International Journal of Greenhouse Gas Control 11 (2012) 117–132
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International Journal of Greenhouse Gas Control
j ourna l ho mepage: www.elsev ier .com/ locate / i jggc
lobal potential for biomass and carbon dioxide capture, transport and storagep to 2050
oris Koornneefa,∗, Pieter van Breevoorta, Carlo Hamelincka, Chris Hendriksa,onique Hoogwijkc, Klaas Koopd, Michèle Kopera, Tim Dixonb, Ameena Campsb
Ecofys bv, P.O. Box 8408, 3503 RK Utrecht, The NetherlandsIEA Greenhouse Gas R&D Programme, The Orchard Business Centre, Stoke Orchard, Cheltenham, GL52 7RZ, United KingdomGemeente Utrecht, Ravellaan 96, 3533 JR, Utrecht, The NetherlandsRoyal HaskoningDHV, PO Box 1132, 3800 BC, Amersfoort, The Netherlands
r t i c l e i n f o
rticle history:eceived 29 December 2011eceived in revised form 27 July 2012ccepted 30 July 2012vailable online 30 August 2012
eywords:
a b s t r a c t
Biomass in combination with carbon capture and storage (CCS) technologies is one of few options thatmakes an actual reduction of global CO2 concentration in the atmosphere possible and is likely to berequired to meet low atmospheric concentration of CO2. This study shows the global potential for com-bining biomass with CCS technologies (bio-CCS) up to 2030 and 2050. The assessment includes six bio-CCSroutes for the production of power and biofuels in combination with CCS. For these routes we have ana-lysed the technical and economic potential. The results show the global technical potential for bio-CCS
io-energyarbon capture and storageE-CCSIO-CCS
technologies is large and, if deployed, can result in negative greenhouse gas emissions (GHG) up to 10.4 GtCO2 eq. on an annual basis in 2050. This is a large reduction potential compared to the global energy-related CO2 emissions which grew to 30.6 Gt CO2 in 2010. The economic potential reaches up to 3.5 Gt ofnegative GHG emissions when assuming a CO2 price of 50 D/tonne. Next to quantitative estimates of these
globaers t
lobal potential potentials in the form of
barriers and enhance driv
. Introduction
Carbon Dioxide Capture, Transport and Storage (CCS) can poten-ially reduce emissions of CO2 considerably over the next fewecades. It is considered a key technology, amongst many otherreenhouse gas (GHG) emission reduction options, such as energyavings and renewable energy technologies, to allow reachingtringent climate targets.
CCS is often associated with fossil energy conversion, but canlso be combined with bio-energy conversion, dubbed bio-CCS.hort-cycle carbon is then harvested and stored deep underground.ffectively, this suggests that carbon dioxide is removed from thetmosphere, leading potentially to negative GHG emissions. Thisrings bio-CCS into a select group of technologies that make anctual reduction of global CO2 concentration in the atmosphereossible. In fact, several mitigation scenarios show that biomass,
n combination with CCS, is likely to be required to meet lowi.e. 350 ppm) atmospheric concentration of CO2 (Azar et al., 2006;
EA/OECD, 2008; IEA, 2009; Luckow et al., 2010).
Bio-CCS technologies may play a considerable role in the futuref a low- carbon energy supply. It is thus of eminent interest to
create a good understanding of global and regional potential ofbiomass and CO2 storage capacity. In addition, it is important toassess how that potential may be utilized in bio-CCS technologies.
The aim of this study is to provide a first order assessmentof the potential for bio-CCS technologies to 2050, with an addi-tional focus on the medium term, i.e. 2030. We make a distinctionbetween technical potential (the potential that is technically fea-sible and not restricted by economical limitations) and economicpotential (the potential at competitive cost compared to alterna-tives). The difference between these potentials can be large and itis therefore imperative to understand these differences and identifythe restrictions that constrain the deployment of the full potential.Next to quantitative estimates of these potentials, in the form ofregional and global supply curves, we present recommendationsto overcome possible deployment barriers and enhance drivers tostimulate the deployment of bio-CCS technologies.
2. Modelling the potential of bio-CCS technologies
2.1. Conversion and capture technologies included in the analysis
Multiple sectors and technologies have been proposed wherebiomass conversion and CCS can be combined. Bio-CCS technolo-gies are proposed for processes in the bio-refining sector, biofuelsector, power and heat sector and in industrial processes for the
Biofuel productionBio-ethanol-advanced generation Advanced production of Bio-ethanol
through hydrolysis plus fermentation– 100% biomass share– Nearly pure CO2; only drying and compression
and
cth
emeotaccccaK
bsF22
FT biodiesel Biodiesel based on gasificationFischer–Tropsch synthesis
a Share of biomass on a primary energy basis.
ement, steel and paper sector (EBTP/ZEP, 2012). We focus on thoseechnologies and sectors that have been described in literature asaving the greatest anticipated potential.
Möllersten et al. (2003) suggest that CO2 capture from bio-thanol production and from chemical pulp mills are promisingarket niches for bio-CCS. In recent studies, the bio-CCS potential is
stimated to be greatest when combining CCS with the productionf power and biofuels (IEA, 2009; Luckow et al., 2010). Promisingechnologies mentioned for the production of power with biomassnd CCS are co-firing biomass in coal fired power plants with post-ombustion CCS and the dedicated firing of biomass in fluidised bedombustion technology with CCS (IEA GHG, 2009a). In addition toombustion, (co-) gasification of biomass in combination with pre-ombustion CCS in an (B)IGCC is also widely proposed in literatures an option for the production of power and heat (Rhodes andeith, 2005; Luckow et al., 2010).
For the production of biofuels, mainly two technologies areeing considered: CO2 capture from ethanol production and from
ynthetic biodiesel production using biomass gasification andischer–Tropsch (FT) synthesis (Möllersten et al., 2003; Ecofys,007a,b; van Vliet et al., 2009; Larson et al., 2010; Luckow et al.,010; Xu et al., 2010).
Fig. 1. Steps in the bio-CCS routes. Per step the op
– 100% biomass share– Nearly pure CO2 from pre-combustion; only compression
The two major sectors we focus on are large-scale electricitygeneration and biofuel production. We have selected six technologyroutes for a detailed assessment (see Table 1). In Fig. 1, we showthe steps in the full chain of the bio-CCS routes that are analysedin detail. The status and performance of the selected technologyroutes are described in the sections below.
2.1.1. Combustion based power production with post-combustioncapture
Typical large scale (up to GWe size range) combustion technolo-gies available for biomass co-firing are pulverized coal power plantand fluidised bed combustion. Low co-firing shares (up to ∼20%)have limited consequences on the performance of the boiler, fluegas treatment and maintenance. Moving to higher shares (40–50%),which is the subject of current development efforts, requires tech-nical modifications in boiler design (burner configuration), biomassfeeding lines (pre-treatment) and may result in fouling, slaggingand corrosion problems. It is expected that co-firing shares of 50%
can be reached in the coming decades (Faaij, 2006; NETBIOCOF,2006; IEA/OECD, 2007b; COFITECK, 2008; IEA ETSAP, 2010a,b)
The conversion efficiency (35–45%) in large-scale coal plants isgenerally higher in comparison with dedicated firing of biomass
tions researched in this study are indicated.
J. Koornneef et al. / International Journal of Greenhouse Gas Control 11 (2012) 117–132 119
Table 2Overview of performance and cost of biomass fired conversion technologies for power generation with CO2 capture and compression.
verall conversion cost are calculated based on a depreciation period of 30 years, aa Biomass share on an energy basis.
IEA/OECD, 2007b). This is due to the size of the power plant andssociated benefits, such as higher steam parameters and lowereat losses. Increase in conversion efficiency is expected for theoming decades with RD&D efforts aimed at reaching higher steamarameters, i.e. towards ultra-supercritical steam conditions.
Dedicated biomass fired power plants are currently also in theommercial phase. A technology currently widely used for 100%iomass firing is fluidised bed combustion. Technologies are avail-ble up to 100 MWe and further scale up is deemed possible toeveral hundreds of MWe. We assume scales of dedicated powerlants of approximately 500 MWe to be very likely in the comingecades, cf. (IEA GHG, 2009a).
