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Acknowledgments

We would like to acknowledge the funding provided by the U.S. Department
of Energy, the General Services Administration, and the Naval Facilities
Engineering Command, which made this project possible. We would like to
thank Franklin Associates, Ltd. and Sylvatica Corporation for their
significant contributions to this report. We also want to acknowledge
the valuable contributions of the many volunteers who worked with us as
part of the project advisory group, all of whom are listed on the
project Web site and in the *U.S. LCI Database Project Phase I Final
Report*. We also want to thank Paul Torcellini and Michael Deru of the
National Renewable Energy Laboratory, for their advice, forbearance, and
support throughout the project. Finally, we thank Dr. Patrick
Hofstetter, who chaired the critical review team comprising of Gregory
Keoleian at the University of Michigan, John Sullivan at Ford Motor
Company, and Keith Weitz at Research Triangle Institute. All gave freely
of their time and provided a detailed and highly constructive review
report with specific recommendations that have vastly improved these
guidelines.

Table of Contents

[U.S. LCI Database Project Development Guidelines
1](#__RefHeading___Toc61773629)

[Phase I Final Version 1](#__RefHeading___Toc61773630)

[1 Introduction 1](#introduction)

[2 Goal and Scope Definition 2](#goal-and-scope-definition)

[2.1 Project Goal 2](#project-goal)

[2.2 Compliance with ISO 14041 3](#compliance-with-iso-14041)

[3 Boundaries 4](#boundaries)

[3.1 General Description 4](#general-description)

[3.2 Specific Boundaries 4](#specific-boundaries)

[3.3 Non-Domestic Production 5](#non-domestic-production)

[4 Unit-Process Data Development 5](#unit-process-data-development)

[5 Data Types 6](#data-types)

[5.1 Primary vs. Secondary 6](#primary-vs.-secondary)

[5.2 Units 6](#units)

[5.3 Technology 6](#technology)

[6 Elementary Flows 7](#elementary-flows)

[7 Exclusion of Small Amounts 7](#exclusion-of-small-amounts)

[8 Carbon Cycle 8](#carbon-cycle)

[9 Energy Resources Used as Material Inputs
8](#energy-resources-used-as-material-inputs)

[10 Common Energy and Transportation Modules
9](#common-energy-and-transportation-modules)

[11 Data Format and Communication 10](#data-format-and-communication)

[12 Transparency 11](#transparency)

[13 Data Quality and Uncertainty 13](#data-quality-and-uncertainty)

[14 Co-Product Allocation 15](#co-product-allocation)

[14.1 Allocation Involving Industrial Scrap or Wastes
16](#allocation-involving-industrial-scrap-or-wastes)

[15 Allocation for Reuse and Recycling
18](#allocation-for-reuse-and-recycling)

[15.1 Open-loop recycling 19](#open-loop-recycling)

[15.2 Closed-Loop Recycling 19](#closed-loop-recycling)

[16 Sensitivity Analysis 20](#sensitivity-analysis)

[17 Critical Review 20](#critical-review)

[Appendix A --- Conversion Factors A-1](#appendix-a-conversion-factors)

[Appendix B --- Guidelines for Applying Economic Allocation to
Multi-Product Unit Processes and Systems
B-1](#appendix-b-guidelines-for-applying-economic-allocation-to-multi-product-unit-processes-and-systems)

[]{#__RefHeading___Toc61773629 .anchor}U.S. LCI Database Project\
Development Guidelines[^1]

# Introduction

This report is intended as a guide for the development of life-cycle
inventory (LCI) database during Phase II of the U.S. Database
Project.[^2]

The ultimate objective of the project is to develop publicly available
LCI data modules for commonly used materials, products and processes.
The purpose is threefold: 1) to support public, private, and non-profit
sector efforts to develop product life-cycle assessments (LCAs) and
LCA-based decision support systems and tools; 2) to provide regional
benchmark data for generating or assessing company, plant, or new
technology data; 3) and to provide a firm foundation and broad data
resource base for conducting LCAs generally.

The project is intended to support the growing trend of taking a systems
view when evaluating the environmental performance of products and
services. However, tradeoffs are often encountered in systems analyses,
and database users might find it appropriate to choose a subsystem or
material that carries higher environmental burdens over alternatives
because it imparts an overall environmental performance improvement to
the product system under study. Providing sufficiently reliable
information to assess system environmental performance in the light of
tradeoffs is one of the prime reasons for developing such a database.

As discussed in the following section on goal and scope definition, the
U.S. Database Project differs from typical life-cycle assessments of
individual products, processes, or systems. Those differences affect
this document in certain fundamental ways that are made clear in various
sections of the guidelines. We especially have to anticipate a much
broader range of potential uses and users of the LCI data, with
attendant variety in the manner in which, and degree to which, the LCI
data will be used for full LCA purposes.

This document is intended for use by LCA practitioners or others who
will be directly involved in development of the LCI data modules, as
well as those interested in observing or reviewing the project. As a
result, we have assumed a basic level of understanding about LCA
principles and practices, including the International Organization for
Standardization (ISO) 14000 series of standards and technical reports,
and have not attempted to explain or justify all of the procedures or
guidelines.

The guidelines have been prepared as part of a broader Phase I
work-programming effort. The companion document, *Work Program for Phase
II*, as outlined in the *U.S. LCI Database Project Phase I Final
Report*, or *Phase I Final Report*, provides a list of the processes
recommended for study in Phase II, in priority order, as well as an
overview discussion of current data availability from the perspective of
this project. It also makes recommendations for further work that will
augment or supplement this report. In fact, as explained in that report,
the guidelines are a work in progress. This Phase I final version has
been modified to account for some, but not all, of the comments received
as a result of the formal review process. Further modification is
expected early in Phase II, but the guidelines should continue to evolve
as the science evolves and as lessons are learned during its
application.

An important task recommended in the *Work Program for Phase II* is the
development of a detailed data user's guide that will explain how
modules can be used in full LCAs (see Section 2: Goal and Scope
Definitions, below, for a description of the module concept). The user's
guide will contain example process trees and clear guidelines to ensure,
to the extent possible, that data users take full account of relevant
environmental effects without double counting, including during the use
phase of products. The user's guide will be particularly important with
regard to such difficult LCA steps as co-product allocation and
accounting for material recycling and reuse (see Section 14: Co-product
Allocation and Section 15: Allocation for Reuse and Recycling of these
guidelines).

# Goal and Scope Definition

## Project Goal

The basic goal of Phase II of the database project is to establish and
maintain LCI modules that can be readily accessed, combined, and
augmented to develop more complex LCIs or full LCAs.

The goal is not to carry out full product LCIs in this project, but
rather to make the creation of such LCIs easier, while reducing the
problem of data inconsistency and incompatibility that currently plagues
the LCA field in general. Accordingly, database modules will provide
data on many of the processes needed to conduct life-cycle analyses, but
will not contain data characterizing the full life cycles of specific
products. For example, LCI data on electricity generation,
transportation fuel use and emissions, and energy production and
pre-combustion, is required for virtually all LCAs, and will be provided
as a series of modules. Other modules could include mining and quarrying
activities, commodity metals production, the production of basic
building block petrochemicals, etc. Data documentation released by the
project must support the project goal.

