QUALITY ASSURANCE AND QUALITY CONTROL
INTRODUCTION
An important goal of IPCC good practice guidance is to support the development of national greenhouse gas inventories that can be readily assessed in terms of quality and completeness. It is good practice to implement quality assurance and quality control (QA/QC) procedures in the development of national greenhouse gas inventories to accomplish this goal. This guidance establishes good practice consistent with the Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories (IPCC Guidelines). The QA/QC good practice guidance outlined here reflects practicality, acceptability, cost-effectiveness, existing experience, and the potential for application on a worldwide basis. A QA/QC programme contributes to the objectives of good practice guidance, namely to improve transparency, consistency, comparability, completeness, and confidence in national inventories of emissions estimates.
The outcomes of the QA/QC process may result in a reassessment of inventory or source category uncertainty estimates. For example, if data quality is found to be lower than previously thought and this situation cannot be rectified in the timeframe of the current inventory, the uncertainty estimates ought to be re-evaluated.
The terms ‘quality control’ and ‘quality assurance’ are often used incorrectly. The definitions of QC and QA in
DEFINITION OF QA/QC
Quality Control (QC) is a system of routine technical activities, to measure and control the quality
of the inventory as it is being developed. The QC system is designed to:
(i) Provide routine and consistent checks to ensure data integrity, correctness, and completeness;
(ii) Identify and address errors and omissions;
(iii) Document and archive inventory material and record all QC activities. QC activities include general methods such as accuracy checks on data acquisition and calculations and the use of approved standardised procedures for emission calculations, measurements, estimating uncertainties, archiving information and reporting. Higher tier QC activities include technical reviews of source categories, activity and emission factor data, and methods.
Quality Assurance (QA) activities include a planned system of review procedures conducted by personnel not directly involved in the inventory compilation/development process. Reviews, preferably by independent third parties, should be performed upon a finalised inventory following the implementation of QC procedures. Reviews verify that data quality objectives were met, ensure that the inventory represents the best possible estimates of emissions and sinks given the current state of scientific knowledge and data available, and support the effectiveness of the QC programme. Before implementing QA/QC activities, it is necessary to determine which techniques should be used, and where and when they will be applied. There are technical and practical considerations in making these decisions. The technical considerations related to the various QA/QC techniques are discussed in general in this chapter, and specific applications to source categories are described in the source category-specific good practice guidance. The practical considerations involve assessing national circumstances such as available resources and expertise and the particular characteristics of the inventory. The level of QA/QC activities should be compatible with the methods or tiers used to estimate emissions for particular source categories. In addition,
resources should be focused on priority areas, such as the key source
PRACTICAL CONSIDERATIONS IN DEVELOPING QA/QC SYSTEMS
Implementing QA/QC procedures requires resources, expertise and time. In developing any QA/QC system, it is expected that judgements will need to be made on the following:
• Resources allocated to QC for different source categories and the compilation process;
• Time allocated to conduct the checks and reviews of emissions estimates;
• Availability and access to information on activity data and emission factors, including data quality;
• Procedures to ensure confidentiality of inventory and source category information, when required;
• Requirements for archiving information;
• Frequency of QA/QC checks on different parts of the inventory;
• The level of QC appropriate for each source category;
• Whether increased effort on QC will result in improved emissions estimates and reduced uncertainties;
• Whether sufficient expertise is available to conduct the checks and reviews.
In practice, the QA/QC system is only part of the inventory development process and inventory agencies do not have unlimited resources. Quality control requirements, improved accuracy and reduced uncertainty need to be balanced against requirements for timeliness and cost effectiveness. A good practice system seeks to achieve that balance and to enable continuous improvement of inventory estimates. Within the QA/QC system, good practice provides for greater effort for key source categories and for those source categories where data and methodological changes have recently occurred, than for other source categories. It is unlikely that inventory agencies will have sufficient resources to conduct all the QA/QC procedures outlined in this chapter on all source categories. In addition, it is not necessary to conduct all of these
procedures every year. For example, data collection processes conducted by national statistical agencies are not likely to change significantly from one year to the next. Once the inventory agency has identified what quality controls are in place, assessed the uncertainty of that data, and documented the details for future inventory reference, it is unnecessary to revisit this aspect of the QC procedure every year. However, it is good practice to check the validity of this information periodically as changes in sample size, methods of collection, or frequency of data collection may occur. The optimal frequency of such checks will depend on national circumstances. While focusing QA/QC activities on key source categories will lead to the most significant improvements in the overall inventory estimates, it is good practice to plan to conduct at least the general procedures outlined in Section 8.6, General QC Procedures (Tier 1), on all parts of the inventory over a period of time. Some source categories may require more frequent QA/QC than others because of their significance to the total inventory estimates, contribution to trends in emissions over time or changes in data or characteristics of the source category, including the level of uncertainty. For example, if technological advancements occur in an industrial source category, it is good practice to conduct a thorough QC check of the data sources and the compilation process to ensure that the inventory methods remain appropriate. It is recognised that resource requirements will be higher in the initial stages of implementing any QA/QC ystem than in later years. As capacity to conduct QA/QC procedures develops in the inventory agency and in other associated organisations, improvements in efficiency should be expected.
