Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories

CHEC KS AND V ER IFICA TION AT
NA TIONAL AND IN TERNA TIONA L
L E V ELSACKNOWLEDGEMENTS
This paper was written by Jos Oliver (RIVM, The Netherlands), Wilfried Winiwarter, (ARCS, Austria), JeanPierre Chang (CITEPA, France) and has been reviewed by Roberto Acosta (UNFCCC), Dina Kruger (USEPA),
Joe Mangino (ERG), Katarina Mareckova (IPCC/OECD/IEA), Jim Penman (DETR) and Karen Treanton (IEA).

ABSTRACT
National inventories submitted under the UN Framework Convention on Climate Change are updated annually,i.e. the inventory for a new year is compiled and added and the emissions of the other inventory years are being
revised when considered appropriate. Since this process requires the handling of much data and often many
persons are involved, both in selecting representative emission factors as well data processing, errors andinconsistencies may easily slip in. This paper reviews the needs and possibilities for validation (checking) andverifying procedures, i.e., checking the internal consistency of the inventory and activities using external data toverify the emission estimates, respectively. Concrete options are reviewed that could typically be done atnational level, by national teams, and options at the international level that comprise for example inter-country
comparisons and comparisons with independently compiled datasets (global emission inventories andinternational statistics). The latter could most efficiently be done at international level by international bodies orby international co-operation of national experts. In this paper we will primarily focus on what individual
countries can do. In addition, procedures, priority setting and reporting requirements of checks and verification
activities at national level are discussed, as well as possible institutional arrangements for activities atinternational level.

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Background Paper

1

INTRODUCTION

1.1

The inventory compilation process

Emission inventories may be compiled for a special purpose as a one-time activity. In order to monitor
environmental progress, however, periodic updates of these inventories are needed. Under the Kyoto Protocol of
the United Nations Framework Convention on Climate Change (UNFCCC) countries are required to submit an
update of their greenhouse gas emission inventory to the Climate Change Secretariat annually. In year t theinventory should contain final figures for the years 1990 up to t-2 inclusive and preliminary emissions for theyear t-1. There is no need to re-submit final emission data for earlier years, unless these data have been changed(e.g. due to recalculations, re-allocations or addition of new sources). Any extension or update of existing
inventories will build on the existing one: addition of a year, finalisation of preliminary previous year or possible
adjustments of the so-called final historical years (‘recalculation’). In addition to emission figures, theinventories prepared for the UNFCCC should also include information on the uncertainty estimate for thereported figures.
So, following the activities that take place annually, the annual inventory update process can be split into fourparts, building on the existing historical inventory in place (including estimated uncertainties) which is the resultof last year's activities, on a source-by-source basis:•

New additions to the emission inventory (new year[s], possibly new sources);•

Finalisation of last year’s preliminary data;•

Adjustments to the existing inventory (e.g. recalculation) (if applicable), and•(Re) evaluation of the estimated uncertainties.

It is this sequel of activities that also provides many opportunities for carrying out internal checks at various
stages of the update process.

1.2

The need for checking and verification

Because of the many data and many institutions involved in the emission inventory compilation, as well as –ultimately – in the judgement of representativity of emission factors, small or large errors and inconsistencies(e.g. across sources or in time) may easily slip in. Therefore, checking and verification procedures are importantand indispensable elements of the Quality Assurance/Quality Control (QA/QC) system of the inventory
management (see Chapter ‘QA/QC of inventory systems’ in (IPCC, 2000)).
Checking is part of the validation of the inventory, which involves ensuring that the inventory has been compiled
correctly, i.e., calculations have been done correctly and in line with guidelines and reporting instructions. Thus
validation refers to internal checks of the consistency of the inventory. Verification, on the other hand, refers toactivities using external data that help to establish the reliability for the intended applications of the inventory
viz: external methods to check the truth of the inventory include comparisons with reference calculations, withestimates made by other bodies, with atmospheric concentrations or external review.
This paper aims at presenting concrete options for the internal checking and verifying national greenhouse gas
inventories. For each of the components of the inventory process we will describe readily available techniques
for performing quick basic checks on apparent errors (order-of-magnitude checks), completeness, consistency,
and comparability. This paper will present the practical checks and verification procedures that we recommend
to be taken. Using the instructions given, a system can be established for priority setting and for reporting thechecks and verification activities performed and their results (see Section 5). In addition, we will discuss other,more elaborate methods of verifying the inventory on these aspects thoroughly, which are beyond the scope of
inventory guidelines at this time.

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2

DATA QUALITY OBJECTIVESIn order to provide confidence to the inventory system, the establishment of high quality data is indispensable.
An inventory system becomes useful in the international context only if it can be proven to meet the objectives it
has been devised for as defined in the ‘data quality objectives’.
For national and international (UNFCCC) purposes of establishing credibility of the national inventories, the
UNFCCC preparation guidelines describe the data quality to be achieved in terms of accuracy and the three c’s:Completeness, Consistency and Comparability. Accuracy refers to emissions being calculated correctly andunbiased - as far as can be judged - and uncertainties being reduced as far as practicable. This calls for
identification and correction of apparent errors in input and calculation (e.g. order-of-magnitude checks) and for
efforts being made to reduce the largest uncertainties. Completeness means that all relevant sources are includedin the inventory. Consistency means that per source category for all years the emissions are calculated with thesame emission calculation methodology and for all years the same source definition (allocation) is used.
Comparability means that the emission inventories are comparable across countries. This refers to bothemissions and the estimated uncertainty. Emissions of two countries are called comparable if they use the same
source definitions, similar emission calculation methodologies and similar emission factors in similar cases.
Therefore, they can also be considered comparable if for major national sources the calculated aggregated(‘implied’) emission factors are well within the estimated uncertainty or if large deviations from others (a set offactors reported by a group of apparently ‘similar’ countries, or - if these are not available - IPCC defaults) areclarified and justified. In other words, verifying comparability requires checking for and documenting ofobserved seemingly deviating figures for (aggregated) emission factors.
From the description given above, it shows that for checking comparability it is required that emission datacompiled at the international level are made available either by independent organisations or by the UNFCCC
Secretariat. Individual countries can perform this type of verification, but also other organisations as well as
individual scientists. In this paper we will primarily focus on what individual countries can do.

3

OVERVIEW OF OPTIONS ON THE NATIONAL
SCALE

3.1

Approaches in relation to data quality
objectives

A number of approaches have been identified for quality control of elements for which the UNFCCC has defined
its objectives (EEA, 1997; Lim et al, 1999; Van Amstel et al., 1999) as follows:•internal quality checks (comparison between years and inventory versions);•

inventory inter-comparisons (comparison with other independently compiled estimates, with national
inventories of other but similar countries and with IPCC defaults);•

comparison of density indicators;•

verification by comparison with direct atmospheric concentration measurements;•

comparison with atmospheric budgets derived from atmospheric models, and•direct source testing (on site measurement of large emission sources).

The degree to which countries check or independently verify the inventory varies between approaches – as does
the capacity required to perform these activities. Therefore, we will distinguish between the more easy, lesselaborate ones, referred to as ‘checks’ (either internal or using external data), and more complex, data intensive,
time-consuming activities, referred to as ‘verification’. For example, direct source testing is a means of groundtruth verification, which however will often not be simple to perform. In addition, for practical reasons we will
also distinguish between options using national data only and options which require the availability ofinternational data. Based on the mentioned approaches, a number of options have been identified, which aredescribed in more detail in separate sections, i.e. options for (a) checking and (b) verification using national data,and (c) use of international data.

