Approaches to fill data gaps and evaluate process completeness in LCA—perspectives from solid waste management systems Abstract Purpose Large data amounts are required in an LCA, but often, site-specific data are missing and less representative surrogate data must be used to fill data gaps. No standardized rules exist on how to address data gaps and process completeness. We suggest a systematic evaluation of process completeness, identification of data gaps, and application of surrogate values to fill the gaps. The study focus on foreground process data. Methods A solid waste management (SWM) scenario was used to illustrate the suggested method. The expected input and output flows in a waste incineration model were identified based on legislation and expert judgment, after which process completeness scores were calculated and missing flows identified. To illustrate the use of different types of surrogate data to fill data gaps, data gaps were selected for 16 different parameters in five SWM processes. We compared the global warming potential (GWP) from using surrogate data, and from leaving the gap, to identify the data gaps where representative surrogate data should be used. Results and discussion The completeness score for the material inputs to waste incineration was 78%, and the missing flows were auxiliary fuels and precipitation chemicals. The completeness score for air emissions were between 38 and 50% with and without expert judgment. If only greenhouse gases were considered (CO2, CH4, and N2O), the completeness score would be 67%. Applying weighting factors according to the greenhouse gas contribution in the USA gave a completeness score of 94%. The system-wide data gaps, where representative surrogate data should be applied, were the CH4 release from composting; electricity generation efficiency of incineration; recovery efficiencies at a material recovery facility; and composition of the plastic, metal, and paper fractions in the household waste; in these cases, leaving the gap changed the GWP results by > 5%. Conclusions Completeness evaluation should take into account the relevance and importance of flows; relevance depends on the considered life cycle impact methods and importance depends on the weighting of the different flows. The set of expected flows and evaluation of relevance and importance must be documented in a transparent manner. The choice of surrogate values to fill data gaps depends on the availability of secondary data and on whether the data gap matters, i.e., significantly affects the LCA results. The suggested method can be used to properly document the identification of missing flows and to select and apply surrogate values to fill the data gaps.

