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Greenhouse Gas Emissions Forecasting: Learning from International Best Practices

What are the Best Practices of GHG Emissions Reductions Forecasting?

In reviewing best practices in GHG emissions forecasting, a useful starting point is the main areas of concern addressed by the NRTEE in its 2007 KPIA Response:

  • Clear and transparent definitions of the modelling approaches used are absolutely essential. Particularly important are the assumptions about the time frame to which the models are being applied. It is also important to provide sufficient detail on the methods and data employed.
  • For any specific modelling framework, it is important to provide prioritized information about the baseline forecast assumptions about behaviour and the cost of technology.
  • Also critical is a clear and transparent definition of the particular policies being studied. In general, market-based approaches are commonly modelled within an economic framework. In contrast, non-market based policies are more difficult to assess, with analyses often based on ad hoc assessments. It is in that context that issues of consistency and integration of results are most critical.

Beyond these key concerns are a range of issues pertaining to methodology and governance in emissions forecasting, which we set out below.

4.1. Methodology

From a methodological perspective, BAU forecast has to be explicit about key drivers and assumptions (s.3.1, criteria 3) and about key response dynamics (s.3.1, criteria 2). Even under a BAU forecast, this latter criterion is important. For example, what will be the full response over the next 40 years to a long-run trend to higher real oil prices? Then, the issue of dynamics continues to be extremely important as we try to forecast the effect of policies. At this point, sensitivity analysis is also key (s.3.1, criteria 4).

While there are many approaches to emissions forecasting, the two approaches consistently determined as best practices from a methodological perspective from academic, government, and institutional peer review are the International Energy Agency’s (IEA) World Energy Outlook and the U.S. Energy Information Administration’s (EIA) International Energy Outlook.[16]

Through its annual World Energy Outlook, the IEA produces a BAU forecast as well as a policy forecast (World Alternative Policy Scenario). It can be determined that the IEA utilizes "best" forecasting practices for the following reasons: first, it provides a systematic analysis of both aggregate measures and intensities: GDP, energy supply, and energy supply per unit GDP. Contrast this with Canada’s 2006 reference case[17] where everything is in rates and average shares, which is inherently less easy to verify or adapt. The IEA forecasts are quite flexible, and allow one to easily see where errors have occurred (e.g., growth was underestimated, so emissions will be as well). In Canada’s case, there were no hard values for GDP, population, etc., only hard values for energy use and emissions. If the Canadian reference case were to have underlying trends on important aggregates, it might be easier to update emissions forecasts, which would make them more credible. Second, and related to the first, the IEA periodically has a section in its new editions that examines why its previous forecasts may have erred: Was it an error in GDP or in emissions per GDP forecasts that led to an error in emissions forecasts?[18] Third, the IEA also discusses up front the key assumptions and sources of uncertainty. Main uncertainties include macroeconomic conditions (e.g., slower GDP growth than assumed in both scenarios would cause demand to grow less rapidly), uncertain effects of resource availability and supply on energy prices, and changes in government and energy environmental policies.[19] It also expands on one of the key sources of uncertainty, the adoption of policy (as the NRTEE assessed through its 2007 KPIA Response). The IEA responds to this uncertainty by proposing an "Alternative Policy Scenario," in which it examines what would be likely to happen given the underlying forecast assumptions if certain policies being discussed were adopted.

The EIA provides worldwide forecasts of energy demand and supply through 2030 in its annual assessment of global energy markets that is published in the International Energy Outlook (IEO). Similar to the IEA’s long-term outlooks, the IEO employs measures of economic growth (GDP), population, and energy intensity to derive its forecasts. All of these statistics are reported either in the body of the text or in the appendices that accompany the report. The IEO includes regional projections of carbon dioxide emissions by fossil fuel. The report also includes an examination of the forecast relative to prior-year releases and, in the 2006 edition of the report, a comparison of past IEO projections with the actual historical data. This assessment can also be found in the appendices of the various IEO editions, all of which are archived on the EIA website.