Conversion efficiencies for smaller dedicated biomass plants aren the range between 25 and 30%;but for larger plants of about0–80 MWe efficiencies in the 30–36% range are possible (Faaij,006; IEA GHG, 2009a; IEA ETSAP, 2010a). Conversion efficienciesill most likely increase in the coming decades due to the develop-ent of enhanced steam cycles for dedicated biomass power plants.evertheless, conversion efficiencies are expected to be below thatf fossil-fired power plants due to a higher energy requirement forn-site pre-treatment and operation, and due to the lower heatingalues of the feedstock1.
In general, the same CO2 capture technology that can be appliedo pulverized coal fired power combustion plants is suitable forquivalent biomass fired systems considered here, being post-ombustion capture. Post-combustion CO2 capture is the mostikely near term option for both co-firing and dedicated firing inoncepts based on combustion.
Capture efficiencies mentioned in literature for the post-ombustion option are generally 85–95% (Damen et al., 2006). It isossible to reach nearly 100%. This is however not attractive from
thermodynamic point of view. The energy demand for CO2 cap-ure, resulting in an efficiency penalty up to 10% points as estimatedere, is expected to decrease in the future (see also (Damen et al.,006; van den Broek, 2010). Capturing CO2 with post-combustionrom dedicated firing of biomass in fluidised bed combustion sys-
ems results in a higher loss in generating efficiency compared tooal-fired installations (IEA GHG, 2009a).
1 A lower heating value of the feedstock results in a higher mass and volumeandling (fuel and flue gas) per unit of primary energy input, resulting in relativelyigher parasitic load; and with it reducing the overall efficiency. Lower heatingalues also affect the combustion characteristics and heat transfer.
52% 95% 1518 385 75 23
nt rate of 10% and 7800 full load hours per year.
The cost estimates for the power generation technologies arebased on earlier work by Hendriks et al. (2004) and were deflatedto D2010. Cost assumptions for the dedicated routes are updatedwith data from IEA GHG (2009a). Decrease in conversion cost dueto technological development, i.e. learning, is taken into accountby using cost development estimates published by Hendriks et al.(2004).
For the PC route, it is shown that co-firing requires additionalinvestment costs compared to coal firing alone, but this cost pre-mium is assumed to decrease on the longer term. The capital costincrease, as investments are required for biomass treatment andfeeding facilities.
Incremental investment cost required for co-firing biomass isin the range of 40–200 D/kWe summing up for the total plant(without CO2 capture) to 900–1000 D/kWe (IEA/OECD, 2007b). Ina more recent publication by the IEA (IEA ETSAP, 2010a) incremen-tal investments of 250 D/kWe (200–350) are reported. In this studywe assume specific investment cost of 1477 D/kWe for the viewyear 2030 and 1360 D/kWe in 2050 for co-firing biomass in coalfired power plants with co-firing rates of 30% in 2030, and of 50%in 2050 (see Table 2).
In Table 2 it is shown that the cost level (in D/kWe) of adding CO2capture is independent of whether or not co-firing is applied. Over-all capital cost and O&M cost are assumed to decrease significantlytowards the year 2050 (cf. van den Broek, 2010).
Firing 100% biomass requires higher specific investment cost,which is mainly due to more extensive fuel treatment and due to thelower conversion efficiency. In Europe, the investment cost of dedi-cated biomass plants varies considerably from 2300 to 4600 D/kWe,depending on plant technology, level of maturity and plant size(IEA/OECD, 2007b; IEA ETSAP, 2010a). In (IEA ETSAP, 2010a) totalinvestment cost for dedicated power plants in 2010, 2020 and 2030are estimated respectively at 2900, 2400 and 2100 D/kWe. Faaij(2006) reports 1600–2500 D/kWe for dedicated biomass powerplants. The IEA GHG (2009a) reports 1357 euro/kW for a CFBpower plant and 2447 euro/kW for a BFB power plant. We esti-mate the future investment cost of dedicated power plants at about1600 euro/kW in 2030 decreasing to approximately 1450 euro/kWin 2050.
The capital requirements for adding CO2 capture to CFB powerplants is assumed to be significantly higher, due to extensive flue
gas treatment which is not required in CFB power plants withoutcapture (IEA GHG, 2009a). For dedicated power plants the specificinvestment cost for conversion and CO2 capture are assumed todecrease with the same rate as for co-firing technologies.
1 of Gre
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tcfthohfo
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(Fabbri et al., 2010). Additional investment costs are estimatedat 36–37 D/kWoutput
4; together with the O&M cost this sums upto 0.3 D/GJ. This investment cost is low compared the specific
2 In this study, first generation bio-ethanol production is assumed to phase outover time as this route relies on feedstock that are generally also used for food (Bauenet al., 2009). This option is therefore not considered in detail in further analyses forthe view years 2030 and 2050. See Cornelissen et al. (2012) and references therein fora detailed discussion on the exclusion of land used for food, feed and fibre production
20 J. Koornneef et al. / International Journal
.1.2. Gasification based power production with pre-combustionapture
The IGCC concept based on fossil fuels can be characteriseds ‘early commercial’. There is relative little experience with co-asification of biomass and fossil fuels compared to co-firing inombustion concepts (Fernando, 2009). It is expected that co-asification rates in the order of 20–30% (on energy basis) areechnically feasible (cf. Fernando, 2009). Higher rates may be possi-le depending on the feedstock quality (e.g. high heating value, lowoisture content). Current reference design plants are available at
he scale of 600 MWe up to over 1 GWe. Conversion efficienciesf IGCCs are found up to 45% (LHV) (IEA ETSAP, 2010b). Improve-ent in efficiency in IGCC on the longer term is expected through
ncreased conversion efficiency of the gas turbine, higher operatingressure in the gasifier, process integration and hot syngas cleaningKoornneef, 2010).
In IEA ETSAP (2010b) an efficiency of 52% (LHV) is estimatedor coal fired IGCCs in 2030. On the longer term fuel cells maye applied to generate electricity from the syngas boosting effi-iencies to 50 and even above 60% (Knoope, 2010). This requiresowever significant RD&D to develop, demonstrate, and commer-ialize these systems (Faaij, 2006). In this study, we assume thatonversion efficiencies of the IGCC can be increased towards ∼55%n the longer term, which is within the range reported in literature.
Dedicated gasification of biomass for power production isemonstrated in the range of several MWe and this technology
s considered the least mature conversion technology for powerroduction (see details in Bauen et al. (2009)). Dedicated BIGCClants are possible in the scale range of ∼30 MWe on the shortererm increasing to ∼100 MWe size range on the mid-term (Faaij,006). Following developments in the scale of gasifiers and fossil-red IGCCs, we expect that BIGCC at a size of 500 MWe can becomevailable in the longer term. Near future generating efficiencies arestimated at around 30–40% (LHV) for the size range of tens of MWe.lthough extensive RD&D is required, we expect that conversionfficiencies above 50% can be achieved on the longer term.
Pre-combustion capture is currently the most promising optiono capture CO2 from gasification based technologies with high effi-iencies in the range of 85–95%. The technology to capture CO2rom the syngas generated in a gasifier can be considered provenechnology and is commercially available in other applications (e.g.ydrogen production from natural gas or coal for the productionf ammonia) than for electricity production. Due to the typicallyigher CO2 partial pressure in the shifted syngas, the energy penalty
or pre-combustion capture is theoretically lower compared tother capture concepts (IPCC, 2005).
Table 2 shows that specific investment cost for IGCC powerlants with and without CO2 capture are estimated to be lowerhan for PC power plants with and without CO2 capture. The spe-ific investment cost of BIGCC with and without CO2 capture aren IEA/OECD (2008) estimated to be significantly higher than bothther conversion routes (IGCC and PC).
This is also shown in Table 2, where BIGCC has 16% highernvestment cost in 2030 and 9% in 2050. The relative and absoluteifference in investment cost between IGCC and BIGCC is decreas-
ng over time due to technology development. For the BIGCC, whichs a less mature technology, the possibilities for improvement areonsidered more extensive and therefore a higher cost reduction isoreseen. Such a trend in cost decrease has been observed for sev-ral power generation technologies in history (see also Riahi et al.2004) and Junginger et al. (2006)) This holds also for O&M cost,hich are typically higher for the BIGCC compared to the IGCC.
