PREFACE This report is the result of my graduation ... - Archief IVEM

PREFACE
This report is the result of my graduation research project at KEMA Gas Consulting & Services
in Groningen, for my Master program “Energy and Environmental Sciences”, affiliated to the
faculty of mathematics and natural sciences at the University of Groningen, the Netherlands. The
reported research is the graduation thesis, conducted during the period between March 2010 and
September 2010.
I worked together with fellow student and intern Lukas Grond at KEMA, to determine the costs
and energy use throughout the green gas chain. Similarities could therefore occur in his report and
this one.
I would like to thank Harm Vlap for offering me this research opportunity and his supervision at
KEMA. I enjoyed the weekly meetings where we discussed the progress and results at a down-toearth
way and with humor. I also would like to thank Henk Moll and Sandra Bellekom for their
supervision at the university. A word of thank to Henk Moll for his scenario teaching, and Sandra
Bellekom for her quick replies to my drafts. My appreciation goes to those who were willing to
help me with this research by taking time for an interview and/or discussion: Harm Vlap, Johan
Holstein, Rob van Ommen, and Janneke van Wingerden at KEMA. I also would like to thank my
parents for their faith in me. Last but not least, I would like to express my gratitude to Lukas
Grond, with whom I enjoyed working as interns at KEMA. You helped me at lot with your technical
process explanations, discussions about green gas and your great sense of humor.

GLOSSARY
CH4 Methane
CO2 Carbon Dioxide
CRF Capital Recovery Factor. The CRF gives the annual capital cost based on an annuity,
resulting from the investment, by including interest rate and economic lifetime.
Eq. Equivalent
GHG Greenhouse gas
Green gas A bio-based gas with the quality of natural gas. In this research, biogas from anaerobic
digestion of manure and maize silage is used as a bio-based gas. This is
upgraded to the quality (composition) of natural gas.
IRR Internal Rate of Return; presents the interest rate (in %) to reach the break-even
point.
MCDA Multi Criteria Decision Analysis
MEA Mono-ethanolamine. Chemical scrubbing absorbent in the liquid scrub upgrading
technique.
MJ Mega Joule. In this research, MJ refers to thermal MJ.
N Nitrogen
N2O Nitrous oxide
Natural gas In this research, natural gas refers to natural gas of Groningen quality.
Nm 3 Normal cubic meter. Normal means normal conditions: 0 o C and 1 bar of pressure.
NPV Net Present Value; indicates how much value (in €) an investment will add, or
not.
PP Payback Period

SUMMARY
The use of fossil fuels has environmental consequences, which drives developments in bioenergy.
For the Netherlands, green gas is a potential, new emerging form of bio-energy. Generally,
green gas is anaerobic digested biomass upgraded to natural gas quality. The source for biogas
production by anaerobic digestion is organic material, for which currently manure is used,
enriched with maize silage. The produced biogas has a different composition than that of natural
gas, so upgrading is required. Among the most commonly used upgrading techniques are the liquid
scrub and water wash, which are considered in this research. The then produced green gas
could be injected into the natural gas grid, currently being the distribution grid and regional grid.
At the moment a nationwide discussion is going on about the sustainability of renewable energy.
Sustainability is, and sustainable bio-energy systems are, based on three aspects: the environmental,
economic and social demands, also known as People, Planet and Profit. The sustainability
of bio-energy is important since unsustainable bio-energy production could negatively influence
the image of biomass as a sustainable energy carrier, and hence hinder further development.
Therefore, this research raises the question to what extent green gas is sustainable.
The green gas production chain analyzed in this research includes all steps from biomass production
to green gas injection in a natural gas grid. The disposal of and emissions resulting from the
production of capital goods are not included.
The sustainability of green gas production is assessed by the use of scenarios. First, an assessment
is made per aspect of sustainability. For the environmental sustainability, the indicators CO2,
CH4, and N2O emissions are used, expressed in global warming potential as grams of CO2equivalents
per Mega Joule. For the economic sustainability, the Net Present Value, Internal Rate
of Return and Payback Period are calculated, and costs are expressed in Euros per Mega Joule.
The social aspect is expressed in a single index based on employment and competition with food.
The highest environmental and social sustainability is found when a biomass composition of 50%
manure – 50% maize silage is used as input. For economic sustainability large biogas production
capacity shows the best results.
Subsequently, the environmental, economic and social aspects of sustainability are related to each
other by use of normalization. In doing so, each aspect is considered to be of equal importance.
Trade offs are found when the biomass composition is changed from 90% manure – 10% maize
silage to 50% manure – 50% maize silage, where better environmental and social results come at
higher economic cost. The increase of biogas production capacity leads to somewhat better environmental
results at a higher cost for the economic and social aspects. When digestate is processed,
social benefits come at higher economic cost.
From the studied scenarios in this research, it can be concluded that the most sustainable green
gas chain has a result of 1.8 on an index scale between 0.0 and 3.0. Moreover, the most sustainable
green gas chain has a configuration with a biomass composition of 50% manure – 50%
maize silage, liquid scrub upgrading and large biogas production capacity. The differences between
the location of the digester, being de-central or central, and the way digestate is used are
too small to draw a valid conclusion, considering the sensitivity of used input parameters. Furthermore,
the total results of each scenario are dependent on the gas yields of manure and maize
silage, the maize silage price and the investment period.
This research is based on a limited set of indicators. Including more indicators could influence the
conclusion. Furthermore, the scenarios represent the current situation of the green gas chain in the
Netherlands. These are not necessarily representing optimal configurations. Further research is
recommended for both aspects.

SAMENVATTING
Het gebruik van fossiele brandstoffen heeft gevolgen voor het milieu. Dit vormt een stimulans
voor het ontwikkelen van groene energie. In Nederland is groen gas één van de nieuw opkomende
vormen van groene energie. Groen gas is het product van anaerobe vergisting van biomassa dat is
opgewaardeerd tot aardgaskwaliteit. Op dit moment wordt mest en maïs gebruikt als input voor
de vergisting. Het geproduceerde biogas heeft een andere gassamenstelling dan aardgas, waardoor
opwerking noodzakelijk is. Twee veel voorkomende technieken hiervoor werken op basis
van water en op basis van een chemisch absorptiemiddel. Het hiermee geproduceerde groen gas
kan in het aardgasnet worden geïnjecteerd. Op dit moment worden het distributienet en het regionale
net hiervoor gebruikt. Momenteel wordt er landelijk een discussie gevoerd over de duurzaamheid
van groene energie. Duurzaamheid is, en duurzame energiesystemen zijn, gebaseerd op
drie factoren: milieu, economische en sociale vereisten, tevens bekend als People, Plant, Profit.
De duurzaamheid van groene energie is belangrijk omdat niet duurzame groene energie het imago
van biomassa als duurzame energie drager kan beschadigen en zo verdere ontwikkelingen kan
belemmeren. Dit rapport onderzoekt daarom de duurzaamheid van groen gas.
In dit onderzoek is de groen gas-keten geanalyseerd. Deze keten omvat alle stappen van biomassa
productie tot groen gas injectie in het aardgasnet. Het verwijderen van en emissies afkomstig uit
de productie van kapitaalgoederen zijn niet meegenomen in de analyse. De duurzaamheid van
groen gas productie is bepaald middels scenario’s. Eerst is de duurzaamheid van elke factor afzonderlijk
uitgedrukt met indicatoren. Voor milieu zijn de indicatoren CO2, CH4, and N2O gebruikt,
uitgedrukt in het potentieel voor klimaatverwarming in gr. CO2-equivalents per megajoule.
Voor de economische duurzaamheid zijn de netto contante waarde, de interne opbrengstvoet en
de terugverdientijd berekend, en zijn als indicator de kosten uitgedrukt in euro's per megajoule.
Het sociale aspect is uitgedrukt in een index die gebaseerd is op werkgelegenheid en concurrentie
met voedsel. De beste uitkomsten voor de milieu- en sociale factoren worden bepaald door het
gebruik van een biomassa samenstelling van 50% mest en 50% maïs. Economisch gezien is een
grotere schaal van biogas productie voordelig. Vervolgens zijn de milieu, economische en sociale
aspecten aan elkaar gekoppeld door de uitkomsten te normaliseren en op te tellen. Hierbij is elke
duurzaamheidaspect van gelijk belang geacht. Er is een wisselwerking tussen de milieu- en sociale
aspecten enerzijds en de economische anderzijds bij het veranderen van de biomassa samenstelling
van 90% mest – 10% maïs naar 50% mest – 50% maïs. Een hogere biogas productie capaciteit
leidt to wat lagere kosten, terwijl de milieu en sociale aspecten inleveren aan duurzaamheid.
Bij het verwerken van digestaat, het residu na vergisting, tot kunstmest komen sociale voordelen
met hogere kosten.
Dit onderzoek concludeert dat de meest duurzame groen-gas-productieketen een resultaat heeft
van 1.8 op een indexschaal van 0.0 tot 3.0. Deze groen-gas-productieketen bestaat uit, in volgorde
van invloed, een biomassa samenstelling van 50% mest - 50% maïs, een opwaardeertechniek op
basis van een chemisch absorbeermiddel en een hoge capaciteit biogasproductie. Dit is gebaseerd
op de gebruikte scenario’s. Het effect van de locatie van de vergistinginstallatie en de wijze van
digestaat gebruik zijn erg klein in vergelijking met de gevoeligheid van de invoer parameters. De
totale resultaten van de scenario’s zijn afhankelijk van de gasopbrengsten van mest en maïs, de
maïsprijs, en de investeringsperiode.
Dit onderzoek is gebaseerd op een beperkte set van indicatoren. Het gebruik van nog meer indicatoren
kan invloed hebben op de getrokken conclusie. Verder zijn de scenario’s gebaseerd op de
groen gas-keten zoals deze op dit moment in Nederland is ingericht. Dit zijn niet noodzakelijkerwijs
optimale configuraties. Deze punten worden aanbevolen als onderwerpen voor verder onderzoek.

TABLE OF CONTENTS
1 Introduction......................................................................................................................................... 7
1.1 Problem formulation.................................................................................................................... 7
1.2 Research outline .......................................................................................................................... 8
2 Methodology...................................................................................................................................... 11
2.1 System design............................................................................................................................ 11
2.2 Scenarios ................................................................................................................................... 12
2.3 Indicators................................................................................................................................... 15
2.4 Interpretation ............................................................................................................................. 17
2.5 Summary ................................................................................................................................... 18
3 Environmental aspect ....................................................................................................................... 19
3.1 Inventory ................................................................................................................................... 19
3.2 Assessment ................................................................................................................................ 20
3.3 Summary ................................................................................................................................... 22
4 Economic apsect................................................................................................................................ 23
4.1 Inventory ................................................................................................................................... 23
4.2 Assessment ................................................................................................................................ 23
4.3 Summary ................................................................................................................................... 25
5 Social aspect....................................................................................................................................... 27
5.1 Inventory ................................................................................................................................... 27
5.2 Assessment ................................................................................................................................ 28
5.3 Summary ................................................................................................................................... 30
6 Interpretation .................................................................................................................................... 31
6.1 Comparison ............................................................................................................................... 31
6.2 Combination.............................................................................................................................. 32
6.3 Validation.................................................................................................................................. 33
6.4 Summary ................................................................................................................................... 35
7 Conclusion & Discussion .................................................................................................................. 37
7.1 Conclusion................................................................................................................................. 37
7.2 Discussion ................................................................................................................................. 38
7.3 Recommendations for further research...................................................................................... 40
References ................................................................................................................................................... 41
Appendices .............................................................................................................................................. 47
1. Gas composition............................................................................................................................. 48
2. Upgrading techniques..................................................................................................................... 49
3. General input calculations.............................................................................................................. 50
4. Environmental data inventory & calculation.................................................................................. 52
5. Economic data inventory & calculations........................................................................................ 57
6. Social data inventory & calculations.............................................................................................. 61
7. Compression calculation ................................................................................................................ 64
8. Total results.................................................................................................................................... 66
9. Normalized results ......................................................................................................................... 67
10. Sensitivity analysis......................................................................................................................... 68

1 INTRODUCTION
1.1 Problem formulation
The use of fossil fuels has environmental consequences, which drives developments in bioenergy.
However, bio-energy is not sustainable per se (Buchholz et al., 2009; Cherubini et al.,
2009; Jury et al., 2010). For the Netherlands, green gas is a potential, new emerging form of bioenergy
(Welink et al., 2007). Generally, it is anaerobic digested a biomass upgraded to natural gas
quality. Currently there is a nationwide discussion going on about the sustainability of renewable
energy (Bekkering et al., 2010). Therefore, this research raises the question to what extent green
gas is sustainable.
Sustainability is "meeting the needs of the present generation without compromising the ability of
future generations to meet their needs" (World Commission on Environment and Development
(WCED), 1987). Sustainability is, and sustainable bio-energy systems are, based on three aspects:
economic, environmental and social demands (United Nations, 2005), also known as People,
Planet and Profit (Cramer, 2007). Although sometimes technology is included as a fourth aspect
of sustainability (La Rovere et al., 2010; Wang et al., 2009), its indicators b are included under
environment in case of three aspects. Therefore, the most commonly accepted definition based on
three aspects is used (Buchholz et al., 2009).
‘Green gas’ is a bio-based gas with the quality of natural gas. Green gas can be either upgraded
biogas or Synthetic Natural Gas (SNG). Upgraded biogas is produced by anaerobic digestion
(from here on referred to as digestion) of waste water, fermentation of organic waste at landfills,
or digestion at farms of manure possibly enriched with co-products. The principle behind SNG is
gasification of biomass (Welink, 2007; Zwart, 2006). Since SNG is currently in its experimental
phase of development and (co-)digestion has the highest green gas potential in the Netherlands,
this research will only focus on the (co-)digestion biogas route (Wempe et al., 2004; Bekkering et
al., 2010; CBS, 2009).
The source for biogas production by anaerobic digestion is organic material. Currently manure is
used, enriched with biomass. All organic matter can be digested, except for woody materials
(Appels et al., 2008). The fermented residue is called digestate. The disposal of digestate is,
among others, a key concern for the production of biogas and, consequently, green gas (Gebrezgabher
et al., 2009). In the Netherlands, when the digestion is based on at least 50 (weight)
percent manure and the co-products are listed on the so-called “white list” or “positive list”, the
digestate is considered as manure. Then, it is to be used like manure, namely, among others, as a
fertilizer.
Biogas has a different composition than natural gas, and can therefore not instantly be used as
green gas. The main components that are not in accordance with natural gas are CO2, H2S, NH3,
nitrogen and siloxanes. c The gas composition is important, since differences have consequences
on the combustion process at end users (Polman, 2007; Wellinger & Lindberg, 2001).
Therefore, upgrading is necessary to meet natural gas quality. This consists of removal of the
mentioned components and other contaminants like siloxanes. Techniques that could be used are
(vacuum) pressure swing adsorption, water wash, liquid scrub, cryogen and membranes (Bekker-
a Anaerobic digestion is the process of the breakdown of biodegradable material by micro-organisms in the
absence of oxygen, with biogas and digestate (the residue) as output.
b Generally focused on energy performance of the system.
c An overview of the compositions of biogas and natural gas (of Groningen quality) is given in appendix 1.
7

