Life Cycle Inventory Datasets Research Articles

Selection of the most appropriate life cycle inventory dataset: new selection proxy methodology and case study application

Using generic or country-specific life cycle inventory (LCI) datasets for life cycle assessments (LCAs) with no site-specific LCI datasets can result in inaccurate LCA results, whereas comprehensive site-specific LCI datasets require considerable time and effort. We use the term site-specific as a broad term, the site denoting a site, region, or technology. We propose a methodology for systematic selection of the most appropriate proxy dataset for a specific site, from the available LCI datasets for a specific background process. The “Selection Proxy” methodology applies rigorous mathematical and statistical techniques. The selection process is based on the concept of a descriptive characteristics space. Each potential proxy dataset and the missing dataset are assigned coordinates in the characteristics space. The proxy is selected based on the “distance” between candidate LCI datasets and the known coordinates of the target dataset in the characteristics space. The dataset with the minimum distance is the “Selection Proxy” dataset. The methodology is demonstrated on water supply systems using a harmonized set of 22 LCA studies, focusing on climate change, with analysis of four additional impact categories. The methodology is corroborated on climate change of coal-fired electric power stations using a harmonized set of 100 LCA studies. The results that we have obtained for assessing climate change of water supply systems indicate the potentially high approximation power of our “Selection Proxy” methodology. The proposed method provides LCA impact scores that in most cases are considerably closer to “true values” at only a small fraction of the effort needed to create a comprehensive site-specific LCI dataset. The application of the methodology to the coal-fired power stations demonstrated the approximation power and cost-effectiveness of the methodology. The methodology incorporates a built-in improvement capability: every additional unique LCI dataset improves the accuracy of results. The new methodology enables selection of a dataset that represents the missing dataset that leads in most cases to a much better approximation of environmental impacts than a dataset selected by default or by geographical proximity. The methodology is general and is applicable to various background processes. The models developed for water supply systems and coal-fired power stations are freely available upon request and can be used “as is” for LCAs in locations for which site-specific LCIs for these processes are not available.

Life cycle Inventory of NiCrAl/NiCr-Cr3C2 Composite Coatings for Plasma Spraying Process

In order to solve the problem of lack of data on the environmental impact list of the current plasma spraying process，Life Cycle Assessment (LCA) method was used to collect the inventory data of NiCrAl / NiCr-Cr3C2 composite coating prepared by plasma spraying. The Input-Process-Output (IPO) process models were established, and the process resources, energy input and environmental impact were collected. The blank of plasma spray process life cycle inventory data set was effectively filled.

Life Cycle Inventory of technologies for stone quarrying, cutting and finishing: Contribution to fill data gaps

Italy is among the major producers of dimension stones and a world leader in terms of technologies for stone quarrying, cutting and finishing. In the current context of European Environmental and Raw Material policies, the stone sector is expected to enhance its overall sustainability and circularity. Previous studies have used Life Cycle Assessment (LCA) to evaluate the environmental performance of stone production, along the supply chain. Nevertheless, despite the fairly high level of maturity in terms of methodology, previous LCA studies have highlighted the scarce availability of Life Cycle Inventory (LCI) datasets related to stone sector technologies, which inevitably required the introduction of heavy simplifications. The present paper contributes to fill these gaps by providing detailed LCI datasets of the most common technologies and tools for stone quarrying, cutting and finishing. Datasets have been developed on the basis of primary data provided by three major Italian producers of cutting tools, complemented with secondary data from literature, where necessary. Moreover, modelling parameters have been set to enable the datasets update or their adaptation to specific production chains of the stone or other sectors. “Supplementary Material” provides details on the analysed technologies and on the related datasets (data sources, functional unit, system boundaries, Life Cycle models, parameters and uncertainty). Finally, LCI datasets are provided in file format as well.