General QC procedures outlined in Table 8.1, Tier 1 General Inventory Level QC Procedures, and a peer review of the inventory estimates are considered minimal QA/QC activities for all inventory compilations. The general procedures require no additional expertise in addition to that needed to develop the estimates and compile the inventory and should be performed on estimates developed using Tier 1 or higher tier methods for source categories. A review of the final inventory report by a person not involved in the compilation is also good practice, even if the inventory were compiled using only Tier 1 methods. More extensive QC and more rigorous review processes are encouraged if higher tier methods have been used. Availability of appropriate expertise may limit the degree of independence of expert reviews in some cases. The QA/QC process is intended to ensure transparency and quality.
There may be some inventory items that involve confidential information, as discussed in Chapters 2 to 5. The inventory agency should have procedures in place during a review process to ensure that reviewers respect that confidentiality.
ELEMENTS OF A QA/QC SYSTEM
The following are the major elements to be considered in the development of a QA/QC system to be
implemented in tracking inventory compilation:
• An inventory agency responsible for coordinating QA/QC activities;
• A QA/QC plan;
• General QC procedures (Tier 1);
• Source category-specific QC procedures (Tier 2);
• QA review procedures;
• Reporting, documentation, and archiving procedures.
For purposes of the QA/QC system, the Tier 2 QC approach includes all procedures in Tier 1 plus additional source category-specific activities.
INVENTORY AGENCY
The inventory agency is responsible for coordinating QA/QC activities for the national inventory. The inventory
agency may designate responsibilities for implementing and documenting these QA/QC procedures to other
agencies or organisations. The inventory agency should ensure that other organisations involved in the
preparation of the inventory are following applicable QA/QC procedures.
The inventory agency is also responsible for ensuring that the QA/QC plan is developed and implemented. It is
good practice for the inventory agency to designate a QA/QC coordinator, who would be responsible for
ensuring that the objectives of the QA/QC programme are implemented.
QA/QC PLAN
A QA/QC plan is a fundamental element of a QA/QC system, and it is good practice to develop one. The plan
should, in general, outline QA/QC activities that will be implemented, and include a scheduled time frame that
follows inventory preparation from its initial development through to final reporting in any year. It should
contain an outline of the processes and schedule to review all source categories.
The QA/QC plan is an internal document to organise, plan, and implement QA/QC activities. Once developed, it
can be referenced and used in subsequent inventory preparation, or modified as appropriate (i.e. when changes in
processes occur or on advice of independent reviewers). This plan should be available for external review.
In developing and implementing the QA/QC plan, it may be useful to refer to the standards and guidelines
published by the International Organization for Standardization (ISO), including the ISO 9000 series (see Box
ISO AS A DATA QUALITY MANAGEMENT SYSTEM
The International Organization for Standardization (ISO) series programme provides standards for
data documentation and audits as part of a quality management system. Though the ISO series is
not designed explicitly for emissions data development, many of the principles may be applied to
ensure the production of a quality inventory. Inventory agencies may find these documents useful
source material for developing QA/QC plans for greenhouse gas inventories. Some countries (e.g.
the
standards for their inventory development process and data management.
The following standards and guidelines published under the ISO series may supplement source
category-specific QA/QC procedures for inventory development and provide practical guidance
for ensuring data quality and a transparent reporting system.
ISO 9004-1: General quality guidelines to implement a quality system.
ISO 9004-4: Guidelines for implementing continuous quality improvement within the
organisation, using tools and techniques based on data collection and analysis.
ISO 10005: Guidance on how to prepare quality plans for the control of specific projects.
ISO 10011-1: Guidelines for auditing a quality system.
ISO 10011-2: Guidance on the qualification criteria for quality systems auditors.
ISO 10011-3: Guidelines for managing quality system audit programmes.
ISO 10012: Guidelines on calibration systems and statistical controls to ensure that
measurements are made with the intended accuracy.
ISO 10013: Guidelines for developing quality manuals to meet specific needs.
