Detailed Process

This page offers a summary of the process for conducting life cycle assessments (LCAs) as outlined in the Techno-Economic Assessment & Life Cycle Assessment Guidelines for CO2 Utilization (Version 2.0) published by the Global CO2 Initiative. Please note that the guidance offered on this page is primarily tailored toward carbon capture and utilization (CCU) technologies although the general framework can be adapted to any technology.

If you are conducting your own life cycle assessment, you may find value in reading through this page to gain a high-level understanding of the process and then using the guidelines document directly to complete the study. Our templates and instructional videos may also be useful when conducting the study.


LCA is a quantitative evaluation of the various environmental impacts of a product throughout all stages of its life cycle, including raw materials extraction, manufacturing, distribution, use, recycling, and disposal. These impacts can include contribution to climate change, ground-level ozone creation, atmospheric ozone depletion, human toxicity, eco-toxicity, and fossil energy depletion.

High-level standards for conducting LCAs are set by ISO 14040 and ISO 14044. The Global CO2 Initiative’s guidelines are consistent with the ISO standards but offer guidance that is more uniquely tailored to carbon capture and utilization technologies. The primary steps within the LCA framework are shown in the graphic below.

Life cycle assessment framework: goal, scope, inventory, impact assessment, and interpretation along with direct applications of LCA

Once the goal and scope for the study are defined, the practitioner can collect necessary inventory data. This data is then analyzed as part of the impact assessment, which translates the inventory data into quantified environmental impact metrics. The iterative interpretation phase takes place throughout the study to update the goal and scope as it becomes clear whether the purpose of the study can be fulfilled. Once the study satisfies the goal, results can be used to help a variety of stakeholders develop and improve products, plan for necessary changes to meet regulatory requirements, make relevant policies, advertise and promote products, and more.

Consistent guidance for conducting LCAs is important for standardizing results and allowing for “apples-to-apples” comparisons across technologies. LCA is particularly important for carbon capture, utilization, and storage (CCUS) technologies as it is vital to know if and how they offer environmental benefits compared to their fossil fuel-dependent alternatives. In addition to characterizing benefits and identifying potential areas of improvement, using LCA helps identify and avoid the shifting of environmental burdens from one environmental impact category to another or from one stage to other stages of a product’s life cycle.

Identifying a Goal for the Assessment

LCA goals guide the rest of the study. While LCA cannot determine whether a product is “sustainable” or “green” without separately imposed definitions or thresholds for these concepts, it can provide important information about how products relate to each other in terms of environmental impacts. LCA can also identify environmental hotspots for a technology and help uncover effective strategies for reducing those impacts.

The goal of the study explicitly states how the study will be used to accomplish these ends. Common goals for CCU LCAs include determining environmental benefits relative to fossil-based benchmark products, seeking environmental hotspots for technology developers to address, and quantifying environmental impacts that customers are likely to care about when making purchasing decisions.

Thus, the LCA goal should state the core research question motivating the study as well as how results are intended to be used. In addition, the practitioner should state the intended audience, the study commissioners, whether comparative assertions will be made, and potential limitations of study results.

Intended scenarios for scenario analysis should also be communicated. As CCUS technologies often involve significant energy consumption, scenarios often model the use and subsequent impacts of different possible energy sources. Any scenarios chosen should be consistent with those chosen for any corresponding techno-economic assessments (TEAs) that are also being performed.

All of this information is important for both shaping the study as well as increasing its transparency, which helps ease the processes of peer review or replication of the assessment.

Setting the Scope

Setting the scope for the LCA is often one of the most complicated steps as it involves fully mapping out the life cycle of the system under consideration, considering the final function of the product, drawing reasonable system boundaries to demarcate the unit processes that will be assessed, and addressing allocation of impacts between multiple products produced by a single industrial system. All of these considerations also make setting the scope one of the most important steps of an LCA, as it determines what inventory data is necessary to accomplish the goal of the study.

The product application is the first thing that must be defined as part of the scope of the assessment. This is how the product will be used by the customer or final user. Once the application is specified, the functional unit and reference flow must be described. The functional unit is a quantified description of the application. The reference flow is the quantified amount of the product necessary to achieve the performance described by the functional unit.

