Allocation In Life Cycle Assessment Research Articles

Process design analysis of a hybrid power-and-biomass-to-liquid process – An approach combining life cycle and techno-economic assessment

Techno-economically and ecologically optimized processes require understanding of trade-offs between efficiencies, costs and environmental impacts. For this purpose, DLR’s in-house tool TEPET for techno-economic analysis was enhanced to enable simultaneous life cycle assessment (LCA). Within this study a hybrid Power-and-Biomass-to-Liquid concept is analysed that can switch between a biomass alone and hydrogen enhanced operation. In order to integrate the techno-economic and ecological results, a dimensionless cost-impact factor is introduced, which gets minimised when both costs and environmental impacts are low. The methodology is applied to investigate process parameter variations within this process concept. The varied process parameters are H2/CO ratio, H2 conversion in the Fischer-Tropsch synthesis and CO2 recycle rate to the gasification. Furthermore, the influence of LCA allocation methods on the preferable set of process parameters was examined. Results show a correlation of lowest environmental impact with high fuel efficiency (energetic fuel output per overall energetic input) for economic allocation. For energetic allocation, high process efficiency (ratio of overall energetic output to overall energetic input) leads to the lowest environmental impact. High carbon efficiency is especially important when biomass has a big impact on a certain category. Sensitivity studies for the global warming potential demonstrate a low sensitivity to the investigated process parameter variations compared with changes in input parameters like biomass and electricity source or transport distance. As the net production cost (NPC) are more sensitive towards the process parameter variations, the cost-impact factor is lowest for the set of process parameters with the lowest NPC.

The Application of Circular Footprint Formula in Bioenergy/Bioeconomy: Challenges, Case Study, and Comparison with Life Cycle Assessment Allocation Methods

Allocation methodological choices in Life Cycle Assessment (LCA) is a relevant issue for the Circular Bioeconomy context. The recent Product Environmental Footprint Guide from the European Commission includes the Circular Footprint Formula (CFF) as a new way to deal with energy recovery/recycling processes. This paper investigated CFF vs. other different LCA allocation methods in Brazilian briquette production. A cradle-to-gate LCA study was conducted considering 1 MJ of energy from recovered and dedicated Eucalyptus briquette production. Global Warming Potential (GWP) and Cumulative Energy Demand (CED) were selected as the impact categories to evaluate the allocation methods choice that influences the potential impacts. LCA results were compared regarding four allocation methods. Eucalyptus wood as a biomass supply scenario achieved impact results up to 4.3 kg CO2-eq. for GWP and 0.0272 MJ-eq. for CED. The recovery wood scenario presented LCA burdens reduction by up to 206% for GWP, however a 492% increase in the CED results. CFF provided the lowest results for both impact categories. However, the CFF method still doesn’t address particular aspects of circular bioenergy systems. Biomass and bioenergy LCA require further adjustments focusing on biochemical flows in the CFF calculation procedure to lead the development of innovative circular business models.

Internal causality in agri-food Life Cycle Assessments: Solving allocation problems based on feed energy utilization in egg production

Physical allocation in Life Cycle Assessment (LCA) should, ideally, be based on underlying causal relationships. While both cause-oriented and effect-oriented causality referred to in LCA literature are forms of external causality, internal causality addresses the actual flow of materials and inputs in a system – in other words, the real behaviour of the system under study. While a number or examples of allocation based on physical causality have been used in poultry LCAs, none of these represent the internal causality (the actual biological processes) in egg production. The current study remedies that gap by proposing such a method. Agri-food LCAs, in particular LCAs of livestock production, were used to identify existing physical allocation approaches consistent with internal causality. The most commonly used approach was found to be based on the allocation of feed energy to support the various physiological functions of the livestock species. A feed energy – Metabolizable Energy (ME) – utilization model for allocation in egg production LCAs is hence similarly proposed. Using the inventory of a previous LCA study of egg production in Canada, allocation ratios for eggs and spent hens were developed. Feed utilization models specific to each unit process were identified. The overall differences between ME utilization (∼95% eggs, 5% spent hens) and gross chemical energy content (92% eggs, 8% spent hens) for allocation were relatively small. Scenario analysis, however, showed that the allocation ratios can be considerably different if the causal relationship is interpreted differently. Differences over ∼20% was seen in a scenario which did not allocate between the co-products of each unit process in the system, but rather to the products at the end of a biological causal chain straddling multiple unit processes. The proposed approach is consistent with the interpretation of LCA as a natural sciences framework, and with the ISO 14044 multi-functionality hierarchy, because it reflects actual biological causality in egg production systems. The study results also underscore that practitioners should not only clearly justify their choice of allocation strategy, but also describe its application in detail, since small differences in methods can result in divergent outcomes.

