Meta-Analysis of Life Cycle Assessment Studies on Electricity Generation with Carbon Capture and Storage


  • Andrea Schreiber,

  • Petra Zapp,

  • Josefine Marx

Andrea Schreiber, Forschungszentrum Jülich, Institute of Energy and Climate Research-Systems Analysis and Technology Evaluation (IEK-STE), D-52425 Jülich, Germany. Email:


In the last decade, numerous life cycle assessments (LCAs) on environmental impacts of electricity generation with carbon capture and storage (CCS) have been conducted. This meta-analysis comprises 15 LCAs of the three CCS technologies (postcombustion, oxyfuel, precombustion) with a focus on greenhouse gas reduction for different regions (Europe, United States, Japan, global), different fuels (hard coal, lignite, natural gas), and different time horizons (between the present and 2050). It presents a condensed overview of methodological variations, findings, and conclusions gathered from these LCAs.

All LCAs show the expected reduction in global warming potential but an increase in many other impact categories, regardless of capture technology, time horizon, or fuel considered. Three parameter sets have been identified that have a significant impact on the results: (1) power plant efficiency and energy penalty of the capture process, (2) carbon dioxide capture efficiency and purity, and (3) fuel origin and composition.

This meta-analysis proves that LCA is a helpful tool to investigate the variety of environmental consequences associated with CCS. However, there are differences in the underlying assumptions of the LCAs as well as methodological shortcomings that yield heterogeneity of results. Without a better understanding of the technology, it is not possible to give a comprehensive picture. There also remains a wide field of subjects and technologies that have not yet been covered.


Currently electricity generation contributes to 40% of global carbon dioxide (CO2) emissions. Beside other measures, carbon capture and storage (CCS) technology is widely recognized as an appropriate option to achieve ambitious CO2 reduction targets. In principle, there are three main technology routes (postcombustion, oxyfuel, and precombustion) that offer removal of CO2 from combustion and gasification processes. In postcombustion separation, CO2 is removed after the combustion process by chemical treatment of the flue gas with amines. Oxyfuel combustion systems use oxygen instead of air for combustion, resulting in the formation of CO2-enriched flue gas. Precombustion technology with a subsequent carbon monoxide (CO) shift reaction results in formation of CO2 and hydrogen gas (H2). If H2 can be continuously removed from the gas mixture, then CO2 can be easily separated and stored. Hydrogen can be used for electricity generation in gas turbines or for production of synthetic fuels or chemicals. The environmental performance of CCS beyond the reduction of CO2 emissions has increasingly become a subject of discussion.

For a holistic assessment of environmental effects, life cycle assessment (LCA) is a standardized method (ISO 2006) for determining all resources, emissions, and energy flows as well as their potential environmental effects along the whole life cycle of a product or technology. This “cradle-to-grave” approach implies the extraction of raw materials (including primary energy resources), their processing, all transport and manufacturing processes, product use, dismantling, and disposal.

In the last 10 years, several LCA studies have addressed the environmental effects of carbon capture at fossil-fuel power plants. The goal of this meta-analysis is to provide a structured overview of assumptions and methodological choices made and, where possible, their effects on the outcomes. Therefore the authors selected 15 LCAs that focus on CCS projects differing in capture technology, fuel used, time horizon, or region. Furthermore, CCS studies dealing with enhanced oil and gas recovery (EOR, EGR) are excluded to maintain comparability. While the primary purpose of EOR and EGR is to improve the recovery rate, and while they have their own requirements for the CO2 stream, the focus of CCS in the selected studies is to improve the greenhouse gas (GHG) performance in fossil-fuel power production. Nine studies have a European focus, three consider the United States, one looks at Japan, and two take a global approach. This report answers three key questions:

  • 1Is LCA an appropriate method to evaluate the environmental effects of CCS systems, and with what validity or limitations?
  • 2Is it possible to draw general conclusions regarding the environmental performance of CCS power plants compared to power plants without CCS from the existing LCAs?
  • 3Do certain trends arise across the different capture routes (postcombustion, oxyfuel, precombustion) or fuels used?

More detailed results and a comprehensive appendix including all data are available through the International Energy Agency's Greenhouse Gas Research and Development (R&D) Programme (IEAGHG) (Marx et al. 2010). Table 1 provides a glossary of abbreviations and acronyms used in this article.