For example, the product application or function of a lighting system might be to provide light to the user. The functional unit could then be described in terms of lumens, which is a measure of brightness. The reference flow could be the number and type of light bulbs necessary to reach a specific level of brightness. An LCA comparing LED and fluorescent bulbs, for example, might consider the different numbers of each type of bulb necessary to reach the same functional unit of brightness. While lighting systems involve many other important characteristics, such as different colors or the ease of installation, these may be excluded to simplify the analysis. These characteristics must still be reported, however, and inclusion or exclusion must be transparently justified.

There are certain guidelines for setting functional units that are especially relevant for CCU technologies shown in the below decision tree.

Decision tree with questions to ask to set functional units and system boundaries. Cradle-to-gate for substitutes, else cradle-to-grave

In some cases, the CCU process might involve the production of a product that is a molecularly identical substitute of an existing product. An example might be a commodity chemical that is currently made using a fossil feedstock but could be made using captured CO2 instead. In this example, it would make the most sense to compare the products on the basis of mass instead of product performance, as 1 kg of the CCU product will be physically equivalent to 1 kg of the conventional product.

A similar logic applies to fuels; gasoline from a CCU source should be compared to conventional gasoline on the basis of energy content, using a unit such a 1 megajoule (MJ) of fuel. In cases where the CCU product is molecularly different from the conventional product, the LCA may require comparison on the basis of some lifetime performance measure to capture subsequent differences in the product’s performance. For example, concrete that sequesters CO2 and involves a different mix than conventional concrete may last longer, in which case the basis of comparison could potentially be normalized to years of service rather than merely mass.

Once the practitioner specifies the functional unit and reference flow, the system boundaries must be mapped out. System boundaries refer to the life cycle stages and processes that are considered in a given study. Cradle-to-grave assessments assess every stage of a product’s life cycle from raw materials extraction to final recycling or disposal. Cradle-to-gate assessments analyze every stage from raw material extraction to when the product leaves the factory gate, meaning that the use phase and any subsequent phases are ignored. Practitioners should carefully deliberate over what to include and exclude in a given system boundary, and they should transparently report all justifications for their decisions.

Note that the source of CO2 should always be included in the system boundaries for CCUS assessments given that carbon capture is a fundamental part of these technologies. For more information about life cycle accounting for feedstock CO2, please refer to “The carbon footprint of the carbon feedstock CO2 by Müller et al., which is a direct follow-up of the Global CO2 Initiative’s guidelines.

As the decision tree above shows, cradle-to-gate analysis is recommended if a new CCU product is an identical substitute of a conventional product, as impacts after the factory gate are likely to be identical. The graphic below demonstrates how this could be the case with a CCU product.

Sideways bar graph showing similar impacts after a product's production if it's an exact substitute of a conventional product

In addition to identifying the life cycle stages that will be considered, setting the system boundary also involves classifying all of the unit processes—the individual processing steps along a product’s life cycle—and other material and energy flows. Only an estimate of material and energy flows is necessary at this point because specifics will be calculated as part of the inventory phase. The system boundary is then “drawn around” the unit processes to demonstrate what will and will not be considered as part of the study. The graphic below depicts a simplified visualization of a system boundary.

Unit processes in an LCA system with input flows entering and output flows leaving system boundary

In reality, all systems in the world are connected to one another in some way. Of course, not everything can be assessed by one study, and the practitioner needs to draw system boundaries that support meeting the goal of the study. For example, in an assessment of the use of carbon-sequestering concrete for a road, it would probably not make sense to assess the production of the cars that drive on that road even though this is a system that technically intersects with the use of the concrete. Some factors, such as how automakers might change the design of their cars if this concrete were used to construct certain roads, are likely too uncertain to assess in a rigorous way.

However, if the carbon-sequestering concrete led to a different amount of local particulate matter pollution from tires on existing cars, this is likely something that could be captured in the LCA and would be relevant to analyze depending on the goal of the study. Setting system boundaries demands a great deal of attention and careful thought from practitioners given its complexity.

Specifying how the study will handle multifunctionality is another important aspect of the scope phase. Multifunctionality refers to systems that have more than just one function, which can include the use of wastes from other processes as inputs, the use of waste from the process under consideration in the process itself, or the production of valuable co-products. CCU systems generally involve a source of CO2 (such as an industrial point source or direct air capture) that is used to create some product and often multiple products, meaning that multifunctionality is a common issue when conducting LCA for CCU. There are multiple ways to address multifunctionality, and there is clear guidance and a hierarchy of methods to follow provided as part of the ISO LCA standards and the ILCD Handbook.

