Life Cycle Inventory Datasets Research Articles

Data quality assessment of aggregated LCI datasets: A case study on fossil‐based and bio‐based plastic food packaging

AbstractEnvironmental impacts resulting from plastic food packaging, made from both fossil‐based and bio‐based polymers, are increasingly analyzed in life cycle assessment (LCA) studies. However, the literature reveals significant variations in results for the same polymer within the same scope. To enhance the reliability of these assessments, data quality assessment (DQA) plays a relevant role. However, despite most of the LCA studies employing aggregated life cycle inventory (LCI) datasets, in the literature, DQA methods for aggregated processes are not available. To fill this gap, in this paper, a DQA for aggregated LCI datasets is proposed and demonstrated through its application to 101 aggregated LCI datasets, extracted from Ecoinvent and GaBi databases. The DQA method has been developed by adapting and integrating the pedigree matrix and the data quality ranking proposed by the recently published EC Plastic LCA method. The three data quality indicators (DQIs) used are technological, geographical, and time‐related representativeness. The application of this method exhibits an overall positive evaluation of the selected datasets with differences among the three DQIs. Moreover, it highlights the role of metadata structure in adequately supporting a robust DQA. Indeed, in the absence of a common framework that defines, assesses, and provides access to data quality information, transparency must be assured by the operator in the metadata interpretation and related assumptions along the DQA process. Finally, although the proposed DQA method was developed for the plastic sector, its application can be extended to LCI aggregated datasets relevant to other sectors, materials, and products.

Life cycle inventory dataset for systematic environmental remediation of soil, groundwater and sediment

Life cycle inventory dataset for systematic environmental remediation of soil, groundwater and sediment

Reclaimed water treatment life cycle inventory dataset for China

Reclaimed water treatment life cycle inventory dataset for China

Replacing location-based electricity consumption with market-based residual mixes in background data to avoid possible double counting: a quantitative analysis of effects and challenges

PurposeMost life cycle inventory (LCI) datasets include location-based electricity mixes. Using these LCI datasets in combination with market-based electricity accounting in life cycle assessments (LCAs) leads to double counting of electricity from specific sources, such as renewable energy. The goal of this paper is to analyze market-based accounting by replacing location-based electricity consumption with market-based residual mixes in all processes of the ecoinvent database. The python script for this replacement procedure is openly available.Materials and methodsWe use the Brightway 2 software package to replace European location-based electricity consumption in all 21,238 processes of the ecoinvent database with residual electricity mixes on the corresponding voltage level. The ecoinvent database provides residual electricity mixes for all countries involved in European trade with market-based energy attribute certificates—Guarantees of Origin. We analyze the induced changes to the database both on an individual process level and on a database-wide level. The analysis focusses on the impact category climate change but is further extended to the impact categories terrestrial acidification, freshwater eutrophication, marine eutrophication, ozone depletion, and particulate matter formation.Results and discussionFor European processes, the implementation of the residual electricity mixes leads to average changes in the life cycle impact assessment (LCIA) results for climate change of 1%, 10%, 20%, and 50% for 2958, 733, 387, and 107 processes, respectively. Changes are especially pronounced for Norwegian and Icelandic processes due to the large differences among their location-based and residual electricity mixes. For the other analyzed impact categories, the changes in LCIA results are particularly high for freshwater eutrophication. With the push towards more primary data in LCA and GHG accounting, the impacts of using residual electricity mixes instead of location-based electricity mixes need further research on basis of quantified figures, which we present in this paper.ConclusionThis paper presents an approach towards enabling more consistent market-based accounting throughout LCAs and thereby contributes to the avoidance of double counting. Since only European residual mixes are considered, the database of this paper leads to distortion of LCA results. Further, research is needed to address double counting beyond the European electricity sector. This includes an expansion of this research to a global level and other industrial sectors. Furthermore, research is needed regarding industry-specific electricity sources in LCI datasets, which may also lead to double counting.