A LCA study to investigate resource-efficient strategies for managing post-consumer gypsum waste in Lombardy region (Italy)

This study aimed at evaluating environmental sustainable solutions for managing the gypsum waste in Lombardy region (Italy), based on the Life Cycle Assessment (LCA) methodology. Primary data and information related to gypsum waste flows, recovery technologies and end-market of recycled materials were gathered to depict the whole recycling chain and to build up a life cycle inventory dataset specific for the geographical context under study. The LCA analysis of the current scenario allowed to identify strength and weak points of the regional system: up to date, most impacts are related to the recovery of gypsum waste by mixing with other mineral construction and demolition waste, which appeared as the prevalent option. Different alternative scenarios were hence analyzed by considering that all the gypsum waste is recycled in dedicated plants and by analyzing different end-uses of the recycled material. The focus was placed on four major sectors for which the use of recycled gypsum is technically feasible: plasterboard manufacturing, cement industry, disinfection of sewage sludge, and agriculture. For each analyzed end-use scenario, the potential market demand in Lombardy region as well as the technical requirements of the recycled gypsum were evaluated as key points in the LCA. Results from the impact assessment were used to provide recommendations for the regional government to move towards a more resource-efficient waste management.

Life Cycle Inventory of techniques for stone quarrying, cutting and finishing: Contribution to fill data gaps.

In the current EU Environmental and Raw Materials policies, raw materials play a key role in the transition from a linear to a circular economy, where a Life Cycle (LC) approach can help improve the overall sustainability. Within the dimension stone sector, some environmental studies have been developed through the standardised Life Cycle Assessment (LCA) tool. However, these studies are often based on incomplete or not fully representative inventory datasets. In this context, this paper contributes to fill some gaps in Life Cycle Inventory (LCI) datasets in terms of quality and availability. Detailed LCI datasets on stone quarrying, cutting and finishing techniques are described and discusses, as well as provided in file format for future use by LCA practitioners. Datasets refer to the techniques most commonly employed in the Italian stone sector (and exported worldwide) and are mainly based on primary data collected from 2014 to 2016. This contribution can therefore support future studies and concretely support more sustainable solutions in the stone sector, as well as boost the use of LCA among stone companies.

Life cycle assessment with primary data on heavy rare earth oxides from ion-adsorption clays

Heavy and light rare earth elements (REEs) are critical to clean energy technologies, and thus the environmental impacts from their production are increasingly scrutinized. Most previous LCAs of REE production focus on sites producing light REEs. This research addresses this gap by collecting primary data from sites producing heavy rare earth oxides (HREOs) from ion-adsorption clays, conducting an LCA, and providing open-source life cycle inventory (LCI) datasets of HREO production for the LCA community. This study conducts a LCA based on acquired primary data from four mining sites in Jiangxi Province, China. The functional unit is 1 kg of mixed HREOs of 90% purity from ion-adsorption clays using the technology of in situ leaching. Previous studies have used the Ecoinvent database, relying mostly on European or global life cycle inventories (LCIs). Here, the Chinese Life Cycle Database provided China-specific reference life cycle inventories (LCIs) for all inputs and processes with the exception of electricity generation LCIs used in a scenario analysis, which were provided by Ecoinvent 3. Twelve impact categories were examined using Impact 2002+, USEtox 2.01, and IPCC methods. Results are provided as a bounded range, reflecting low and high estimates based on collected primary data. Results show 1 kg of mixed HREOs emit 258–408 kg CO2e, and consume 270–443 MJ primary energy. These values fall within the range of previous LCAs that examined both bastnaesite/monazite deposits and ion-adsorption clays using literature values. Other impact categories considered are not similar across studies, however. Differences are due to variability in resource type and quality, technology, and modeling choices, such as reference LCI sources. Mining and extraction contribute most to impacts due to large quantities of chemicals for leaching and precipitation of REOs, and electricity consumption. Among chemicals, ammonium sulfate is the largest contributor to many impact categories. When China’s electricity grid mix change over time is included, environmental impacts for the whole production process can change up to 12%. The primary contributions of this study are the collection and publication of primary data from mining companies in Jiangxi Province, China; the provision of open-source LCI datasets for mixed HREOs from ion-adsorption clays; and a comparison of results between this study and previously published studies. While the scope of this study concludes at the production of mixed HREO, which is a limitation, it provides a foundation for development of LCIs for refined heavy REEs.

Towards Standards-Based Generation of Reusable Life Cycle Inventory Data Models for Manufacturing Processes.