ing et al., 2010; Zwart, 2009). The liquid scrub and the water wash are among the most widely
used techniques (Petersson & Wellinger, 2006)
The green gas produced can be injected into one of the three different natural gas grid types, being
the distribution grid at 8 bar of pressure, the regional grid at 40 bar, or the high pressure grid
at 67 bar. Currently, green gas is generally injected into the distribution grid. Recently, one location
in the Netherlands established green gas injection into the regional grid.
Research on green gas so far focused on technologies for green gas production (e.g. Wempe et al.,
2007), potential estimations (e.g. Koppejan et al., 2009), possible use of green gas (e.g. Welink et
al., 2007), gas compositions (e.g. Polman, 2007), and economics of green gas production (e.g.
Gebrezgabher et al., 2010).
What has not been addressed is the sustainability of green gas (Pöschl et al., 2010). The sustainability
of bio-energy is important since unsustainable bio-energy production could negatively influence
the image of biomass as a sustainable energy carrier, and hence hinder further development
(Cramer, 2006).
Therefore, the main question of this research is which green gas production route is the most sustainable.
1.2 Research outline
The aim of this research is to assess the sustainability of the green gas, through the comparison of
differently organized green gas chains in scenarios, by presenting the benefits and burdens
throughout the chain and indicate trade-offs between the three aspects of sustainability.
The green gas chain in this research is defined from biomass production to injection into the natural
gas grid. This research is limited to cattle manure digestion and co-digestion based on a biomass
composition of manure and maize silage, like in Pöschl et al. (2010); Urban et al. (2009);
Walla & Schneeberger (2008). The use of fertilization for the cultivation of maize silage is included,
by applying chemical fertilizer and processed digestate. Also unprocessed digestate is
assessed.
A Multi-criteria Decision Analysis (MCDA) will be used for interpretation of the results. By presenting
the relative results, arbitrary weighting factors are avoided.
This research is a static assessment of the sustainability of green gas production in the Netherlands,
based on the most recent developments.
Based on the most commonly accepted definition, sustainability is defined by environmental,
economic and social aspects (Buchholz et al., 2009). For this research environment is defined by
the greenhouse gas (GHG) balance (based on CO2, CH4, and N2O) , and the use of chemical fertilizer;
economics is defined by the Net Present Value (NPV), Internal Rate of Return (IRR) and
Payback Period (PP); social demands are defined by food competition and job creation.
Sub-questions
− What are the environmental consequences of green gas production, throughout the chain?
o What is the GHG emission balance?
o What are the environmental effects of the use of chemical fertilizer?
− What are the economic consequences of green gas production, throughout the chain?
o What is the Net Present Value of a green gas chain?
o What is the Payback Period of a green gas chain?
− What are the social consequences of green gas production, throughout the chain?
8

o To what extent does green gas production compete with food?
o To what extent does green gas production create new jobs?
− How can the environmental, economic and social consequences be related to each other?
o Where are the benefits and burdens throughout the chain for the three aspects of sustainability?
o Can trade-offs be identified between the aspects, and, if so, what are those trade-offs?
In the next chapter, the integral methodology is given. The system design and scenario development
are described, the various indicators are more extensively explained, and the use of the
multi criteria decision analysis is clarified. In chapter three, the environmental aspects of green
gas production are discussed. Then, in chapter four, the economic aspects of green gas are given.
Here, the data inventory is clarified, the chosen indicators are explained, and the results are given.
Chapter five covers the social aspects of the green gas chain. The three aspects are related to each
other in chapter six. Finally, in chapter seven, this report is concluded with a discussion of the
results and the used method, and the conclusion is drawn.
9

2 METHODOLOGY
This chapter addresses the methodology that is used to assess the sustainability of green gas.
First, the system design is described. Then the scenario set up is explained. Thirdly, a literature
overview that determines the indicators that are used is presented. After that, the use of a multi
criteria decision analysis (MCDA) for interpretation of the result is given. This chapter is concluded
with a short summary.
2.1 System design
The green gas chain in this research is defined from biomass production to injection into the natural
gas grid.
Extensive studies on green gas focus on two types of input for digestion, being maize silage and
cattle manure (Pöschl et al., 2010; Urban et al., 2009; Zwart et al., 2006; Walla & Schneeberger,
2008). For maize silage production, cultivation and harvest are included. For manure, cattle manure
available in sheds is used as a source for digestion.
Depending on the location of the availability of the biomass, transport is required to the digester.
The produced biogas is upgraded to natural gas quality. The green gas can then be injected into
the natural gas grid.
Besides biogas a residue called digestate is produced. The disposal of digestate is a key concern
for the production of biogas and, consequently, green gas (Gebrezgabher et al., 2009; Poeschl et
al., 2010). Since maize silage is on the so-called "white list" or "positive list", the digestate may
be treated as manure. Therefore, the digestate can be used like manure to be spread on the fields,
or it can be processed to a replacement for chemical fertilizer. Fertilization during the cultivation
of maize silage is included in the system by chemical fertilizer and by the processed digestate.
Nitrogen is the most important element in fertilizer, so the required fertilizer is calculated based
on the nitrogen requirements.
Furthermore, this system design is assessed for the three aspects of sustainability. This system
does not include the emissions from the production of capital goods, like the truck, digester, upgrading
installation, compressor and injection facility. This is the result of a lack of data on the
material requirements for most of these capital goods. d Also the disposal of capital goods is not
included. For the fuels that are used in the chain, being electricity, natural gas and diesel, the full
cycle CO2 emissions are used.
This system design is shown in Figure 2.1.
d For this reason, a full Life Cycle Analysis could not be made.
11

Figure 2.1: System design.
2.2 Scenarios
A spreadsheet model has been developed in which the system as above is modeled. In this model,
data is collected and linked to generate outcomes for all possible chain configurations. However,
numerous chain configurations are possible to assess the sustainability of green gas. Therefore,
scenarios are developed to assess the sustainability of the most commonly used configurations.
The aim of the scenarios is to identify the best overall chain configuration by assessing the aspects
that determine the benefits and burdens of green gas production.
Chain variables
The variables in the green gas production chain are the biomass source, the biogas production
capacity, the upgrading technique (Berglund, 2006; Pöschl et al., 2010; Pertl et al, 2010; Urban et
al., 2009), the grid type injection, the use of digestate (Gebrezgabher et al., 2009), the distances
between the biomass, digester, upgrading installation and injection point (Ghafoori et al., 2007;
Caputo et al., 2005), and the type of transport that is used to cover these distances.
Some of these variables are not independent. The biogas production capacity is related to the grid
type of injection after upgrading, caused by relative low intake capacities in the Distribution Grid.
The distances are linked to the type of transport. Distances in the Netherlands are rather small,
which determines that maize transport is done by truck (Walla & Schneeberger, 2008), manure
12
Sustainability
System boundary
Maize
production
Manure
Spreading
digestate
Chemical
fertilizer
production
Environment Economic Social
Transport
maize
silage
Transport
manure
Transport
digestate
Transport
processed
digestate
Digestion
Digestate
processing
Transport
biogas
Diesel
Natural
gas (heat)
Upgrading Injection
Emissions from production of capital goods Disposal of capital goods
Electricity
Primary
energy

transport is also done by truck (Ghafoori et al., 2007), and biogas is transported through a
(HDPE) e pipeline at a pressure of 8 bars f .
As a result of these dependencies, the number of variables to design the scenarios is reduced to
five, being: the biomass source, the biogas production capacity (and hence the grid type injection),
the location of the digester, the upgrading technique, and the use of digestate. These variables
determine the scenarios.
1. Biomass composition
As stated before, extensive studies on green gas focus on two types of input for digestion, being
maize silage and cattle manure (Pöschl et al., 2010; Urban et al., 2009; Zwart et al., 2006; Walla
& Schneeberger, 2008). The biomass composition is assessed by a combination of 90% manure –
10% maize silage and 50% manure – 50% maize silage. In terms of the steps in the system design,
this variable includes maize production, manure, and chemical fertilizer production.
2. Biogas production capacity
Two biogas production capacities of digesters are chosen. The biogas production capacity of 250
Nm 3 biogas/hr g is in line with the average digester size in the Netherlands (Bekkering et al., 2010).
Consequences of scale enlargement (Bekkering et al., 2010) are assessed by 1000 Nm 3 biogas/hr
biogas production capacity. After digestion and upgrading, the green gas is injected into the two
most common grid types, being the Distribution Grid (DG) for the lower biogas production capacity
and the Regional Grid (RG) for the higher biogas production capacity.
Consequently, this variable includes digestion and injection.
3. Digester location
The effect of transport of either manure or biogas is assessed by the location of the digester. Central
digestion means digestion at the point of injection, de-central digestion means digestion at the
farm. In terms of the steps in the system design, this variable includes the transport of manure and
the transport of biogas.
4. Upgrading technique
Two commonly used upgrading techniques are chosen that can be used for the biogas production
capacities, being Liquid Scrub and Water Wash (Petersson & Wellinger, 2009). Furthermore, data
is available for these techniques, which is not the case for all other techniques.
5. Use of digestate
Digestate can be spread untreated or processed to a chemical fertilizer replacement. In the case of
the latter, processing is done at the digester location. The digestate is separated into a liquid and
solid fraction. The solid fraction is treated by drying and composting to create commercial fertilizer
replacement (Pöschl et al., 2010; Veefkind et al., 2009). As a result, this variable includes
digestate spreading and digestate processing.
Each of these five variables is assessed by changing only one variable in comparison to the previous
scenario, to identify the aspects that determine the benefits and burdens of green gas production,
to result in identification of the best overall chain configuration. This results in the scenarios
that are given in Table 2.1.
e
HDPE: High Density Poly-Ethylene, a synthetic that is used for relatively small gas pipelines and can deal
with the composition of biogas.
f
Hence compression is included for biogas transport.
g 3 o
Nm = Normal cubic meter, referring to normal conditions: 0 C and 1 atmosphere of pressure.
13

Table 2.1: Scenario configuration
Scenario Biomass composition Capacity
(manure-maize) (Nm 3 Digester loca- Upgrading Use of diges-
biogas/hr) tion
technique tate
1 90% - 10% 250 (+DG) de-central liquid scrub spread
2 50% - 50% 250 (+DG) de-central liquid scrub spread
3 50% - 50% 1000 (+RG) de-central liquid scrub spread
4 50% - 50% 1000 (+RG) central liquid scrub spread
5 50% - 50% 1000 (+RG) central water wash spread
6 50% - 50% 1000 (+RG) central water wash fertilizer
DG = Distribution Grid; RG = Regional Grid; spread = spreading at the dairy farm; fertilizer = processing
to chemical fertilizer replacement.
Additional parameters
The scenarios are based on a Dutch dairy farm, on an approximated distance of 5 km from an injection
point in the Distribution Grid and 10 km from an injection point in the Regional Grid.
Maize is cultivated at a maize farm located approximately 50 km from the dairy farm h . It is transported
by a 8 ton truck to the dairy farm for co-digestion. The upgrading installation is assumed
to be located at the point of injection. Transport of manure requires quality control to prevent the
spread of diseases (Luesink, 2010). The processed digestate to chemical fertilizer replacement is
used in the area where the maize is cultivated. Consequently, the processed digestate transport
distance is 50 km.
The scenarios are based on additional input values, given in Table 2.2. These values are used for
all three aspects of sustainability. More specific values per aspect are explained in the particular
chapters.
As presented in Table 2.2, there is a large difference in gas yield for manure and maize silage.
The low gas yield of manure is the result of its high water content. Combining the gas yields result
in a requirement of 5.5 ton manure per hour and 0.6 ton maize per hour for a biomass composition
of 90% manure – 10% maize silage and a biogas production capacity of 250 Nm 3 biogas/hr,
while a biomass composition of 50% manure – 50% maize silage requires 1.12 ton manure per
hour and 1.12 ton maize silage per hour for the same biogas production capacity. This calculation
is explained in appendix 3.
Table 2.2: Main input data
Aspect Value Unit Reference
Operational hours/yr 8000 hrs/yr Urban et al., 2009
Maize silage harvest yield 45 ton/ha Walla & Schneeberger, 2008
Manure gas yield 23 Nm 3 biogas/ton Pöschl et al., 2010; Gebrezgabher et
al., 2010
Maize silage gas yield 200 Nm 3 biogas/ton Walla & Schneeberger, 2008;
Pöschl et al., 2010
Energy content biogas 21 MJ/Nm 3 biogas Appels et al., 2008; Wellinger and
Lindberg, 2001.
Energy content green gas i 31.7 MJ/Nm 3 green gas NMa, 2006
Max nitrogen application 170 kg N/ha/yr European Commission, 1991
Manure digestate, % of ton input 70 % Poeschl et al., 2010.
Maize silage digestate, % of ton input 90 % Bermejo & Ellmer, 2010
Processed digestate, % of total digestate
40 % Poeschl et al., 2010.
h It is assumed that the distance between the areas with dairy farms and arable farming is 50 km.
i Equals by definition the energy content of natural gas. For this research, the natural gas quality of Groningen
gas is used. The presented value is the lower value.
14

