter of double Arrhenius equation

Ad Frequency factor of single Arrhenius equation

ADM1 Anaerobic Digestion Model No. 1

Ae Amplitude of sine function describing the external

storage temperature

Am Amplitude of sine function describing the manure

pit temperature

b1 Parameter of double Arrhenius equation

b2 Parameter of double Arrhenius equation

be Bias of sine function describing the external

storage temperature

bm Bias of sine function describing the manure pit

temperature

CHP Combined heat and power

CSTR Continuous stirred tank reactor

COD Chemical oxygen demand

Ed Activation energy of single Arrhenius equation

fbu,aa Fraction of butyrate from amino acids

fbu,su Fraction of butyrate from sugars

fch,xc Fraction of carbohydrates from composites

fe Frequency of sine function describing the external

storage temperature

ffa,li Fraction of long chain fatty acids from lipids

fh2,aa Fraction of hydrogen gas from amino acids

fh2,su Fraction of hydrogen gas from sugars

fli,xc Fraction of lipids from composites

fm Frequency of sine function describing the manure

pit temperature

fpro,aa Fraction of propionate from amino acids

fpro,su Fraction of propionate from sugars

fpr,xc Fraction of proteins from composites

fsCH4,xc Fraction of methane gas from composites

fsI,xc Fraction of soluble inerts from composites

fva,aa Fraction of valerate from amino acids

fxb,xc Fraction of microbial biomass from composites

fxI,xc Fraction of particulate inerts from composites

GASCH4 Methane gas concentration

GWP Global warming potential

IPCC Intergovernmental Panel on Climate Change

kd Temperature-dependent decay constant

kd37 Decay constant at 37 �Ckh Temperature-dependent hydrolysis constant

kh37 Hydrolysis constant at 37 �CkLaCH4 Gas-liquid transfer coefficient

KH,i Temperature-dependent Henry constant for gas i

LCFA Long chain fatty acids

pCH4 Partial pressure of methane in gas phase (outside

air) above storage tanks

pCH4,d Partial pressure of methane in the digester

pe Phase of sine function describing the external

storage temperature

pm Phase of sine function describing the manure pit

temperature

PGAS,CH4 Cumulative methane gas release or production

Qin Ingoing flow to manure or digestate storage

Qin,d Ingoing flow of manure to digester

Qout Outgoing flow of manure from manure pit

Qout,d Outgoing flow of digestate from digester

Rd Ideal gas constant of single Arrhenius equation

Rh Ideal gas constant of equation for Henry constant

SCH4 Soluble methane concentration

SCH4,in Ingoing soluble methane concentration of fresh

manure

SI Soluble inerts concentration

SI,in Ingoing soluble inerts concentration of fresh

manure

T Temperature

T0 Standard temperature of double Arrhenius

equation

Te Manure or digestate temperature in the external

storage

Tm Manure temperature in the manure pit

V Volume in the manure pit/external digestate

storage

Vd Digester volume

VS Volatile solids

XB Microbial biomass concentration

XB,in Ingoing microbial biomass concentration of fresh

manure

XC Composite concentration (organic content)

XC,in Ingoing organic content of fresh manure

XI Particulate inerts concentration

XI,in Ingoing particulate inerts concentration of fresh

manure

Yaa Yield of amino acids

Yac Yield of acetate

Yc4 Yield of butyrate and valerate

Yfa Yield of long chain fatty acids

Yh2 Yield of hydrogen gas

Ypro Yield of propionate

Ysu Yield of sugars

rdecay Decay process rate

rhydr Hydrolysis process rate

b i o s y s t em s e n g i n e e r i n g 1 8 1 ( 2 0 1 9 ) 1 5 7e1 7 2158

1. Introduction

The last decades have been characterised by a large increase

in livestock production to respond to the increased demand

for meat and dairy products due to the growing global

population and economic development. The economic

importance of livestock production is shown by its 40%

contribution to the monetary value of all global agricultural

goods (FAO, 2006). However, the livestock sector also accounts

for 14.5% of the global anthropogenic greenhouse gas emis-

sions, 44% of which is in the form of methane (Gerber et al.,

b i o s y s t em s e ng i n e e r i n g 1 8 1 ( 2 0 1 9 ) 1 5 7e1 7 2 159

2013) with a global warming potential (GWP) of 34 over a 100-

year time horizon (IPCC, 2013). Methane from livestock is

mainly emitted during enteric fermentation (39.1%), the

contribution from which can be reduced through several di-

etary strategies (Martin, Morgavi, & Doreau, 2010), and

manure management like storage (4.3%) (Gerber et al., 2013).

In most European countries, long-term manure storage is

applied because the EU Nitrates Directive (91/676/EEC) re-

stricts the period duringwhich fertiliser application is allowed

(European Commission, 1991). Although the contribution of

manure storage to greenhouse gas emissions seems rather

small, future emission increases due to increasing livestock

numbers should be avoided. Appropriate manure manage-

ment systems could support the commitment made by the EU

to achieve a greenhouse gas emission reduction of respec-

tively 40% and 80e95% by 2030 and 2050 compared to 1990

(European Commission, 2011).

While anaerobic conditions during manure storage result

in unwanted methane formation and emissions to the atmo-

sphere, controlled anaerobic digestion is a promising strategy

to reduce methane emissions (Mara~n�on, Salter, Castrill�on,

Heaven, & Fern�andez-Nava, 2011; Mesa-Dominguez, Styles,

Zennaro, & Thompson, 2015; Miranda, Tuomisto, & McCul-

loch, 2015). Under anaerobic conditions (i.e. in the absence of

oxygen, nitrite and nitrate), manure is converted to biogas (a

mixture of mainly CO2 and CH4) and digestate (digested

manure) through a complex reaction network mediated by a

wide diversity of micro-organisms (Pavlostathis & Giraldo-

Gomez, 1991). During farm-scale digestion, storage facilities

can be coupled directly to an anaerobic digester, thus pre-

venting methane emissions from long-term manure storage.

Note that the term ‘anaerobic digestion’ is used in this

contribution to refer to controlled anaerobic digestion in a

dedicated reactor, rather than to the anaerobic conversion

processes in manure or digestate storage facilities which

cause unwanted methane emissions. The methane produced

in the anaerobic digester is burnt in a combined heat and

power unit (CHP) to supply electricity and heat, which allows

digester-owning farmers to become (partly) energy self-

sufficient and less dependent on fluctuating and generally

increasing energy prices. An additional advantage of anaer-

obic digestion is the partial conversion of organically bound

nitrogen to mineral nitrogen (predominantly NH4þeN) (M€oller,

Stinner, Deuker, & Leithold, 2008) creating a fertiliser product

with a possibly improved nutrient use efficiency in compari-

son to raw manure (Gutser, Ebertseder, Weber, Schraml, &

Schmidhalter, 2005; Sigurnjak, De Waele et al., 2017).

Furthermore, odour nuisance will be reduced due to fatty acid

conversion (WPA, 2007). Farm-scale digestion is widely

implemented in Germany, Italy and the United Kingdom

(Cave, 2013; EurObserv'ER, 2017). In Flanders, farm-scale

digestion is also gaining ground due to the potential finan-

cial benefits, with a total installed capacity of 725 kWelectrical

power in 2017 (Decorte & Tessens, 2018).