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3.2

Options for checking

In the context of the present paper, the checks at national level considered here relate to checks to be performed
when the inventory is finished (as draft or final version). So compared to the QC processes, the same checking
methods may be used. The differences arise from the fact that the QC processes include larger checks (forexample data management system controls) and start from the beginning of the inventory preparation as
described in the ‘QA/QC of inventory System’ chapter ( Cross-Cutting Issues) of this publication. With respect
to this matter, we can wonder whether these considered checks at national level are part of QC processes or not.
A first reply could be ‘yes’, in the case that it is done by the national inventory team, but ‘no’, if it is performedby an external team or organisation. To illustrate the point, we can give the example of related practices with
CORINAIR inventories. In case of CORINAIR inventories managed by the European Environment Agency(EEA), after national inventory checks, national individual checks are also performed by the ETC/AE (European
Topic Centre on Air Emission) [now merged into: ETC on Air and Climate Change, ETC/ACC]. But it is time(and effort) consuming, especially when there are feedback processes and successive national reviews. Therefore
the tendency is no longer to carry out the detailed individual checks ETC level, but to expect countries toperform the QA/QC processes.
There are a number of options to perform quick basic checks on new figures using the existing inventory which
has already been quality assured:•Comparison of trends and comparison with previous reported data (emissions, but can also be applied toactivity levels and emission factors):
Purpose: consistency and completeness check;•

Checking for documentation and any methodological changes in the components of the inventory (activity
data, emission factors, emission calculation methodology):
Purpose: consistency check; documenting and justifying data and methods used;•

Order-of-magnitude checks (for example by comparison with IPCC Tier I calculations using IPCC default
factors or by comparing an activity to a related one):
Purpose: quick indirect check for possible major calculation errors and inclusion of major sources;•

Reference calculation, such as for CO2 (based on apparent consumption):
Purpose: top-down versus bottom-up comparison to ensure completeness and right order-of-magnitude, inthe case of an inventory based on a bottom-up approach, and•Checking estimated uncertainties.
Purpose: check the order-of-magnitude of the estimated uncertainty for possible errors in input or
calculation and for apparent country-specific uncertainty levels in either activity data or emission factors.

3.2.1

Comparison of trends and previous reported data

A consistency and completeness check using the available historical inventory data for multiple years is based on
the experience that the emission level of most sources does not abruptly change from year to year, due to gradualchanges in both activity levels and emission factors, if any. In most circumstances, the change in emissions willbe less than 10% per year. Thus percentage changes of emissions in year t compared with year t-1 are a good
indicator of possible input or calculation errors. An additional result of this basic consistency check is - except
for correction of identified errors resulting in large differences - that it automatically identifies the areas in theinventory which call for a clarification if not justification.
In case of important emission changes between year t-1 and t, and especially in case of major emission
contributing sources, further checks with trends from historical data can be performed respectively for activity
rates and emission factors. For example, historical trend analysis on activity data can help the activity checks bycomparing the historical activity trend up to the last inventory, with an expected activity trend, or with the trendof a related and correlated indicator. For emission factor trend checks, the historical emission factor for a given
pollutant and sector, can be compared to an expected trend (for example from an external expert in the given
sector) due to technology evolution or other reasons.
Another routine check that can be made with the newly finalised data for a year t, provided that the previous
version of the inventory contains preliminary figures for that year t, is inspection of the difference between the
final and the preliminary figures. The actual checking process is identical with the checking of differences
between subsequent years, but it is qualitatively a different type of check, since it checks both the accuracy of the526

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Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories

newly finalised data and utilises source-specific knowledge about the likely trend in it. Moreover, it provides areview of the quality of the estimation procedure for the reported ‘preliminary emissions’.
Phase in compilation process and update types
Routine checks using the internal consistency of the inventory may be applied at three points in time in theinventory update process:A. Draft sectoral inventories: per sector, per gas;
B. Final sectoral inventories: per sector, per gas, and
C. Final inventory: per gas, total inventory, main source sectors.
The term ‘draft’ or ‘final’ may apply to all parts of the update process:1. Newly finalised emissions for year t (in previous version possibly labelled as ‘preliminary’): comparison
with previous year’s emissions (i.e. in year t-1) and with the ‘preliminary’ emissions for year t in last year’s
version of the inventory (if available);
2. New preliminary emissions for a year t+1: comparison with previous year’s emissions (i.e. year t), and
3. Revisions of older ‘final’ emissions: comparison both with previous year’s emissions and with emissions inlast year’s version of the inventory.
Procedure for routine consistency checks•

Standard checks (see example below);•Standard actions (log of check; correction of data or explanation of differences), and•In case of corrections: re-apply standard checks for corrected sections.

After the calculation of differences, the largest percentage differences (in any direction) can be flagged, either byvisual inspection of the list, or visual inspection of graphical presentation of differences (e.g. in a spreadsheet) or
by using a dedicated software programme that puts flags and rankings to the list of differences. When dealing
with very many sub-sources graphical presentation of differences is a very efficient tool to get an overview ofthe differences for all sources and to point out the sources with the largest differences. If all data are available
electronically, these checks could be done for all sub-categories available without much additional effort.
Possibly erroneous results could be flagged, for example, using a dedicated programme or screening the results.
Example of routine consistency check (applicable to any of the points A-C and update types 1-3):
Check annual increase/decrease of emissions per sub-sector available in the inventory, expressed as percentage[figures and percentages used to be evaluated by the individual country according to priorities and national
experience]:
1.

Check the 5 largest percentage differences for arithmetic errors

Check the reason for the difference and either correct or explain the differences; if differences are larger than
10% and appear to be correct, then justify the figures.
When explaining or justifying observed large differences, one should keep in mind that for more aggregate
sectors less change is expected than for sub-sectors. For example, total emissions from petrol cars are not likely
to change substantially on an annual basis, but emissions from sub-categories, such as catalyst-equipped petrolcars, may show substantial changes if their market share is not in equilibrium or average technology appliedchanges quickly.
2.

In addition, check all cases with differences larger than 10% for arithmetic errors:

If considered important for the source category or the quality of the update process, one could extend the checkto all cases that show differences of over 10%. However, here too, one should keep in mind that annual
differences in minor sub-sectors may be larger than in higher aggregates.
Checking the reasons for the differences
Possible causes of major differences are:1.

Printing or arithmetic errors in statistical and emission factor data used:

To be checked by comparing with the values used for the previous year (data at this level can also be routinely
checked by systematic comparison with the values used for the previous year as described for the resulting
emissions). If these do not differ much, then the following checks should be made:Checks and Verification at National and International Levels

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Input errors (to be checked by comparing input data with the external source of the activity level andemission factor), and•Arithmetic errors (to be checked by recalculation).

2.

Large discontinuities in calculation methodology or source definition:

To be checked for if the first check on printing or arithmetic errors does not provide sufficient clarification oflarge annual changes:•

Substantial changes (discontinuity) in methodology for establishing the annual activity level for a specificcategory (to be checked with the agency that compiled the statistics), and•Discontinuities due to a change of source definitions (may be related to methodological changes too). This
may show up as a shift between two or more sub-categories, one increasing and other(s) decreasing, while
the change in the total remains small. Examples: different inclusions of off-road vehicles, cogeneration(CHP), some ‘miscellaneous’ categories (to be checked by asking the people or organisation, which actually
did the emission calculation, or the organisation that co-ordinates the overall inventory process for any
changes of this nature).

