5-okt-07
Category / Projections
Version / 3 (draft 0) / Guidebook Revision, 2007/2008
Major change since earlier versions /
- This chapter presents an outline for a chapter on Projections
Projections
Contents
1Introduction: Understanding Projections
2Terminology:
3Methodological Choice
3.1Formula:
3.2Stratification:
3.3Simplification:
3.4Checks and controls:
3.5Dealing with gaps in projected data.
3.6Data Sources:
4Sensitivities
5Steps to Estimating Emission Projections
6Sectoral Overview of methods
6.1Energy: Stationary Combustion:
6.2Energy: Transport
6.3Industrial Processes
6.4Solvent Use
6.5Agriculture
6.6Waste
References:
Annex 1 Definitions:
Verification with centralised data….
Ex-Ante assessments..
Version 3 (draft 1)crosscuttingchapter-projections_v0_2(tp) / 1 of 19
Gpg Good Practice Guidance: General Guidance on Projections
1Introduction: Understanding Projections
Emission Projections are used nationally and internationally to assess progress to targets and to help model future health, ecosystem impacts. It is stressed here that a projection is not a prediction but rather a method to perform a “what-if” study. Projections inherently aim at contrasting different possible developments in the economy, behaviour and in technology. As such they are a tool t Assess:
- what has been done (“Bussiness as Usual” and “Baseline” scenarios) what will be done (“Policies in Place” scenarios)what could be done (“Best available technologies” scenariossupport environmental decision making in contrasting these type of scenarios
- whether or not developments are on target.
The activities involved in estimating projections also provide a valuable contribution to establishing efficient and effective policies and measures though the development of an understanding of sources, economic drivers and the effectiveness of technologies and controls. Projections will be much less certain that the historic inventory and will require additional assumptions about growth in activities (e.g. production, transport, population) and about technologies, efficiencies and controls that reduce the emissions per unit of activity.
This chapter is designed to provide some general guidance on estimating national projections that might accompany national inventory reporting under EMEP or other policies and measures reporting.
The material is intended both for countries establishing projected emissions estimates for the first time and for countries with established projection approaches.
This chapter covers:
- Terminology used on projections and projections reporting.
- Methods used to estimate projections
- Guidance on tackling common problems with gathering appropriate emission factors and activity data and in ensuring consistency with historic emissions inventories.
The chapter draws on information from a range of institutions. Where possible additional documents have been identified and referenced so that users can find more detailed information. Sector specific projection issues are described in brief in the sections of this chapter and in the sector specific Volumes of this Guidebook.
2Terminology:
Figure 1 illustrates the components in and terminology used in projecting emissions. Most projections will include a number of different estimates (known as scenarios) comprising different combinations of assumptions about future activities, technologies and or controls. These assumptions will relate to basic expectations of growth as well as the impacts of new technologies and local, national and international efforts (known as “policies and measures”) designed to reduce emissions, ranging from emission controls for vehicles and industrial plant to incentives for cleaner fuels and technologies or to change behaviour.
Figure 1: Emissions Projections
There are three scenario groups that are commonly used for reporting projected emissions and emission reduction potentials:
- Without Measures (WoM, formerly known as “Business as Usual” or “Baseline” scenarios): presents a picture of the expected outcome of emissions if the measures that are currently in place had not been implemented and no new specific policies or measures are implemented. These scenarios are often referred to as a “Business As Usual”, “Reference” or “Baseline” scenarios. Usually these “With out Measures” scenarios present the expected activity growth (e.g. population, economy, industrial production) without additional controls or policies (or without further implementation of them) specifically designed to reduce emissions (e.g. IPPC, renewables policies, vehicle abatement). Without Measures Scenarios usually start from a convenient historic year (e.g. 1995 or 2000) and the impacts of existing measures for those years removed from the historic estimates.
- With Measures (WM, formerly known as “Policies in Place” or “Policies in Pipeline” scenarios): presents a picture of the expected outcome of emissions includes existing policies and measures. Existing policies and measures are those for which one or more of the following applies: (a) national legislation is in force (Current Legislation); (b) one or more voluntary agreements have been established; (c) financial resources have been allocated; (d) human resources have been mobilised; (e) an official government decision has been made and there is a clear commitment to proceed with implementation. It is good practice for the starting year for with measures scenarios to be the latest year of the historic inventory.
- With additional Measures (WaM, also known as “Best Available Technology” scenarios): presents a picture of the expected outcome of emissions if, on top of WM,projections will encompass planned policies and measures with a realistic chance of being adopted and implemented in time to influence the emissions. . It is good practice for the starting year for with additional measures scenarios to be the latest year of the historic inventory. Maximum Feasible Reduction (MFR) would be a variant on the with additional measures scenario that includes the furthest reaching action that can be achieved through all possible technical and non technical measures. Sometimes Maximum Feasible Non Technical Reduction (MFNTR) and Maximum Feasible Technical Reduction (MFTR) are presented separately.