The production stage of a product's life cycle can significantly contribute to its overall environmental impact. Estimates of environmental impact for a product are typically produced using Life Cycle Assessment (LCA) methods. These methods rely on Life Cycle Inventory (LCI) data containing impact estimates of manufacturing processes and other operations that contribute to a product's creation. The accuracy of LCI data is critical for quality assessments; however, this data is often insufficient in the types and varieties of manufacturing processes covered and is often only a coarse estimate of actual impacts. At the same time, much manufacturing research focuses on how to model, measure, assess, and reduce the environmental impacts of manufacturing processes. Recent standards emerging from ASTM International define a structured format for presenting these studies in a reusable way. In this paper, we investigate the potential for using the ASTM E3012-16 format to generate LCI datasets suitable to perform LCA by mapping from the ASTM standard into the widely-adopted ecoSpold2 format. A process is presented for generating LCI datasets from ASTM models, and overlaps and gaps between the two standards are identified.

An inventory framework for inclusion of textile chemicals in life cycle assessment

PurposeToxicity impacts of chemicals have only been covered to a minor extent in LCA studies of textile products. The two main reasons for this exclusion are (1) the lack of life cycle inventory (LCI) data on use and emissions of textile-related chemicals, and (2) the lack of life cycle impact assessment (LCIA) data for calculating impacts based on the LCI data. This paper addresses the first of these two.MethodsIn order to facilitate the LCI analysis for LCA practitioners, an inventory framework was developed. The framework builds on a nomenclature for textile-related chemicals which was used to build up a generic chemical product inventory for use in LCA of textiles. In the chemical product inventory, each chemical product and its content was modelled to fit the subsequent LCIA step. This means that the content and subsequent emission data are time-integrated, including both original content and, when relevant, transformation products as well as impurities. Another key feature of the framework is the modelling of modularised process performance in terms of emissions to air and water.Results and discussionThe inventory framework follows the traditional structure of LCI databases to allow for use together with existing LCI and LCIA data. It contains LCI data sets for common textile processes (unit processes), including use and emissions of textile-related chemicals. The data sets can be used for screening LCA studies and/or, due to their modular structure, also modified. Modified data sets can be modelled from recipes of input chemicals, where the chemical product inventory provides LCA-compatible content and emission data. The data sets and the chemical product inventory can also be used as data collection templates in more detailed LCA studies.ConclusionsA parallel development of a nomenclature for and acquisition of LCI data resulted in the creation of a modularised inventory framework. The framework advances the LCA method to provide results that can guide towards reduced environmental impact from textile production, including also the toxicity impacts from textile chemicals.RecommendationsThe framework can be used for guiding stakeholders of the textile sector in macro-level decisions regarding the effectiveness of different impact reduction interventions, as well as for guiding on-site decisions in textile manufacturing.

Integrating site-specific dispersion modeling into life cycle assessment, with a focus on inhalation risks in chemical production

ABSTRACTIt has become increasingly important for environmental managers to evaluate the human health (HH) impact of chemicals in their supply chain. Current life cycle assessment (LCA) methods are limited because they often only address the HH impact at large geographical scales. This paper aims to develop a method that derives a regionalized life cycle inventory data set and site-specific air dispersion modeling to evaluate the HH impact of chemicals along the life cycle phases at finer geographical scales to improve decision-making, with focus on inhalation pathway. More specifically, cancer risk and noncancer hazard index (HI) are quantified at the county level to identify high-risk regions and at the census tract level to reveal the geographical pattern of health impacts. The results showed that along the cradle-to-gate life cycle stages of a widely used chemical, methylene diphenyl diisocyanate (MDI), the accumulative inhalation risk was 3 orders of magnitude below the U.S. Environmental Protection Agency (EPA) risk management thresholds for both cancer risk (2.16 × 10−9) and noncancer HI (1.53 × 10−3). However, the absolute value of inhalation risks caused by the case study chemicals varied significantly in different geographical areas, up to 4 orders of magnitude. This paper demonstrates a feasible approach to improve human health impact assessment (HHIA) by combining site-specific air dispersion modeling and LCA using publicly available inventory data. This proposed method complements existing life cycle impact assessment (LCIA) models to improve HHIA by employing both HH risk assessment and LCA techniques. One potential outcome is to prioritize pollution prevention and risk reduction measures based on the risk maps derived from this method.Implications: It has become increasingly important for environmental managers to evaluate the human health impacts of chemicals in their supply chain. Regionalized life cycle inventory data sets should be developed using publically available databases such as EPA’s toxic release inventory. The combination of site-specific dispersion modeling and life cycle assessment modeling can improve human health impact assessment of chemicals by providing more regionalized results along their supply chain.