Ideally, a method known as subdivision can be used, which isolates and allocates impacts on dedicated production lines for each product. This may be applicable when direct air capture of CO2 provides a dedicated stream for utilization. However, CCU often entails expanded analysis as the CO2 frequently comes not from direct air capture but from a source that is making another product, such as electricity, cement, or steel.

System boundary expansion involves integrating the plant that could act as the CO2 source into the study to allow for a more holistic assessment of the incremental impact of the CCU production system. When doing system boundary expansion, both the “main product” and the “reference product” will be included in the functional unit of the assessment. The graphic below shows how one might structure this analysis.

Reference production vs. CCU production showing need to consider main product production in system boundary expansion

The reason that a practitioner may want to consider both the production system under consideration as well as the separate “main product” production system (which could be something such as electricity, cement, or steel) is that extra energy and materials will have to be generated and used to capture and transport the CO2. There may also be impacts on product quality for the “main product” that may have to be compensated for and thus considered in the study. These extra needs must be accounted for in order to have a holistic understanding of the environmental impacts of the process.

For example, when CO2 is captured from a natural gas-fired power plant, there will likely be what is known as a parasitic load, which refers to the amount of energy that is used in the CO2 capture and compression process. More gas may need to be burned to make up for the use of this energy, which means that a certain level of captured CO2 will be offset by extra emissions. As carbon capture and the parasitic load are not occurring at the gas plant in the case of the benchmark or reference production system, LCA practitioners have to compare the anticipated changes to the systems in order to fully account for the incremental differences between the two processes.

Other ways of addressing this problem are discussed in section C.4.3.3 of the Global CO2 Initiative’s LCA guidelines. These include methods for allocating environmental impacts to processes that yield multiple co-products. Allocation can be based on mass, energy content, cost, or other factors.

LCA practitioners must think very carefully about all of the incremental differences between the CCUS system and the benchmark/reference system when setting the scope of the study. These differences may substantially influence the inventory data that must be collected and ultimately have a significant impact on the results of the study.

Collecting Inventory Data

In the inventory collection phase of the study, data related to the material and energy flows through the entire process are specified. This begins by defining the flows of material and energy between all of the different unit processes listed as part of the scope definition. While full mass and energy balances for the entire process in the system boundaries are preferable, this level of detail may not be necessary depending on the goal of the study.

It is often necessary to use various estimation methods to bridge potential gaps in data. Any such methods should either be compliant with the goal and scope of the study or lead to changes in expectations from the study. One such method is using stoichiometric, mass, or energy balances and assuming 100% efficiency in terms of material savings and energy use throughout the process.

If it is found that the CCUS system is more environmentally damaging than the benchmark system even with 100% efficiency (the best-case scenario), then the practitioner knows that the real system that would feature some level of inefficiency will not be superior to the benchmark product. This kind of analysis is common for early-stage technologies that involve uncertainty with respect to how efficient the scaled process will be.

Another estimation technique involves gate-to-gate inventory estimation, which applies factors derived from past, empirical studies to the yields of material and energy at each step. Deviation ranges for these factors can also be used to conduct sensitivity analysis during the interpretation phase. Section C.5.2.2 in the LCA guidelines contains references to papers that explain this method. Finally, there are emerging techniques using artificial neural networks that can help researchers in the event of a total lack of process data.

Often, flows related to the material and energy involved in the manufacture of capital equipment for the process are ignored, as they are difficult to find and most capital equipment contributes very little in terms of environmental impacts when their individual impacts are allocated across the large number of products they produce over their lifetimes. However, this is not always the case, so some studies may want to consider the impacts that arise from purchases of capital equipment if these impacts are expected to be substantial.

Conducting an Impact Assessment

Note: this website contains an LCA databases page that links to various sources where impact assessment data for LCAs can be found. Many impact assessments are not performed manually but rather are performed using custom LCA software, such as SimaPro, GaBi, and openLCA. While some of these software packages can require expensive subscriptions and experience to use, they are utilized very frequently by professional LCA practitioners and can make the process much easier.

After the inventory is complete, the LCA practitioner will have an entire process flow diagram listing quantified material and energy flows taking place throughout an entire product system, including for any co-products, utilized wastes, and recycled inputs. The impact assessment phase translates these flows into corresponding environmental impacts in a way that attempts to satisfy the goal of the study.