Several studies have been conducted to quantify methane

gas emitted duringmanure and/or digestate storage using lab-

scale experiments (Amon, Kryvoruchko, Amon, &

Zechmeister-Boltenstern, 2006; Clemens, Trimborn, Weiland,

& Amon, 2006; Petersen, Olsen, Elsgaard, Triolo, & Sommer,

2016), measuring campaigns (Daelman, van Voorthuizen, van

Dongen, Volcke, & van Loosdrecht, 2012; Flesch, Desjardins, &

Worth, 2011; Groth, Maurer, Reiser, & Kranert, 2015; Liebetrau

et al., 2010; Reinelt, Liebetrau,&Nelles, 2016) and rudimentary

calculations or life cycle analysis based on the IPCC

methodology (Cornejo&Wilkie, 2010; De Vries, Groenestein,&

De Boer, 2012; Kaparaju & Rintala, 2011; Liang, Lal, Du, Wu, &

Meng, 2013; Mara~n�on et al., 2011). However, dynamically

simulating the anaerobic digestion process through physical-

basedmodels allows for the comparison of different scenarios

in a time-efficient way. The Anaerobic Digestion Model No. 1

(ADM1) (Batstone et al., 2002) has been widely applied, mainly

for anaerobic digestion of sewage sludge. Nonetheless, it is not

often used by practitioners due to its complexity and the large

number of parameters. Efforts have been made by, for

example, Page, Hickey, Narula, Main, and Grimberg (2008) to

define a parameter set for ADM1 by which the performance of

a dairy manure digester could be estimated. However, this

parameter set was not optimal to fit all experimental data.

Zeeman (1994) investigated the influence of some specific

temperature values and storage times onmethane production

and emissions from cow and pig manure through a (steady

state) anaerobic digestion model including the hydrolysis and

methanogenesis process calibrated on experimental data

(Zeeman, 1991). Furthermore, empirical relations were set up

in the past to estimate methane emissions, for example in

function of volatile solids (VS) reduction and temperature

(Sommer, Petersen, & Møller, 2004) or in function of storage

time at two different temperatures (de Mol & Hilhorst, 2003).

The results of these studies indicate that both storage time

and temperature will strongly affect the anaerobic digestion

process and are therefore key variables in simulating and

comparing the annual methane emission and/or production

profiles of several (digestion) farms.

Considering that often not all model inputs can be accu-

rately approximated, this study aims to set up a fit-for-

purpose anaerobic digestion model which can estimate the

methane emission reduction potential through farm-scale

digestion of dairy manure taking into account the daily vari-

ability in storedmanure volume and temperature. To this end,

ADM1 is simplified to a one-stepmodel, under the assumption

that hydrolysis is rate-limiting (Parkin & Owen, 1986;

Pavlostathis & Giraldo-Gomez, 1991; Vavilin, Rytov, & Lok-

shina, 1996), and further adjusted to be suitable for dynamic

modelling of methane emissions from storage and methane

production from anaerobic digestion. The influence of

different factors on methane emissions and production is

identified with this model. Besides, a specific case study for

Flanders is elaborated to assess the carbon footprint of dairy

farms based on simulation results, literature data and data

from practice.

2. Materials and methods

2.1. Simplified anaerobic digestion model ebioconversion processes

Manure mainly consists of non-readily biodegradable com-

pounds (Vavilin et al., 1996). As a result, the rate-limiting step

during anaerobic digestion of manure is typically the

Table 1 e Simplified anaerobic digestion model, obtained from ADM1 model reduction assuming hydrolysis as the rate-limiting step. Gujer matrix representation including process stoichiometry and kinetics.

Component i [kg [COD] m¡3] / 1 2 3 4 5 Process rate rj [kg [COD] m¡3 d¡1]

Process j ↓ XC XB SCH4 SI XI

1 Methane production �1 0.0984 0.6016 0.1 0.2 kh ,XC

2 Biomass decay 1 �1 kd ,XB

b i o s y s t em s e n g i n e e r i n g 1 8 1 ( 2 0 1 9 ) 1 5 7e1 7 2160

extracellular hydrolysis process, during which complex

molecules are converted into more soluble compounds

(Parkin & Owen, 1986; Pavlostathis & Giraldo-Gomez, 1991;

Vavilin et al., 1996). Based on this assumption, the generally

accepted ADM1 (Batstone et al., 2002) could be simplified to a

one-step model, describing the direct conversion of com-

posites (XC) into methane (SCH4) and microbial biomass (XB),

besides soluble inerts (SI) and particulate inerts (XI). The

corresponding reaction stoichiometry was obtained by

substituting the remaining state variables through the stoi-

chiometric relations of the original ADM1, while lumping all

microbial groups into a single state variable XB

(Supplementary information A). The concentration of the

different components was expressed in kg [COD] m�3, as in

ADM1. The rate of the overall methane producing and

biomass growth reaction was described as a first-order

equation characterised by a hydrolysis constant for com-

posite material (kh [d�1]) (Veeken & Hamelers, 1999), lumping

hydrolysis of carbohydrates, proteins and lipids. Biomass

decay was also included as a first order process with the

decay constant kd [d�1] (Gerber, 2008). Hence, the original

ADM1 with 19 processes and 32 state variables was reduced

to 2 processes and 5 state variables (Table 1).

The simplified anaerobic digestion model assumes that

hydrolysis is the rate-limiting step and is applicable only if

this assumption is fulfilled. The model is thus not suitable to

simulate anaerobic digestion of soluble substrates for which

methanogenesis is the rate-limiting step rather than hydro-

lysis (Cervantes, Pavlostathis, & van Haandel, 2006). Besides,

methane production was described as a first order reaction

and all possible inhibition effects were neglected. This implies

that the digester is assumed to be operated under sufficiently

small loading rates not to have ammonia inhibition, which is

often mentioned in the context of manure digestion, espe-

cially when overloading the system (Chen, Cheng, & Creamer,

2008). However, the risk of ammonia inhibition is anyhow less

of an issue for dairy manure than for pig manure since the

latter has a lower C:N-ratio (Rynk et al., 1992). Moreover,

ammonia inhibition will depend on pH, temperature, ionic

strength, type of micro-organisms and their adaptation to

ammonia making its occurrence case-specific (Chen et al.,

2008), but seems not to be a problem in the currently

running mono-digesters on dairy manure (Pocket Power

stakeholder event, personal communication, 2018). Further-

more, pH was assumed to range between 6.8 and 7.2 which is

optimal for anaerobic digestion (Ward, Hobbs, Holliman, &

Jones, 2008).

2.2. Model parameters and assumptions

The parameter values proposed in the ADM1 report (Batstone

et al., 2002) were meant to describe anaerobic digestion of

sewage sludge, somore specific values for anaerobic digestion

of dairy manure were gathered in this study. The hydrolysis

constant of dairy manure at 37 �C was derived from Li et al.