The result of the scenarios are presented in the different processes in the green gas chain. Table
2.3 explains which steps as mentioned in the system design together form a process.
Table 2.3: Process definitions
Process Steps as mentioned in the system design
Biomass Maize production; manure; chemical fertilizer production
Digestion Digestion
Upgrading Upgrading
Injection Injection
Transport Transport maize silage; transport manure; transport processed digestate; transport biogas
Digestate Digestate processing; spreading digestate
2.3 Indicators
A literature review is given to determine the indicators to assess the performance of each aspect
of sustainability.
Environmental indicators
Little research is done in the environmental consequences of green gas production. The study by
Pertl et al. (2010) is explicitly about green gas production from biogas based on a life cycle approach,
uses the indicators CO2, N2O, and CH4 (Pertl et al., 2010).
From a broader perspective, La Rovere et al. (2010) mention in their research on sustainable expansion
of electricity generation, among others, CO2 and non-CO2 emissions as environmental
indicators. Wang et al. (2009) are more specific by listing CO2, CO, NOx, SO2, and particles
emissions, for a multi-criteria decision analysis in sustainable energy decision making. In particular
for sustainability criteria bio-energy, Buchholz et al. (2009) state in their research that the
most important criterion for the environmental aspect is the greenhouse gas balance (Buchholz et
al. 2009). More specific, Cherubini et al. (2009) use CO2, N2O and CH4 emissions as environmental
indicators for bio-fuels and bio-energy systems.
The effects of emissions of CO2, CH4 and N2O are global warming, (Forster et al., 2007, in IPCC,
2007; Pehnt, 2006) expressed in CO2-equivalents. The conversion factors are presented in Table
2.4. Therefore, the indicators CO2, CH4, and N2O are selected as indicators for the environmental
performance of green gas. The lowest total emissions in CO2-equivalents determine the best scenario.
Table 2.4: Global Warming Potential (Forster et al., 2007, in IPCC, 2007).
Emission Global Warming Potential (CO2-equivalent; time horizon 100 yrs)
CO2
1
CH4
25
N2O 298
Economic indicators
The microeconomic sustainability is the most important economic criterion in an sustainability
assessment of bio-energy (Buchholz et al, 2009). Microeconomics is based on the individual parts
of the economy. This is analyzed by the Net Present Value (NPV) and the Internal Rate of Return
(IRR) concepts as valuation criteria (Gebrezgabher et al., 2009), the two most important criteria
for choosing between investment projects (Osborne, 2010).
The NPV indicates how much value an investment will add, or not. All incoming and outgoing
cash flows (CF) are included in the calculation and are discounted to their present value. The IRR
is similar to the NPV, but now the minimal interest rate is calculated to recover the investment.
Generally speaking, the higher a project's internal rate of return, the more desirable it is to under-
15

take the project. The Payback Period (PP) indicates after how many years profit will be made,
calculated by dividing the investment with the annual net income.
NPV = −I
+
0 = −I
+
I
PP =
Ra
16
n
∑
t=
0
n
∑
t=
0
CFt
( 1+
r)
CF
t
( 1+
IRR)
t
t
Equation 1: Net Present Value (€)
Equation 2: Internal Rate of Return (%)
Equation 3: Payback Period (years)
With: I = Investment (€); CF = Cash Flow (€); r = inflation rate (%); t = time (yrs); Ra = Revenues
per annum.
The best result has the largest NPV, the largest IRR and the smallest PP.
To gain more insight into the aspects that determine the costs and revenues of which the NPV,
IRR and PP are calculated, the scenarios will also be expressed in €/MJ. To calculate the annual
costs, de Hullu et al. (2008) use in their review of upgrading techniques a rather straight forward
calculation, where they do not include the effect of time on the interest rate. Therefore, the more
detailed calculation of Urban et al. (2009) and Karellas et al (2010) is used, based on an annuity j .
The annuity is calculated with the so-called capital recovery factor (CRF), given in Equation 4.
This formula gives the percentage of the investment that has to be paid annually during the economic
lifetime (n) of the facility, dependent on the interest rate (i). The used interest rate is based
on the ‘weighted average cost of capital’ value of 7.8% (Lensink et al., 2010). k
CRF
n
i(
1+
i)
( 1+
i)
−1
= n
Equation 4: Capital Recovery Factor
The scenario with the lowest costs determine the best scenario.
Social indicators
The study of Evans et al. (2010) about sustainability of electricity generation from biomass, states
that food competition is the key social issue to be addressed. La Rovere et al. (2010) only focus
on job creation, which is also mentioned in Wang et al. (2009). Job creation and food competition
are also listed in the review of sustainability criteria by Buchholz et al. (2009). Therefore these
two aspects are used in this research as indicators for the social aspect of green gas production.
Food competition is expressed in terms of land requirement, in m 2 /MJ (Buchholz et al., 2009),
where a lower result is better (La Rovere et al., 2010). Land requirements are the result of the
biomass demand, the size of the installations and the additional land that is needed to spread the
digestate. In other words, the additional land for digestate is the amount of land that is needed
j In an annuity, the repayment of the loan and interest is constant over time.
k Weighted Average Cost of Capital (WACC) is the minimum return that should be earned to satisfy providers
of the capital, or that might be earned by an investment elsewhere. In the Dutch situation it is assumed
to consist of 80% liability at 6% interest and 20% equity at 15% interest. (Lensink et al., 2010; van
Ommen, 2010)

from spreading the digestate at maximum nitrogen levels, minus the land that is available at an
the average dairy farm.
Employment is expressed in seconds of work per MJ, where a higher result is better (Wang et al.,
2009; La Rovere et al., 2010). To obtain one single indicator for the social performance, a social
index Is is set up. First, both aspects are multiplied by a factor to obtain the same unit, based on
the commonly used additive value function (Løken, 2007; Wang et al., 2009; La Rovere et al.,
2010). Employment is multiplied with the cost of work; competition with food is multiplied with
cost for land use. Both factors are based on the Dutch situation. This results in Is being defined as
given in Equation 5.
I s =
α1 f i −α
2
e
i
Equation 5: Social index
With: α1 = average price for arable land (0.25 €/m 2 l ); α2 = average income throughout the green
gas production chain (0.01 €/s m ); fi = total competition with food for scenario i (in m 2 /MJ); ei =
total employment for scenario i (in s/MJ).
The interpretation of the social index is based on both factors separately. However, the scenario
with the lowest overall index is the best scenario.
2.4 Interpretation
Conventional single criteria decision making usually aimed for minimizing costs to maximize
benefits. Growing environmental awareness resulted in including environmental and social considerations
into energy planning. As a consequence multi criteria approaches are increasingly
used. (Pohekar & Ramachandran, 2004). In this research, a Multi-Criteria Decision Analysis
(MCDA) will be used for interpretation of the results. This method is useful because of the multidimensionality
of sustainability (Wang et al., 2009).
The aim of an MCA is to compare and rank different options and to evaluate their impacts based
on the established criteria. As in Life Cycle Assessments, MCDAs often use weighting factors to
avoid conversion into a common unit (Hermann et al., 2007). However, weighting factors are a
subjective expression of relative severity, which make them a matter of controversy (Lundie &
Huppes, 1999).
So, to avoid subjectivity, a common unit should be developed for comparison. Afgan et al (2000)
assess energy systems with sustainability indicators, by normalizing each indicator on the minimal
value of the options under consideration.
Since in this research the indicators that are used to assess the aspects of sustainability are based
on a minimum value as most desirable, each indicator is normalized to its maximum total scenario
value. In other words, the maximum scenario result of each aspect is converted to a value of
1. Without converting the minimal value to zero, the relative size of the results per aspect can still
be compared. Subsequently, these relative results are used to determine trade offs between the
aspects.
For economics the revenues (presented as a negative value) of digestate are subtracted from the
digestate costs, and then normalized. The other aspects only give positive values, so no additional
step is needed.
l Based on average arable land price (January to July 2010), and a CRF (annuity; formula given in Equation
4) based on 30 yrs and 5% interest rate. This results in 2500 €/ha/yr = 0.25 €/m 2 /yr.
m Assumed average income throughout the chain of 36 €/hr = 0.01 €/s
17

To avoid additional weighting factors by determining the best scenario, the best scenario is defined
by the sum of the normalized values of the aspects. By doing so, each aspect is assumed to
be of equal importance of the overall result. Consequently, the best scenario has the lowest result,
while the worst scenario has the highest result, with a maximum value of 3 (3 x 1).
2.5 Summary
The system design of this research includes the green gas production chain, defined from biomass
production to natural gas grid injection. Emissions from the production of capital goods and disposal
of capital goods in general are not included.
Since many configurations are possible, scenarios are developed to assess the sustainability of the
green gas production chain. The scenarios are based on the current state of green gas in the Netherlands.
The parameters in the scenarios, which are all assessed, are: the biomass composition;
the biogas production capacity with corresponding grid type injection; the location of the digester;
the upgrading technique; and the use of digestate.
The indicators that are selected for the environmental aspect are CO2, CH4, and N2O, expressed in
global warming potential as gr. CO2-equivalents. The indicators for the economic aspect are the
NPV, IRR and PP, and, additionally, the costs will be expressed in €/MJ. For the social aspect,
food competition and employment are combined into a single social index. The lowest result is
the best for all three aspects.
The environmental, economic and social aspects of sustainability are related to each other by
normalization, where the maximum scenario result per aspect is given the value 1. Since the
minimum scenario result per aspect is not set as zero, the total relative results can be compared.
18

3 ENVIRONMENTAL ASPECT
In this chapter the environmental aspect of the sustainability of green gas is assessed, to answer
the first sub-question: what are the environmental consequences of green gas production,
throughout the chain? First, the data inventory is described. This is followed by the assessment
where the results of the scenarios are presented. The chapter is concluded with a short summary.
3.1 Inventory
Biomass composition
The data used for emissions from maize cultivation are derived from Zwart et al. (2006) and Meijer
et al. (2008). Data for emissions from manure before it enters the digester is derived from
Broeze et al. (2005). Emissions as a result of diesel consumption for agricultural practices, like
plough and harvesting, are derived from Gerin et al. (2008) and converted to CO2 emissions, by
the full-cycle diesel CO2 emissions, derived from Börjesson (1996). It is assumed that the maximum
allowed level of nitrogen fertilizer is applied for maize production, by chemical fertilizer.
Emissions for the production of chemical fertilizer are derived from Bos et al. (2007) and Cederberg
& Flysjö (2004). In case of chemical nitrogen fertilizer application, N2O emissions are 1%
of the NH3 emissions and they occur according to IPCC (2006) at a rate of 10% of total nitrogen
applied (Cherubini et al., 2009). A reduction of 80% of the ammonia emissions could be achieved
by good agricultural practices (Jury et al., 2010). It is assumed that the Netherlands has good agricultural
practices. Therefore, the NH3 emissions of chemical nitrogen fertilizer are 2% of total
nitrogen n . Furthermore, there are direct N2O emissions from the soil as a result of the use of
chemical fertilizer, at a rate of 1% of the nitrogen in the NH3 (IPCC, 2006). Finally, 0.225% of
total nitrogen applied is emitted to the air as N2O via runoff to groundwater.
Biogas production capacity
The digester emits 1% of the emissions that occur during long term storage, as a result of losses
(Zwart et al., 2006). To heat the sludge in the digester it is assumed that natural gas is used, with a
thermal efficiency of 90%. Heat requirements are derived from Urban et al. (2009). These are
presented there in Euros, and are calculated to heat requirement by their used costs for heat.
Digester location
Values for truck transport of biomass are derived from Berglund and Börjesson (2006), based on
a 16 ton truck, including return trips. Gas pipeline emissions occur in the form of leakage at a rate
of approximately 0.0001% per km (Koornneef et al., 2008 o ; Dienst & Lechtenbohmer, 2009).
Direct emissions from compression to inject in the natural gas grids are 0.03% of the green gas
compressed due to leakage (Koornneef et al, 2008). Indirect emissions of grid injection are based
on the energy consumption for an electricity driven compressor, derived from the formula in Damen
(2007), which are converted to CO2 emissions by the average electricity production emissions
in the Netherlands.
Upgrading technique
Emissions during upgrading occur directly by methane slip and the removal of CO2 from the
treated biogas, and indirectly by its energy consumption (Pertl et al., 2010). Data for the energy
consumption of both upgrading techniques are calculated from Urban et al. (2009). According to
Vlap (2010), these values are more in line with results in practice than the values presented in
Zwart (2009) and Bekkering et al. (2010). The indirect emissions from the consumption of the
n This corresponds with the 2% mentioned by van den Broek, 2000, in Cherubini et al., 2010.
o This article is about Carbon Capture and Storage. To address CO2 transport, it uses data of natural gas
pipelines without adjustments. This data can therefore be used in this thesis.
19

scrubbing liquid (in this research mono-ethanolamine (MEA) is used as scrubbing liquid) in the
liquid scrub are determined by Urban et al. (2009) (for the rate of consumption) and Koornneef et
al. (2008) (for MEA production).
Use of digestate
When manure is used as a fertilizer, NH3 emissions occur according to IPCC (2006) at a rate of
20% of total N applied (Cherubini et al., 2009). Analogously to the argument for chemical fertilizer,
the NH3 emissions of chemical N-fertilizer are 4% of total N. Direct N2O emissions from the
soil as a result of the use of manure as a fertilizer are 2% of the N in the NH3 (IPCC, 2006). Furthermore,
0.225% of total N applied is emitted to the air in the form of N2O through runoff and
leaching to groundwater (Cherubini et al., 2009).
The values for emissions to the air from the soil of manure are used to determine the emissions of
spreading untreated digestate, those of chemical fertilizer are used for processed digestate used
for maize cultivation.
The used input values and calculations are included in appendix 4.
3.2 Assessment
The emissions resulting from the scenarios are given in Figure 3.1. It should be noted that the unit
is CO2-equivalents, for which the CH4 emissions are multiplied by a factor 25 and N2O emissions
are multiplied by a factor 298 (as stated in chapter 2; Table 2.4; page 15).
Figure 3.1: Emissions in the green gas chain for the six scenarios.
Biomass composition
The difference between scenario 1 and 2 shows the impact of change in emissions between a
biomass composition of 90% manure – 10% maize silage and 50% manure – 50% maize silage,
respectively. The total reduction of scenario 2 by 20% relative to scenario 1, is primary (18 percentage
points of the 20) caused by the reduction in digestate, by lower emissions from soil resulting
from the spreading of digestate. This decrease is explained by the higher gas yield of
maize silage than of that of manure. This requires less input volume for the same biogas production
capacity and consequently a lower digestate production. Also the emissions from digestion
are reduced, resulting from a lower heat demand. The emissions from 10% maize silage in sce-
20
gr CO2-eq./MJ
120
100
80
60
40
20
0
scenario 1
scenario 2
scenario 3
scenario 4
scenario 5
scenario 6
digestate
transport
injection
upgrading
digestion
biomass

