Electric passenger car transport and passenger car life cycle inventories in ecoinvent version 3

Purpose

Due to the large environmental challenges posed by the transport sector, reliable and state-of-the art data for its life cycle assessment is essential for enabling a successful transition towards more sustainable systems. In this paper, the new electric passenger car transport and vehicle datasets, which have been developed for ecoinvent version 3, are presented.

Methods

The new datasets have been developed with a strong modular approach, defining a hierarchy of datasets corresponding to various technical components in the vehicle. A vehicle is therefore modelled by linking together the various component datasets. Also, parameters and mathematical formulas have been introduced in order to define the amount of exchanges in the datasets through common transport and vehicle characteristics. This supports users in the choice of the amount of exchanges and enhances the transparency of the dataset.

Results

The new transport dataset describes the transport over 1 km with a battery electric passenger car taking into account the vehicle production and end of life, the energy consumption due to the use phase, non-exhaust emissions, maintenance and road infrastructure. The dataset has been developed and is suitable for a compact class vehicle.

Conclusions

A new electric passenger car transport dataset has been developed for version 3 of the ecoinvent database which exploits modularisation and parameters with the aim of facilitating users in adapting the data to their specific needs. Apart from the direct use of the transport dataset for background data, the various datasets for the different components can also be used as building blocks for virtual vehicles.

     

Prioritizing regionalization efforts in life cycle assessment through global sensitivity analysis: a sector meta-analysis based on ecoinvent v3

The International Journal of Life Cycle Assessment - Regionalization in life cycle assessment (LCA) aims to increase the representativeness of LCA results and reduce the uncertainty due to spatial...     

On the relevance of scope 3 emissions and power trade for regional life cycle inventories of electricity consumption in the USA

The International Journal of Life Cycle Assessment - Most life cycle inventories (LCIs) of electricity consumed in different regions of the USA disregard the power that is being traded between...     

Framework for modelling data uncertainty in life cycle inventories

Modelling data uncertainty is not common practice in life cycle inventories (LCI), although different techniques are available for estimating and expressing uncertainties, and for propagating the uncertainties to the final model results. To clarify and stimulate the use of data uncertainty assessments in common LCI practice, the SETAC working group ‘Data Availability and Quality’ presents a framework for data uncertainty assessment in LCI. Data uncertainty is divided in two categories: (1) lack of data, further specified as complete lack of data (data gaps) and a lack of representative data, and (2) data inaccuracy. Filling data gaps can be done by input-output modelling, using information for similar products or the main ingredients of a product, and applying the law of mass conservation. Lack of temporal, geographical and further technological correlation between the data used and needed may be accounted for by applying uncertainty factors to the non-representative data. Stochastic modelling, which can be performed by Monte Carlo simulation, is a promising technique to deal with data inaccuracy in LCIs.     

Life cycle inventories and life cycle assessment for an electricity grid network: case study of the Jamali grid,Indonesia

The International Journal of Life Cycle Assessment - The electricity and heat sectors are reported to contribute approximately 40% of total CO2 emissions from the energy sector in Indonesia....     

A life cycle model for high-speed rail infrastructure: environmental inventories and assessment of the Tours-Bordeaux railway in France

Purpose

The objective of the study is to progress towards a comprehensive component-based Life Cycle Assessment model with clear and reusable Life Cycle Inventories (LCIs) for high-speed rail (HSR) infrastructure components, and to assess the main environmental impacts of HSR infrastructure over its lifespan, to finally determine environmental hotpots and good practices.

Methods

A process-based LCA compliant with ISO 14040 and 14044 is performed. Construction-stage LCIs rely on data collection conducted with the concessionaire of the HSR line combined with EcoInvent 3.1 inventories. Use and End-of-Life stages LCIs rest on expert feedback scenarios and field data. A set of 13 midpoint indicators is proposed to capture the diversity of the environmental damage: climate change, consumptions of primary energy and non-renewable resources, human toxicity and ecotoxicities, eutrophication, acidification, radioactive and bulk wastes, stratospheric ozone depletion, and summer smog. Three characterization methods are used: the “Cumulative Energy Demand” method to quantify energy demand, the EDIP method for waste productions, and the CML method for the rest.