IMPACT World+: a globally regionalized life cycle impact assessment method Abstract Purpose This paper addresses the need for a globally regionalized method for life cycle impact assessment (LCIA), integrating multiple state-of-the-art developments as well as damages on water and carbon areas of concern within a consistent LCIA framework. This method, named IMPACT World+, is the update of the IMPACT 2002+, LUCAS, and EDIP methods. This paper first presents the IMPACT World+ novelties and results and then analyzes the spatial variability for each regionalized impact category. Methods With IMPACT World+, we propose a midpoint-damage framework with four distinct complementary viewpoints to present an LCIA profile: (1) midpoint impacts, (2) damage impacts, (3) damages on human health, ecosystem quality, and resources & ecosystem service areas of protection, and (4) damages on water and carbon areas of concerns. Most of the regional impact categories have been spatially resolved and all the long-term impact categories have been subdivided between shorter-term damages (over the 100 years after the emission) and long-term damages. The IMPACT World+ method integrates developments in the following categories, all structured according to fate (or competition/scarcity), exposure, exposure response, and severity: (a) Complementary to the global warming potential (GWP100), the IPCC Global Temperature Potentials (GTP100) are used as a proxy for climate change long-term impacts at midpoint. At damage level, shorter-term damages (over the first 100 years after emission) are also differentiated from long-term damages. (b) Marine acidification impact is based on the same fate model as climate change, combined with the H+ concentration affecting 50% of the exposed species. (c) For mineral resources depletion impact, the material competition scarcity index is applied as a midpoint indicator. (d) Terrestrial and freshwater acidification impact assessment combines, at a resolution of 2° × 2.5° (latitude × longitude), global atmospheric source-deposition relationships with soil and water ecosystems’ sensitivity. (e) Freshwater eutrophication impact is spatially assessed at a resolution grid of 0.5° × 0.5°, based on a global hydrological dataset. (f) Ecotoxicity and human toxicity impact are based on the parameterized version of USEtox for continents. We consider indoor emissions and differentiate the impacts of metals and persistent organic pollutants for the first 100 years from longer-term impacts. (g) Impacts on human health related to particulate matter formation are modeled using the USEtox regional archetypes to calculate intake fractions and epidemiologically derived exposure response factors. (h) Water consumption impacts are modeled using the consensus-based scarcity indicator AWARE as a proxy midpoint, whereas damages account for competition and adaptation capacity. (i) Impacts on ecosystem quality from land transformation and occupation are empirically characterized at the biome level. Results and discussion We analyze the magnitude of global potential damages for each impact indicator, based on an estimation of the total annual anthropogenic emissions and extractions at the global scale (i.e., “doing the LCA of the world”). Similarly with ReCiPe and IMPACT 2002+, IMPACT World+ finds that (a) climate change and impacts of particulate matter formation have a dominant contribution to global human health impacts whereas ionizing radiation, ozone layer depletion, and photochemical oxidant formation have a low contribution and (b) climate change and land use have a dominant contribution to global ecosystem quality impact. (c) New impact indicators introduced in IMPACT World+ and not considered in ReCiPe or IMPACT 2002+, in particular water consumption impacts on human health and the long-term impacts of marine acidification on ecosystem quality, are significant contributors to the overall global potential damage. According to the areas of concern version of IMPACT World+ applied to the total annual world emissions and extractions, damages on the water area of concern, carbon area of concern, and the remaining damages (not considered in those two areas of concern) are of the same order of magnitude, highlighting the need to consider all the impact categories. The spatial variability of human health impacts related to exposure to toxic substances and particulate matter is well reflected by using outdoor rural, outdoor urban, and indoor environment archetypes. For “human toxicity cancer” impact of substances emitted to continental air, the variability between continents is of two orders of magnitude, which is substantially lower than the 13 orders of magnitude total variability across substances. For impacts of water consumption on human health, the spatial variability across extraction locations is substantially higher than the variations between different water qualities. For regionalized impact categories affecting ecosystem quality (acidification, eutrophication, and land use), the characterization factors of half of the regions (25th to 75th percentiles) are within one to two orders of magnitude and the 95th percentile within three to four orders of magnitude, which is higher than the variability between substances, highlighting the relevance of regionalizing. Conclusions IMPACT World+ provides characterization factors within a consistent impact assessment framework for all regionalized impacts at four complementary resolutions: global default, continental, country, and native (i.e., original and non-aggregated) resolutions. IMPACT World+ enables the practitioner to parsimoniously account for spatial variability and to identify the elementary flows to be regionalized in priority to increase the discriminating power of LCA.

Determining the climate impact of food for use in a climate tax — design of a consistent and transparent model Abstract Purpose The aim of this study was to determine transparent food carbon footprint values for use in a climate tax, using a consistent methodology across the taxed food products and taking into account the need for such a tax to be administratively simple and accepted by affected stakeholders. Methods A method based on Life Cycle Assessment following the ISO 14067 standard was developed for establishing simplified, yet consistent and transparent, datasets on the carbon footprint of food, for use as a base in a climate tax on food. Several sensitivity analyses were carried out to test the effects of inevitable methodological choices on the carbon footprint of different foods. The choices were then discussed in relation to taxation of food. The methodological choices included in the sensitivity analyses were different approaches to system boundaries, how to account for soil carbon changes and how to weigh greenhouse gases (GHGs). Results and discussion The results on the carbon footprint of food calculated with the suggested method are in line with earlier findings in the field, with animal products, especially beef, showing a substantially higher value than most plant-based foods. Regarding choice of system boundaries for using the values in a tax, it is of particular importance to target emissions from biological processes, as these are currently untaxed. This would also be administratively simpler but less acceptable as large emission sources especially for imported products and greenhouse grown vegetables would not be included. Modelling emissions from soil carbon changes using a site-dependent method can be an advantage to obtain results in line with empirical data. Using Global Warming Potential over 100 years to weigh GHGs would be most in line with current climate reporting, which is an advantage for the consistency and acceptability of a tax. Conclusions Ultimately, how taxes are set is a political decision, but food carbon footprint values determined with a consistent and simplified methodology are required in the process. This study presents carbon footprint values established using such method and provides valuable insights into how methodological choices affect the results of climate impact values and the implications for taxation.