An axiomatic method for goal-dependent allocation in life cycle assessment

An axiomatic method for goal-dependent allocation in life cycle assessment

Development of a Life Cycle Assessment Allocation Approach for Circular Economy in the Built Environment

Transitioning the built environment to a circular economy (CE) is vital to achieve sustainability goals but requires metrics. Life cycle assessment (LCA) can analyse the environmental performance of CE. However, conventional LCA methods assess individual products and single life cycles whereas circular assessment requires a systems perspective as buildings, components and materials potentially have multiple use and life cycles. How should benefits and burdens be allocated between life cycles? This study compares four different LCA allocation approaches: (a) the EN 15804/15978 cut-off approach, (b) the Circular Footprint Formula (CFF), (c) the 50:50 approach, and (d) the linearly degressive (LD) approach. The environmental impacts of four ‘circular building components’ is calculated: (1) a concrete column and (2) a timber column both designed for direct reuse, (3) a recyclable roof felt and (4) a window with a reusable frame. Notable differences in impact distributions between the allocation approaches were found, thus incentivising different CE principles. The LD approach was found to be promising for open and closed-loop systems within a closed loop supply chain (such as the ones assessed here). A CE LD approach was developed to enhance the LD approach’s applicability, to closer align it with the CE concept, and to create an incentive for CE in the industry.

Correction to: Allocation in life cycle assessment of lignin

Correction to: Allocation in life cycle assessment of lignin

Accounting for biogenic carbon and end-of-life allocation in life cycle assessment of multi-output wood cascade systems

Wood cascade systems composed of products with long service lives can contribute to carbon storage, resource efficiency and circular economy. The environmental assessment of such multi-output systems is however challenging due to (i) multiple products and recycling steps, and (ii) the distribution of emissions, particularly of biogenic CO2, over long time spans. In Life Cycle Assessment (LCA), the former is usually dealt through end-of-life (EoL) allocation methods, while the latter is assessed via biogenic carbon accounting (BCA) methods. This article aims to assess how different BCA and EoL allocation methods may influence the LCA results of wood cascade systems, particularly their biogenic carbon footprint (BCF), both at supply chain and product levels. Six BCA methods and five EoL allocation methods were analysed, combined and applied to a wood cascade system delivering multiple products: (1) flooring, (4) particleboard (PB) and (5) electricity (reference flow: 1 m3 wood). At supply chain level (prior to the application of EoL allocation methods), distinct BCFs were obtained ranging from −211 to +52 kgCO2eq/m3 of wood (as input). At product level, when applying the different EoL allocation methods, the variability further increased. For instance, the BCF of PB ranged from −5.61 to +0.04 kgCO2eq/kgPB; while the BCF of electricity ranged from −0.50 to +0.39 kgCO2eq/kWh (considering results within the 25–75 percentiles). Other factors influencing the results were the assumptions regarding the timing of forest growth, the stage in the cascade chain, the recycling content and the EoL scenario. A proper understanding of the influence of the BCA and EoL allocation methods and their assumptions on the BCF of wood cascading products is key, especially for countries/regions promoting a circular economy.

Archetypes of Goal and Scope Definitions for Consistent Allocation in LCA

The selection of an appropriate allocation procedure for co-production and recycling in Life Cycle Assessment (LCA) depends on the goal and scope of the analysis. However, it is not always clear when partitioning or system expansion can be applied, or when to conduct an attributional or a consequential LCA, both for LCA practitioners and users of LCA results. In this paper, the influence of the goal and scope on the selected modeling approaches is clarified. The distinction between process-oriented and product-oriented LCAs, between system expansion and substitution, and between the cut-off approach and other allocation procedures are highlighted. Archetypes of goal and scope definitions are developed. These archetypes reflect the minimum amount of information required to select an allocation procedure. It is demonstrated via an illustrative example that the question “what is the environmental impact of a product” can result in at least 15 different research questions requiring at least five different modeling methods. Finally, perspectives are provided on the use of attributional and consequential approaches to evaluate the environmental, social, and economic sustainability of products and processes.