3.

In case of comparison with preliminary figures: unexpected actual developments in the source:

Differences can be caused by either a trend estimation methodology for preliminary figures that appears to be too
simple to capture the real developments of the source or by unexpected developments in the past that theestimators were not aware of at the time when the preliminary estimate was made.
4.

In case of revisions of older ‘final’ emissions:Differences may be caused by any change in underlying activity data, emission factors or emission calculation
methodology. Good practice is to report (a) for which gases and sectors figures are changed compared to lastyear’s release of the inventory, (b) the size of the largest changes, (c) the cause of these changes, and (d)justification of the largest changes.

3.2.2

Checking for methodological changes

For reasons of transparency and consistency, any methodological changes in the components of the inventory
compared to the last year’s version, either in the existing final inventory or in the new or newly finalised
sections, should be checked and reported as follows: activity data, emission factors, emission calculation
methodology. Large changes in any of these should have been identified already in the previous checks of trends
and of different versions. In addition, the organisations or people actually doing the sectoral emission
calculations should be asked to document and justify any change in data and methods used. In particular, whensource definitions have been changed it should be checked that neither overlap nor gap has been created (forexample check of proper co-ordination between the sector groups).

3.2.3

Order-of-magnitude checks

This type of quick check for possible major calculation errors and inclusion of major sources is particularly
valuable if the emissions have been calculated as the sum of many individual sub-sources (e.g. many point
sources in industry and energy sectors or many sub-categories of road transport). Comparison of emissions witha top-down approach for example IPCC Tier I calculations using national total statistics as activity data and
IPCC default factors is essential. For an example of this comparison for the UK inventory see Salway (1998). In
case of major discrepancies between the emissions, as a further check the underlying sum of activities or theweighted average emission factors can be compared. In some cases another basic check is to compare theemissions with a country of seemingly similar characteristics and size (cf. options involving international data,
item 3.4 and 4.1.1).
Comparing the activity of one type to another is a further type of order-of-magnitude check that can be made.
Examples are: calculation of average annual fuel consumption per car by dividing total fuel consumption of roadtransport by the number of cars, dividing total production of animal manure by the total number of livestock,
total amount of waste produced by the number inhabitants. If these do not relate to sensible figures per car, peranimal or per person, then this is an indication of an input or calculation error.

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3.2.4

Reference calculations

In a number of cases where emissions are calculated as the sum of sectoral activities based on consumption of a
specific commodity, for example fuels or products like HFCs, PFCs or SF6, emissions could alternatively be
estimated using apparent consumption figures: national total production + import - export ± stock changes. For
CO2 from fossil fuel combustion a reference calculation based on apparent fuel consumption per fuel type ismandatory according to the Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories (IPCC
Guidelines) . Furthermore, in cases where the inventory is based on a bottom-up approach, a top-down versus
bottom-up comparison of activity data is an efficient check of completeness and order-of-magnitude of this partof the inventory.

3.2.5

Checking estimated uncertainties

Irrespective of the Tier used for estimating uncertainty in reported emissions, it is Good Practice to compare thequantitative national results for the main source categories with the order of magnitude uncertainty indicator
resulting from using the IPCC Tier I default uncertainties (as provided in the Good Practice Guidance report(IPCC, 2000) for specific sectoral emissions).
If the results per main sector or for the country total are very different, a calculation or input error could haveoccurred in estimating the sectoral uncertainty per gas or the national total per gas. In such cases, it isrecommended to check whether country-specific uncertainties in key parts of the inventory are indeed very
different from the IPCC defaults for Tier I. If that is the case, it is Good Practice to document the references forthe uncertainties used as input for the calculation of these sectoral uncertainties as well. If inspection shows thatthe country-specific uncertainties in key parts of the inventory are not quite different, then it is Good Practice to
do a check on inputs and calculations.

3.3

Options for verification at national level

In some countries there may be more institutions estimating greenhouse gas emissions. It is then feasible toproduce complete or partial inventories that have been compiled independently, with their own choice of data
sources and methodologies. Comparison of the official national inventory with these independently compiled
estimates provides a quick check for apparent errors such as lack of completeness and incorrect source
allocation. More elaborate options at the national level take advantage of data that is independently collected.
Such data can be derived from actual measurements. Climate change gases generally are characterised by a long
half-life in the atmosphere. As a consequence, their typical atmospheric concentrations are relatively stable.
Increments due to sources thus are relatively small compared to background concentration. The challenge in
identifying the contribution of a source or source area is to identify a minute increase over a stable baseline. In
order to assess the maximum increase possible, one may wish to obtain the possibly strongest signal, which is
obviously very close to a source: Direct source testing involves local measurement of key parameters as a meansof ground truth verification of key sources. Comparison with atmospheric measurements at national scale serves
as independent, ground truth verification of annual emission levels and, possibly, emission trends. Other options
for verification are comparisons with estimates published in scientific literature, based on a review of thenationally available literature. Also publications analysing the quality of the official national inventory may be
used in this respect.

3.3.1

Comparison with other national data

Comparisons with other, independently compiled, national emissions data for the country are a quick option to
verify completeness, approximate emission level and correct source allocation – if such an independent
inventory is available. It can be made per compound at national, sectoral and sub-sectoral level, as far as thedifferences in definitions/sectoral nomenclatures enable it. Procedures to be taken resemble those of comparisonswith international data. In this respect see Section 3.4 for more details.

3.3.2

Direct source testing

The following approaches for direct source testing have been used previously:

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On-line stack measurements:

Currently, many major power plants are equipped with routine monitoring equipment for CO2 measurements.
While this instrumentation helps maintain combustion conditions, usually the C content of fuels is considered amore reliable indicator for CO2 emissions.
•In-plume measurements

The in-plume freight of a constituent may be estimated from its concentration in a cross section and the transport
velocity. Emission estimates of this kind have been made to assess volcanic CO2 emissions (Allard et al., 1991)
or conventional pollutants in city plumes (Klemm and Ziomas, 1998), which however already include amultitude of single sources.
•

Remote measurements

Open-path FTIR spectroscopy has been successfully shown to assess SF6 (Hashmonay et al., 1999) and NH3emissions of diffuse area sources, but it also has a high potential for CO2, CH4, N2O and other gases (Schäfer etal., 1999). Results are obtained with the help of inverse dispersion modelling to reconstruct emissions fromconcentration measurements.
•

Indirect methods

Using a tracer (or adding a tracer to the plume of a stack) allows the identification of even small amounts of acompound, once the ratio between the compound and the tracer is known and there is sufficient reason to believethat they behave identically during atmospheric transport. This method has been applied in identifying SO2
emissions from power plants by adding deuterated methane as tracer (Malm et al., 1990).
All these approaches allow the direct attribution of observed concentrations of the emissions from a certain source.
However, they do not allow for a complete coverage of a country, as normally only a small part of the emission
sources of a country can actually be measured. Especially assessment of area emissions is very laborious and costly,
and in practice will only be done to obtain emission factors – maybe with the exception of rare and single sources as
volcanoes. In cases when it is unsure if general emission factors may be applied to a certain country, measurementsof this kind are advisable. In direct source testing, uncertainty of measurements (including the associated steps foremission calculation, like model uncertainties) are considered to be as low or lower than the uncertainty in theemission inventory. Therefore results may be used to reduce total inventory uncertainty.