Table 1.  Glossary of abbreviations and acronyms
Abbreviation Definition
ADPabiotic depletion potential
AIaggregated indicator
APacidification potential
CEDcumulative energy demand
CCScarbon capture and storage
CMLInstitute of Environmental Sciences of the Faculty of Science of Leiden University
EDIPenvironmental design of industrial products
EGRenhanced gas recovery
EORenhanced oil recovery
EPeutrophication potential
FAETPfreshwater aquatic eco-toxicity potential
GWPglobal warming potential
HTPhuman toxicity potential
IGCCintegrated gasification combined cycle
ISOInternational Organization for Standardization
LCAlife cycle assessment
LCIlife cycle inventory
LCIAlife cycle impact assessment
LUland use
MAETPmarine aquatic eco-toxicity potential
NGCCnatural gas combined cycle
ODPozone depletion potential
PCpulverized coal combustion
PM 10particulate matter equivalent
POCPphotochemical ozone creation potential
TETPterrestrial eco-toxicity potential
WUwater use

Systematic Comparison of the LCAs

A comparison of competing energy technologies requires a thorough understanding of each system and its boundaries. The use of the same assumptions regarding system boundaries and generic data is essential. The wide range of performance possibilities and methodological shortcomings of LCA make a close investigation of the LCAs and their comparability necessary.

Technical Differences

The 15 LCAs vary in the CCS technologies analyzed. Some studies compare different CCS technologies against each other, while other studies concentrate on one specific CCS technology or compare CCS against alternatives such as renewable energy production.

Capture Technology

The three technology routes for the capture process—postcombustion, oxyfuel, and precombustion—constitute the first differentiation criteria of the studies. Postcombustion is chosen most often as the investigated system (14 times), precombustion is analyzed less often (8 times), and oxyfuel is studied least (3 times). Monoethanolamine (MEA) scrubbing is the postcombustion technology of choice. Only three studies consider other postcombustion technologies (D’Addario et al. 2003; Khoo 2006) or other solvents (Muramatsu and Iijima 2002).

As fuel, hard coal is considered in 11 studies. In four studies (NEEDS 2008; Pehnt and Henkel 2008; Schreiber et al. 2009; Viebahn et al. 2007), local lignite fuel becomes an option. Three of the lignite studies look at Germany (Pehnt and Henkel 2008; Schreiber et al. 2009; Viebahn et al. 2007). NEEDS (2008) considers one power plant in Germany and one in the Czech Republic. Looking at a wider European or global view, natural gas must be integrated (eight studies). Table 2 illustrates the scope of each study examined in this meta-analysis.

Table 2.  Scope of LCA studies examined in this meta-analysis
Study/year Region Time horizon Fuel Capture Coverage Capt./trans. storage Outcomes
Hard coal Lignite Gas Postcomb. Precomb. Oxyfuel Emissions GWP Other impacts Normal step Aggregation
  1. Notes: n.a = not available; *= personal communication (Bauer 2009) based on NEEDS inventory; **=Bauer and colleagues (2008); capt./trans. storage = capture and transport storage; postcomb. = postcombustion; precomb. = precombustion; GWP = global warming potential.

D’Addario et al./2003 Middle ItalyPresent  xxx  xxx  
Doctor et al./2001 U.S.Presentx   x Only capt. + trans. xx  
IEA/2006GlobalPresent–2050x xxx  xxx  
Khoo/2006 U.S.Presentx  x  xxxxxx
Koornneef et al./2008 Netherlands2000/2020x  x  xxxxx 
Korre et al./2009 Globaln.a.x  x   xxx  
Lombardi/2003 Hypothetical (Italian costs)n.a.x xxx  xx   
Modahl et al./2009 Norwayn.a.  xx  x xxxx
Muramatsu and Iijima/2002 JapanPresentx  x  xxx   
NEEDS/2008Europe2020–2050xxxxxxxxxx* x**
Odeh and Cockerill/2008 UK2005x xxx xxx   
Pehnt and Henkel/2008 Germany2020 x xxxxxxx  
Schreiber et al./2009 Germany2020xx x  xxxxx 
Spath and Mann/2004 U.S.Presentx xx  xxx   
Viebahn et al./2007 Germany2020xxxxxxxxxx  

As CCS is a future technology, its representation in the literature varies considerably. The estimated process performance figures sometimes represent bench-scale studies and sometimes full-scale commercial plants for other applications. No common understanding of future efficiency of commercial power production exists, let alone of energy penalties due to capture. It is often not clear which detailed technical assumptions–technological representation or emission reduction efficiencies, for example–are used for the analysis. In figure 1, the net efficiencies and the assumed energy penalties of the different studies are presented with respect to the fuels used.

Figure 1.

Net efficiency and energy penalty for postcombustion, oxyfuel, and precombustion CCS technologies, according to the literature. In the case of hard coal, values for Korre and colleagues (2009) are not available; additionally, r. = retrofit, g. = greenfield. In the case of natural gas, values for Spath and Mann (2004) are not available. Plant efficiency refers to the left axis; CCS energy penalty refers to the right axis. Post, Oxy, and Pre refer to the carbon capture technologies of postcombustion separation, oxyfuel combustion, and precombustion separation.