nario 1 are rather high, resulting from of the high conversion factor from N2O emissions to CO2equivalents.
The change in biomass composition of 10 % maize silage to 50% maize silage, results
in only a doubling of the weight of the maize silage input, which is seen by larger emissions
from biomass and the transport to the digester. These higher emissions from biomass are compensated
by lower emissions from the digester, because of lower heating requirements.
Biogas production capacity
The decrease between scenario 2 and 3 (4% reduction of total CO2-eq. emissions when increasing
biogas production capacity from 250 to 1000 Nm 3 biogas/hr) results from the reduced emissions of
injection and by lower emissions from digestion. This is probably the result of lower heat losses
from the digester, since the total surface of the digester is relatively smaller at higher capacities.
Digester location
The difference between scenario 3 and 4 is de-central digestion and central digestion. This means
either biogas is transported, or manure, respectively. The effect of this change is shown by the
minor increase of scenario 4, relative to scenario 3 (0.5% increase of total emissions in terms of
CO2-eq.).
Upgrading technique
A large increase in total emissions is found between scenario 4 and 5; scenario 5 has 23% higher
total emissions than scenario 4. The difference between the scenarios is the upgrading technique,
changed from liquid scrub to water wash. The high emissions are the result of the purpose of upgrading,
namely, among others, to remove CO2 from the biogas. The liquid scrub technique could
reach a methane level of 100% in the gas; the water wash reaches 97%. Hence, the liquid scrub
has higher CO2 emissions. However, the difference in emissions is mainly caused by CH4 losses.
These are considerably higher for the water wash technique (3%) than when the liquid scrub is
used (0.1%), p which makes the latter more attractive from an environmental point of view. Emissions
resulting from the scrubbing absorbent (MEA) in the liquid scrub technique are very small,
as a result of its reuse.
Emissions resulting from the energy use in upgrading also increase, but this is partly compensated
by lower energy requirements for compression. This is the result of the working pressure of the
upgrading techniques: a liquid scrub operates at atmospheric pressure, while the water wash operates
at 8 bar. The latter reduces the need for compression for injection into the natural gas grid.
Use of digestate
Processing digestate to chemical fertilizer replacement requires much energy per ton of digestate,
and hence high indirect CO2 emissions in scenario 6. When only comparing the emissions from
digestate between scenario 5 and 6, the emissions of processing digestate are fully compensated,
mainly by the reduction in soil emissions of unprocessed digestate. Looking at the whole chain,
the reduction by avoiding the use of chemical fertilizer, a total reduction of 5% is achieved, relative
to scenario 5.
The role of chemical fertilizer ranges from a minimal value of 4.1% in scenario 1, to a maximum
value of 9.7% in scenario 3 (see Table 3.1). In scenario 6 no chemical fertilizer is used, but processed
digestate, so the emissions here are nil. The highest percentage is caused by the lowest total
emissions for this scenario. In absolute terms it can be seen that the emissions per MJ are equal
for scenario 2 to 5. Scenario 1 has a lower maize silage requirement, since here 90% manure –
10% maize silage is used in the digester, resulting in less use of chemical fertilizer. Furthermore,
p Values based on averages from Zwart (2009), Pertl et al. (2010) and Bekkering et al. (2010). See also ap-
pendix 0.
21

it can be seen that the emissions from soil after application are double in their environmental effect
than that of production of chemical fertilizer.
Table 3.1: Share in total scenario emissions of the use of chemical fertilizer.
Scenario 1 2 3 4 5 6
% of total scenario emissions 4.1 9.3 9.7 9.7 7.9 0.0
CO2 emissions from production (gr.CO2/MJ) 1.3 2.4 2.4 2.4 2.4 0.0
N2O emissions from soil after application
(gr. CO2-equiv./MJ) 2.9 5.2 5.2 5.2 5.2 0.0
3.3 Summary
This chapter assessed the first sub-question, about the environmental consequences of green gas
production. The scenario with the lowest total emissions is scenario 3, followed by scenario 4
(0.5% higher total emissions) and 2 (7% total higher emissions than scenario 3). In absolute results,
the greenhouse gas balance varies among the scenarios from 78.4 gr. CO2-equivalents to
102.8 gr. CO2-equivalents per MJ.
Other findings are that benefits of a larger biogas production capacity are hardly noticeable, and
that benefits of digestate processing are the result of the lack of emissions from chemical fertilizer.
The environmental effects of the use of chemical fertilizer is ranging between 4.1% to 9.7%
of the total emissions of its scenario. This is mainly caused by the emissions from soil after application.
Concluding, the lowest environmental impact is found when a biomass composition of 50% manure
- 50% maize silage and the liquid scrub upgrading technique is used.
22

4 ECONOMIC APSECT
This chapter addresses the economic sustainability of green gas. First, the used data is explained.
Then the results of the scenarios are presented. The chapter is concluded with a short summary.
4.1 Inventory
Extensive research into costs of biogas production, upgrading and injection into natural gas networks
has been performed in Germany by the Fraunhofer Institute (Urban et al., 2009). These
data are adjusted to the Dutch situation by adjusting the economic lifetime and biomass prices.
The economic lifetime for investments in green gas is set to 12 years, since the Dutch subsidy
regime for renewable gas lasts this long (Agentschap NL, 2010).
Biomass composition
The Dutch biomass prices are derived from Lensink et al. (2009), Lensink et al. (2010) and Walla
& Schneeberger (2008).
Biogas production capacity
Urban et al. (2009) present data for digesters that handle biomass compositions of 90% manure –
10% maize silage and 10% manure – 90% maize silage. From these data a digester for a biomass
composition of 50% manure – 50% maize silage is calculated by using the average values of both
given digesters.
Digester location
The cost of a typical HDPE gas pipeline is calculated, using data from the publically available
document of Enexis (2009), in which grid expansion is calculated. This results in a cost of 98
€/m, which is confirmed to be used as an approximate value (Vlap, 2010; Holstein, 2010). Investment
costs for compressors are not publically available. These data were analyzed to find a
relation between the capacity and the investment, and between the capacity and the costs per
normal cubic meter of biogas. Based on these relations, the costs for the different capacities are
determined. These figures are rounded and used as indicative values.
Costs for manure and maize silage transport are derived from Walla & Schneeberger (2008).
When manure is transported, it needs to be checked and weighted, costing an additional 1 €/ton
(Luesink, 2010).
Upgrading technique
The costs for the upgrading techniques are derived from Urban et al., (2009).
Use of digestate
Costs for digestate processing are derived from Veefkind et al. (2009), costs for digestate transport
and loading and spreading are derived from Poeschl et al. (2010). The price of processed digestate
is derived from Ahlgren et al. (2010), where it is calculated based on the price for nitrogen
in chemical fertilizer.
The used values and calculations are listed in appendix 5.
4.2 Assessment
The results in Table 4.1 represent the total result of the green gas chain for the different scenarios.
From this table it can be seen that scenario 3, 4, and 5 are economically feasible, because these
NPVs are positive. Consequently, the IRR could be calculated, which is mathematically not possible
for negative NPVs. Scenario 1 has a payback period, but this is very long. Negative payback
23

period values are given, since these are mathematically a solution to the equation, but should be
interpreted that the project would not be paid back by its generated revenues. Concluding, scenario
5 is the best scenario based on the values for the NPV, IRR and PP.
Table 4.1: Results of the indictors for the six scenarios.
Scenario 1 Scenario 2 Scenario 3 Scenario 4 Scenario 5 Scenario 6
NPV (*10 3 €) -322 -1,332 2,613 3,227 4,147 -7,524
IRR (%) not possible not possible 6.9% 7.6% 8.4% not possible
PP (yr) -274 -22 18 15 13 -9
Since the gas revenues are equal per MJ of produced gas for all scenarios, and to interpret the
outcome of Table 4.1 correctly, Figure 4.1 presents the costs more into detail, by giving the costs
per MJ throughout the chain for the different scenarios. As digestate, when processed, gives additional
revenues, these are included as negative cost. In general, this figure shows that the total
costs are mainly determined by biomass, digestion, upgrading and processing digestate.
Figure 4.1: Costs over the green gas chain for the six scenarios.
Biomass composition
The difference between scenario 1 and 2 shows the impact of change in emissions between a
biomass composition of 90% manure – 10% maize silage and 50% manure – 50% maize silage,
respectively. The difference between the two scenarios is caused by the change in biomass. Since
the manure is assumed to be freely available, the price for biomass is low in scenario 1. The price
for biomass in scenario 2 is higher since more maize silage has to be bought. But as a result of the
relative small biogas production capacity, the share of biomass in the total costs remains relatively
small. The largest share of the total cost are accounted by the digester.
Biogas production capacity
By increasing the biogas production capacity from 250 to 1000 Nm 3 biogas/hr, (scenario 2 to 3, respectively)
the total costs decreases strongly (by 20% relative to scenario 2). This is the result of
economies of scale for digestion and upgrading. For digestion the economies of scale are the result
of the investment and heat requirements. For upgrading economies of scale are mainly the
result of the investment.
24
€/MJ
0.025
0.020
0.015
0.010
0.005
0.000
-0.005
scenario 1
scenario 2
scenario 3
scenario 4
scenario 5
scenario 6
digestate
transport
injection
upgrading
digestion
biomass
digestate revenues

Digester location
The difference between scenario 3 and 4 is in the location of the digester, being de-central or central.
As a result, a 2% reduction is seen in scenario 4 relative to scenario 3, caused by a reduction
in transport. This difference is surprising, since manure has a low methane content, and hence
requires much transport for relatively little biogas production. However, for biogas transport,
compression is needed, independent of the distance. Therefore, biogas transport is expensive at
short distances. As a consequence, a small decrease is found when the digester is centrally located.
Upgrading technique
The costs of upgrading when the water wash technique is used, are slightly lower than the costs of
the liquid scrub technique, as shown by the difference of 4% between scenario 4 and 5. This is the
result of lower operational cost for the water wash than for the liquid scrub, which is per MJ more
influential that lower investment of the liquid scrub.
Use of digestate
The difference between scenario 5 and 6 is in the handling of digestate. The costs for digestate
processing to a replacement for chemical fertilizer is significant relative to the total costs. Furthermore,
the revenues of the processed digestate are much smaller than the costs. Consequently,
processing digestate is economically not beneficial. Moreover, since the price of processed digestate
is assumed to be equal to chemical fertilizer, there is no benefit for the cost of biomass.
4.3 Summary
This chapter assessed the second sub-question about the economic consequences of green gas
production. The best economic scenario is scenario 5.
The least costs, or the highest economic sustainability, is mainly caused by a large biogas production
capacity and no digestate processing. In addition, using the water wash upgrading technique
and de-central digestion, scenario 5 has the lowest costs per MJ, followed by scenario 4 and 3. In
absolute terms, the costs of producing green gas vary between 0.016 and 0.022 €/MJ.
For these three best scenarios, the highest NPV is seen, best IRR and shortest PP. Also in terms of
these indicators, the best scenario is scenario 5, with a NPV 4,147 (*10 3 ) €, an IRR of 8.4% and a
PP of 13 years.
Another finding is that manure transport is cheaper than biogas transport on relative short distances.
Furthermore, costs of digestate processing do not outweigh the benefits of avoiding
chemical fertilizer.
Concluding, the lowest economic cost is found when a large biogas production capacity is used
and when digestate is spread unprocessed.
25

5 SOCIAL ASPECT
This chapter addresses the social sustainability of green gas. First, the used data is explained.
Then the results of the scenarios are presented. The chapter is concluded with a short summary.
5.1 Inventory
Biomass composition
The land requirement resulting from the demand for maize silage is calculated by the yield of
maize. The level of employment in agriculture is derived from Bos & van de Ven (1999). They
present a value of 2000 hrs/yr for an arable farm of 80 ha. Based on the land requirement for
maize silage, the employment for maize silage cultivation is calculated.
Biogas production capacity
Data for land requirements for digesters are not found. These are therefore calculated, by determining
the volume of sludge in the digester (based on a density of maize silage of 0,7 ton/m 3 and
a density of manure of 1 ton/m 3 ; and a retention time of 20 days (Appels et al., 2008)), with the
assumption that the radius equals the height of the digester (Grond, 2010). q The employment for
digestion for the different biogas production capacities are calculated from Urban et al. (2009).
Although these data are given in Euros, they are converted to annual employment by the use of
their assumptions for employment cost. Finally, this value is converted to employment in seconds
of work per MJ.
Digester location
Employment for transport is calculated by the transport time. This is done by using the type of
truck that was used in the economic assessment in chapter 4 (maize silage 8t; manure 16t; Walla
& Schneeberger, 2008), and an assumed average speed of 30 km/hr. r An extensive study to the
cost composition of natural gas pipelines is given by Schoots et al. (2010). However, this study
only focuses on steel pipelines. On average, about 1/3 of the costs are for labor. The cost structure
for HDPE (bio)gas pipelines are different, by much lower material costs and lower costs resulting
from right-of-way. Therefore, labor costs for HDPE pipelines are assumed to be 50% of the investment,
at a labor cost of 50 €/hr. Employment for a compressor are assumed to be 40% of the
investment, at 50 €/hr. Data from practice on the injection facility are not publically available.
Therefore, these figures are rounded and serve as indicative values.
Upgrading technique
The land required for upgrading is given by the water wash technique of the company DMT
(DMT, 2009). This technique measures 14m by 6m for 250 Nm 3 biogas/hr, and at a very large biogas
capacity of 4000 Nm 3 biogas/hr is measures 16m by 8m. The latter is used for the scenarios with
1000 Nm 3 biogas/hr production. Due to a lack of data for the liquid scrub technique, the same dimensions
are assumed. These data are also used as indicative for the injection facility. Employment
for upgrading for the different biogas production capacities are calculated from Urban et al.
(2009). Although these data are given in Euros, they are converted to annual employment by the
use of their assumptions for cost of employees. Finally, this value is converted to employment in
seconds of work per MJ.
q 2 V
V = π*r *h. By using r = h, r = 3 . Now r can be calculated, the surface can be calculated with S = πr
π
2
r
Although the actual average speed is probably higher, this low estimation aims to take waiting time at the
farm into account.
27

Use of digestate
For digestate the additional land requirement (as competition with food is defined) is calculated
by the nitrogen levels of the digestate and the maximum level of nitrogen application to the land.
Employment for loading and spreading of digestate is derived from Rohde et al. (2006). From this
data in Euros, it is assumed that the variable cost are only employment costs. By the use of their
used cost for employment, the employment in seconds of work per MJ is calculated.
5.2 Assessment
The results of the social index are given in Figure 5.1. To interpret the social index correctly, results
of employment and competition with food are also included, at the bottom left and right,
respectively. Data and calculations are included in appendix 6.
Figure 5.1: Social index.
Biomass composition
Competition with food resulting from a biomass composition of 90% manure – 10% maize silage
(scenario 1 in Figure 5.1) are mainly determined by the spreading of digestate. The change to a
biomass composition of 50% manure – 50% maize silage results in a much lower competition
28
sec/MJ
0.90
0.80
0.70
0.60
0.50
0.40
0.30
0.20
0.10
0.00
scenario 1
scenario 2
scenario 3
I s
scenario 4
0.06
0.05
0.04
0.03
0.02
0.01
0.00
scenario 5
scenario 1
scenario 6
scenario 2
scenario 3
m 2 /MJ
Social index
0.30
0.25
0.20
0.15
0.10
0.05
0.00
scenario 4
scenario 1
scenario 2
scenario 5
scenario 3
scenario 6
Employment Competition with food
.
scenario 4
scenario 5
scenario 6
digestate
transport
injection
upgrading
digestion
biomass

with food to spread the unprocessed digestate. This is explained by higher gas yields of maize
silage than of manure, so less input volume and hence a lower digestate volume. The competition
with food for biomass increases by a factor two with the change from a biomass composition of
90% manure – 10% maize silage to 50% manure – 50% maize silage.
In scenario 1, biomass digestate account both for the largest shares of total employment. The
change to a biomass composition of 50% maize silage results in a much higher employment requirement,
due to more employment in biomass (due to cultivation) and in transport. The latter is
caused by the higher maize silage requirement. The digestate requires less employment in scenario
2, caused by the lower amount of digestate. However, this does not counteract the increase
of employment in biomass and transport.
Biogas production capacity
The impact of a larger biogas production capacity is assessed by the changes between scenario 2
and 3. The increase in competition with food is caused by more digestate at a higher biogas production
capacity.
Employment per MJ is reduced by increasing the biogas production capacity, mainly at digestion,
upgrading and injection.
Digester location
The influence of de-central and central digestion has no consequences on the competition with
food.
The location of the digester does have an influence on employment, which is higher for central
digestion (scenario 4) than de-central (scenario 3). Employment for truck transport for central
digestion are operationally dependent, while a biogas pipeline for de-central digestion only have
employment in construction.
Upgrading technique
There is no change in competition with food when the liquid scrub (scenario 4) or the water wash
(scenario 5) technique is used, since these are assumed to be equal in size. Furthermore, the share
of the upgrading installation is very small relative to the competition with food of biomass cultivation
and/or digestate spreading.
A reduction in employment is seen between scenario 4 and 5. Employment for upgrading is a
small share in the total per MJ. The consequence of applying the water wash technique is noticed
at employment for injection, since the water wash technique operates at a higher pressure than the
liquid scrub technique and hence less additional compression is needed than when the liquid
scrub technique is used.
Use of digestate
The effect of processing digestate is seen in the difference between scenario 5 (unprocessed digestate)
and scenario 6 (processed digestate). The reduction in competition with food is the result
of less digestate. Even though processed digestate contains higher levels of nitrogen, and hence
influences the amount of additional land required (and therefore competition with food), this does
not compensate the reduction in digestate volume.
Processing digestate influences the employment requirements, mainly by its transport to the
maize farm. Processing digestate requires only a small amount employment. It should be noted
that this is based on a rough assumption.
29