Environmental impact assessment of european non-ferro mining industries through life-cycle assessment

European mining industries are the vast industrial sector which contributes largely on their economy which constitutes of ferro and non-ferro metals and minerals industries. The non-ferro metals extraction and processing industries require focus of attention due to sustainability concerns as their manufacturing processes are highly energy intensive and impacts globally on environment. This paper analyses major environmental effects caused by European metal industries based on the life-cycle impact analysis technologies. This research work is the first work in considering the comparative environmental impact analysis of European non-ferro metal industries which will reveal their technological similarities and dissimilarities to assess their environmental loads. The life-cycle inventory datasets are collected from the EcoInvent database while the analysis is done using the CML baseline and ReCipe endpoint method using SimaPro software version 8.4. The CML and ReCipe method are chosen because they are specialized impact assessment methods for European continent. The impact categories outlined for discussion here are human health, global warming and ecotoxicity. The analysis results reveal that the gold industry is vulnerable for the environment due to waste emission and similar result retained by silver mines a little bit. But copper, lead, manganese and zinc mining processes and industries are environment friendly in terms of metal extraction technologies and waste emissions.

A framework for increasing the availability of life cycle inventory data based on the role of multinational companies

PurposeThe aim of the paper is to assess the role and effectiveness of a proposed novel strategy for Life Cycle Inventory (LCI) data collection in the food sector and associated supply chains. The study represents one of the first of its type and provides answers to some of the key questions regarding the data collection process developed, managed and implemented by a multinational food company across the supply chain.MethodsAn integrated LCI data collection process for confectionery products was developed and implemented by Nestlé, a multinational food company. Some of the key features includes (1) management and implementation by a multinational food company; (2) types of roles to manage, provide and facilitate data exchange; (3) procedures to identify key products, suppliers and customers; (4) LCI questionnaire and cover letter and (5) data quality management based on the pedigree matrix. Overall, the combined features in an integrated framework provide a new way of thinking about the collection of LCI data from the perspective of a multinational food company.Results and discussionThe integrated LCI collection framework spanned across 5 months and resulted in 87 new LCI datasets for confectionery products from raw material, primary resource use, emission and waste release data collected from suppliers across 19 countries. The data collected was found to be of medium to high quality compared with secondary data. However, for retailers and waste service companies, only partially completed questionnaires were returned. Some of the key challenges encountered during the collection and creation of data included lack of experience, identifying key actors, communication and technical language, commercial compromise, confidentiality protection and complexity of multi-tiered supplier systems. A range of recommendations are proposed to reconcile these challenges which include standardisation of environmental data from suppliers, concise and targeted LCI questionnaires and visualising complexity through drawings.ConclusionsThe integrated LCI data collection process and strategy has demonstrated the potential role of a multinational company to quickly engage and act as a strong enabler to unlock latent data for various aspects of the confectionery supply chain. Overall, it is recommended that the research findings serve as the foundations to transition towards a standardised procedure which can practically guide other multinational companies to considerably increase the availability of LCI data.

Life cycle assessment of adoption of local recycled aggregates and green concrete in Singapore perspective

Singapore is a city-state with limited land space and resources, and most construction materials are imported from foreign countries. In this study, a detailed whole building life cycle assessment (LCA) of a base case building in Singapore as well as material LCA were conducted with customized life cycle inventory datasets by considering materials importation and transportation in particular, and by considering the effects of adopting local recycled aggregates. Results showed that importation and transportation of construction materials significantly alter environmental impacts. This highlights the necessity of considering transportation for importing materials in Singapore context. Inclusion of local recycled aggregates for concrete production to reduce potential environmental load is significant. This suggests adoption of local recycled aggregates is an important strategy for the development of sustainable construction in Singapore.