For hard coal postcombustion, efficiency values fall between 29.6% (Schreiber et al. 2009) and 49% (NEEDS 2008). For lignite, the difference between the lowest efficiency (26.3%; Schreiber et al. 2009) and the highest efficiency (49%; NEEDS 2008) is even greater. The energy penalty of lignite fuel postcombustion power plants ranges from 5% to 18.2%. One reason for the significant differences is the underlying time perspective; another reason is the future technological assumptions of the studies. As expected, the study with the longest time horizon (to 2050) assumes the highest net efficiencies (NEEDS 2008). In the oxyfuel process, a large portion of the energy is needed for oxygen production. The specific demand is still very unclear, so figures range from 160 kilowatt-hours per tonne of oxygen (kWh/t O2) (Doosan Babcock Energy 2009) to 320 kWh/t O2 (Pehnt and Henkel 2008).1

Transport and Storage

After capture, the CO2 must be stored. Capture and storage sites will generally not be the same, thus transport has to be included in the LCA. Especially for transport and storage, site-specific information is necessary, which confirms the uniqueness of each study in this area of CCS. Several LCAs include CO2 transport and storage. However, the associated data are not always expressed separately: the two numbers are instead sometimes expressed as one. Additionally, the estimated share of transportation and storage on environmental impacts can vary by as much as one order of magnitude. While Modahl and colleagues (2009), Muramatsu and Iijima (2002), and Pehnt and Henkel (2008) calculate a share of transport and storage on the total global warming potential (GWP) of less than 1%, NEEDS (2008), Schreiber and colleagues (2009), and Viebahn and colleagues (2007) determine a contribution to GWP of between 3% and 10%. This figure depends on the investigated system and fuel. Smaller influences on the share of CO2 from transport and storage are the type of storage (gas field, aquifer), associated depth of injection, transport distance, and number of recompression steps along the pipeline. For instance, Wildbolz (2007) calculated a fourfold GWP value for a 400 kilometer (km)2 pipeline and storage in a 2,500 meter (m)3 deep depleted gas field in contrast to a 200 km pipeline and storage in an 800 m deep aquifer. The type of storage therefore has a greater influence than the transport distance.

Only Khoo (2006) and Viebahn and colleagues (2007) include leakage rates in a sensitivity analysis.

Differences in Life Cycle Assessment Methodology

With the wide margin of flexibility in performing LCAs (ISO 2006), some choices will heavily impact the overall results. In the following sections, different choices are systematically described and examples of the impacts on these choices are given.

Functional Unit

The functional unit in the studies compared is always 1 kWh of net electricity produced. A second product created in power plants is CO2. Although CO2 is regarded as a waste product to be stored, the gas is produced in different qualities, purities, and pressures by the different capture systems. These different characteristics of CO2 have an impact on the energy penalty. However, there is rarely information in the LCAs about the quality of CO2 produced. By comparing the studies, it is not clear to what extent a different CO2 quality might influence the results. The operating expenses for compression and transport are also dependent on CO2 purity.

Only D’Addario and colleagues (2003) keep the amount of captured CO2 constant. The amount of CO2 that is fixed can be regarded as an extension of the functional unit to a second parameter. Hence the results of this study are not directly comparable to the others. By adjusting the amount of captured CO2 to one specific value, D’Addario and colleagues change the capture rate of the systems compared, in contrast to the other studies where it is kept constant.

For precombustion, the coproduction of other products (e.g., hydrogen, sulfur) besides electricity is possible. In only one LCA has an allocation procedure been carried out for an integrated gasification combined cycle (IGCC) process with production of energy and hydrogen as a case study (Doctor et al. 2001).

Data Quality and Availability

One of the most common shortcomings in LCA is the quality of input data. In order for LCA to be widely accepted, specific and well-researched data are required. Data for future processes are rare and are based on assumptions that are unlikely to be unique for all data sources. Inevitably, some data will be characterized by a greater degree of uncertainty. Specific attention must be paid when the results are dominated by data from upstream (e.g., fuel or solvent supply) and downstream (e.g., wastewater treatment, disposal) processes, which are often not well understood and provide poor-quality data due to greater generalization of system boundaries. For power generation, data required to address many GHG emissions and acid rain precursors have been relatively firmly established, in contrast to data for photochemical smog or human toxicity.

Data for the LCAs investigated are gathered in many different ways. There are measured data for some process components, modeled data for specific systems, expert assumptions on technology development, literature-derived data for conventional technologies, estimations for data gaps, and figures from databases, especially for upstream and downstream processes. For life cycle modeling, nearly all studies use commercially available LCA software (SimaPro, TEAM, GaBi, Umberto); only a few develop their own software or models. The underlying power plant details are either done by personal modeling (often using Aspen) or by literature reviews. As several of the studies focus on Europe, the Ecoinvent database (Ecoinvent 2007) is often used for background data and upstream and downstream process chains.