5.3 Summary
This chapter assessed the third sub-question about the social consequences of green gas production.
The best scenario is scenario 6, followed by scenario 2 (29% higher than scenario 6). In absolute
terms, the impact of producing green gas varies between 0.007 and 0.053.
These best index outcomes are the result of high levels of employment and low competition with
food. One trade-off is seen in scenario 1, between the highest level of food competition and the
lowest labor requirement. The explanation is the use of manure, which has less employment and a
high amount of digestate. The latter results in a high additional land requirement, and hence food
competition. Another findings is that economies of scale are socially not beneficial.
Green gas production competes with food production as a result of the use of maize silage and,
more important, the additional land required to spread digestate. Furthermore, it generates the
most employment by using a biomass composition of 50% manure and 50% maize silage, small
biogas production capacity and processing digestate.
Concluding, the lowest social impact, or the highest social sustainability, is mainly caused by a
biomass composition of 50% manure and 50% maize silage and processing digestate.
30

6 INTERPRETATION
This chapter addresses the sub-question about the interpretation of the three aspects of sustainability.
First, the benefits, burdens and trade-offs throughout the chain are assessed, based on the
results of the previous three chapters. After that, the aspects are combined to make an comparison
of the scenarios, to find the best overall scenario. The chapter is concluded with a short summary.
6.1 Comparison
Benefits and burdens
The benefits and burdens of the green gas chain are shown in Figure 6.1, where the normalized
indicator results are presented.
Environmental benefits are found when a biomass composition of 50% manure – 50% maize silage
and the liquid scrub upgrading technique is used. The lowest costs are mainly caused by a
large biogas production capacity and no digestate processing. The highest social benefits are
mainly caused by a biomass composition of 50% manure – 50% maize silage and processing digestate.
So, the biomass composition and the way digestate is used determines benefits (and
therefore also burdens).
The worst environmental result is found in scenario 1, resulting from a biomass composition of
90% manure – 10% maize silage. The highest costs are found in scenario 2. This is explained by
the small biogas production capacity in combination with a biomass composition of 50% manure
– 50% maize silage. The cause for the high result of scenario 6 is found in the high costs for digestate
processing. The highest social burdens are found in scenario 1, where the highest amount
of digestate requires much additional land and therefore a high competition with food.
normalized value
1.0
0.8
0.6
0.4
0.2
0.0
environment
economics
social index
environment
economics
social index
environment
economics
Figure 6.1: Comparison of all normalized indicator results. Exact values are given in appendix 9.
social index
scenario 1 scenario 2 scenario 3 scenario 4 scenario 5 scenario 6
environment
economics
social index
environment
economics
social index
environment
economics
social index
31

Trade offs
A trade-off is defined as benefits from a changing situation for one variable with at the same time
burdens for another aspect. Trade offs are found by using Figure 6.1.
A first trade off is found between scenario 1 and 2. The difference between scenario 1 and 2 is the
change of biomass composition, from 90% manure – 10% maize silage to 50% manure – 50%
maize silage. As a consequence, high environmental and social burdens change to much better
environmental and social results, while the economic aspect increases. This is explained by a
higher biomass price for maize silage, but since maize silage has a much higher gas yield than
manure, the digestate volume decreases significant and hence less additional land requirements
and emissions from spreading. However, the increase in economics is minor relative to the strong
decrease of the other two aspects.
Also the change between scenario 2 and 3 result in a trade off. Increasing the biogas production
capacity results in somewhat better environmental and much better economic sustainability, while
the social index rises strongly. The better environmental and economic sustainability are the result
of a higher efficiency at a larger biogas production capacity, while the higher amount of digestate
causes more additional land requirement en hence a higher social index.
The difference between scenario 4 and 5 is the change from the liquid scrub upgrading technique
to the water wash upgrading technique. Although the latter results in a somewhat higher economic
sustainability, it is less environmentally sustainable.
Between scenario 5 and 6 a trade off is found resulting from the use of digestate. Using digestate
as a chemical fertilizer replacement instead of unprocessed spreading, results in a significant reduction
of the social index, but at cost of the economic aspect. This is caused by the high price for
processing digestate and less additional land requirements, so less food competition.
6.2 Combination
The normalized values of the previous section are combined to generate total scenario results.
This is presented in Figure 6.2. It should be noted that, as explained in the methodology chapter,
additional weighting factors are not used, and each aspect is considered as equal important.
Scenario 1 has the highest combined result, primary caused by the highest (and therefore worst)
environmental and social impact. This implies that a biomass composition of 90% manure – 10%
maize silage is the least sustainable.
Scenario 2 is 31% more sustainable than scenario 1. This means that the trade off between economics
on the one hand and environment and social aspects on the other, as identified in the previous
section, has a positive net effect. So, a biomass composition of 50% manure – 50% maize
silage is more sustainable than a biomass composition of 90% manure – 10% maize silage.
Scenario 3 is 6% more sustainable than scenario 2. It has the best environmental sustainability
and the second best economic sustainability. This scenario is less socially sustainable, but in
terms of the normative index, the social result is lower relative to the environmental and economic
index result. The higher sustainability of scenario 3 compared to scenario 2 implies that a
high biogas production capacity is more favorable.
Scenario 4 is the most sustainable scenario. The total decrease relative to scenario 3 is caused by
the economic aspect and a small social benefit (a total difference of 1% relative to scenario 3). In
other words, there is a minor positive effect of using manure truck transport to a centrally located
32

digester instead of a biogas pipeline. This scenario does not include any of the best results per
aspect.
Scenario 5 has a less overall sustainability (8% higher overall result than scenario 4). This is primarily
caused by the lowest environmental sustainability, although there are some small economic
benefits. This implies that the liquid scrub upgrading technique is more sustainable that the
water wash.
Scenario 6 has a slightly worse overall sustainability than scenario 5 (by 2%). This is explained
by the trade off mentioned in the previous section: the lower social impact of digestate processing
comes at a much higher economic cost. So, the social benefit of processing digestate do not outweigh
the higher economic burden. Consequently, spreading unprocessed digestate is more sustainable.
normalized index
3.0
2.5
2.0
1.5
1.0
0.5
0.0
scenario 1
1.00
0.89
1.00
scenario 2
0.19
1.00
Figure 6.2: Normalized overall results.
0.31 0.30
0.79 0.78
0.80 0.76 0.77
scenario 3
scenario 4
0.94 0.89
Thus, scenario 4 is the most sustainable scenario. This is explained by, in order of importance, the
biomass composition of 50% manure – 50% maize silage (reduction of 31% relative to 90% manure
– 10% maize silage), liquid scrub upgrading (8% relative to water wash), large biogas production
capacity (6% relative to small biogas production capacity), digestate spreading (2% relative
to digestate processing) and the location of the digester (1% in favor of manure truck transport
relative to biogas pipeline transport).
6.3 Validation
A sensitivity analysis is made for several parameters to check whether the used assumptions influence
the results for the best scenario from the previous section.
Within the scenario design, assumptions are made on the distance from the farm to the natural gas
grid (the grid type is included in the biogas production capacity) and the distance of the maize
farm to the digester. Besides, it is assumed that the maize farm has good arable practices. The
social index uses the average income throughout the green gas chain to convert employment to a
unit that is can be related to food competition. The assumed value for average income is therefore
of influence on the social index and hence on the total result. Also the average speed of the truck
is of influence on employment.
Furthermore, parameters that are used for all scenarios are included in the sensitivity analysis.
Several prices are volatile, and consequently influence the results. This counts for the price of
scenario 5
0.30
0.74
scenario 6
0.13
1.00
social
economics
environment
33

natural gas and hence of green gas, the price of chemical fertilizer and consequently for the price
of processed digestate, and for the price of maize silage.
Besides, influencing all results, the investment period in this research is 12 years, as the subsidy
regime requires, but investment periods for (natural) gas pipelines can be 30 years. Finally, the
gas yields from maize silage and manure is of influence on all results.
For these 10 input parameters a sensitivity analysis is made and related to the overall sustainability
index result of the best scenario (no. 4). This is presented in Figure 6.3.
Since the effects of the assumptions of the size of the digester, upgrading installation and digestate
processer are negligible in the results, these are not assessed in the sensitivity analysis.
Figure 6.3: Sensitivity analysis for ten input parameters.
Figure 6.3 shows that the sensitivity six out of ten input parameters is small relative to the overall
result of scenario 4. It should be noted that the x-axis scale is rather large, while the scale on the
y-axis is rather small. The change of the output of scenario 4 is sensitive for six parameters in the
order of -2% to 1%. The explanation for this small influence is that the effect is dampened by the
aspect(s) that are not influenced by the change.
The maize silage price shows, in relation to the other parameters, that the overall result is sensitive
for changes in this value. A higher price has a negative effect on the overall sustainability.
The opposite holds for the investment period: a longer period results in a higher sustainability.
The outcome is most sensitive to the maize silage gas yield. Somewhat higher gas yield result in a
much higher sustainability. These last four parameters to which the results are highly sensitive
play a role in each scenario. Therefore, the overall results are dependent on the gas yields, maize
silage price and investment period.
34
change of overall result (%)
3
2
1
0
-1
-2
-3
-50 -25 0 25 50
change of input value (%)
distance gas grid
distance maize farm
arable practice
average income
average speed truck
investment period
fertilizer price
maize silage price
manure gas yield
maize silage gas yield

Table 6.1: Sensitivity of green gas price on the economic viability.
Change in green gas price s -10% -5% 0% (=scenario 4) 5% 10%
NPV (*10 3 €) -41 1,570 3,227 4,884 6,494
IRR (%) not possible 5.4% 7.6% 9.2% 10.3%
PP (yrs) 95 27 15 11 8
The green gas price is only included in the calculation of the NPV, IRR and PP. The sensitivity of
the green gas price is therefore assessed on these indicators. The results are shown in Table 6.1.
As can be seen, the economic viability is highly sensitive for changes in the green gas price. For a
10% lower total green gas price there is a negative net present value, consequently no internal
rate of return and a very much larger payback period.
6.4 Summary
Benefits for the environmental and social aspect are found when a biomass composition of 50%
manure – 50% maize silage is used. For economics, large biogas production capacity is beneficial.
Trade offs are found between a significant reduction in the environmental and social aspect at
cost of the economic aspect, by the change from a biomass composition of 90% manure – 10%
maize silage to 50% manure – 50% maize silage. A trade off is also identified by the biogas production
capacity increase, where better environmental and economic results are at higher cost for
the social aspect. A third trade off is identified by digestate processing: social benefits come at
higher economic cost.
When the normalized results of each scenario are combined, the best scenario is scenario 4. This
most sustainable green gas chain has a result of 1.8 on an index scale between 0.0 and 3.0. This
scenario does not include any of the best results per aspect. The best scenario has a chain configuration
with, in order of importance, a biomass composition of 50% manure – 50% maize silage,
liquid scrub upgrading, large biogas production capacity, unprocessed digestate spreading and a
centrally located digester is the most sustainable. However, the difference between de-centrally
and centrally located digestion is very small. Moreover, the sensitivity of specific input parameters
is in the same range. Therefore, scenario 3 and 4 are concluded to be the most sustainable
scenarios. However, the total results of all scenarios are dependent on the gas yields of manure
and maize silage, the maize silage price and the investment period.
s The green gas price in this research is the total price for green gas, so the natural gas price plus subsidy.
35

7 CONCLUSION & DISCUSSION
7.1 Conclusion
This paragraph follows the sub-questions, which lead to an answer to the main research question.
The highest environmental sustainability is found when a biomass composition of 50% manure –
50% maize silage and the liquid scrub upgrading technique are used. In absolute results, the green
house gas balance varies among the studied scenarios from 78.4 gr. CO2-equivalents to 102.8 gr.
CO2-equivalents. The environmental effects of the use of chemical fertilizer ranges between 4.1%
to 9.7% of the total emissions per scenario. Although production of chemical fertilizer is energy
intensive, this is mainly caused by the emissions from soil after application.
The highest economic sustainability, is found when a high biogas production capacity is used and
digestate is spread unprocessed. Of less importance to the overall result are the use of the water
wash upgrading technique and de-central digestion. For the best scenario, the highest NPV is seen
(4,147 *10 3 €), best IRR (8.4 %) and PP (13 years). Another finding is that the costs of digestate
processing do not outweigh the benefits of avoiding chemical fertilizer.
The highest social sustainability is mainly caused by a biomass composition of 50% manure –
50% maize silage and processing digestate to chemical fertilizer replacement. Green gas production
competes with food production as a result of the use of maize silage and, more important,
additional land required to spread digestate. Furthermore, employment is generated when a biomass
composition of 50% manure – 50% maize silage is used, at a small biogas production capacity
and the digestate is processed.
Subsequently, the environmental, economic and social aspects of sustainability are related to each
other, by normalizing the result.
Benefits for the environmental and social aspect are found when a biomass composition of 50%
manure – 50% maize silage is used. For economics, large biogas production capacity is beneficial.
Trade offs are found between a significant reduction in the environmental and social aspect at
cost of the economic aspect, by the change from a biomass composition of 90% manure – 10%
maize silage to 50% manure – 50% maize silage. A trade off is also identified by biogas production
capacity increase, where somewhat better environmental results come at high cost for the
economic and social aspects. A third and last trade off is identified by digestate processing: social
benefits come at higher economic cost.
From the studied scenarios in this research, it can be concluded that the most sustainable green
gas chain has a result of 1.8 on an index scale between 0.0 and 3.0. Moreover, the most sustainable
green gas chain has a configuration with a biomass composition of 50% manure – 50%
maize silage, liquid scrub upgrading and large biogas production capacity. The differences between
the location of the digester, being de-central or central, and the way digestate is used are
too small to draw a valid conclusion, considering the sensitivity of used input parameters. Furthermore,
the total results of each scenario are dependent on the gas yields of manure and maize
silage, the maize silage price and the investment period.
37