An LCA impact assessment model linking land occupation and malnutrition-related DALYs Abstract Purpose So far, land occupation impact assessment models in life-cycle assessment have predominantly considered biodiversity, ecosystem quality and ecosystem services. However, in a manner similar to water consumption, land occupation has the potential to impact food production and thereby human health. In this study, the impact pathway linking land occupation and protein-energy malnutrition was modelled, establishing a new set of regionalised characterisation factors which were applied in a case study of cotton cultivation. Methods The impact assessment model has three main components: a food production model, a food trade model and an effect factor that relates potential food deficits to malnutrition expressed in disability-adjusted life years (DALYs). The food production model uses an NPP-based index to account for variation in the productive capability of land, as well as data on irrigation water supply and national agricultural yields to account for variation in prevailing agricultural technologies. Food production losses have the potential to impact national and global food supplies according to trade status and economic adaptation capacity assessed using the Inequality-adjusted Human Development Index. Health damage data from the Global Burden of Disease report and depth of national food deficit data from the FAO are the basis of the effect factor. Results and discussion The model reports potential human health impacts related to land occupation (DALY/m2 year) at 5-arc-minute spatial resolution. The model is relevant to all kinds of land occupation, including food production, as no assumptions are made about the ways food products are utilised, which can be many. The model delivers results sensibly in proportion to potential human health impacts of freshwater consumption, i.e. greater in tropical areas and lesser in arid areas. The case study showed that land occupation impacts on human health might cause one DALY/t seed cotton in extreme cases and less than one DALY per thousand tonnes in others. In the case of India, ~ 9% of national malnutrition-related DALYs were attributable to cotton cultivation which occupies ~ 8% of arable land. Conclusions This new model will enable more complete assessment of land occupation impacts in LCA and is especially relevant to the assessment of food, fibre, and bioenergy products. In addition, the model enhances the ability to assess trade-offs which frequently occur, such as between land and water use and GHG emissions. The cotton case study showed that human health impacts can be grossly underestimated in LCA studies when land occupation impacts are not included.

Everything is relative and nothing is certain. Toward a theory and practice of comparative probabilistic LCA Abstract Introduction It is widely recognized that LCA is in most cases relative and contains uncertainties due to choices and data. This paper analyses the combination of the two comparative uncertainties. Basic concepts We carefully define the idea of relativity and uncertainty within LCA. We finish off by giving an example of case where inappropriate handling of comparative uncertainties will lead to a misleading result for a decision-maker. Correlations We develop a generic framework for probabilistic comparative LCA and analyse at which places correlations may be present. We also discuss the most convenient approaches for handling such correlated uncertainties. Conclusion We put the elements discussed in a structure that provides a research agenda for dealing with comparative uncertainties in LCA.

Social life cycle assessment framework for evaluation of potential job creation with an application in the French carbon fiber aeronautical recycling sector Abstract Purpose Due to the increased consumption of carbon fibers, it is expected that an important amount of carbon-fiber-reinforced plastic (CFRP)-based products will enter in the coming years, at the end of their life cycle. Considering the challenges ahead in the establishment of a new recycling sector, it is appropriate to investigate the sustainable creation of a CFRP end-of-life management sector. The following work is part of a national funded project called SEARRCH, whose goal was to provide sustainability assessment indicators and methodology to stakeholders, for the implementation of a carbon fiber recycling sector. This article will focus on detailing the methodology aiming at characterizing the social dimension through the evaluation of potential job creation. Methods This publication describes the development of a method for the evaluation of potential job creation built on an adaptation of the Hunkeler societal life cycle assessment (societal LCA). This methodology based on life cycle inventory (LCI) has been adapted using input-output tables from the French national institute of statistics and economic studies (INSEE) or the Social Hotspot Database (SHDB) and a material flow analysis (MFA). A practical application in the CFRP recycling sector is then described. This research was conducted as part of a national project funded by the French Government France; therefore, this study respects data corresponding to the French national borders and assumes the use of a pyrolysis recycling process in calculating the amount of CFRP production and waste available at the end-of-life stage from the aeronautical sector. Results and discussion The amount of direct and indirect employment was obtained for different periods of time. Using technical coefficients extracted from the SHDB, it was determined that for the CFRP coming from the aeronautical sector, 85 direct and indirect induced jobs would be created for the period between 2046 and 2050. Using technical coefficients calculated from the input-output tables provided by the INSEE, the estimated number of jobs was 108 for the same period. Conclusions This publication demonstrated that the quantity of CFRP at the end-of-life stage could represent a potential benefit for direct and indirect job creation if the implementation of the end-of-life CFRP sector is anchored in a sustainable way, by establishing a new recycling sector for this material. Moreover, this method can provide calculations for other periods of time, sectors, and geographic scales, separately or in combination.