Allocation in life cycle assessment of lignin

PurposeLignin extraction in pulp mills and biorefineries are emerging technologies. Lignin is always the product of a multi-output process. Assessing such processes using life cycle assessment (LCA) requires the environmental impacts to be divided between the co-products of the system, referred to as allocation. This article explores different allocation approaches for lignin and illustrates the influence of the choice of allocation approach on the climate impact in a case study.MethodTen different applicable allocation methods were found in literature and two more were developed. Lignin production in a Kraft pulp mill using the LignoBoost process for lignin extraction was selected as a study object for the case study, and due to limited data availability only climate impact was considered. A cradle-to-gate LCA was done for the study object, and all of the twelve allocation approaches were applied; for eight of the methods, factors that strongly influence the results were identified and varied. Finally, the results were put in the context of cradle-to-grave LCAs from literature for different possible uses of lignin to give an indication of how important the choice of allocation approach can be when assessing lignin as a substitute for other raw materials.Results and discussionResults show that all allocation approaches tested were applicable to the special case of lignin, but each one of them comes with inherent challenges. Factors that often have a large impact on the results are (1) market and price of different outputs; (2) what is seen as the main product or the driver of the system or system changes; (3) what the surrounding system looks like and hence what other products will be displaced by outputs. These factors can be particularly challenging in prospective studies as such studies are future-oriented and consider systems that do not yet exist. Finally, the results show that the choice of allocation could have a significant influence on the climate impact on the cradle-to-grave climate impact of the final product.ConclusionsWe recommend for LCAs of lignin-based technologies that allocation methods are very carefully selected based on the goal and scope of the study and that when relevant, several methods are applied and factors are varied within them in a sensitivity analysis. In particular, the driver(s) of the system’s existence or of changes to it, sometimes reflected in market prices of outputs, should be carefully considered.

The ISO 14067 approach to open-loop recycling of paper products: Making it operational

Allocating environmental impacts within life cycle assessment (LCA) is a recognised methodological problem. Different allocation methods have been developed to fulfil the various goals of LCA studies. At present, there is neither a consensus regarding the method to be used nor a one-fits-all method for dealing with recycling in LCA. The paper discusses some of the main allocation procedures practised in the pulp and paper industry, namely those covered by ISO/TS 14067:2018, GHG Protocol/PAS 2050, and the Product Environmental Footprint (PEF). All in all, the allocation method described in the ISO/TS 14067:2018 standard was considered the most appropriate to account for open-loop recycling of paper products. However, the method neither considers the number of subsequent uses of recycled fibres, nor the recycled fibre age. Yet, both of them are considered especially important in the open-loop recycling of paper products. In order to account for these aspects, the present study proposes an advanced, step-wise approach to handle allocation in LCAs accounting for the open-loop recycling of paper products. The advanced approach is based on the fibre mass flow model used to calculate the mean fibre age and the mean number of uses of paper products within the European context. The approach was validated with the data from the pulp and paper industry, particularly examining the newsprint paper grade with different contents of recycled fibre and fibre age. The paper, however, introduces all the parameters required to perform allocation based on the proposed method for other paper grades. The categpory of global warming potential was considered in the study as an illustrative example. yet the method could be applied to other impact assessment categories. The results calculated using the proposed allocation approach were compared to those obtained with the allocation methods described in the GHG Protocol/PAS 2050 and the PEF. The proposed allocation method can be used to guide further development of available standards and the product category rules, which will contribute to increased harmonisation and consistency of LCA studies in the pulp and paper sector, as well as to the enhanced practical implementation of LCA in industry.

Choice of Allocations and Constructs for Attributional or Consequential Life Cycle Assessment and Input‐Output Analysis

SummaryThe divide between attributional and consequential research perspectives partly overlaps with the long‐standing methodological discussions in the life cycle assessment (LCA) and input‐output analysis (IO) research communities on the choice of techniques and models for dealing with situations of coproduction.The recent harmonization of LCA allocations and IO constructs revealed a more diverse set of coproduction models than had previously been understood. This increased flexibility and transparency in inventory modeling warrants a re‐evaluation of the treatment of coproduction in analyses with attributional and consequential perspectives.In the present article, the main types of coproductions situations and of coproduction models are reviewed, along with key desirable characteristics of attributional and consequential studies. A concordance analysis leads to clear recommendations, which call for important refinements to current guidelines for both LCA/IO practitioners and database developers. We notably challenge the simple association between, on the one hand, attributional LCA and partition allocation, and on the one hand, consequential LCA and substitution modeling.

