Time filter

Source Type

Kittery Point, ME, United States

Prado-Lopez V.,Arizona State University | Seager T.P.,Arizona State University | Chester M.,Arizona State University | Laurin L.,EarthShift LLC | And 2 more authors.
International Journal of Life Cycle Assessment | Year: 2014

Purpose: Comparative life-cycle assessments (LCAs) today lack robust methods of interpretation that help decision makers understand and identify tradeoffs in the selection process. Truncating the analysis at characterization is misleading and existing practices for normalization and weighting may unwittingly oversimplify important aspects of a comparison. This paper introduces a novel approach based on a multi-criteria decision analytic method known as stochastic multi-attribute analysis for life-cycle impact assessment (SMAA-LCIA) that uses internal normalization by means of outranking and exploration of feasible weight spaces. Methods: To contrast different valuation methods, this study performs a comparative LCA of liquid and powder laundry detergents using three approaches to normalization and weighting: (1) characterization with internal normalization and equal weighting, (2) typical valuation consisting of external normalization and weights, and (3) SMAA-LCIA using outranking normalization and stochastic weighting. Characterized results are often represented by LCA software with respect to their relative impacts normalized to 100 %. Typical valuation approaches rely on normalization references, single value weights, and utilizes discrete numbers throughout the calculation process to generate single scores. Alternatively, SMAA-LCIA is capable of exploring high uncertainty in the input parameters, normalizes internally by pair-wise comparisons (outranking) and allows for the stochastic exploration of weights. SMAA-LCIA yields probabilistic, rather than discrete comparisons that reflect uncertainty in the relative performance of alternatives. Results and discussion: All methods favored liquid over powder detergent. However, each method results in different conclusions regarding the environmental tradeoffs. Graphical outputs at characterization of comparative assessments portray results in a way that is insensitive to magnitude and thus can be easily misinterpreted. Typical valuation generates results that are oversimplified and unintentionally biased towards a few impact categories due to the use of normalization references. Alternatively, SMAA-LCIA avoids the bias introduced by external normalization references, includes uncertainty in the performance of alternatives and weights, and focuses the analysis on identifying the mutual differences most important to the eventual rank ordering. Conclusions: SMAA-LCIA is particularly appropriate for comparative LCAs because it evaluates mutual differences and weights stochastically. This allows for tradeoff identification and the ability to sample multiple perspectives simultaneously. SMAA-LCIA is a robust tool that can improve understanding of comparative LCA by decision or policy makers. © 2013 Springer-Verlag Berlin Heidelberg. Source

Passell H.,Sandia National Laboratories | Dhaliwal H.,EarthShift LLC | Reno M.,Sandia National Laboratories | Wu B.,Sandia National Laboratories | And 6 more authors.
Journal of Environmental Management | Year: 2013

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 ~1000m2 production area (the base case), and compare that with a hypothetical scaled up facility of 101,000m2 (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 1MJ 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 0.18kg 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 (3g/m2/day) reported by the commercial producer, relative to the much higher productivities (20-30g/m2/day) reported by other sources. Notable results include a sensitivity analysis showing that algae with an oil yield of 0.75kg 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. © 2013 Elsevier Ltd. Source

Dhaliwal H.,EarthShift LLC | Browne M.,General Electric | Flanagan W.,General Electric | Laurin L.,EarthShift LLC | Hamilton M.,EarthShift LLC
International Journal of Life Cycle Assessment | Year: 2014

Purpose: This paper compares environmental impacts of two packaging options for contrast media offered by GE Healthcare: +PLUSPAK™ polymer bottle and traditional glass bottle. The study includes all relevant life cycle stages from manufacturing to use and final disposal of the bottles and includes evaluation of a variety of end-of-life disposal scenarios. The study was performed in accordance with the international standards ISO 14040/14044, and a third-party critical review was conducted.Methods: The functional unit is defined as the packaging of contrast media required to deliver one dose of 96 mL to a patient for an X-ray procedure. Primary data are from GE Healthcare and its suppliers; secondary data are from the ecoinvent database and the literature. A variety of end-of-life disposal scenarios are explored using both cutoff and market-based allocation. Impact assessment includes human health (midpoint) and ecosystems and resources (end point) categories from ReCiPe (H) and cumulative energy demand. Sensitivity analyses include (1) bottle size, (2) secondary packaging, (3) manufacturing electricity, (4) glass recycled content, (5) scrap rate, (6) distribution transport, (7) contrast media, and (8) choice of impact assessment method. Uncertainty analysis is performed to determine how data quality affects the study conclusions.Results and discussion: This study indicates that the polymer bottle outperforms the glass bottle in every environmental impact category considered. Bottle components are the most significant contributors, and the vial body has the highest impacts among bottle components for both polymer and glass bottles. The polymer bottle exhibits lower impact in all impact categories considered regardless of the following: end-of-life treatment (using either cutoff or market-based allocation), bottle size, manufacturing electricity grid mix, glass recycled content, scrap rate, contrast media, distribution transport (air vs. ocean), and choice of impact assessment method. Secondary packaging can be a major contributor to impact. The polymer bottle has considerably lower impact compared to the glass bottle for all multi-pack configurations, but the comparison is less clear for single-pack configurations due to significantly higher packaging material used per functional dose, resulting in proportionally higher impacts in all impact categories.Conclusions: The lower impacts of the polymer bottle for this packaging application can be attributed to lower material and manufacturing impacts, lower distribution impacts, and lower end-of-life disposal impacts. The results of this study suggest that using polymer rather than glass bottles provides a means by which to lower environmental impact of contrast media packaging. © 2014, The Author(s). Source

Discover hidden collaborations