(2013) as kh37 ¼ 0.06 d�1. Its temperature dependency (T [K])

was defined by a double Arrhenius equation (Equation (2.1))

since this equation is able to describe the rapid decrease at

high temperatures (Batstone et al., 2002; Pavlostathis &

Giraldo-Gomez, 1991). The parameter values a1 ¼ 0.15 K�1,

a2 ¼ 0.3 K�1, b1 ¼ 0.75 and b2 ¼ 0.14 were taken from

Pavlostathis and Giraldo-Gomez (1991) as well as the standard

temperature at mesophilic conditions T0 ¼ 303.15 K.

kh ¼ kh37$ðb1$expða1$ðT� T0Þ Þ � b2$expða2$ðT � T0Þ Þ Þ (2.1)

The decay constant at 37 �C was adopted from Batstone

et al. (2002) as kd37 ¼ 0.02 d�1 while the activation energy

and the ideal gas constant were derived from Banik,

Viraraghavan, and Dague (1998) as respectively

Ed ¼ 35229 J mol�1 and Rd ¼ 8.3145 J mol�1 K�1. The decay

constant was made temperature-dependent by means of a

single Arrhenius equation (Equation (2.2)) as demonstrated by

Banik et al. (1998). Given a temperature T of 310.15 K (37 �C),

the frequency factor Ad [e] was calculated by substituting all

parameter values in Equation (2.2).

kd ¼ kd37$

�Ad$exp

�� Ed

Rd$T

��(2.2)

The equilibrium between gas and liquid was described by

Henry's law (for dilute solutions) with Sgas,i the equilibrium

concentration of the gas in the liquid phase [kg [COD] m�3],

KH,i the temperature-dependent Henry constant [kg [COD]

m�3 kPa�1] and pgas,i the partial pressure of the gas in the gas

phase [kPa] (Equation (2.3)). KH,CH4 accounts for the transfer

rate ofmethanewith the ideal gas constant Rh¼ 8.3145 kPam3

kmol�1 K�1 and T the manure or digestate temperature [K]

(Equation (2.4)). The latter equation and parameters were

derived from Gernaey, Jeppsson, Vanrolleghem, and Copp

(2014). However, the original equation was adjusted for unit

conversion as discussed by Batstone et al. (2002) and tem-

perature T is not solely related to the optimal temperature for

anaerobic digestion anymore. All model variables and

parameter values are listed in Supplementary information C.

Sgas;i ¼ KH;i$pgas;i (2.3)

b i o s y s t em s e ng i n e e r i n g 1 8 1 ( 2 0 1 9 ) 1 5 7e1 7 2 161

KH;CH4 ¼ 64$0:000014$exp

�� 14240

Rh$

�1

298:15� 1

T

��

(2.4)

2.3. Mass balances for digester and storage tanks

The model was applied to simulate anaerobic digestion in an

ideal continuous stirred tank reactor (CSTR), thus the hy-

draulic retention time equals the solids retention time and the

outgoing concentration of the different components equals

their concentrations in the reactor. Themanure volume in the

digester was considered to be constant and volume reduction

through digestion was neglected. As a result, the outgoing

flow rate equalled the incoming one, even though their values

may be time-dependent. Individual liquidmass balanceswere

set up for all state variables, i.e. component concentrations

represented in Table 1, expressing that accumulation of a

component's mass with time is due to mass that enters and

leaves the reactor, and mass that is produced and consumed

in the reactor (Supplementary information B). Mass balances

over the storage tanks formanure and digestate were set up as

well, taking into account the variation of stored manure and

digestate volumes in time - due to their dependence on the

allowance for fertiliser application on the field. The cumula-

tive amount of methane gas produced in the digester and

released from the storage tanks was calculated based on the

driving force for liquid-gas transport. The model was imple-

mented in Matlab®-Simulink®.

2.4. Reference case e Identification of influencing factors

As reference case, a dairy farm with 70 cows, which excrete a

total of about 5 m3 of manure per day (RVO, 2015), was

assumed. The organic content (composite concentration) of

fresh dairy manure was considered to be 110 kg [COD] m�3

manure based on literature (Garcıa& P�erez, 2013;Martin, 2003;

Spellman & Whiting, 2007; Zaher & Chen, 2006). The consid-

ered manure and digestate storage tanks are open to the air

(worst case) so the partial pressure of methane in these tanks

was assumed negligible. The digester has a volume of 125 m3,

which corresponds to a retention time of 25 days, and oper-

ates at a temperature of 37 �C. The steady state conditions in

the digester obtained for the reference case were set as the

initial conditions for both the digester and the digestate

storage tank (Supplementary information D). The partial

pressure of methane in the digester, derived from Rosen &

Jeppsson (2006) as pCH4,d ¼ 65 kPa, was assumed to be con-

stant, which is reasonable for a double membrane gas dome

as typically applied in practice.

The influence of temperature and storage time on the

amount of methane emitted during manure and digestate

storage was quantified through steady state simulations. For

these simulations, manure and digestate were subjected to

various temperatures (5, 10, 15, 20 and 25 �C) and retention

times (10, 20, 30, 40 and 50 d). Besides, a sensitivity analysis

was performed to determine the influence of ingoing organic

content, temperature, retention time, methane partial pres-

sure, hydrolysis constant at 37 �C and decay constant at 37 �Con the methane production in the farm-scale digester. More

specifically, the change in methane production compared to

the reference casewas assessed for a 10% increase or decrease

in an individual parameter value (relative to the reference

value), while the other parameters were kept at their

reference values.

2.5. Case study: Flanders

The model was used to quantify annual methane emissions

from storage on specific Flemish dairy farms by including the

variability of stored manure or digestate volume and tempera-

ture. It was assumed that the animals stayed inside the stable

and the dailymanure productionwas constant (ingoing flow on

Fig. 7B) because of the ongoing increase in scale and intensifi-

cation in the dairy sector (van Bruggen & Faqiri, 2015) and for

reasons of simplicity. The amount of manure or digestate

applied on land was determined following the allowance for

fertiliser spreading (outgoing flow on Fig. 7B) described in the

FlemishManureDecree. This Flemish implementation of theEU

Nitrates Directive states that in general fertilisers can only be

applied on the field from mid-February till the end of August

(VLM, 2015). In this study, daily applicationwas assumedduring

two distinct periods: from mid-February till mid-April, to fer-

tilise grassland and fields for early crops, and from the begin-

ning of July till the endofAugust, to fertilise fields for later crops,

to ensure a second fertilisation where needed and to provide

sufficient storage capacity during autumn and winter. Even

though in practice manure will not be spread on the field each

dayof theseperiodsand thestoredvolumewill be farm-specific,

it was implemented like this to account for average manure

management variability between farmers and crop types. As a

result of the constant manure production and discontinuous

application, the overall volume of manure and digestate on the

farm varies over the year.

A dynamic outside air temperature profile was defined

based on measured monthly averaged temperature values for

Belgium between 1981 and 2010, which varied from 3.3 �C to

18.4 �C, the highest temperature value coinciding with July 20th

(KMI, 2010). The temperature profiles in the manure pit and in

the external storage tank were defined as sinusoids with a

period of 1 year, theirmaximumwas set equal to themeasured

or assumed maximum temperature at the corresponding day

and their amplitudes were defined as the difference between

measured or assumedmaximum and minimum temperatures

(Fig. 1). Themaximum temperature in themanure pit (Tm) was

set equal to the measured outside air temperature in summer

(18.4 �C) while its minimum temperature was assumed some-

what higher than the outside air temperature inwinter (7.5 �C),considering the temperature in the manure pit to be the same

as the controlled temperature in the stable (Sommer et al.,

2004). The minimum and maximum temperature of manure

or digestate in the external storage (Te) were estimated to be 5

and 15 �C, respectively. This temperature range is narrower

than that ofmanure in the pit since the external storagewill be

more subject to changing weather conditions (Sommer,

Christensen, Schmidt, & Jensen, 2013) but stored manure or

digestate temperatures will fluctuate less rapidly than the

outside air temperature (Rodhe, Ascue, & Nordberg, 2009). The

temperature of digestate was considered equal to that of

manure which was stored in the same way.