7.2 Discussion
First the conclusions will be discussed. Then the results of this research are discussed by the used
data, indicators, scenarios and the interpretation method. After that more other considerations are
presented.
Conclusions
Some sub conclusions can be related to other studies.
The conclusion on the environmental sustainability is partly confirmed by the article of Pertl et al.
(2010), which is specifically about the climate balance of green gas production. They conclude
that “GHG emissions from scenarios including digestion of organic waste are less harmful to the
climate than energy production based on renewable agricultural resources” (Pertl et al., 2010; p.
98). This research shows the contrary: GHG emissions of manure (as an organic waste) are the
most harmful to the climate. This is caused by the large share in the total emissions by spreading
the digestate. It is the digestate that is not included in the study by Pertl et al. (2010).
The study of Jury et al. (2010) is a (partial) LCA of green gas production, compared to the environmental
effects of natural gas. They conclude that farming activities have the highest contribution
to climate damages. However, their research does not include direct CO2 emissions from upgrading
and use of digestate, which are indicated in this research as factors that have a large influence
on the conclusion.
The conclusion on the economic sustainability is rather confirmed by the article by Gebrezgabher
et al. (2010). They indicate that a positive NPV for green gas production is the result of the subsidized
green gas price, and that the price of the additional product that is used besides manure in
digestion is an important determinant of the economic success. They also conclude that the choice
of digestate handling is an important factor in the economic success. These findings are in line
with the results of this research.
No references were found to confirm or contradict the results and conclusions for the social aspect
of sustainability and the combination and interpretation of the separate aspects.
Therefore, a strength of this research seems the inclusion of more steps of the green gas production
chain in the system design, the assessment of social sustainability of green gas production
and relating the three aspects. However, as a consequence of insufficient external validation of
the social sustainability and the interpretation, these findings include a level of uncertainty.
Data
In addition to the above stated, due to the lack of data, no margin of error is given for the results.
Furthermore, in this research, the direct energy requirements of compression were used to determine
the emissions. While the energy requirements are the largest at its use phase, this does not
necessarily imply that the largest environmental impact is at its usage (Moll, 1993). Therefore,
more specific data for construction is needed. Additionally, many studies, including this one, use
the study of Urban et al. (2009) because of its specificity. More data at this level of detail is
needed for verification, and could then possibly influence the results. Moreover, particularly for
the social aspect, assumptions are made to assess the sustainability, as a result of data limitations.
Again, more data could help in verification and could result in other findings.
Finally, the economic data used, could be influenced by economic considerations. Since, for example,
the provider of upgrading techniques has commercial interest to promote its own technique,
given data might be too low. On the other hand, economic data from Urban et al. (2009)
might be too high, since all costs (investment and variable costs) of digestion and upgrading are
higher in Germany than in the Netherlands (Vlap, 2010). Both aspects could influence the results
and hence the conclusion.
38

Indicators
In this study, only a limited number of indicators are used per aspect of sustainability. It is argued
that the chosen indicators are the most important for this research. However, there are many more
indicators that could be included, which consequently could influence the results.
For the environmental aspect of sustainability, for instance water consumption is not included.
This is noteworthy since the water wash technique has a high water consumption (Electrigaz,
2008; Reppich et al., 2009). Furthermore, the removal of CO2 from biogas at the upgrading step
could be excluded by considering these emissions as short cyclic. However, when included, this
would not drastically influence the results, since the level of removal is about the same for both
upgrading techniques.
For the economic aspect of sustainability, the revenues are not included in the finally used indicator,
since these are equal in the expressed unit (per MJ). Another indicator could be the size of the
total initial investment, since this could be a barrier to invest in a green gas production chain.
For the social aspect of sustainability, the calculations for food competition fertilization of chemical
fertilizer and digestate (as the additional land requirements) are based on the nitrogen levels.
Although this is a very important aspect, also Phosphorus and Potassium are important nutrients.
Furthermore, including an indicator for animal wellbeing might be interesting, since many cows
are needed for only a small amount of biogas production. Moreover, from a biogas production
point of view, the cows are preferably kept in shed for easy manure collection. Including such
indicators could influence the presented results.
Scenarios
The scenarios of this research are based on the current green gas situation in the Netherlands, and
cover only the most commonly seen configurations. New developments, e.g. in upgrading techniques,
other co-products instead of maize silage, or gas hubs (where several biogas producers
upgrade their gas to green gas), could result is different outcomes.
Also, the scenarios do not necessarily represent the best routing. A best chain configuration is
dependent on site specific elements, like the number of farms in the area that could possibly cooperate
in the green gas production chain, difficulty of pipeline construction (e.g. when (rail)road
crossings are necessary) and exact location of the natural gas grids.
Interpretation
In normalizing the results, no baseline is used. Using a baseline influences the relative changes,
and could hence influence the conclusions. The interpretation of the results did not use additional
weighting factors. It was chosen to consider the three aspects of sustainability of equal importance.
However, there is a vivid discussion about the use of weighting factors. When additional
weighting factors are applied, the aspect with the highest normative result is the most sensitive.
For the most sustainable scenario found in this research, applying additional weighting factors for
the environmental and economic aspect would consequently have the most influence. Additional
weighting factors could be used by the different stakeholders involved in green gas production.
Without the use of weighting factors, the stakeholders could still choose to only consider one or
two aspects of sustainability. For example, from the perspective of the investor, the lowest cost
and highest NPV would probably be chosen. This is scenario 5. In comparison to the overall best
scenario (no. 4), this implies a significantly worse environmental sustainability. In addition, one
could argue to exclude the scenarios that result in a negative NPV, sinces these are not profitable
and might therefore not be realised as such. However, it should then also be noted that the NPV is
very sensitive to changes in the (green) gas price.
39

Other considerations
Although green gas production, as considered in this research, is a bio-energy partly from cattle
manure, this does not prevent emissions from the Dutch dairy production. About 80% of the
methane is already emitted in the gaseous form by the cows themselves (Bos et al., 2007).
Furthermore, the number of cows that are needed for biogas production is high. For instance, the
manure of 220 cows are needed for a biomass composition of 50% manure – 50% maize silage at
a biogas production capacity of 250 Nm 3 biogas/hr. This is due to the low methane yield of cattle
manure. Moreover, biogas production is no solution to the manure surplus in the Netherlands, as
can be seen by the high additional land requirements.
The fluctuating green gas price seems to cause investment uncertainty, since the results are highly
sensitive to this parameter. In addition, the investment period of 12 years is low compared to the
investment periods in natural gas. As the sensitivity analysis showed, this parameter has a high
influence on the overall results. Both aspects could be interesting findings for an evaluation of the
Dutch subsidy regime for green gas.
7.3 Recommendations for further research
Based on the discussion, further research is recommended.
More data is required throughout the green gas chain, to verify the used data. Especially the role
of Urban et al. (2009) is large throughout publications about green gas, since many studies are
indirectly based on these data.
Interesting would be research to a optimal green gas production chain configuration, by looking at
the effect of a green gas hub (central upgrading for several biogas producing farms) and specific
system configurations.
Finally, it would be interesting to compare the results of this research with the use of biogas in a
Combined Heat and Power (CHP) installation and with similar assessments for other (green) energy
carriers.
40

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Ahlgren, S., Bernesson, S., Nordberg, A., Hansson, P.-A. (2010). Nitrogen fertilizer production
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46

Appendices
47

1. Gas composition
The composition of biogas and the composition of natural gas is given in the table below. The
composition of biogas produced by anaerobic digestion is derived from Klaas (2007). The values
given are the typical values; the values between the brackets indicate the range of the component
in the gas. The average values are listed in the table below, with their outer values for these cases
given between the brackets.
The list is completed with values given in the article of Appels et al. (2008).
The composition of Groningen gas is given by DTe (Service of Supervision for Energy) of the
NMa (Dutch Competition Authority), derived from “aansluit- en transportvoorwaarden gas”
(connection and transport conditions for gas). The document is part of the conditions as referred
to in the Dutch gas law. The range of the Wobbe index and specific gas quality values are given.
In some cases higher values are allowed, indicated with their outer value (ov).
BIOGAS t Component Unit
NATURAL GAS
AD G-gas u
Caloric value MJ/Nm 3 Wobbe index MJ/Nm
23 31.67
3 20 43.46-44.41
Methane nr. >130 (ov=>80)
Methane % 57 (55-58)
Sulphur (total) mg/Nm 3 0.9 (ov=45)
H2S mg/Nm 3

2. Upgrading techniques
Upgrading is necessary to meet natural gas quality. Generally, the removal of CO2 results in
higher methane levels and consequently in a higher Wobbe index (Hagen et al., 2001). Furthermore,
biogas has to be cleaned from other contaminants as H2S, NH3, and siloxanes.
Currently five different techniques exist for upgrading biogas to natural gas quality, being: pressure
swing adsorption, membrane, water wash, liquid scrubbing and cryogen.
Vacuum Pressure Swing Adsorption (VPSA)
In this technique biogas is filtered by the use of activated carbon molecular sieves. In these sieves
mainly CO2 is adsorbed, while the methane passes. Lowering the pressure to a vacuum releases
the CO2. This also regenerates the coal, which can be used again at the higher pressure for CO2
adsorption (Zwart, 2009).
Membranes
The continuous biogas flow is split into two different streams by a membrane. This membrane
has a high selectivity for CO2 and a low selectivity for CH4 (Zwart, 2009). This technique is also
currently under development for the removal of H2S (McKinsey Zicari, 2003). Membranes can be
used for biogas capacities up to 2000 Nm 3 biogas/hr.
Water scrubber
The principle of this technique is the higher dissolving rate of CO2 in circulating cold water, than
CH4. The contaminated water is heated to remove the CO2 and can be reused when cooled down.
This technique also removes H2S (Polman et al., 2007), and H2 (IEA, 2004).
Liquid scrubber
The principle of water wash is used here, but with another absorber to improve the separation of
CO2 and CH4. The absorber is an amine solution, like mono-ethanolamine (MEA) (Kapdi et al.,
2005; Reppich et al., 2009). It is a continuous process at a low pressure. Liquid absorption is also
used to remove siloxanes, for example since 1993 at a landfill in Dortmund-Huckarde, Germany
(IEA, 2004). However, siloxane removal is still under research (Polman et al., 2007). This technique
is suitable for plants with a capacity of 160 – 1600 Nm 3 biogas/hr (Dumont, 2009).
Cryogen
The principle of this technique is the lower temperature of CH4 to liquefy (-160 o C), than CO2 (-
78 o C) (Zwart, 2009). Also a combination of high pressure (80 bars) and less extreme temperatures
(-45 o C) are used (Kapdi et al., 2005). It can either be used in batches or continuously. This
technique is expected to become viable in the near future, because of its low energy requirements
(Schenk, 2007). Moreover, CO2 is captured in its liquid phase and highly pure, which make it
possible to be marketed (Reppich et al., 2009) in for example the food industry (Janssen, 2010).
Furthermore, 99.3% of all siloxanes are removed when biogas is cooled to -70 o C (Dewil et al.,
2006) x . This technique is available for gas flows as from 300 Nm 3 biogas/hr.
x Cooling to 5 o C leads to 12% siloxane removal; -25 o C leads to a removal of 26%; at -70 o C 99,8% is re-
moved (Dewil et al., 2006).
49

3. General input calculations
General input data
Aspect Value Unit Reference
Operational hours/yr 8000 hrs/yr Urban et al., 2009
Maize silage harvest yield 45 ton/ha Walla & Schneeberger, 2008
Manure gas yield 23 Nm 3 biogas/ton Pöschl et al., 2010; Gebrezgabher et
al., 2010
Maize silage gas yield 200 Nm 3 biogas/ton Walla & Schneeberger, 2008;
Pöschl et al., 2010
Energy content biogas 21 MJ/Nm 3 biogas Appels et al., 2008; Wellinger and
Lindberg, 2001.
Energy content green gas y 31.7 MJ/Nm 3 green gas NMa, 2006
Max nitrogen application 170 kg N/ha/yr European Commission, 1991
Manure digestate, % of ton input 70 % Poeschl et al., 2010.
Maize silage digestate, % of ton input 90 % Bermejo & Ellmer, 2010
Processed digestate, % of total digestate
40 % Poeschl et al., 2010.
Distances used in the scenarios.
Scenario Maize Manure trans- Biogas Digestate trans- Processed digestate
transport
port transport
port
transport
1 50 0 5 0 0
2 50 0 5 0 0
3 50 0 10 0 0
4 50 10 0 10 0
5 50 10 0 10 0
6 50 10 0 10 50
Biomass input; digestate output in the scenarios
Total biomass input = biogas production capacity / (manure share * gas yield manure + maize
silage share * maize silage gas yield)
Scenario Maize silage Manure Biogas
(ton/hr) (ton/hr) (Nm 3 Digestate Processed digestate
biogas/hr) (ton/hr)
(ton/hr)
1 0.61 5.53 250 4.98 0
2 1.12 1.12 250 1.91 0
3 4.48 4.48 1000 7.62 0
4 4.48 4.48 1000 7.62 0
5 4.48 4.48 1000 7.62 0
6 4.48 4.48 1000 0 3.05
y Equals by definition the energy content of natural gas. For this research, the natural gas quality of Groningen
gas is used. The presented value is the lower value.
50

Biomass composition
Calculation of the amount of hectares of land required, needed to calculate the emissions from
cultivation and harvest, and fertilizer requirement.
Annual maize silage requirement = ton input per hour * operational hours
Ha land required = annual maize silage requirement / maize silage yield.
Manure – maize silage; bio- 90-10; 50-50; 50-50;
gas production capacity
250 250 1000
silage maize yield 45 45 45 ton/ha/yr
ton maize req/yr 4,914 8,969 35,874 ton maize/yr
ha required 109 199 797 ha/yr
51