Time Horizon

Another point of interest is the time horizon. Almost all studies consider present and future power plants and CCS systems up to the year 2020, when CCS technology is expected to be commercially viable. Only in IEA (2006) and NEEDS (2008) are the power plants modeled out as far as 2050. The performance data of the main processes (first-order processes) are updated to represent technical progress. Second-order processes (e.g., upstream coal chain, solvent supply chain, other energy and material supplies) and third-order processes (e.g., construction of infrastructure for the coal supply, CO2 capture facilities, or CO2 transport and injection) are seldom adjusted in the same way. However, for some background systems (e.g., energy mix, waste treatment of flue gas cleaning, and solvent residues), change is likely and can have a considerable impact on the results. Viebahn and colleagues (2007) update the data for the energy mix as well as for steel and aluminum production based on higher metal recycling rates in the year 2010. NEEDS (2008) and Schreiber and colleagues (2009) also consider different background systems (e.g., energy mix) based on different fuel import structures and energy scenarios in 2025 and 2050, respectively. Koornneef and colleagues (2008) use updated data for emission factors of flue gas cleaning units and electrical equivalence factors of enhanced capture units based on the future reference year 2020. All studies estimate technical progress in one or another way, without mentioning it explicitly.

The choice of time horizon plays an important role in evaluating the storage process and possible leakage. Comparison between short- and long-term emissions is an open question in LCA methodology, and is especially relevant to CO2 storage. Even with a GWP based on 500 years, the long-term emissions are implicitly cut off. It is not clear how far into the future long-term CO2 emissions from storage sites will have a negative environmental effect; forecasts about climate conditions and the CO2 buffer action of oceans and the biosphere are highly uncertain. The selection of storage sites will also favor sites with no leakage, so only a certain percentage will leak and will likely be abandoned quite early. However, the calculation of CO2 lifetime as the balance between the rates of removal and reemission is not the focus of the selected studies. Possible leakage of CO2 during long-term storage is analyzed by Khoo (2006) and Viebahn and colleagues (2007) in a sensitivity analysis to gain an idea of the impact and therefore not underestimate the storage phase by ignoring it. Viebahn and colleagues (2007) examine different annual leakage rates (1%, 0.1%, 0.01%, and 0.001% per year) for 40,000 years. In the case of 0.1%/year leakage, the total CO2 stored will be emitted again after 6,000 years. If the leakage rate is assumed to be only 0.01%/year, the total CO2 stored will be emitted again after 40,000 years. After nearly 7,000 years, half of the CO2 stored will have already been released.

In the discussion about weighting of short- and long-term emissions, other fundamental differences are observable in attitude and perspective. Some articles weight long-term effects over short-term, while others assume that long-term environmental problems will be solved by technological developments. Some articles suppose that every possible effect should be seriously taken into account, while others only engage in scientifically proven issues of concern. Hofstetter (1998) discussed the different “types of people” and developed a simplified characterization of archetypes—hierarchist, individualist, and egalitarian—by observing different criteria of time perspective, manageability, and required level of evidence used in some LCA validation methods (e.g., eco-indicator). These aspects result in different discounting rates for the different archetypes. However, until now there has been no differentiation in LCAs between short-, middle-, and long-term emissions. Consequently, a method should be developed for discounting long-term GHG emissions to compare these with short-term emissions in a widely accepted way.

Spatial Representation

Some elements in the CCS process chain are highly site-specific, such as coal origin and extraction, routes of coal transport to the power plants, and CO2 transport routes and storage sites. The LCAs use different coal types and coal import mixes. Power plants using low-rank coals (subbituminous or lignite) with relatively high moisture and low heating values need more coal per kilowatt-hour of electricity than power plants fired by hard coal. Furthermore, the coal sulfur content and ash content can have a major effect on emissions.

In CCS, the storage is highly site-specific. It is questionable whether an average storage modulation is applicable at all. Very limited LCA-specific information from the few existing storage sites is available. Therefore no information can be used to describe the process in those LCAs where storage is included. The common site-related assumption concerning storage that is made is the transportation distance between power plant and storage site. The number of wells and the energy demand for recompression and injection are only considered in a few studies (Khoo 2006; Koornneef et al. 2008; NEEDS 2008; Schreiber et al. 2009), and only Khoo (2006) generated data. The other authors used data from Wildbolz (2007). The impact assessments of the LCAs show that transport and storage impacts are small compared to the power plant itself. For second-order processes, many products are very site specific, such as the fuel and material supply and origin, or the electricity mix. This is not an explicit CCS issue, but shows a large impact on study outcomes. Hence efforts to improve the environmental balance of CCS should focus on improvements in power plant efficiency and capture techniques as well as on important upstream chains like coal supply and solvent production and disposal.

Environmental impacts contribute on different scales: global, regional, or even local. While the mechanism for global impact categories is the same worldwide, the impacts for regionally or locally scaled emissions can vary widely depending on ecosystem sensitivity. The methodological framework for these emissions and their impacts is still under discussion. Although there are now some approaches for including regionally differentiated environmental impacts (Posch et al. 2008; Seppälä et al. 2006), no study yet uses site- or region-dependent impact factors. On the one hand, the desired inclusion of regionally differentiated impacts results in even less comparability due to invisible differences in technology; on the other hand, it gives better insight into how identical technologies perform differently depending on location.