Source: http://www.iso.ch/
GENERAL QC PROCEDURES (TIER 1)
The focus of general QC techniques is on the processing, handling, documenting, archiving and reporting
procedures that are common to all the inventory source categories. Table 8.1, Tier 1 General Inventory Level QC Procedures, lists the general QC checks that the inventory agency should use routinely throughout the preparation of the annual inventory. Most of the checks shown in Table 8.1 could be performed by cross-checks, recalculation, or through visual inspections. The results of these QC activities and procedures should be documented as set out in Section 8.10.1, Internal Documentation and Archiving, below. If checks are performed electronically, these systems should be periodically reviewed to ensure the integrity of the checking function. It will not be possible to check all aspects of inventory input data, parameters and calculations every year. Checks may be performed on selected sets of data and processes, such that identified key source categories are considered every year. Checks on other source categories may be conducted less frequently. However, a sample of data and calculations from every sector should be included in the QC process each year to ensure that all sectors are addressed on an ongoing basis. In establishing criteria and processes for selecting the sample data sets and processes, it is good practice for the inventory agency to plan to undertake QC checks on all parts of the inventory over an appropriate period of time.
TIER 1 GENERAL INVENTORY LEVEL QC PROCEDURES
QC Activity Procedures
Check that assumptions and criteria for the selection of activity data and emission factors are documented.
• Cross-check descriptions of activity data and emission factors with information on source categories and ensure
that these are properly recorded and archived. Check for transcription errors in data input and reference
• Confirm that bibliographical data references are properly cited in the internal documentation.
• Cross-check a sample of input data from each source category (either measurements or parameters used in calculations) for transcription errors. Check that emissions are calculated correctly.
• Reproduce a representative sample of emissions calculations.
• Selectively mimic complex model calculations with abbreviated calculations to judge relative accuracy. Check that parameter and emission units are correctly recorded and that appropriate conversion factors are used.
• Check that units are properly labelled in calculation sheets.
• Check that units are correctly carried through from beginning to end of calculations.
• Check that conversion factors are correct.
• Check that temporal and spatial adjustment factors are used correctly. Check the integrity of database files.
• Confirm that the appropriate data processing steps are correctly represented in the database.
• Confirm that data relationships are correctly represented in the database.
• Ensure that data fields are properly labelled and have the correct design specifications.
• Ensure that adequate documentation of database and model structure and operation are archived. Check for consistency in data between source categories.
• Identify parameters (e.g. activity data, constants) that are common to multiple source categories and confirm that here
is consistency in the values used for these parameters in the emissions calculations. Check that the movement of nventory data among processing steps is correct.
• Check that emissions data are correctly aggregated from lower reporting levels to higher reporting levels when
preparing summaries.
• Check that emissions data are correctly transcribed between different intermediate products.
TIER 1 GENERAL INVENTORY LEVEL QC PROCEDURES
QC Activity Procedures
Check that uncertainties in emissions and removals are estimated or calculated correctly.
• Check that qualifications of individuals providing expert judgement for uncertainty estimates are appropriate.
• Check that qualifications, assumptions and expert judgements are recorded. Check that calculated uncertainties are complete and calculated correctly.
• If necessary, duplicate error calculations or a small sample of the probability distributions used by
analyses. Undertake review of internal documentation.
• Check that there is detailed internal documentation to support the estimates and enable duplication of the emission
and uncertainty estimates.
• Check that inventory data, supporting data, and inventory records are archived and stored to facilitate detailed review.
• Check integrity of any data archiving arrangements of outside organisations involved in inventory preparation.
Check methodological and data changes resulting in recalculations.
• Check for temporal consistency in time series input data for each source category.
• Check for consistency in the algorithm/method used for calculations throughout the time series. Undertake completeness checks.
• Confirm that estimates are reported for all source categories and for all years from the appropriate base year to the
period of the current inventory.
• Check that known data gaps that result in incomplete source category emissions estimates are documented.
Compare estimates to previous estimates.
• For each source category, current inventory estimates should be compared to previous estimates. If there are
significant changes or departures from expected trends, recheck estimates and explain any difference.
should be applied irrespective of the type of data used to develop the inventory
estimates and are equally applicable to source categories where default values or national data are used as the basis for the estimates. In some cases, emissions estimates are prepared for the inventory agency by outside consultants or agencies. The inventory agency should ensure that the QC checks listed in Table 8.1, Tier 1 General Inventory Level QC Procedure, are communicated to the consultants/agencies. This will assist in making sure that QC procedures are performed and recorded by the consultant or outside agency. The inventory agency should review these QA/QC activities. In cases where official national statistics are relied upon – primarily for activity data – QC procedures may already have been implemented on these national data. However, it is good practice for the inventory agency to confirm that national statistical agencies have implemented adequate QC procedures equivalent Due to the quantity of data that needs to be checked for some source categories, automated checks are encouraged where possible. For example, one of the most common QC activities involves checking that data keyed into a computer database are correct. A QC procedure could be set up to use an automated range check (based on the range of expected values of the input data from the original reference) for the input values as recorded in the database. A combination of manual and automated checks may constitute the most effective procedures in checking large quantities of input data.
