TFI Technical Bulletin 1

Use of Facility–Specific Data in National Greenhouse
Gas Inventories"Supporting material prepared for consideration by the Intergovernmental Panel on Climate Change. This supporting material has notbeen subject to formal IPCC review processes.”

Introduction
The 2006 IPCC Guidelines for National Greenhouse Gas
Inventories give users methods for estimating emissions frommost sources of emissions and removals by sinks. While they
allow the use of detailed plant-specific data where this is available,
they provide few details on the practical considerations to guideinventory compilers. The Guidelines provide general principles on
including plant-specific data but not detailed guidance. With thedevelopment of plant and facility reporting systems in a number ofdifferent countries and regions, interest is growing in the use ofthis data. This Technical Bulletin is intended to explain theapplication of the IPCC Guidelines for National Greenhouse Gas
Inventories in the light of users’ experiences, and to provide
inventory compilers practical approaches they may wish to adopt.
This Technical Bulletin does not alter or add to the Guidelines
themselves.
This Technical Bulletin is an output from an expert meeting
convened by the IPCC’s Task Force on National Greenhouse
Gas Inventories (TFI) on this issue in Wellington, New Zealand,
18th-20th July 2011. This document has been reviewed by theparticipants and the Bureau of the TFI; however it has not been
subject to the formal IPCC review and approval process and istherefore IPCC Supporting Material prepared for consideration by
the Intergovernmental Panel on Climate Change.
This document should help to inventory compilers using either the
Revised 1996 Guidelines for National Greenhouse Gas
Inventories (IPCC 1997) or the 2006 IPCC Guidelines for National
Greenhouse Gas Inventories (IPCC 2006). The Revised 1996
Guidelines were supplemented by two sets of Good PracticeGuidance (IPCC 2000; IPCC 2003), and the Good PracticeGuidance was incorporated into the main body of the 2006
Guidelines. In either case, Good Practice Guidance (GPG) is
intended to provide a way to ensure that inventories are as
unbiased, and as precise, as possible, within available resources.
This document follows GPG.
Users of plant or facility level data will need to consider thisdocument in light of their specific situation. Such data will come inmany different forms and so the discussion here must remain
fairly general.
There are a number of key issues that have been identified andare discussed in the following chapters:Ensuring data is of sufficient qualityConsistency with definitions

Estimating uncertainties

Consistent use of data

Dealing with incomplete coverage and time seriesconsistency

Facility level data is information related to emissions from anindividual plant, installation or factory. It can come in a number offorms:
Measurement data. Emissions can be measured directly (e.g.
stack measurements) or indirectly (e.g. fuel carbon contents
leading to CO2 estimates). Measurements may be continuous(e.g. CEMS) or periodic, leading to plant specific emission factors.
Plant-Specific activity data may also be available. This isparticularly useful where plant can be stratified into different
groups with known emission rates (e.g. presence of different
mitigations options). Where the plant cannot be grouped in thisway the data may still be useful to compare with national sectoral
estimates.
Emission factors for specific plant require plant-specific activity
data to give plant-specific emissions. If plant specific emission
factors are not accompanied by plant-specific activity data, it may
be difficult to use such data to improve the inventory.
Using facility-level data would mean replacing an emission
estimate for a category (the “sectoral emission estimate”) with thesum of all the facility level data from all the facilities in thatcategory, or by a combination of the sum of facility–level data andan estimate for the plants that have not reported their emissions.

Use of facility level data usually results in Tier 3 (or mixed
Tier2/3) estimates. Inventory compilers should avoid using facility
level data if more accurate estimates can be made without using
it – but in these cases facility level data could still be useful for
QC purposes.

procedures of whichever national statistical system initiallycollected the data. Where the inventory compilers believe that thenational system QA/QC meets the requirements of the GPG thenthey do not need to duplicate all these QA/QC checks again.
However, they should be able to demonstrate and document thatthese checks have taken place. In any case, examination of thedata by inventory compilers will increase their understanding andability to best use the data.

