EarthShift Global Sustainability News Articles

Environmental Performance of Copper-alloy Net-pens: Life cycle Assessment of Atlantic Salmon Grow-out in Copper-alloy and Nylon Net-pens

Authors:  Nathan Ayer, Shelly Martin, Robert L. Dwyer, Langley Gace, Lise Laurin
 
Abstract:
 
The environmental impacts of culturing Atlantic salmon in copper-alloy mesh (CAM) net-pens were studied using infrastructure and operating data from a pilot study in Chile in 2012. The analysis included a comparative assessment of culturing fish in CAM net-pens relative to industry-average Chilean nylon net-pen systems in 2012, and an environmental hot-spot analysis of the CAM net-pen supply chain. Life cycle assessment (LCA) was used to quantify the environmental performance of both systems in compliance with the ISO 14040 and 14044 standards for LCA, including sensitivity analysis and uncertainty analysis to test the robustness of the methodology and key assumptions. Results of the study indicated that use of the CAM resulted in improvements in several key performance characteristics, including reductions in feed inputs, on-site energy use, application of antibiotics, and labor hours. These operating performance improvements resulted in reductions in life cycle impacts relative to conventional nylon net-pen systems for nearly all environmental indicators considered, including climate change, acidification, marine eco-toxicity, metal depletion, and cumulative energy demand. The reduced impacts for marine eco-toxicity and metal depletion were a result of lower copper leach rates for the CAM netting relative to nylon netting coated in antifouling paint, as well as the high recyclability of the CAM net material. The recyclability of the CAM nets could result in a more cyclical and sustainable use of copper in the aquaculture industry relative to the one-time use and permanent loss of copper used in anti-fouling paints for nylon nets. The International Copper Association (ICA) is continuing to collect life cycle inventory (LCI) data to further characterize the environmental performance of CAM net-pen systems in an effort to provide further quantitative evidence of the benefits of this emerging alternative to nylon net-pen systems.
 
Aquaculture
Volume 453, 20 February 2016, Pages 93–103
 
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Algae Biodiesel Life Cycle Assessment using Commercial Data

Authors:  Howard Passell, Harnoor Dhaliwal, Marissa Reno, Ben Wu, Ami Ben Amotz, Etai Ivry, Marcus Gay, Tom Czartoski, Lise Laurin, Nathan Ayer
 
Abstract:
 
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 m2 production area (the base case), and compare that with a hypothetical scaled up facility of 101,000 m2 (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/m2/day) reported by the commercial producer, relative to the much higher productivities (20–30 g/m2/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.
 
Journal of Environmental Management
Volume 129, 15 November 2013, Pages 103–111
 
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A Life Cycle Assessment of Packaging Options for Contrast Media Delivery: Comparing Polymer Bottle vs. Glass Bottle

Authors:  Harnoor Dhaliwal, Martin Browne, William Flanagan, Lise Laurin, Melissa Hamilton
 
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.
 
The International Journal of Life Cycle Assessment
December 2014, Volume 19, Issue 12, pp 1965–1973
 
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Stochastic Multi-attribute Analysis (SMAA) as an Interpretation Method for Comparative Life-cycle Assessment

Authors:  Valentina Prado-Lopez, Thomas P. Seager, Mikhail Chester, Lise Laurin, Melissa Bernardo, Steven Tylock
 
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.
 
The International Journal of Life Cycle Assessment
February 2014, Volume 19, Issue 2, pp 405–416
 
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Illustrating Anticipatory Life Cycle Assessment for Emerging Photovoltaic Technologies

Authors:  Ben A. Wender, Rider W. Foley, Valentina Prado-Lopez, Dwarakanath Ravikumar, Daniel A. Eisenberg, Troy A. Hottle, Jathan Sadowski, William P. Flanagan, Angela Fisher, Lise Laurin, Matthew E. Bates, Igor Linkov, Thomas P. Seager, Matthew P. Fraser, and David H. Guston
 
Abstract:
 
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.
 
Environmental Science & Technology
2014, 48, 10531−10538
 
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