SOURCE CATERGORY-SPECIFIC QC PROCEDURES (TIER 2)
In contrast to general inventory QC techniques, source category-specific QC procedures are directed at specific types of data used in the methods for individual source categories and require knowledge of the emission source category, the types of data available and the parameters associated with emissions.
It is important to note that Tier 2 source category-specific QC activities are in addition to the general QC
conducted as part of Tier 1 (i.e. include QC checks listed in Table 8.1). The source category-specific measures are applied on a case-by-case basis focusing on key source categories (see Chapter 7, Methodological Choice and Recalculation) and on source categories where significant methodological and data revisions have taken place. It is good practice that inventory agencies applying higher tier methods in compiling national inventories utilise Tier 2 QC procedures. Specific applications of source category-specific Tier 2 QC procedures are provided in the energy, agriculture, industrial processes and waste chapters of this report.
Source category-specific QC activities include the following:
• Emission data QC;
• Activity data QC;
• QC of uncertainty estimates.
The first two activities relate to the types of data used to prepare the emissions estimates for a given source
category. QC of uncertainty estimates covers activities associated with determining uncertainties in emissions
estimates (for more information on the determination of these uncertainties, see Chapter 6, Quantifying
Uncertainties in Practice).
The actual QC procedures that need to be implemented by the inventory agency will depend on the method used
to estimate the emissions for a given source category. If estimates are developed by outside agencies, the
inventory agency may, upon review, reference the QC activities of the outside agency as part of the QA/QC plan.
There is no need to duplicate QC activities if the inventory agency is satisfied that the QC activities performed
by the outside agency meet the minimum requirements of the QA/QC plan.
Emissions data QC
The following sections describe QC checks on IPCC default factors, country-specific emission factors, and direct
emission measurements from individual sites (used either as the basis for a site-specific emission factor or
directly for an emissions estimate). Emission comparison procedures are described in Section 8.7.1.4, Emission
Comparisons. Inventory agencies should take into account the practical considerations discussed in Section 8.2,
Practical Considerations in Developing QA/QC Systems, when determining what level of QC activities to
undertake.
IPCC DEFAULT EMISSION FACTORS
Where IPCC default emission factors are used, it is good practice for the inventory agency to assess the
applicability of these factors to national circumstances. This assessment may include an evaluation of national
conditions compared to the context of the studies upon which the IPCC default factors were based. If there is
insufficient information on the context of the IPCC default factors, the inventory agency should take account of
this in assessing the uncertainty of the national emissions estimates based on the IPCC default emission factors.
For key source categories, inventory agencies should consider options for obtaining emission factors that are
known to be representative of national circumstances. The results of this assessment should be documented.
If possible, IPCC default emission factor checks could be supplemented by comparisons with national site or
plant-level factors to determine their representativeness relative to actual sources in the country. This
supplementary check is good practice even if data are only available for a small percentage of sites or plants.
COUNTRY-SPECIFIC EMISSION FACTORS
Country-specific emission factors may be developed at a national or other aggregated level within the country
based on prevailing technology, science, local characteristics and other criteria. These factors are not necessarily
site-specific, but are used to represent a source category or sub-source category. Two steps are necessary to
ensure good practice emission factor QC for country-specific factors.
The first is to perform QC checks on the data used to develop the emission factors. The adequacy of the emission factors and the QA/QC performed during their development should be assessed. If emission factors were developed based on site-specific or source-level testing, then the inventory agency should check if the measurement programme included appropriate QC procedures.
Frequently, country-specific emission factors will be based on secondary d ta sources, such as published studies or other literature.1 In these cases, the inventory agency could attempt to determine whether the QC activities conducted during the original preparation of the data are consistent with the applicable QC procedures outlined in Table 8.1 and whether any limitations of the secondary data have been identified and documented. The inventory agency could also attempt to establish whether the secondary data have undergone peer review and record the scope of such a review.
If it is determined that the QA/QC associated with the secondary data is adequate, then the inventory agency can simply reference the data source for QC documentation and document the applicability of the data for use in emissions estimates.
If it is determined that the QA/QC associated with the secondary data is inadequate, then the inventory agency hould attempt to have QA/QC checks on the secondary data established. It should also reassess the uncertainty of any emissions estimates derived from the secondary data. The inventory agency may also reconsider how the data are used and whether any alternative data, (including IPCC default values) may provide a better estimate of emissions from this source category.
Second, country-specific factors and circumstances should be compared with relevant IPCC default factors and the characteristics of the studies on which the default factors are based. The intent of this comparison is to determine whether country-specific factors are reasonable, given similarities or differences between the national source category and the ‘average’ source category represented by the defaults. Large differences between country-specific factors and default factors should be explained and documented.