31/08 30/09 31/10 30/11 31/12 31/01 28/02 31/03 30/04 31/05 30/06 31/07 31/08

5

10

15

20

Tem

pera

ture

[°C

]

Outside air temperatureManure pit temperatureExternal storage temperature

Fig. 1 e Estimated annual temperature profiles for manure

in the pit (Tm ¼ 5.45 sin(0.0172 T þ 2.2938) þ 12.95) and

manure or digestate in the external storage (Te ¼ 5

sin(0.0172 T þ 2.2938) þ 10) compared to the average

outside air temperature profile of Belgium (KMI, 2010).

b i o s y s t em s e n g i n e e r i n g 1 8 1 ( 2 0 1 9 ) 1 5 7e1 7 2162

Four scenarios were considered for investigation (Fig. 2).

Scenario 1 focused on a conventional Flemish dairy farm con-

sisting of a stable with a manure pit beneath a slatted floor. In

scenario 2, the effect of external instead of internal manure

storage was investigated, reflecting the recent trend of using a

solid floor and a manure scraper to ensure direct pumping of

freshmanure to an external storage tank or a digester. The use

of a manure scraper is recognised as an ammonia-reducing

technique in Flanders (VLM, 2017) and the associated invest-

ment is partly co-funded by the European Rural Development

Funds (Departement Landbouw en Visserij, 2017). Scenario 3

and4 focusedondigestion farmswithout orwith pre-storage of

manure. In scenario 3, a farm-scale digester was fed daily with

all fresh manure excreted by the dairy cows which was

collected from the solid floor by a manure scraper (De

Dobbelaere et al., 2015). After the digestion period, the diges-

tatewas stored externally till spreadingwas allowed. The effect

of keeping amanure pit while considering the implementation

of a digester was investigated in scenario 4, since the

Fig. 2 e Overview of the different simulated scenarios with sce

slatted floor in which the manure temperature varies between 7

scraper and external manure storage where manure temperatu

floor and manure scraper which collects fresh manure, farm-sca

a retention time of 25 days and external digestate storage in w

and scenario 4: a stable with a manure pit beneath the slatted fl

temperatures ranging from 7.5 to 18.4 �C, farm-scale digester op

time of 25 days and external digestate storage with digestate t

adaptation from a manure pit beneath the slatted floor to a

manure scraper on a solid floor is associated with a large in-

vestment cost. More specifically, the impact of feeding pre-

stored manure (20 days) to the digester was explored. In this

scenario, the manure pit always contained 100 m3 of manure.

The composition ofmanure after a 20-day storage period (from

the 11th till the 30th ofAugust)was used as the initial conditions

for scenario 4 (Supplementary information D).

Emission sources other thanmethane frommanure and/or

digestate storage will also contribute to the overall carbon

footprint of dairy farms (Table 2). Emissions related to elec-

tricity consumption will depend on the layout of the dairy

farm. The presence of a manure scraper (scenario 2 and 3) will

increase the electricity consumption and related emissions.

Furthermore, water for the milking area can be heated by

means of butane gas or an electrical heater. An electrical

heater was assumed in all scenarios as butane gas is

increasingly less used on Flemish dairy farms (Inagro, per-

sonal communication, 2018). However, both would induce a

similar amount of CO2-equivalents per cow per year. If a

digester is present on a dairy farm, carbon neutral renewable

electricity can be produced from the methane (Miranda et al.,

2015). The possible electricity production can be directly

calculated from the simulated methane production given the

density of methane, the conversion factor from methane to

kWh and the electrical efficiency. Part of this electricity will be

consumed by the digester itself. If the remaining part is larger

than the electricity need of a specific dairy farm, the excess of

produced electricity could replace electricity from fossil fuels

to be used elsewhere. If not, some fossil fuel derived electricity

has to be bought to meet the demand, increasing the carbon

footprint. Furthermore, digester operation can induce

methane emissions through leakages, methane slip and an

active overpressure safety device, of which the quantity de-

pends on the total methane production simulated in this

nario 1: a dairy cow stable with a manure pit beneath the

.5 and 18.4 �C, scenario 2: a stable with a solid floor, manure

res range from 5 to 15 �C, scenario 3: a stable with a solid

le digester operating at a constant temperature of 37 �C and

hich the digestate temperature varies between 5 and 15 �Coor in which pre-storage of 20 days takes place at manure

erating at a constant temperature of 37 �C and a retention

emperatures varying between 5 and 15 �C.

Table 2 e Parameter values used to approximate the carbon footprint of specific Flemish dairy farms.

Parameter Value Reference

Electricity consumption

Average electricity consumption of farm

(without manure scraper and electrical heater)

729 kWh cow�1 y�1 Mara~n�on et al. (2011)

Average electricity consumption of manure scraper 20 kWh cow�1 y�1 Mara~n�on et al. (2011)

Electricity consumption of electrical heater 150 kWh cow�1 y�1 Mara~n�on et al. (2011)

Emission factor of electricity 0.33 kg [CO2,eq.] kWh�1 VMM (2014)

Number of cows 70 cows Case study assumption

Total manure production 5 m3 d�1 RVO (2015)

Density of CH4 0.657 kg [CH4] m�3 Unitrove (2018)

Conversion factor from CH4 to kWh 10 kWh m�3 [CH4] Banks (2009)

Electrical efficiency 30% Kasper and Peters (2012)

Electricity consumption of digester 25% De Dobbelaere (2017)

Digester methane losses: leakages, methane slip, overpressure safety device

CH4 leakages as percentage of CH4 production 0.99% Battini, Agostini, Boulamanti, Giuntoli,

and Amaducci (2014); Liebetrau et al. (2010);

Michel, Weiske, and M€oller (2010)

Methane slip as percentage of CH4 production 1.61% Daelman et al. (2012); Liebetrau et al. (2010);

Woess-Gallasch et al. (2010)

CH4 from overpressure safety device as

percentage of CH4 production

1.83% Reinelt et al. (2016)

GWP of CH4 (for 100-year time horizon) 34 kg [CO2,eq.] kg�1 [CH4] IPCC (2013)

GWP of N2O (for 100-year time horizon) 298 kg [CO2,eq.] kg�1 [N2O] IPCC (2013)

Fertiliser application

N2O from manure application 3.8 g [N2O] m�3 manure Amon et al. (2006)

N2O from digestate application 2.7 g [N2O] m�3 manure Amon et al. (2006)

CH4 from manure application 1.3 g [CH4] m�3 manure Amon et al. (2006)

CH4 from digestate application 2 g [CH4] m�3 manure Amon et al. (2006)

Storage

N2O from manure storage 20.2 g [N2O] m�3 manure Amon et al. (2006)

N2O from digestate storage 28.5 g [N2O] m�3 manure Amon et al. (2006)

CH4 from manure storage This study (model simulations)

CH4 from digestate storage This study (model simulations)

b i o s y s t em s e ng i n e e r i n g 1 8 1 ( 2 0 1 9 ) 1 5 7e1 7 2 163

study. Since due to current legislation, digestate from mono-

or co-digestion of manure can still not serve as a worthy

substitute for synthetic fertilisers (European Parliament, 2013)

even though research shows its potential (Sigurnjak,

Vaneeckhaute, et al., 2017), no emission reduction related to

the lower synthetic fertiliser usewas taken into consideration.

The possible carbon footprint reduction of the different sce-

narios compared to the default dairy farm (scenario 1) were

estimated by combining simulation results from this study

with literature data on these other emission sources (Table 2).

Calculation details are given in Supplementary information E

and in the Excel file (Supplementary information F) which can

be freely used by researchers and practitioners.