Results and discussion

The study shows major contributions to environmental impact from rails (10–71%), roadbed (3–48%), and civil engineering structures (4–28%). More limited impact is noted from ballast (1–22%), building machines (0–17%), sleepers (4–11%), and power supply system (2–12%). The two last components, chairs and fasteners, have negligible impact (max. 1 and 3% of total contributions, respectively). Direct transportation can contribute up to 18% of total impact. The production and maintenance stages contribute roughly equally to environmental deterioration (respectively average of 62 and 59%). Because the End-of-Life (EoL) mainly includes recycling with environmental credit accounted for in our 100:100 approach, this stage has globally a positive impact (??9 to ??98%) on all the impact categories except terrestrial ecotoxicity (58%), radioactive waste (11%), and ozone depletion (8%). Contribution analyses show that if concrete production is one of the important contributing processes over the construction stage, primary steel production is unquestionably the most important process on all the impact categories over the entire life cycle.

Conclusions

These results are of interest for public authorities and the rail industry, in order to consider the full life cycle impacts of transportation infrastructure in a decision-making process with better understanding and inclusion of the environmental constraints. Suggestions are provided in this way for life cycle good practices—for instance as regards gravel recycling choices—and additional research to reduce the impact of current major contributors.

     

Toward a solution of allocation in life cycle inventories: the use of least-squares techniques

Purpose  

The matrix method for the solution of the so-called inventory problem in LCA generally determines the inventory vector related to a specific system of processes by solving a system of linear equations. The paper proposes a new approach to deal with systems characterized by a rectangular (and thus non-invertible) coefficients matrix. The approach, based on the application of regression techniques, allows solving the system without using computational expedients such as the allocation procedure.     

Carbon footprint and air emissions inventories for US honey production: case studies

Purpose

The primary purpose of this study is to estimate the life cycle greenhouse gas (GHG) emissions (carbon footprint) and criteria pollutant emissions during honey production and processing for US conditions based on several case studies of different scale beekeeping and processing operations. Commercial beekeeping operations yield two coproducts, honey and pollination services. These two products present an interesting coproduct allocation problem since beekeeping operations cannot be clearly subdivided, pollination services do not have a substitutable product or service, and pollination services cannot be characterized by physical properties for value-based allocation. Thus, a secondary purpose is to identify an appropriate allocation method and to discuss how the choice of allocation strategies influences the outcomes.

Methods

The commercial honey production supply chain comprises the following two primary steps: raw honey production by beekeepers and honey processing and packaging by processors. A case study approach was used based on detailed operation data provided by several beekeepers and processors from key honey-producing regions in the USA. Process-based life cycle assessment was conducted following the ISO guidelines, and economic allocation was used as a baseline method for coproduct allocation.

Results and discussion

Life cycle modeling of one complete commercial supply chain (raw honey production, transport to a processer, and processing) shows that total life cycle GHG emissions range from 0.67 to 0.92 kg CO₂ equivalent/kg of processed honey; however, outcomes show significant variability. Results show commercial honey production emits more GHGs and criteria pollutants than processing. Truck transport of bees is the dominant contributor of both GHG emissions and criteria pollutants within the life cycle of raw honey production. However, honey processing, which depends on natural gas and electricity, contributes a significant fraction of SO _x . These results are based on economic allocation among beekeeping coproducts. In addition to economic allocation, subdivision was applied to beekeeping activities. Because hive management (feed and medication) could not be further subdivided, a bounded range was generated for raw honey production, where the lower and upper bounds represent two extremes where all the environmental burdens associated with hive management were allocated to pollination or honey production.

Conclusions

Economic allocation tends to fall near or below the lower bound for the subdivision method. Interestingly, some beekeepers reported that their hive management practices were driven more by demand for pollination services than honey, which seems to be reflected in the coordination of lower-bound subdivision and economic allocation results.     

Correction to: Methodology to address potential impacts of plastic emissions in life cycle assessment

The International Journal of Life Cycle Assessment -     

A general framework for including biogenic carbon emissions and removals in the life cycle assessments for forestry products

The International Journal of Life Cycle Assessment -     

Accounting for overfishing in life cycle assessment: new impact categories for biotic resource use

Purpose

Overfishing is a relevant issue to include in all life cycle assessments (LCAs) involving wild caught fish, as overfishing of fish stocks clearly targets the LCA safeguard objects of natural resources and natural ecosystems. Yet no robust method for assessing overfishing has been available. We propose lost potential yield (LPY) as a midpoint impact category to quantify overfishing, comparing the outcome of current with target fisheries management. This category primarily reflects the impact on biotic resource availability, but also serves as a proxy for ecosystem impacts within each stock.

Methods

LPY represents average lost catches owing to ongoing overfishing, assessed by simplified biomass projections covering different fishing mortality scenarios. It is based on the maximum sustainable yield concept and complemented by two alternative methods, overfishing though fishing mortality (OF) and overfishedness of biomass (OB), that are less data-demanding.