A supplementary step is to compare the country-specific factors with site-specific or plant-level factors if these are available. For example, if there are emission factors available for a few plants (but not enough to support a bottom-up approach) these plant-specific factors could be compared with the aggregated factor used in the inventory. This type of comparison provides an indication of both the reasonableness of the country-specific factor and its representativeness.
DIRECT EMISSION MEASUREMENTS
Emissions from a source category may be estimated using direct measurements in the following ways:
• Sample emissions measurements from a facility may be used to develop a representative emission factor for that individual site, or for the entire category (i.e. for development of a national level emission factor);
• Continuous emissions monitoring (CEM) data may be used to compile an annual estimate of emissions for a particular process. In theory, CEM can provide a complete set of quantified emissions data across the
inventory period for an individual facility process, and does not have to be correlated back to a process
parameter or input variable like an emission factor. Regardless of how direct measurement data are being used, the inventory agency should review the processes and check the measurements as part of the QC activities. Use of standard measurement methods improves the consistency of resulting data and knowledge of the statistical properties of the data. If standard reference methods for measuring specific greenhouse gas emissions (and removals) are available, inventory agencies should encourage plants to use these. If specific standard methods are not available, the inventory agency should confirm whether nationally or internationally recognized standard methods such as ISO 10012 are used for measurements and whether the measurement equipment is calibrated and maintained properly. For example, ISO has published standards that specify procedures to quantify some of the performance characteristics of all air quality measurement methods such as bias, calibration, instability, lower detection limits, sensitivity, and upper limits of measurement (ISO, 1994). While these standards are not associated with a 1 Secondary data sources refer to reference sources for inventory data that are not designed for the express purpose of inventory development. Secondary data sources typically include national statistical databases, scientific literature, and other studies produced by agencies or organisations not associated with the inventory development.
EMISSION COMPARISONS
It is standard QC practice to compare emissions from each source category with emissions previously providedfrom the same source category or against historical trends and reference calculations as described below. The objective of these comparisons (often referred to as ‘reality checks’) is to ensure that the emission values are not wildly improbable or that they fall within a range that is considered reasonable. If the estimates seem unreasonable, emission checks can lead to a re-evaluation of emission factors and activity data before the inventory process has advanced to its final stages.
The first step of an emissions comparison is a consistency and completeness check using available historical inventory data for multiple years. The emission levels of most source categories do not abruptly change from year to year, as changes in both activity data and emission factors are generally gradual. In most circumstances, the change in emissions will be less than 10% per year. Thus, significant changes in emissions from previous years may indicate possible input or calculation errors. After calculating differences, the larger percentage differences (in any direction) should be flagged, by visual inspection of the list, by visual inspection of the graphical presentation of differences (e.g. in a spreadsheet) or by using a dedicated software programme that puts flags and rankings in the list of differences.
It is good practice to also check the annual increase or decrease of changes in emissions levels in ignificant subsource categories of some source categories. Sub-source categories may show greater percentage changes than the aggregated source categories. For example, total emissions from petrol cars are not likely to change ubstantially on an annual basis, but emissions from sub-source categories, such as catalyst-equipped petrol cars, may show substantial changes if the market share is not in equilibrium or if the technology is changing and rapidly being adopted in the marketplace.
It is good practice to check the emissions estimates for all source categories or sub-source categories that show greater than 10% change in a year compared to the previous year’s inventory. Source categories and sub-source categories should be ranked according to the percentage difference in emissions from the previous year. Supplementary emission comparisons can also be performed, if appropriate, including order-of-magnitudechecks and reference calculations.
ORDER-OF-MAGNITUDE CHECKS
Order of magnitude checks look for major calculation errors and exclusion of major source categories or subsource categories. Method-based comparisons may 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 (i.e. emissions estimates were determined for each individual production plant based on plant-specific data), the emissions check would consist of comparing the sum of the individual plant-level emissions to a top-down emission estimate based on national nitric acid production figures and IPCC default Tier 1 factors. If significant differences are found in the comparison, further investigation using the source category-specific QC techniques described in Section 8.7, Source Category- Specific QC Procedures (Tier 2), would be necessary to answer the following questions:
• Are there inaccuracies associated with any of the individual plant estimates (e.g. an extreme outlier may be accounting for an unreasonable quantity of emissions)?
• Are the plant-specific emission factors significantly different from each other?
• 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 representativeness of the emissions data. Knowledge of the source category is required to
isolate the parameter that is causing the difference in emissions estimates and to understand the reasons for the
difference.