Our cost estimates are confirmed by those in recent literature.
EA (2008) estimates 2093–2415 D/kWe for a biomass fired IGCC
ith CCS for the year 2025, which places our estimate of 2231 forhe year 2030 in the middle of that range. Our estimate for the
enhouse Gas Control 11 (2012) 117–132
year 2050 (1657 D/kWe) is in range with estimates by Rhodes andKeith (2005), being 1623 D/kWe, although they do not specify thereference year.
2.1.3. Bio-ethanol production with CO2 removalFirst generation2 ethanol production from sugar and starch
crops is currently a mature and commercial technology. Theethanol production is based on the enzymatic conversion ofbiomass into sugars, and/or fermentation of 6-carbon sugars withfinal distillation of ethanol to fuel grade.
Second or advanced production of bio-ethanol from ligno-cellulosic biomass is in the applied R&D phase and entering thecommercial demonstration phase. It is more difficult to break downthe ligno-cellulosic biomass into sugars than starch, and there-fore the production of ethanol requires advanced pre-treatmentand conversion processes. Most process steps are relatively simi-lar, such as the fermentation step. Developments in the productionof ligno-cellulose ethanol have accelerated in recent years and it isconsidered to be likely that commercial scale plants will becomeavailable in the coming decade (Bauen et al., 2009). Here it isassumed that this technology comes available in the range of200–400 MWfinal (230–470 ktonnes/year) in the coming decadeswith conversion efficiencies of up to 36% (LHV) (Ecofys, 2007a,b;IEA/OECD, 2007a; Bauen et al., 2009; REN21, 2010).
The fermentation step yields a high purity CO2 stream. Depend-ing on the conversion efficiency of the process, about 11–13%3 ofbiogenic CO2 in the advanced bio-ethanol production route is pro-duced in the form of high purity CO2. The remaining carbon ends upin the product, in residues or is emitted through the stack. Besidesdrying and compression, further treatment of the CO2 from the fer-mentation step is not deemed necessary (de Visser et al., 2011;Laude et al., 2011).
The conversion cost estimates are primarily based on earlierwork by Hamelinck and Hoogwijk (Ecofys, 2007a), see Table 3. Costestimates for CO2 capture are based on work by Ecofys (2007b), vanVliet et al. (2009) and de Visser et al. (2011).
There is a clear difference between conventional and advancedbio-ethanol production. Conventional bio-ethanol production iscommercially available and widely applied. Commercial scaleplants for advanced production will become available in the comingyears (Bauen et al., 2009). The specific investment costs of advancedbio-ethanol plants based on ligno-cellulosic biomass are estimatedto be significantly higher than that of conventional bio-ethanolplants. We assume that capital cost reductions due to economiesof scale and lower feedstock cost makes the ligno-cellulosic optioncompetitive in the longer run (Ecofys, 2007a,b; Bauen et al., 2009).
The costs of CO2 capture from the fermentation step are ingeneral low as investment cost, operational costs and the energyrequirement for drying and compression are relatively small(de Visser et al., 2011). In earlier studies the cost of capturefrom fermentation step (excluding transport and storage) wasestimated between 4.5 and 9 D/tonne CO2, (Xu et al., 2010),8 D/tonne (Bonijoly et al., 2009) and approximately 20 D/tonne
and the effect on the biomass supply potential.3 For every litre of ethanol produced, 765 g of CO2 is generated.4 This number refers to the specific investment cost per output (in kW) for the
whole plant. This number does not refer to the specific investment cost per kW
J. Koornneef et al. / International Journal of Greenhouse Gas Control 11 (2012) 117–132 121
Table 3Overview of performance and cost of biomass conversion technologies for biofuel production with CO2 capture and compression.
View year Capture technology Conversionefficiency(LHV)
2.2.1. Technical potentialTo determine the technical potential, we combine existing stud-
verall conversion cost are calculated based on a depreciation period of 30 years, aa Capture of CO2 only from fermentation step, CO2 capture from conversion of fob Capture of CO2 from tail gas is not included.
nvestment cost for the conversion plant between 1064 (in 2030)nd 1580 D/kWoutput (in 2050), see Table 3.
.1.4. Fischer–Tropsch biodiesel production with CO2 captureWith the use of thermochemical conversion process, a wide
ange of feedstock can be converted into a wide range of trans-ort fuels, including synthetic diesel and gasoline, methanol,imethylether, methane, and hydrogen. In this study, the conver-ion process for biomass feedstock into bio-diesel with the usef Fischer–Tropsch (FT) synthesis is further assessed. Gasificationombined with FT synthesis is an advanced technology for the con-ersion of biomass into liquid biofuels. Several types of FT processre commercially available and are being used to convert coal intoydrocarbons on a large scale. (van Vliet et al., 2009; IEA ETSAP,010c; Larson et al., 2010)
The FT process has become much more efficient and economicince it was invented (van Vliet et al., 2009; Vrijmoed et al., 2010).verall conversion of feedstock to product is expected to be in the
ange between 44% and 52% (LHV) based on estimates by Larsont al. (2010) and van Vliet et al. (2009). We assume based on work byamelinck and Hoogwijk (2007) a rather conservative conversionfficiency in both view years (2030 and 2050) of 42%.
Combining CCS with biodiesel production is interesting becausere-combustion CO2 removal is already part of the biodiesel pro-uction process. According to literature, approximately 54% ofhe total carbon in the feedstock is captured with the use ofre-combustion capture technology. Larson et al. (2010) reportspproximately 51–54% of the CO2 to be captured and stored. Theargest remainder (23–32%) of the carbon content is embodied inhe FT product, i.e. bio-diesel (van Vliet et al., 2009). Although inrinciple possible, it is assumed here that the capture of CO2 comingrom the combustion of the tail gas is not implemented.
It is estimated that biomass conversion into FT-biodieselequires specific investment cost of approximately 1600 D/kWoutput
n 2030, which is assumed to decrease on the long term towards300 D/kWoutput. The cost of CO2 removal largely depends onhe assumptions on the energy use and equipment cost of CO2ompression and drying. Here we assume relative small additional
nvestment cost of 60–80 D/kWoutput based on van Vliet et al. (2009).ost of conversion and capture are expected to decrease over timeue to economies of scale. Annual O&M cost for capture are here
f compression power. Capital cost of capture are estimated at 7.5 Meuro for a.2 Mtonne scale plant, using a scale factor of 1.
nt rate of 10% and 8000 full load hours per year.els or residues into power and heat is not included.
estimated at 22–23 D/kWoutput, which are dominated by the costof electricity, assumed at 40 D/MWh, needed for CO2 compression.
2.1.5. CO2 compressionThe CO2 is compressed in a multistage compressor to the
required transport pressure, which is typically above 100 bars.CO2 is typically released at atmospheric pressures from post-combustion and bio-ethanol routes. The energy requirement forcompression from atmospheric pressure to 100–140 bars amountsto about 0.11–0.12 MWhe/tonne CO2 (IPCC, 2005). For the FT-biodiesel route the CO2 is released at higher pressure which reducesthe energy requirement for compression to about 0.1 MWhe/tonne(van Vliet et al., 2009).
2.2. Common terminology for assessing potentials
There is no common terminology for defining (energy) poten-tials (Resch et al., 2008). Therefore, it is imperative to understandthe definitions and classification of potentials we use in this study.
The difference in various terms used to define potentials liesin the limitations or constraints that have been applied to the‘availability of resources’. If there were no constraints on using allavailable resources then this is the maximum potential. This theo-retical potential represents the upper limit of what can be producedfrom a certain energy resource and is based on current scientificknowledge. If we apply current or future technical constraints, thenwe derive the technical potential. These constraints vary over timedue to technological progress. For biomass and CCS technologies,the technical potential is constrained by the availability of sustain-able biomass5, CO2 storage capacity and the (future) technologicalperformance of the conversion and capture technology. The eco-nomic potential is the part of the technical potential that can berealised cost-effectively in the light of projected average energycosts in the future. This potential takes into consideration the costof the use of resources and the cost of (a set of) competing tech-nologies.
ies on biomass potentials (in EJ/yr primary energy) and CO2 storage
5 In some studies the technical potential of biomass supply is considered the globalpotential of biomass supply without sustainability criteria applied (see for instanceEC (2009). Throughout this report, we only consider the sustainable biomass sup-ply potential. When we refer to the ‘Technical potential’, sustainability criteria arealready taken into account.
