LCA Capability Roadmap: Product System Model Description and Revision.

Life cycle assessment (LCA) practitioners face many challenges in their efforts to describe, share, review, and revise their product system models; and to reproduce the models and results of others. Current Life cycle inventory modeling techniques have weaknesses in the areas of describing model structure; documenting the use of proxy or non-ideal data; specifying allocation; and including modeler's observations and assumptions -- all affecting how the study is interpreted and limiting the reuse of models. Moreover, LCA software systems manage modeling information in different and sometimes non-compatible ways. Practitioners must also deal with licensing, privacy / confidentiality of data, and other issues around data access which impact how a model can be shared. The aim of this SETAC North America working group is to define a roadmap of the technical advances needed to achieve easier LCA model sharing and improve replicability of LCA results among different users in a way that is independent of the LCA software used to compute the results and does not infringe on any licensing restrictions or confidentiality requirements.

Illustrating anticipatory life cycle assessment for emerging photovoltaic technologies.

Current research policy and strategy documents recommend applying life cycle assessment (LCA) early in research and development (R&D) to guide emerging technologies toward decreased environmental burden. However, existing LCA practices are ill-suited to support these recommendations. Barriers related to data availability, rapid technology change, and isolation of environmental from technical research inhibit application of LCA to developing technologies. Overcoming these challenges requires methodological advances that help identify environmental opportunities prior to large R&D investments. Such an anticipatory approach to LCA requires synthesis of social, environmental, and technical knowledge beyond the capabilities of current practices. This paper introduces a novel framework for anticipatory LCA that incorporates technology forecasting, risk research, social engagement, and comparative impact assessment, then applies this framework to photovoltaic (PV) technologies. These examples illustrate the potential for anticipatory LCA to prioritize research questions and help guide environmentally responsible innovation of emerging technologies.

Algae biodiesel life cycle assessment using current commercial data.

Autotrophic microalgae represent a potential feedstock for transportation fuels, but life cycle assessment (LCA) studies based on laboratory-scale or theoretical data have shown mixed results. We attempt to bridge the gap between laboratory-scale and larger scale biodiesel production by using cultivation and harvesting data from a commercial algae producer with ∼1000 m(2) production area (the base case), and compare that with a hypothetical scaled up facility of 101,000 m(2) (the future case). Extraction and separation data are from Solution Recovery Services, Inc. Conversion and combustion data are from the Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation Model (GREET). The LCA boundaries are defined as "pond-to-wheels". Environmental impacts are quantified as NER (energy in/energy out), global warming potential, photochemical oxidation potential, water depletion, particulate matter, and total NOx and SOx. The functional unit is 1 MJ of energy produced in a passenger car. Results for the base case and the future case show an NER of 33.4 and 1.37, respectively and GWP of 2.9 and 0.18 kg CO2-equivalent, respectively. In comparison, petroleum diesel and soy diesel show an NER of 0.18 and 0.80, respectively and GWP of 0.12 and 0.025, respectively. A critical feature in this work is the low algal productivity (3 g/m(2)/day) reported by the commercial producer, relative to the much higher productivities (20-30 g/m(2)/day) reported by other sources. Notable results include a sensitivity analysis showing that algae with an oil yield of 0.75 kg oil/kg dry biomass in the future case can bring the NER down to 0.64, more comparable with petroleum diesel and soy biodiesel. An important assumption in this work is that all processes are fully co-located and that no transport of intermediate or final products from processing stage to stage is required.