Prospective life cycle inventory datasets for conventional and hybrid-electric aircraft technologies

Hybrid-electric aircraft represent a promising solution for the urgent need to decarbonize short-haul flights and bolster aviation sustainability. Nevertheless, the realization of hybrid-electric aircraft demands rigorous environmental impact analysis, given the substantial investments, time, and research required for technology development. This study offers a comprehensive life cycle inventory spanning the years 2030, 2040, and 2050 for both conventional and hybrid-electric aircraft configurations. Our inventory datasets are meticulously constructed through a systematic approach, ensuring data harmonization by drawing upon scientific literature, industry expertise, and primary data sources. This extensive dataset encompasses all pertinent systems necessary to model the environmental footprint of flights covering distances ranging from 200 to 600 nautical miles, utilizing a 50-passenger aircraft with the ATR42 as a reference model. Additionally, we furnish supplemental data for end-of-life considerations and uncertainty analysis. The systems under examination include the airframe, powertrain, power electronics and drives, batteries, fuel cells, hydrogen onboard storage, airport infrastructure, and battery charging stations. Notably, the carbon footprint of conventional aircraft aligns with data from the ecoinvent v3.8 database; however, our provided datasets are more than tenfold more detailed and incorporate a forward-looking perspective. These meticulously curated life cycle inventories can be amalgamated to simulate the potential environmental ramifications of conventional aircraft powered by kerosene or alternative aviation fuels, hybrid-electric aircraft utilizing battery technology, and hybrid-electric aircraft employing hydrogen as a fuel in conjunction with batteries. In this context, our findings play a pivotal role in nurturing the development of technology roadmaps that prioritize environmental sustainability within the realm of regional aviation.

Problematic consequences of the inclusion of capital goods inventory data in Environmental Product Declarations

PurposeA recent update to the Product Category Rules (PCRs) for Construction Products (of the International EPD System) has triggered a methodological issue for owners and users of Environmental Product Declarations (EPDs). The updated PCR has led to capital goods data being implicitly included in the Life Cycle Inventory (LCI) of EPDs. This paper critically examines the role of capital goods in EPDs and establishes major shortcomings in the current methodology, LCI datasets and interpretation.MethodsTo evaluate the role of capital goods in EPDs, this paper provides a discourse on the fundamentals of Life Cycle Assessment (LCA) methodology, scope, available LCI data and the impact of capital goods on EPD outcomes. Using the ecoinvent database, we analyse the impact of the inclusion and exclusion of capital goods in selected 38 construction products based on the EN 15804+A2 (2019) Standard. Finally, we estimate the relative contribution of capital goods to a suite of Life Cycle Impact Assessment (LCIA) indicators based on the archetypes of capital goods available in ecoinvent and apply Monte Carlo simulation to establish the range of uncertainties in the capital goods data for the selected construction products.Results and discussionOur research confirms that when capital goods are included based on currently available background LCI data, they mostly have a low effect (<10% increase) on climate change, but they can have an enormous effect (>100% increase) on abiotic depletion (minerals and metals), land use and/or human toxicity indicators. Interestingly, when looking further into the ecoinvent capital goods LCI datasets, it becomes clear that there are inaccuracies, inconsistencies, and possibly incorrect estimates of capital goods and infrastructure data. These findings raise questions about the suitability of the underlying LCI background data and whether non-attributable capital goods should be allowed to define EPD outcomes.ConclusionThe requirement for the inclusion of capital goods leads to a major conundrum for LCA practitioners. It is suggested that capital goods be excluded until there is better refinement and improvement of the quality of LCI datasets and EPD programs provide clearer guidance on dealing with capital goods. Alternatively, EPDs could document transparently the inclusion or exclusion of capital goods, so that there is a clear separation of the effects of capital goods on LCIA indicators.