122 J. Koornneef et al. / International Journal of Greenhouse Gas Control 11 (2012) 117–132
ig. 2. Regional breakdown biomass potentials in primary energy (EJ/yr) per costquals the annual technical biomass supply potential. Africa & Middle East (AFMEoviet Union (NOEU), North America (NOAM) and OECD Europe (OEU). Note that ea
otentials (in total Gt CO2). The net energy conversion efficiencyincluding the energy penalty) and the carbon removal efficiencyf the bio-CCS route then determine the technical potential foriomass CCS in terms of primary energy converted, final energy andet (negative) GHG emissions. It should be noted that we do not usen economic optimisation, but calculate the maximum potential asf all biomass were allocated to one specific bio-CCS route.
We divided the world into seven regions: Africa & Middle EastAFME), Asia (ASIA), Oceania (OCEA), Latin America (LAAM), Non-ECD Europe & the Former Soviet Union (NOEU), North America
NOAM) and OECD Europe (OEU). This geographic breakdown issed to show the availability of sustainable biomass resources andeological storage capacity per region, see Figs. 2 and 3. It allows theegional assessment of the potential for the selected bio-CCS routes.
e then assess per region whether the CO2 storage capacity or thevailability of biomass is the limiting factor.
The global potential is determined by combining the global stor-ge and biomass potential including inter-regional transport ofiomass and CO2. Combining biomass resource and storage capac-
ty to determine the technical potential yields a challenge. Theiomass potential is given as an annual potential. The storageotential is a finite resource, which is given as the total amountf CO2 that can be stored. Within our model we need to convert
0
5
10
15
20
Hy Aq UCS Hy Aq
tseBwoL
Storagepo
ten�
al(in
GtCO
2)Thou
sand
s
Fig. 3. Regional CO2 storage potentials showing lower, best and high estimates. Hource: Hendriks et al. (2004), NETL/DOE (2008), GeoCapacity (2009).
ory (cat I–IV). The sum of regional potentials in the highest cost category (cat IV) (ASIA), Oceania (OCEA), Latin America (LAAM), Non-OECD Europe & the Former
st category represents a step in the cost supply curve for the biomass potential.
this total amount of storage capacity to an annual storage capacity.For the technical potential, we therefore assumed that 1/50 of thetotal storage capacity can be used annually. This is based on theconservative assumption that a project developer does not start aCO2 injection activity if storage capacity is not assured for at leastthe entire lifetime – typically less than 50 years – of the energyconversion facility generating the CO2.
2.2.2. Economic potentialTo determine the economic potential we first assess the cost of
producing electricity and biofuels – with and without CCS – assum-ing a CO2 price of 50 D/tonne. This yields cost supply curves for thebio-CCS routes in 2030 and 2050, see Figs. 7 and 8.
These figures show the total production cost on the y-axis whichincreases with higher biomass prices; the associated productionpotential (in EJ/yr) is shown on the x-axis.
The economic potential is determined by combining the price ofbiomass resources with the costs for biomass conversion and CCS;
and comparing the production costs with those of fossil references.The economic bio-CCS potential is then the total amount of finalenergy that can be produced at lower cost than the selected fossilreference technologies.
UCS Hy Aq UCS
hgiH
OEU
NOAM
NOEU
LAA M
OCEA
ASIA
AFME
y = depleted hydrocarbon fields, Aq = aquifers, UCS = unmineable coal seams.
of Greenhouse Gas Control 11 (2012) 117–132 123
2
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Tbt
1
2
3
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af0ecfiac
aoblbt
a
Table 4Cost and price of biomass potential – from biomass production cost to pellet pricesat factory gate.
We examine three categories6 of biomass: energy crops (likeillow, poplar or perennial grasses), forestry residues and agri-
ultural residues. The worldwide sustainable biomass potential forhese categories is estimated based on studies from van Vuurent al. (2009), Hoogwijk (2004) and Hoogwijk et al. (2010). Poten-ials for forestry residues and agricultural residues are taken fromoogwijk et al. (2010). The potential for agricultural residues isstimated at 42 EJ/yr. For forestry residues, a range between 19 and5 EJ/yr is assumed (Hoogwijk, 2004; Hoogwijk et al., 2010). We usehe lowest values to produce a conservative estimate.
The energy crop potential is taken from van Vuuren et al. (2009).hey indicate a biomass potential for energy crops that rangeetween 65 and 148 EJ/yr in 2050, depending on the set of sus-ainability criteria:
. Strict set of criteria: land occupied by expanding nature reserves,land areas that face mild risk for water scarcity and mildlydegraded areas are excluded.
. Mild set of criteria: new nature reserves, water scarce areas andsevere degraded areas are excluded.
. No criteria: the full technical potential without sustainabilitycriteria applied.
Van Vuuren et al. estimate the full technical biomass potentialithout such criteria at 148 EJ/yr in 2050. Here we apply the ‘strict
riteria’, which equates to a potential for energy crops of about5 EJ/yr in 2050. Although we do not take into account all sustain-bility criteria that are currently being discussed (see for exampleSmeets et al., 2005; Dehue, 2006; EC, 2008, 2009; WBA, 2009;ehue et al., 2010; EC, 2010)), we consider this set appropriatenough to estimate the sustainable production of bio-energy withio-CCS technologies.
All potential estimates are based on the potential given for050. The total potential for energy crops in 2030 is approximately0% lower, see van Vuuren et al. (2009). For forestry residues, weave used the same 40% reduction for 2030 compared to 2050. Forgricultural residues, we have used a linear extrapolation of theotential between 2005 and 2050 to estimate the potential in 2030.
The cost of the biomass supply chain includes the production,ransport and pre-treatment of the biomass. For the production stepe have developed cost-supply curves on a regional level wheree combined the cost-supply curves of biomass production fromoogwijk (2004) with the sustainable biomass potential estimatesy van Vuuren et al. (2009). The cost-supply curves in Hoogwijk2004) are based on four steps, or cost categories (Cat I: < 0.8 D/GJ;at II: < 1.7 D/GJ; Cat III: < 3.3 D/GJ and Cat IV: < 41.5 D/GJ)7.
For residues, both agricultural and forestry, we used thessumption from Hoogwijk et al. (2010)8 that 10% of the potentialulfilling certain sustainability criteria is available at costs below.8 D/GJ and 100% below 41.5 D/GJ. With an extrapolation, we have
stimated what share of the potential can be produced in eachost category. This yields that 10% of the potential falls within therst cost category, 26% within the second, 42% within the thirdnd 22% within the fourth category. For residues, the shape of theost-supply curves is assumed equal for all regions.
6 Our selection excludes categories such as organic waste, animal dung/matternd the potential of aquatic biomass production in form of (micro or macro) algaer seaweed. Recent studies have estimated that the potential of this category ofiomass may be in the order of several hundreds or even thousands of EJ on the
onger term (Florentinus et al., 2008; Bauen et al., 2009). This aquatic biomass haseen excluded from the current analysis as it is less extensively studied comparedo land-based biomass resources.
7 All cost are presented in D2010 unless otherwise stated.8 Hoogwijk et al. (2010) applied this cost-curve solely to forestry residues, but we
ssumed this for both agricultural and forestry residues.
Price incl. densification and transport D/GJprimary 4.7 6.3 9.6 51.2Price of biomass pellets at factory gate D/GJpellets 5.2 7.0 10.7 56.9
The total potential per cost category including residues andenergy crops is shown in Fig. 2. To calculate the economic poten-tial, the price of biomass is also relevant. We therefore assumed aratio to convert biomass production cost into market prices. Theratios for the cost categories are based on figures reported by theIEA (Bauen et al., 2009). The difference between cost of biomassproduction and price is estimated in that study to vary betweenfactors 2 and 5. This factor is not assumed to be equal for all costcategories as the relative margins on high cost biomass are mostlikely to be lower. The arguable price-to-cost-ratios assumed hereare presented in Table 4.