In addition to a reference case projection, the IEO typically includes a number of side cases. These cases estimate the impact on energy markets of high and low macroeconomic growth assumptions and high and low energy prices. These results help to quantify the uncertainty in the IEO projections. While the EIA does not routinely include climate change policy side cases in its outlook, in 2006 it did include an analysis of the impact of the Kyoto Protocol on the countries and regions that ratified the treaty (including, of course, Canada).

As described above, the EIA’s International Energy Module is similar to the IEA’s forecasting approach. For the purposes of this report, it is important to understand that the EIA and IEA forecasts are BAU, and that it is policy forecasting that is especially challenging. However, both the EIA and IEA build on their BAU forecasts with complementary analyses and alternative policy scenarios that depict different futures (e.g., the adoption of more aggressive GHG targets or faster deployment of clean technologies) from the reference case or BAU forecast, which projects what will happen if current actions and policies remain in place. This is particularly important for Canada, as discussed in section 5.1. Therefore, for the context of this report, the approaches described above can serve as best-practice benchmarks from a methodological perspective for emissions forecasting.

4.2 Governance

As mentioned above, there are some basic best practices in regard to governance in emissions forecasting. These include clear and transparent definitions of the modelling approaches used, the provision of sufficient detail on the methods and data employed, and clear and transparent definitions of the particular policies being studied. This allows for a common understanding of the government’s emissions forecasts and permits a straightforward evaluation of emissions reductions estimates and forecasts by not only government officials, but by third parties as well.

Beyond this, there is the issue of on-going evaluation. The importance of independent peer review cannot be overemphasized as a governance best practice. This ensures that the government’s approach to emissions forecasting, including modelling, is rigorous and reflects key analytical, economic, regional, and sectoral considerations. While different types of review are possible, great care should be taken to make sure that the review is truly independent of the sponsoring agency and the modelling effort. Sometimes it is even useful to showcase the results of a report of this sort in a public meeting, as in the case with the EIA’s annual forecasts, involving a wide range of stakeholders. Such meetings are able to examine the results and methods, as well as future plans to improve the analysis--all in the context of international best practices.

Broadly speaking, as will be discussed in section 5 below, countries with integrated, centralized, independent emissions forecasting agencies are more likely to produce accurate forecasts than those countries with responsibilities for data gathering and modelling diffused across various departments. Some countries are recognizing this, as shown by the newly created U.K. Committee on Climate Change and the Australian Department of Climate Change.

4.3 Canada’s Approach

The Canadian government has set a national goal of reducing GHG emissions, relative to 2006 levels, by 20 per cent by 2020, and by 60 to 70 per cent by 2050. As illustrated by the government’s most recent climate change plan Turning the Corner,[20] Canada uses forecasts to determine future GHG emissions reductions. In the plan, federal measures alone will reduce emissions in 2020 by approximately 230 megatonnes below forecasted levels, with 165 megatonnes of that reduction being attributable to the federal Regulatory Framework for Industrial GHG Emissions.

Various departments collect, analyze, and model data (in some cases modelling emissions forecasts for specific policies and measures) and provide that information to Environment Canada, the department responsible for coordinating climate policy (including forecasting) within the federal government. While this practice does not necessarily lead to inaccurate forecasts, issues arise when the central agency is neither independent nor has the authority to override the data and analysis it receives from other departments. The NRTEE drew attention to this issue in its 2007 KPIA Response when it emphasized the importance of consistency in approaches across different departments and programs, and the need to integrate the findings in a holistic framework. This issue is clearly illustrated in the U.S. case study set out in section 4.4.2 below.

4.3.1 Forecasting Model [21]

The emissions and economic forecasts presented in the government’s plan were estimated through Environment Canada’s economic model (the Energy-Economy-Environment Model for Canada, or E3MC). The E3MC model is a combination of the Energy 2020 model and the Informetrica Model (TIM). According to Environment Canada, E3MC permits "integrated energy-economy policy simulations in a manner that fully addresses the challenges of additionality, free-riders, rebound effects, and policy interaction effects that commonly arise in this type of complex analysis"[22]--the very effects the NRTEE highlighted in its KPIA Response. This most recent plan was released following the NRTEE’s 2007 KPIA Response.