3. Results and discussion

3.1. Influence of influent and operational characteristicson methane emissions and production

Methane emissions during manure and digestate storage in

function of the temperature and retention time (RT) are dis-

played in Fig. 3. Higher temperatures induced more methane

emissions because the rate-limiting hydrolysis process is

accelerated under such conditions. Furthermore, longer

retention times led to an increased amount of emitted

methane, since over the prolonged time period a more

extensive conversion could take place. Similar trends were

found by Zeeman (1994) regarding the effect of temperature

and retention time on methane emissions. At low retention

times (10 d) and low temperatures (5 �C), methane emissions

from both manure and digestate storage were minimal

(respectively 0.17 and 0.08 kg [CH4] m�3 manure) (Fig. 3). In

practice however, such conditions will be difficult to realise.

Since the outside air temperature cannot be changed, prac-

tical solutions for the construction of low-temperature

storages must be investigated. Furthermore, storage time de-

pends on restrictions for fertiliser spreading.

Methane emissions from digestate storage were signifi-

cantly lower than those from manure storage at the same

temperature and retention time. A reduction of about 58%

could be noticed if emissions from manure and digestate

storage were compared at both retention times of 10 d and

50 d (25 �C) (Fig. 3). This reduction can be explained by the

digestion step prior to storage of digestate, during which a

large part of the composites was converted to methane. More

specifically, a decrease from 110 to 44.9 kg [COD] m�3 manure

could be noticed after fresh manure digestion of 25 days,

5 10 15 20 25Temperature [°C]

0

2

4

6

8

10

Met

hane

em

issi

ons

man

ure

stor

age

[kg

[CH

4] m-3

man

ure]

A

RT = 10 dRT = 20 dRT = 30 dRT = 40 dRT = 50 d

5 10 15 20 25Temperature [°C]

0

2

4

6

8

10

Met

hane

em

issi

ons

dige

stat

est

orag

e [k

g [C

H4] m

-3 m

anur

e]

B

RT = 10 dRT = 20 dRT = 30 dRT = 40 dRT = 50 d

Fig. 3 e Effect of temperature and retention time on methane emissions [kg [CH4] m¡3 manure] (A) during storage of manure

and (B) during storage of digestate, after fresh manure digestion of 25 days.

b i o s y s t em s e n g i n e e r i n g 1 8 1 ( 2 0 1 9 ) 1 5 7e1 7 2164

implying a methane conversion factor (MCF) of about 59% and

a desired production of about 10.11 kg [CH4] m�3 manure

(Supplementary information D). Although long-term manure

storage in the manure pit and thus unwanted anaerobic

digestion can be remedied through fresh manure digestion,

methane emissions will not be completely avoided as

(methane emissions from) digestate storage will remain

dependent on fertiliser spreading restrictions.

Methane production in the digester is given as a function of

temperature in Fig. 4. An increase in methane production

0 5 10 15 20 25 30 35 40Temperature [°C]

0

2

4

6

8

10

12

Met

hane

pro

duct

ion

[kg

[CH

4] m-3

man

ure]

0

0.02

0.04

0.06

0.08

Hyd

roly

sis

cons

tant

[d-1

]Methane productionHydrolysis constant

Fig. 4 e Effect of temperature on both the methane

production in the digester and hydrolysis constant as

implemented in the model.

Table 3 e Sensitivity analysis regarding the influence of varioudigester by decreasing and increasing the selected parameter

Parameter p Reference value Unit �10%[kg [CH4] m

�3

XC,in 110 [kg [COD] m�3] 9.10 (�10

Temperaturea 37 [�C] 9.43 (�7%

Retention time 25 [d] 9.66 (�4%

pCH4,d 65 [kPa] 10.11 (þ0

kh37 0.06 [d�1] 9.67 (�4%

kd37 0.02 [d�1] 10.10 (�0

a Temperature change in �C (10% of 37 �C).

from 0 �C to about 35e37 �C is followed by a steep decrease till

almost negligible at a temperature of 42 �C. Methane produc-

tion can almost be completely explained through the hydro-

lysis constant, as the same trend can be noticed if the

hydrolysis constant is displayed as a function of temperature

(Fig. 4). However, high Henry constants will induce a faster

decrease in methane gas production at low temperatures

because under these circumstances methane will mainly be

present in the liquid phase. Besides high hydrolysis constants,

low Henry constants and high decay constants will increase

methane production at high temperatures (Supplementary

information D).

The sensitivity of methane production in the digester to

influent characteristics (organic content), operating param-

eters (temperature, retention time, methane partial pres-

sure) and model parameters (hydrolysis constant at 37 �C,decay constant at 37 �C) is summarised in Table 3. A changing

ingoing organic content had a large effect on methane pro-

duction. In practice, the ingoing organic content of manure

has a strong variability, ranging from 80 to 128 kg [COD] m�3

manure (Martin, 2003). Defining an accurate value will thus

be crucial to dimension the digester correctly and avoid

overloading. A 10% deviation from the reference retention

time (25 days), which is very common in practice (De

Dobbelaere & Verleden, 2018), led to a 4% change in

s parameters on methane production in the farm-scalevalue by 10% relative to its reference value.

manure]Reference value

[kg [CH4] m�3 manure]

þ10%[kg [CH4] m

�3 manure]

%) 10.11 11.12 (þ10%)

) 10.11 4.73 (�53%)

) 10.11 10.52 (þ4%)

.01%) 10.11 10.11 (�0.01%)

) 10.11 10.50 (þ4%)

.1%) 10.11 10.13 (þ0.1%)

b i o s y s t em s e ng i n e e r i n g 1 8 1 ( 2 0 1 9 ) 1 5 7e1 7 2 165

methane production. Themodel-specific hydrolysis constant

also strongly influenced the methane production. A large

variability in hydrolysis constants is reported in literature (Li

et al., 2013; Myint, Nirmalakhandan, & Speece, 2007;

Pavlostathis & Giraldo-Gomez, 1991; Rosen & Jeppsson,

2006). From Table 3, it is clear that the change in methane

production with changes in parameters is not always linear.

For instance, increasing the temperature with 10% above

37 �C has a larger impact on the methane production than

decreasing the temperature by the same percentage. The

nonlinear dependency of methane production on tempera-

ture is largely explained by the nonlinear effect of tempera-

ture on the hydrolysis constant (Fig. 4). A change in the decay

constant at 37 �C and the partial pressure of methane in the

digester only had a minor effect on the methane production.

3.2. Case study: Flanders

3.2.1. Methane productionThe gross electricity production values of seven dairy manure

mono-digesters with an electrical power of 9.7 kW were

gathered through a survey that was recently conducted by

Inagro, the Flemish research and advice centre in agriculture

and horticulture (De Dobbelaere & Verleden, 2018). The

monthly values provided were converted to annual averages.

Given the average annual ingoing flow of dairymanure, which

varies from farm to farm, the electricity production per m3 of

manure was calculated. Values between 28.4 and 41.2 kWh

m�3manurewere obtained at digester retention times ranging

from 12.4 to 20.9 days (Fig. 5). It seems that a retention time of

25 days is not often achieved in practice although this or

higher retention times are generally recommended (Biogas-E,

2018).