It is also important to carefully distinguish the concept of [publicly
available data]{.underline} from the idea of data [for use by the
general public]{.underline}. While the data modules developed through
this project will be made publicly available, they will not be intended
for use by the general public in the way that full product LCIs might be
used. The modules will typically be used in combination with each other,
and with other data to be developed or provided by data users.

It is expected that users of the database are likely to include the
following groups:

-   Manufacturers, researchers, policy analysts, and others undertaking
    LCAs of specific products or processes;

-   Developers and users of tools for LCA practitioners;

-   Developers of tools for non-practitioners, which typically do not
    allow the user to modify embedded databases; and

-   Organizations or individuals engaged in product assessment and
    labeling at various levels of system complexity, from relatively
    simple consumer products to complex systems like buildings and
    automobiles.

Two common threads run through this list:

1.  An assumed level of knowledge and sophistication on the part of the
    anticipated users, and

2.  The fact that the database will provide a resource base for LCAs,
    rather than presenting completed cradle-to-grave LCA comparisons of
    individual product life cycles.

It is important to recognize that point 2, above, dictates adoption of
the highest feasible data development standards. Because we do not know
in advance precisely how or why individual database modules will be
used, this report assumes the most stringent requirements in terms of
data categories, transparency, review, and other factors that are
normally determined by the starting goal and scope statement of a study
as described in ISO 14041. In general, that means assuming the data will
be used in full LCAs for the purpose of making public comparative
assertions.

A critical proviso with regard to the use of the database modules is
that they will be developed principally for use in "attributional" LCAs,
which seek to establish the burdens associated with the production and
use of a product, or with a specific service or process, at a point in
time (typically in the recent past). The modules will not be developed
at the outset to serve the needs of those undertaking "consequential"
LCAs, which seek to identify the environmental consequences of a
decision or a proposed change in a system under study. Consequential
LCAs can impose different requirements from an LCI perspective (e.g.,
marginal electricity generation may be more appropriate for a
consequential LCA than average generation), and it is not clear at this
point that the data modules can be developed to serve both needs equally
well. We have therefore opted to focus first on the needs of
attributional studies, leaving the data requirements of consequential
studies for future assessment as the database evolves.

## Compliance with ISO 14041

This project intends to develop a database of LCI data modules that are
compliant with ISO 14041, and that help users conduct full LCAs that are
ISO 14041-compliant. If for any reason a study module cannot adhere to a
relevant requirement of ISO 14041, it will be incumbent on the analysts
first to obtain agreement from the project managers for any departure
and then to fully explain the departure, at least indicating the
directional effect(s) on the relevant unit processes.

Other aspects of the project scope are covered in the following sections
of these guidelines.

# Boundaries 

## General Description

Production systems generally consist of a combination of unit processes
(see Section 4: Unit-Process Data Development for a discussion of unit
process definition). In a full product LCI or LCA, the entire system
must be limited by an imaginary boundary that encompasses the full life
cycle and all of the essential operations for which information will be
collected.

This project, in contrast, will be providing basic LCI data modules
covering some, but not necessarily all, of the unit processes contained
within the boundary of a full product LCI or LCA. The boundaries for
each production module under study in this project will therefore be
separately and more narrowly determined on a case-by-case basis, with
some modules covering cradle-to-gate and some gate-to-gate processes.
For example, a module could be defined to include just the extraction
and crushing of limestone with boundaries that stop at the quarry or
crushing facility gate. Any more elaborate process that requires
limestone, like cement manufacturing, could then call on that module and
incorporate the LCI data for this common unit process.

By combining appropriate modules, it will be possible to construct the
cradle-to-gate systems necessary to reach predefined levels of
production for materials or products that have been studied. The
predefined level may in some cases be an intermediate product such as
steel reinforcing bar, and in other cases a final product like softwood
lumber.

Boundaries will also have to be established for generic transformation
unit processes included in the project. Transformations are defined as
typical manufacturing, finishing or end-of-life processes (e.g.,
extruding, stamping, painting, shredding and baling, and incineration)
that would be applicable to a wide range of full LCI/LCA studies of
specific products. This project will not include use and maintenance
phase activities other than those that might be covered by
transformation modules as defined above.

## Specific Boundaries

Data and estimates must be based on relevant, practical and appropriate
analysis boundaries. The boundaries may include activities such as the
following:

-   Acquisition, beneficiation, storage, and transfer of raw materials,
    including construction and earth-moving, which must be done to gain
    access to a raw material, and non-point emissions from these
    operations;

-   Acquisition, storage, and transfer of energy which will be
    calculated from a set of standard processes unless specific data is
    available for a unit process;

-   Processing of raw materials into primary products (e.g., steel,
    rolls of paperboard);

-   Transformation of primary products into secondary products (e.g.,
    steel joists, corrugated boxes);

-   Disposal, incineration, recovery of waste materials, and recycling
    and other end-of-life unit processes;

-   Transportation of materials, fuels and products at all stages; and

-   Allocated energy requirements of, and waste accumulation from,
    pollution control processes that are not an integral part of the
    industrial processes under study (e.g., a central waste water
    treatment plant).

The boundaries will not typically include the following activities,
depending on relative environmental significance per unit of production
(see Section 6: Elementary Flows and Section 7: Exclusion of Small
Amounts):

-   Construction of plants, vehicles, or other machinery used for any
    phase of production;

-   Maintenance and administration of plants or equipment; and

-   Transportation of people to work and related infrastructure costs.

One of the recommended Phase II tasks is the development of tests for
relevance that can be made available as an annex to these guidelines. In
the absence of such tests, the preceding items can be excluded with the
proviso that datasets may require subsequent modification to add missing
elements found to be more important than previously thought.

## Non-Domestic Production

Researchers will not be required to trace with primary data the full
energy and environmental costs of non-domestic production of raw
resources or components to the countries of origin. If data are
available for non-domestic processes for the region of interest, it will
be used with appropriate citations. In cases where region-appropriate
LCI data for non-domestic processes are unavailable from both primary
and secondary sources, the supply chain will be modeled using process
data characterizing U.S. production technologies. These data should then
be adapted where possible by using available information to characterize
key aspects of the non-domestic supply chain, such as transportation
distances, and fuels used to generate electricity.

Transportation energy and associated emissions will be included for
imports based on the actual location of production, hauling distances,
and typical modes of transportation.

# Unit-Process Data Development

Descriptions of industrial processes can be obtained and aggregated at
different levels of complexity and extent. ISO 14040 defines a unit
process as the "smallest portion of a product system for which data are
collected when performing a life-cycle assessment." Thus, if data (on
inventory flows, product flows, and inputs from other processes) are
collected at the level of a stamping press, then the stamping press is
by definition a unit process. If the same sorts of data are collected at
the level of entire factories, the factory level is then defined as a
unit process. A model of an entire supply chain will generally contain
data for unit processes at various physical scales.