Energy 2020 (E2020) is a "bottom-up" technology model used to forecast the effect of policies on emissions.[23] The model forecasts the adoption of energy-using and energy-producing technologies throughout the Canadian economy. E2020 accounts for the technologies in use and forecasts consumers’ choices of future technologies. Consumer choices are based on both financial factors (the operating and capital costs of technologies) as well as non-financial preferences, as drawn from historical data. Technology options (with different efficiencies or powered by different fuels) are associated with different energy use and different emissions. The model forecasts future emissions first under a reference scenario, which models emissions under current conditions, and second under a policy scenario, which models emissions under the proposed policy package. The difference between the two trends illustrates the forecasted effects of the proposed policies.

The Informetrica Model (TIM) is a macroeconomic model used to assess the effect of the Turning the Corner policy package on the economy. Using the investments in new technology and resulting savings forecast by E2020, TIM models the effects of these factors on consumption, investment, production, and trade decisions in the rest of the economy. These effects are modelled by balancing inputs and outputs of commodities and capital. TIM includes both industry-specific and regional breakdowns.

The E3MC model is a "hybrid" model as it effectively iterates between the E2020 and TIM models by re-running one model with the outputs of the other. This iteration continues for each year in the simulation until model outputs no longer change (this stability suggests the models have found an equilibrium solution).

Government Forecasts of Canadian GHG Emissions

Government Forecasts of Canadian GHG Emissions

Source: Simpson, Jaccard and Rivers (2007), p. 166.

4.3.2 Accuracy of Canada’s Forecasts

As the NRTEE has conducted an evaluation of the government’s policies and measures in reducing GHG emissions in the accompanying 2008 KPIA Response, this report will not contain an analysis of the government’s approach and accuracy of its forecasts. However, as noted earlier in this report, the government has taken significant steps in its 2008 KPIA Plan to address the different and inconsistent forecasting methods that various federal departments used to describe the emissions reductions accruing from a particular initiative, which the NRTEE identified as problematic in its 2007 KPIA Response.

As observed by some economic experts, Canada has found it a challenge to produce consistent and accurate forecasts, "…underestimating growth of GHGs under BAU conditions."[24] These forecasts have presumably been evaluated on the assumption that BAU conditions are what Canada has had. It is important to note there has not been a recent comprehensive, technical analysis and review of the government’s forecasting methodology and governance, by either an independent agency or third-party peer review.[25] In regard to the E3MC model, while there was a review of the Energy 2020 model in 2000 through the Analysis and Modelling Group (AMG) process, the model has been updated considerably since that time. There has not been, therefore, a peer review or independent analysis of the E3MC. Canada has, in the past, subjected its environment-economy models to peer review. A good example and potential approach for an independent review of the current E3MC is the 2001 Royal Society of Canada Report of an Expert Panel to Review the Socio-Economic Models and Related Components Supporting the Development of Canada-Wide Standards for Particulate Matter and Ozone. [26] The Panel was formed in response to a request from a committee of industry stakeholders and government regulators for an objective and independent review of methods used to estimate and compare the costs and benefits of particulate matter (PM) and ozone reduction.

4.4 Case Studies

4.4.1 Introduction

The selection of case studies to provide examples of international best practices in GHG emissions forecasting is not as straightforward as may seem apparent. The original intention was to select countries with similar challenges to those of Canada in forecasting GHG policies, and that followed best practices in methodology and governance as outlined in sections 4.1 and 4.2. Countries selected as having similar economic traits to those of Canada (e.g., resource-based, export-led) were the U.S., Norway, and Australia; with jurisdictional similarities, the U.S. and Australia; and for well-acknowledged best practices, the U.K. and U.S. However, this study has revealed that very few countries follow all best practices together from both methodological and governance perspectives in their emissions forecasting. Therefore, the U.S. and the U.K. are the sole countries highlighted in this report as having overall best practices in emissions forecasting.

To be fair, the forecasting of emissions reductions from GHG policies is an evolving practice. Some countries have consistently attempted to adopt best practices from the early days of reporting emissions projections; others are only more recently making concerted efforts to improve their methodology and governance vis-à-vis forecasting. There is a discussion of this issue following the case studies.

