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Life Cycle Emission Distributions Within the Economy: Implications for Life Cycle Impact Assessment

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  • Gregory A. Norris

Abstract

Refinements of methods for life cycle impact assessment (LCIA) are directed at removing unjustified simplifications and quantifying and reducing uncertainties in results. The amount of uncertainty reduction that is actually achieved through LCIA method refinement depends on the structure of the life cycle inventory model. We investigate the general structure of inventory models using an economic input/output (I/O) life cycle assessment model of the U.S. economy. In particular, we study the results of applying a streamlining algorithm to the I/O LCA model. The streamlining algorithm retains only those “branches” of the process tree that are jointly required to account for a specified fraction of the total impacts upstream of each point in the tree. We examine the implications of these “tree pruning” results for site‐informed LCIA. Percentiles are presented for U.S. commodities and several important pollutants, for the share of total upstream emissions contributed by the set of processes in each supply tier, that is, each set of processes that directly supply inputs to another set of processes. Capturing at least 90% of the total direct plus upstream emissions for criteria air pollutants and toxic releases for at least 75% of the commodities in the U.S. economy requires full modeling of direct emissions plus the first five supply tiers. The requirements for capturing a high percentage (e.g., > 80%) of total emissions vary widely across products or commodities. To capture more than 60% of total emissions for more than half of all commodities requires models with more than 4,000 process instances. To well characterize the total impacts of products, life cycle impact assessment methods must characterize foreground process impacts in a site‐informed way and mean impacts of far‐removed processes in an unbiased way.

Suggested Citation

  • Gregory A. Norris, 2002. "Life Cycle Emission Distributions Within the Economy: Implications for Life Cycle Impact Assessment," Risk Analysis, John Wiley & Sons, vol. 22(5), pages 919-930, October.
    • Handle: RePEc:wly:riskan:v:22:y:2002:i:5:p:919-930
    DOI: 10.1111/1539-6924.00261
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    References listed on IDEAS

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    1. Satish Joshi, 1999. "Product Environmental Life‐Cycle Assessment Using Input‐Output Techniques," Journal of Industrial Ecology, Yale University, vol. 3(2‐3), pages 95-120, April.
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    1. Hauke Ward & Leonie Wenz & Jan C. Steckel & Jan C. Minx, 2018. "Truncation Error Estimates in Process Life Cycle Assessment Using Input‐Output Analysis," Journal of Industrial Ecology, Yale University, vol. 22(5), pages 1080-1091, October.
    2. Hanbury, O. & Vasquez, V.R., 2018. "Life cycle analysis of geothermal energy for power and transportation: A stochastic approach," Renewable Energy, Elsevier, vol. 115(C), pages 371-381.
    3. Maxime Agez & Guillaume Majeau‐Bettez & Manuele Margni & Anders H. Strømman & Réjean Samson, 2020. "Lifting the veil on the correction of double counting incidents in hybrid life cycle assessment," Journal of Industrial Ecology, Yale University, vol. 24(3), pages 517-533, June.
    4. Glen Peters & Edgar Hertwich, 2006. "Structural analysis of international trade: Environmental impacts of Norway," Economic Systems Research, Taylor & Francis Journals, vol. 18(2), pages 155-181.

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