Parameterized Modeling of the Energy Demand of Machining Processes as a Basis for Reusable Life Cycle Inventory Datasets

Manufacturing processes have a significant contribution to energy consumption and related greenhouse gas (GHG) emissions in a product’s life cycle. Today, information on GHG emissions is increasingly demanded from companies in a life cycle perspective, based on the methodology of Life Cycle Assessment. Manufacturing companies supply producers of final products and are, therefore, requested to provide data on GHG of their manufacturing processes and resulting products. Obtaining such data for real-world manufacturing processes represents a huge effort. This challenge can be overcome with the use of a parameterized model, the Extended Energy Modeling Approach (EEMA), that has been developed for the machining process, which is a widespread industrial manufacturing process. The model calculates the total energy demand from power key values, which report the average power consumption of the constant and variable units of the machinery equipment, the consumer groups, as well as the different operating states of the equipment. Therefore, EEMA enables the reuse of a single measurement campaign for follow-up investigations of the specific machine tool, thereby significantly improving the efficiency of data acquisition for the calculation of the total energy demand and life-cycle-based GHG emissions. To use EEMA for the compilation of life cycle inventory datasets, methodological requirements were analyzed to derive a procedure for LCA-compliant datasets for machine tools. The key findings of applying the EEMA for the case study of a turning machine show that the constant consumer groups have a significant influence on the total energy demand. The share of the variable consumer groups in the total energy demand increases with increasing machine utilization but is always below 5%.

Prospective Life Cycle Inventory Datasets for Conventional and Hybrid-Electric Aircraft Technologies

Prospective Life Cycle Inventory Datasets for Conventional and Hybrid-Electric Aircraft Technologies

A price-based life cycle impact assessment method to quantify the reduced accessibility to mineral resources value

PurposeSeveral methods were developed to quantify the damage to mineral resources in LCA. Building on these and further expanding the concept of how to assess mineral resources in LCA, the authors developed in previous articles a method to account for dissipative resource flows in life cycle inventory (LCI). This article presents a price-based life cycle impact assessment method to quantify the potential impact of dissipative uses of resources.MethodsThis article firstly defines an impact pathway from resource use to resource dissipation and subsequent damage to the safeguard subject for “mineral resources”. It explores the quantification of this damage through the definition of characterization factors (CFs), for application to dissipative flows reported in LCI datasets. Market prices are used as a relevant proxy for the multiple, complex and varied functions and values held by mineral resources. Price data are collected considering a 50-year timeframe. Intervals of 10, 15, 20 and 30 years are considered for sensitivity analysis. Price-based CFs are tested on one cradle-to-gate case-study (copper production), in combination with accounted resources dissipated across the life-cycle. An approach to calculate the normalization factor (NF) is explored at the EU level.Results and discussionCFs are calculated for 66 mineral resources, considering copper as reference substance. Precious and specialty metals have the largest CFs. Minerals are instead ranked at the bottom of the hierarchy. New insights that this method brings in LCA are discussed for the copper production case-study. Losses due to final disposal of tailings are key (90% of total value loss), as opposed to e.g. emissions to environment. Relevance, robustness, completeness and consistency of the price-based CFs are discussed. This method in particular offers a relatively large coverage of elementary flows, with underlying data of good quality. Sensitivity of CFs to the chosen time interval is relatively limited. Initial analysis for a NF based on 14 key resources dissipated in the EU in 2016 is presented.ConclusionsThe developed CFs are relevant to address the issue of mineral resources value loss in LCA. They may be used in combination with dissipation-based methods at the LCI level, as tested in this study, or potentially (i) with classical extraction-based LCI datasets or (ii) as potential complements to existing life cycle impact assessment methods not capturing damage to resource value. Future refinements shall aim at extension to additional mineral resources and investigate the possibility of regionalisation of CFs and NF calculation.

An instrumental value-based framework for assessing the damages of abiotic resources use in life cycle assessment

Abiotic resources are extensively used in industrialized societies to deliver multiple services that contribute to human well-being. Their increased extraction and use can potentially reduce their accessibility, increase competition among users, and ultimately lead to a deficit of those services. Life cycle assessment is a relevant tool to assess the potential damages of dissipating natural resources. Building on the general consensus recommending evaluating the damages on the instrumental value of resources to humans in order to assess the consequences of resources dissipation, this research work proposes a novel conceptual framework to assess the potential loss of services provided by abiotic resources, which when facing unmet demand can lead to a deficit to human users and have consequences on human well-being. A framework is proposed to describe the mechanisms that link human intervention on the resources in the accessible stock to competition among users. Users facing the deficit of resource services are assumed to have to pay to recover the services, using backup technologies. The mechanisms that are proposed to be characterized are dissipation and degradation. Data needed to later operationalize the framework for abiotic resources are identified. It also proposes a framework at the life cycle inventory level to harmonize life cycle inventories with the current impact assessment framework to fully characterize impacts on resource services. It regards ensuring mass balances of elements between inputs and outputs of life cycle inventory datasets as well as including the functionality of resource flows. The framework provides recommendations for the development of operational life cycle impact assessment (LCIA) methods for resource services deficit assessment. It establishes the impact pathway to damage on the area of protection “Resource Services”, data needed to feed the model and recommendations to improve the current state of life cycle inventories to be harmonized with the LCIA framework.