Another original intention of this report was to highlight best practices in jurisdictions other than national-level governments, particularly some Canadian provinces and U.S. states. Given the unique jurisdictional issues of climate policy in Canada, and the fact that 16 megatonnes of annual emissions reductions in Turning the Corner are attributed to provincial and territorial initiatives, it is important to determine if provinces are conducting accurate forecasts of their climate policies and measures. Few provinces, however, have released detailed plans with emission policy forecasts. Nevertheless, they have set GHG emissions reductions targets and announced policies and measures to achieve these targets, but have not accompanied these with detailed emissions forecasts which would attribute specific reductions and measures to forecasts, with accompanying methodology to allow for independent validation.

This is not to say that provinces are not taking action--British Columbia is supposed to release a climate plan with detailed forecasts by summer 2008 and Alberta is also developing its own forecasts. However, it is important that all provinces produce emissions policy forecasts utilizing best practices to ensure an accurate understanding of the scale of the emissions reduction challenge in Canada and ultimately to result in coordinated or complementary policy approaches across Canada.

Even in the case of California, often touted as a North American leader in climate policy and filling a federal policy vacuum on climate change, forecasts are based on the voluntary Climate Action Registry. No systematic, independent forecasting is conducted. Considering the large scale of regional initiatives taking place (including proposed emissions trading initiatives), and the expected need for emissions trading systems to link, the collection of data and forecasting of emissions at both the federal and provincial levels is vital to ensure coherent, coordinated climate policy making for Canada as a whole.

Table 1: Comparison of Governance and Methodology in Emissions Forecasting

 GovernanceMethodology
United StatesIndependent statistical agency responsible for forecasting (EIA)Single hybrid model (NEMS); independent peer review of forecasting model
United KingdomCentral department responsible for forecasting with input from other departments (DEFRA); central agency coordinating climate action across departments (OCC)Single hybrid model (M-M model); two independent audits of government forecasts; one non-governmental review of forecasts.
Norway*Independent statistical agency responsible for forecasting (Statistics Norway); climate policy coordinated by Ministry of the EnvironmentGeneral equilibrium model (MSG); commitment by government for future independent peer review of model and forecasts
Australia*Newly-created Department of Climate Change responsible for all climate policy, including forecasting
Use of multiple models across sectors.

* Studied for the purposes of this report but not included as a best-practice case study.

4.4.2 United States

Approach

In the U.S., the Energy Information Administration (EIA) performs the majority of energy-based emissions forecasting. The EIA, created by Congress in 1977, is a statistical agency of the U.S. Department of Energy. Its mission is to provide "policy-neutral data, forecasts, and analyses to promote sound policy making, efficient markets, and public understanding regarding energy and its interaction with the economy and the environment."[27] The Department of Energy Organization Act (Public Law 95-91) allows EIA’s processes and products to be independent from review by Executive Branch officials.[28] Its domestic energy projections are based on the National Energy Modeling System (NEMS), a detailed model that utilizes various modelling methodologies to represent individual domestic energy markets (electricity, refining, industrial, etc.) Confidence in the model may be reflected by the number of think tanks, academic institutions, private entities, and laboratories that use it. The EIA’s Annual Energy Outlook (AEO) contains a reference case and often more than 30 alternative scenarios. In addition, the EIA publishes an assumptions document, model documentation, and an assessment of its forecasts.

In its publications, the EIA makes reference to the importance of sustained and significant levels of resource commitment to the production of national GHG emissions projections. Producing detailed forecasts and alternative policy scenarios on an annual basis requires substantial funds. Significant resources also ensure capacity in producing the forecasts and ensure that the model is based on the most recent data.