Figure 2 QA/QC Checks

Specific QA/QC activities for facility level data include:

Checks of the internal consistency between the detailed
activity data, emissions factors and reported emissions. If theinventory compiler cannot get access to the detailed source
data behind the estimates of facility level emissions a way ofchecking the data needs to be established. For example, theinventory agency can try to calculate implied emission
factors1 using an alternative source of activity data to see if
the emission estimates are reasonable. Note that it may not
be good practice to accept facility level data if the quality ofthe data cannot be understood. Therefore access toestimated emissions alone, while potentially useful, is ofoften of limited value.



If the concept of materiality2 and/or a risk-based approachhas been used in the verification process for facility level

Figure 1 Overview of process of using facility level data in national
greenhouse gas inventories.

Ensuring Data Quality - QA/QC
Clearly the data should pass quality checks to ensure it
contributes to the overall inventory quality. However, there is noone-size-fits-all definition for data quality, and expert judgementfrom experienced inventory compilers will be needed, taking into
account national circumstances, uncertainty of existing sectoral
estimates, and anticipated improvement of the overall inventory.
Inventory compilers need to lay down criteria for quality covering:
methodology for deriving data; QA/QC procedures in line with
IPCC Guidelines; sample size and uncertainty; transparency andrepresentativeness.

1 An implied emission factor is the emission divided by some activity data(which may not be the same as data used to estimate the emission). For
example emission measured emissions from coal combustion can be divided
by the amount burnt and the implied emission factor compared withpublished default emission factors.

In the 2006 IPCC Guidelines in Volume 1, Chapter 6 there is aconsiderable body of information on QA/QC that lays out what
QA/QC is expected of data used in national GHG inventories. In
many cases the facility level data will have to comply with QA/QC

2

2

Materiality is a concept (derived from accounting) relating to theimportance or significance of a source or sink. This can be expressed indifferent ways. For example, in some reporting requirements, a source maydata, users should document this and explain whatmateriality level has been applied. Note that application of amateriality level would mean there still could be unidentified
errors in the data. Users should also note that where plantless than a specific threshold have not reported facility-level
data, these smaller plant may be systematically different to
the larger plant and have different emission rates. Thus it
may be difficult to apply data derived from the larger plant tosmall plant. There is no materiality criterion that exempts
emissions from small plant from national greenhouse gas
inventory reporting consistent with good practice.
It may be possible to suggest changes to reporting to makematching to IPCC categories easier. Where facility level reportingis being considered, input from inventory compilers can make theresultant data more useful without significant additional costs.
If the inventory compiler considers the facility level data to be highquality then the most important issues are ensuring that there is
no double counting, that all emissions are reported, and that
where the emissions are reported is transparently documented.
Small errors in allocation across source categories are lessimportant because they will not affect the national total.

Understand and document the quality checks that have been
applied to the facility level data.

Uncertainties

Categorisation

The impact of the use of facility level data on the uncertainty of anemission estimate for an inventory category should be estimated.

Facility level data needs to be allocated to individual IPCC subcategories. If the facility level data are not clearly in one IPCC
category then inventory compilers should consider:

Uncertainty depends on the analyst’s state of knowledge which inturn depends on the quality and quantity of applicable data as
well as knowledge of underlying processes and inference
methods. Uncertainty comprises:

1)
Do facility emissions cover more than one IPCC
category (e.g. do plant emissions combine combustion andprocess emissions, or do the refinery emission estimates coverboth fuel conversion and chemical production), if so additional
information is needed to correctly allocate emissions.

random variation around a mean value (precision); andbias (accuracy).

The 2006 IPCC Guidelines provide general guidance on how toestimate uncertainty for sources estimated with facility level data.
A reduction in uncertainty of the source’s emission estimate is a
desirable outcome of any inventory improvement.

2)
Do estimates include off-site emissions? These arecommonly called SCOPE 2 3 or SCOPE 3 (World Resources
Institute and World Business Council for Sustainable
Development 2004). National Greenhouse Gas inventories
include emission from electricity generation, waste disposal,
travel etc., under other inventory categories so there is a potential
for double counting.