For this project, the goal is to obtain data for unit-process modules
that represent subsets of an industry so that users of the data can
understand and combine various components of a product system and so
that critical reviewers can conduct technical analyses. Higher levels of
aggregation of data (e.g., defining a unit process to include more
activities) will result in a loss of information, reduce the level of
transparency, and inhibit critical review.

In addition, some components of a product system, such as limestone
quarrying, are used in many applications. Defining that type of activity
as a separate unit process will eliminate the need to conduct multiple
procurements of the same data. It will also prove useful to users
constructing many different LCI models.

# Data Types

## Primary vs. Secondary

There are numerous types of data that can be acquired for conducting LCI
studies, and it is important to distinguish between primary and
secondary data.

> [Primary data]{.underline} are those obtained from specific
> facilities.
>
> [Secondary data]{.underline} are those included in the product system
> life-cycle inventory that have been obtained from published sources.
> Examples of secondary data sources include published literature, other
> LCI studies, emissions permits, and general government statistics
> (e.g., mineral industry surveys, Bureau of Labor statistics, and
> Energy Information Administration data).

All data should be identified as being either primary or secondary as
part of routine data documentation. The most representative and reliable
data should always be used, with the proviso that critical reviewers
should be able to verify that the data is current and that it reasonably
represents relevant aspects of the unit process under study (see Section
12: Transparency).

## Units

All data should be presented in metric (SI) units. Where conversions are
required from imperial or U.S. units, the conversion factors provided in
Appendix A must be used and the conversion must be clearly identified in
the data documentation.

## Technology

The intent is to develop industry average data for the range of
technologies currently in use for specific unit processes. If more than
one technology is used in an industry, data should be collected for the
full technology range and then aggregated to produce weighted averages,
with the relative contribution to the market by each technology type
used as the weights (see also Section 13: Data Quality and Uncertainty).
Data by technology type should also be separately reported unless
confidentiality agreements with manufacturers prevent its disclosure.

# Elementary Flows 

The Tool for Reduction and Assessment of Chemical Impacts, or TRACI,
under development by the U.S. Environmental Protection Agency (EPA),
will be used in conjunction with other impact assessment methods to
determine impact assessment data requirements. The elementary flows
(environmental interventions) to be tracked will be, to the extent
possible or practical, those required to support characterization
measures in systems such as TRACI.

While it is important to gather all reasonably available resource use
and emission data and not unduly restrict data collection efforts, it is
also important to balance often conflicting criteria of practicality and
comprehensiveness. For example, characterization measures concerning
land use in TRACI and other methodologies have not yet been developed to
a level that would deem them to be "generally accepted". The significant
data requirements of those measures are therefore considered of lower
priority in this project, with a higher priority given to data required
to calculate global warming, acidification, eutrophication,
photochemical ozone creation, and ozone depletion measures. In addition,
any data should be reported that is required to be collected by
regulatory agencies and is available at a unit process level (e.g., EPA
criteria air pollutants and Toxic Release Inventory data).

Data collection should also include all significant raw resource
requirements and solid wastes, categorized as either hazardous or
non-hazardous.

Prior to Phase II data collection, an annex to these guidelines will be
issued with substance nomenclature and other specific data reporting
guidelines.

# Exclusion of Small Amounts

Within the defined boundary of a process, the level of detail of the
analysis should be sufficient to reveal all significant environmental
effects. Effort need not be spent on developing data for materials of
negligible significance.

The decision rules for this project are as follows:

-   Include all material inputs that have a cumulative total of at least
    95% of the inputs to the unit process, by mass;

-   Include all material inputs that have a cumulative total of at least
    95% of total energy inputs to the unit process; and

-   Include any material, no matter how small its mass or energy
    contribution, that has significant effects in its extraction,
    manufacture, use or disposal, is highly toxic, or is classed as
    hazardous waste.

The above percentages are intended as guides. Analysts are expected to
document the procedures and decisions per the requirements of Section
12: Transparency, including the justification for deviations from the
above guides.

# Carbon Cycle

The CO~2~ emissions generated by a system under study must be
documented, and several relevant aspects of the carbon cycle must be
distinguished:

-   Sequestration of carbon in biomass;

-   Emissions from combustion of fossil and biomass fuels;

-   Process emissions (e.g., decomposition of carbonate in a cement
    kiln);

-   Emissions from landfills or other end-of-life processes; and

-   Re-carbonization of products originally containing carbonates, such
    as concrete or limestone products.

Emissions from the combustion of fossil fuels will be captured in common
energy combustion modules (see Section 10: Common Energy and
Transportation Modules). In the case of biomass fuels, CO~2~ emissions
should be separately identified so that users of the data modules can
readily determine whether to include or exclude the emissions in
characterization measures.

Where data availability permits, unit process data should also
explicitly report sequestration of CO~2~ where relevant, so that users
of the data will be able to identify the net flux of CO~2~ to the
atmosphere that results from the entire sequence of unit processes in a
given life cycle.

In the case of end-of-life unit process modules, carbon releases (or
expected carbon releases), including releases in the form of methane,
should be separately identified to the extent possible, with full
documentation of any calculations or other rationale underlying
estimates of expected releases.

Re-carbonization of concrete or other products originally containing
carbonates is essentially a use-phase effect that will normally be
outside the scope of analysis for LCI modules developed in this project.
However, care must be taken in data presentation to alert data users to
take account of re-carbonization as appropriate (e.g., by clearly noting
that it has not yet been accounted for in process modules).

# Energy Resources Used as Material Inputs

The energy value of fossil fuels used as material feedstocks will be
included in the energy requirements for a unit process as if those
fossil fuels were burned as fuels. For example, hydrocarbons that are
used to manufacture plastics will have an energy value (often termed
"inherent energy" or "feedstock energy") reported even though they are
not burned. These values will be clearly marked and reported separately
from energy derived from fuel combustion, and will also be added as part
of aggregate energy use for a unit process.

The inherent or feedstock energy of biomass feedstocks will not be
included in aggregate energy use for a unit process because biomass is
not currently a significant source of energy in the United States. For
example, paper products are not derived from logs intended to be used
for direct combustion to produce energy, nor would the logs be harvested
for that purpose.

However, biomass such as logs used for paper production, may in the
future account for a larger percentage of the fuel supply through
conversion processes, to ethanol for example. As this practice becomes
more significant, feedstock energy values may have to be attributed as
fossil fuels. If so, the guidelines will be revised accordingly. Because
quantities of biomass used as material inputs will have been tracked in
LCI modules, it will make it possible to revise the calculations in the
future to include the appropriate feedstock energy values if warranted.
Where there is any question or doubt as to whether a specific feedstock
should be considered as a significant energy resource, the corresponding
feedstock values will be assigned and separately reported, but not
included in aggregated energy totals.

To the extent that biomass is burned for energy in a manufacturing
process, that energy will be reported as biomass energy and will be
included in aggregated energy totals.