A new method of biophysical allocation in LCA of livestock co-products: modeling metabolic energy requirements of body-tissue growth

In agricultural life cycle assessment (LCA), the allocation method chosen to divide impacts among co-products is an important issue, since it may change conclusions about a product’s impacts. We developed a biophysical allocation method to assign upstream environmental burdens and the use of raw materials at farm gate to the livestock co-products at the slaughterhouse based on their metabolic energy requirements. Biophysical allocation is designed to build a relationship between co-products of a meat-production system and their associated net metabolic energy requirements. A metabolic growth model (Gompertz function) was combined with an energy calculation model to estimate metabolic energy requirements for the growth of an animal from birth to slaughter age. Allocation factors were calculated based on the energy required to maintain and produce body tissues (excluding waste), as a function of their chemical (protein and lipid) and physiological properties. This method was applied for an average beef cow and then compared to other allocation methods (e.g., mass, dry matter, protein, and economic). At slaughter age, carcass tissues required the most energy (44 %) due to their high quantity of protein; the gastrointestinal tract and liver required about 28 and 5 %, respectively, of total metabolic energy requirements due to their roles in body metabolism. Biophysical allocation considers the energy cost of building and maintaining the tissues, regardless of their final uses. It reflects physical relationships among co-products as well as other allocation methods do. It also reveals the cause-effect relationship between tissues according to the energy required to maintain physiological functions. Once the growing time until slaughter is set, biophysical allocation factors are not influenced over time, unlike those of economic allocation, which is highly influenced by price variability. This study provides a generic and robust biophysical allocation method for estimating environmental burdens of co-products, in accordance with ISO allocation rules. The method can be considered an original contribution to international debates on allocation methods applied to livestock products in LCA. In this paper, it is applied to cattle-related product, but it is generic and the principles can be adapted to any kind of livestock species. It should be considered and discussed by stakeholders in livestock production industries.

Developing a systematic framework for consistent allocation in LCA

Multifunctionality in life-cycle assessment (LCA) is solved with allocation, for which many different procedures are available. Lack of sufficient guidance and difficulties to identify the correct allocation approach cause a large number of combinations of methods to exist in scientific literature. This paper reviews allocation procedures for recycling situations, with the aim to identify a systematic approach to apply allocation. Assumptions and definitions for the most important terms related to multifunctionality and recycling in LCA are given. The most relevant allocation procedures are identified from literature. These procedures are expressed in mathematical formulas and schemes and arranged in a systematic framework based on the underlying objectives and assumptions of the procedures. If the LCA goal asks for an attributional approach, multifunctionality can be solved by applying system expansion—i.e. including the co-functions in the functional unit—or partitioning. The cut-off approach is a form of partitioning, attributing all the impacts to the functional unit. If the LCA goal asks for a consequential approach, substitution is applied, for which three methods are identified: the end-of-life recycling method and the waste mining method, which are combined in the 50/50 method. We propose to merge these methods in a new formula: the market price-based substitution method. The inclusion of economic values and maintaining a strict separation between attributional and consequential LCA are considered to increase realism and consistency of the LCA method. We identified the most pertinent allocation procedures—for recycling as well as co-production and energy recovery—and expressed them in mathematical formulas and schemes. Based on the underlying objectives of the allocation procedures, we positioned them in a systematic and consistent framework, relating the procedures to the LCA goal definition and an attributional or consequential approach. We identified a new substitution method that replaces the three existing methods in consequential LCA. Further research should test the validity of the systematic framework and the market price-based substitution method by means of case studies.

Environmental profile, packaging intensity and food waste generation for three types of dinner meals

This study was carried out as part of the packaging optimization program in Norway, and the purpose was to study waste generation, energy use and greenhouse gas (GHG)-emissions from the whole product value chain of meals prepared from fresh ingredients at home, based in semi-prepared ingredients or as ready to eat meals. Consumer attitudes to ready to eat meals was also included in the study. The study was done with basis in Life Cycle Assessment methodologies and Material Flow Analyses, based in real cooking situations and experimental design. Portion sizes and left-overs from cooking and eating data are based in the experimental design. Food waste data from the retail sector is based in the Norwegian statistics from the ForMat project, whereas packaging data was measured from the used products. The consumer study was done through a standard web panel with 1000 respondents, with respondents representative for the Norwegian population. Reallocation of impacts from wasting of food to the place waste is generated has been applied combined with conventional Life Cycle Assessment (LCA) methods.We found that ready to eat meals had higher energy consumption and GHG-emissions than meals prepared from fresh ingredients, which again had slightly higher energy consumption and GHG-emissions than semi-prepared ingredients. Production of ingredients (especially meat) was the most important element for all products. Main contributions to the differences between the dinner types were the use stage, packaging production and transport based in conventional LCA allocation. The effect of food wasting was best shown with the reallocation method, where the impact of total food waste was on the same level as impacts from the use stage. Preventing food waste from retail and use stages would contribute to 13% reduction in GHG-emissions. Ready made food generated more food waste in the retail sector, whereas food waste by consumers was lower than for the two other types of meals. Lower degree of filling contributed to more transport work and higher emissions and energy consumption from transport. More packaging, especially plastic packaging did also contribute to higher GHG-emissions from incineration compared to the other solutions. Consumers regarded packaging solutions from ready to eat meals to be too big and with materials that are difficult to recycle. Changing from only using traditional dinner meal based on fresh ingredients to only ready to eat dinner by a Norwegian household equals GHG-emissions from a standard car driving 900 km or 8% of the average total driving distance per year in Norway.