Development of Eco-factors for the European Union based on the Ecological Scarcity Method Abstract Purpose Weighting as an optional step in life cycle impact assessment (LCIA) has recently gained momentum through increased policy requirements in the European Union. In this context, the existing Ecological Scarcity Method (ESM), published and developed in Switzerland, is one method for Distance-to-Target (DtT) weighting which is based on the ratio of desired policy targets to the current environmental situation. The purpose of this study is the application of the ESM to the European Union (EU) as well as its application in a case study. Methods Based on the ESM, a baseline set of eco-factors was determined, including weighting factors for a broad set of substances and resource uses based on the current environmental situation and policy targets of the EU. This includes data collection for a wide range of emissions and resource uses, as well as the identification of corresponding binding and non-binding policy targets. In addition to the baseline set, two other sets, considering the short-term and binding character of targets, were compiled for a sensitivity analysis. By applying all sets to the current European environmental situation, a comparative case study was conducted. Results and discussion A baseline set including eco-factors for various emissions and resource uses for a total of 11 environmental issues was developed. The application of this baseline set to the current environmental situation of the EU showed a high relative importance of climate change (28%) and main air pollutants (30%) in the aggregated results. The sensitivity analysis demonstrated that if only short-term or binding targets are considered, weighting results in comparison to the baseline set are 43 to 60% lower, respectively. The main reasons for this shift are less restrictive reduction targets (e.g., climate targets) from a short-term perspective or non-existing binding targets. Conclusions The ESM was transferred to the EU as a DtT weighting method. The presented eco-factors take into account long-term targets, which could make it a meaningful method for decision-makers promoting forward-looking actions in the EU. Nonetheless, it was not possible to cover all substances (e.g., nitrogen and phosphorus inputs into surface waters and soil, heavy metals and pesticides in soil, mineral primary resources, and radioactive waste) due to the lack of quantitative policy targets and current emission data. Such missing substances or environmental issues should be integrated in the development of future methodologies.

Environmental impact assessment of biomass process chains at early design stages using decision trees Abstract Purpose Life cycle assessment (LCA) is generally considered as a suitable methodology for the evaluation of environmental impacts of processes. However, it requires large amount and often inaccessible process data at early design stages. The present study provides an approach to streamline LCA for a broad set of biomass process chains. The proposed method breaks away from conventional LCA work in that the purpose is to support decision at early stages assuming minimal use of data available and points to most dominant LCA impacts, providing useful feedback to process design. Methods The prediction mechanism employs decision trees, which form “if-then rules” using a set of critical parameters of the process chain with respect to various environmental impacts. The models classify products into three classes, namely having low, medium, and high environmental impact. Data for model development were obtained from early design stages and include descriptors of the molecular structure of the product and process chain-related variables corresponding to chemistry, complexity, and generic process conditions. Twenty-three LCA metrics were selected as target attributes, according to the ReCiPe and the cumulative energy demand (CED) methods. A broad set of process chains is derived from the work of Karka et al. (Int J Life Cycle Assess 22(9):1418–1440, 2017). Results and discussion Results demonstrate that the average classification error for the decision trees ranges between 13.4 and 43.8% for the various LCA metrics and multifunctionality approaches. Allocation approaches present a better classification performance (up to 25% error) compared with the substitution approach for LCA metrics, such as climate change, CED, and human health. For the majority of models, low- and high-output classes are characterized by better predictive performance compared with the medium class. The interpretability of selected decision trees is analyzed in terms of pruning levels and “irrational” branches. The results of the application of the decision tress for recently published case studies show for instance that 8 out of 13 cases were correctly classified for CED. Conclusions The proposed approach provides a first generation of models in the form of computationally inexpensive and easily interpretable decision trees that can be used as pre-screening tools for the environmental assessment of bio-based production ahead of detailed design and conventional LCA approaches. The transparent structure of the decision trees facilitates the identification of critical decision variables providing insights for improvement in terms of process parameters, biomass feedstock, or even targeted product.