# Common Energy and Transportation Modules

As discussed in the final *Work Program for Phase II* planning report,
the U.S. LCI database project will include separate data modules for
common electricity generation, energy combustion, energy pre-combustion
and transportation processes applicable to virtually all LCAs. It is
therefore critical that all other unit-process modules avoid double
counting by doing the following:

1.  Record electricity use in kilowatt hours and voltage (if available)
    at the point of use (e.g., with no adjustments for line losses),
    rather than in estimated amounts of primary energy used to generate
    electricity;

2.  Record energy use by fuel and equipment type (e.g., natural gas
    turbine), but not combustion emissions or pre-combustion effects
    unless there is data available that is specific to that unit
    process, in which case it must be clearly described; and

3.  Record tonne-kilometers of transportation by mode at all process
    stages, and identify if empty backhauls are typical for specific
    transportation links (e.g., hauling of aggregates from quarries),
    but not the actual energy use or effects of combustion.

The common energy and transportation modules will include at least the
following:

-   Process and transportation energy and process emissions for the
    production and processing of fuels including coal, natural gas, fuel
    oil (distillate and residual), gasoline, liquefied petroleum gas,
    fuel grade uranium, and emerging energy sources;

-   Total pre-combustion fuel use and fuel-related emissions for the
    production of the above fuels;

-   Pre-combustion and combustion energy factors for fuels (energy units
    per physical fuel unit);

-   Energy consumption for the generation and delivery of one composite
    kilowatt-hour of electricity for U.S. national and regional grids
    (pre-combustion and combustion energy in both fuel and energy
    units);

-   Transportation fuel requirements (in fuel units and energy per
    tonne-kilometer for various transportation modes, including
    pre-combustion and combustion energy); and

-   Environmental emissions (pre-combustion and combustion) per 1,000
    fuel units for the combustion of fuels used in the following:

-   Industrial and utility boilers

-   Industrial equipment

-   Various modes of transportation, including

    i.  Tractor-trailer trucks

    ii. Single unit trucks

    iii. Locomotives

    iv. Barges

    v.  Ocean freighters

    vi. Air cargo.

Users of the database modules will have to be advised that the
electricity grids used in an LCI should match the LCI's functional unit
and boundaries: where unit process data are available on a regional
basis, regional grids should be used; where unit-process data cannot be
related to specific regions, the national grid should be used; and, in
situations where electricity is an especially important issue and plant
locations are dictated by sources of electricity (e.g., electro-process
industries), specific industry data should be used. Both national and
regional electricity grids will be included in the electricity, fuels,
and energy database.

Note that fuel use for self-generated electricity should be included in
the process energy reported for a unit process.

# Data Format and Communication

The central data access objective of the U.S. LCI database project is to
make the data available for a variety of intended user groups in a
manner that will ensure an informative and time- and cost-efficient use
as possible (see Section 2.1: Project Goal). Data will therefore be
documented in accordance with the ISO 14048 documentation format, and
presented on a fully disaggregated unit-process basis.

Proprietary information provided on a confidential basis by individual
companies or plants will have to be protected. This need will
automatically be met in most cases by the normal process of combining
company-specific unit-process data across an industry, and reporting
aggregate data for each unit process ("horizontal aggregation"). In some
instances, for example if the sample of reporting companies is small, it
may be necessary to aggregate data for two or more unit processes which
occur in series before publishing the results in the database ("vertical
aggregation"). In extreme cases (e.g., when there is only one
manufacturer of a product and that manufacturer provides data under a
confidentiality agreement), it may be necessary to aggregate data for
one product with that for another similar product, thereby creating a
combined product class.

Because of the losses of information, transparency, and utility,
vertical aggregation should only be used when it is required to avoid
disclosure of competition-sensitive information.

When aggregation is necessary to protect any proprietary manufacturer
information, roll-up procedures must be clearly explained.

The project will also make unit-process "tree" models available to users
so that individual unit-process modules can be clearly understood within
the context of broader product process trees.

Transparency and longevity of the data will be further ensured by
maintaining a confidentially held copy of the original data that were
aggregated to produce the publicly released data. In this way, it will
always remain possible to re-evaluate and re-compute the modules in the
event that new guidance arises for procedures such as allocation, or
questions arise as to the basis for the aggregated data.

# Transparency

Transparency requires open access to all pertinent "data about the
data," or meta-data. Central transparency objectives of the U.S. LCI
database project are to develop and publish LCI data in a form that
provides enough information about the nature and sources of the data so
that users and third parties can do the following for each data item:

-   Know the source(s) and age of the data;

-   Know how well the data represents an industry or process;

-   Understand how the underlying calculations were made;

-   Evaluate the appropriateness of the data for the user's intended
    application;

-   Validate the results through testing and cross-checking of data and
    modeling; and, ultimately,

-   Make an informed determination concerning the extent to which they
    can rely on the data and conclusions drawn from it.

[Adequacy of Documentation]{.underline} will be ensured through the
following means:

-   Open publication of these guidelines governing how the databases are
    to be developed;

-   Adherence to guidance on the documentation from ISO 14040 and 14041;
    and

-   Use of the ISO 14048 Technical Specification "LCA Data Documentation
    Format" in documenting the unit-process data and system data.

All data developed in the U.S. LCI database project will be communicated
to third parties (e.g., other than the commissioner of the study and the
LCA practitioner). Data developers must therefore adhere to all
applicable elements of Section 6 of ISO 14040, which specifies the
required contents for such third-party reports. Life-cycle impact
analysis is an example of an element of ISO 14040 that is not applicable
since it is outside the scope of this project. The same is true of
documentation related to life-cycle interpretation, although in that
case documentation to meet the requirements of other elements should be
sufficient to enable users to assess the quality of the data. Key
elements of ISO 14041, which sets out more specific reporting
requirements, are listed in Table 1, with an indication of the approach
to be taken in project documentation.

Given the public nature of the U.S. LCI database and its availability
through the Web site, it will be essential to have a formal process for
changing data sets and for others to comment on, or challenge, data.
This matter is outside the scope of this report, but must certainly be
the subject of clear guidelines in the data user's guide and be
highlighted on the Web site.

**Table 1. Key elements of ISO 14041 with an indication of**

**the project documentation approach**

  ------------------------------------------------------- ---------------
  **Aspect for inclusion per ISO 14041**                  **Approach to
                                                          be taken**

  Section 5.3.3 on initial system boundaries states that  Systems *shall*
  "the system *should* be described in sufficient detail  be described in
  and clarity to allow another practitioner to duplicate  sufficient
  the inventory analysis."                                detail

  Section 5.3.5, on criteria for initial inclusion of     Full compliance
  inputs and outputs: "The criteria and the assumptions   in the context
  on which they are established *shall* be clearly        of the unit
  described. The potential effect of the criteria         process under
  selected on the outcome of the study *shall* also be    study
  assessed and described in the final report." And,       
  "Where the study is intended to support a comparative   
  assertion made to the public, the final sensitivity     
  analysis of the inputs and outputs data *shall* include 
  the mass, energy and environmental relevance criteria." 