A first step in considering regional specifics is normalization. Normalization makes it possible to translate impact scores across categories into a relative contribution of the product or system based on a reference situation. Those studies that include the normalization step in their analysis (Koornneef et al. 2008; Modahl et al. 2009; Schreiber et al. 2009) use the same approach of CML 2001 (Guinèe 2002), but use country-specific data to set the relation.

Upstream and Downstream Processes

The system boundaries of power plant analyses commonly encompass all processes between the fuel extraction (mining of coal or extraction of natural gas) and storage of the captured CO2. The studies differ in the depth of their investigation upstream and downstream (table 3). Upstream and downstream process chains are often not represented with the same quality as the main processes. Downstream activities must be handled cautiously, as some studies include downstream chains in their investigation without explicit mention. The share of the environmental impacts of upstream and downstream processes differs with respect to the impact category in the 15 LCAs.

Table 3.  Consideration of life cycle phases and general upstream and downstream processes, including the capture-process
Study/year Construction Mining and transport Operation Dismantling General Capture-specific up/downstream
Upstream Downstream
D’Addario et al./2003  xx x  
Doctor et al./2001 xxxxxxx
IEA/2006 xx xxx
Khoo/2006  xx x  
Koornneef et al./2008 xxxxxxx
Korre et al./2009  xx xxx
Lombardi/2003 xxxxx x
Modahl et al./2009 xxxxxxx
Muramatsu and Iijima/2002 xxx x  
Odeh and Cockerill/2008 xxxxxxx
Pehnt and Henkel/2008 xxxxx x
Schreiber et al./2009  xx xxx
Spath and Mann/2004 xxx x x
Viebahn et al./2007 xxxxx x

Most of the studies include construction and dismantling. For conventional power systems it has often been shown that those life cycle phases can be neglected. Koornneef and colleagues (2008) and Pehnt and Henkel (2008) consider less than 0.2% of total GWP connected to the construction and dismantling of a power plant. The inclusion of CCS technology increases this value: due to the reduction of absolute emissions of power plant operations, the relative share increases. The studies differ in their estimation of the share of total infrastructure on total GHG emissions, from 0.34% in Lombardi (2003) for a hard coal-based IGCC to 4.9% in NEEDS (2008) for a lignite-fueled oxyfuel system. The share of infrastructural requirements for CO2 capture, transport, and storage on total GHG emissions is only 0.3% in Koornneef and colleagues (2008) for a hard coal postcombustion power plant and 0.83% of GHG emissions for total power plant infrastructure, including CO2 capture, transport, and storage.

Analysis of the different studies clearly shows the significant influence of the upstream and downstream processes on overall emissions and their impacts. For power plants with CCS, this influence is generally higher than for power plants without CCS, due to losses in efficiency and the associated additional amounts of fuel. For different impact categories, that share can vary considerably. Figure 2 shows the share of impacts from upstream and downstream processes on GWP.

Figure 2.

The share of impacts from upstream and downstream processes on global warming potential for several studies in power plants with and without CCS.

The share of impacts from upstream and downstream processes increases from about 10% to 50% to 60% for hard coal power plants without and with CCS, respectively (Koornneef et al. 2008; Schreiber et al. 2009; Viebahn et al. 2007). In the cases of a natural gas combined cycle (NGCC) plant (Modahl et al. 2009) and a power plant fired by lignite (Pehnt and Henkel 2008), the share of impacts from upstream and downstream processes is markedly smaller, amounting to only 30% and 20%, respectively, for CCS plants. The reason for this is the greater influence of a hard coal supply chain on the GWP compared with the natural gas and lignite supply chains. The important influence of coal type, origin, and transport routes has been verified in some LCAs (see Korre et al. 2009; Odeh and Cockerill 2008; Schreiber et al. 2009).

Life Cycle Inventory

In the life cycle inventory (LCI), all inputs and outputs connected with the production of 1 kWh of electricity are gathered. It is not possible to present the enormous amount of data for all technologies considered in the study. Normally these data are managed in the LCA software. Nevertheless, the estimated emissions build the basis for the subsequent impact assessment and comparison. For better understanding and transparency, some studies present selected input and output data. Input data are typically the amount of coal or scrubbing solution. Frequently discussed emissions are sulfur oxides (SOx) or nitrogen oxides (NOx). CO2 emissions are also generally accounted for. Some studies (Doctor et al. 2001; Koornneef et al. 2008; Pehnt and Henkel 2008; Schreiber et al. 2009) also include other, less frequently measured emissions, such as hydrogen fluoride (HF), hydrochloric acid (HCL), monoethanolamine (MEA), and ammonia (NH3), which affect other environmental impacts.

Impact Categories

For some impact categories, several characterization models and category indicators are suggested. It therefore might be that studies, although addressing the same impact category, cannot be compared directly because they use different category indicators. To transform the results into the same indicator, a detailed knowledge of all emissions is indispensable, but such knowledge is largely unavailable.

