Uncertainty in EIOLCA Hybrid LCA Models

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Uncertainty in EIO-LCA /Hybrid LCA Models
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Uncertainty in LCA

• Uncertainty exists for all LCA data mass flows,
  emissions, impacts, weights and change effects,
  e.g.
• Proprietary data problems
• Boundary problems Lenzen (2000, Journal
  Industrial Ecology) finds truncation errors on
  the order of 50 for Australian LCA. Similar to
  Hocking result.
• Measurement, transfer, change, etc.

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Uncertainty Implications

• Consistency and reproducibility of results (e.g.
  are paper or plastic cups superior).
• Certainty of conclusions and usefulness of LCA.
• Uncertainty for LCA studies in general obvious -
  we will focus on EIO-LCA
• Data problems, combining data problems,
  allocation..
• Numbers of significant digits how many digits
  appropriate for www.eiolca.net result?

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EIO-LCA Uncertainty Sources

• Survey Errors sampling and reporting errors
  depends on companies and census agencies.
• Old Data IO tables are typically 2 to 7 years
  old. Last US benchmark 1997 released 12/2002.
• Incomplete Data reports from only some sectors
  or plants (e.g. tri sector and threshold limits,
  holes in census surveys). Note similarity to
  boundary problem in conventional LCA!

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EIO-LCA Uncertainty (cont)

• Missing data Census data missing many topics,
  such as habitat destruction. Non-monetary
  inter-sector dependencies also not represented,
  e.g. congestion effects from truck services.
• Aggregation Sectors too large for detailed
  analysis on specific products. Problem sectors ?

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Uncertainty (cont.)

• Imports EIO treats imports as similar to
  domestic production.
• Model form Linearity of EIO, lack of
  substitution as scale economies change.
• Mapping and Allocation Problems
• Product Prices

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Uncertainty (Pacca 2003)
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Mitigating Factors and Approaches

• Parameter stability over time
• Positive Correlations
• More and better data
• Simulation analyses
• User adjustments

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Parameter Stability Over Time

• Requirements matrix relatively stable over time
• Using 1961 final demand from IO tables of 1939 to
  1961 found similar intermediate outputs (Carter,
  1970).
• Intermediate use relatively constant (Ma, 2003)
• Environmental impact vectors more dynamic.

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Intermediate Use 1972-1997
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Positive Correlations

• Deciding on the best of two designs may be more
  certain than overall impact due to positive
  correlations. The designs may share many
  elements in common, and these elements would be
  positively correlated. If the element is bad, it
  is bad for both. If good, it is good for both.
• Numerical analysis of effect Cano (2000).

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Difference of Correlated Variables

• Suppose impact of design a is X and impact of
  design b is Y. We are interested to know if X
  Y or X Y 0.
• EX-Y EX EY
• VX-Y VX VY 2 covX,Y correlation
  means variability is reduced.
• Ex X N(1,1), Y N(0,1), Cov (0.5), then EX-Y
  1, VX-Y 1, Pr(X-Y0) 0.84

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More and Better Data

• Mixed picture for more and better data.
• No water use data since 1980s in US.
• No workfiles for 1997 benchmark released.
• Better industrial environmental management
  systems to collect data.
• More international co-operation and public data
  international tri.

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User Adjustments

• Many adjustments possible due to known
  aggregation or emissions problems
• Hybrid models including EIO and process models.
• Parameter adjustments to reflect non-linearities.
• Disaggregating individual EIO sectors.
• Bayesian methods applicable here adjusting
  estimates based on expectations.
• Multiple approaches EIO-LCA and Conventional LCA.

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Advantages of Conventional LCA vs. EIO-LCA
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Disadvantages of Conventional LCA vs. EIO-LCA
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References

• Cano-Ruiz, Alexandro Jose, (2000). Decision
  Support Tools for Environmentally Conscious
  Chemical Process Design, unpublished PhD
  Dissertation, MIT.
• Lenzen, Manfred, (2000). Errors in Conventional
  and Input-Output-based Life-Cycle Inventories,
  J. of Industrial Ecology, 4(4), pp. 127-148.
• Pacca, S., (2003). Global Warming Effect Applied
  to Electricity Generation Technologies, PhD
  Thesis, UC Berkeley.