Results and discussion

Characterization factors are provided for 31 European commercial fish stocks in 2010, representing 74 % of European and 7 % of global landings. However, large spatial and temporal variations were observed, requiring novel approaches for the LCA practitioner. The methodology is considered compliant with the International Reference Life Cycle Data System (ILCD) standard in most relevant aspects, although harmonization through normalization and endpoint characterization is only briefly discussed.

Conclusions

Seafood LCAs including any of the three approaches can be a powerful communicative tool for the food industry, seafood certification programmes, and for fisheries management.     

An extended life cycle analysis of packaging systems for fruit and vegetable transport in Europe

Purpose

The year-round supply of fresh fruit and vegetables in Europe requires a complex logistics system. In this study, the most common European fruit and vegetable transport packaging systems, namely single-use wooden and cardboard boxes and re-useable plastic crates, are analyzed and compared considering environmental, economic, and social impacts.

Methods

The environmental, economic, and social potentials of the three transport packaging systems are examined and compared from a life cycle perspective using Life Cycle Assessment (LCA), Life Cycle Costing (LCC) and Life Cycle Working Environment (LCWE) methodologies. Relevant parameters influencing the results are analyzed in different scenarios, and their impacts are quantified. The underlying environmental analysis is an ISO 14040 and 14044 comparative Life Cycle Assessment that was critically reviewed by an independent expert panel.

Results and discussion

The results show that wooden boxes and plastic crates perform very similarly in the Global Warming Potential, Acidification Potential, and Photochemical Ozone Creation Potential categories; while plastic crates have a lower impact in the Eutrophication Potential and Abiotic Resource Depletion Potential categories. Cardboard boxes show the highest impacts in all assessed categories. The analysis of the life cycle costs show that the re-usable system is the most cost effective over its entire life cycle. For the production of a single crate, the plastic crates require the most human labor. The share of female employment for the cardboard boxes is the lowest. All three systems require a relatively large share of low-qualified employees. The plastic crate system shows a much lower lethal accident rate. The higher rate for the wooden and cardboard boxes arises mainly from wood logging. In addition, the sustainability consequences due to the influence of packaging in preventing food losses are discussed, and future research combining aspects both from food LCAs and transport packing/packaging LCAs is recommended.

Conclusions

For all three systems, optimization potentials regarding their environmental life cycle performance were identified. Wooden boxes (single use) and plastic crates (re-usable) show preferable environmental performance. The calibration of the system parameters, such as end-of-life treatment, showed environmental optimization potentials in all transport packaging systems. The assessment of the economic and the social dimensions in parallel is important in order to avoid trade-offs between the three sustainability dimensions. Merging economic and social aspects into a Life Cycle Assessment is becoming more and more important, and their integration into one model ensures a consistent modeling approach for a manageable effort.     

USEtox fate and ecotoxicity factors for comparative assessment of toxic emissions in life cycle analysis: sensitivity to key chemical properties

Purpose  

The USEtox model was developed in a scientific consensus process involving comparison of and harmonization between existing environmental multimedia fate models. USEtox quantitatively models the continuum from chemical emission to freshwater ecosystem toxicity via chemical-specific characterization factors (CFs) for Life Cycle Impact Assessment (LCIA). This work provides understanding of the key mechanisms and chemical parameters influencing fate in the environment and impact on aquatic ecosystems.     

USEtox human exposure and toxicity factors for comparative assessment of toxic emissions in life cycle analysis: sensitivity to key chemical properties

Purpose

The aim of this paper is to provide science-based consensus and guidance for health effects modelling in comparative assessments based on human exposure and toxicity. This aim is achieved by (a) describing the USEtox? exposure and toxicity models representing consensus and recommended modelling practice, (b) identifying key mechanisms influencing human exposure and toxicity effects of chemical emissions, (c) extending substance coverage.

Methods

The methods section of this paper contains a detailed documentation of both the human exposure and toxic effects models of USEtox?, to determine impacts on human health per kilogram substance emitted in different compartments. These are considered as scientific consensus and therefore recommended practice for comparative toxic impact assessment. The framework of the exposure model is described in details including the modelling of each exposure pathway considered (i.e. inhalation through air, ingestion through (a) drinking water, (b) agricultural produce, (c) meat and milk, and (d) fish). The calculation of human health effect factors for cancer and non-cancer effects via ingestion and inhalation exposure respectively is described. This section also includes discussions regarding parameterisation and estimation of input data needed, including route-to-route and acute-to-chronic extrapolations.