4. Environmental data inventory & calculation
Environmental input values.
Aspect Value Unit Reference
Cattle manure availability 23 ton/cow/yr CBS, 2009
Nitrogen content cattle manure 4.3 kg N/ton Zwart et al., 2006
Nitrogen content maize silage 13 kg N/ton Zwart et al., 2006
CH4 emission factor, manure 1.8 kg CH4/ton Zwart et al., 2006
CH4 emission factor, maize silage 3.1 kg CH4/ton Zwart et al., 2006
Digestate processing (scrubber) 78.6 MJprimary/ton Pöschl et al., 2010
Loading digestate 15.5 MJprimary/ton Berglund & Börjesson, 2006
Spreading digestate 4.75 MJprimary/ton Berglund & Börjesson, 2006
Manure transport 1.6 MJprimary/ton km Berglund & Börjesson, 2006
Maize transport 1.1 MJprimary/ton km Berglund & Börjesson, 2006
Electricity production emission 69.4 gr CO2/MJprimary SenterNovem
Emissions from natural gas use 56.1 gr CO2/MJ Vreuls, 2004
Emissions from diesel use 3.255 gr CO2/l Börjesson, 1996 z
Global Warming Potential CH4 25 aa gr CO2-eq./gr CH4 Forster et al. [IPCC], 2007
Global Warming Potential N2O 298 gr CO2-eq./gr N2O Forster et al. [IPCC], 2007
Diesel consumption for cultivation of maize, from Gerin et al. (2008).
diesel (liter /ha /yr)
Soil ploughing and crumbling 32.7
sowing 9.4
weed control 3
harvest 27.4
harvest transport (2km) 7.3
Emissions from maize cultivation = diesel consumption * maize land requirement * CO2 emission
per liter of diesel.
Manure – maize silage; bio- 90-10; 50-50; 50-50;
gas production capacity
250 250 1000
Emissions from cultivation 28,365 51,769 207,074 kg CO2 /yr
Chemical N-fertilizer production, from Cederberg & Flysjo, 2004; WUR, 2007.
energy requirements 41.8 MJ/kg N
CO2 emission 2.95 kg CO2/kg N
N2O emission 9.3 gr N2O-N/kg N
Fertilizer requirement = Fertilizer rate * land required for maize silage cultivation.
Manure – maize silage; bio- 90-10; 50-50; 50-50;
gas production capacity
250 250 1000
Fertilizer rate 170 170 170 Kg N/ha/yr
Max N to be applied 18,564 33,881 135,526 Kg N/yr
z 3.255 kgCO2 is emitted per liter diesel, including the emissions involved in diesel production and distribution.
Based on 23 kgC/GJ for full fuel-cycle (Börjesson, 1996) and an energy content of 38.6 MJ/l.
aa On a time horizon of 100 years.
52

Emissions from fertilization of arable land, from Cherubini et al. (2000)
30% of total N to Nitrate
0,75% of Nitrate to N2O
2% of total N as N in NH3, for chemical fertilizer
4% of total N as N in NH3, for manure
1% direct soil emission of N2O, for chemical fertilizer
2% direct soil emission of N2O, for manure
So, the emissions of chemical fertilizer are in total:
Manure – maize silage; bio- 90-10; 50-50; 50-50;
gas production capacity
250 250 1000
CO2 emission from chemical
fertilizer production 54,764 99,950 399,801 kg CO2 /yr
Emission from soil 404 737 2,948 kg N2O-N /yr
Emissions from unprocessed digestate:
Manure – maize silage; bio- 90-10; 50-50; 50-50;
gas production capacity
CO2 emission from chemical
250 250 1000
fertilizer production 0 0 0 kg CO2 /yr
Emission from soil 4,251 1,628 6,513 kg N2O-N /yr
Emissions from processed digestate:
Manure – maize silage; bio- 90-10; 50-50; 50-50;
gas production capacity
CO2 emission from chemical
250 250 1000
fertilizer production 0 0 0 kg CO2 /yr
Emission from soil 1,814 695 2,779 kg N2O-N /yr
Emissions of storage, from Zwart et al., 2006.
Content * emissions fraction * amount of biomass required = long term storage emission.
kg/m3 emission fraction
Manure Methane 1.8
N2O 4.3 0.10%
Maize silage Methane 3.1
N2O 13 0.10%
5% of the emissions of long term storage are emitted before the biomass enters the di-
gester (Zwart et al., 2006).
Manure – maize silage; biogas
production capacity
90-10;
250
50-50;
250
50-50;
1000
CH4 4,742 2,197 8,789 Kg CH4 / yr
N2O 13 8 31 Kg N2O-N/ yr
Emissions from digester are 1% of long term storage:
Manure – maize silage; bio- 90-10; 50-50; 50-50;
gas production capacity
250 250 1000
CH4 948 439 1,758 Kg CH4 / yr
N2O 3 2 6 Kg N2O-N/ yr
53

Digestion
Emissions from energy use by the digester, based on Urban et al., 2009.
90% manure - 10% maize 50% manure - 50% maize
biogas production capacity Nm3/hr 250 1000 250 1000
Electricity 0.045 0.045 0.045 0.045 MJprimary /MJbiogas
heat (by natural gas boiler) 0.192 0.130 0.058 0.045 MJprimary /MJbiogas
CO2 emissions of electricity cons 129,917 519,667 129,917 519,667 kgCO2 /yr
CO2 emissions of heat cons 452,390 1,229,369 137,782 422,770 kgCO2 /yr
CO2 emissions 582,307 1,749,037 267,698 942,437 kgCO2 /yr
Upgrading
Source: Urban et al., 2009.
company: Malmberg MT-Energie
Water wash Chemical scrub
input cap Nm3/hr 250 1000 250 1000
output cap Nm3/hr 135 539 136 544
MJp el/yr 3,000,000 12,000,000 1,800,000 7,200,000
MJ th/ yr 480,000 480,000 440,000 1,304,000
kgCO2/ yr 235,128 859,728 149,604 572,834
kg MEA/ yr - - 9,540 30,720
Emissions from production of chemical liquid (MEA) in the liquid scrub technique.
MEA emissions
0.333 kWh/kg MEA Koornneef et al., 2008
1.58 gr NH3/kg MEA Koornneef et al., 2008
26.5 gr CO2/kg MEA Koornneef et al., 2008
0.2091 gr NH3/kg CO2 Koornneef et al., 2008
250 Nm 15.07 kg NH3/yr direct, at use
3 biogas/hr
252.89 kg CO2/yr indirect at MEA production
1000 Nm 48.54 kg NH3/yr direct, at use
3 biogas/hr
814.16 kg CO2/yr indirect at MEA production
Methane losses.
Zwart Pertl et al. Bekkering et al.
(2009) (2010) (2010) Avergage
water wash 3% 1.5% 3% 2.5% 0.0171 kg CH4/Nm3 biogas
liquid scrub 0% 0% 0% 0.00057 kg CH4/Nm3 biogas
Transport
Emissions from biogas transport are calculated from the electricity requirement. Calculation of
the electricity requirement are given in appendix 7.
Emissions from truck transport are calculated with the data given in the environmental input values,
times distance, and ton of biomass.
Injection
Emissions from injection are based on the electricity requirement of compression needed from
upgrading to the grid pressure. Calculation of the electricity requirement are given in appendix 7.
Methane emissions are 0.03% of the amount of compressed gas.
54

Digestate
digestate processing (decanter +
scrub)
78.6 MJprimary/ton digestate Pöschl et al., 2010
Processing digestate: drying, electricity
130 MJprimary/ton digestate Pöschl et al., 2010
Processing digestate: composting,
electricity
510 MJprimary/ton digestate Pöschl et al., 2010
Processed digestate fraction of initial
digestate
40 % Poeschl et al., 2010
loading digestate 15.5 MJprimary/ton digestate Berglund & Borjesson, 2006
spreading digestate 4.75 MJprimary/ton digestate Berglund & Borjesson, 2006
transport, incl empty return 1.6 MJprimary/ton digestate km Berglund & Borjesson, 2006
Emissions of digestate processing = energy requirements digestate processing * amount of digestate
+ (energy requirements drying + composting) * amount of solid digestate.
Manure – maize silage; biogas 90-10; 50-50; 50-50;
production capacity
250 250 1000
Digestate processing 924,285 354,046 1,416,183 Kg CO2/yr
Digestate transport 107,416 41,146 164,582 Kg CO2/yr
Digestate loading & spreading 27,190 10,415 41,660 Kg CO2/yr
55

Scenario results for environment
Global Warming Potential
gr. CO2-equivalents / MJ
scenario 1 scenario 2 scenario 3 scenario 4 scenario 5 scenario 6
CO2 direct, biomass 0.675 1.233 1.233 1.233 1.233 1.233
CO2 indirect, biomass 1.304 2.380 2.380 2.380 2.380 0.000
CH4, biomass 2.823 1.308 1.308 1.308 1.308 1.308
N2O-N, biomass 3.741 5.774 5.774 5.774 5.774 0.545
CO2 direct, biomass transport 0.543 0.990 0.990 1.279 1.279 1.279
CO2 indirect, digester 13.864 10.119 8.010 8.010 8.010 8.010
CH4, digester 0.565 0.262 0.262 0.262 0.262 0.262
N2O-N, digester 0.175 0.109 0.109 0.109 0.109 0.109
CO2 indirect, biogas transport 0.097 0.097 0.097 0.000 0.000 0.000
CH4, biogas transport 0.000 0.000 0.000 0.000 0.000 0.000
CO2 direct, upgrading 40.449 40.449 40.449 40.449 37.714 37.714
CO2 indirect, upgrading 3.568 3.568 3.415 3.415 5.117 5.117
CH4, upgrading 0.679 0.679 0.679 0.679 20.357 20.357
CO2 indirect, injection 2.868 2.868 1.555 1.555 0.930 0.930
CH4, injection 0.132 0.132 0.132 0.132 0.130 0.130
CO2 indirect, digestate processing 0.000 0.000 0.000 0.000 0.000 8.430
CO2 direct, digestate transport 0.000 0.000 0.000 0.000 0.000 0.980
CO2 direct, digestate load & spread 0.647 0.248 0.248 0.248 0.248 0.248
N2O, digestate soil 30.704 11.761 11.761 11.761 11.761 5.010
56

5. Economic data inventory & calculations
Economic parameters
Parameter Value Unit Source
Investment period 12 yrs Agentschap NL, 2010; Lensink et al., 2010
Inflation rate 2 %
Interest rate 7.8 % Lensink et al., 2010
Green gas price bb 0.713 €/Nm 3 Lensink et al., 2010
Electricity price 0.10 €/kWh
Manure price 10 cc €/ton Lensink et al., 2009
Maize silage price 18 €/ton Lensink et al., 2009; Walla & Schneeberger,
2008
Digestate processing 17 €/ton Veefkind et al., 2009
Digestate load & spread, manure 0.25 €/ton Poeschl et al., 2010
Digestate load & spread, maize silage 1.05 €/ton Poeschl et al., 2010
Transport of digestate, manure 0.04 €/ton/km Poeschl et al., 2010
Transport of digestate, maize silage 0.14 €/ton/km Poeschl et al., 2010
Price for nitrogen in (chemical) fertilizer
1.00 €/kg N Ahlgren et al., 2010.
CRF = interest rate * (1 + interest rate) investment period / ((1 + interest rate) investment period – 1)
Biomass
Biomass price [€/Nm 3 biogas] = manure price * manure input / manure yield + maize silage price *
maize silage input / maize silage yield
Price chemical fertilizer [€/Nm 3 biogas] = N fertilizer rate * land requirement for maize cultivation *
price for nitrogen in fertilizer / (biogas production capacity * operational hours per year).
bb Maximum green gas price including subsidy.
cc The manure price is dependent on the location: in a manure surplus area manure disposal cost about 10
€/ton, while in a shortage area manure is valued with 10 €/ton. Since manure is a waste product, it is considered
to be available at dairy farms without cost.
57

Digester
Capital costs = Investment * CRF Annual costs = variable costs + capital cost.
Costs of digestion [€/Nm 3 biogas] = annual cost / (biogas production capacity * operational hours
per year).
Source: Urban et al., 2009
58
90% manure, 10% maize silage
digester
50% manure – 50% maize silage
digester
unit 250 Nm 3 biogas 1000 Nm 3 biogas 250 Nm 3 biogas 1000 Nm 3 biogas
Investment costs € 1,080,000 3,226,316 1,227,500 3,813,158
machine technology € 147,000 437,684 150,500 449,842
digester € 619,500 1,875,789 623,250 1,894,895
substrate storage € 125,000 500,000
electro and control technology € 94,500 250,105 107,750 290,053
other € 189,000 562,737 193,500 578,368
Dismantling € 30,000 100,000 27,500 100,000
Annual costs €/a 331,095 991,695 327,803 997,315
Variable costs €/a 189,266 555,380 166,604 496,559
Employees €/a 38,300 106,472 44,700 117,136
Maintenance €/a 16,200 49,859 18,400 57,929
Electricity €/a 20,800 83,200 20,800 83,200
Heat costs €/a 96,666 262,690 63,054 176,514
other €/a 17,300 53,159 19,650 61,780
Capital costs €/a 141,829 436,315 161,199 500,756
Upgrading
Capital costs = Investment * CRF Annual costs = variable costs + capital cost
Costs of upgrading [€/Nm 3 biogas] = annual cost / (biogas production capacity * operational hours
per year).
Source: Urban et al., 2009
Water Wash Chemical scrub
input cap Nm3/hr 250 1000 500 1000
output cap Nm3/hr 135 539 272 544
Investment costs € 1,145,000 1,699,000 1,057,400 1,556,100
installation € 900,000 1,380,000 1,007,000 1,482,000
off-gas treatment € 200,000 250,000
associated costs € 45,000 69,000 50,400 74,100
construction on site €
commissioning €
initial installation spare parts €
Annual costs €/a 236,519 471,072 332,525 553,984
operational costs €/a 86,154 247,954 193,664 349,632
electricity €/a 50,000 200,000 60,000 120,000
means of production €/a 300 1,000 92,400 153,600
heat €/a
thermal off-gas treatment €/a 5.754 5,754 7,864 15,632
equipment €/a
employees €/a 7,200 7,200 6,400 6,400
repair- and maintenance costs €/a 22.900 34,000 27,000 54,000
capital costs €/a 150,365 223,118 138,861 204,352

Injection
Indicative figures.
Capital costs = Investment * CRF
source: Vlap, 2010 8 bar 40 bar 67 bar
fysical connection 25,000 250,000 350,000
gaschromatograph 40,000 40,000 40,000
dewpoint meter 5,000 5,000 5,000
flowmeter 10,000 10,000 10,000
hepa filter 20,000 20,000 20,000
odorisation 20,000 20,000 20,000
TOTAL 120,000 345,000 445,000
entry tarif 40 bar grid 15 €/(m3/hr)/yr
Compression
Calculated from confidential data; rounded figures, used as indicative data.
Capital costs = Investment * CRF
Variable costs are calculated with the energy requirements for compression; see appendix 7.
investment
1 bar - 8 bar 400,000
8 bar - 40 bar 450,000
1 bar - 40 bar 800,000
Digestate
Manure – maize silage; biogas 90-10; 50-50; 50-50;
production capacity
250 250 1000
Digestate processing 676,658 259,193 1,036,771 €/yr
Digestate transport 40,688 28,341 113,363 €/yr
Digestate loading & spreading 5,396 4,108 16,430 €/yr
Costs of digestate [€/Nm 3 biogas] = annual cost / (biogas production capacity * operational hours per
year).
59