The forecasts produced by the EIA are based on current laws and regulations but the EIA does produce forecasts on future policies when directed by Congress. This issue is particularly important for Canada, as one of the issues noted in section 4.3.2 is that the Turning the Corner modelling analysis assumed that "provincial mitigation policies improve over time and become more consistent between provinces." Since provincial GHG reduction policies are emerging as an important issue in Canada, this distinction takes on added significance. One implication here is that future Canadian analyses might consider starting with projections of GHG emissions based on existing laws and policies and then explicitly add scenarios to reflect assumptions about improvements in provincial policies. This would give policy makers more precise information as to the challenges and opportunities surrounding specific policies. Such an approach would, at a minimum, increase transparency and facilitate evaluation of future forecasts.

Governance

As noted, the EIA is an independent statistical agency. The only person appointed to a position in the EIA is the Administrator. The Administrator is always an energy professional or statistician. The EIA responds to requests from Congress from all political parties. From its inception, the EIA organizing legislation was constructed in such a way as to make it as independent and free from political manoeuvring as possible. Its products are not reviewed or approved by the Administration. They go out under the signature of the Administrator.

Because it is an independent statistical agency, the EIA is often considered "unbiased." Beyond its annual projections, the EIA performs policy analyses at the request of Congress or the Administration that specifies the "policy." EIA analyses usually illustrate the impact of the policy compared to its reference case, the nature of the critical assumptions, and the uncertainty of key variables.

A corollary to the methodological issue mentioned earlier concerns the treatment by the responsible forecasting agency of analyses performed by other government departments or agencies. In the U.S., as in other countries, individual departments or agencies routinely prepare analyses of specific GHG reduction programs--typically of programs they themselves administer. For example, the U.S. EPA routinely projects emissions reductions resulting from its voluntary programs. While these agency analyses are reviewed by the EIA, they are not necessarily adopted by the EIA. This is an important point. Unless the agency in charge of forecasting GHG emissions has the authority/independence to make its own professional judgments about the effectiveness of individual programs, there is a potential for the forecasts to be driven by more narrow program-driven considerations rather than a more independent and integrated analysis. A perceived strength of the EIA is that it can, and does, have the authority and independence to disagree with other agencies on the forecasts they are provided with.

Audit/Review Function of Forecast Accuracy and Methodology

Audits and reviews of emissions forecasts are an important evaluation and accountability tool. Internal to the U.S. Department of Energy is an Inspector General with authority to review the EIA’s products and processes. There is also the General Accountability Office that has authority to review government programs. According to communications with EIA officials for the purposes of this report, neither has expended much effort to date in reviewing EIA data or projections. Internal to the EIA, however, is an office of statistical methods that reviews documentation and hires independent experts to review model results and accuracy. Prior to publication, all of the offices of the EIA review the AEO through an established clearance process. There are also working groups composed of experts from throughout the department and industry that meet biannually and review model methodology and projections. The EIA also publishes a retrospective that evaluates its previous reference case projections.[29] Along with these processes, the EIA holds an annual conference that highlights the AEO projections and models. Its projections and models have been reviewed frequently in academic journals; it has a memorandum of understanding with the American Statistical Association; it conducts biannual meetings that often address model methodology and statistical methods; and it participates in energy modelling fora that compare and contrast modelling methodologies and results.

Beyond academic peer reviews in journals and stakeholder meetings, the only significant external evaluation of U.S. emissions forecasts have been the UNFCCC through its Report on the in-depth review of the third national communication of the United States of America. The report is highly complimentary of NEMS, stating "the rich representation of technology in NEMS allows analysis of the impact of mitigation policies thanks to the model’s explicit representation of vintaged (time-dependent) capital (energy equipment and structures such as power plants), and tracking of its turnover rates."[30]