3.3.3

Comparisons with atmospheric measurements

The processes between emissions and ambient concentrations are complex even for climate change gases, which
do not easily undergo conversion processes. Still at a given site, background concentrations may be assessedfrom the low concentration levels, and enhanced concentrations (plumes) from high levels. Under certain
circumstances, emissions may be considered proportional already to the difference between such low and highlevels. Nevertheless, the use of an atmospheric model should be advised in order to adjust for the dilution anddeposition processes, and also to cover transport direction. Measurements are to be performed on one or several
fixed sites. One option is to compare measured concentrations with modelled concentrations. In terms ofemission assessment, it seems more appropriate however to perform inverse modelling, i.e. estimate emissions
from measured concentrations.
Clearly, in comparison to the direct source, testing the signal-to-background ratio may prove to be an evenstronger challenge. This may be overcome for climate change gases that do not have so high backgroundconcentrations (SF6, CFCs), or by using markers within compounds, which differ strongly from the background.
Such markers can be stable isotopes, which occur in different abundance in the background and in the emission
source. These markers (13C) have been used for assessing CH4 emissions (Levin et al., 1999). Theoretically, also
application on 15N (in N2O) is possible, as has been shown for NH3 (Bruckner et al., 1996). As for example, theabundance of 13C is not only different between background and emissions, but also between different emission
sources, conclusions may be drawn on the relative contribution of each such source to the total.
The applicability of such methods obviously is not limited to areas defined by national boundaries, but rather toareas that are characterised by elevated source strength, since it is only possible to differentiate areas of differing
emissions strengths. As industrial and population centres are frequently situated at both sides of a nationalboundary, however, an evaluation for just one country is not possible because emissions can only be assessed forthe whole area. In such a case, the methods become valuable only on a bilateral or international level.
In practice, due to the limitations, uncertainty associated with measurements and inverse modelling may becomerather high, and a careful evaluation of the measurement/model system uncertainty with respect to the inventory

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uncertainty becomes essential (see Chapter ‘Quantifying uncertainties in practice’ in IPCC (2000)). For
performing a significance test, the following results are possible:•

Measurement/model results are significantly different from the inventory→ Falsification of the inventory; sources are missing, inadequate emission factors or statistics used,
calculation error.

•

Measurement and inventory do not differ significantly; uncertainty of measurement is lower thanuncertainty of inventory.
→ Measurement results may be used to reduce inventory uncertainty.

•

Measurements and inventory do not differ significantly, uncertainty of measurement is higher thanuncertainty of inventory.
→ Measurement results are not useful in terms of the inventory, except that it confirms previous
assumptions on completeness and lack of errors.

3.3.4

Comparison with scientific publications and external
review

Although the government is responsible for the compilation and submission of the national greenhouse gas
inventory, there may be other independent publications on the same subject, for example in scientific literature.
This provides another option for comparison with other national estimates. Also publications analysing thequality of the official national inventory may be used in this respect. While scientists are basically limited to themethods described above, other results may be already available. In practice, such a comparison implies
reviewing the nationally available literature and compare data on paper. The review report should document theresults of the comparison and be included in the report on QC activities performed.
In addition, external review of the national inventory, either peer review commissioned by the compilation
agency or public review encouraged by the agency, is an opportunity to compare methods and data used by theinventory preparation agency with the judgement of scientific experts or stakeholders and others with specificknowledge in this field.

3.4

Options for verification involving
international data

There are several different comparisons that can be performed using international data:•

Comparison of emission density indicators with similar countries (for example emissions per capita;
industrial emissions per unit value added; transport emissions per car; emissions from power generation per
kWh of electricity produced by fuel type (coal, oil, gas) (excluding cogeneration), etc.):
Purpose: quick indirect check and verification;•

Performing comparisons of emissions with other estimates: with independently compiled authoritative
estimates (international datasets e.g. from IEA, CDIAC, GEIA/EDGAR or WRI):
Purpose: checking completeness, consistency, correct source allocation, order-of-magnitude;•

Comparisons of emission factors:• with IPCC defaults;•

with literature values;•

with those used by similar countries, and•with the set of implied factors reported to UNFCCC (as proposed in the ‘Common Reporting Format’,
CRF):

Purpose: checking comparability and country-specificity;•

Comparisons of activity data:•with independently compiled estimates (IEA, UN, FAO), andChecks and Verification at National and International Levels

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with activity density indicators from similar countries (for example activity rate per inhabitant, peremployee, per unit of GDP, per number of households or per number of vehicles, etc., according to
the source sectors):

Purpose: checking completeness; order-of-magnitude check;•Comparisons of uncertainty estimates of data reported to UNFCCC:
Purpose: checking order of magnitude of own uncertainty estimates against others.

It will be clear that for a given source, different parallel comparisons can be performed:•

Comparisons with other independently compiled emissions data for the specific country: checking
completeness, magnitude, and proper source allocation, and•Inter-country comparisons: for a specific year, the comparison of background data (activity levels,
aggregated emission factors or other factors used in the methodology) from different countries.

The first kind of comparison with other estimates for the country under investigation is a quick check forcompleteness, approximate emission level and correct source allocation. It can be made per compound at
national, sectoral and sub-sectoral level, to the extent that is allowable taking into account the differences indefinitions/sectoral nomenclatures. In Section 4.1.1 examples of reference databases are presented. Existence oflarge discrepancies does not necessarily mean that one or both inventories contain flaws, but rather points topossible inadvertent errors, which are also aspects of uncertainty within inventories that can only be evaluatedusing this method. In those cases, one may wish to do a further check on activity levels or emission factors inthat sector. In case of large differences for sub-sectors, one should also be aware that in either inventory the sumof the sub-sources might well be comparable by hiding shifts of part of the emissions between these sectors.
Comparison with reference inventories developed by other authoritative sources is also a check of thecomparability, when the reference inventory uses a common methodology for all countries. If inventory
preparers have calculated national emissions using the Tier I methodologies of IPCC Guidelines (IPCC, 1997),
then comparing emissions automatically means also a check against the default emission factors recommended
by IPCC - if activity levels used in the reference dataset are similar to national data.
Concerning the latter kind of inter-country comparison of emissions, emission density, reported or backgroundemission factors, activity or activity density: such checks can be based on reported results from international
checks (cf. options on the international scale, item 4.1.1) but with a delay in time, or based on national initiatives
to get/calculate such data/density indicators for the more recent inventoried year as well as for other countries.
The inter-country comparison of reported aggregated emission factors could be combined by plotting in a single
graph: for the different countries, the reference year data (1990), the more recent year data, and the minimum
and maximum value, for each source sector and possible aggregations and according to the fuel types whenrelevant (see Figure 1). The comparison of data is relevant if the data are comparable. Consistency checks oftrends in emission factors at national level and cross-country comparisons of emission factors can be processed
as far as units are fixed (there are a few exceptions). These can be based on the sectoral background tables of the‘Common Reporting Format’ (CRF) trend. Thus, comparisons of (aggregated) emission factors can be madewith the set of implied factors reported to UNFCCC (as proposed in the ‘Common Reporting Format’, CRF). If
some national emission factors appear to be outliers, further comparison could be made by checking with thoseused by similar countries. Furthermore comparison with the recommended IPCC Tier I default values and withliterature values may be informative in establishing the comparability or the country-specificity of the emission
factors used.
Concerning checking of activity rates, on the basis of the CRF, common comparable indicators should be
defined for the purpose of international comparison (for example, activity rate per inhabitant, per employee, perunit of GDP, per number of households or per number of vehicles, etc., according to the source sectors). This
will enable order-of-magnitude checks as well as checks for outliers that may be caused by input or calculation
errors. Comparing with international statistics for national countries, which were in principle independently
compiled from the greenhouse gas inventory preparation agency, can make a similar check.
Countries have to submit uncertainty estimates by source or sink categories for each compound given. An
international comparison of the figures submitted could be performed on the basis of relative uncertainties (aspercentage). For this purpose the following steps could be taken next:
1.