A pseudo-statistical approach to treat choice uncertainty: the example of partitioning allocation methods

Despite efforts to treat uncertainty due to methodological choices in life cycle assessment (LCA) such as standardization, one-at-a-time (OAT) sensitivity analysis, and analytical and statistical methods, no method exists that propagate this source of uncertainty for all relevant processes simultaneously with data uncertainty through LCA. This study aims to develop, implement, and test such a method, for the particular example of the choice of partitioning methods for allocation in LCA, to be used in LCA calculations and software. Monte Carlo simulations were used jointly with the CMLCA software for propagating into distributions of LCA results, uncertainty due to the choice of allocation method together with uncertainty of unit process data. In this study, a methodological preference is assigned to each partitioning method, applicable to multi-functional processes in the system. The allocation methods are sampled per process according to these preferences. A case study on rapeseed oil focusing on three greenhouse gas (GHG) emissions and their global warming impacts is presented to illustrate the method developed. The results of the developed method are compared with those for the same case similarly quantifying uncertainty of unit process data but accompanied by separate scenarios for the different partitioning choices. The median of the inventory flows (emissions) for separate scenarios varies due to the partitioning choices and unit process data uncertainties. Inventory variations are reflected in the global warming results. Results for the approach of this study vary with the methodological preference assigned to the different allocation methods per multi-functional process and with the continuous distribution of unit process data. The method proved feasible and implementable. However, absolute uncertainties only further increased. Therefore, it should be further researched to reflect relative uncertainties, more relevant for comparative LCAs. Propagation of uncertainties due to the choice of partitioning methods and to unit process data into LCA results is enabled by the proposed method, while capturing variability due to both sources. It is a practical proposal to tackle unresolved debates about partitioning choices increasing robustness and transparency of LCA results. Assigning a methodological preference to each allocation method of multi-functional processes in the system enables pseudo-statistical propagation of uncertainty due to allocation. Involving stakeholders in determining these methodological preferences allows for participatory approaches. Eventually, this method could be expanded to also cover other ways of dealing with allocation and to other methodological choices in LCA.

Biofuels via Fast Pyrolysis of Perennial Grasses: A Life Cycle Evaluation of Energy Consumption and Greenhouse Gas Emissions.

A well-to-wheel (WTW) life cycle assessment (LCA) model is developed to evaluate the environmental profile of producing liquid transportation fuels via fast pyrolysis of perennial grasses: switchgrass and miscanthus. The framework established in this study consists of (1) an agricultural model used to determine biomass growth rates, agrochemical application rates, and other key parameters in the production of miscanthus and switchgrass biofeedstock; (2) an ASPEN model utilized to simulate thermochemical conversion via fast pyrolysis and catalytic upgrading of bio-oil to renewable transportation fuel. Monte Carlo analysis is performed to determine statistical bounds for key sustainability and performance measures including life cycle greenhouse gas (GHG) emissions and Energy Return on Investment (EROI). The results of this work reveal that the EROI and GHG emissions (gCO2e/MJ-fuel) for fast pyrolysis derived fuels range from 1.52 to 2.56 and 22.5 to 61.0 respectively, over the host of scenarios evaluated. Further analysis reveals that the energetic performance and GHG reduction potential of fast pyrolysis-derived fuels are highly sensitive to the choice of coproduct scenario and LCA allocation scheme, and in select cases can change the life cycle carbon balance from meeting to exceeding the renewable fuel standard emissions reduction threshold for cellulosic biofuels.