  Section 6.3, on data collection: "A description of each Full compliance
  unit process *shall* be recorded. This involves the     
  quantitative and qualitative description of the inputs  
  and outputs needed to determine where the process       
  starts and ends, and the function of the unit process.  
  Where the unit process has multiple inputs... or        
  multiple outputs, data relevant for allocation          
  procedures *shall* be documented and recorded."         

  Section 6.4.5, on refining the system boundaries with   Full compliance
  sensitivity analysis to test significance: "The results where relevant
  of this refining process and the sensitivity analysis   
  *shall* be documented."                                 

  Section 6.5.2, on allocation principles: "The           Full compliance
  allocation procedure used for each unit process of      
  which the inputs and outputs are allocated *shall* be   
  documented and justified."                              
  ------------------------------------------------------- ---------------

# Data Quality and Uncertainty

The information about, and consequences of, uncertainty and data quality
in life-cycle inventory analysis operate at three levels:

1.  **Process Level:** First, there is the quality of, and uncertainty
    in, the data at the level of individual unit processes.

2.  **System Level:** Second, there are the total uncertainties in
    "rolled-up," cradle-to-gate aggregated life-cycle inventory results
    for a product or material; and

3.  **Application Level:** Third, in a given application, there is the
    additional layer of uncertainties (and their net effects) arising
    through mismatches between the subjects of the original LCI data and
    the actual unit processes or systems that they are being used to
    model.

The U.S. LCI database project will be consistent with ISO 14041 section
5.3.6. It must also take into account the need to protect
competition-sensitive information about the production methods or
economics of any single company. In most cases this will be addressed by
combining company-specific data across an industry, and reporting
aggregate data for each unit process.

The data formatting guidelines in ISO 14048 specify the following
minimum data quality documentation requirements for each unit process.
The required documentation will capture the information needed to
support subsequent analysis of the aggregated uncertainty of
cradle-to-gate data sets. The documentation will also allow users to
understand what the data represent and assess how well this correlates
with the intended use of the data.

The documentation requirements are as follows:

1.  For primary and secondary data:

    a.  Identification of age, source, method of collection (e.g.,
        measured, estimated from process engineering, etc.)

    b.  Identification of how representative the data are of an industry
        or process group (e.g., the percentage of total production
        represented by the sampled plants, rather than just "4 plants
        out of 20"). Also, documentation should make clear the nature of
        technology sampled (e.g., average, best-available, etc.) and the
        aggregation method used to produce the industry average data
        required in the data modules.

2.  Documentation of the methods used to estimate missing data or to
    justify excluding ancillary materials or missing data from the
    analysis. If sensitivity analysis is used, its results should be
    summarized; if surrogate data are used from other processes, these
    processes and their data sources should be clearly identified.

3.  Description of the aggregation approach used to protect
    competition-sensitive company-specific information (e.g., use of
    weighted averages, data for one product rolled in with that of a
    similar product, etc.).

4.  Explanation of all assumptions and calculation methods in sufficient
    detail that a reader or reviewer can duplicate basic calculations or
    evaluate sensitivity of results to key assumptions or methodological
    choices (e.g., for co-product allocation).

For each unit process, the following uncertainty documentation shall
also be provided:

1.  For primary data: All available information characterizing the
    uncertainty of the data, including but not limited to sample size,
    mean, minimum and maximum values, standard deviation, suggested best
    representative distribution shape, etc. OR,\
    if the sample size is small, an estimate of the uncertainty of the
    data (e.g., +/- 20%) based on sources or expert judgment, along with
    documentation of who provided the estimate and on what basis.

2.  For secondary data: All information available from the source that
    characterized the uncertainty of the data such as the information
    described above.

# Co-Product Allocation

There are cases where a unit process produces multiple outputs that are
considered by the producer to be primary products (as opposed to scrap
or waste). The problem for life cycle inventory (LCI) modeling is to
properly allocate elementary flows for that unit process among the
product outputs. For example, a forest products manufacturing plant may
convert wood into a number of products such as dimension lumber,
plywood, particle board and engineered lumber, as well as marketable
trim or scrap products such as side cuts, wood chips and sawdust. In
addition, some of the wood may be burned as an energy source. The
problem is to allocate raw materials, such as wood and energy, and
environmental releases to the various outputs.

General guidelines for doing this are provided by ISO documents.
Allocation procedures for this project will be in accordance with ISO
14041:1998(E), section 6.5.3, and 14049:2000(E), section 7.2.

ISO sets out a three-step hierarchy for allocation.

> **Step 1** is to *avoid* allocation altogether. When the "unit
> process" actually consists of multiple parallel sub-process chains,
> then using greater modeling detail may avoid the need for allocation.
> The second avoidance approach described by ISO is to expand the system
> model, effectively giving credit to the primary or "determining"
> product for other production displaced, or avoided, by the
> co-products. (See ISO/TR 14049:2000(E) for examples of the application
> of Step 1 procedures.) Wide variation in the LCI results can arise if
> there are multiple products with significantly different burdens that
> the co-product is displacing in the current situation or may displace
> in a future situation. Wide variation in the LCI results can also
> arise if there are multiple (and differently burdened) production
> paths for displaced products. Finally, significant extra data
> gathering and modeling is required if there are multiple displaced
> products and/or production routes, and if the data for these displaced
> products are not already available (e.g., within the US LCI database)
> We therefore recommend that system expansion be used only when there
> is a dominant, identifiable displaced product; and when there is a
> dominant, identifiable production path for the displaced product.
>
> **Step 2** is to study the system to determine how the elementary
> flows (i.e., the process inputs and releases) are changed by shifts in
> the co-product shares, and to then allocate the process elementary
> flows based on direct *physical relationships.* Alternatively,
> regression analysis may provide coefficients estimating burden per
> unit of each output. Either way, the resulting Step 2 allocation basis
> must (i.e., "shall") reflect the "underlying physical relationships"
> between the elementary flows and the output shares. The result of such
> system study or regression analysis may turn out to be equivalent to
> apportioning based on mass or some other physical characteristic of
> the product outputs, but ISO explicitly states that Step 2 is not the
> same as ***a priori*** apportioning of elementary flows to co-products
> according to their mass or molar shares. For example, in a sawmill,
> the energy allocation for sawing dimension lumber and side cuts could
> be studied by comparing examples where a larger or smaller fraction of
> the log goes to dimension lumber in search of an analytical basis for
> allocating energy to lumber. (See ISO/TR 14049:2000(E) for additional
> examples).
>
> **Step 3** is necessary if Steps 1 and 2 cannot be done. Step 3 is to
> use some *other relationship* between the elementary flows and the
> product output as a basis for allocation. Here, ISO identifies
> economic allocation as the first preference among Step 3 options, and
> use of the economic value shares among the product outputs is
> recommended where feasible.
>
> In summary, allocation practice should be carried out with the
> following guidelines:

1.  Be fully consistent with the ISO hierarchy among methods; avoid
    allocation if possible; use physical relationships that approximate
    the causal influence of output share variations upon elementary
    flows; or use other cause-approximating relationships.