Methane production as a function of the retention time in

the digester (from 12 to 25 days) was also calculated through

model simulations, assuming reference conditions and

including digester methane losses (from leakages, methane

slip and an active overpressure safety device, amounting to

12 13 14 15 16 17 18 19 20 21 22 23 24 25Digester retention time [d]

0

10

20

30

40

50

Ele

ctric

ity p

rodu

ctio

n[k

Wh

m-3

]

0

2

4

6

8

10

Met

hane

pro

duct

ion

[kg

[CH

4] m-3

]

Electricity production surveyMethane/electricity production model

Fig. 5 e Comparison between gross electricity production

values of seven digestion farms obtained from a survey (De

Dobbelaere & Verleden, 2018) and the electricity

production calculated from the simulated methane

production (reference conditions, including digester

methane losses which are 4.4% of the methane production)

and standard conversion factors (a density of 0.657 kg [CH4]

m¡3 (Unitrove, 2018), a conversion factor of 10 kWh m¡3

[CH4] (Banks, 2009) and an electrical efficiency of 30%

(Kasper & Peters, 2012)).

4.4% of the methane production, see Table 2). The

corresponding gross electricity production values were

calculated via conversion factors (Table 2). Methane produc-

tion in the digester, and thus electricity production, increased

with increasing digester retention times (Fig. 5).

The predicted gross electricity production, based on the

model simulation results, closelymatches the values reported

from practice. It can thus be concluded that the model is valid

and that the simulated methane production will be in line

with the methane production from real mono-digesters on

dairy manure.

3.2.2. Net methane emissionsOn a default dairy farm with a manure pit beneath the slatted

floor (scenario 1), 5233 kg [CH4] was emitted during one year

due to long-term storage of manure (Fig. 6). Given a volume of

1825m3manure produced per year and a GWP of 34 kg [CO2,eq.]

kg�1 [CH4] (IPCC, 2013), methane emissions from storage in the

manure pit corresponded to 97.5 kg [CO2,eq.] m�3 manure. This

value lies between the maximal amount of emissions from

slurry calculated by Mara~n�on et al. (2011) and the average

amount defined by Owen and Silver (2015) which are respec-

tively 85.9 and 131.3 kg [CO2,eq.] m�3 manure after recalcula-

tion based on the modified GWP from 25 (IPCC, 2007) to 34 kg

[CO2,eq.] kg�1 [CH4] (IPCC, 2013). Variation in daily methane

emissions (Fig. 7A) canmainly be attributed to the variation in

storedmanure volume (Fig. 7B), as the same trend is obtained.

However, methane emissions changed less or more linearly

than the stored manure volume due to the effect of

temperature (Fig. 7C), which determines the rate of the hy-

drolysis process. Most methane emissions are expected at

long manure storage times (large manure volumes) and high

manure temperatures, as shown in Fig. 3. In practice however,

these conditions mostly do not coincide as long-termmanure

storage mainly occurs in autumn and winter and higher

temperatures typically arise in spring and summer. As a

consequence, higher amounts of methane emissions during

manure storage will be indirectly avoided. Emissions over the

four seasons were about equally divided, with the highest

percentages in winter (27%) and summer (31%) as can be

calculated from Fig. 7A. The equal division again demon-

strates that both stored manure volume and temperature

have a major effect on methane emissions. From the 31st of

August till the 15th of February, manure is stored without any

possibility for field application leading to 30.2 kg [CH4] emis-

sions per cow. Based on the Tier 2 method described by IPCC

(2006), methane emissions from a 168-day storage period

can be calculated given a default value for the maximum

methane producing capacity in Western Europe of 0.24 m3

[CH4] kg�1 [VS] (IPCC, 2006), a methane conversion factor of

19% since manure is stored for more than one month and the

average outside air temperature of Belgium is about 11 �C(IPCC, 2006) and a daily amount of excreted volatile solids of

5.3 kg [VS] cow�1 (VMM et al., 2016). The model results were in

line with the emissions frommanure storage calculated based

on this IPCC methodology, which amounted 27.2 kg [CH4] per

cow.

Annual methane emissions decreased to 3567 kg [CH4]

(Fig. 6), if a shift was made from a conventional manure pit

beneath the slatted floor (scenario 1) to animal

1.Manurepit

2.Externalmanurestorage

3.Digestionfreshmanure

4.Digestionpre-storedmanure

0

5

10

15

20

103 k

g [C

H4] y

-1

Methane production during digestionMethane emissions from storage

Fig. 6 e Overview of the annual methane emissions (from

manure and/or digestate storage) and production [103 kg

[CH4] y¡1] for all four scenarios.

b i o s y s t em s e n g i n e e r i n g 1 8 1 ( 2 0 1 9 ) 1 5 7e1 7 2166

confinements with a solid floor, manure scraper and

external manure storage (scenario 2). This corresponds to a

methane emission reduction of 32%. The stored manure

volume in the external storage was equal to that in the

manure pit (Fig. 7B). However, the manure temperature

(Fig. 7C) in the external storage was assumed lower leading

to lower methane production rates and thus reduced

methane emissions. Daily methane emissions (Fig. 7A)

differed most in summer because of the larger temperature

difference between both manure storage methods. Besides,

the hydrolysis constant varied more by a change in the

higher temperature range (summer) than in the lower one

(winter). The organic content in the external manure stor-

age (Fig. 7D) was generally higher since less conversion to

methane took place at lower temperatures. However, peak

values at the 15th of April and 31st of August remained the

same as these were related to the moments when 5 m3 of

fresh manure entered the empty manure pit or external

manure storage. Hilhorst et al. (2002) put forward a methane

emission reduction of 5e10% due to an average annual

temperature difference of 1e2 �C between these manure

storage methods. A somewhat higher reduction of about

12% was obtained through simulation, given a temperature

difference of 1 �C instead of the previously assumed differ-

ence of 2.5e3.4 �C (results not shown). From the comparison

of these manure storage methods, it can be noted that lower

temperature storage will mitigate methane emissions to

some extent, though still a significant amount of methane

will be released into the atmosphere. On-site measurements

of manure temperatures are recommended, as the deter-

mination of a realistic temperature profile can be crucial to

correctly estimate methane emissions and compare the

impact of different storage types.

Annual methane emissions decreased even further (1512 kg

[CH4]) (Fig. 6) by directly connecting the manure scraper to a

digester and external digestate storage tank (scenario 3). The

externally stored digestate volume (Fig. 7B) is equal to the

manure volume when no digester is implemented (scenario 1

and 2), since restrictions for fertiliser spreading remain valid for

digestate and volume reduction through digestion was

neglected. The digestate temperature was considered equal to

the temperature of manure which was stored in the same way

(Fig. 7C). Emissions were only related to external digestate

storage as freshly collected manure was almost immediately

digested. Because of the desirable conversion of manure to

methane before digestate storage, the initial organic content of

digestate was much lower (Fig. 7D) and therefore less methane

could be released into the atmosphere during external digestate

storage as demonstrated in Fig. 3. A potential methane emis-

sion reduction of respectively 71% and 58% could be reached

compared to default dairy farms with amanure pit beneath the

slatted floor (scenario 1) or with a manure scraper and external

manure storage (scenario 2). The former is in line with the

78.5% reduction found in the meta-analysis of Miranda et al.

(2015). Clemens et al. (2006) demonstrated that methane

emissions reduce significantly if digestion takes place before

storage. At a temperature of 11 �C, methane emissions

decreased by 99% when comparing storage of raw manure to

storage of digestate while at 30 �C this was a reduction of 58%.

Although in this study the retention time in the digester was

somewhat lower (25 days instead of 29 days) and the temper-

ature profile was variable throughout the year, the reductions

seemed to be in the same range.