Biomass pre-treatment and transport makes up a significantpart of the biomass supply chain cost. Using ranges presented ina study by van Vliet et al. (2009) we estimate the cost of localtransport, densification and ocean shipping.
Most forms of biomass tend to have a relatively low energydensity per unit of volume or mass. Long distance transport andinternational trade is limited to commodities that have sufficientenergy densities. Pre-treatment of biomass is required to increasethe energy density of the biomass and make transport economicand energetic viable. In this study, two processes are assumed tobe available in the view years:
• Biomass pellet production through heating followed by compres-sion and cooling resulting in densities of 600–700 kg/m3.
• Biomass pellet production through torrefaction. The biomass isheated to produce a material similar to charcoal, which canbe compressed to form pellets with a typical density of up to800 kg/m3.
The pre-treatment of raw biomass feedstock into (torrefied) pel-lets comes with an energy penalty. That is, during the heating anddensification energy is consumed, which is estimated in the rangeof 10–20% of the primary energy of the biomass input (van Vlietet al., 2009). Here we assume an energy and carbon efficiency of90%. We have estimated the cost of pre-treatment to be between0.4 and 1.7 D/GJ based on estimates by van Vliet et al. (2009).
The cost of transport is largely determined by the distanceand transport mode9. Total costs of transport are estimatedat 0.2–0.6 D/GJ. As default values we assume the averagepre-treatment and transport cost adding to approximately1.3 D/GJprimary. Following Luckow et al. (2010), we conservativelyassume that this cost premium will apply on all biomass produc-tion. The resulting overall costs and final prices of biomass arepresented in Table 4.
For the bio-CCS routes that co-utilize biomass and coal we
assume a default coal price of 3.7 D/GJ for both view years.
9 The cost of inland train and push tugs (up to 300 km) ranges between 0.1and 0.4 D2005/GJ. Cost of ocean shipping (up to 12,000 km) is approximately0.1–0.2 D2005/GJ.
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24 J. Koornneef et al. / International Journal
.4. Potential and cost of CO2 transport and storage
The costs of CO2 transport depend strongly on the mode of trans-ort, i.e. by pipeline, ship, train or truck. Of these options, transporty pipeline is considered the most cost-effective one. Transport byhip can be economically favourable when large quantities have toe transported over long distances (>1000 km) (IPCC, 2005) or tomaller/multiple storage sites. Transport by train or truck is notonsidered cost-effective for large-scale transport of CO2 (IPCC,005). In this study, it is assumed that CO2 will be transported byipelines only.
A typical issue that has to be addressed for CO2 transport isesigning and planning an optimal infrastructure to deploy CCSffectively and at the lowest cost possible. IEA GHG (2009b) reportshat 20 Gt10 of CO2 can be transported and stored for projects start-ng in 2030 with average cost below 4 D/tonne transported. Storing
ore than 20 Gt CO2 requires matching of sources and sinks thatre economically less favourable. This will result in higher marginalost rising to 23 D/tonne. It is beyond the scope of this study to pro-ide a detailed matching of sinks and CO2 sources equipped withio-CCS technologies. Instead we use a global range of CO2 trans-ort cost covering the range of cost reported by the IEA GHG (2009b)or the various regions. This range is estimated to be between the
and 30 D/tonne. The default value assumed is 5 D/tonne.The next step in the bio-CCS chain is the storage of CO2 by
njecting it into geological formations. We consider three types ofeservoirs:
. Depleted hydrocarbon fields (oil and gas fields).
. Aquifers.
. Unmineable coal seams.
For the CO2 storage potential we used estimates from Hendrikst al. (2004) which gives storage estimates for 17 world regions,hich we brought back to the same 7 regions listed above. Fig. 3
ives an overview of the storage capacity for these reservoirs com-ined.
For North America we updated storage resource estimatesith more recent information from the second edition of NETL-OE’s Carbon sequestration Atlas (NETL/DOE, 2008). For Europe,e updated the CO2 storage estimates with more detailed results
rom the GeoCapacity study (GeoCapacity, 2009). Overall, the globaltorage capacity used here corresponds best to the ‘theoretical’ oreffective’ capacity11.
Because the estimations on global storage potential are first esti-ations (storage sites have to be assessed individually to assess the
apacity and suitability more accurately), we included three esti-ates for each region: Low, Best12 and High (following Hendriks
t al. (2004)). By default, we used the ‘Best’ estimate to determinehe technical potential for the six routes.
The costs for CO2 storage largely depend on the drilling ofells and operational costs. The average costs range from 1 to 13/tonne of carbon dioxide, mainly depending on the depth, size,
10 This is cumulative amount of CO2 transported and stored.11 The CSLF taskforce (CSLF, 2008) has proposed the following characterisation ofO2 storage potentials: Theoretical Storage Capacity is the physical limit of whathe geological system can accept. Effective Storage Capacity represents a subset ofhe theoretical capacity that can be physically accessed and which meets a range ofeological and engineering criteria. Practical Storage Capacity is that subset of theffective capacity that is obtained by considering technical, legal and regulatory,nfrastructural and general economic barriers to CO2 geological storage. Matchedtorage Capacity is that subset of the practical capacity that is obtained by detailedatching of large stationary CO2 sources with geological storage sites that are ade-
uate in terms of capacity, injectivity and supply rate to contain CO2 streams sentor storage from that source or sources.12 For Europe, we used the results from GeoCapacity (2009) and categorised thiss a ‘Best’-estimation.
enhouse Gas Control 11 (2012) 117–132
permeability and the type of reservoir. Onshore storage is typi-cally less expensive than offshore storage (Hendriks et al., 2004;Damen et al., 2006; van den Broek, 2010). Here we assume a valueof 5 D/tonne with an uncertainty range between 1 and 13 D/tonne.
2.5. Greenhouse gas balance
The technical bio-CCS potential is determined by assessing theamount of biomass that can be converted into secondary energycarriers, i.e. electricity and biofuels. During this conversion, CO2 isgenerated which can be captured, transported and stored. It is thusimperative to know how much CO2 is generated in the conversionstep. This is determined by the direct emission factor. This togetherwith the capture efficiency determines the amount of CO2 that canbe captured.
In order to estimate the net greenhouse gas balance of bio-CCSroutes we also need to know the indirect emission factor, whichquantifies the GHG emissions in the fuel supply chain. This indirectemission factor cannot be easily standardised by biomass resourceas this depends on the fuel supply chain.
The net greenhouse gas balance is calculated by the sum ofdirect and indirect non-biogenic GHG emissions and the amountof biogenic CO2 stored, which counts as negative emissions. In theco-firing routes, we count the fraction of CO2 from the coal sharethat is captured, transported and stored as not emitted. The frac-tion not captured, in the case of coal, obviously adds to the directemissions of non-biogenic GHG.
2.5.1. Direct emissionsThe direct emission factor is arguably assumed to be equal for
all biomass resources and is set at 100 kg CO2/GJ (IPCC, 2006).An uncertainty range between 85 and 117 kg CO2/GJ is assumed,reflecting lower and higher estimates given by the IPCC (2006).Direct emissions of other GHG emissions (e.g. CH4 and N2O) fromthe conversion processes are not included as they are assumed neg-ligible. The direct emission factor for coal is assumed to be 95 kgCO2/GJ.
2.5.2. Emissions in biomass supply chainMain emissions in the supply chain of biomass occur during pro-
duction, transport and conversion. Inputs like fertilizers and useof diesel during production, and the agricultural part of the sup-ply chain cause greenhouse gas emissions attributed to biomassproduction.
The Joint Research Centre has published an overview of well-to-gate emissions for biomass supply chains (JRC, 2008). Since theagricultural processes of the feedstock are very different, the green-house gas burden of the various supply chains is very differentranging between 2.4 and 30.6 kg CO2 eq./GJprimary.