- MFNTR includes measures such as economic drivers (e.g. fuel price rises) and behavioural change (e.g. awareness raising).
- MFTR includes measures such as abatement and control or the encouragement of new technologies.
Note: In some cases other and sometimes conflicting terms and interpretations are used (e.g. Business as Usual is used by countries to refer to the expected outcome “With Measures” Scenario). It is good practice when documenting scenarios to refer to the “WM, WoM, WaM” scenario and definitions in order to be clear on what the projection represents
Current Reduction Plans (CRP): A Current Reduction Plan is not a scenario but is a politically determined intention to reach a specific national emission reduction target (or “emission ceiling”), as defined in the various Protocols of the UN/ECE-CLRTAP. Such an emission reduction target is not regarded an emission projection. However, it may have originated from a particular scenario estimated at the time of setting targets.
It is good practice for the starting point, for the ‘with measures’ and ‘with additional measures’ projections, to be the latest year for which inventory data are available. For the ‘without measures’ projection, the starting point can be an earlier year such as 2000, 1995 or 1990 and used to illustrate emissions savings achieved to data as a result of implemented policies measures.
It is good practice for projections to be estimates relative to unadjusted inventory data for the preceding years.
3Methodological Choice
Emission projections are, as with emission inventories, a function of a rate of activity (activity data) combined with an (emission factor) emission rate or controls applicable to the source. However, with projections a number of elements that make up the Activity Data and Emission Factor can not be measured or counted and have to be estimates or modelled using assumptions about future activities and future emission rates.
- Future Activity: Future activity assumptions are based on forecasts of industrial growth, population growth, changes in land use patterns, and transportation demand. Energy models often combines the above basic growth factors with energy price information to estimate energy demand by sector and fuel. These models can be used as a core dataset as long as the assumptions underpinning them are consistent with national economic strategies and policies and measures.
- Future Emission Factor:. It is good practice for the changes in the emission rate of sources, influenced by technological advances, environmental regulations, age or deterioration, how the source is operated, and fuel formulations to be reflected in the emission factors used for these future years. Rates of penetration of new technologies and/or controls are important in developing the right sectoral emission factors.
It is good practice for a tiered approach to be used to estimate projections, where key sources [1]or sources where changes in technology or controls are expected to be significant are estimated using tier 2 or tier 3 methods. The decision tree below outlines the approach to take.
Tier 3 projections are where detailed models are available that provide emissions projections taking account of a number of complex variables and parameters. However, these models must us input data that is consistent with national economic, energy and activity projections used elsewhere in the projected emissions estimates.
Tier 2 projections would be expected to take reasonable account of future activity changes for the sector based on national activity projections and where appropriate (where measures are applied to a source) take account of future changes to emission factors. Expect to stratify your source category in order to apply the appropriate new technology or control factors to sub-sectors.
Tier 1 projection methods can be applied to non-key categories and sources not expected to have future measures applied. Tier 1projections will only assume generic or zero growth rates and basic projected or latest years historic emission factors.
3.1Formula:
The following general formula for projecting emissions for each source is based on projecting forward an existing historic emissions inventory[2]. The basic function involves two key elements (the Activity Growth factor and the Future Emission Factor) will need to be applied in varying forms of complexity depending on the need to incorporate future technologies and controls.
The simplest form is :
Where:
En = The source emission calculated for the projected year n
ADs = The Activity data for a historic year chosen as the starting year for the projection
GFn = The growth factor for the activity to year n
EFn = A emission factor appropriate for the future emission rate of the source.
Where no changes are expected to the emission rate EFn or the source is not a Key Source EFn can be set to the latest historic emission factor. Where a source responds to a simple global measure (e.g. a change in the sulphur content to the fuel), EFn can simply be applied to the whole sector. However, where a policy or measure applied to a source is complex and has an incremental affect on the overall sectors emissions performance, or contains a number of different technologies or controls, the following equation will be needed to derive an appropriate national average factor EFn that takes account of the penetration of that technology or control.
Where:
Efn = The emission factor calculated for the prjected year n
EFt = The emission factor for a source using a specific technology or control
ADt = The projected activity data (consumption/production) for a source using a particular technology or control.
p = the total number of technologies
ADn = The projected activity for the whole source in year n (= Ads * GFn).
3.2Understanding available Technologies:
Details of current technologies and controls and their emission factors and abatement factors can be found in the individual sectoral chapters. However, future technologies that have not been introduced may not be available. Suitable data may be available from national test measurement activities, indicated as limit levels in draft legislation or, for industry, from BREF notes that provide details of possible technologies.
