Sustainability News and Views Newsletter
Thursday, November 8, 2018, 1:00 pm ET
Eliminating the Idea of Waste with TerraCycle - Free Brown Bag Webinar
A discussion around the current realities of post-consumer plastics recycling in the United States and introduction to TerraCycle — a highly-awarded and globally recognized recycling company operating in over 21 countries globally developing circular solutions for difficult-to-recycle waste streams & eliminating the very idea of waste altogether. .... Read more here
EarthShift Global was Proud to Again Sponsor the Student Poster Awards at LCA XVIII
VeeAnder Mealing, Mochen Liao and Braden Dale Beckstom Receive Prizes for Their Team's Projects:
A Predictive Life Cycle Assessment Model of Activated Carbon Production using Artificial Neural Network
Mochen Liao, Yuan Yao of North Carolina State University
Activated carbon (AC) is a type of porous carbonaceous material that has been widely used as the adsorbent. In 2015, the worldwide demand for AC was 12.8 million ton1
and keeps growing. Depending on the feedstocks and technologies, the environmental footprints and resource consumption of AC production have large variations. For example, with steam activation, the water consumption of AC produced from coal is significantly high than that from coconut shell. Various technologies (e.g., physical activation and chemical activation) applied to specific feedstock will also lead to different environmental impacts. Therefore, it is critical to understand the environmental impacts of the whole life cycle of AC by different feedstocks and technologies, in order to enhance the decision making towards more suitable and sustainable process design for AC supply chains.
A few studies have evaluated the environmental impacts of AC through Life Cycle Assessment (LCA). However, those studies are limited to specific process and feedstock, and previous LCA models may not be applied to a wide range of feedstocks and technologies. In this work, a predictive LCA model is developed by integrating mathematical models into a flexible LCA framework. A large dataset of AC production is collected and used for the training of Artificial Neural Network (ANN), which is combined with the kinetic model to get the Life Cycle Inventory (LCI) data. Scenarios of different combinations of lignocellulosic biomass and production technologies are developed and used to demonstrate the model.
The cradle-to-gate life cycle environmental impacts of various AC production will be presented. The results can be used to screen diverse feedstocks or technology combinations to produce AC, greatly enhancing the process design and optimization for AC production in specific regions. The data generated by the model can also serve as a data source for further analysis of AC. In addition, the integrated methods developed in this work has the potential to be applied to emerging technologies that lack LCI data.
1 P. González-García, “Activated carbon from lignocellulosics precursors: A review of the synthesis methods, characterization techniques and applications,” Renew. Sustain. Energy Rev., 82,1393-1414,2017
Chen, Y., Lv, R., Wang, H., Liao, M., & Li, L. (2016). Ternary liquid – Liquid equilibria for methyl isopropyl ketone + (resorcinol or hydroquinone) + water systems at different temperatures. Fluid Phase Equilibria, 429, 93–97. https://doi.org/10.1016/j.fluid.2016.08.040
Li, Y., Cai, Z., Liao, M., Long, J., Zhao, W., Chen, Y., & Li, X. (2017). Catalytic depolymerization of organosolv sugarcane bagasse lignin in cooperative ionic liquid pairs. Catalysis Today, 298(April), 168–174. https://doi.org/10.1016/j.cattod.2017.04.059
Zhou, S., Liao, M., Liu, D., Li, L., & Chen, Y. (2017). Liquid−Liquid Equilibrium for the Ternary Systems Methyl tert-Butyl Ketone + o , m , p Cresol + Water at (298.2, 313.2, and 323.2) K. Journal of Chemical and Engineering Data, 62, 1929–1936. https://doi.org/10.1021/acs.jced.6b00825
Life Cycle Assessment of Cultivating Guar in the American Southwest
, Hailey Summers2
, Pragnya Eranki1
, Evan Sproul2
, Amy Landis1
, Jason Quinn2
Colorado School of Mines, US; 2
Colorado State University
Guar (Cyamopsis tetragonoloba) is harvested to produce guar gum, a thickening and stabilizing agent used in oil and gas recovery, the production of paper, cosmetics, paints, and detergents. The rise of hydraulic fracturing for shale oil production has increased the world market demand for guar by 250% in the past decade. The United States currently imports the majority (>80%) of its guar demands from India, with increasing annual demands further escalating a continual reliance on imports. This reliance has led to the investigation of cultivating guar in the United States in an effort to generate a more reliable domestic supply chain.