Higher transparency: A desideratum in environmental life cycle assessment research

Transparency in reporting of Life Cycle Inventory (LCI) data and disclosure of analysis scripts of an environmental Life Cycle Assessment (LCA) model are important as they serve to provide the core evidence underpinning scientific claims. In this study, a transparency assessment was conducted against 438 recently published LCA research. Primary LCI data are frequently disclosed for the majority of the research examined (n = 419, 96%), while a full list of secondary LCI data is only available for one third of the research (n = 152, 35%). The lowest transparency is found in the disclosure of the analysis scripts of LCA models, with only seven research (<2%) providing the information. The adoption of open-source programming languages has the highest potential for improving the data and model transparency and the reproducibility of an LCA. Based on one of the most widely adopted secondary LCI databases, ecoinvent database, the Global Warming Potential of 5280 activities of the 740 unique reference products was calculated. High within-product variations are observed for selected activities, suggesting the need for full disclosure of secondary data applied in an LCA to support the interpretation of its results. Provision of justification on the selection and adaptation of secondary LCI datasets, which is usually not given in the research reviewed, is also highly recommended. With a relatively higher weighting given to the disclosure of secondary datasets, a new “SEARI” scoring system for assessing data and model transparency is proposed, aiming to contribute to the progressive improvement in transparency of LCA studies.

Life Cycle Assessment of the Polyvinylidene Fluoride Polymer with Applications in Various Emerging Technologies

Polyvinylidene fluoride (PVDF) is one of the most popular fluoropolymers in the market. It is commonly used as pipes and cables, binder materials, and membrane materials. Lately, PVDF is being examined for applications in batteries, biomedical research, chemical engineering, and wastewater management. These PVDF applications cover most emerging technologies, which can be attributed to its outstanding physicochemical properties. With the global demand for PVDF in diverse technologies increasing significantly, it is imperative to quantify the environmental impacts associated with its production. Life cycle assessment (LCA) methodology is a standardized approach for evaluating the environmental impacts of novel materials. However, most previous LCA studies have not accounted for PVDF in a scientifically rigorous manner. While compiling the life cycle inventory (LCI) on PVDF, several kinds of surrogates were chosen to bridge the data gap, rather than establishing the new dataset for PVDF. When we investigate the similarities and differences between PVDF and popular surrogates regarding the synthesis pathways, adopting surrogates to replace PVDF becomes difficult. Due to the use of these surrogates, the global warming potential (GWP) calculated in the literature varies significantly, with a difference of 60.7 kg CO2 equiv between the highest and lowest estimates. After evaluating the life cycle environmental profiles of those commonly used surrogates, we find that the application of surrogates is hardly reliable; besides, the PVDF inventory dataset is underestimated. For this reason, we model the PVDF production process according to the commercialized synthesis approach and assess the cradle-to-gate impacts, which lowers uncertainty. The impact assessment on the PVDF inventory dataset results in an acceptable GWP value (55.8 kg CO2 equiv/kg PVDF), but a high cumulative energy demand (CED, 756 MJ equiv/kg PVDF), due to the large demand for chlorine during the production of vinylidene fluoride (VDF). In terms of uncertainty analysis, the upper and lower bounds for the newly developed LCI dataset for PVDF are 801 and 714 MJ equiv for CED values and 59.1 and 52.8 kg CO2 equiv for GWP values, respectively. Notably, this is the first study to develop a detailed LCI for PVDF involved in emerging technologies.