Results and discussion

For most chemicals in USEtox?, inhalation, above-ground agricultural produce, and fish are the important exposure pathways with key driving factors being the compartment and place of emission, partitioning, degradation, bioaccumulation and bioconcentration, and dietary habits of the population. For inhalation, the population density is the key factor driving the intake, thus the importance to differentiate emissions in urban areas, except for very persistent and mobile chemicals that are taken in by the global population independently from their place of emission. The analysis of carcinogenic potency (TD₅₀) when volatile chemicals are administrated to rats and mice by both inhalation and an oral route suggests that results by one route can reasonably be used to represent another route. However, we first identify and mark as interim chemicals for which observed tumours are directly related to a given exposure route (e.g. for nasal or lung, or gastrointestinal cancers) or for which absorbed fraction by inhalation and by oral route differ greatly.

Conclusions

A documentation of the human exposure and toxicity models of USEtox? is provided, and key factors driving the human health characterisation factor are identified. Approaches are proposed to derive human toxic effect factors and expand the number of chemicals in USEtox?, primarily by extrapolating from an oral route to exposure in air (and optionally acute-to-chronic). Some exposure pathways (e.g. indoor inhalation, pesticide residues, dermal exposure) will be included in a later stage. USEtox? is applicable in various comparative toxicity impact assessments and not limited to LCA.     

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

Purpose

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.

Methods

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.

Results and discussion

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.

Conclusions

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.     

Geographical and technological differences in life cycle inventories shown by the use of process models for waste incinerators part I. technological and geographical differences

Goal and Background  Geographical and technological differences in Life Cycle Inventory data are an important source for uncertainty in the result of Life Cycle Assessments. Knowledge on their impact on the result of an LCA is scarce, and also knowledge on how to manage them in an LCA case study. Objective  Goal of this paper is to explore these differences for municipal solid waste incinerator plants, and to develop recommendations for managing technological and geographical differences. Methodology  The paper provides a definition of technological and geographical differences, and analyses their possible impacts. In a case study, the differences are caused intentionally in ‘games’, by virtually transplanting incineration plants to a different location and by changing parameters such as the composition of the waste input incinerated. The games are performed by using a modular model for municipal solid waste incinerator plants. In each case, an LCA including an Impact Assessment is calculated to trace the impact of these changes, and the results are compared. Conclusions  The conclusions of the paper are two-fold: (1) reduce the differences in inventory data where their impact on the result is high; where it is possible reducing them to a great extent, and the effort for performing the change acceptable; in the case of incineration plants: Adapt the flue gas treatment, especially a possible DeNOx step, to the real conditions; (2) make use of modular process models that allow adapting plant parameters to better meet real conditions, but be aware of possible modelling errors. The paper invites the scientific community to validate the model used for a waste incinerator plant, and suggest putting up similar models for other processes, preferably those of similar relevance for Life Cycle Inventories.     

A methodology for separating uncertainty and variability in the life cycle greenhouse gas emissions of coal-fueled power generation in the USA

Purpose

Results of life cycle assessments (LCAs) of power generation technologies are increasingly reported in terms of typical values and possible ranges. Extents of these ranges result from both variability and uncertainty. Uncertainty may be reduced via additional research. However, variability is a characteristic of supply chains as they exist; as such, it cannot be reduced without modifying existing systems. The goal of this study is to separately quantify uncertainty and variability in LCA.

Methods

In this paper, we present a novel method for differentiating uncertainty from variability in life cycle assessments of coal-fueled power generation, with a specific focus on greenhouse gas emissions. Individual coal supply chains were analyzed for 364 US coal power plants. Uncertainty in CO₂ and CH₄ emissions throughout these supply chains was quantified via Monte Carlo simulation. The method may be used to identify key factors that drive the range of life cycle emissions as well as the limits of precision of an LCA.

Results and discussion

Using this method, we statistically characterized the carbon footprint of coal power in the USA in 2009. Our method reveals that the average carbon footprint of coal power (100 year time horizon) ranges from 0.97 to 1.69 kg CO₂eq/kWh of generated electricity (95 % confidence interval), primarily due to variability in plant efficiency. Uncertainty in the carbon footprints of individual plants spans a factor of 1.04 for the least uncertain plant footprint to a factor of 1.2 for the most uncertain plant footprint (95 % uncertainty intervals). The uncertainty in the total carbon footprint of all US coal power plants spans a factor of 1.05.

Conclusions

We have developed and successfully implemented a framework for separating uncertainty and variability in the carbon footprint of coal-fired power plants. Reduction of uncertainty will not substantially reduce the range of predicted emissions. The range can only be reduced via substantial changes to the US coal power infrastructure. The finding that variability is larger than uncertainty can obviously not be generalized to other product systems and impact categories. Our framework can, however, be used to assess the relative influence of uncertainty and variability for a whole range of product systems and environmental impacts.