Check the uncertainty given by the individual country for each category/compound combination. Values
which have an unusually low uncertainty associated with their emissions should be checked individually forconsistency of their reporting;2.

Check/calculate total uncertainty of a country for a given compound, and3.

Check consistency of given number/uncertainty with verification measurement/uncertainty.

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Figure 1

Example: Graph for an inter-country comparison ofemission factors

Emissionfactors(fromreference
to current
year)(unit)

Sector/sub-sector :xxx
Pollutant :xxx
90
97
90

90

97

97

90

90/97

97
90/97

country1 country2 country3 country4 country5 country6

countries

N.B. : the E.F. range for a given country relates here to the minimum and maximum E.F. during the period 90-97

These comparison processes do not always represent verifications of the data themselves, but verification of thereliability and the consistency of data (in trend and across countries). Practically, these comparison processes
will enable reviewers to focus on more limited cases of inconsistencies or doubts for which deeper data
verifications will need to be performed. Obviously, the amount of time to be spent on these independentvalidation and verification activities should be prioritised (see Section 5).
More examples of emission comparisons are given in the Annex.

4

OVERVIEW OF OPTIONS ON THE
INTERNATIONAL SCALE

UN bodies, governments, individual scientists, scientific research programmes, NGO’s may show interest inscientific peer review or public review of national inventories by analysing and comparing various data sources(official national inventories, other estimates, information available from the UNFCCC Secretariat, etc.). In
addition, both IPCC WG I and the IPCC TSU on National Greenhouse Gas Inventories will be encouraging these
activities from the perspective of improving current knowledge on global budgets, source strengths andrepresentative default emission factors. The following approaches can be identified: (a) international
comparisons, (b) comparisons with scientific publications, (c) evaluation of budgets and source strengths, (d)updating IPCC reports. Each of these will be described below in more detail.
Comparisons of emissions cannot be interpreted without some quantitative knowledge of the associateduncertainty. As the art of estimating country emissions and their associated uncertainty is at different levels of
sophistication in different countries, the Good Practice Guidelines recommend a Tiered Approach aiming at
quantified uncertainty estimates (see Chapter ‘Quantifying uncertainties in practice’ in IPCC (2000)). Tier I is a
simplified method for calculating a quantitative indication of the uncertainty in the total national emissions bymeans of classical arithmetic methods of combining uncertainties (assuming standard, Gaussian distributions,
independent variables and uncertainties smaller than 60%). Subsequent Tiers use more detailed, data-intensive
methods for the uncertainty estimates. However, for performing a Tier I calculation of indicator of uncertainty
one also needs an estimate of the uncertainty in all underlying activity data and emission factors. It requires atleast expert-judgement of the uncertainty as order of magnitude (see Table 1), except for cases where better
information is readily available (for example selected from a range as described in the Chapter ‘Quantifying
uncertainties in practice’ in IPCC (2000)).

Checks and Verification at National and International Levels

533

Background Paper.
TABLE 1
EXAMPLE OF A CLASSIFICATION OF UNCERTAINTIES
Range(±)

Uncertainty (±%)

Uncertainty Factor*

Confidence

Qualitative description

2-10%

5%

1.05

High

very small

5-20%

10%

1.1

High

small

10-50%

25%

1.25

Medium (High)medium20-100%50%

l.5Medium (Low)large

50-150%

100%

2.

Low

very large

100-400%

200%

3.

Low

extremely large* An uncertainty factor UF corresponds with the following range around the emissions level EM: from EM/UF to EM*UF.

For greenhouse gases one could seek guidance from the qualifications and values already used in UNFCCC
submissions, e.g. as reported in FCCC/SBSTA/1998/7, Table 14 (p. 36-37).
This will provide a means for generating quantitative uncertainty figures for many countries in the short term.
This facilitates cross-country comparison of uncertainty estimates. In addition, it will allow reported levels of
uncertainty to be evaluated in a more comprehensive way in assessments of uncertainties in a broader context,
for example in regional or sectoral comparisons and in ‘chain calculations’ from emissions to climate change,
which address uncertainty in all elements of the chain in a harmonised way, for example through the use of
uncertainty factors.
Examples of applications in which uncertainty estimates are an essential element are:•cross-country comparison for all countries where inventories are available (for checking comparability,
inadvertent errors or identifying highly deviating emission factors and/or apparent country-specificcircumstances);•

providing uncertainty estimates for world regions (e.g. Annex I countries to the UNFCCC);•

providing (by extrapolation, if required) uncertainty estimates for the world;•

providing insight in the robustness of reported multi-year emission trends;•

comparison with reference inventories developed by other authoritative sources (for checking completeness,consistency, correct source allocation, and for inadvertent errors, which are also aspects of uncertainty
within inventories that can only be evaluated using this method), and•comparison with independent top-down estimates by reverse modelling of atmospheric concentration
measurements (for checking for possible biases in country totals or global or regional sectoral totals).

4.1

International comparisonsComparison of national greenhouse gas inventories with international data sources can be a means to
independently verify the reported figures, in particular with respect to comparability and possible group bias. In
addition to the activities described in Section 3.4, which are done from the perspective of a specific country, we
also do a more systematic comparison for a larger group of countries and draw conclusions at another level. Here
we can distinguish between comparison with other, but independently compiled, bottom-up emission estimatesand comparison with emissions based on top-down estimates from atmospheric concentration measurements.

4.1.1

Comparisons with emissions, emission factors or activity
data

Typically, the comparisons are similar to those already introduced in Section 3.4:•

Reference calculation for CO2 (based on international energy statistics, cf. Section 3.2.4);•

Comparisons of emissions with independently compiled estimates (global emission inventories);

534

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Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories•

Comparisons of emission factors (outlier detection in implied factors reported to UNFCCC);•

Comparison of emission density indicators (as a quick indirect check/verification), and•Comparisons of activity data (including activity density indicators).