REFERENCE CALCULATIONS
Another emission comparison may be used for source categories that rely on empirical formulas for the
calculation of emissions. Where such formulas are used, final calculated emission levels should follow
stochiometric ratios and conserve energy and mass. In a number of cases where emissions are calculated as the sum of sectoral activities based on the consumption of a specific commodity (e.g. fuels or products like HFCs, PFCs or SF6), the 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 ased on apparent fuel consumption per fuel type is mandatory according to the IPCC Guidelines. Another example is estimating emissions from manure management. The total quantity of methane produced should not exceed the quantity that could be expected based on the carbon content of the volatile solids in the manure. Discrepancies between inventory data and reference calculations do not necessarily imply that the inventory data are in error. It is important to consider that there may be large uncertainties associated with the reference calculations themselves when analysing discrepancies.
Activi ty data QC
The estimation methods for many source categories rely on the use of activity data and associated input variables that are not directly prepared by the inventory agency. Activity data is normally collated at a national level using secondary data sources or from site-specific data prepared by site or plant personnel from their own measurements. Inventory agencies should take into account the practical considerations discussed above when determining the level of QC activities to undertake.
NATIONAL LEVEL ACTIVITY DATA
Where national activity data from secondary data sources are used in the inventory, it is good practice for the inventory agency or its designees to evaluate and document the associated QA/QC activities. This is particularly important with regard to activity data, since most activity data are originally prepared for purposes other than as input to estimates of greenhouse gas emissions. Though not always readily available, many statistical organisations, for example, have their own procedures for assessing the quality of the data independently of what the end use of the data may be. If it is determined that these procedures satisfy minimum activities listed in the QA/QC plan, the inventory agency can simply reference the QA/QC activities conducted by the statistical organization It is good practice for the inventory agency to detrmine if the level of QC associated with secondary activity data includes those QC procedures In addition, the inventory agency may establish whether the secondary data have been peer reviewed and record the scope of this review. If it is determined that the QA/QC associated with the secondary data is adequate, then the inventory agency can simply reference the data source and document the applicability of the data for use in its emissions estimates.If it is determined that the QC associated with the secondary data is inadequate, then the inventory agency should attempt to have QA/QC checks on the secondary data established. It should also reassess the uncertainty of emissions estimates in light of the findings from its assessment of the QA/QC associated with secondary data. The inventory agency should also reconsider how the data are used and whether any alternative data, including IPCC default values and international data sets, may provide for a better estimate of emissions. If no alternative data sources are available, the inventory agency should document the inadequacies associated with the secondary data QC as part of its summary report on QA/QC (see Section 8.10.2, Reporting, for reporting guidance).For example, in the transportation category, countries typically use either fuel usage or kilometer (km) statistics to develop emissions estimates. The national statistics on fuel usage and kms travelled by vehicles are usually prepared by a different agency from the inventory agency. However, it is the responsibility of the inventory agency to determine what QA/QC activities were implemented by the agency that prepared the original fuel usage and km statistics for vehicles. Questions that may be asked in this context are:
• Does the statistical agency have a QA/QC plan that covers the preparation of the data?
• What sampling protocol was used to estimate fuel usage or kms travelled?
• How recently was the sampling protocol reviewed?
• Has any potential bias in the data been identified by the statistical agency?
• Has the statistical agency identified and documented uncertainties in the data?
• Has the statistical agency identified and documented errors in the data?
National level activity data should be compared with previous year’s data for the source category being
evaluated. Activity data for most source categories tend to exhibit relatively consistent changes from year to year without sharp increases or decreases. If the national activity data for any year diverge greatly from the historical trend, the activity data should be checked for errors. If the general mathematical checks do not reveal errors, the characteristics of the source category could be investigated and any change identified and documented. Where possible, a comparison check of activity data from multiple reference sources should be undertaken. This is important for source categories that have a high level of uncertainty associated with their estimates. For example, many of the agricultural source-categories rely on government statistics for activity data such as livestock populations, areas under cultivation, and the extent of prescribed burning. Similar statistics may be prepared by industry, universities, or other organisations and can be used to compare with standard reference sources. As part of the QC check, the inventory agency should ascertain whether independent data have been used to derive alternative activity data sets. In some cases, the same data are treated differently by different agencies to meet varying needs. Comparisons may need to be made at a regional level or with a subset of the national data since many alternative references for such activity data have limited scope and do not cover the entire nation.
SITE-SPECIFIC ACTIVITY DATA
Some methods rely on the use of site-specific activity data used in conjunction with IPCC default or countryspecific emission factors. Site or plant personnel typically prepare these estimates of activity, often for purposes other than as inputs to emissions inventories. QC checks should focus on inconsistencies between sites to establish whether these reflect errors, different measurement techniques, or real differences in emissions, operating conditions or technology.
A variety of QC checks can be used to identify er ors in site-level activity data. The inventory agency should establish whether recognised national or international standards were used in measuring activity data at the individual sites. If measurements were made according to recognised national or international standards and a QA/QC process is in place, the inventory agency should satisfy itself that the QA/QC process at the site isacceptable under the inventory QA/QC plan and at least includes Tier 1 activities. Acceptable QC procedures in use at the site may be directly referenced. If the measurements were not made using standard methods and QA/QC is not of an acceptable standard, then the use of these activity data should be carefully evaluated, uncertainty estimates reconsidered, and qualifications documented.
