Better, but good enough? Indicators for absolute environmental sustainability in a life cycle perspective

    Research output: Book/ReportPh.D. thesis

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    An increasing focus on sustainability has led to proliferation of the use of environmental indicators to guide various types of decisions, from individual consumer choices to policy making at the national, regional and global scale. Most environmental indicators are relative, meaning that quantified environmental interferences of a studied anthropogenic system (a product, a company, a city, etc.) are compared to those of chosen anthropogenic systems of reference. The use of relative indicators can give the impression that societies are moving towards environmental sustainability when decisions are being made which favour solutions with lower environmental interferences than alternative solutions. This impression is very problematic considering that monitoring repeatedly shows that many environments are highly degraded and that degradation often increases over time. This shows that society-nature interactions in many cases are environmentally unsustainable and that the level of unsustainability may be increasing over time. A clear rationale therefore exists for developing and using absolute environmental sustainability indicators (AESI) that not only can identify the anthropogenic system with the lowest environmental interferences in a comparison of systems, but also can evaluate whether any of the compared systems can be considered environmentally sustainable, and if not, can quantify the decrease in environmental interferences required for environmental sustainability. The purpose of this PhD thesis is to improve AESI using life cycle assessment (LCA) and to deepen the understanding of drivers and obstacles for increasing the use of AESI in decision- support. The thesis summarizes in three core chapters the work of five peer reviewed scientific articles and one scientific viewpoint article. The first chapter is concerned with operationalizing the concept of carrying capacity as reference value of environmental sustainability in environmental indicators in general and in LCA indicators specifically. LCA is a tool that quantifies environmental stressors (resource use and emissions) occurring over the life cycles (“cradle to grave”) of anthropogenic systems and translates these stressors into metrics of environmental interferences for a number of mutually exclusive and collectively exhaustive “impact categories”, such as climate change, eutrophication and ecotoxicity. Carrying capacity is in this thesis defined as “the maximum sustained environmental interference a natural system can withstand without experiencing negative changes in structure or functioning that are difficult or impossible to revert.” In the design of AESI a choice needs to be made for each of 12 identified concerns. Existing AESI are found to be based on different choices for concerns, such as “threshold value”, “quantifying environmental interferences of studied system” and “modelling of carrying capacity.” This difference in choices across AESI can lead to high uncertainties in indicator scores, potentially 3 orders of magnitude, and should thus be reduced where possible. Existing AESI are also found to only partially cover all impact categories. LCA indicators can potentially contribute to increasing the coverage of impact categories in AESI and to reducing indicator uncertainties, due to the consistent choices made for LCA indicators for many of the 12 indicator concerns. LCA indicators are relative and must be modified with carrying capacity references to become AESI. This modification can either happen in the normalisation of indicator scores or by developing new characterisation factors (CFs) used to translate environmental stressors to metrics of environmental interferences in LCA. Operational global and European carrying capacity based normalisation references are developed for 11 LCA impact categories and can be used to translate indicator scores from metrics specific to each impact category (such as Global Warming Potential for the impact category climate change) to a common metric of carrying capacity occupation, expressed in person years. To improve the representation of spatial variations, a generic mathematical equation for integrating carrying capacity in CFs is developed. Such CFs express indicator scores as hectare years, i.e. occupation of carrying capacity integrated over space and time. CFs for the impact category terrestrial acidification are developed and show strong local and regional variations (e.g. ranging above a factor of 5 across contiguous United States). The high spatial variation is an argument for using carrying capacity modified CFs, as opposed to modified normalisation references, when the locations of stressors of a studied anthropogenic system are known. The second chapter is concerned with calculating carrying capacity entitlement of individual anthropogenic systems, with analysing the applicability of different valuation principles in calculating entitlements and with how sensitive calculated entitlements are to choice of valuation principle. Entitlements must be calculated to evaluate whether an anthropogenic system can be considered environmentally sustainable, which is the case when carrying capacity occupation does not exceed entitlement. Calculation of entitlement must consider the perceived value of a studied system relative to systems that compete for the same carrying capacity for their functioning. An ideal and a simplified method for identifying competing systems in a spatial assessment are outlined. A list of valuation principles is presented and includes contribution to Gross domestic product (GDP) and contribution to meeting human needs. The applicability of the valuation principles on different types of anthropogenic systems (territorial or lifecycle-based from micro- to macro scale) is analysed. Case studies are used to illustrate that the choice of valuation principle has a potentially large influence on the carrying capacity entitled to an anthropogenic system. The third chapter is concerned with characterising companies’ use of AESI in stakeholder communication and with how to increase this use. Companies have recently been encouraged by various initiatives to adopt AESI to define targets with deadlines for environmental sustainability at company level. A screening and context analysis of the largest global database of corporate responsibility reports found that only 23 out of 9,000 companies were following this advice. Explanations for the low share may be that the use of AESI is (still) not being sufficiently demanded by critical stakeholders and that operational AESI for impact categories other than climate change are either not available or not compatible with the tools with which companies express their environmental interferences. Two strategies for increasing the use of AESI by companies are proposed: 1) AESI based on LCA indicators should be further developed and made available to companies, since many companies already use LCA to reporting environmental interferences. 2) The awareness of AESI must be increased amongst critical stakeholders so that they can pressure companies to adopt AESI. Following the three core chapters, a final chapter with recommendations is provided. This chapter outlines future research needs on AESI related to indicator development and refinement, inventory data, social sustainability references and consensus needs. Practical measures for increasing the use of AESI in decision- making are also proposed.
    Original languageEnglish
    Place of PublicationLyngby
    PublisherDTU Management Engineering
    Number of pages366
    Publication statusPublished - 2015
    SeriesDTU Management Engineering. PhD thesis


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