Life cycle assessment of natural graphite production for lithium-ion battery anodes based on industrial primary data

The production of battery materials has been identified as the main contributor to the greenhouse gas (GHG) emissions of lithium-ion batteries for automotive applications. Graphite manufacturing is characterized by energy intense production processes (including extraction), mainly being operated in China with low energy prices and a relatively high GHG emission intensity of electricity generation.Industrial scale primary data related to the production of battery materials lacks transparency and remains scarce in general. In particular, life cycle inventory datasets related to the extraction, refining and coating of graphite as anode material for lithium-ion batteries are incomplete, out of date and hardly representative for today's battery applications. Nevertheless, primary life cycle inventory data of battery materials like graphite, produced on an industrial scale are crucial for a robust evaluation of batteries for electric vehicles, material sourcing and development of robust decarbonization strategies.This paper addresses this issue by first providing a comprehensive overview of the existing graphite datasets and their original sources, and outlining the reasons for wide variations of reported environmental impact results. Furthermore, this paper aims at closing existing data gaps by providing transparent primary data from a Chinese graphite producer from 2019 and assessing the environmental impacts (cradle-to-gate) in form of a life cycle assessment (LCA) for a vertically integrated graphite production. The life cycle inventory covers material, water, energy flows and direct emissions associated with the production of natural graphite anode material for an automotive battery application and associated transport activities along the supply chain. The results of the LCA show that the production of 1000 kg of natural graphite anode material has a global warming potential (GWP) of approximately 9616 kg CO2eq. The subsequent uncertainty analysis in the form of a Monte-Carlo-Analysis with 10000 runs reveals that the 95% confidence interval is in the range between 9297 and 9940 kg CO2eq. This value is more than four times higher than the reported GWP of battery-grade graphite in the ecoinvent database version 3.7.1.

Methodology for a combined uncertainty analysis and data quality rating of existing graphite datasets in context of battery LCAs

Battery raw materials have been identified as one of the main contributors to the overall environmental impact of batteries, however the primary data related to their production remains scarce and is subjected to high uncertainty. In particular, the commercial life cycle inventory datasets related to refining and processing of graphite as an anode material for lithium ion batteries are subjected to in-transparency and are difficult to be traced back. The existing Life Cycle Assessment (LCA) studies on traction batteries make use of these old and partly incomplete graphite datasets without consideration of underlying uncertainties and their effects on the overall environmental impacts. This paper addresses this issue by providing a comprehensive overview of the conventional graphite production processes, a summary of existing graphite datasets, along with their sources and presenting the underlying reasons for the major deviations. Subsequently, the quality of nine different Life Cycle Inventory (LCI) graphite datasets is discussed based on evaluation performed according to EPA data quality guidelines, whereby data gaps are identified and datasets are ranked according to an established data quality rating (DQR) methodology. Furthermore, the paper provides a common base for LCA results of existing graphite production datasets which were remodeled and assessed in Brightway2 (BW2) using background data from a ecoinvent. The results of DQR and LCA reveal major discrepancies in the datasets for the production of battery grade graphite. A Monte Carlo (MC) analysis is also provided to identify uncertainties stemming from technospheric flows, generating result bandwidths. A subsequent case study on state of the art lithium ion battery cell is also presented revealing that the choice of a certain graphite dataset could have a significant impact on the overall LCA results of a battery. The study highlights the need of the graphite datasets to receive more attention in the future.

Cradle-to-gate life cycle assessment of beneficiated phosphate rock production in Tunisia