The collection of facility data based on measurements increases
the knowledge and information about the uncertainty associatedwith an emission source. Data on facility measurements provide
more information in relation to the:3)
Is sufficient information available to categorise individual
plant? For example, size of boiler may be known but not its use,making it difficult to allocate these emissions to inventory
categories without double counting or omissions. The ISIC code(or similar) for the business may help in allocate the plant to an
IPCC category, if it is available.



precision and accuracy of emission estimates for individual
facilities;
distribution of emissions across facilities for a source; andvariability of emission estimates over time.

It is likely that the use of data based on facility measurements will
decrease the uncertainty of an emission estimate compared withthe uncertainty associated with simpler Tier 1 or Tier 2
approaches.

4)
How do data relate to national statistics (energy balance,
production)?

In some cases, the improvement in the knowledge andinformation from the use of facility data may lead to an apparent
increase in the estimate of uncertainty. This is possible ifpreviously the uncertainty associated with a lower Tier emission
estimate was underestimated.

only be reported if it is larger than a materiality threshold which could beeither an absolute size or a fraction of the total emission.
3 Produced by World Resources Institute and the World Business Council for

Sustainable Development, the GHG protocol is designed for corporate
emissions and recognises that a company’s activities result in emissions that
occur offsite as well as those within a plant boundary (e.g. emissions form
the generation of electricity). The GHG Protocol defines three types ofemission estimates: Scope 1 (direct GHG emissions) – emissions fromsources that the company owns or controls; Scope 2 (indirect GHG emission
from purchased electricity, steam, or heat) – emissions associated with thegeneration of electricity, steam, or heat purchased and consumed byfacilities or equipment that the company owns or controls; and Scope 3(other indirect GHG emissions) – emissions from other sources the company
does not own or control. This may include waste disposal,
leased/outsourced activities, or emissions such as those related to businesstravel and employee commuting.

The IPCC Guidelines explain how to estimate uncertainties. The
first step is determining the uncertainties in all the input data. For
measured data, this should be clear from the measurement
method. The IPCC Guidelines provide guidance on how to do
this4. For the overall sectoral emission estimate the process isfairly simple, the uncertainties of the input data (e.g. emission
4 See Chapter 6 of the IPCC GPG 2000 or Chapter Volume 1 Chapter 3 ofthe 2006 Guidelines

3

factor and activity data) are combined according to the guidance
provided. The same approach can be used for category estimatesderived from facility-level data.

abatement) and to apply appropriate emission factors toeach strata.

However, using facility level data does add to the complexity of
the calculations and may depend on how the data is to be used.
Where all the facilities in a category report their emissions, theoverall uncertainty can be readily derived from the individual
facility data. Where there is a residual of emission sources notcovered by the reporting facilities then the uncertainty of thisresidual must be estimated.
If the collected facility-level data are considered representative of
the whole source, the uncertainty value for the collected data
should be applied to the residual. However, if the collected facility
data are not representative of the residual or if the characteristicsof the residual are unknown, the situation is more complex.
One approach is to consider stratification of the collected data
into homogenous sub-groups, if appropriate. This can help
understand the representativeness of that data in relation to theunknown residual. Homogenous sub-groups of a source may
reflect regional influences such as climate or geological factors or
technological drivers such as a common mitigation technique.



Where the emission factor used differs from the default
emission factor used by the inventory agency, or from the
IPCC default, then, in accordance with GPG, this difference
should be investigated and the reasons documented. This
may lead to improved emission factors.

Such facility level activity data may be helpful in
supplementing other data e.g. national energy balance data
(in the case of fuel), and other national statistics. In the caseof facility level fuel consumption, these data may help moreaccurately estimate fuel use in individual categories (such as
1A2f), and may be useful in helping understand the range
and characteristics of fuels used (e.g. in refineries).