2.  Be fully consistent with the ISO requirement to document the reasons
    for every choice of allocation method, and provide enough
    transparency to enable interested LCA practitioners to conduct their
    own tests of the sensitivity of results to the selection of
    different allocation approaches.

3.  Where possible, carry out sensitivity analyses to illustrate the
    variability in results for alternative allocation methods

## 14.1 Allocation Involving Industrial Scrap or Wastes {#allocation-involving-industrial-scrap-or-wastes .unnumbered}

In addition to a range of co-products, which are responsible for most of
the revenues received by a manufacturing facility, there may be a
variety of minor products, scrap, or wastes that have little or no
economic value. As an example, a plastics fabrication plant may produce
a significant amount of trim scrap and waste in addition to several
primary products. While the waste may bring in no revenues, the scrap
may have value and be carefully prepared for reuse or recycling, despite
the fact that it is not intentionally produced. In fact, the production
of such scrap will usually be minimized to the extent possible given the
nature of the process or technology. Nevertheless, a by-product of this
nature has some value and therefore may be legitimately allocated some
portion of the elementary flows associated with the production process.

**Waste.** For the purpose of this discussion, a waste is defined as a
product outflow that has no economic value to the producer, whether or
not it is subsequently used by another process. In the case of wastes,
which produce no revenue to the facility, and may result in costs for
collection and disposal, ISO 14041 is clear about their treatment when
it states that, "... it is necessary to identify the ratio between
co-products and waste since the inputs and outputs shall be allocated to
the co-products part only". In fact, any burdens associated with
disposal should also be allocated to the co-products. If a waste is
subsequently used in some other industry or process, that material can
then be brought into the new process free of any elementary flows
associated with its original production (but not free of flows
associated with the collection and processing to make the waste usable).
Multiple uses of recovered waste material are addressed through system
expansion, or open loop recycling. The points relevant to this project
are that (a) a product outflow is considered a waste if it has no
economic value to the producer, whether or not it is subsequently used
by another process; and (b) in keeping with ISO, no wastes shall have
the burdens of their producing process assigned to them.

**Scrap.** In the case of byproducts (which have some economic value
even though their production is minimized and possibly unintentional),
such as trim scrap that is sold and therefore generates revenues, the
allocation of LCI elementary flows is treated differently by different
practitioners. The different methodologies have differing implications
for the entities generating and using the scrap. The two extremes are:

-   Treat scrap as an intentionally produced co-product, with full
    allocation of elementary flows; or

-   Treat it as if it were a waste, with no allocation of elementary
    flows arising from its production. (Note that no allocation is
    necessary in the case of 'home scrap', which is used within the
    facility where it is produced. Such internal recycling simply
    reduces the need for purchased raw materials, and is reflected in
    the material input requirements for the unit process.)

The implications for both the producers and users of scrap materials
differ depending on the way the scrap is treated.

[Waste Method]{.underline} Under the waste method, the primary product
carries all of the LCI elementary flows, with the reduction in solid
waste assigned to the primary product as the only environmental
incentive for the producing facility to find or create markets for the
scrap. On the other hand, there is more incentive to recover materials
by potential secondary users, since it can come in "free" of all
upstream burdens for production.

[Co-Product Method]{.underline} When scrap is treated as a co-product,
the elementary flows that otherwise would have been allocated solely to
the primary product(s) are now allocated among the scrap and primary
product(s). This might encourage the producer to sell the scrap, rather
than having it discarded as waste, in order to reduce the elementary
flows allocated to the primary products. On the other hand, potential
users of recovered materials with allocated elementary flows may be
discouraged from doing so.

Given these alternatives and their implications, data developers may
want to carry out sensitivity analyses to determine the range of values
resulting from the different methods. However, the modular, generic
approach of the U.S. LCI Database Project does not support the provision
of ranges or alternative sets of results in the final posted
datasets.[^3] Subsequent versions of the database format may support
data quality ranges, but at this point, he project requires one uniform
approach.

In principle, by-products such as trim scrap could be subjected to the
full ISO hierarchy, as for any co-product. In practice, however, it is
unlikely that step 1 will apply or that a causal relationship will be
found to satisfy the Step 2 criteria. We therefore recommend the use of
economic allocation for by-products, as per Step 3, unless there is a
clear reason to undertake the additional analysis required for Steps 1
or 2 in the hierarchy. The ultimate rationale for applying a more
onerous Step 1 or Step 2 approach is a high probability that such an
approach will strike a better balance among the data criteria of
accuracy, intelligibility, persuasiveness/credibility to users, and
affordability (in time and money terms).

If a revenue-producing output is treated as a by-product, with
application of the above streamlined approach, the data submitter must
demonstrate or attest to the fact that it meets the following criteria:

1.  It must account for no more than 5% (10%?) of total revenues[^4];

2.  It must be an unintentional, or even undesirable, output of the
    process; and

Its production is minimized (if production would be increased to
increase revenues, then the output in question is automatically deemed
to be a co-product).

# Allocation for Reuse and Recycling

The approach to modeling unit processes associated with waste management
and recycling in the U.S. LCI database project shall fully conform to
the ISO 14041 standard, also illustrated in ISO Technical Report 14049
("Examples of application of ISO 14041"). In particular, the approaches
to handling allocation associated with recycling will follow the methods
outlined in section 6.5.4 of ISO 14041, Allocation Procedures for Reuse
and Recycling.

The standards cited above pertain to full attributional (as opposed to
consequential) life-cycle assessments, and to system models that include
either a closed-loop chain of processes or an open-loop system requiring
estimation of the number of total life cycles that will occur after the
primary product usage phase. In contrast, the U.S. LCI database project
is providing unit process LCI results for systems that do not include
the usage phase of product lives. As a result, the database project will
not include entire closed loops around the usage phase, with
post-consumer resource recovery, processing, and subsequent displacement
of virgin material (as described, for example, in Figures 14-17 of ISO
14049). Instead, the database must do the following:

-   Provide data that can be used as part of total life-cycle assessment
    models that are constructed in an ISO-compliant manner;

-   Capture, and provide users with, information about the shares of
    recycled content used as inputs to production in current practice;

-   Enable users to analyze life-cycle scenarios with various levels of
    post-consumer recovery and recycling; and

-   Enable users to analyze product systems involving alternative
    scenarios regarding shares of recycled content used as inputs to
    production.

## Open-loop recycling

ISO 14041 specifies that changes in the inherent properties of materials
shall be taken into account, and that open loop allocation procedures
and modeling be applied when recycled material undergoes changes to its
inherent properties, as shown in Figure 4 of 14041. Specifically, ISO
calls for open loop modeling of the recycling of property-changing
materials, and closed-loop allocation procedures for other materials
whose inherent properties are not changed by recycling, whether they are
in fact recycled in the same or a different product system.

For materials whose inherent properties change as a result of recycling,
the U.S. LCI database shall model the input of recovered materials to
processes as follows.

1)  The original production of the recovered product shall be modeled
    using LCI data for a representative or typical product actually
    found entering the material recovery stream of interest, based on
    current U.S. conditions.