Comparisons of activity data from different reference sources may also be used to expand the activity data QC.
For example, in estimating PFC emissions from primary aluminium smelting, many inventory agencies use
smelter-specific activity data to prepare the inventory estimates. A QC check of the aggregated activity data from all aluminium smelters can be made against national production statistics for the industry. Also, production data can be compared across different sites, possibly with adjustments made for plant capacities, to evaluate the reasonableness of the production data. Similar comparisons of activity data can be made for other manufacturing-based source categories where there are published data on national production. If outliers are identified, they should be investigated to determine if the difference can be explained by the unique characteristics of the site or there is an error in the reported activity.
Site-specific activity data checks may also be applied to methods based on product usage. For example, one
method for estimating SF6 emissions from use in electrical equipment relies on an account balance of gas
purchases, gas sales for recycling, the amount of gas stored on site (outside of equipment), handling losses,
refills for maintenance, and the total holding capacity of the equipment system. This account balance system should be used at each facility where the equipment is in place. A QC check of overall national activity could be made by performing the same kind of account balancing procedure on a national basis. This national account balancing would consider national sales of SF6 for use in electrical equipment, the nation-wide increase in the total handling capacity of the equipment (that may be obtained from equipment manufacturers), and the quantity of SF6 destroyed in the country. The results of the bottom-up and top-down account balancing analyses should agree or large differences should be explained. Similar accounting techniques can be used as QC checks on other categories based on gas usage (e.g. substitutes for ozone-depleting substances) to check consumption and emissions.
QC of uncertainty estimates
QC should also be undertaken on calculations or estimates of uncertainty associated with emissions estimates.
Good practice for estimating inventory uncertainties is described in Chapter 6, Quantifying Uncertainties in
Practice, and relies on calculations of uncertainty at the source category level that are then combined to summary
levels for the entire inventory. Some of the methods rely on the use of measured data associated with the
emission factors or activity data to develop probability density functions from which uncertainty estimates can
be made. In the absence of measured data, many uncertainty estimates will rely on expert judgement.
It is good practice for QC procedures to be applied to the uncertainty estimations to confirm that calculations are
correct and that there is sufficient documentation to duplicate them. The assumptions on which uncertainty
estimations have been based should be documented for each source category. Calculations of source categoryspecific
and aggregated uncertainty estimates should be checked and any errors addressed. For uncertainty
estimates involving expert judgement, the qualifications of experts should also be checked and documented, as
should the process of eliciting expert judgement, including information on the data considered, literature
references, assumptions made and scenarios considered. Chapter 6 contains advice on how to document expert
judgements on uncertainties.
QA PROCEDURES
Good practice for QA procedures requires an objective review to assess the quality of the inventory, and also to identify areas where improvements could be made. The inventory may be reviewed as a whole or in parts. QA procedures are utilised in addition to the Tier 1 and Tier 2 QC. The objective in QA implementation is to involve reviewers that can conduct an unbiased review of the inventory. It is good practice to use QA reviewers that have not been involved in preparing the inventory. Preferably these reviewers would be independent experts from other agencies or a national or international expert or group not closely connected with national inventory compilation. Where third party reviewers outside the inventory agency are not available, staff from another part of the inventory agency not involved in the portion of the inventory being reviewed can also fulfil QA roles. It is good practice for inventory agencies to conduct a basic expert peer review (Tier 1 QA) prior to inventory submission in order to identify potential problems and make corrections where possible. It is also good practice to apply this review to all source categories in the inventory. However, this will not always be practical due to timing and resource constraints. Key source categories should be given priority as well as source categories where significant changes in methods or data have been made. Inventory agencies may also choose to perform more extensive peer reviews or audits or both as additional (Tier 2) QA procedures within the available
resources. More specific information on QA procedures related to individual source categories is provided in the source
EXPERT PEER REVIEW
Expert peer review consists of a review of calculations or assumptions by experts in relevant technical fields.
This procedure is generally accomplished by reviewing the documentation associated with the methods and
results, but usually does not include rigorous certification of data or references such as might be undertaken in an
audit. The objective of the expert peer review is to ensure that the inventory’s results, assumptions, and methods
are reasonable as judged by those knowledgeable in the specific field. Expert review processes may involve
technical experts and, where a country has formal stakeholder and public review mechanisms in place, these
reviews can supplement but not replace expert peer review.
There are no standard tools or mechanisms for expert peer review, and its use should be considered on a case-bycase
basis. If there is a high level of uncertainty associated with an emission estimate for a source category,
expert peer review may provide information to improve the estimate, or at least to better quantify the uncertainty.