Construction cost of plant compounds provides a physical relationship for co-product allocation in life cycle assessment

Purpose Although, according to the ISO 14044 standard, economic allocation should be the solution of last resort, it is frequently used in LCA studies of agri-food systems because of the inadequacy of solutions preferred by ISO. We propose a new way of allocating impacts to plant co-products according to the underlying physical relationships between the co-products. We compare this method to two current allocation methods.

Unified Theory of Allocations and Constructs in Life Cycle Assessment and Input‐Output Analysis

SummaryThe treatment of coproducts is one of the most persistent methodological challenges for both input‐output (IO) analysis and life cycle assessment (LCA). The two fields have developed distinct modeling traditions to artificially extract independent Leontief production functions (technological “recipes”) for products of multioutput activities; whereas IO operates in terms of system‐wide models named constructs, LCA practitioners usually use allocations or system expansion on a process‐by‐process basis. Recently, there have been renewed efforts to connect these two modeling traditions on the basis of their underlying assumptions. A formal description of a unified framework for the treatment of coproducts is still lacking, however. The present article strives to fill this gap. From a single generalized allocation equation, we derive all practical LCA allocations and IO constructs. This approach extends previous studies by arranging the different models in a formal “taxonomic tree,” clarifying the relation between the different LCA allocation and IO construct models. This framework also clarifies the relation of certain models to classical system expansion. We then analyze the properties of these models when combined with different types of inventories and make recommendations for best practice in inventory compilation.

Economic Allocation in Life Cycle Assessment

SummaryThis article examines methods for analyzing allocation in life cycle assessment (LCA); it focuses on comparisons of economic allocation with other feasible alternatives. The International Organization for Standardization's (ISO) guideline 14044 indicates that economic allocation should only be used as a last resort, when other methods are not suitable. However, the LCA literature reports several examples of the use of economic allocation. This is due partly to its simplicity and partly to its ability to illustrate the properties of complex systems. Sometimes a price summarizes complex attributes of product or service quality that cannot be easily measured by physical criteria. On the other hand, economic allocation does have limitations arising, for example, from the variability of prices and the low correlation between prices and physical flows. This article presents the state of the debate on the topic and some hypothetical examples for illustration. A general conclusion is that it is not possible to determine one “best” allocation method. The allocation procedure has to be selected on a case‐by‐case basis and no single approach is suitable for every situation. Despite its limitations, economic allocation has certain qualities that make it flexible and potentially suitable for different contexts. In some situations, economic allocation should not be the last methodological resort. The option of economic allocation should be considered, for example, whenever the prices of coproducts and coservices differ widely.

A life cycle assessment of seasonal grass-based and confinement dairy farms

Life cycle assessment (LCA) is a holistic systems approach that aims to assess the environmental impacts (potential pollutants and resource use) of the production of goods and services. The aim of this study was to develop an LCA model to compare contrasting milk production systems, a seasonal pasture-based dairy farm and a confinement dairy farm. The environmental impacts considered were global warming, eutrophication, acidification, land use and non-renewable energy use. The LCA estimated on-farm, off-farm (pollutants and resources associated with the production and supply of purchased farm inputs) and total (on-farm and off-farm) environmental impacts. Environmental impacts were quantified per unit of milk and per unit area. The study only considered two research farms, because high quality data were unavailable for a large number of farms. Thus, this was not a representative LCA comparison. The genetic merit of cows modelled was similar for each system. A total mixed ration was fed in the confinement system and grazed grass was mainly fed in the grass-based system. Research data were used to confirm simulated dry matter intake (DMI) and predicted enteric CH4 output from simulated DMI. The study found that when expressed per unit of milk and per on-farm area, all total environmental impacts were greater for the confinement system compared to the grass-based system. Per total farm area (on-farm and off-farm area), all environmental impacts except global warming were lower for the grass-based system. The greater environmental impact of the confinement dairy system was due to the greater use of concentrate feed and the longer manure storage period. Scenario modelling demonstrated that there is potential to decrease the environmental impact of dairy systems, particularly the confinement system, by reducing the use of concentrate ingredients with a high environmental impact and by storing manure in solid systems. Scenario modelling also showed that assumptions regarding the carbon cycle should be clearly outlined when assessing milk production systems and that standardisation of LCA allocation procedures is required. This LCA study is one of the few to directly compare the environmental impact of a grass-based and a confinement dairy system. However direct comparisons are needed, using an LCA methodology such as described in this paper, and using data from a greater number of farms so that each system is better represented thereby ensuring a robust comparison of the two systems on a regional or national basis.