There may be examples of facilities reporting only limited
sets of data – e.g. emissions mitigated. With care, such data
may be used to improve estimates made using othermethods.

Choosing between sectoral and facility level data
Where inventory compilers have choices between use of facilitylevel data (e.g. ETS data) and other data (e.g. national energy
statistics), they need to develop guidance on making consistentdecisions. A key consideration is the quality of the activity dataand how to judge this quality. Steps to this can include:

Another approach is to try to identify why the collected facility
data may not be representative of the residual. This may help
understanding of the uncertainty of the overall emission source.
The representativeness of the collected facility data in relation to
the unknown residual may be tested through the collection of
more information. A sampling procedure can be designed tocollect relevant information from the unknown residual of thesource while balancing reporting burdens on facilities andadministrative cost considerations. For example, where the facility
data collection system is designed for facilities that exceed
certain emission thresholds, or where reporting is undertaken on
a voluntary basis, a targeted sample may be conducted to collectinformation from the missing facilities.

1.

Assess the difference between two different data sets anddocument the assessment and its results.

2.

Consider whether the uncertainty of the facility level data is
lower or higher than the sectoral emission factor-based
estimates made by the inventory agency. Try and determine
the uncertainties associated with emissions, and if possible
emission factors and activity data. Where a Tier-based
approach to facility level estimates has been used,
determine the uncertainty level associated with each Tier.
This will necessitate access to the detailed data behind thecalculations. Given a choice between facility-level data
based heavily on default emission factors and any
associated assumptions compared with sectoral estimatesthat made with country specific emission factors then the
country specific data sets should normally be used.

3.

Consider any QA/QC verification that has been applied andhow this relates to the requirements of good practice. The

Deciding how to use Facility Level Data
Useful Facility Level Data
The most useful facility level data is likely to be where theemissions data has been derived from plant-specific information
or measurements. For example, measured emissions ormeasured plant specific fuel quality (e.g. carbon content of fuel)should give improved emission estimates compared to sectoral
estimates based on default or country specific emission factors
for the reporting facilities.

Deciding How to Use Facility-Level Data - Key Questions

Where the facility level data are produced using sector-wide
emission factors and plant level activity data (e.g. fuelconsumption or output) the data will probably not lead to moreaccurate estimates of emissions than sectoral approach (and may,in fact be equivalent). This does not mean that such data cannot
be used:It may be the case that the facility-level data allows inventory
compilers to stratify the category (e.g. into different levels of

4

Are the data based on measurements?
Is additional information available to allow stratification?
Can the data be used to derive EFs or be used for
QA/QC?
Has clear guidance been developed on deciding how to
use facility-level data?
For combustion emissions: how does this data comparewith national energy statistics?
Is the sample size adequate compared with the number offacilities in the IPCC category?

fact that QA/QC and verification has been applied should not
be always taken to indicate low uncertainty.
4.

In addition, as a QA/QC measure, facility-level data should becompared with a proxy measure such as fuel use, production,
vehicle kilometres or passenger numbers. Any differences need
to be explained and documented.

Make a comparison between the activity data of the facilitylevel data and comparable national and/or international
statistics, if available.

Consistent use of data

Inventory compilers may wish to develop decision trees to guidetheir decision to use a specific body of data. This would beparticularly useful where there are facility-level data covering a
number of inventory categories. The use of a decision tree would
enable the compiler to demonstrate that consistent criteria had
been used to decide on how to use the data. Compilers candevise separate decision trees for emissions factor data andactivity data but this may not be needed.

In deciding if and how to use facility-level data a formal,
documented, decision process leads to clear, well justified
decisions and a consistent treatment of facility-level data (Figure3). This is especially the case where facility-level data cover
several inventory categories and choices must be made,category-by-category, on whether or not to use the data, and ifused, how to use the data.

Specific Fuel Combustion Considerations
For combustion emissions, compilers should consider how thesefacility-level data improve emission estimates. In particular:Time Series Issues
Usually facility-level data do not provide a complete time series.
The 2006 Guidelines, in Volume 1, Chapter 5 “Time Series
Consistency” provide guidance on how to splice data sets and to
fill any gaps. It is possible to splice together facility-level data withdata from other sources.

