Data for modeling life cycle inventories is always a critical need in LCA. In this session we will learn from the experts on development of data for air transport and chemicals and their applications. We will also hear talks on understanding the implications of data updates in a large database and on a new, innovate way of publishing LCA studies including underlying data. Following the talks, engaging discussion is expected to understand how this research is helping address evolving needs in the LCA community.
Key Discussion Points:
- How can the air transport model presented be a model for future LCI development?
- How well can we rapidly generate life cycle inventories for complex systems? What are the advantages and pitfalls of more automated approaches?
- How important is it for practitioners to understand the data developments and modelling choices in their background databases? How do we help them do so and reduce the misuse/misinterpretation of the data?
- What is the value of tools like the one presented by Dr. Kuceznski to allow clients and interested parties to better understand LCA results and the data they are based on?
|14:00||Brian Cox and Wojciech Jemiolo
Parameterised Life Cycle Assessment of Air Transport Based on Fleet Data
ABSTRACT. We analysed the environmental performance of passenger and freight air transport from 1990 to 2050 for five different plane size categories.
We developed a parameterised model of an airplane, including thrust requirements, passenger and freight capacity, operating empty mass, and flight stages including idling, ground maneuvering, landing, take-off and cruising. Aircraft material composition, fuel consumption and operating emissions are modeled based on the year of aircraft manufacture. Values from 1990 to 2015 are based on historical data from the European commercial aircraft fleet, while projections are used until 2050. We used our model to construct life cycle inventories for airplane travel with flight length, freight and seat load factor, landing and take-off cycle characteristics, aircraft lifetime, and year of aircraft manufacture as variable parameters. We assessed the comparative importance of each LCI input parameter with simplified sensitivity analysis.
Preliminary results indicate that airplane fuel consumption and exhaust emissions are strongly dependent on the year of aircraft manufacture; this parameter has rarely been included in LCA calculations. We also demonstrate the importance of user assumptions such as seat and freight capacity load factors. The separation of flight stages will allow the future addition of regionalised and altitude dependent impact methods for operation pollutant emissions.
Our model allows for more realistic and less uncertain inclusion of the per-passenger or -ton kilometer impacts of air transport. Parameterisation of important input variables will allow LCI database users to more accurately reflect their specific input conditions and help further the understanding of the environmental impacts of air travel. Finally, fleet analysis over time shows that the environmental impacts of aircraft travel are diminishing as aircraft technology develops, and gives an indication of what the impacts of future aircraft travel may look like.
This work was supported by the SCCER Mobility project (www.sccer-mobility.ch).
|14:15||Stefano Cucurachi and Sangwon Suh
Rapid estimation of the life-cycle impacts of new chemicals using the CLiCC tool
ABSTRACT. The Chemical Abstract Service (CAS) registry contains more than 96 million unique organic and inorganic chemical substances. New chemical are added to the registry at the rate of 15,000 per day.
LCA needs to respond to such rapid pace of new chemical discoveries, since the results of LCA studies are increasingly required by regulatory bodies. The California’s Safer Consumer Product regulation, the EU REACH (Registration, Evaluation, Authorization and Restriction of Chemicals) directive, and other chemical substance control regulations in part also require the information on life-cycle impacts of chemicals. Under the multi-disciplinary project Chemical Life-Cycle Collaborative (CLiCC; clicc.ucsb.edu), we created a partnership between industry, academia, and government to develop an open-access tool to rapidly evaluate life-cycle environmental impacts of chemicals.
The CLiCC tool allows assessing chemicals at an early stage of their development also when only limited information is available. The CLiCC tool uses techniques such as chemical process design simulation based on Feinberg’s theorem, predictive toxicology models, multi-media fate-and-transport models, and use and end-of-life phase simulators to rapidly construct LCI data and characterization models of a chemical with uncertainty estimations. The analysis can be subsequently refined as additional data becomes available.A modular structure is employed, allowing the user to run single or more complex assessments according to their specific needs. The tool also makes use of cutting-edge information technologies such as semantic network and Resource Description Framework (RDF) techniques. These novel techniques allow an efficient storage of the resulting LCI and LCIA outputs to the database library allowing the open-access LCA database to organically grow.
Through the assessment of some preliminary results, we will discuss the relevance of the project to the research field of LCA, but also to the broader stakeholders’ base, which is contributing to its development. The CLiCC tool, in fact, allows chemical industries, consumer product manufacturers, researchers, and regulators to develop and access information on chemical life-cycle impacts and facilitate science and data-driven alternative assessment.
|14:30||Gregor Wernet and Bernhard Steubing
Impacts of modeling choices versus data updates in a large data system
ABSTRACT. In LCA, practitioners commonly rely on large LCI databases to model background data in their studies. Such databases are complex systems, so a proven and reliable database can be a significant time-saver. However, the practitioner is still required to understand the background data and their influences on the study results. With the transition to version 3, the ecoinvent database, a large background LCI database, has changed both methodological approaches and carried out a significant data update at the same time. This parallel development can leave practitioners uncertain why results changed in datasets compared to previous versions. An analysis was carried out to assess the major causes of results changes. The presentation highlights the relevant changes in version 3 and explains their impacts on LCIA results throughout the database. Some, such as the global modeling of supply chains, have a significant effect on results, with supply chains now reflecting the impacts of global industrial distribution better, leading to a noticeable increase in impacts in parts of the database. System model changes, e.g. to a consequential model, can have drastic effects but are not mandatory, and beneficial for practitioners working with a consequential goal and scope. Data updates have significant effects on the results of studies, and are often the major source of differences, together with the globalized supply chains. Other changes, e.g. the introduction of consumption mixes (market datasets) have little to no effect on the overall results. As the database under analysis is one of the most commonly used databases, the findings will be of relevance to many LCA practitioners planning to or already working with the ecoinvent database in their daily work.
|14:45||Brandon Kuczenski and Sabina Beraha
A Web Service for LCA Study Publication, Interaction, and Evaluation
ABSTRACT. Although there is a wide variety of software available for preparation of LCA studies and computation of results, the community lacks a straightforward way to publish results that facilitates open-ended evaluation and interpretation. The traditional publication format for an LCA is a static technical report describing the model from a single point of view and (by necessity) containing a limited scope of analysis. If another researcher wishes to make use of the results to compare them against another study, or investigate the model’s sensitivity to input parameters, that researcher must hope that the required information is contained in the published report, or else painstakingly reconstruct the model.
Following a recent experience conducting a high-profile LCA study for a state agency, we were motivated to develop a mechanism that would permit the study audience to conduct independent scenario and sensitivity analysis of the results directly, without an interpretive step to reproduce the model. To do this we designed a web service that implements the core inventory and impact assessment computations, enabling data users to submit queries regarding the model structure and receive results in a machine-readable format for automated processing and integration. The tool supports parametric scenario development, sensitivity analysis, and contribution analysis at different hierarchical levels within the product system model. Data sets designated as private are withheld from direct scrutiny, but their contributions to category scores are still included.
The web service approach provides a provenance framework for LCA results, permitting users to trace results back to source data and perform independent validation and verification without the involvement of the study author. The product system model is also described precisely, filling a gap in existing LCA data serialization formats. Using the tool, study authors can present their models and results transparently while protecting confidential data. By providing a structured, interactive format for publishing and data sharing, the tool can foster the use of LCA for applications involving high levels of scrutiny and public review, such as public policy development.