Guar’s high water use efficiency, and low moisture storage requirements make it a drought resistant crop ideal for arid regions of the American Southwest. Initial work to determine the feasibility of integrating guar into the American Southwest has focused on developing models to quantify the resources required to cultivate guar as well as downstream bioprocessing to obtain guar gum. These models were leveraged to develop a life cycle assessment (LCA) which uses the TRACI 2.1 lifecycle impact assessment (LCIA) method to evaluate environmental impacts.
Preliminary results of agricultural modeling show that irrigation and harvesting practices have the highest impact among all TRACI categories. A preliminary sensitivity analysis shows that decreasing the irrigation rate to a minimum value found in literature results in a decrease across all impact categories by over 50%. Results from bioprocessing models have shown that the heating requirements used for guar gum extraction represent the highest energy demand. Modeling results will be used to optimize the overall production of guar gum with experimental work validating models throughout development. Furthermore, the integration of co-products will be investigated, namely the feasibility of obtaining biofuels from residual plant matter. Co-products have the potential to reduce environmental impact and economic costs. Through our analyses, we will determine the environmental impact of cultivating guar in the American Southwest, while considering both the regional and rural economies.
Carbon Sequestration in an Algae Biorefinery Through Bio-Plastic Production.
Braden Dale Beckstrom1
, Michael H. Wilson2
, Mark Crocker2
, Ashton Zeller3
, Jason C. Quinn1
Department of Mechanical Engineering, Colorado State University, Fort Collins, CO; 2
Center for Applied Energy Research, University of Kentucky, Lexington, KY; 3
ALGIX, Meridian, MS
Algae biomass represents a promising feedstock for biorefining into products such as fuels and high value products. Questions have been raised as to the environmental sustainability and economic viability of algal derived products. A promising route for reducing the carbon footprint and cost of production is through the production of high value products. These additional value co-products such as animal feed, specialty chemicals, and nutraceuticals greatly increase the value of the algae biomass, reducing the cost of the produced fuel. In addition to increased biomass value, co-products improve the environmental impact by displacing sales to cleaner production pathways. One co-product sector that has been under explored is bioplastics. Since bioplastic production requires only the protein content of the algae, a fractionation process matches up well with the implementation of bioplastic production. Bioplastics can replace multiple products, including flexible foam, synthetic films and imitation fibers, food packaging, mulch, 3-D printing filament, and others. These products range in value from 0.3-4 $/lb, much higher than other protein uses typically investigated in algal processing. This project leverages engineering process models to analyze the potential improvements in GHG emissions (g CO2 eq/ MJ), net energy ratio, and cost of fuel production ($/gal) from including bioplastics as a co-product in an algal to fuel biorefinery. Sub-process models are validated with experimental work across the entire algal value chain. Experimental data was obtained from growth data specific to flue-gas fed biomass and a fractionation processing system. Results show the inclusion of a bioplastic co-product favorably impacts the environmental impact quantified through GHGs to meet the renewable fuel standard of less than 45 g CO2-eq MJ-1 and decreases the minimum fuel selling price to less than $4 GGE-1. Modeling work compares traditional processing with the integration of a bioplastic revenue stream. Algae biofuels can become an important pathway to successfully monetize carbon capture methods by capturing the carbon while also producing marketable products to consumers.
Interpreting Comparative LCAs Using Multi-Attribute Analysis
A method for ranking alternatives in a comparative LCA, named SMAA (stochastic multi-attribute analysis) is especially useful in those cases when there is no clear best alternative. The goal of LCAs is support for decision-making, but when you have to reconcile trade-offs and differing priorities, how do you evaluate the overall score? SMAA helps you go from mid-point results to a ranking of the alternatives that reflects both performance and the values of decision makers. In other words, the ranking process can help you find the best and worst alternatives of a set.
Confused About Sustainability Terms?
Definitions for Executives, Strategic Planners, Practitioners
Sustainability Training Courses
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November 5-6, 2018 Intro to LCA 1:00 pm to 4:00 pm EST (17:00-20:00 UTC)
November 28-29, 2018 Interpretation 1:00 pm to 4:00 pm EST (17:00-20:00 UTC)
December 4-5, 2018 Practical LCA 1:00 pm to 4:00 pm EST (17:00-20:00 UTC)
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