Economic results
€/MJ
scenario 1 scenario 2 scenario 3 scenario 4 scenario 5 scenario 6
biomass 0.00255 0.00465 0.00465 0.00465 0.00465 0.00384
biomass transport 0.00035 0.00064 0.00064 0.00104 0.00104 0.00104
digester 0.00788 0.00780 0.00594 0.00594 0.00594 0.00594
biogas transport 0.00186 0.00186 0.00109 0.00000 0.00000 0.00000
upgrading 0.00513 0.00513 0.00330 0.00330 0.00280 0.00280
injection 0.00055 0.00055 0.00076 0.00076 0.00056 0.00056
digestate processing 0.00000 0.00000 0.00000 0.00000 0.00000 0.00617
digestate transport 0.00000 0.00000 0.00000 0.00034 0.00034 0.00169
digestate loading & spreading 0.00032 0.00024 0.00024 0.00024 0.00024 0.00024
green gas revenues -0.02249 -0.02249 -0.02249 -0.02249 -0.02249 -0.02249
digestate revenues 0.00000 0.00000 0.00000 0.00000 0.00000 -0.00135
NPV -322,113 -1,332,125 2,612,644 3,226,688 4,147,095 -7,523,613
IRR not possible not possible 6.9% 7.6% 8.4% not possible
PP -274 -22 18 15 13 -9
60

6. Social data inventory & calculations
Social parameters
Parameter Value Unit Source
Employment pipeline construc- 50 % Schoots et al., 2010
tion (% of total cost)
Approximate value.
Minimal space cow in shed 6 m 2
Employment in agriculture 25 hr/ha/yr Bos & van de Veen, 1999
Cattle manure availability 23 ton/cow/yr CBS, 2009
N-content unprocessed digestate 4.8 kg/ton Jury et al., 2010; Pöschl et al, 2010; Broeze et
al., 2005
N-content solid digestate 9.3 kg/ton Gebrezgabher et al., 2009
Land at a dairy farm 125 ha Pierik, 2001b
Land at a arable farm 300 ha Pierik, 2001a
Biomass
Annual labor requirement = Employment in agriculture * annual land requirement for maize cultivation
Digestion
Manure – maize silage; bio- 90-10; 50-50; 50-50;
gas production capacity
250 250 1000
Employment 1,094 1,277 3,347 hrs/yr
Land surface 295 138 348 m 2
Upgrading
water wash 250 m3/hr 14*6*8m 84 m2
4,000 m3/hr 16*8*8m 128 m2
Assumption 1: 1000 Nm 3 biogas/hr is equal in size of the 4000 Nm 3 biogas/hr.
Assumption 2: same sizes account for the liquid scrub technique.
Employment. Source: Urban et al., 2009
Water Wash Chemical scrub
input cap Nm3/hr 250 1000 500 1000
output cap Nm3/hr 135 539 272 544
Employees (@ 35 €/hr) €/a 7,200 7,200 6,400 6,400
hrs hrs/a 206 206 183 183
Injection
Source: Vlap, 2010.
Employment grid connection € €/hr hrs
indirect engineering 10,000 50 200
management design 100,000 100 1,000
construction 40,000 50 800
TOTAL 150,000 2,000
The employment for grid connection is divided by the economic lifetime.
61

Compression
assumption 40% labor cost of total investment 50 €/hr
employment, employment
investment
€
hrs/compressor
1 bar - 8 bar 250,000 100,000 2,000
8 bar - 40 bar 200,000 80,000 1,600
1 bar - 40 bar 375,000 150,000 3,000
Digestate
Source: Rohde et al., 2006. Variable cost are assumed to cover only employment; based on a labor
cost of 17 €/hr.
liquid digestate (=unprocessed); load 0.12 €/t actual t/ha:
liquid digestate (=unprocessed); spread 0.80 €/t; based on 30 t/ha 35
solid digestate; load 0.45 €/t
solid digestate; spread 0.35 €/t; based on 20 t/ha 18
Employment unprocessed digestate = (liquid digestate; load + liquid digestate; spread) * amount
of liquid digestate / labor cost.
Employment processed digestate = (solid digestate; load + solid digestate; spread) * amount of
solid digestate / labor cost.
Manure – maize silage; biogas production 90-10; 50-50; 50-50;
capacity
250 250 1000
Total N in unprocessed digestate 191,057 73,184 292,735 kgN/yr
Total N in solid digestate 148,069 56,717 226,870 kgN/yr
Land for unprocessed digestate 1,124 430 1,722 ha/yr
Land for solid digestate spreading 871 334 1,335 ha/yr
Food competition liquid digestate = Additional land requirement liquid digestate = total kg N in unprocessed
digestate / max kg annual N application – land area at dairy farm
Food competition solid digestate = Additional land requirement solid digestate = total kg N in solid digestate
/ max kg annual N application – land area at maize farm
Social results
employment sec/MJ
scenario 1 scenario 2 scenario 3 scenario 4 scenario 5 scenario 6
biomass 0.234 0.427 0.427 0.427 0.427 0.427
biomass transport 0.088 0.160 0.160 0.182 0.182 0.182
digester 0.094 0.109 0.072 0.072 0.072 0.072
biogas transport 0.000 0.000 0.000 0.000 0.000 0.000
upgrading 0.016 0.016 0.004 0.004 0.004 0.004
injection 0.035 0.035 0.015 0.015 0.010 0.010
digestate processing 0.000 0.000 0.000 0.000 0.000 0.004
digestate transport 0.000 0.000 0.000 0.022 0.022 0.109
digestate loading & spreading 0.185 0.071 0.071 0.071 0.071 0.025
62

land use m 2 /MJ
scenario 1 scenario 2 scenario 3 scenario 4 scenario 5 scenario 6
biomass, maize 0.026 0.047 0.047 0.047 0.047 0.047
biomass, shed 0.000158 0.000032 0.000032 0.000032 0.000032 0.000032
biomass transport 0 0 0 0 0 0
digester 0.000007 0.000003 0.000002 0.000002 0.000002 0.000002
biogas transport 0 0 0 0 0 0
upgrading 0.000002 0.000002 0.000001 0.000001 0.000001 0.000001
injection 0.000002 0.000002 0.000001 0.000001 0.000001 0.000001
digestate processing 0.000002 0.000002 0.000001 0.000001 0.000001 0.000001
digestate transport 0 0 0 0 0 0
digestate loading & spreading 0.238 0.073 0.095 0.095 0.095 0.062
Social index
scenario 1 scenario 2 scenario 3 scenario 4 scenario 5 scenario 6
0.052986 0.010009 0.016286 0.015855 0.015902 0.007079
63

7. Compression calculation
γ −1/
Nγ
ZRT1
Nγ
⎡⎛
p ⎤
2 ⎞
W = ⎢ −1⎥
1 ⎜
⎟
M γ − ⎢⎣
⎝ p1
⎠ ⎥⎦
W
Eel
=
η η 3600
E
64
primary
is
m
E
=
el
× ρ × 3.
6×
2.
5
31.
6
Formula to calculate the energy requirement of compressors (Damen, 2007).
In these formulas W is the specific work (in kJ/kg gas); E is the specific electricity requirement
(kWh/kg gas); Z is the compressibility factor (0.9942); R is the universal gas constant (8.3145
J/(mole K)); T1 is the suction temperature (313.15 K); γ is the specific heat ratio (cp/cv)
(1.293759); M is the molar mass (18.63 g/mole); p1 is the suction pressure (MPa) (transport =
0.101325); p2, discharge pressure (MPa) (dependent on the type of grid that is injected into); N is
the number of compressor stages (transport = 4, injection = 2). E is the electricity requirement
(kWh/kg gas), ηis is the isentropic efficiency (0.8%) and ηm is the mechanical efficiency (0.9%).
The primary energy use, Eprimary (MJprimary/MJgas) is found by multiplying it with the density of the
gas (0.81 for natural gas), then converting the electric energy to Mega Joule by the factor 3.6,
and converting it to primary energy by multiplying with a factor 2.5 (after Zwart, 2009). Dividing
this by the energy content of a normal cubic meter of gas , gives the primary energy requirement
for compression. The first formula is used to calculate the energy required for compression of
different gasses, by adjusting the molar mass to other gasses, in this case biogas and green gas.
Molar mass calculation of biogas
density mass/m3 biogas mol%
CO2 1.98 0.792 kg CO2/m 3 biogas 0.01800 mol/l 65
CH4 0.717 0.4302 kg CH4/m 3 biogas 0.00978 mol/l 35
total 1.2222 kg/m 3 biogas 0.02778 mol/l
Component Formula Mol-% Molar mass / component Molar mass
Methane CH4 35 16.043 5.615
Carbon dioxide CO2 62 44.010 27.286
TOTAL 32.901
Molar mass of natural gas
Component Formula Mol-% Molar mass / component Molar mass
Methane CH4 81.29 16.043 13.041
Ethane C2H6 2.87 30.070 0.863
Propane C3H8 0.38 44.097 0.167
Butane C4H10 0.15 50.125 0.075
Pentane C5H12 0.04 72.150 0.029
Hexane C6H14 0.05 86.177 0.043
Nitrogen N2 14.32 28.013 4.011
Oxygen O2 0.01 31.999 0.003
Carbon dioxide CO2 0.89 44.010 0.392
TOTAL 18.625

Pressure of green gas after upgrading
Unit: bar Zwart et al., 2009 Dena, 2009 Persson et al. 2006 de Hullu et al 2008 Average
water wash 8 6 8 10 8
liquid scrub 8 0 1 3
65

8. Total results
The unit for the environmental results is gr. CO2-equivalent/MJ.
The unit for the economic results is €/MJ.
scenario 1 scenario 2 scenario 3
social
social
social
Environment economics index environment economics index environment economics index
biomass 8.543 0.003 10.694 0.005 10.694 0.005
digestion 14.604 0.008 10.490 0.008 8.381 0.006
upgrading 44.695 0.005 44.695 0.005 44.542 0.003
injection 2.999 0.001 2.999 0.001 1.686 0.001
transport 0.640 0.002 1.087 0.002 1.087 0.002
digestate 31.352 0.000 12.009 0.000 12.009 0.000
Is 0.053 0.010 0.016
TOTAL 102.832 0.019 0.053 81.975 0.021 0.010 78.399 0.017 0.016
continued:
scenario 4 scenario 5 Scenario 6
social
social
social
environment economics index environment economics index environment economics index
biomass 10.694 0.005 10.694 0.005 3.085 0.004
digestion 8.381 0.006 8.381 0.006 8.381 0.006
upgrading 44.542 0.003 63.189 0.003 63.189 0.003
injection 1.686 0.001 1.061 0.001 1.061 0.001
transport 1.475 0.001 1.475 0.001 2.258 0.003
digestate 12.009 0.000 12.009 0.000 13.688 0.008
Is 0.016 0.016 0.007
TOTAL 78.786 0.016 0.016 96.808 0.016 0.016 91.662 0.021 0.007
66

9. Normalized results
The results are normalized on the maximum scenario value per aspect.
scenario 1 scenario 2 scenario 3
social
social
social
environment economics index environment economics index environment economics index
biomass 0.083 0.122 0.104 0.222 0.104 0.222
digestion 0.142 0.376 0.102 0.373 0.082 0.284
upgrading 0.435 0.245 0.435 0.245 0.433 0.157
injection 0.029 0.026 0.029 0.026 0.016 0.036
transport 0.006 0.105 0.011 0.119 0.011 0.083
digestate 0.305 0.015 0.117 0.012 0.117 0.012
Is 1.000 0.248 0.363
TOTAL 1.000 0.891 1.000 0.797 0.997 0.248 0.762 0.794 0.363
continued:
scenario 4 scenario 5 Scenario 6
social
social
social
environment economics index environment economics index environment economics index
biomass 0.104 0.222 0.104 0.222 0.030 0.184
digestion 0.082 0.284 0.082 0.284 0.082 0.284
upgrading 0.433 0.157 0.614 0.134 0.614 0.134
injection 0.016 0.036 0.010 0.027 0.010 0.027
transport 0.014 0.066 0.014 0.066 0.022 0.130
digestate 0.117 0.012 0.117 0.012 0.133 0.242
Is 0.353 0.355 0.210
TOTAL 0.766 0.777 0.353 0.941 0.744 0.355 0.891 1.000 0.210
67

10. Sensitivity analysis
Absolute change of input parameter. 0% is the used parameter value in this research.
-50% -25% 0% 25% 50%
distance gas grid 5 7.5 10 12.5 15
distance maize farm 25 37.5 50 62.5 75
fertilizer price 0.5 0.75 1.00 1.25 1.5
average income 18 27 36.00 45 54
investment period 6 9 12.00 15 18
average speed truck 15 22.5 30.00 37.5 45
maize silage price 9 13.5 18.00 22.5 27
manure gas yield 11.5 17.25 23.00 28.75 34.5
maize silage gas
yield 100 150 200.00 250 300
arable practice 40 60 80 - -
Results
change of input parameter
parameter -50% -25% 0% 25% 50%
distance gas grid -0.45 -0.23 0.00 0.23 0.45
distance maize farm -0.16 -0.08 0.00 0.08 0.16
fertilizer price -1.10 -0.55 0.00 0.55 1.10
average income 0.00 0.00 0.00 0.00 0.00
investment period 7.61 2.49 0.00 -1.45 -2.37
average speed truck -2.08 -0.69 0.00 0.42 0.69
maize price -5.25 -2.63 0.00 2.63 5.25
manure gas yield 2.63 1.28 0.00 -1.21 -2.37
maize silage gas
yield 39.27 13.96 0.00 -8.85 -14.95
arable practice 0.28 0.14 0.00
Arable practice was assumed to be best in the Netherlands. Therefore only worse situations are assessed
in the sensitivity.
Economic sensitivity
-10% -5% 0% 5% 10%
gas revenues 0.642 0.677 0.713 0.749 0.784
NPV (absolute. €) -41.008 1.569.828 3.226.688 4.883.547 6.494.383
IRR (absolute. %) not possible 5.4% 7.6% 9.2% 10.3%
PP (absolute. yr) 95 27 15.47 11 8
NPV (relative. %) -1% 49% 100% 151% 201%
IRR (relative. %) not possible 70% 100% 120% 135%
PP (relative. %) 613% 174% 100% 70% 54%
68