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Hybrid Life Cycle Assessment

• Combining process models and EIO-LCA

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Models of LCA

• Conventional LCA, developed by SETAC and EPA,
  based on process models
• Economic input-output analysis-based LCA
  (EIO-LCA), developed by Carnegie Mellons Green
  Design Initiative and Others
• Hybrid models
• Using eiolca model to guide boundary and scope of
  process models.
• Disaggregating or augmenting io model.
• Using eiolca for some processes, products and
  supply chain elements (where sector aggregation
  is not a major issue), with process models for
  remainder.

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Utility of Two LCA Approaches
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Goals of Hybrid LCA Models

• Incorporate the advantages of the two models,
  reduce disadvantages
• Include detailed, process-level data, as well as
  the economy-wide effects
• Provide environmental and economic information
  about every major product and process in the
  economy
• Quantify the widest range of environmental data
• Two obvious high level alternatives for hybrid
  models

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Integration of EIO-LCA Data into Conventional LCA
EIO-LCA
Process models
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Integration of Conventional LCA Data into EIO-LCA
EIO-LCA
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Economic and Environmental Implications of Online
Retailing and Centralized Stock Keeping in the
United States
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E-Commerce Retail Quarterly Volume (B)
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Traditional Retail Logistics System

• Factory to warehouse to warehouse to retailer.
• Last leg of trip by private vehicle

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Single Facility Sales

• LL Bean, Lands End - catalogue sales
• Amazon (original), MusicOutpost - web based sales
  from a single facility

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How to Model E-Commerce for LCA?
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Book Publishing Case Study

• Traditional System
• logistics printer warehouse warehouse
  retailer home, all by truck/car
• unsold returns - roughly 35 for bestsellers
• E-commerce System
• logistics printer warehouse distribution
  center home, by air and truck.
• No unsold returns

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Comparative Analysis is EIOLCA Sector Use

• Traditional
• truck transport (1000 mi)
• Warehousing
• production of returns
• reverse travel of returns
• private automobile transport

• E-Commerce
• air transport (500 mi)
• truck transport (500 mi)
• Warehousing

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Comparative Costs ( 1000s for 1 M or 290,000
books)
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Why are E-Commerce Costs Lower?

• Higher transportation costs for e-commerce, but
• Returns of unsold copies
• Lower retail transactions costs
• Lower (private) automobile cost
• Result is cost advantage for e-Commerce

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Summary Environmental Impacts(per-book basis)
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Sensitivity Analysis

• Traditional becomes better if
• Local distance to bookstore
• Air transport of books 700 miles
• Orders not shipped together
• Ecommerce better if
• Switch from Air transport
• Multiple origin sites
• Greater density of sales.

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Harry Potter Case

• 250,000 books shipped on release date by
  Amazon.com
• 9,000 trucks and 100 airplanes
• 2.5 lb. book, 0.7 lb. packaging (3.2 lbs.)
• Bookstores got 10 per box
• Shopping trips for books avg. 11 miles
• Marginal effects

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This is Research.
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Some Analysis Issues

• What are E-commerce future scenarios?
• What will happen with local manufacturing
  technology?
• What will be impact of new business models for
  controlling inventory (warehousing),
  manufacturing and shipping.
• What is appropriate time scale of analysis?

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Analysis Boundary Issues (cont.)

• Buildings - decrease in retail or warehouse
  space?
• Shopping - will individuals substitute other
  travel for reduced shopping travel?
• Computers - what fraction of personal computer
  burdens should be allocated to E-commerce?

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Will E-commerce Improve or Degrade the
Environment?

• Net Effect - hypothesis depends upon product and
  processes and upon the analysis boundary.
• Appropriate Public Policy -
• Dont ignore service industries in environmental
  policy.
• Consider life cycle costs including social costs.
• Take advantage of cost savings to create
  environmental benefits