The evaluated impact categories vary from solely GWP in Lombardi (2003) and Muramatsu and Iijima (2002) to a wider spectrum with 10 environmental categories in Koornneef and colleagues (2008). Table 4 gives an overview of the impact categories used. The NEEDS (2008) study considers only inventory data. On the basis of these data, Bauer (2009) provides impact data for a 2025 system to allow for comparison with the other studies.

Table 4.  Impact categories considered in the studies
  1. Note:* denotes personal communication with Bauer (2009). GWP = global warming potential; AP = acidification potential; EP = eutrophication potential; POCP = photochemical ozone creation potential; ODP = ozone depletion potential; HTP = human toxicity potential; FAETP = freshwater aquatic eco-toxicity potential; MAETP = marine aquatic eco-toxicity potential; TETP = terrestrial eco-toxicity potential; CED = cumulative energy demand; ADP = abiotic depletion potential; PM 10 = particulate matter, 10 μm diameter; LU = land use; WU = water use; W = waste; AI = aggregated indicator.

D’Addario et al./2003 xxxx        x  
Doctor et al./2001 xxxx x  xxxxx  
IEA/2006xxxxxxx xx     
Khoo/2006 xxx  xxxxx   xx
Koornneef et al./2008 xxxxxxxxxx     
Korre et al./2009 xxxx xx  x     
Lombardi/2003 x              
Modahl et al./2009 xxxx     x    x
Muramatsu and Iijima/2002 x              
NEEDS/2008xx*x*x*     x*     
Odeh and Cockerill/2008 x        x     
Pehnt and Henkel/2008 xxxx x   x     
Schreiber et al./2009 xxxx x   x     
Spath and Mann/2004 x        x     
Viebahn et al./2007 xxxx     xx    

Only those categories for which a sufficient number of studies use the same impact indicator are chosen for comparison. The considered categories are GWP, acidification potential (AP), eutrophication potential (EP), photochemical ozone creation potential (POCP), and cumulative energy demand (CED). It has to be stated that Koornneef and colleagues (2008) and Korre and colleagues (2009) cover information about resource depletion in the category “abiotic depletion potential” (ADP). As they are the only two, CED was chosen instead.

One impact category that is significantly affected by CCS technology is the human toxicity potential (HTP). The studies that include this category often show an increase of nearly 200% for systems with CCS. Unfortunately, HTP is one of the impact categories needing more research to consolidate exposure pathways of emissions and select the most appropriate impact model and indicators. Although HTP is considered in most studies, the use of several different impact indicators makes comparison impossible. Normalization also shows that HTP for conventional power production systems is quite low. Even with a dramatic increase in HTP in CCS plants, the fraction remains low. In the end, it should be stressed that the scores for toxicity potentials (HTP, marine aquatic eco-toxicity potential [MAETP], freshwater aquatic eco-toxicity potential [FAETP]) are often highly uncertain due to inaccurate data on production processes or open questions on characterization.

Operational Valuation and Weighting Methods

It is generally recognized that valuation requires political, ideological, and ethical judgments, and that these are influenced by perceptions and worldviews. Weighting factors, choice of valuation methodology, and choosing to use a valuation method at all are influenced by fundamental ethics and ideologies (Hofstetter 1998). Because there is no consensus on these fundamental values, neither is there consensus on weighting factors, valuation methods, or the choice to use valuation.

In many studies, different impact categories are simply listed equally side by side. Only two studies use models to weight and aggregate the results in a single score (table 4). Khoo (2006) and Modahl and colleagues (2009) have chosen two and three different aggregation methods, respectively, to test the robustness of their results. Khoo (2006) used Environmental Design of Industrial Products (EDIP; a problem-oriented midpoint approach) and Eco-indicator ’99 (a damage-oriented endpoint approach), while Modahl and colleagues (2009) selected an IMPACT 2002+ combined midpoint/damage approach, EDIP, and an EPS 2000 monetizing method. While trends in the results of EDIP and Eco-indicator ’99 in Khoo (2006) are similar, the discrepancy in magnitude demonstrates the distinction between midpoint and endpoint approaches. In the work of Modahl and colleagues (2009), all results display similar trends. The article states that toxic effects are strongly in focus in the EDIP method, while in EPS 2000 and IMPACT 2002+ the use of nonrenewable energy dominates. In the work of Bauer and colleagues (2008), the final results based on the NEEDS (2008) inventory are presented using Eco-indicator ’99 and the IMPACT pathway analysis external costs method.

The trends of the results in the work of Bauer and colleagues (2008) based on the NEEDS (2008) inventory differ between the damage-oriented Eco-indicator and the external cost approach. The choice of fuel has an especially big impact on the results. While natural gas proves worst in Eco-indicator ’99, it is best for external costs. Within one fuel group, power generation with CCS clearly performs better on external costs, while Eco-indicator ’99 does not always show considerable advantages. The choices of weighting and grouping clearly determine the outcome of a study.