Since none of the advanced chains are currently commerciallyoperated, the supply chain emissions should be regarded as indica-tive for the future, i.e. towards 2020 and beyond. A recent studyby the COWI Consortium (COWI, 2009) indicated possible trendsin emission reductions for relevant parts of the biomass supplychains. The main GHG emission reductions are expected in the fer-tilizer production and processing industry. The combination of theexpected emissions reported by Joint Research Centre of the Euro-pean Commission (JRC, 2008) and the expected trends in emissionas reported by COWI (2009) give a range for the biomass supplychain emissions as expected towards 2020.
For the biomass supply chains of energy crops (farmed wood)the expected emission reductions related to the use of fertilizerwill have an impact on the 2020 supply chain emissions. For part of
the chains of agricultural residues or forest residues, no emissionsare attributed, as – for instance – fewer fertilizers are used duringproduction (like wood residues). For the wood chips from forestresidues case no emission reductions are expected towards 2020.
J. Koornneef et al. / International Journal of Greenhouse Gas Control 11 (2012) 117–132 125
Table 5Range for biomass supply chain emissions in 2020. All figures are in kg CO2 eq./GJprimary.
Feedstock Cultivation Processing Transport and distribution Overall supply chain emissions
Table 5 presents the range of biomass supply chain emissionsor the well to gate part of the supply chain as expected in 2020. Noetailed assessments are available for the longer term, i.e. towards050. We therefore use the 2020 figures also for the view years030 and 2050.
. Results
An overview of technical and economic potentials expressed innergy (primary and final) and net greenhouse gas emissions isrovided in Figs. 4 and 5. Cost supply curves that are used to derivehe economic potential for the six routes are shown in Figs. 7 and 8.
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Economic potential (final energy - biomass) Economic potential (final energy - biomass and coal)
ig. 4. Global technical and economic energy potential (in EJ/yr) per bio-CCS route for thasis and cannot simply be added, as they may compete and substitute each other. ‘Coal’
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ig. 5. Greenhouse gas emission balance (in Gt CO2 eq./yr) for the global technical and eotentials are assessed on a route-by-route basis and cannot simply be added, as they ma
1.4 61.0 21.9 2
3.1. Technical potential
All routes have a similar technical potential in terms of primaryenergy converted. The technical potential expressed in final energythen solely depends on the conversion efficiency of the bio-CCStechnologies. This is greatest for the IGCC co-firing route and thelowest for the advanced generation of ethanol. Deploying the fulltechnical potential equates to up to 59 EJ/yr of bio-electricity or
47 EJ/yr of biofuels. Compared to the current (2009 statistics) elec-tricity generation of approximately 72 EJ/yr (IEA, 2011a) this is alarge potential, but be reminded of our assumption that the fullbiomass potential is allocated to one technology route at a time.
2030
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BioEthanol FT biodiesel
Technical potential (final energy - bio mass)
Technical potential (final energy - bio mass and coal)
e view years 2030 and 2050. Note that potentials are assessed on a route by routeis only applicable for the co-firing routes.
2030
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BioEthanol FT biodiesel
he full biomass potential)
conomic potential per bio-CCS route for the view years 2030 and 2050. Note thaty compete and substitute each other.
126 J. Koornneef et al. / International Journal of Greenhouse Gas Control 11 (2012) 117–132
0%
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Fig. 6. Share of annualised technical storage potential utilised when deploying the global technical and economic potential.
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PC-CCS co-firin g Bio Ethano l BIGCC-CCS dedi cated CFB-CCS de dicated
FT biodie sel IGCC-CCS PC-CCS coa l IGCC-CCS coa l
Fig. 7. Global supply curve for the six bio-CCS technology routes and coal reference technologies for the year 2030 with a CO2 price of 50 D/tonne.
FT biod iesel IGCC-CCS PC-CCS coa l IGCC-CCS coa l
Fig. 8. Global supply curve for the six bio-CCS technology routes and coal reference technologies for the year 2050 with a CO2 price of 50 D/tonne.
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Comparing the world regions, we found the technical potentialo be the greatest in Asia and Latin America. The potential is the low-st in Oceania, Non-OECD Europe & the Former Soviet Union (FSU)nd OECD Europe. The results also show a vast storage potential inorth America, Non-OECD Europe and FSU and Africa and Middleast13. The technical bio-CCS potential is in those regions limited byhe supply of sustainable biomass. For most regions there is likely toe enough storage capacity to store the captured CO2; being most
ikely for the 100% biomass fired routes. An exception could be theegion Oceania where storage capacity may be the limiting factoror the co-firing routes when applying the available biomass on aegional base only.
In the biofuel routes a relatively small fraction of CO2 is cap-ured, therefore a relatively small storage capacity is required wheneploying the full biomass potential. In the 100% biomass routesor power generation, less storage capacity is required comparedo the co-firing routes when deploying the full technical biomassotential (see Fig. 6).
The potential for negative GHG emissions increases towards050, as both biomass supply and the capture efficiency is esti-ated to increase. The coal co-firing rate is also an important factor.
his affects the net GHG balance (in CO2 eq.) for the co-firing routess more emissions from fossil origin are emitted in the bio-CCShain deteriorating the GHG balance. The negative emissions arehe largest, up to 10.4 Gt of CO2 eq. annually in 2050, for the dedi-ated routes: BIGCC and CFB with CCS. The negative emissions up to.8 Gt of CO2 eq. for the biofuel routes with CCS are lower because
smaller fraction of the CO2 is captured and stored. Overall, theechnical potential of the bio-CCS routes offers a large reductionotential compared to current (2010) energy-related CO2 emis-ions of about 31 Gt CO2 (IEA, 2011b).
.2. Economic potential
The supply curves show that the route using the BIGCC withCS has the lowest cost of electricity production when using lowost biomass (see Figs. 7 and 8). This despite the higher specificnvestment cost and lower conversion efficiency compared to otherio-CCS technologies. The low cost biomass and CO2 price of 50uro/tonne offsets these disadvantages.
With higher cost for biomass resources, the production costncrease for all routes, though the most for the dedicated routes:FB, BIGCCC, bio-ethanol and FT-biodiesel. These routes are moreensitive for changes in biomass prices compared to the co-firingoutes as the coal share suppresses the increase of production costhen biomass prices increase. The cost supply curves are thus
teeper for the dedicated routes.The dedicated route using the CFB technology is the only route
here the conversion costs for power production are overall lowerhen the plant is not equipped with CCS. The cost difference is
he largest for the medium term, i.e. for 2030. In the other routeshe production costs are predominantly lower when CCS is imple-
ented compared to the same technology not equipped with CCS.With a CO2 price of 50 D/tonne, the economic potential for bio-
CS technologies is up to 20 EJ/yr for bio-electricity routes (IGCCnd BIGCC) or up to 26 EJ/yr for the Fischer–Tropsch biodiesel route.he greatest economic potential is found in the gasification basedoutes. The smallest economic potential is found for the PC and CFBoutes: about 1 EJ/yr for the year 2030.
Up to one third to half of the technical potential can be consid-
red economically attractive, yielding an annual potential of up to.5 Gt of negative GHG emissions for the bio-electricity routes orp to 3.1 Gt CO2 eq./yr for the biofuel routes. The bio-ethanol route
13 Africa and the Middle East are treated as one region.
enhouse Gas Control 11 (2012) 117–132 127
shows a low economic potential in 2030 of 1.2 EJ/yr, but grows sig-nificantly to about 13 EJ/yr in 2050. This is equal to 0.4 Gt of netnegative GHG emissions, which is the lowest economic potentialfor all six routes in the year 2050.
4. Sensitivity analysis
To test the robustness of the results presented above we haveassessed the impact of varying key assumptions regarding thebiomass and CO2 storage potential on the results for the technicalpotential.
Regarding the biomass potential we assessed the impact of vary-ing the set of sustainability criteria. By default we use the ‘Strict’set of sustainability criteria. In the sensitivity analysis we assesswhat the effect is when we apply ‘Mild’ or ‘No’ criteria. The resultsfor the technical are very sensitive to the set of criteria applied, asthe biomass potential is the dominant constraint limiting the bio-CCS potential, and with no or a limited set of criteria applied thebiomass potential can be larger. These two factors combined resultin an increase in the technical potential of more than 60% for bothview years, when no criteria are applied and an increase of about40% in the case of the mild criteria. Varying the application of sus-tainability criteria on the biomass supply thus has severe influenceon the biomass potential (see also Cornelissen et al. (2012)) andwith it on the technical potential.