Interpreting life cycle assessment results for integrated sustainability decision support: can an ecological economic perspective help us to connect the dots? Abstract Life cycle assessment (LCA) is often described as a sustainability decision support tool. In practice, however, the interpretation and application of most LCA studies are restricted to eco-efficiency considerations, which provide an important but incomplete basis for sustainability decision-making. Recent methodological advances in the field enable assessing LCA results against sustainability boundaries or thresholds at planetary or more finely resolved scales. Weighting, although controversial, facilitates consistent, stakeholder-appropriate decision-making that reflects prioritization among multiple and potentially competing sustainability outcomes. Here, we discuss how the three minimum necessary criteria for sustainability (i.e., sustainable scale relative to biocapacity, distributive justice, and efficient allocation), as proposed by ecological economist Herman Daly, may provide an internally consistent basis for integrating these methodological developments, and for subsequently better positioning LCA as a sustainability decision support framework.

Estimation of shadow prices of soil organic carbon depletion and freshwater depletion for use in LCA Abstract Purpose The interpretation of differences between alternative systems in life cycle assessment (LCA) can be problematic when different impact categories point to different directions. Using shadow prices is one way to overcome this problem, as the results are expressed in a monetary value, making comparison easy for decision makers. However, for the International Reference Life Cycle Data System midpoint impact categories ‘water depletion’ and ‘land use’, the shadow prices were missing. In the current paper, these were derived from literature sources. Methods Abatement-based shadow prices (Pa) were established from the costs of the abatement measures minus the additional benefits. The damage-based shadow price (Pd) was based on the economic damage per unit of impact. Damage to ecosystems or human health was not included, as monetary values were lacking. As a consequence, Pd is an underestimation. Pa prices for land use, based on soil organic carbon (SOC) depletion, were derived from the cost of abatement measures like adding organic matter to agricultural soil or changing tillage. The response of crop yield to SOC, for several countries and crops, was used for the Pd calculation. For water depletion, Pa was based on water saving measures and desalination techniques, and Pd was based on economic losses due to water unavailability. Results and discussion The following shadow prices were found for SOC depletion: Pa of 0.10 € kg−1 SOC and Pd of 0.0286 € kg−1 SOC. For water depletion, Pa of 15.8 € m−3 eq. was based on replacing turf with less-water-consuming planting. The value of water for irrigation was the base for the Pd 5.17 € m−3 eq. Freshwater and SOC Pa values unexpectedly exceeded the Pd values. This originated partly from the methods used. Pd was established by averaging marginal costs, while Pa used the most expensive measure, and this may lead to Pa exceeding Pd. Furthermore, the damage-based Pd for SOC and water depletion was mainly based on crop yield, and other types of ecological or societal damage will exist. Including these damages that lacked reliable data will increase Pd. Conclusions The shadow prices presented here are the first science-based global estimates. For LCA, the Pd values should preferably be used. The values are regarded as conservative estimates since only economic damage was included as other damages like ecological damage could not be monetised. The estimated shadow prices were derived for impacts where economic data is relatively scarce, and this limited the quality of the estimates. More extensive studies are needed to further improve the quality of the estimated prices.