4.4.3 United Kingdom

Approach

While there are a number of inputs into forecasting emissions reductions in the U.K., the Department for Environment, Food and Rural Affairs (DEFRA) coordinates and releases the emissions forecasts on an annual basis. The U.K. MARKAL-Macro Energy Model (M-M model) has been the main model to explore the technological and macroeconomic implications of reducing U.K. domestic carbon emissions by its declared target of 60% by 2050. The M-M model is an integrated energy-macro model, covering the entire energy system in considerable technological detail, including electricity generation, heat, and transport. The model explores how, under different assumptions about future fossil fuel prices and the pace of technological innovation, the energy system will evolve under a carbon constraint, and what the macroeconomic implications to the U.K. economy might be, including the costs to GDP. The main driver for increased emissions is economic growth, as described by the macro module of the model apparatus. Because the M-M model describes the economy in equilibrium, it is unable to capture transition costs that might occur as the economy adjusts to changes in energy policy or prices. As a U.K- only model, it also does not capture the implications for U.K. trade and competitiveness as a result of policies aimed at reducing carbon emissions. Therefore, in addition to the M-M analysis, the U.K. government has also used the Oxford Energy-Industry Model (OEIM) and global macroeconomic model (GMM) to explore the potential short- to medium-term adjustment costs associated with moving to a low carbon economy. As a purely domestic model, the M-M model also cannot explore the implications of international carbon trading.

The way in which activity data are broken down to estimate emissions closely resembles the basis on which the government monitors economic activity. As a result, much of the economic activity data gathered by government is already classified in a format that can facilitate estimates of emissions. One of the major sources of activity data, covering around 85 per cent of emissions, is the Digest of U.K. Energy Statistics (DUKES) produced annually by the Department of Business, Enterprise and Regulatory Reform. It is the most authoritative source of annual data on energy use in the U.K. The rest of the data activity comes from a variety of sources, including the Transport and Environment Departments. Many of the data providers are government departments but some of the data used to estimate emissions come from trade associations and directly from industry.

Governance

While DEFRA coordinates and releases emissions forecasts in the U.K., the newly-created Office of Climate Change (OCC) will work across the U.K. government to support analytical work on climate change and the development of climate change policy and strategy. Many government departments are involved in climate-related activities or in helping the U.K. and other countries adapt to its possible future impacts. All departments utilize the OCC.

The Climate Change Bill, which is currently being subjected to a full public consultation alongside pre-legislative scrutiny in Parliament, sets out a fundamentally new and more structured approach to the setting of emissions reduction targets and the monitoring of performance against them. It will translate into U.K. legislation, the goal of which the government announced in its 2003 White Paper--namely, a 60 per cent reduction in carbon dioxide by 2050 measured against a 1990 baseline. It will create a system of five-year carbon budgets to place the U.K. on a trajectory to meet its long-term goal, and require the Secretary of State for the Environment to set and meet carbon budgets for up to 15 years in advance. A newly created Committee on Climate Change will be responsible for advising the government on the level of carbon budgets to be set, and for monitoring emissions through annual reports to Parliament that will include a more comprehensive assessment of performance after the end of each five-year budgetary period.

Audit/Review Function of Forecast Accuracy and Methodology

The forecasting of GHG emissions reductions has been the subject of at least two audits[31] by the U.K. National Audit Office. Of the countries researched for this report, the U.K. is the only one to have had its entire emissions forecasting measurement and reporting audited by an independent third party. The audit had a number of key findings:

  • The U.K. will meet or exceed its Kyoto target on all but the most pessimistic assumptions, and will fall short of its 2010 domestic target in all but the most optimistic assumptions.
  • Forecasts made in 2000 have been revised to reflect a reduction in the expected savings from individual policy measures, changes in fossil fuel price assumptions, and gradual refinements to the former Department of Technology and Innovation’s (DTI) energy demand model and adjustments to the 1990 baseline. A degree of change in projections is to be expected; the U.K. government recognized that the 2000 estimates were subject to considerable uncertainty.
  • The forecasts are based on sophisticated modelling approaches. The models are subject to expert review and other quality assurance processes.
  • U.K. Government has taken steps to make the 2006 forecasts more robust than those in 2000. The review of projected policy impacts that took place in 2006 involved a more skeptical scrutiny of the emission reductions to be expected from policy measures. There was also more detailed analysis of uncertainty.
  • Forecasts against the 2020 and 2050 domestic targets to reduce CO2 are less well developed and necessarily more speculative. As the 2010 target approaches, it is important to switch attention to the realism and delivery of these future targets.
  • International reporting requirements specify the basis on which emissions should be estimated. The U.K.’s estimates follow best practices and have been reviewed favourably by international experts in GHG measurement appointed by the UN.
  • The Climate Change Bill provides a new framework for setting U.K. targets. Its provisions will introduce concepts such as the "net U.K. carbon account" and requirements to account for the contribution made by carbon credits and debits from emissions trading schemes. Such provisions could complicate the reporting framework further, or else provide an opportunity to develop a more comprehensive and transparent basis for presenting climate change statistics.[32]