We also tested variables for the storage potential: the type ofestimate (Best, Low High), the reservoir types and the annualisedstorage factor.
In the base case we use the ‘Best’ estimates for the storage poten-tial. In the sensitivity cases we have used the ‘Low’ and the ‘High’estimates (see Fig. 3) for all reservoir types. The results did not showan effect on the technical potential.
We also assessed the impact of increasing the “Annualised stor-age capacity factor” from 50 to 70. This reduces only the technicalpotential for the routes for electricity production when inter-regional transport of biomass (and CO2) is not possible. The biofuelproduction routes are not affected as storage capacity is not a con-straint in those routes. The co-firing routes are affected the mostas more storage capacity is required in those routes. The technicalpotential of the IGCC co-firing route in 2050 is reduced the mostwith 8 EJ/yr (4 EJ/yr biomass share) and the dedicated routes theleast with 1 EJ/yr.
Subsequently, we varied the types of reservoir that are includedin the CO2 storage potential. In the sensitivity case we have chosen‘Hydrocarbon only’ excluding the potential of aquifers and under-ground coal seams as presented in Fig. 3. This assumption doeshave a considerable effect on the technical potential when inter-regional transport is not included. The results in that case indicatethat reducing the storage potential leads to a constraint and limitingthe overall technical potential, especially for the co-firing routes.In these routes, more CO2 storage capacity is needed per EJ of finalenergy produced with biomass. These results show that globallythere is assumed to be enough storage potential in hydrocarbonreservoirs for the CO2 derived from BE-CCS technologies. However,there is a geographic mismatch between the supply of biomassand the storage capacity in hydrocarbon reservoirs in the definedregions.
We selected also variables to assess the sensitivity of ourassumptions on the outcome for the economic potential in moredetail, being: CO2 price, coal price, discount factor, cost of CO2transport and storage and the price of biomass supply. The basecase values and ranges used in the sensitivity analysis are shown
in Table 6.
The results in Figs. 9 and 10 show that the economic potential ishighly dependent on the CO2 price. Reducing the CO2 price to 20 Dresults in an increase in production cost of up to about 30% for the
128 J. Koornneef et al. / International Journal of Greenhouse Gas Control 11 (2012) 117–132
Table 6Ranges used for key assumptions in the sensitivity analysis.
Variable Unit Base case Variant 1 Variant 2
Sustainability criteria biomass supply – Strict Mild NoStorage potential estimate – Best ‘Low’ ‘High’Storage potential reservoir types – All Hydrocarbon onlyAnnualised storage capacity factor Years 50 70CO2 price D/tonne 50 20 100Coal price D/GJ 3.7 2.6 4.9Discount factor (cost of financing) % 10 6 15CO2 transport and storage cost
Cost of transport D/tonne 5 3 10Cost of storage D/tonne 5 1 13
Biomass price % 100% −50% +50%
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Base CO2 price low CO2 price high
Coal pr ice low Coal pr ice high Discoun t f actor low
Discount fac tor high CO2 transport an d st orage cost low CO2 transpo rt and storage c ost hig h
Biomass pric e low Biom ass price high
Fig. 9. Outcomes for the economic potential under different assumptions for key variables, results for the year 2030. Note that the final energy potential includes bothbiomass and coal shares for the co-firing routes.
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Base CO2 pric e low CO2 price high
Coal price low Coa l price high Discoun t factor low
Discoun t factor high CO2 tran sport and storage cost low CO2 transp ort and storage c ost hig h
Biomass price low Biomass pri ce hi gh
Fig. 10. Outcomes for the economic potential under different assumptions for key variables, results for the year 2050. Note that the final energy potential includes bothbiomass and coal shares for the co-firing routes.
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volume and price of biomass would be a valuable next step fora more robust assessment of the economic potential of bio-CCStechnologies.
14 The technical potential is defined as the third order potential after ‘Theoretical’and ‘Conversion potential’. The ‘Technical potential’ takes into account additional
J. Koornneef et al. / International Journal
edicated biomass routes producing electricity. The impact is loweror the co-firing routes and for the routes that capture less CO2.
hen increasing the CO2 price to 100 D the production cost of finalnergy decrease up to about 60% for the dedicated routes in 2050.
higher CO2 price thus decreases the bio-CCS production costsubstantially and increases the costs for the reference technologies,esulting in a substantial increase of competitiveness for the bio-CS technologies.
The coal price directly affects the production cost of electricityor the co-firing routes. This entails a decrease or increase of about–8% and their economic potential is directly affected. A higher coalrice also results indirectly in a higher economic potential for allio-CCS technologies producing electricity as reference technolo-ies firing 100% coal become more expensive.
The biomass price significantly affects the production cost of alloutes. Halving the biomass price for the year 2050, results in aecrease in production cost of up to 39% for the dedicated routes.he production cost of co-firing routes decrease up to 18% in 2050.ncreasing the biomass price with 50%, results in the rise of produc-ion cost up to 28% in 2030 and up to 31% in 2050. The productionost of co-firing routes are least affected, depending on the co-firinghare of biomass. A higher biomass price decreases the economicotential of almost all routes to zero for the year 2030.
The effect of a higher or lower discount rate is typically moreevere for the capital-intensive routes, being the dedicated routesring only biomass (see Table 2). It results in a 15–20% change inroduction cost, but has in general a low impact on the economicotential.
Doubling the cost of CO2 transport and storage to 23 D/tonneesults in an increase in the production cost of maximally 16%.
hen the costs are halved (4 D/tonne), the production costs willecrease up to 7%. The impact on the economic potential is clearlyo see for the CFB, IGCC and BIGCC routes in 2030, where theconomic potential sharply decreases with increasing cost of CO2ransport and storage. For 2050, we can see that varying the trans-ort and storage cost strongly influences the economic potential ofhe co-firing routes. The economic potential of the routes produc-ng biofuels are not affected by changes in cost of CO2 transport andtorage.
. Discussion
.1. Limitations when estimating potentials
The main limitations when estimating the technical potentialre caused by the uncertainty in estimates for the global sustainableiomass potential and CO2 storage potential.
For the biomass potential, this uncertainty is primarily causedy differences in assumptions in underlying studies on the land usecenarios, yield development, food consumption and constraintset by sustainability criteria for the supply of biomass availableor energy. The latter includes issues such as water scarcity, landegradation, loss in biodiversity and (in)direct land use change.ariations in land use scenarios and yield potential estimates rang-
ng between 120 and 300 EJ/yr. van Vuuren et al. (2009) estimatehe potential to be approximately 150 EJ/yr without constraintsn land degradation, water scarcity and nature reserve expansion.hen applying these constraints, the potential decreases to about
5–115 EJ/yr. Luckow et al. (2010) cite other studies, estimatinghe global biomass potential to range between 100 and 400 EJ/yr.n (EC, 2009), an overview of estimates for sustainable biomass
otentials in 2050 is presented yielding estimates of sustainableiomass potentials up to almost 500 EJ/yr. In a study ordered byREC and Greenpeace (2010) global biomass potential estimatesange between 66 and 110 EJ/yr for 2020 and 94–184 EJ/yr for 2050.
enhouse Gas Control 11 (2012) 117–132 129
The overall technical potential14 is estimated to be 102 EJ/yr in2020, 129 EJ/yr in 2030 and 184 EJ/yr in 2050. Our estimate canbe considered slightly conservative when compared to these esti-mates, but the results for the technical potential, expressed in finalenergy and the maximum amount of CO2 stored, are very sensitiveto the amount of sustainable biomass and thus to the applicationof sustainability criteria.
For storage potential the uncertainty arises from the difficulty ofaccurately estimating storage capacities, particularly for aquifers.In addition, the studies that have been gathered and used toestimate the global storage potential do not use consistent method-ologies to estimate the amount of CO2 that can be stored. It isbeyond the scope of this study to perform a detailed consistencyanalysis on the used storage estimates. Due to the unavailabilityof detailed storage capacity estimates, the technical potential maybe minimally higher or lower than the ‘best’ estimate used in ourstudy by a factor of 2.