The CCS technologies are compared considering different capture techniques and types of fuel. As most studies include coal-fired electricity production, the results shown in this article refer only to hard coal. For lignite and natural gas, see the full report by Marx and colleagues (2010). The absolute impact equivalents of each electricity generation technology are presented in figures 3a and 4a. The subsequent graphs (figures 3b, 3c, and 3b) show the relative differences in absolute figures due to CO2 capture. As previously discussed, a presentation of relative changes in one diagram without further analysis might overvalue impact categories with big changes but small contribution to total environmental impacts. Therefore yearly contribution to a specific region is used in a normalization step. As the different studies cover different regions, the average global values for the year 2000 (the latest available values from CML 2001) are chosen for a reference system for the different impact categories. For consistency, electricity generation figures for the different energy sources in the same year, 2000, are considered: hard coal (5,296 terawatt-hours [TWh]),4 lignite (693 TWh), natural gas (2,676 TWh) (OECD/IEA, 2007). It is then estimated what impacts electricity produced exclusively by CCS technology would have had. Two cases are calculated: In the first (best) case for each fuel type, the technology with the lowest impact values in all the LCA studies is used to calculate the impacts of electricity production, representing the best performance possible. In the second (worst) case, the technology with the highest impact values is used in the calculation, representing the worst performance. This step reveals the importance of the various impact categories associated with electricity production and relates the results to worldwide impacts.

Figure 4.

Environmental impacts of an integrated coal gasification system without capture (a) and relative impacts of systems with precombustion capture (b) (left axis). On the right axis are normalized values relative to total global emissions in 2000 and calculated for lowest and highest impact values. IGCC = integrated gasification combined cycle; CCS = carbon capture and storage; GWP = global warming potential; AP = acidification potential; EP = eutrophication potential; POCP = photochemical ozone creation potential; CED = cumulative energy demand. For color versions of this figure, please see figures S2a and S2b in the supporting information on the Web.

Figure 3.

Environmental impacts of hard coal-fired pulverized coal combustion technology without capture (a), and relative impacts for plants with (b) postcombustion/monoethanolamine (MEA) or (c) oxyfuel capture (left axis). On the right axis are normalized values relative to total global emissions in 2000 and calculated for lowest and highest impact values. NEEDS PC 2025 is based on Bauer (2009). CCS = carbon capture and storage; CO2 equiv. = carbon dioxide equivalent; SO2 equiv. = sulfur dioxide equivalent; PO3-4 equiv. = phosphate equivalent; C2H4 equiv. = ethylene equivalent GWP = global warming potential; AP = acidification potential; EP = eutrophication potential; POCP = photochemical ozone creation potential; CED = cumulative energy demand. For color versions of this figure, please see figures S1a, S1b, and S1c in the supporting information on the Web.

The absolute GWP of the pulverized hard coal combustion technology without capture varies from 765 grams of CO2-equivalent per kilowatt-hour (g CO2-eq/kWh)5 to 1,092 g CO2-eq/kWh, depending on the estimated efficiency and type of coal used (figure 3a). Acidification potential values are more scattered. Koornneef and colleagues (2008) assume a very high value (2.76 g sulfur dioxide equivalent per kilowatt-hour [g SO2-eq/kWh]) for “old” average pulverized coal combustion (PC) plants from 2000; Korre and colleagues (2009) find a lowest value of 0.39 g SO2-eq/kWh. EP, POCP, and CED do not vary considerably.

The normalization shows that power generation without CCS is a considerable portion of the total global GWP, with 13.2%, assuming worldwide power production with only low-performance plants. If the best technology is used worldwide, still 10% of total global GWP is related to power production. The share of global AP from power production using worst-case technologies is 3.5%, while best-case technology reduces this value to about 1%. Effects on the EP and POCP are even smaller. As expected, the results of a hard coal power generation system with CCS clearly indicate a substantial reduction in GWP (figures 3b and 3c). The LCAs show an increase in all the other impact categories considered (AP, EP, POCP, and CED) for postcombustion; this is due to loss of power plant efficiency and associated increases in coal and solvent supply, as well as use and disposal of solvent and its residues. For instance, the share in global AP increases from 3.5% to 5.3% for the worst-case scenario, mainly due to the energy penalty for CCS power plants resulting in more fuel input and transport. In several LCAs, EP and POCP increase by 100% or more compared to power plants without CCS. Still, the normalization figures show global shares of 2% or less for technologies with high EP and POCP, and they are negligible for best-case technologies. The impact assessments of the two studies analyzing hard coal oxyfuel power plants present no consistent results except for GWP. The values for AP lie between −16% and 40% and the values for EP lie between −9% and 40%. For POCP, values lie between 23% and 54%. Reasons for this might be the differences in efficiency and energy penalty, improvements in flue gas treatment, or the distribution of SO2 and NOx in the compressed CO2 stream versus in flue gas emissions. This implies that no general conclusions can be drawn for the environmental assessment of oxyfuel power plants from two studies.