Compared to the Section 3.4 (options at national scale), there is an important constraint to focus on, which is thenecessity for harmonised reported inventory datasets (Lim and Boileau, 1999). The different detailed crosscountry comparisons (of sectoral/sub-sectoral emission factors or activities) assume that such detailed
harmonised reported inventories at international level are available.
Comparison of national emission inventories with independently compiled authoritative international datasets
will assist in checking completeness, consistency, correct source allocation and magnitude of both inventories national and international. Such global databases currently exist, for example on CO2 from fossil fuelcombustion only compiled by International Energy Agency (IEA) and by the Carbon Doixide Information andAnalysis Centre (CDIAC), global total anthropogenic inventories of all greenhouse gases of the Global Emission
Inventory Activity (GEIA, a component of IGAC/IGBP) and of the Emission Database for Global AtmosphericResearch (EDGAR) compiled by TNO and RIVM in close co-operation with GEIA, or datasets compiled by theWorld Resources Institute (WRI) (IEA, 1998; Marland et al., 1994; Graedel et al., 1993; Olivier et al., 1999).
Emissions of a group of countries (e.g. Annex I, that is OECD countries and Economies in Transition in Central
and Eastern Europe) can be compared with regional totals of global inventories that were validated against
global, regional and zonal budgets. In particular when emission estimates differ substantially, the emission
factors used could be compared, in more detail, with the defaults that the IPCC Guidelines recommend. Fromthese evaluations conclusions can be drawn regarding comparability, applicability of defaults and countryspecificity. The same type of comparison as described for emissions can be done with the underlying activity
data in order to check completeness and as an order-of-magnitude check: these can be compared with de facto
independently compiled international statistics (e.g. maintained by IEA, UN, FAO, AFEAS). One should,
however, not always expect to find exact matches since the activity data used by the inventory compilation team
may be taken from different data source or different versions of it. This version will be different from theoriginal national data collected by these international organisations. For examples see Schipper et al. (1992).
However, when evaluating the results of these comparisons, it should be remembered that various data sources
are not always completely independent of each other. For example, EDGAR starts with IEA energy data tocalculate CO2 emissions from fuel combustion and CDIAC/GEIA start with UN energy data. In addition, even
the IEA and UN energy data are not completely independent. In order to avoid duplication of work, the IEA andthe United Nations have established a co-operation in data exchange, and receive common questionnaires forsome countries. Nevertheless, there are still differences in the data released by the two organisations due, interalia, to sources of data, methodology, revision in historical series, geographical coverage, etc.
Comparison of emission density indicators, such as emissions per capita, industrial emissions per unit of value
added, transport emissions per car, emissions from power generation per kWh of electricity produced etc.,
provides a quick indirect check and verification of the order of magnitude of the emissions. Of course, thecorrelation between emissions and an independent variable does not necessarily imply cause and effect.
However, it is an easy means to flag certain anomalies at country or sector level, if any. More examples forenergy indicators can be found in Schipper and Haas (1997) and Bossebeuf et al. (1997).
The cross-country comparison of data is relevant if the data are comparable. For the emission factor comparison,that can be possible on the basis of the sectoral background tables of the ‘Common Reporting Format’ (CRF). The
emission factors comparisons can be performed at different aggregation level as far as emission factors have to bereported at different level within the ‘Common Reporting Format’. Of course, cross-country comparisons ofemission factors can be processed as far as emission factor units are fixed, or unit conversion ratios are available.
From practical aspects, different kinds of comparison could be combined: for example, cross-country emission
factor comparison can be combined with historical trend by plotting in a single graph, for the different countries,
the reference year data (1990), the more recent year data, and the minimum and maximum value, for each source
sector and possible aggregations and according to the fuel types when relevant (see Figure 2). Another practicalexample of combined emission factor comparison is the combination with estimated uncertainties whenavailable. In this case, one could plot a single graph for the different countries, the current year emission factor
and the related uncertainty range, for a given source sector and according to the fuel types that are relevant. This
combined comparison including uncertainties is quite important as far as emission factor discrepancies analysis
and checks require complementary information on uncertainty, to be more relevant (Figure 2). Thus, from thecomparisons of the implied emission factors reported to UNFCCC (as proposed in the ‘Common Reporting
Format’, CRF), if some national emission factors appear to be outliers, further comparison could be made bychecking with those used by apparently similar countries. Furthermore, comparison with the recommended IPCC
Tier I default values and with literature values may be informative in establishing the comparability or thecountry-specificity of the emission factors used.

Checks and Verification at National and International Levels

535

Background Paper

Figure 2

Example: Graph for an inter-country comparison ofemission factor uncertainties

Emissionfactors anduncertainty
ranges(unit)

Sector/sub-sector :xxx
Pollutant :xxx

Year :xxx

country1 country2 country3 country4 country5 country6

countries

N.B. : the E.F. range for a given country relates here to the uncertainty range of the current E.F.

As for emission factors, the cross-country comparison of activities requires a harmonised reporting format as the‘Common Reporting Format'. But due to country ‘volume’ effect, apparent activity discrepancies from such
crude comparisons, are not really significant. So on the basis of the CRF and the basis of common comparable
indicators to be chosen, activity density indicators can be defined, for the purpose of international comparison(e.g., activity rate per inhabitant, per employee, per unit of GDP, per number of households or per number ofvehicles, etc., according to the source sectors).
The different levels of comparison will also assist in evaluating the estimated uncertainty estimates of national
inventories as well as of global emission inventories, especially by checking for any group bias and by the sizeof the existing differences at country level.

4.1.2

Comparisons with atmospheric measurements atregional and global scale

Evidently, methods for national and international scale do not differ by definition. Comparisons which are usefulon the national scale may also be applied internationally (see Section 3 for details). The difference is that at thisscale there are increasing possibilities to concentrate on source regions rather than borderline dependent areas.
Methods that are otherwise only valid in large countries may safely be applied here. Additional options become
available on the international scale:•Continental plumeA strong difference between source and non-source (sink) regions may generally be found between
continent and sea. Routine measurements may be performed close to an ocean, at offshore islands, or on
ships. In evaluation one may consider the difference between clean background air and the polluted plume,
taking advantage of wind sector analysis or trajectory analysis. In European continental plume a number ofgreenhouse gases, including CFCs, N2O and CH4, has been detected at Mace Head, Ireland. The results havebeen used for subsequent quantification of the European emission source strength (Derwent et al., 1998a,b;Vermeulen et al., 1999). For quantification, an inverse modelling procedure is performed.

•

Satellite observation
Satellite observations allow retrieving a quasi-continuous concentration profile for all of the globe. The
method is still in its infancy, even if specific instruments have already been designed to collect data on
climate change gases. A sensor currently active is GOME, which has been validated recently to detect total
columns of O3, NO2, BrO, HCHO and OClO (Goede et al., 2000). In the near future, SCIAMACHY will belaunching a passive spectrometer observing absorption in UV, visible and NIR spectral ranges. It will be

536

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Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories

able to yield concentrations of O3, NO2, N2O, CO, CO2, CH4 both in the troposphere and stratosphere.
Maximum horizontal resolution will be 30 km x 60 km. Thus it seems reasonable to assume that plumes
may be detected at different scales.
•

Global dynamic approaches
Concentration trends of compounds also indicate the result of a discrepancy between sources and sinks. Fromsuch trends, conclusions on either of these two may be drawn, once the other is considered fixed. Such approaches
have been taken for methane (Dlugokencky et al., 1994) and SF6 (Maiss and Brenninkmeijer, 1998).

The obvious advantage of the methods discussed above is that a large share of global emissions is covered, andmonitoring is possible on a routine basis. However, it is almost impossible to trace back to individual sources or source
sectors, if their emissions do not contain some sort of ‘fingerprint’. This may be a specific type of carbon isotope incase of CO2 and CH4 emissions from fossil fuels, or typical temporal profile (seasonality or diurnal variation) or zonal
variation (for example, latitudinal distribution), that enables us to distinguish them from other sources.