Privacy-preserving aggregation in life cycle assessment

Life cycle assessment (LCA) is the standard technique used to make a quantitative evaluation about the ecological sustainability of a product or service. The life cycle inventory (LCI) data sets that provide input to LCA computations can express essential information about the operation of a process or production step. As a consequence, LCI data are often regarded as confidential and are typically concealed through aggregation with other data sets. Despite the importance of privacy protection in publishing LCA studies, the community lacks a formal framework for managing private data, and no techniques exist for performing aggregation of LCI data sets that preserve the privacy of input data. However, emerging computational techniques known as “secure multiparty computation” enable data contributors to jointly compute numerical results without enabling any party to determine another party’s private data. In the proposed approach, parties who agree on a shared computation model, but do not trust one another and also do not trust a common third party, can collaboratively compute a weighted average of an LCA metric without sharing their private data with any other party. First, we formulate the LCA aggregation problem as an inner product over a foreground inventory model. Then, we show how LCA aggregations can be computed as the ratio of two secure sums. The protocol is useful when preparing LCA studies involving mutually competitive firms.

Challenges and opportunities for web-shared publication of quality-assured life cycle data: the contributions of the Life Cycle Data Network

PurposeThe European Commission’s Integrated Product Policy Communication, 2003, defined Life Cycle Assessment (LCA) as the ‘best framework for assessing the potential environmental impacts of products’. Since then, the use of LCA and life cycle approaches has been developing in a wide range of European policies, and its use has also significantly grown in business. Increasing the availability of quality-assured Life Cycle Inventory (LCI) data is the current challenge to ensure the development of LCA in various areas.MethodsOne solution to increase availability is to use LCI data from multiple database sources but under the condition that such LCI data are fully interoperable.Results and discussionThis paper presents original solutions and recent achievements towards increased availability, quality and interoperability of life cycle inventory data, developed through European Commission-led activities and based on wide stakeholder consultation and international dialogue. An overview of related activities, such as the International Reference Life Cycle Data System (ILCD), the European Reference Life Cycle Database (ELCD) and the ILCD Entry-Level quality requirements are presented. The focus is then on the Life Cycle Data Network (LCDN).ConclusionsA non-centralised data network of LCI datasets complying with minimum quality requirements that was politically launched in February 2014, already includes several database nodes from different worldwide sources and has the potential to contribute to the needs of the international community.

Change impact analysis on the life cycle carbon emissions of energy systems – The nuclear example

The life cycle carbon emission factor (measured by t-CO2/GWh) of nuclear power is much lower than those of fossil fueled power generation technologies. However, the fact of nuclear energy being a low carbon power source comes with many assumptions. These assumptions range from system and process definitions, to input–output definitions, to system boundary and cut-off criteria selections, and life cycle inventory dataset. However, there is a somewhat neglected but critical aspect – the design aspect. This refers to the impacts on the life cycle carbon emissions from the change in design parameters related to nuclear power. The design parameters identified in this paper include: (1) the uranium ore grade, (2) the critical process technologies, represented by the average initial enrichment concentration of 235U in the reactor fuel, and (3) the size of the nuclear power reactor (measured by the generating capacity). If not properly tested, assumptions in the design aspect can lead to an erroneous estimation on the life cycle carbon emission factor of nuclear power. In this paper, a methodology is developed using the Process Chain Analysis (PCA) approach to quantify the impacts of the changes in the selected design parameters on the life cycle carbon emission factor of nuclear power. The concept of doing so broadens the scope of PCAs on energy systems from “one-off” calculation to analysis towards favorable/preferred designs. The findings from the analyses can serve as addition to the life cycle inventory database for nuclear power as well as provide indications for the sustainability of nuclear energy systems.