To improve the sustainable management of phosphorus, numerous LCA studies, using primary data, have been conducted for phosphorus recovery technologies from wastewater, but not for phosphate rock mining.This article addresses this issue by conducting a cradle to gate assessment of beneficiated phosphate rock production using primary data. This study aims to share an updated Life Cycle Inventory dataset of beneficiated phosphate rock production.The studied system is the open-pit mining operations and the wet beneficiation process located in the south of Tunisia. The functional unit is 1 kg of P2O5. Twelve environmental impact categories were assessed using the ReCiPe Midpoint method.The results of Life Cycle Inventory show that the average loss of phosphorus between mining operations, mechanical preparation, and the wet beneficiation is 0.3 kg of P2O5 per 1 kg P2O5. The losses occur mainly during the scrubbing and hydrocycloning. Compared to the production system in Florida, USA, according to the Ecoinvent database 3.4, the production of 1 kg P2O5 in Tunisia has higher Global Warming Potenzial, higher water depletion potential, higher PM10 emission, Photochemical oxidant formation, soil pollution potential, and human toxicity potential.In conclusion, primary data shows comparable results to the generic Life cycle Inventory of wet beneficiation phosphate rock in the Ecoinvent database. This study contributes to enlarge data about sedimentary phosphate rock extraction and beneficiation globally as currently only the USA and Morocco were reported in databases.

Nutrition-Oriented Reformulation of Extruded Cereals and Associated Environmental Footprint: A Case Study

The global food system faces a dual challenge for the decades ahead: to (re)formulate foods capable to feed a growing population while reducing their environmental footprint. In this analysis, nutritional composition, recipe, and sourcing data were analyzed alongside five environmental indicators: climate change (CC), freshwater consumption scarcity (FWCS), abiotic resource depletion (ARD), land use impacts on biodiversity (LUIB), and impacts on ecosphere/ecosystems quality (IEEQ) to assess improvement after three reformulation cycles (2003, 2010, 2018) in three extruded breakfast cereals. A life cycle assessment (LCA) was performed using life cycle inventory (LCI) composed by both primary data from the manufacturer and secondary data from usual third-party LCI datasets. Reformulation led to improved nutritional quality for all three products. In terms of environmental impact, improvements were observed for the CC, ARD, and IEEQ indicators, with average reductions of 12%, 14%, and 2% between 2003 and 2018, respectively. Conversely, the FWCS and LUIB indicators were increased by 57% and 70%, respectively. For all indicators but ARD, ingredients contributed most to the environmental impact. This study highlights the need for further focus on the selection of less demanding ingredients and improvements in agricultural practices in order to achieve environmental and nutritional improvements.

Production Chains of Soft-Weak Stones: Life Cycle Inventory of Techniques and Technologies

The dimension stone sector is more and more active in developing new solutions to improve the sustainability of its supply chain, partly as a consequence of the current EU policies on Circular Economy and Raw Materials. The Life Cycle Assessment (LCA) is a recognized scientific tool for evaluating environmental impacts of the processes. Nevertheless, in the stone sector, LCA is hindered by the scarce availability of Life Cycle Inventory (LCI) datasets for the specific processes of the stone supply chain. This paper provides LCI datasets of the most common and widespread techniques and related technologies for quarrying, cutting and finishing soft-weak stones. To this aim primary data were collected in Italian marble quarries and processing plants and in companies producing cutting tools. When necessary, industry data were complemented with secondary data from literature. High replicability and flexibility of the datasets is obtained through the provision of Unit process inventories for each technology/technique and through the set of parameters. In addition, the uncertainty of the resulting LCI datasets has been evaluated with the well-established procedure of Ecoinvent pedigree matrix. The availability of these datasets contributes to the population of Life Cycle databases and is expected to boost the measurement and enhancement of the key aspects of sustainability in the stone sector.

Uncertainty in LCA: An estimation of practitioner-related effects

The aim of the paper is to quantitatively analyse a main source of uncertainty in LCA practice, i.e. the one due to the LCA practitioner. The same life cycle inventory dataset was used by six practitioners to independently compute six environmental impact categories with a cradle to grave approach, considering a red wine bottle produced by an Italian winery. To obtain the repeatability (r) and reproducibility (R) limits for each impact categories, LCA results were analyzed according to the ASTM E691-05 standard specifications. After a first stage of the study, in which relevant differences in the approach used and results were observed, all the practitioners considered the same system boundaries and processes, and, as a consequence, the results of all the impact categories became comparable. Nevertheless, the choice of different inventory datasets for describing the same process caused variations among the practitioners’ outcomes. This study highlighted how the uncertainties due to the practitioner choices may significantly affect LCA results, especially when lack of information affects the data collection. The practitioner-related uncertainty should be considered in the same way as other uncertainty sources, especially when the Life Cycle impacts of a product are compared to the ones published in other studies.