1)
How do these data sets compare with national energybalance?
2)
Will using these data improve the national total orreallocate emissions between sub-categories? (e.g. where you
have only part of a combustion category covered by facility-level
data )One issue that may arise is that facility-level data is normally notrecalculated after the emission estimates have been accepted –this may be a problem if errors are detected by the inventory
agency or other organisations. This is a particular problem whereemission factors are used. Good practice requires that emission
estimates are unbiased and so, if the inventory agency detects abias in future years, it should correct the error, recalculate, andreport the deviation between the new estimate of emission andthe original estimate. Recalculations will also be needed if othererrors are detected in previous years’ estimates.

If the energy balance and fuel characteristics are well known thenit is unlikely that facility-level data will significantly improve thenational total fuel combustion CO2 emission estimate, but will
improve the split between sub-categories. However emission
estimates of non-CO2 gases from combustion, fugitive emissions
and other processes can be improved.

Sample Size

Where the facility-level data is only periodically available (e.g.
measurements made every other year) then the inventory
compiler could integrate the available data into the time series
using the procedures set out in the 2006 Guidelines, oralternatively the facility-level data could be used as QA/QC checkagainst the compiler’s own estimates.

Often the facility-level data do not cover all the facilities in an
IPCC category (e.g. see discussion of materiality above).
Perhaps only facility greater that a size threshold have to report,
or maybe only larger facility have to produce measured emissions
while smaller facility can report estimates based on emission
factors. In such cases the usefulness of the data may be
improved by dividing available data into homogeneous subcategories. Guidance on stratification is given in Volume 1
Chapter 3 of the 2006 Guidelines.

Documentation of the approach used to ensure time seriesconsistency and of the assumptions and data used is needed tosupport transparent and verifiable estimates.

However, caution is required when applying EFs from a limited
sample of facilities to a much larger group: compilers need tounderstand the actual processes and methods used in thefacilities to be able to demonstrate they are similar in theiremission characteristics. Users should:

Problems with time series consistency are likely. For years prior
to facility-level data becoming available, inventory compilers willneed to calculate using IPCC category method and splicing thetwo time series using the methods outline in the good practiceguidance on time series consistency..

1) Usually compilers should use the overlap method torecalculate earlier years. Alternatively, they may consider
using new emission factors for earlier years based on facilitylevel data or from elsewhere.



determine the sample size (data available for each category)compared to number of facilities in the category;consider the probability distribution for each category – anarrow range of measured emission rates implies that theemission rate can be extrapolated to the unmeasured facility
with more accuracy;
assess uncertainty and compare with the uncertainty of
sectoral emission factor approaches

2) Compilers may want to wait until there are several years’
data before using facility-level data so that the two data sets
can be compared.

53) Compilers need to consider how far back in time torecalculate. Current facility may not exist in base year,
abatement, management and fuel quality may have changed
and so earlier, sectorial data may be more reliable.

role in identifying otherwise unknown emission sources. Other
sources of data to help assess the overall size of the category
could be national statistics, trade association data and national
inventory stakeholder committees.

4) Trading scheme data may not be recalculated as new
information and corrections of errors become available (e.g.
EUETS). Compilers should use their judgement on how todeal with these depending on the individual circumstances.

Consistent Use of Data - Key Questions5) Compilers need to consider uniformity of methods used togenerate facility-level data over time and ensure thatchanges do not introduce time series inconsistency.Dealing with incomplete coverage

Where facility data is well characterised but represents a subset
of a category a decision tree may be used to assess how to use
this data.

One key consideration to apply when selecting facility-level datais completeness and consistency of category coverage. The
following causes for incomplete or inconsistent data should beconsidered:Reporting thresholds – many data collection systems
contain corporate, facility or source thresholds. Data below
these thresholds are not reported by facilities.