Environmental impacts result from a complex set of interactions between materials and the environment. In LCA, there is a distinction between midpoint indicators and endpoint impacts. Midpoint indicators occur earlier than endpoint impacts in the cause-and-effect chain of events and are thus more direct consequences of a process. An example of a midpoint indicator could be the contribution to climate change, which is measured in kilograms of carbon dioxide equivalent (kg CO2-eq) emissions from a given process. When conducting an LCA, a practitioner might calculate this midpoint indicator in particular by:

  • Finding the greenhouse gases emitted per unit for all of the different material and energy flows specified in the inventory;
  • Multiplying these factors by the total amount of each flow;
  • Adding to find the total greenhouse gas emissions from the system;
  • Converting the different greenhouse gas emissions into carbon dioxide equivalent values using something like the Intergovernmental Panel on Climate Change’s 100-year global warming potential factors; and
  • Dividing by the number of units produced by the system to determine the kg CO2-eq per unit produced to compare to the value for the benchmark product or convert into an endpoint impact for further analysis.

Endpoint impacts occur at the end of the cause-and-effect chain and are therefore more uncertain than midpoint indicators. An example could be the health impacts on humans as a result of the level of climate change caused by the greenhouse gas emissions from the process. While endpoints are important to society and are easier to communicate about and conceptualize, there are often significant levels of uncertainty in terms of how midpoints quantitatively translate to endpoints. Multiple midpoints often contribute to the same endpoints as well (e.g., both climate change and ground-level ozone creation affect human health), which can lead to compounding uncertainties.

Regardless, midpoint indicators are a necessary part of LCA. They can be found by multiplying factors describing the level of different environmental impacts per unit of material or energy by the materials and energy used by a particular system and then applying specific impact assessment methods as necessary. The focus of CCUS technologies is often on reducing carbon dioxide emissions relative to the benchmark product, meaning that practitioners generally put a great deal of effort into ensuring accurate factors for greenhouse gases emitted by the materials and energy used in the product system.

Some practitioners may be interested in only analyzing the CO2 or greenhouse gas emissions from a process. Such analyses are referred to as carbon accounting and greenhouse gas accounting, respectively. LCA generally requires that practitioners assess all environmental impact categories over all stages of a product’s life cycle. All of these studies may feature similar approaches, but it is important to use the proper terminology to ensure clarity and consistency.

Impact categories other than climate change-related ones that may be assessed using both midpoint indicators and endpoint impacts include ozone layer depletion, acidification, eutrophication, human toxicity, and so on. Choice of impact categories depends both on the study’s purpose along with the data available. Calculating all of the other environmental impacts arising from a process is necessary to either create strategies to reduce their burden or fully understand the environmental tradeoffs that a particular technology might involve.

There are many different defined methods for conducting impact assessments, and each includes different impact categories. For example, the International Environmental Product Declaration System uses a method called CML that is provided by the Institute of Environmental Sciences at the University of Leiden, which is also the default recommended method by the Global CO2 Initiative’s LCA guidelines. The geography and audience of the study may dictate what method should be used. For Europe, the method provided by the European Commission’s Joint Research Centre is frequently used, and for the United States, the use of the Tool for Reduction and Assessment of Chemicals and Other Environmental Impacts (TRACI) method is common. When normalizing different greenhouse gas emissions to their CO2 equivalent basis, the global warming potentials for 20- and 100-year time horizons from the Intergovernmental Panel on Climate Change are recommended.

Interpreting Results

The interpretation phase both ends the iterative aspect of previous phases and conducts analysis to yield specific conclusions and recommendations relating to the goal of the study. The latter is done using uncertainty and sensitivity analyses to help uncover the most important inputs and how their variation could affect results. Scenario analysis using the scenarios identified in the goal phase should also be performed in this step.

Given that carbon capture, utilization, and storage technologies make significant use of CO2 and are often intended to reduce climate impacts, the determination of the net emissions from the product’s process is often a highly relevant part of the conclusions of corresponding LCAs. It is imperative that practitioners pay careful attention to the labels they are using for a particular technology. The graphics below help demonstrate when a technology can be carbon neutral, carbon negative, or GHG emission reducing.