On dairy farms with fresh manure digestion, not only are

methane emissions reduced but also renewable energy is

produced. Digestion of fresh manure (scenario 3) resulted in

an annual production of about 18454 kg [CH4] (Fig. 6). This

amount of methane could be valorised to about 84 GWh of

electricity, neglecting digester methane losses through leak-

ages, methane slip and an active overpressure safety device.

Methane emissions from digestate storage amounted 8.2% of

the total methane production which lies between the mini-

mum (1.43%) and maximum percentage (10.36%) found by

Liebetrau et al. (2010). Emissions from a whole biogas plant

amount respectively 3.8 and 3.1% of the total methane pro-

duction according to Groth et al. (2015) and Flesch et al. (2011).

The results of Groth et al. (2015) are based on a one-day

measurement in winter while the average annual percent-

age found by Flesch et al. (2011) is calculated based on emis-

sions from a Canadian digestion farm during normal

operation of the digester. The higher percentages in this study

could be attributed to the higher overall temperature which

will induce significantly more methane emissions, as was

shown in Figs. 3 and 7.

Methane emissions are related to both manure and

digestate storage on farms with a digester but without an

adapted stable system for fresh manure collection (scenario

4). Respectively 2210 kg [CH4] and 1420 kg [CH4] was

emitted during manure and digestate storage when manure

was pre-stored in the manure pit for 20 days. Total

methane emissions reduced by 31% compared to a default

dairy farm with a manure pit (scenario 1) since the manure

storage period was shorter and anaerobic digestion took

place after manure storage, resulting in digestate with a

reduced organic content (Fig. 7D). In Fig. 7D, only the

organic content of the digestate is shown while in Fig. 7A

emissions from manure and digestate storage were com-

bined. Methane emissions from fresh manure digestion

(scenario 3) were 58% lower. The digester produced about

17274 kg [CH4] per year (79 GWh of electricity without

digester methane losses) (scenario 4) which is 6.4% less

than when fresh manure was digested (scenario 3). Møller,

Sommer, and Ahring (2004) found that methane production

decreases by respectively 6.6 or 11.9% when dairy manure

is stored for 15 or 30 days at a fixed temperature of 20 �C

Fig. 7 e Dynamic simulation results of a stable with a manure pit beneath the slatted floor (scenario 1) compared to a stable

with a solid floor, manure scraper and external manure storage (scenario 2), a stable with a solid floor, manure scraper,

farm-scale digester and external digestate storage (scenario 3) and a stable with a manure pit, farm-scale digester and

external digestate storage (scenario 4) with (A) the daily emitted methane quantity [kg [CH4] d¡1], (B) the stored manure or

digestate volume [m3] determined by both the ingoing flow [m3 d¡1] which depends on the excretion per animal, and the

fertiliser spreading pattern (outgoing flow [m3 d¡1]) based on restrictions imposed by Flemish legislation, (C) the hydrolysis

constant [d¡1] determined by the manure or digestate temperature [�C] and (D) the composite concentration (organic

content) of manure or digestate [kg [COD] m¡3].

b i o s y s t em s e ng i n e e r i n g 1 8 1 ( 2 0 1 9 ) 1 5 7e1 7 2 167

before it is pumped to the digester. The somewhat smaller

decrease in this study could be attributed to lower tem-

peratures in the manure pit meaning that less methane will

be lost before the manure is pumped to the digester. Since

methane production in the digester and methane emis-

sions from storage respectively increased and decreased by

feeding fresh manure to the digester instead of pre-stored

manure, the implementation of a manure scraper should

be encouraged when installing a digester.

Methane emissions from digestate storage remain sig-

nificant, although they are much lower than those from

manure storage. For example, methane emissions from

digestate storage after fresh manure digestion at a digester

retention time of 25 days (scenario 3) amounted 29% of the

methane emissions from manure storage in the pit (sce-

nario 1). To decrease methane emissions from digestate

storage even further, the storage tank can be made gas-tight

so that it can serve as a post digester, as is already

mandatory in Germany (Federal Republic of Germany, 2014).

If this were the case in Flanders, the 1512 and 1420 kg [CH4]

emitted during external digestate storage (scenario 3 and 4)

could be transferred to the CHP-unit for valorisation,

assuming that the methane concentration is high enough.

This measure could increase the methane production from

both fresh manure (scenario 3) and pre-stored manure

digestion (scenario 4) by about 8%. This increase is much

higher than the 3% increase in summer found by

Weissbach, Engler, and Webeling (2011) as in this study a

digester retention time of 25 days was chosen instead of 40

days, which means that less conversion will take place in

the digester and more methane could therefore still be

emitted during storage of digestate. Making the digestate

storage tank gas-tight will thus have a larger impact on

methane emissions and production in case of lower digester

retention times. If valorisation of methane from digestate

storage would not be possible, a flare can be installed so that

not methane, but the less ecologically harmful carbon di-

oxide is released into the atmosphere.

3.2.3. Overall carbon footprintOn a default dairy farm with a manure pit (scenario 1), 116 kg

[CO2,eq.] m�3 manure were emitted (Fig. 8, Supplementary

1.Manurepit

2.Externalmanurestorage

3.Digestionfreshmanure

4.Digestionpre-storedmanure

0

20

40

60

80

100

120

140

160

180

kg [C

O2,

eq.] m

-3 m

anur

e

Electricity consumptionDigester CH4 losses

N2O from spreading

CH4 from spreading

N2O from storage

CH4 from storage

Fig. 8 e Overall carbon footprint for all scenarios [kg [CO2,eq.] m¡3 manure] based on results from model simulations and

literature (RT ¼ 25 days).

b i o s y s t em s e n g i n e e r i n g 1 8 1 ( 2 0 1 9 ) 1 5 7e1 7 2168

information E and F). Methane emissions from manure

storage were by far the most important factor in the high

carbon footprint with a share of about 80%. Electricity con-

sumption resulted in emissions that were about one ninth of

those from manure storage. The remaining part of the carbon

footprint was induced by manure spreading. External manure

storage (scenario 2) reduced the carbon footprint from the

default dairy farm (scenario 1) by 27%. This reduction is due to

the lower temperature of the externally stored manure and

thus lower methane production rate, as the emissions of

almost all other sources remained equal. Only emissions from

electricity consumption were slightly higher due to the use of

a manure scraper. Fresh manure digestion (scenario 3)

reduced the carbon footprint by 54% compared to the default

dairy farm (scenario 1), which is consistent with the relative

change found by Miranda et al. (2015). The net renewable

electricity production from methane (60 MWh), calculated by

taking into account digester methane losses (leakages,

methane slip, active overpressure safety device) and the

fraction of electricity used for digester operation (Table 2),

could almost entirely meet the electricity demand of the farm

(63MWh), including the use of amanure scraper and electrical

heater. The remainder was complemented with fossil fuel

based electricity, leading to a small contribution of this

emission source to the carbon footprint. Methane losses from

the digester (scenario 3) exceeded the emissions from elec-

tricity consumption in the case of no digester (scenario 1 and

2) since methane is a much stronger greenhouse gas than

carbon dioxide and the electrical efficiency to convert

methane is rather low. Introducing a digester (scenario 3) on

farms which already consist of a solid floor, manure scraper

and external storage (scenario 2) reduced the carbon footprint

by 38%. This reduction is mainly caused by the difference in

emissions from storage of manure or digestate, since the

emissions from electricity consumption in the case of no

digester (scenario 2) were compensated by emissions related

to digester operation (scenario 3). Digestion of pre-stored

manure (scenario 4) reduced the carbon footprint of the

default dairy farm (scenario 1) by 15%. Although renewable

electricity replaced electricity from fossil fuels almost

entirely, a rather low overall reduction was achieved due to

high emissions from both manure and digestate storage as

well as digester operation. Digestion of pre-stored manure

(scenario 4) would be less effective (13%) in the reduction of

the carbon footprint than the scenario in which only a solid

floor, manure scraper and external manure storage are

implemented (scenario 2). However, if digester methane los-

ses could be completely avoided in scenario 4, the ability to

reduce greenhouse gas emissions would be similar. The

elaboration of this carbon footprint analysis can be found in

Supplementary information F.