Unknown facilities – a complete list of facilities within acategory may not be known.

Non-compliance – facilities may choose not to report theirdata. Data collection systems with compliance provisions
can help mitigate non-compliance.

Has clear guidance been developed on deciding how to
use facility-level data?
Does the data provide a complete time series? If not, howwill time series consistency be ensured?
Is the data consistent?
Does the data cover all facilities in an IPCC Category?
How are recalculations dealt with?

Because representativeness will vary according to a Party’s
national circumstances (e.g. the size of the category, whether
mitigation and technology changes are included in the facilitylevel data), ultimately expert judgement will need to be used inassessing whether and how facility-level data should beincorporated into the national inventory.

Use of data in EFDBThe IPCC’s Emission Factor database (EFDB) is a library of data
to be used in conjunction with IPCC Guidelines by inventory
compilers to improve their estimates by using factors that better
represent their national circumstances than the IPCC default data.
While countries are encouraged to derive their own countryspecific data, the ability to do this is limited by available resources
and time. Compilers can look at the EFDB data to find material
that is appropriate to their national circumstances.



Incorrect reporting – facilities may make errors in theirfacility-level reporting. Data collection systems with clear
guidance, data evaluation systems and complianceprovisions can help mitigate incorrect reporting.



Geographic incompleteness – regional factors may lead toincomplete coverage of facilities.



Selection of methods – Some emissions reporting systems
provide facilities with the option of estimating facility specificemissions data or using default factors. This self-selection
could lead to a bias in the reported data.

Scientific verification is not done by EFDB Editorial board but they
ensure that that the data is robust and that adequate
documentation is available so that the users can judge whether
EFs can be used for their inventory. It is the responsibility of theusers themselves to ensure the data they use is appropriate totheir specific circumstances.

These factors may lead to a bias in the reported data if it is used
to represent the whole category. However, it may still provide
representative data for one or more sub-categories.

Facility-level EFs may provide a valuable source of such data andshould be submitted to the EFDB.

Characterising the size of the overall sector is an iterative andcontinuing process where facility-level data can play an important6

Figure 3 Examples of Decision Trees for Treatment of Facility-Level Data

7

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Bonduki Y., Griggs D.J. and Callander B.A. Houghton J.T. Paris, IPCC/OECD/IEA.
IPCC (2000). Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories. Penman J,. Kruger D.,
Galbally I., Hiraishi T., Nyenzi B., Emmanuel S., Buendia L., Hoppaus R., Martinsen T., Meijer J., Miwa K., Tanabe K., .
Hayama Japan, IGES.
IPCC (2003). Good Practice Guidance for Land Use, land-Use Change and Forestry. Penman J., Gytarsky M., Hiraishi T., Krug, T.,
Kruger D., Pipatti R., Buendia L., Miwa K., Ngara T., Tanabe K., Wagner F.,. Hayama Japan, IGES.
IPCC (2006). 2006 IPCC Guidelines for National Greenhouse Gas Inventories. Eggleston H.S., Buendia L., Miwa K., Ngara T.,
Tanabe K Hayama Japan, IGES.
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Further Information
Further information, copies of the IPCC Guidelines and additional material are available for the TechnicalSupport Unit of the TFI.
www.ipcc-nggip.iges.or.jp
or e-mailnggip-tsu@iges.or.jp

Technical Bulletin, are intended to explain the application of the IPCC Guidelines for National Greenhouse
Gas Inventories in the light of users’ experience, and to provide inventory compilers practical approaches they
may adopt if they so wish. This Technical Bulletin does not alter or add to the Guidelines themselves.
This Technical Bulletin is an output from an expert meeting convened by the IPCC’s Task Force on National
Greenhouse Gas Inventories (TFI) on this issue in Wellington, New Zealand, 18th-20th July 2011. This
document has been reviewed by the participants and the Bureau of the TFI; however it has not been subject
to the formal IPCC review and approval process and is therefore IPCC Supporting Material prepared forconsideration by the Intergovernmental Panel on Climate Change.