Carbon neutrality from releasing as much CO2 as removing. Negative emissions from sequestering more atmospheric carbon than releasing
GHG or carbon emission reducing if emissions less than conventional product system but still positive overall
In these diagrams, the color gradient of the arrows represents the distance of the carbon dioxide from the atmosphere, the blue dashed lines represent an exchange with the atmosphere, the minus signs represent sequestration of carbon dioxide, and the grey boxes in the sky represent accumulation of carbon dioxide in the atmosphere

A process is carbon negative only if it involves removing carbon from the atmosphere and permanently sequestering it without causing more emissions elsewhere. An example of this could be direct air capture and geological sequestration, both powered by renewable energy sources. CCUS technologies can only be carbon neutral if they permanently sequester as much CO2 as they release or if they release CO2 that was recently captured from the atmosphere.

A simple example of a carbon neutral system could be a highly efficient biomass energy project (grown on non-deforested land), where specific, dedicated crops absorb CO2 from the atmosphere as they grow that is then released back into the atmosphere when they are combusted for energy. CCUS processes can also be carbon neutral if they sequester the same amount of CO2 that is taken out of the ground to perform a given industrial process. An example of this could be complete sequestration of the CO2 generated by the production of steel assuming other parts of the process were decarbonized as well.

GHG emission-reducing technologies simply reduce the amount of CO2 released into the atmosphere relative to the conventional product. These could also be referred to as “carbon reducing,” but this term is not recommended as “carbon reduction” has a specific and separate chemical meaning. An example of a GHG emission-reducing process could be manufacturing methanol using captured CO2. This process still involves a level of emissions and will release CO2 back to the atmosphere when the methanol is used in a downstream process, but CCU methanol can emit less over its life cycle than methanol from conventional sources, making this technology GHG emission-reducing. Consistently and accurately using terms like carbon negativity, carbon neutrality, and GHG reduction is important for establishing a commonly accepted understanding of these vital concepts.

Uncertainty in the results of the LCA study can arise from parameter uncertainty, model uncertainty, or uncertainty related to choices of the practitioner. These sources respectively represent imprecise measurements or estimates, issues with system boundaries and impact assessment methods, and possible issues arising from the choice of functional units or allocation methods. Uncertainty analysis in LCA can address all of these different types of uncertainty. Parameter uncertainty analysis is performed by modeling how different potential values for input parameters change the final results of the model. These values are generally uncovered during inventory data collection. Separately, there are various methods, including Monte Carlo simulations, for conducting further uncertainty analysis that can addresses other forms of uncertainty. Recommendations relating to these methods are present in Section C.7.2 of the LCA guidelines. Some of these methods are built into existing LCA software platforms as well.

Sensitivity analysis helps uncover the input parameters to which the final results are the most sensitive. Local sensitivity analysis varies one parameter at a time to analyze how the study results change. An example is varying the power rating of a single machine to analyze how it affects overall emissions. Global sensitivity analysis simultaneously varies multiple inputs and may analyze the interaction effects among different inputs. For example, CO2 capture energy demand and CO2 purity for the process are two different possible parameters for an LCA model that generally affect one another, and global sensitivity analysis would attempt to capture and analyze this relationship. The graphic below outlines how the results of local sensitivity analysis might be presented using tornado diagrams and spider charts. The “Nominal value” is the default value for the parameter used in the default model.

Use of tornado diagram and spider chart to visualize sensitivity analysis and how varying multiple parameters affects outputs and indicators

The combination of uncertainty and sensitivity analyses can also allow for an iterative process with other parts of the study. If this combination reveals highly uncertain data to which the impact assessment results are highly sensitive, then the practitioner will likely have to return to the inventory phase to find better data or even consider changing the goal of the study if such data cannot be found. The quadrants in the graphic below can help classify data priorities at this step in the study. Naturally, high quality data to which the results are not sensitive should not be a priority for improvement whereas highly uncertain and influential data should be.

Priorities for data improvement: high for very uncertain data that results are sensitive to; low for certain data that results are not sensitive to

Reporting Results

Reporting of LCA results should be as transparent as possible while also ensuring that any confidential information is protected. Reports ought to be written without bias and with the audience in mind to enhance usability. Often, reports can be split into an executive summary that briefly summarizes the study and its findings, a technical summary that lists technical inputs and results geared to a technical audience, and the main report itself that features all of the relevant information from the study. 

The ISO 14044 guidance requires critical review by a panel of external parties before public, comparative assertions can be made using the results of the study. This practice helps ensure transparency, rigor, and defensibility of results in service of enhancing trust in the LCA process.

The LCA Reporting Checklists can help guide authors as they are writing executive summaries and reports for LCA studies.