4.1.3

Comparisons of uncertainty estimates of data reported
to UNFCCC

The reporting format for uncertainty estimates has been described in the Chapter ‘Quantifying uncertainties inpractice’ in IPCC (2000). Countries will submit uncertainty estimates by source or sink categories for eachcompound given. An international comparison of the figures submitted may be performed on the basis of relative
uncertainties (as percentage).
The next steps to be taken are as follows:•

Check for each category/compound combination the uncertainty given by the individual country. Values
with unusual low uncertainty associated with their emissions should be checked individually for consistencyof their reporting;•

Check/calculate total uncertainty of a country for a given compound, and•Check consistency of given number/uncertainty with verification measurement/uncertainty.

4.2

Scientific publications

In the scientific literature, there may be publications providing other estimates of national emissions or publications inwhich the quality of the official national inventory is analysed. Comparison of these different national estimates andthe results of those analyses are important elements of a critical check of the quality of the official national inventory,
which can be used when comparing or integrating the greenhouse gas emissions of various countries.

4.3

Evaluation of global or regional budgets andsource strengths

Confronting summed official inventories with global inventories and with global or regional emission levels
established as part of a total budget analysis is a means either to update global budgets or to provide feedback tonational inventory developers and IPCC TSU on Inventories on apparent biases. Provided that sufficient
information is available on spatial and temporal distribution of the sources, including the natural ones, one may
be able to draw conclusions on the likely biases in specific major sources, if these have specific own spatial or
temporal characteristics, that helps distinguishing them form others (Heimann, 1996, for CO2; Janssen et al.,1999, for CH4; Bouwman and Taylor, 1996, for N2O). This type of evaluation is the ultimate verification ofbottom-up compiled emission estimates since at the global level all emissions are part of a big chain of material
flows from sources to sinks.

4.4

Updating IPCC reports

Comparison of emission factors submitted by countries and the methodologies used with defaults recommended
by the current IPCC Guidelines and comparison of reported emissions with figures currently used in thescientific literature could also provide important input to revisions of the following sections of IPCC reports:

Checks and Verification at National and International Levels

537

Background Paper•

Evaluation and updating of defaults methods and emission factors recommended in the IPCC Guidelines(IPCC, 1996) (for example by comparing sets of nationally applied emission factors with recommended
IPCC default values), and•Evaluation of global or regional budgets compiled by IPCC Working Group I (WG I), as discussed andpublished by the scientific community (IPCC, 2001).

5

WORKING PROCEDURES, PRIORITISATION
AND REPORTING FORMAT AT THE
NATIONAL LEVEL

5.1

Phases and prioritised national approachThis paper describes many concrete options for checks and verification, some of which are very easy to carryout, others are costly and difficult to implement:•

Immediately available procedures (efficient ones for quick checks; priorities for checking and verifying bothlarge and fast changing components) using national data only;•

Procedures using available international data, and•Procedures to be developed (more elaborated verification, for example direct source testing or comparison
with atmospheric concentration measurements).

Thus, there is a clear need for guidelines to decide how much time and money should be devoted to checking andverification versus the effort to be put in the basic compilation process (data gathering, calculations,recalculations, uncertainty estimates, reporting).
Evidently, a number of key basic checks should be routinely incorporated at the appropriate stage in thecompilation process. For more guidelines on the procedure, we refer to the Chapter ‘QA/QC of inventory
systems’ in IPCC (2000). Here we point out, that the detailed level of checks and verification will be laid out in
the QA/QC plan. Those checks will be important on the performance of those sources that apparently contribute
substantially to the national emission control programme. In other words, it is recommended that the monitoringof actual emissions as described in the national inventory will be checked for its credibility. Checks involving
international data may be applied in more detail for a one-time verification of the inventory; in subsequent years
there will be no need for an extensive check of this kind, except for special sector-gas combinations that have atthat time particular importance for the country.
For the more elaborate verification activities based on atmospheric concentration measurements, a semicontinuous and internationally co-ordinated research programme ‘at the background’ is recommended, aiming atverification at national and international scale. Besides tests of aggregation to the global level and comparison
with alternatively established budgets, this is the only really independent method for verifying emissions andchecking for major systematic biases. Direct source testing should be carried out as part of an overall programmeof reducing uncertainties in the total greenhouse gas inventory. Priority setting will be a function of costs, time,and share in total and sector emissions, both in CO2-eq. and per gas.

5.2

Defining the national procedures on checks
and verification

The inventory update programme has different components, each of which will require different types of checks:•

Existing historical inventory in place;•

New additions to the inventory (new years, possibly new sources to be applied also to previous years);•

Finalisation of preliminary data;•

Adjustments to the existing inventory (including recalculation of the historical inventory, and•Conclusions for prioritising future activities (short term and longer term).

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Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories

In order to minimise the required resources, quality checks and verifications should solely be applied where they
have not been used previously, i.e. mostly to new data. If the existing historical inventory is left as is, no further
checks (or QA/QC programme) are required to confirm this component of the inventory. Thus, apart from a onetime thorough checking of the existing historical inventory, the system would require the following activities tobe performed:
1.

Comparison of trends and previous reported data (see Section 3.2.1);

2.

Checking for methodological changes (see Section 3.2.2);

3.

Order-of-magnitude checks (see Section 3.2.3);

4.

Reference calculations (see Section 3.2.4);

5.

Scientific publications or external review (if available: see Section 3.3.4), and6.

Setting priorities for future inventory improvement, including re-evaluation of uncertainties if necessary(based on results of activities above; see Section 5.1).

As a separate item, verification activities should be performed, focussing either on large sources or on sources
with a large uncertainty as follows:1.

Comparisons of indicators;

2.

Comparisons with other independent estimates, and3.

Comparison with atmospheric concentration measurements.

Priority setting may be (a) to apply the first two methods for the initial inventory (and to updates forconfirmation of trends), and (b) to apply the third method periodically for ground truth verification of absoluteemission levels and emission trends.

5.3

Reporting format for national checking andverification activities

Besides annual submission of the annual inventory and associated uncertainty estimate, it is recommended that aseparate annual report be published and submitted describing for each of the activities described in Section 5.2:•

What has been checked and verified and why was that selected and how was the QC done;•

Feedback from external reviews: summary of key comments, their origin and actions taken;•

Results: findings and correction of the inventory, and•Recommendations for inventory improvements.

It is also considered Good Practice that as a separate report a description is available (for the public, external reviews
and to other Parties to the UNFCCC) of how the QC activities are structured and embedded in the QA system.

6

INTERNATIONAL ACTIVITIES ON CHECKSAND VERIFICATION

Possible activities executed by or encouraged by UN bodies, governments, scientific community, NGOs, IPCC
WG I and the IPCC TSU on National Greenhouse Gas Inventories are:•Public review of national inventories by comparison with other estimates, scientific publications,information available from the UNFCCC Secretariat, inter-country comparisons;•Evaluation and updating of defaults methods and emission factors recommended in the IPCC Guidelines on
Greenhouse Gas Inventories, and•Evaluation of global or regional budgets by the scientific community and IPCC WG I, respectively.

Building up a system for emission verification on the international scale will consist of three stages:

Checks and Verification at National and International Levels

539

Background Paper•

Exploring the possibilities of integrating existing networks (e.g. WMO’s Global Atmospheric Watch
programme; the above-mentioned satellite information) into a global network on international greenhousegas emission monitoring;•

Identifying gaps and further needs to a global network and setting up of missing monitoring sites, and•Development and use of global models to evaluate and interpret measurements.