Life cycle greenhouse gas emissions in California rice production

The nexus of climate change and food security challenges currently facing humanity requires better understanding of how to balance food production needs with climate change mitigation. Life cycle assessment methods provide a way to quantify the climate impacts of a food product by accounting for all greenhouse gas (GHG) emissions associated with its production, including upstream and downstream from the farm. This study modeled life cycle GHG emissions for one kg of milled, unpackaged rice produced in California, USA, a state that achieves some of the highest rice yields in the world. The goal was to (1) provide an assessment of life cycle GHG emissions of a comparatively intensive production system, using local field emissions data, (2) identify emissions hotspots, and (3) create a model that elucidates the life cycle-wide consequences of potential changes in field management practices. Study parameters are based on an annual cropping cycle, with continuous flooding during the growing season and soil incorporation of straw post-harvest, and yields of 9.3Mtha−1 dried paddy rice. Field emissions (growing and fallow seasons) were estimated with empirical data while other emissions were calculated using an engineering model coupled with life cycle inventory datasets and vehicle emission models.The 100-year global warming potential (GWP, based on CO2, CH4 and N2O) was 1.47kgCO2-equivalent (CO2e)kg−1 of milled rice; of which field emissions contributed 69%. These results are relatively low when compared to life cycle studies in other parts of the world, due in large part to higher grain yields and lower field emissions. When using IPCC Tier 1 estimates of field emissions, the GWP increased to 3.60CO2ekg−1 rice, highlighting the importance of using direct field measurements as we have in this study. Due to their large contributions to life cycle GWP, reducing field CH4 emissions through different field management practices, optimizing N fertilizer use, and increasing fuel efficiency or reducing use of farm machinery present the greatest opportunities to reduce life cycle emissions. Because of high variability and uncertainty in estimating field emissions, they should also be targeted for improved measurement and modeling.

Assessment and improvement of the appropriateness of an LCI data set on a system level – application to textile manufacturing

Purpose This paper aims at assessing the appropriateness at the system level of different Life Cycle Inventory (LCI) data sets (including default models) selected by the Life Cycle Assessment (LCA) practitioner. This means that the uncertainty measurements are applied on some specific main parameters of the LCI data set instead of measured input values. This approach aims at providing a pragmatic method to approximate and reduce the uncertainties resulting from a lack of information on a specific step.

Quantifying anthropogenic mobilization, flows (in product systems) and emissions of fixed nitrogen in process-based environmental life cycle assessment: rationale, methods and application to a life cycle inventory

Anthropogenic perturbation of the nitrogen cycle is attracting increasing attention as both an environmental and societal concern. Here, we provide the rationale and propose methods for independent treatment of anthropogenic mobilization, flows (in product systems) and emissions of fixed nitrogen in process-based environmental life cycle assessment. We propose a simple methodology for aggregating N flows in life cycle assessment (LCA), with supporting characterization factors for all nitrogen-containing compounds on the Organization for Economic Cooperation and Development High Production Volume Chemical List for which specific chemical formulae are available, as well as all nitrogen-containing flows in the International Reference Life Cycle Data System. We subsequently apply our method and characterization factors to a life cycle inventory data set representing a subset of the consumption attributable to an average EU-27 consumer and compare the results against previously published estimates for nitrogen emissions at the consumer level that were generated using alternative methods/approaches. We derive a suite of over 2,000 characterization factors for nitrogen-containing compounds. Overall, the results generated by applying our method and characterization factors to the European Commission Basket-of-Products life cycle inventory data set are consistent with those observed from studies having a similar scope but different methodological approach. This outcome suggests that anthropogenic mobilization, flows (in product systems) and emissions of fixed nitrogen can, indeed, be systematically inventoried and aggregated in process-based LCA for the purpose of better understanding and managing anthropogenic impacts on the global nitrogen cycle using the methods and characterization factors we propose.

Interoperability between ecoinvent ver. 3 and US LCI database: a case study

Purpose Building a global Life Cycle Inventory (LCI) database from scratch with a harmonized method and wide process coverage would require significant resources. Therefore, it is worth examining to what extent existing LCI datasets can be adapted to form the basis of a more common database. This study examines the opportunities and challenges of transforming the existing US Life Cycle Inventory (US LCI) database to meet the intrinsic (e.g., assumptions, methods, completeness) and extrinsic (e.g., data format) requirements of ecoinvent 3.