2)  The burden of the initial production of the recovered product (e.g.,
    virgin content) shall be allocated among its initial and current
    uses. Where evidence supports the conclusion that there is already a
    high proportion of recycled content in the recovered material, the
    allocation factor should reflect the average number of previous
    uses.

3)  Where reliable data does not exist to support such a calculation,
    the analysis will assume there has been no previous recycling and
    half the burdens of the initial production shall be allocated to the
    material entering the reprocessing stream.\
    \
    In 2) or 3), above, use-phase-related burdens in the initial or
    subsequent product lives should not be allocated to the
    post-consumer material. However, the full system of processes
    required for recovery and recycling shall be included in the model
    for the recovered material, with 100% of the burdens assigned to the
    current use.

4)  Any recycling or potential for recycling beyond the unit processes
    under study in the project will be the responsibility of users of
    the U.S. LCI database. Suitable guidelines will be provided in the
    separate data user's guide.

##  Closed-Loop Recycling

For recovered materials whose inherent properties do not change as a
result of recycling, the U.S. LCI database models shall show input of
the required amount of recovered material, free of any burdens
associated with its original production, into the full series of
processes required to collect and reprocess the material for input into
manufacturing. If recovered material goes back into manufacture of the
same product, it will be assumed that the inherent properties have not
changed.

Again, the user's guide will provide instruction on the modeling of
recovered materials in this category through subsequent post-consumer
recycling phases.

# Sensitivity Analysis

Sensitivity analysis is used during database development, and it may
also be undertaken later by individual users of the data. For example,
sensitivity analysis may be used in the following instances:

-   During database development to determine whether results are
    sensitive to missing data, based on tests with proxy data; and

-   During data use to analyze the effect of different methods for
    co-product allocation, or to compare specific situations to industry
    averages.

One of the principal advantages of collecting, reporting, and
documenting data at the unit-process level is that it enables users to
undertake this latter form of sensitivity analysis.

When setting the input boundaries for a system and considering the
exclusion of materials that contribute small amounts to the total mass
of the system, or exclusion of missing data, sensitivity analysis shall
be employed to evaluate the environmental significance of the
potentially excluded data. For these cases, surrogate or estimated data
can be used to represent these materials in an initial analysis of the
system, and the potential contributions to system totals from these
materials can be evaluated. The cut-off criteria for excluding materials
from the system boundaries were defined in Section 7: Exclusion of Small
Amounts.

The data documentation required in Section 12: Transparency will provide
information on the data quality, modeling assumptions, and
methodological choices used to develop each unit-process data set. This
documentation should be sufficient to allow the user to understand key
assumptions that were made and to undertake sensitivity analyses of
influential assumptions. For example, a user may wish to examine the
effect on results of various methodological approaches for co-product
allocation in a unit process. The unit-process level of data detail will
also enable many other forms of user-based sensitivity analysis, such as
evaluating the influence of use of a specific supplier (for which the
user has data) compared with the industry average.

# Critical Review

It is important that unit-process data be evaluated by internal and
external experts, and compared with available published data, to ensure
uniformity of approach and consistency with international work. Given a
reasonable allowance for small errors and variations of method, any data
that appears inconsistent with published data should be referred to an
appropriately constituted review panel for judgment. However, this kind
of critical review will not be the direct responsibility of the data
developers working on individual U.S. LCI database modules. Critical
review will be the responsibility of the agency making the data publicly
available, and separate review guidelines should be issued by that
agency.

# Appendix A --- Conversion Factors {#appendix-a-conversion-factors .unnumbered}

**Volume and Mass**

  -------------- --------- ----------- ------------ --------- ------------- ------------ ------------
  **VOLUME**     **cubic   **ml**      **Liters**   **U.S.    **U.S.        **U.S.       **cubic
                 inch**                             fl. oz.** gallons\***   barrels**    feet**

  **cubic inch** x         16.387      0.0164       0.554     4.329x10-3    1.374x10-4   5.787x10-4

  **ml**         0.0610    x           0.001        0.03381   2.642x10-4    8.387x10-6   3.532x10-5

  **liters**     61.024    1000        X            33.815    0.264         8.387x10-3   0.0353

  **U.S. fl.     1.805     29.573      0.0296       x         7.812x10-3    2.48x10-4    1.044x10-3
  oz.**                                                                                  

  **U.S.         231       3785        3.785        128       x             0.0317       0.134
  gallons\***                                                                            

  **U.S.         7276.5    1.192x105   119.237      4032.0    31.5          x            4.21
  barrels**                                                                              

  **cubic feet** 1728      2.832x104   28.316       957.568   7.481         0.2374       x
  -------------- --------- ----------- ------------ --------- ------------- ------------ ------------

  ---------------- ----------- --------------- ------------ ------------ ------------ ------------ ----------------
  **MASS**         **grams**   **kilograms**   **Ounces**   **pounds**   **grains**   **tons**     **milligrams**

  **grams**        X           0.001           3.527x10-2   2.205x10-3   15.432       1.102x10-6   1000

  **kilograms**    1000        x               35.274       2.205        15432        1.102x10-3   1x106

  **ounces**       28.350      0.28            X            0.0625       437.5        3.125x10-5   2.835x104

  **pounds**       453.59      0.453           16.0         x            7000         5.0x10-4     4.536x105

  **grains**       0.065       6.480x10-5      2.286x10-3   1.429x10-4   x            7.142x10-8   64.799

  **tons**         9.072x105   907.19          3.200x104    2000         1.4x107      x            9.072x108

  **milligrams**   0.001       1x10-4          3.527x10-5   2.205x10-6   0.0154       1.102x10-9   x
  ---------------- ----------- --------------- ------------ ------------ ------------ ------------ ----------------

**\*NOTE:** U.S. gallon = 0.80 Imperial gallons (Source: U.S. National
Technical Information Services)

  -------------------------- ----------------------- --------------------
  **To convert from**        **to**                  **multiply by**

  Grams / cu ft              Milligrams / cu m       35.315x 103

  Pounds / 1000 cu ft        Milligrams / cu m       16.018 x 103

  Barrels Imp (petroleum)    liters                  158.98

  Btu\'s                     joules                  1054

  Cubic yards                liters                  764.534

  Feet                       meters                  0.305

  Gallons (British)          liters                  4.546

  Gallons (U. S.)            liters                  3.785

  Inches (in)                meters                  0.025

  Kilowatt - hours (kWh)     Mega joules             3.6

  Miles (statute)            kilometers              1.609

  Ounces (avdp)              kilograms               0.028

  Pounds                     kilograms               0.454

  Square feet                square meters           0.093

  Tons (short)               kilograms               907.185

  Watts                      joules / sec            1

  Yards                      meters                  0.914

  Pounds                     metric ton              0.0004

  Acres                      hectares                0.405

  Square miles               hectares                259

  Cubic feet (ft3)           cubic meters (m3)       0.028

  Cubic inches (in3)         cubic centimeters (cm3) 16.393

  Watt - sec                 joule                   1

  Calories (cal)             joules                  4.105

  Gram - calorie             joules                  4.184

  Watt - years               joules                  3.15 x 107
  -------------------------- ----------------------- --------------------

> **Sources:** 1. Starr, C. *Energy & Power*. Scientific American ,
> 1971; 2. Handbook of Industrial Energy Analysis.

