Incorporation of Life Cycle Assessment for Territorial - Scale Decision Support

Joshua Sohn

Research output: Book/ReportPh.D. thesis


Life cycle assessment has its roots in cumulative energy demand assessments from more than half a century ago, with the Coca-Cola Company introducing what would eventually become modern LCA with a comparison of packaging materials a few years later. Since that time, both the scope, in terms of what environmental impacts are covered, as well as the scale in terms of the types of systems that are assessed have broadened drastically. One development on this front has been the application of LCA for large spatial-scale planning, with the introduction of methods such as those that tie together urban metabolism and LCA. This development is valuable, as it has opened the door for many valuable insights as well as evidence-based design at the regional and national scale, but with these developments come challenges. This PhD serves to answer some of the challenges that arise in this type of largescale assessment.

With a starting point in the No Agricultural Waste (NoAW) horizon 2020 project, this PhDs primary purpose was to provide territorial scale decision support regarding the various biorefinery value chains that were developed within the NoAW project. In order to do this, a deductive process was undertaken, where the desired outcome was described, namely decision support for territorial scale installation of biorefineries that is easily understood by non-experts, in order to develop a shortlist of issues that needed to be solved in order to serve that purpose. This resulted in the outlining of three primary issues that define the first part, and the scientific underpinning, of this PhD:

1. There was a need for uniform delineation of the assessed regions, as political boundaries did not necessarily well-suit the projects demands. In addition, a uniform application of LCA needed to be described to allow for the various assessments that would be undertaken within the project to be joined in projectencompassing decision support.

2. Because the NoAW project deals with installations with a typical service life of two decades or more, the uncertainty with regard to temporal variations needed to be addressed and best practice guidelines for handling temporal system dynamism defined.

3. Because the project was driven primarily by stakeholders without significant knowledge regarding environmental assessment or LCA, and because there was a need to unify results from both environmental and economic assessments, a form of multiple criteria decision support was deemed necessary. Furthermore, the need to provide specific and delineable decisionmaking metrics with incorporation of stakeholder demands necessitated the development of a stakeholder-driven multi-criteria decision support method.

To solve these issues, two methods and one set of best practices were developed. The first issue was addressed through the development of the Territorial Metabolism-LCA (TM-LCA) method. It takes elements of Urban Metabolism-LCA and multi-pronged data acquisition approaches to define the assessment methodology that was eventually used within the NoAW project, and also with potential for applications outside of NoAW for territorial scale LCA. The second issue was addressed through a literature review regarding temporally dynamic LCA. An analysis of these works found that application temporal dynamism varied considerably amongst the assessed works, and that, oftentimes, assessed systems were sensitive to its application. This led to a suggestion that system dynamism be included in the assessment of long-service-life systems like those within the NoAW project, at a minimum, as part of a sensitivity analysis within the assessment.

The final issue was approached through the development of the Argumentation Corrected Context Weighting for LCA (ArgCW-LCA) methodology. It defines an application of the Technique of Order Preference Similarity to the Ideal Solution (TOPSIS) multiple criteria decision assessment method, utilizing weighting derived from stakeholder preference as well as environmental relevance. The former is developed by applying computational argumentation in order to derive a weighting profile for the criteria used within a given assessment from responses solicited from stakeholders. This allowed for the incorporation stakeholder preferences and disparate (non-similar unit) criteria into discrete and quantifiable decision support. The second part of the PhD is defined by the application of these methods and best practices in the context of LCA, primarily within but also outside of the context of NoAW. The following applications were undertaken:

1. An LCA, utilizing the TM-LCA methodology and temporal dynamics, of anaerobic digestion value chains at a territorial scale in Oregon and France comparing a typical set up with a plant that included an add-on step for the production of polyhydroxyalkanoates. It was concluded that there was potential for greenhouse gas emissions reductions that would likely increase in the future as energy grids become more environmentally optimized.

2. An LCA, utilizing the ArgCW-LCA and TM-LCA methodologies, of polyphenol extraction from winery grape marc comparing two extraction technologies, a solvent extraction and a pressurized liquid extraction – both also shown with various ratios of solvent to dry matter. It was shown that while pressurized liquid extraction could be more financially beneficial at the lowest ratio of solvent to dry matter, there was more potential for solvent extraction to outperform pressurized liquid extraction both environmentally and economically.

3. An LCA, utilizing ArgCW-LCA, TM-LCA, and temporal dynamics, of anaerobic digestion value chains at both single farm and territorial scale in Italy and Germany. In addition to environmental assessment, a techno-economic assessment was also performed. Assessed technologies include a typical anaerobic digestion plant as well as a typical plant with a feedstock pretreatment step and a typical anaerobic digestion plant with Polyhydroxyalkanoates production. It was shown that all technologies required significant economic subsidy, but that both environmentally and economically, anaerobic digestion with feedstock pretreatment exhibited the greatest potential for benefits.

4. An LCA, incorporating ArgCW-LCA and TM-LCA, was performed assessing the concept of no agricultural waste. To test the concept, an LCA was performed at a territorial scale for regions in France, Germany, Italy, Sweden, and the US assessing anaerobic digestion, polyphenol extraction, polyhydroxyalkanoates production, thermoplastic filler material production, and potential combinations of these. This was done both at single technology-feedstock-region level as well as at the level of the entire value chain for a given region. It was shown that there is disagreement between overall environmental impacts and global warming potential within the value chains and technologies, e.g. in Sweden all anaerobic digestion technologies exhibited potential for reduction of global warming potential as well as potential for overall environmental damage. Thus, it was shown that the no agricultural waste concept has the potential for environmental benefit, but that this potential must be assessed for each particular situation in order to prevent burden shifting and inadvertent increases in environmental burdens.

5. An LCA of clothing, particularly jeans and t-shirts, was performed utilizing a rich dataset regarding the use stage and purchasing patterns for consumers in Germany, Poland, Sweden, and the US. ArgCW-LCA and monetized environmental damages are used to check the sensitivity of the system to interpretation method, which resulted in an indication of little to no sensitivity. Analysis using Dynamic LCA showed sensitivity to the changes in energy provisioning systems. Through the assessment, it was shown that consumer behavior has particularly great potential to affect the environmental impacts that occur over the life cycle of jeans and t-shirts, with the use stage consumptions patterns accounting for as little as ca. 10% and as much as ca. 50% of total environmental impacts from consumption. Furthermore, by applying the user behaviors of the region with the least use-stage impacts (Sweden) in the region with the greatest use-stage impacts (the US) with regard to jeans consumption, it was shown that a such an example change in user behavior would result in over 50% reductions in environmental impact relative to the average US consumer. As such, it was suggested that the use stage should be a target for impact reductions in the clothing sector and that realistic use stage data should be considered in future LCA of clothing.

Through the development of these methodologies and their application in LCA, it was illustrated how LCA can be incorporated for territorial scale decision support, and how the tools developed for carrying out those assessments might have potential further value to the field of LCA.

Original languageEnglish
Number of pages287
Publication statusPublished - 2020

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