Building an ILCD/EcoSPOLD2–compliant data-reporting template with application to Canadian agri-food LCI data

Food systems are key drivers of environmental impacts, which may be assessed using life cycle assessment (LCA). Canadian agri-food LCA research has been limited by the unavailability of common life cycle inventory (LCI) data resources characterizing processes in Canadian-specific supply chains. We address this issue through identification and evaluation of publicly available Canadian agri-food LCI data for possible inclusion in the forthcoming Canadian Agri-food Life-Cycle Data Centre (CALDC). A data-reporting template was developed based on comparison of the ILCD and ecoSpold2 data-reporting formats, which contains all fields required for minimum compliance with both formats. Canadian agri-food-related practitioners at academic, government and industry organizations were then identified via web and literature searches, along with associated, publicly available resources containing Canadian agri-food LCI data tables. These data sets were classified by process type and geography, and then screened on the basis of their reported metadata against the identified reporting template to determine which data sets are currently reported in sufficient detail to warrant inclusion in the CALDC. This screening focused, in particular on metadata, and the identification of potential areas of improvement in metadata reporting. The identified data-reporting template contained 65 mandatory fields for LCI data, 58 of which related to metadata. Identification of available Canadian agri-food LCI data sets indicated a high degree of coverage in the field crop sector, and the need for significant further development with respect to data in the livestock, poultry, dairy, and agricultural support sectors. Screening of the data sets against the reporting template indicated that none of the identified data sets are currently reported in sufficient detail to warrant inclusion in the CALDC. In order to enable their inclusion, metadata reporting needs to improve in several areas—in particular, with respect to reporting of the percentage of supply represented by the data sets, and information regarding critical review of the data sets. Comparison of ILCD and ecoSpold2 reporting formats yielded a data-reporting template, the use of which ensures compliance with both formats. Provision of this template will help facilitate interoperability between LCI databases and LCA software across all sectors. Application to publicly available Canadian agri-food sector data indicated that the scope of available LCI data sets in Canada must increase in coverage, quantity, and metadata reporting completeness in order to adequately support agri-food LCA modelling activities and associated sustainability initiatives.

Perspectives on “Game Changer” Global Challenges for Sustainable 21st Century: Plant-Based Diet, Unavoidable Food Waste Biorefining, and Circular Economy

Planet Earth is under severe stress from several inter-linked factors mainly associated with rising global population, linear resource consumption, security of resources, unsurmountable waste generation, and social inequality, which unabated will lead to an unsustainable 21st Century. The traditional way products are designed promotes a linear economy that discards recoverable resources and creates negative environmental and social impacts. Here, we suggest multi-disciplinary approaches encompassing chemistry, process engineering and sustainability science, and sustainable solutions in “game changer” challenges in three intersecting arenas of food: Sustainable diet, valorisation of unavoidable food supply chain wastes, and circularity of food value chain systems aligning with the United Nations’ seventeen Sustainable Development Goals. In the arena of sustainable diet, comprehensive life cycle assessment using the global life cycle inventory datasets and recommended daily servings is conducted to rank food choices, covering all food groups from fresh fruits/vegetables, lentils/pulses and grains to livestock, with regard to health and the environment, to emphasise the essence of plant-based diet, especially plant-based sources of protein, for holistic systemic sustainability and stability of the earth system. In the arena of unavoidable food supply chain wastes, economically feasible and synergistically (energy and material) integrated innovative biorefinery systems are suggested to transform unavoidable food waste into functional and platform chemical productions alongside energy vectors: Fuel or combined heat and power generation. In the arena of circularity of food value chain systems, novel materials and methods for plant-based protein functionalisation for food/nutraceutical applications are investigated using regenerative bio-surfactants from unavoidable food waste. This circular economy or industrial symbiosis example thus combines the other two arenas, i.e., plant-based protein sourcing and unavoidable food waste valorisation. The multi-disciplinary analysis here will eventually impact on policies for dietary change, but also contribute knowledge needed by industry and policy makers and raise awareness amongst the population at large for making a better approach to the circular economy of food.