Expert reviews may be conducted on all parts of a source category. For example, if the activity data estimates
from oil and natural gas production are to be reviewed but not the emission factors, experts in the oil and gas
industry could be involved in the review to provide industry expertise even if they do not have direct experience
in greenhouse gas emissions estimation. Effective peer reviews often involve identifying and contacting key
industrial trade organisations associated with specific source categories. It is preferable for this expert input to be
sought early in the inventory development process so that the experts can participate from the start. It is good
practice to involve relevant experts in development and review of methods and data acquisition.
The results of expert peer review, and the response of the inventory agency to those findings, may be important
to widespread acceptance of the final inventory. All expert peer reviews should be well documented, preferably
in a report or checklist format that shows the findings and recommendations for improvement.
AUDITS
For the purpose of good practice in inventory preparation, audits may be used to evaluate how effectively the
inventory agency complies with the minimum QC specifications outlined in the QC plan. It is important that the
auditor be independent of the inventory agency as much as possible so as to be able to provide an objective
assessment of the processes and data evaluated. Audits may be conducted during the preparation of an inventory,
following inventory preparation, or on a previous inventory. Audits are especially useful when new emission
estimation methods are adopted, or when there are substantial changes to existing methods. It is desirable for the
inventory agency to develop a schedule of audits at strategic points in the inventory development. For example,
audits related to initial data collection, measurement work, transcription, calculation and documentation may be
conducted. Audits can be used to verify that the QC steps identified in Table 8.1 have been implemented and that
source category-specific QC procedures have been implemented according to the QC plan.
VERIFICATION OF EMISSIONS DATA
Options for inventory verification processes are described in Annex 2, Verification. Verification techniques can
be applied during inventory development as well as after the inventory is compiled.
Comparisons with other independently compiled, national emissions data (if available) are a quick option to
evaluate completeness, approximate emission levels and correct source category allocations. These comparisons
can be made for different greenhouse gases at national, sectoral, source category, and sub-source category levels,
as far as the differences in definitions enable them.
Although the inventory agency is ultimately responsible for the compilation and submission of the national
greenhouse gas inventory, other independent publications on this subject may be available (e.g. from scientific
literature or other institutes or agencies). These documents may provide the means for comparisons with other
national estimates.
The verification process can help evaluate the uncertainty in emissions estimates, taking into account the quality
and context of both the original inventory data and data used for verification purposes. Where verification
techniques are used, they should be reflected in the QA/QC plan. Improvements resulting from verification
should be documented, as should detailed results of the verification process.
DOCUMENTATION, ARCHIVING AND REPORTING
Interna l documentation and archiving
As part of general QC procedures, it is good practice to document and archive all information required to
produce the national emissions inventory estimates. This includes:
• Assumptions and criteria for selection of activity data and emission factors;
• Emission factors used, including references to the IPCC document for default factors or to published
references or other documentation for emission factors used in higher tier methods;
• Activity data or sufficient information to enable activity data to be traced to the referenced source;
• Information on the uncertainty associated with activity data and emission factors;
• Rationale for choice of methods;
• Methods used, including those used to estimate uncertainty;
• Changes in data inputs or methods from previous years;
• Identification of individuals providing expert judgement for uncertainty estimates and their qualifications to
• Details of electronic databases or software used in production of the inventory, including versions, operating
manuals, hardware requirements and any other information required to enable their later use;
• Worksheets and interim calculations for source category estimates and aggregated estimates and any recalculations
of previous estimates;
• Final inventory report and any analysis of trends from previous years;
• QA/QC plans and outcomes of QA/QC procedures.
It is good practice for inventory agencies to maintain this documentation for every annual inventory produced
and to provide it for review. It is good practice to maintain and archive this documentation in such a way that
every inventory estimate can be fully documented and reproduced if necessary. Inventory agencies should ensure
that records are unambiguous; for example, a reference to ‘IPCC default factor’ is not sufficient. A full reference
to the particular document (e.g. Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories) is
necessary in order to identify the source of the emission factor because there may have been several updates of
default factors as new information has become available.
Records of QA/QC procedures are important information to enable continuous improvement to inventory
estimates. It is good practice for records of QA/QC activities to include the checks/audits/reviews that were
performed, when they were performed, who performed them, and corrections and modifications to the inventory
resulting from the QA/QC activity.
Reporting
It is good practice to report a summary of implemented QA/QC activities and key findings as a supplement to each country’s national inventory. However, it is not practical or necessary to report all the internal
documentation that is retained by the inventory agency. The summary should describe which activities were performed internally and what external reviews were conducted for each source category and on the entire inventory in accordance with the QA/QC plan. The key findings should describe major issues regarding quality of input data, methods, processing, or archiving and show how they were addressed or plan to be addressed in the future.