# Appendix B --- Guidelines for Applying Economic Allocation to Multi-Product Unit Processes and Systems {#appendix-b-guidelines-for-applying-economic-allocation-to-multi-product-unit-processes-and-systems .unnumbered}

# Introduction {#introduction-1 .unnumbered}

This guideline on economic allocation has been prepared as an Annex to
the US LCI Database Project: Database Development Guidelines (January,
2001). The Annex supplements Section 14 of the Guidelines, which deals
with co-product allocation methods.

There are cases when a system or unit process produces multiple outputs.
The problem faced by LCI practitioners is to appropriately allocate
elementary flows across the multiple outputs of that system or unit
process. ISO 14041 sets out a three step procedural hierarchy for first
avoiding and then, if necessary, applying allocation methods. Economic
allocation fits in the final or third step in the hierarchy, and should
only be applied after it has been determined that steps one and two
cannot be satisfied or for some reason do not apply.

This guideline takes a pragmatic approach to applying economic
allocation rather than adding extensive new meta-data requirements in
the completion of an LCI. The document entitled *Life Cycle Assessment,
An Operational Guide to the ISO Standards*, prepared by CML at Leiden
University in May 2001, served as the primary reference in the
preparation of this guideline. For those interested in a more extensive
treatment and discussion of this subject area we recommend visiting
CML's website at \<leidenuniv.nl/cml/lca2/html/index\> to review the
Guide.

# Method {#method .unnumbered}

## *Economic Value Share Approach* {#economic-value-share-approach .unnumbered}

The fundamental underpinning of economic allocation methods assumes a
firm's goal is to maximize total revenue from the sale of
co-products.[^5] Each product's share of total revenues in a given time
period may then be used as a basis for allocating all elementary flows
among the various products of the unit process or system of interest.
This is not meant to imply that there is a direct relationship between
the amounts of elementary flows and relative co-product revenue streams.
While such a relationship may exist to some extent as a result of a
firm's efforts to optimize co-product outputs and maximize profits
(assuming that changes in co-product output levels result in changes in
elementary flows), the sole purpose of an economic allocation is to
allocate the estimated elementary flows. It is also important to
underscore the fact that economic allocation is based on relative
revenues (i.e., price x quantity), not just prices.

For example, in the figure below, the allocation factor (AF~1~) for
product one is calculated as the ratio of the revenues (R~1~) from sales
of product one to the total revenues from the sale of all *n* products
of the multi-product system or unit process (R~1~ + R~2~ + ... + R~n~).
Therefore:

$\text{AF}_{i} = \frac{R_{i}}{R_{1} + R_{2} + \text{.}\text{.}\text{.} + R_{n}}$
(1)

Elementary Flows in (EF~in~) Elementary Flows out (EF~out~)

P~1~ P~2~ P~3~

The fractional result AF~1~ represents product one's allocated share of
all elementary flows in and out of the multiple product system.

When applying this method at the level of *a firm* all product prices
used to derive the allocation factors must be for the same base year as
the unit process inventory data (elementary flows), and preferably
should be FOB (free on board) prices; i.e., prices at the plant gate.

When applying this method at the level of *an industry* all product
prices used to derive the allocation factors must be based on average
prices for the three-year period either immediately preceding or
including the base year for the inventory data. Again, FOB prices are
preferred.

All prices used when applying this procedure should be documented in the
data sheets for the unit process or system in question. The intent of
this reporting requirement is to provide sufficient information to allow
a third party to replicate the results of the allocation procedure, or
to dismantle the allocation and conduct sensitivity analysis using other
allocation methods.

## *Intermediate Product and Missing Price Allocation Factor Development* {#intermediate-product-and-missing-price-allocation-factor-development .unnumbered}

In many cases the unit process of interest may be at a more detailed
level than that of the firm or plant, and revenue shares by product may
not be known for a variety of reasons (e.g., missing price information,
product prices may only be known further downstream, etc.) In these
instances, economic allocation factors can be derived using a gross
sales value method in combination with cost information for the firm.

The following example illustrates the approach. The figure depicts a
multi-product unit process (A) producing two intermediate products
(P~1~^\*^ and P~2~^\*^), for which no market prices are available. Both
intermediate products (P~1~^\*^ and P~2~^\*^) then undergo separate
downstream processing (B and C) before being sold at discernable market
prices.

Elementary Flows in (EFA~in~) Elementary Flows out (EFA~out~)

EFB~in~ P~1~^\*^ P~2~^\*^ EFC~in~

The problem is to allocate the elementary flows of the multi-product
unit process (A) between the two intermediate products. That, in turn,
requires a determination of revenue shares attributable to P~1~^\*^ and
P~2~^\*^.

The method used for this purpose is the gross sales value method. The
gross sales value method starts at the process where the revenues for
each product are known (P~1~ and P~2~ in the schematic above) and then
moves upstream within the firm's process hierarchy until the multiple
product process (A) is encountered. The missing data on revenues is
estimated as the difference between the observable revenues from the
final product and all costs of production from the intermediate to the
final product. The adjusted revenue R~1~^\*^ for product P~1~^\*^
produced by multiple product process (A) is calculated as:

R~1~^\*^ = R~1~- TC~B~ / TC~A+B+C~ where:

R~1~^\*^ is the adjusted revenue for product 1

R~1~ is the total revenue (proceeds) value for product 1

TC~B~ is the total downstream cost associated with processing P~1~ after
leaving the

multiple product process in question

TC~A+B+C~ is the total cost associated with the multiple product process
in question,

plus all downstream unit process costs for the intermediate products in
question

(e.g., P~1~^\*^ and P~2~^\*^)

The results from this calculation may then be used to calculate the
revenue shares among the outputs of Process A, using equation 1.

[^1]: Formerly the U.S. LCI Database Project Research Protocol

[^2]: LCI Database Project available at: <http://www.nrel.gov/lci>

[^3]: Sensitivity results, ranges and optional data sets corresponding
    to different approaches are more feasible for client- or
    product-specific studies. In the case of generic LCI data modules,
    which may be rolled up and separately presented at an aggregated
    level for a specific product, or may be used as input datasets for a
    product LCA, the use of ranges or alternatives could results in an
    unmanageable proliferation of cases.

[^4]: This relatively high percentage is used in recognition of the
    overall level of uncertainty inherent in LCI data.

[^5]: Profit maximization is more likely to be a firm's true objective.
    However, data on profits margins is usually difficult to acquire,
    whereas total revenue estimates can be generated more readily from
    publicly available price and volume data. Economic allocation
    methods therefore use the contribution to total revenues as a proxy
    for contributions to total profit, implicitly assuming that profit
    from each product is proportional to its share of total revenues.