Moving from completing system boundaries to more realistic modeling of the economy in life cycle assessment
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Existing process-based life cycle assessment (LCA) models can be supplemented by input-output (IO) models to correct for the so-called truncation error resulting from an “incomplete” system boundary. The resulting hybrid LCA is not necessarily but probably a closer approximation to an ideally complete process model with a global all-inclusive system boundary. Here, we discuss whether such a complete process model is a goal worth pursuing and whether system boundary is the main limitation of process-based LCA.
We argue that the results of the ideally complete process model, with every single economic activity on earth embodied within, have little to limited implications and relevance for the decisions which LCA seeks to support and which involve changes aimed at reducing environmental impacts through altering product systems or promoting alternatives. The main limitations of process-based LCA, as a supply chain based linear model, lie not in the “incomplete” system boundary but in the narrow focus on supply chain and the unrealistic assumptions, such as omission of price effects and constraints. These assumptions reflect poorly how the economy works. Hybrid LCA, through adding IO models, which are also supply chain and linearity based, doubles down on both the narrow focus on supply chain and the unrealistic assumptions, and thus is a step forward but in the wrong direction.
Results and discussion
Reflecting on advances in corn ethanol research, we show that pursuing a more complete system boundary by, for instance, covering Chinese stuffed animal production does not make the LCA results more accurate or relevant for determining if corn ethanol in the US should be promoted. Not only is the theoretical argument for including Chinese stuffed animal industry tenuous, but there is no evidence it has been affected by US corn ethanol expansion. And by worrying about processes far away up the supply chain could distract us from focusing on the actual market mechanisms, such as indirect land use change, that are more likely to occur and are essential to predicting whether promoting corn ethanol would reduce total carbon emissions.
We suggest future studies shifting focus from “completing” system boundary within the conventional supply chain and linear framework towards more realistic modeling of our complicated human-environment system. Instead of trying to always include everything, we argue for a flexible and market-based system boundary tailored to the decision in question, particularly considering the scale of potential changes it may cause and how it may affect the economy. A change at larger scales is likely to have a broader impact, thus justifying the definition of a broader system boundary. But to cover a broad system boundary for a small change will likely result in overestimates. More is not necessarily better.
KeywordsHybrid life cycle assessment Consequential System boundary Marginal changes
- Dervis K, Dervis K (1982) General equilibrium models for development policy. Cambridge University Press, Cambridge, p 512Google Scholar
- Dixon PB, Jorgenson DW (2012) Handbook of computable general equilibrium modeling. Newnes, OxfordGoogle Scholar
- Elliott J, Deryng D, Müller C, Frieler K, Konzmann M, Gerten D, Glotter M, Flörke M, Wada Y, Best N, Eisner S, Fekete BM, Folberth C, Foster I, Gosling SN, Haddeland I, Khabarov N, Ludwig F, Masaki Y, Olin S, Rosenzweig C, Ruane AC, Satoh Y, Schmid E, Stacke T, Tang Q, Wisser D (2014) Constraints and potentials of future irrigation water availability on agricultural production under climate change. Proc Natl Acad Sci 111:3239–3244CrossRefGoogle Scholar
- FAO (2011) Global food loses and food waste—extent, causes, and prevention. Food and Agriculture Organization of the United Nations, RomeGoogle Scholar
- Gibon T, Schaubroeck T (2017) Lifting the fog on characteristics and limitations of hybrid LCA—a reply to “Does hybrid LCA with a complete system boundary yield adequate results for product promotion?” by Yi Yang. Int J Life Cycle Assess 22(3):456–406. https://doi.org/10.1007/s11367-016-1256-9 Int J Life Cycle Assess 22:1005–1008CrossRefGoogle Scholar
- Heijungs R (2012) Spatial differentiation, GIS-based regionalization, hyperregionalization and the boundaries of LCA. In: Ioppolo G (ed) Environment and energy. Milano, Italy, pp 165–176Google Scholar
- ISO (2006) ISO 14040: environmental management-life cycle assessment-principles and framework. International Organization for Standardization, GenevaGoogle Scholar
- Lundie S, Ciroth A, Huppes G (2007) Inventory methods in LCA: towards consistency and improvement. Final Rep UNEP-SETAC Life Cycle Initiat Life Cycle Inventory LCI Programme Taskforce 3:Google Scholar
- Mirza M (2008) Economic impact of airplane turn-times. AERO Mag Q408Google Scholar
- Stiglitz J (2018) Where modern macroeconomics went wrong. Oxf Rev Econ Policy 34:70–106Google Scholar
- Ten Raa T (2006) The economics of input-output analysis. Cambridge University Press, LondonGoogle Scholar
- Thirlwall AP (1983) Input-output analysis. In: Growth and development with special reference to developing economies. Palgrave, London, pp 231–248Google Scholar
- Wallander S, Claassen R, Nickerson C (2011) The ethanol decade: an expansion of US corn production, 2000–09. US Department of Agriculture, Economic Research Service, Washington DCGoogle Scholar
- Weidema PB (2003) Market information in life cycle assessment. Danish Environmental Protection Agency, CopenhagenGoogle Scholar