3.3Stratification:
There will be many cases where historic emissions cannot be projected using simple growth factors or future emission factors because of complexities in the mix between new and existing emission performance. Stratification helps to account for penetration of measures over a number of years by sub-dividing the sector into it’s components so that the application of measure can be applied to the appropriate fraction of the sectors activity for each year of the projection.
Box on Stratification:
- Road Transport showing the need to break down the source sector by euro class in order to apply the technology uptake factors for each class type.
- FGD showing the need to stratify the power generation sector into FGD and non FGD plant in order to apply the reduction factors expected for the converted FGD plant into the future.
Stratification is only required in cases where emission controls are applied to sub-sectors (e.g. for road transport activity needs to be stratified by age of vehicle so that improved emission factors for newer vehicles can be applied appropriately).
3.4Simplification:
In many cases future activity forecasts (e.g. employment, transport, energy use) will be at a higher level of aggregation that the underlying inventory data. Often fuel types are not broken down in as much detail (e.g. solid fuel) or sectors are more highly aggregated (e.g. a forecast for industry coal may not separate out all of the individual sectors within the inventory). Where appropriate these more aggregated datasets can be used to derive growth factors (GFn) that can be applied to a number of individual sectors. Care should be taken to ensure that the growth factor is representative for the individual sector.
Box on simplification:
Example of Energy forecasts applied to historic emissions inventory.
3.5Checks and controls:
It is important to ensure that resulting emission projections portray a consistent picture to the underlying input data. In particular, checks to the energy related emissions should ensure that energy consumption by fuel derived for the individual sectors in the projected emissions matched the energy consumption used as input to the estimates. Other important elements include ensuring that the transition from the latest year of the emissions inventory to the first year of the projection is realistic. Checks for large step changes in each sector should be undertaken and explanations noted or methods modified.
For a number of countries national projections can be cross-checked against some international datasets held by the Commission. PRIMES provides a centralised view on energy demand across Europe and the CAFÉ GAINS model uses a number of national and international datasets (including PRIMES) to derive detailed emissions projections for a number of pollutants and sectors.
3.6Dealing with gaps in projected data.
For Key Sources it is good practice to fill any projection gaps with national projected estimates through the development of new models or accessing new data on national projections. Where matching projected statistics (e.g. projections of fuel combustion and cement production in cement plant to match historic statistics) are unavailable “surrogate” projections (e.g. housing growth) can be used to help forecast future activity. For non key sources, where no appropriate data or surrogates are available for a source sectors, it is good practice to assumed projections to be the same as for the latest historic year of the inventory. This approach can be applied to the activity data and/or the emission factors where no other data is available.
Issues relating to non disclosure may be encountered (at a sectoral or spatial level) that may impose barriers to acquiring data. As only highly aggregated output data is needed for reporting, signing of non disclosure or confidentiality agreements or asking the data supplier to derive aggregated datasets may improve the accessibility of this data. It will be important that issues relating to this are identified and dealt with in consultation with the national statistical authority.
3.7Data Sources:
The complexity of emissions projections will depend on the level of data available in the country. As a minimum, for good practice, national government sources of data should be used for all key sources. It is good practice for the National government sources of information to be used in preference to other national or international datasets.
3.7.1National Sources
National projected emissions should aim to be consistent with other national activity projections (e.g. Agricultural productivity, population growth, energy demand and supply and industrial production). It is Good Practice to use these national datasets, where they exist, as a starting point for the activity projections in the scenarios. The following datasets are often available from government representatives and Stakeholders and can provide the basis for activity and emission factor projections.
- Statistical departments. Socio-economic projections data (Economic Growth, population, production/consumption)
- Government departments: Sector specific data on activities and policies and measures should be gathered from the different government departments. Available datasets could include (Agriculture activity and livestock, Agricultural practices and emissions, traffic forecasts, energy supply and demand).
- Regulators: Plant upgrade plans, emission limits BREFs
- Industry & Industrial trade associations’ views on growth and technological implementation. Views can sometimes be political and resistant to change.
- Vehicle and Engine manufacturers and regulators
Any policies and measures designed to meet national and international commitments for emission reductions (e.g. directives, protocols etc) should also be used as a key input to emission projections. These may provide assumptions about plant/vehicle replacement, implementation of new technologies and controls from the industry and regulators and include factors on penetration of technologies, population, economic and transport growth. Where possible projections should also include assumptions about the impact of non technical measures (e.g. low emissions zones and carbon trading) and indirect impacts of other policies and measures (e.g. air quality directives & climate change activities).
Future emission factors should be based measured data for in service technologies and fitted abatement. Where this is not possible (e.g. for emerging technologies) future emission factors should be estimated using expert judgement or based on limit levels from regulators and industry and flagged to have a higher level of uncertainty.