The absolute figures for the IGCC system are in the same range as the other techniques, and all impact categories besides GWP increase with precombustion. For IGCC, the increase across all impact categories (except GWP) is approximately 40%, higher than expected due to the capture penalty (figure 4). The reason for this, as previously discussed, is the contribution of upstream (major) and downstream processes. Hence IGCC with CCS shows the same tendency as postcombustion technology, but to a lesser degree. The share of AP increases from 1.7% to a maximum of 2.4%. Only Doctor and colleagues (2001) show a decrease in AP.

In summary, for all fuel types and capture systems, only GWP is a robust impact parameter for comparison across LCAs. For a reliable statement about all environmental impacts, better documentation in LCA, including well-described assumptions, parameters, and uncertainties, is necessary.


Although several LCAs have been performed on CCS in recent years, there are not sufficient data to draw any robust conclusions. The wide range of possible CO2 capture, transport, and storage technologies makes it difficult to sufficiently compare studies. A sophisticated and common understanding of the most important technological parameters is necessary to draw a clearer picture of both single CCS techniques and comparisons across techniques, especially for the oxyfuel process, but also for precombustion. Therefore it is essential that LCAs include well-documented parameters and describe uncertainties and assumptions precisely. To increase the comparability of studies, it is helpful to have a set of background or benchmark information about key parameters of technologies such as efficiency development and energy penalty. New, second-generation technologies, such as chilled ammonia and membranes, should also be covered.

There are some upstream and downstream processes that have a large impact on the results. As not all practitioners of LCA use the same coal input, it would be helpful to present the underlying coal parameters, such as composition, heating value, and transport distances. Production and waste management of solvents also have major impacts on the results. Until now, most studies have used old data from the Ecoinvent database. Because the results are so important, it is worth taking a more detailed look into these upstream and downstream process chains, as well.

Another discussion, in its infancy, is the question of different CO2 qualities and products. Are two processes really comparable if they have the same functional unit of 1 kWh of electricity, but two different CO2 products with different values (like properties and prices), and most probably different requirements (like energy demand) to reach them? Different CO2 qualities do not hinder an equal comparison of two CCS systems from a full life cycle perspective. However, more attention should be paid to assessing how quality requirements change the process performance of CO2 capture.

To streamline the LCA, it is helpful to have prior agreement about impact categories to be considered. Commitment to a particular category indicator yields more comparable data. To get a better understanding of the results, it is very important to consider normalizing in the context of regional impacts so that their importance is not overestimated.

Once the understanding of the life cycle effects of CCS is more robust, the comparison of CCS with other GHG emission mitigation measures, particularly renewable energies, will be useful. Overall performance benchmarks can be concluded from this form of comparison and, once established, can help to identify development targets for CCS. Again, the precise definition of the functional unit will have to be resolved in order to compare conventional and renewable systems. The different availability of 1 kWh of electricity produced by these alternative systems has to be kept in mind when defining the systems boundaries of an LCA.

The LCAs clearly show a considerable decrease for GWP and an increase in many other impact categories by using CCS. Some of these increases are largely associated with upstream chains (e.g., coal supply, solvent use). However, the normalization indicates only a small impact from CCS power plants on total global AP, EP, and POCP. The coal supply–due to losses in power plant efficiency, the production of solvents for CO2 capture, limestone for SO2 control, and ammonia for NOx removal–will increase considerably by the planned large-scale implementation of CCS technology (retrofitting and greenfield plants).


The authors are grateful to Mike Haines for his contribution to the earlier, full version of this research (Marx et al. 2010). The authors would like to thank the IEA Greenhouse Gas R&D Programme for financial support.


  • 1

    One kilowatt-hour (kWh) ≈ 3.6 × 106 joules (J, SI) ≈ 3.412 × 103 British thermal units (Btu). One metric ton (t) = 103 kilograms (kg, SI) ≈ 1.102 short tons.

  • 2

    One kilometer (km, SI) ≈ 0.621 miles (mi).

  • 3

    One meter (m, SI) ≈ 3.28 feet (ft).

  • 4

    One terawatt-hour (TWh) ≈ 3.6 × 1015 joules (J, SI) ≈ 3.412 × 1012 British thermal units (Btu).

  • 5

    One gram (g) = 10−3 kilograms (kg, SI) ≈ 0.035 ounces (oz). CO2-eq: Carbon dioxide equivalent (CO2-eq) is a measure describing the climate-forcing strength of a quantity of greenhouse gases using the functionally equivalent amount of carbon dioxide as the reference.

About the Authors

Josefine Marx is a mechanical engineer, Andrea Schreiber, PhD, is a chemist, and Petra Zapp, PhD, is an energy and process engineer, all working on environmental and energy analyses at the Institute of Energy and Climate Research—Systems Analysis and Technology Evaluation, in Jülich, Germany.