Applying cumulative exergy demand (CExD) indicators to the ecoinvent database

Exergy has been put forward as an indicator for the energetic quality of resources. The exergy of a resource accounts for the minimal work necessary to form the resource or for the maximally obtainable amount of work when bringing the resource’s components to their most common state in the natural environment. Exergy measures are traditionally applied to assess energy efficiency, regarding the exergy losses in a process system. However, the measure can be utilised as an indicator of resource quality demand when considering the specific resources that contain the exergy. Such an exergy measure indicates the required resources and assesses the total exergy removal from nature in order to provide a product, process or service. In the current work, the exergy concept is combined with a large number of life cycle inventory datasets available with ecoinvent data v1.2. The goal was, first, to provide an additional impact category indicator to Life-Cycle Assessment practitioners. Second, this work aims at making a large source of exergy scores available to scientific communities that apply exergy as a primary indicator for energy efficiency and resource quality demand. The indicator Cumulative Exergy Demand (CExD) is introduced to depict total exergy removal from nature to provide a product, summing up the exergy of all resources required. CExD assesses the quality of energy demand and includes the exergy of energy carriers as well as of non-energetic materials. In the current paper, the exergy concept was applied to the resources contained in the ecoinvent database, considering chemical, kinetic, hydro-potential, nuclear, solar-radiative and thermal exergies. The impact category indicator is grouped into the eight resource categories fossil, nuclear, hydropower, biomass, other renewables, water, minerals, and metals. Exergy characterization factors for 112 different resources were included in the calculations. CExD was calculated for 2630 ecoinvent product and process systems. The results are presented as average values and for 26 specific groups containing 1197 products, processes and infrastructure units. Depending on the process/product group considered, energetic resources make up between 9% and 100% of the total CExD, with an average contribution of 88%. The exergy of water contributes on the average to 8% the total exergy demand, but to more than 90% in specific process groups. The average contribution of minerals and metal ores is 4%, but shows an average value as high as 38% and 13%, in metallic products and in building materials, respectively. Looking at individual processes, the contribution of the resource categories varies substantially from these average product group values. In comparison to Cumulative Energy Demand (CED) and the abiotic-resource-depletion category of CML 2001 (CML’01), non-energetic resources tend to be weighted more strongly by the CExD method. Energy and matter used in a society are not destroyed but only transformed. What is consumed and eventually depleted is usable energy and usable matter. Exergy is a measure of such useful energy. Therefore, CExD is a suitable energy based indicator for the quality of resources that are removed from nature. Similar to CED, CExD assesses energy use, but regards the quality of the energy and incorporates non-energetic materials like minerals and metals. However, it can be observed for non-renewable energy-intensive products that CExD is very similar to CED. Since CExD considers energetic and non-energetic resources on the basis of exhaustible exergy, the measure is comparable to resource indicators like the resource use category of Eco-indicator 99 and the resource depletion category of CML 2001. An advantage of CExD in comparison to these methods is that exergy is an inherent property of the resource. Therefore less assumptions and subjective choices need to be made in setting up characterization factors. However, CExD does not coversocietal demand (distinguishing between basic demand and luxury), availability or scarcity of the resource. As a consequence of the different weighting approach, CExD may differ considerably from the resource category indicators in Eco-indicator 99 and CML 2001. The current work shows that the exergy concept can be operationalised in product life cycle assessments. CExD is a suitable indicator to assess energy and resource demand. Due to the consideration of the quality of energy and the integration of non-energetic resources, CExD is a more comprehensive indicator than the widely used CED. All of the eight CExD categories proposed are significant contributors to Cumulative Exergy Demand in at least one of the product groups analysed. In product or service assessments and comparative assertions, a careful and concious selection of the appropriate CExD-categories is required based on the energy and resource quality demand concept to be expressed by CExD. A differentiation between the exergy of fossil, nuclear, hydro-potential, biomass, other renewables, water and mineral/metal resources is recommended in order to obtain a more detailed picture of resource quality demand and to recognise trade-offs between resource use, for instance energetic and non-energetic raw materials, or nonrenewable and renewable energies.