The technical and economic potential are not influenced byusing lower or higher estimates for the global storage potential(see Figs. 3 and 6), as this is not the limiting factor in most of theregions. The technical potential of the co-firing routes is signifi-cantly reduced when storage capacity of aquifers and undergroundcoal seams are excluded as well as excluding inter-regional trans-port of biomass. The impact of varying the ‘annualised storagecapacity factor’ on the technical potential is relatively modest forthe routes producing electricity. No impact is observed for the bio-fuel production routes.
The net greenhouse gas emissions from bio-CCS technologyroutes are sensitive to assumptions on the emission factor ofbiomass. This determines how much emissions can be capturedand stored per unit of energy (primary and final energy). We haveset this emission factor at 100 g CO2/MJ (LHV). Lowering the emis-sion factor would result in lower mitigation potential and thereforeless negative emissions, and conversely when assuming a higheremission factor. In addition, we have estimated the greenhousegas emissions in the biomass supply chain. These emissions do notinclude greenhouse gas emissions due to land use change (director indirect). There is extensive debate on how to include land usechange in the greenhouse gas performance of bio-energy routesand which emission factor should be assumed (see for instance(EC, 2010)). It is likely that the GHG performance of the full bio-CCSchain would be lower (i.e. less negative emissions) when includinga GHG factor to account for land use change, but the opposite effectcan also not be excluded as a possibility.
The determination of the economic potential depends on var-ious assumptions. The most significant are future conversion costof bio-CCS routes and their alternatives, CO2 capture, transport andstorage cost, biomass and fuel price and the CO2 price. All of thesefactors are highly uncertain and estimates for each factor may beover 30% inaccurate. We have demonstrated the effect that vari-ations in these factors have on our results. Short and long-termprice15 estimations are crucial factors when assessing the economicpotential of biomass and CCS. For instance, a better understand-ing and quantification of the key factors that influence the trade
restrictions regarding the area that is realistically available for energy generation.Technological, structural and ecological restrictions, as well as legislative require-ments, are accounted for.
15 See Davison and Thambimuthu (2009) for a more thorough discussion on trendsin investment cost and the uncertainty of future fuel prices.
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Regarding the cost assumptions for CO2 transport and stor-ge, it should be noted that we did not take source-sink matchingnto consideration. Matching the temporal and geographical avail-bility of sources (including the biomass supply chain) and sinksay in practice become a bottleneck. Additional cost for transport
nd/or storage will be incurred when detailed source-sink match-ng is applied. In a recent IEAGHG report (2009), reported costf transport and storage in depleted gas fields vary significantlyetween regions. A regional specific cost curve for CO2 transportnd storage is not applied in our study. Instead, we used a singlealue for the cost of CO2 transport and storage based on a rangef values reported in literature and assessed the impacts of lowerr higher costs on the final result. It is however recommendedhat if the bio-CCS potential is to be estimated on a more detailedevel and on a regional basis, that regional specific supply curvesre used.
The potential for bio-CCS is anticipated to be the largest in theower and biofuel sector, but bio-CCS can also play a role in otherectors, although most likely on a smaller scale and through moreiche market applications (e.g. decentralised production and withO2 re-use). Sectors worthwhile analysing further are believed toe: biomass use in industry combined with CCS (e.g. steel, cementroduction), biomethane production with CCS, and CCS in the pulpnd paper sector.
.2. Drivers and barriers for implementation
Several technical, financial/economic, and public and policyelated drivers and barriers for the deployment of bio-CCS tech-ologies are identified. One important driver is the CO2 price, which
s influenced by climate policy and the development and avail-bility of other mitigation options. Under the current EU Emissionrading Scheme, storing CO2 from biomass will not ‘create’ sellablellowances, i.e. there is no economic value attached to negativemissions (see (Groenenberg and Dixon, 2010; EBTP/ZEP, 2012).urrent CO2 prices16 are nevertheless highly unlikely to result inn economic potential for bio-CCS technologies and substantiallyigher CO2 prices require a stricter climate policy, or other policyctions.
The (lack of) maturity of the technology is a barrier. The combi-ation of CCS and advanced biomass conversion technologies is not
mature technology. Financial and technical risk of the biomass-CS combination can be high, which could create higher financingosts. Uncertainty in the (regular) supply of sustainable biomassnd the availability and certainty of CO2 storage capacity are alsoonsidered significant barriers. The secure supply of low cost andustainable biomass is essential for bio-CCS technologies. Impor-ant factors that influence this are future land use scenarios andompetition with other sectors using biomass.
Public perception is identified as a key factor in the success ofio-CCS. A negative perception of CCS and/or biomass will stall bio-CS or may result in higher transport and storage costs. However,he combination of biomass conversion and CCS technologies mayxpect greater public support than the individual technologies, seeallquist et al. (2012).
. Conclusions
The global technical potential for bio-CCS technologies is largend, if deployed, can result in negative greenhouse gas emissions
16 The CO2 price in 2012 (January–July) was below 10 D/tonne, seettp://www.eex.com/en/
enhouse Gas Control 11 (2012) 117–132
up to 10.4 Gt CO2 eq. annually. This is a large potential comparedto the global energy-related CO2 emissions which grew to 30.6 GtCO2 in 2010 (IEA, 2011b). Other important findings regarding thetechnical potential are:
• The amount of sustainable biomass that can be harvested andsupplied greatly determines the potential for bio-CCS technolo-gies.
• For almost all regions, there is likely to be enough storage capac-ity to store the captured CO2. Only where depleted hydrocarbonfields are used in isolation, storage capacity may become a limit-ing factor.
• Up to 59 EJ/yr of bio-electricity, or 47 EJ/yr of biofuels can be pro-duced when deploying the full technical potential.
• The amount of CO2 stored by conversion routes ranges between0.7 and 20.9 Gt CO2/yr.
• Negative emissions up to 10.4 Gt CO2 eq./yr are the highest for thededicated routes with CCS: BIGCC and CFB. The negative emis-sions for the biofuel routes with CCS are the lowest, rangingbetween 0.5 and 5.8 Gt CO2 eq./yr
The economic potential for bio-CCS technologies is up to 20 EJ/yrfor bio-electricity routes or up to 26 EJ/yr for the biofuel routes,when assuming a CO2 price of 50 D/tonne. About one third (up to3.5 Gt CO2 eq./yr) of the technical potential can be considered eco-nomically attractive when producing bio-electricity; and about half(up to 3.1 Gt CO2 eq./yr) of the technical potential is attractive inthe case of biofuel production.
• For the medium to long-term, the route using the BIGCC with CCShas the lowest cost of electricity production when using low costbiomass.
• The largest economic potential of about 20 EJ/yr (biomass share)is in the gasification-based routes (IGCC and BIGCC) for the year2050. The smallest economic potential is in the PC and CFB routesof about 1 EJ/yr for the year 2030.
• For the biofuel routes, the economic potential is calculated to behighest for the FT-biodiesel route, at 26 EJ/yr and equivalent to−3.1 Gt CO2 eq./yr.
• Estimates for the economic potential are highly sensitive to theCO2 price, coal price and biomass price.
In conclusion, a detailed assessment of future production costand economic potential is difficult considering the current datalimitations. Despite these uncertainties and their impact on theresults, we believe that the relative difference between the tech-nology routes is appropriately assessed showing the trends anddifferences in outcomes.
The most important recommendation that follows from thisstudy is that stored CO2 originating from biomass should get aneconomic value. The CO2 price in combination with low cost sus-tainable biomass will be the key driver for the deployment ofbio-CCS technologies.
Recommendations for further research are aimed at assessingthe bio-CCS potential per region on a higher level of detail throughregional specific cost supply curves for CO2 transport and stor-age including source-sink matching. Together with a more detailed
assessment of the biomass resources and regional supply con-straints, more detailed cost supply curves could be derived forbio-CCS technologies and regions with early opportunities couldbe identified.
An online version of the bio-CCS model can be found throughhe IEA GHG website at: www.ieaghg.org.
cknowledgements
We would like to acknowledge the International Energygency’s Greenhouse Gas R&D Programme for funding and would
ike to thank the reviewers of earlier versions for their valuableomments and input.
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