The forecasting of emissions in the U.K. was also the subject of an audit undertaken by University College London’s Environment Institute. In its report entitled U.K. Greenhouse Gas Emissions: Are We on Target? the Environment Institute found that while the U.K. GHG emission target of a 12.5% cut to the baseline levels required by the Kyoto Protocol will be met, the emissions reductions forecast for the 2020 target will be difficult to meet because of continued significant economic growth that will cause emissions to rise after 2010. The audit suggests current policies would achieve a GHG emission reduction between -12 and -17 per cent by 2020 as opposed to the government’s policy aim of -30 per cent. The audit states that the overriding reasons for the possible failure of current government policies to achieve their stated targets is that nearly all the policies are voluntary.

In its Report of the centralized in-depth review of the fourth national communication, the UNFCCC commends the U.K. for its emissions projections.[33] The U.K. was also commended not only for its consistency with earlier reports, but the transparent and concise nature of its report. The U.K. is further commended for not only including a "with measures" scenario, but a baseline scenario and two "with additional measures" scenarios (including the effect of planned measures). From a governance perspective, the U.K. received praise for the establishment of the Climate Change Projects Office (CCPO), the appointment of a designated national authority for the Clean Development Mechanism (CDM), and the appointment of a designated focal point for joint implementation (JI) projects. The UNFCC further commended the U.K. for its role in the development of the registry software and finally, "lauds the U.K. for its solid and coherent program of action."[34]


16 The EIA’s domestic approach to emissions forecasting is described in Section 3.2.2

17 Natural Resources Canada (2006), Canada’s Energy Outlook: The Reference Case 2006. As noted in this report and the NRTEE’s 2008 KPIA Response, a new baseline (March 2008) has been developed that has significantly improved from the 2006 baseline.

18 For example, see International Energy Agency (2004), World Energy Outlook 2004, Annex B – Energy Projections: Assessment and Comparison, p. 519.

19 IEA (2006), World Energy Outlook 2006, p. 53.

20 For details, refer to Government of Canada (2008), Turning the Corner – Detailed Emissions and Economic Modelling.

21 In two recent reports on long-term issues related to energy and climate change, the NRTEE used the Energy 2020 (bottom-up) model and the CIMS (hybrid) model.

22 Government of Canada (2008), p. iii–iv.

23 Please see Appendix C for a discussion on different modelling approaches.

24 Simpson, J., M. Jaccard, and N. Rivers (2007). Hot Air: Meeting Canada’s Climate Change Challenge. Toronto: McLelland and Stewart, p.165.

25 The Commissioner of the Environment and Sustainable Development has conducted an audit of specific federal climate change measures but not a full, comprehensive review. For details, see http://www.oag-bvg.gc.ca/internet/English/aud_parl_cesd_200609_e_936.html.

26 For details, see http://www.rsc.ca//files/publications/expert_panels/ozone_&_pm/Ozreport.pdf.

27 http://www.eia.doe.gov/neic/aboutEIA/quickfacts.html

28 Further information on the EIA can be found at http://www.eia.doe.gov.

29 See http://www.eia.doe.gov/oiaf/analysispaper/retrospective/pdf/table18.pdf.

30 UNFCCC (2004), Report on the in-depth review of the third national communication of the United States of America, p.11.

31 National Audit Office (2006), Emissions Projections in the 2006 Climate Change Programme Review; National Audit Office (2008), U.K. greenhouse gas emissions: measurement and reporting.

32 National Audit Office (2008), U.K. greenhouse gas emissions: measurement and reporting, p.5.

33 The NRTEE expressed similar concerns to the Canadian government in its 2007 KPIA Response.

34 UNFCCC (2007), Report of the centralized in-depth review of the fourth national communication of the United Kingdom of Great Britain and Northern Ireland, p.18.