Work on this subject may be done by individual organisations or as a concerted action, for example under theencouragement of policy organisations, by a group of cooperating institutes or coordinated into international
research programmes (for example of IGBP/IGAC).
Alternatively, an international institution or organisation may be entrusted to handle measurement and evaluation
programmes concerning emission verification. The mission of such an institution may also be extended towards
scenario analyses using models. It may be operated under the auspices of IPCC. A successful example of such akind of institution is the European Monitoring and Evaluation Programme, EMEP. Like EMEP, a number ofmonitoring sites should be operated by the individual countries, which then undergo vigorous quality control
procedures in order to validate measurement data. This quality test is organised and run by the central institution.
The measurement and validation programme, as much as the modelling efforts, are continuously being reviewed
and improved. It will be the task of this institution to confirm reported emission data or to identify missing
elements using their knowledge on emissions.
This proposed institution would then be responsible for the continuous monitoring and the evaluation of thismonitoring. While it will not (or with great difficulty) be possible to identify single outlying sources, an
overview on the general agreement of the emission estimations to the scientific understanding of the processes
involved will be achieved.
The role of the scientific community is to take advantage of the data collected at this institution, but at the sametime use it to challenge their conclusions, in order to further improve possibilities for emission verification. As this
topic is fairly new, it may be expected that significant improvements to the techniques described in the previous
sections are to be made in the near future, which should be taken up in the routine process as quickly as possible.

7

CONCLUSIONS

Ample opportunities exist for validation (checking) and verifying national inventories. Many options areavailable at national level, by national teams, ranging from very basic checks to more elaborated verification
activities. In addition, specific options are available at the international level, e.g. inter-country comparisons ofemission factors and comparisons with independently compiled datasets (global emission inventories andinternational statistics) or more scientifically oriented ones. An internationally co-ordinated approach of theinternational options seems the most efficient way for performing the latter activities, both for the basic
comparisons as well as for the more fundamental verification activities. Procedural arrangements of checks andverification activities within the quality system for compiling the national inventories, including priority setting
and reporting requirements, are key to establish and guarantee the credibility of the national inventories in termsof data quality objectives. These have been summarised by the UNFCCC guidelines for preparing and reporting
national greenhouse gas inventories as accuracy, consistency, completeness and comparability.

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Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories

ANNEX IEXAMPLES OF EMISSION COMPARISONS

It is recommended that emission comparisons be performed for each source category as standard QC protocol.
The objective of the emission comparisons is to ensure that the emission values are not wildly improbable or thatthey fall within a range that is considered reasonable. These are often referred to as reality checks. The goal is to
identify large mistakes before the inventory process has advanced to its final stages. Also, emission checks canlead to re-evaluations of emission factor and activity data if the estimates seem unreasonable.
One of the most efficient and effective emission checks for large-scale inventories is that based on comparisonsof emission values. Comparison checks are often used at later stages of review as well, for verification andvalidation purposes, but it is important to include them as QC checks as early as possible so that errors inemission estimates can be detected. There are basically four kinds of comparison checks:•

Historical comparisons to past inventories;•

Comparison of estimates based on different methodologies;•

Comparison of estimates from different inventory areas, and•Comparison of estimates derived from atmospheric measurements.

Historical comparisons should be used as standard QC checks of estimated emission quantities. A historicalcomparison simply means to check the current inventory estimates against those from a previous year’s
inventory. This type of comparison is relatively easy to accomplish and can be a very effective way to check forgross errors in the estimated emissions. It is particularly applicable in cases where methodologies have notchanged since the calculated emissions should be within the same order of magnitude barring any significant
changes in activity or practices. Historical comparisons can also be used to check for expected trends in emission
estimates. If, for example, there is a trend of emission reductions for a given source in the years prior to thecurrent inventory and this trend is broken by a spiked increase in the current year’s estimates, this should prompt
further investigation as to why the trend has shifted so dramatically.
Method-based comparisons can be made depending on whether the emissions for the source category were
determined using a top-down or bottom-up approach. For example, if N2O estimates for nitric acid production
were determined using a bottom-up approach (meaning emissions estimates were determined for each individual
production plant based on plant-specific data), the emissions check would consist of comparing the sum of theindividual plant-level emissions to a top-down emission estimate based on national nitric acid production figuresand default factors. If significant discrepancies are found in the comparison, further investigation would benecessary to answer the following questions:•

Are there inaccuracies associated with any of the individual plant estimates, for example an extreme outlier
may be accounting for an unreasonable quantity of emissions)?

•

Are the plant-specific emission factors significantly different from one another?

•

Are the plant-specific production rates consistent with published national level production rates?

•

Is there any other explanation for a significant difference, such as the effect of controls, the manner in which
production is reported or possibly undocumented assumptions?

This is an example of how the result of a relatively simple emission check can lead to a more intensive
investigation of the accuracy of emissions data. It is at this point where someone knowledgeable in the source
category may be able to isolate the parameter that is causing the difference and make a decision on whether it
points to an actual error or not.
Another recommended comparison is checking the emissions from your national inventory to the emissions forthe same source category from a similar country or region. Again, knowledge of the source category and how it
may be similar to another country is critical for this check. For example, if solid waste management practices are
similar between two countries, it may be possible to compare their estimated methane emissions from landfills.
This comparison can be made with a country that uses the same landfill methane estimation method and alsowith a country that uses a different estimation method. A relative adjustment for the quantity of waste can be
accounted for before comparisons are made. A significant discrepancy can be studied to determine if it
represents an error in the calculation or actual differences due to methods or other influencing factors.
Another emissions comparison check involves using estimates based on atmospheric measurements. Somecountries have access to regional atmospheric measurements for their inventory areas. Emission estimates can bederived for various GHG pollutants from these atmospheric measurements and then compared to the inventory
estimates for significant source categories. This approach has been utilised on a global scale to verify global
GHG emission estimates with IPCC global budgets (Lim, Boileau, et al.). It can also be applied on a national, or

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local inventory level for specific source categories. For example, estimated SF6 emissions from a national
inventory could be compared to estimates derived from atmospheric measurements of SF6 for the inventory area.
This type of comparison would provide an order-of-magnitude check on the estimated emissions.
Comparison checks to other inventory areas can be extremely useful and efficient, especially where they allow
cross-method comparisons (for example., if one country used a top-down approach and another used a bottom-up
approach). Also, for source categories where there is an issue of confidentiality associated with estimatedemissions, or where there are no alternative methods available to estimate emissions, comparison checks to otherinventory areas or to estimates derived from atmospheric measurements can be the only means to get an initial
indication of whether emissions have been correctly calculated for a source category or not.
Another emission check can be used for source categories that rely on empirical formulas for the calculation ofemissions. Where such formulas are used, final calculated emission quantities should follow stochiometric ratios
and conserve energy and mass according to the calculation formula. For example, in estimating emissions frommanure management, the total quantity of methane produced should not exceed the quantity that could be
expected based on the carbon content in the volatile solids of the manure. Similar checks would apply to fuelcombustion sources where there should not be more CO2 produced than would be expected from the carbon
content of the fuel. Mass and energy balance checks such as this should be used in all cases where emissions arealgorithmic conversions.

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