At first sight, these results seem really positive for the

small-scale biogas industry, as this technology may serve as a

climate protection measure. However, digester methane los-

ses will be case-specific and could change the overall carbon

footprint significantly. In this study, emissions from leakages,

methane slip and an active overpressure safety device were

assumed to be 4.4% of the total methane production. This

percentage will increase rapidly if the digester is not working

well and/or is not properly managed (Bruun, Jensen, Khanh

Vu, & Sommer, 2014). If 10% of the produced methane were

to be lost, as proposed for default value by the IPCC (IPCC,

2006), the maximum reduction potential obtained through

fresh manure digestion (scenario 3) would decrease to 37%

while no reduction would be achieved anymore by digesting

pre-stored manure (20 days) (scenario 4). It is however

b i o s y s t em s e ng i n e e r i n g 1 8 1 ( 2 0 1 9 ) 1 5 7e1 7 2 169

possible that even higher percentages are lost due to poor

maintenance of the equipment or dimensioning of the

digester. The reduction potential of fresh manure digestion

(scenario 3) will be completely offset if digester methane los-

ses are about 22% of themethane production. Besides digester

methane losses, digester retention time will also have an ef-

fect on the overall carbon footprint. If farmers have a digester

with an effective volume of 125 m3 but house more than 70

cows, more than 5 m3 of manure will be daily sent to the

digester, which will result in a lower retention time. The

retention time will for example decrease from 25 days to 20

days if the daily ingoing flow changes from 5 to 6.25 m3 of

manure because 89 cows are housed. The decrease in reten-

tion timewill lead to a decrease inmethane production perm3

of manure and therefore more methane can still be emitted

during external digestate storage (Supplementary information

E and F). Although the absolute amount of methane lost dur-

ing digestate storage will increase and the carbon footprint

per m3 of manure will remain the same on farms with no

digester (scenario 1 and 2), freshmanure digestion (scenario 3)

will still be able to reduce the carbon footprint from a default

dairy farm (scenario 1) by 51%, assuming a good working

digester with a retention time of 20 days. The overall carbon

footprint reduction remained rather high, even though the

digester retention time decreased, as at lower retention times

(and thus higher ingoing flows), digester methane losses per

m3 of manure will be lower. However, if the retention time

would decrease further to 14 days (128 cows), the reduction

potential by fresh manure digestion (scenario 3) would

decrease to 47% and 0% given that digestermethane losses are

respectively 4.4% and 24.6% of the methane production. Thus,

in order to keep the reduction potential as high as possible,

constructors should fine-tune the digester dimensioning and

inform farmers about the different control procedures and

working mechanisms of the reactor so that they can manage

their digester in a proper way. Furthermore, electricity con-

sumption and the stored volume profile (Fig. 7B) will vary from

farm to farmdepending on its size and activities. Nonetheless,

realistic deviations of the assumed values will probably affect

the overall carbon footprint only slightly. Finally, the effect of

using digestate as a fertiliser instead of artificial fertilisers was

not included in the overall carbon footprint analysis as cur-

rent legislation still does not recognise digestate from diges-

tion of manure as a worthy replacement (European

Parliament, 2013). However, if this were to be the case due to

a proven similar nutrient use efficiency, the polluting pro-

cesses to create artificial fertilisers for soil management could

be abated to some extent, leading to a further reduction in

carbon footprint.

From the emission point of view, the production of

renewable electricity by farm-scale digesters will be bene-

ficial over the production of fossil fuel derived electricity as

also emissions from manure storage are diminished.

Avoided emissions from fossil electricity use and manure

storage amounted about 209.1 ton [CO2,eq.] y�1

(Supplementary information F), given a digester with a

retention time of 25 days in which fresh manure is digested

(scenario 3). In contrast, emissions related to the electricity

production from methane, including emissions caused by

methane slip, leakages, an active overpressure safety

device and storage of the end product, amounted about

94.7 ton [CO2,eq.] y�1 which is approximately two times

lower than emissions related to the production of fossil

fuel derived electricity and manure storage. This ratio can

be even further increased by proper management of the

digester, by increasing the digester retention time, by

decreasing the digestate storage temperature or by making

the digestate storage gas-tight.

4. Conclusions

� A fit-for-purpose anaerobic digestion model was set up

to estimate both methane emissions from storage of

(digested) dairy manure and methane production from

farm-scale anaerobic digestion. The model was based

on the assumption that hydrolysis is the rate-limiting

step during anaerobic digestion of manure and that no

inhibition will take place for the specific case of dairy

manure. The simulation results were in line with fixed

values put forward in literature (calibration) and with

data from practice (validation).

� Methane emissions from storage strongly depended on

temperature, (open) storage time, ingoing organic con-

tent and the hydrolysis constant. The lower these will

be, the less methane will be emitted. Methane produc-

tion depended largely on the ingoing organic content,

which is higher for fresh manure.

� Methane emissions from storage were about equally

divided over the seasons, given that large stored

volumes (autumn and winter) and high temperatures

(spring and summer) mostly do not coincide.

� The overall carbon footprint of dairy farms was calcu-

lated by complementing simulated methane emissions

with emissions related to electricity consumption,

digester operation and fertiliser spreading. Values for

the latter were determined based on literature. The

Excel tool to calculate the overall carbon footprint was

made available for other researchers and practitioners.

� Methane emissions from storage take the largest share

in the overall carbon footprint of dairy farms, up to over

80% for open manure storage under relatively warm

conditions and without controlled digestion.

� Strategies to lower methane emissions from storage

are: to lower the temperature by storing manure

externally, to decrease the organic content of manure

through digestion and to reduce the stored manure

volume by feeding fresh manure to the digester, for

example bymeans of amanure scraper. Emissions from

digestate storage can be significant and need to be

avoided by implementing gas-tight digestate storages.

� Correct dimensioning of the digester is a prerequisite

given that lower manure retention times in the digester

result in more methane emissions and will increase the

carbon footprint. Digester methane losses should be

limited by proper management and maintenance.

� Overall, when following the above recommendations,

farm-scale manure digestion could significantly reduce

(up to over 50%) the overall carbon footprint of dairy

farms.

b i o s y s t em s e n g i n e e r i n g 1 8 1 ( 2 0 1 9 ) 1 5 7e1 7 2170

Acknowledgements

This research was supported by the LA Project Pocket Power

(150913), funded by Flanders Innovation and Entrepreneur-

ship (VLAIO, http://www.vlaio.be). Bart Ryckaert and Jan

Leenknegt are acknowledged for their practice-oriented

feedback as project partners. The authors thank Dr. Matthijs

Daelman for his valuable comments and suggestions. In�es

Verleden is acknowledged for providing additional data from

practice.

Appendix A. Supplementary data

Supplementary data to this article can be found online at

https://doi.org/10.1016/j.biosystemseng.2019.02.005.

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