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5 Cross-sector analysis

In the preceding sections the policy measures that offer additional GHG reductions have been considered at a sector level. These include a wide range of options that build on the many existing measures to contribute to the 2050 target. In this section we draw on the sector level analysis, to rank the measures, to address potential double counting and to assess the total impact and costs.

The most important and objective criteria in this work relate to abatement potential and cost. The overall analysis of measures therefore starts with these. Recognising the inherent uncertainties when considering impacts in 2050, it seems appropriate to group options into broad categories for abatement potential and cost, rather than taking figures as given for an initial prioritisation of options. This is done through inspection of information gathered during the project, as described in Section 4 and the appendices.

As shown below, the highest priority would naturally go to the least expensive measures with the highest abatement potential. Expensive measures of limited potential would be given the lowest priority etc.

Figure 22 Cross Sector Analysis - Concept

An alternative view may be that any option that is low cost should be given very high priority. However, this may divert attention by regulators and other stakeholders towards options with limited potential, and away from options with much greater potential.

Following a review of the range of abatement costs and abatement potential, the following broad boundaries were defined - comprising 4 levels of abatement costs and 3 levels of abatement potential. The selection of the boundaries, allowed the long list of policy measures to be grouped into the 5 categories shown in Figure 22.

Table 37 Categorisation of options with respect to cost and abatement potential.

This is, however, only half of the story. The ranking of measures will also be affected by:

• Confidence in data and associated uncertainty
• Ancillary effects (e.g. on air quality or employment)
• Acceptability of measures (e.g. regarding nuclear power)

These need to be factored in at a second stage in the prioritisation process. Where there is major concern it may be appropriate to drop an option down a category in the ranking. Where there are significant additional benefits to an option, or comparatively low uncertainty it may be appropriate to move an option up a category.

In most cases, it would not be recommended to move an option by more than one category through consideration of secondary concerns - the main drivers for the prioritisation process have to be the costs and effectiveness of dealing with GHG emissions. There are some exceptions, where measures are considered completely unacceptable. In these cases sensitivity analysis could be applied. Options where the non- GHG benefits of a measure are so significant that the measure will be adopted irrespective of climate concerns should be included throughout.

The scores associated with emissions savings and costs are shown in Figure 22. Uncertainty scores range from 0 (relatively certain) to 1 (relatively uncertain) and the "other factor" scores range from -1 (positive ancillary impact) to +1 (negative ancillary impact). The ancillary impacts may be beneficial hence strengthening the case for an option and increasing the priority of the option. Alternatively, the option may have undesirable secondary affects, in which case the priority of the option is reduced.

We recognise that there is a degree of subjectivity in assignment of uncertainty and "other factor" ratings, which are based on expert judgement from those responsible for each sector. Further work would be needed to fully assess the ancillary costs and benefits of each policy option.

This prioritisation process is perhaps best explained by an example. Taking policy option D1, improving the building standards for new housing from 2010, to give a 20% reduction in CO ₂ emissions from 2007 standards:

• The emissions savings associated with this policy are 92 ktCO ₂, which rates as Low abatement potential according to Table 37.
• The abatement costs are £367/tonne, which rates as High cost according to Table 37.
• The Low abatement score and High cost score combine to give an un-adjusted combined score of 5, based on the concept illustrated in Figure 22.
• There is no adjustment for uncertainty as the savings associated with this policy are considered to be relatively certain. The uncertainty score is based on our sector expert's view of the relative certainty of the emissions savings associated with the measure. This will in turn be influenced by their view of the feasibility and likely acceptability of the measure.

The policy is rated as -1 under the "other factor" rating, to account for the positive ancillary impacts of this policy, particularly the effects on fuel poverty. This moves the final rating for the policy up to 4, and so the policy appears within the list of Low priority measures in Table 40. This "other factor" is also used in connection with renewables support, where the score is +1 to reflect the additional and unaccounted for costs of grid upgrade. This process leads to the definition of a set of scenarios for assessment of abatement potential and costs:

• Business as usual / baseline / reference
• Adoption of 'Very High priority measures' (Group 1)
• Adoption of 'Very High' (Group 1) and 'High' priority measures (Group 2)
• Adoption of 'Very High' (Group 1), through to 'Medium' priority measures (Group 3)
• Adoption of 'Very High' (Group 1), through to 'Low' priority measures (Group 4)
• Adoption of 'Very High' (Group 1), through to 'Very Low' priority measures (Group 5)

5.1 Defining each group of measures

The following tables list the policy options in each priority category for 2050:

As described above, the tables show the initial weighting which is based on cost-effectiveness and emissions abated only, for the case where options are introduced in isolation of each other. The weighting is then revised taking account of uncertainty (where it would be sufficiently large to affect the rating according to Table 37 and other factors that may either make the rating better or worse. Within each priority category, measures are then ranked in terms of cost-effectiveness.

Once the final rating is determined, the final abatement potential for each measure is calculated, when in series with the other options being considered. The series abatement calculation is brought in to avoid double counting emission cuts already accounted for. The method used for calculating adjusted emissions savings depends on the nature of the policy and the other measures that have already been taken up. For example:

• Savings from measures that save electricity only, such as high efficiency lighting (policy D5) are assigned a zero emissions saving because the electricity generation sector has already been decarbonised through the introduction of carbon capture and storage (policy E1). Note this is a simplifying assumption since CCS is only 90% effective in emissions reduction and so there will be residual emissions from power generation.
• A policy to introduce nitrogen inhibitors in fertilisers (policy A7) gives lower emissions savings than it would have done in isolation as it is introduced after improved efficiency of fertiliser use (policy A3).
• Emissions savings from powertrain technology measures for road transport have been calculated on the basis that different powertrain technologies are mutually exclusive. This means that the abatement potential from the most cost effective options are included first, and then less cost effective options with greater abatement potential are included in the analysis later, with the important caveat that the earlier, more cost effective powertrain options with lower abatement potential are removed from the analysis to avoid double counting. Hence, battery-electric technology for cars (policy T7) has been chosen in preference to other measures for cars (policies T1-T4) because policy T7 offers a deeper cut albeit at higher abatement costs.

Having allotted options to these different groups, emission savings can be summed, starting with Group 1, as these are generally the measures that make the most difference to total emissions and are most cost-effective. The total impact of implementing each category of options in series can be seen in Figure 23.

The tables also show the policy cost associated with each measure, this is the series abatement potential times the cost of abatement. The policy costs for the more certain policies in Groups 1 to 3 are shown in Figure 25.

Table 38 List of Very High priority measures

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Table 39 List of High priority measures

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Table 40 List of Medium priority measures

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Table 41 List of Low priority measures

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Table 42 List of Very Low priority measures

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5.2 Emission savings and costs

Emission savings and costs are shown in Figure 23 and Figure 25 respectively. It has not been possible to provide costs for Groups 4 and 5 because there are high uncertainties associated with many of the measures in these groups, particularly in the agricultural sector.

There are considerable uncertainties in both costs and emissions savings for measures in Groups 1 to 3 too, which is to be expected given the scope and timeframe of this study and the fact that we are looking ahead over 40 years. Sources of uncertainty include:

• Lack of inclusion of upstream and infrastructure costs for some fuels and technologies, e.g. grid reinforcements required for widespread renewable energy take-up.
• Incomplete accounting for changing costs going forward e.g. learning costs for new technologies. Learning effects have been taken into account where data is available, e.g. for photovoltaics in building applications, but in many cases no information is available after 2020.
• Incomplete accounting for inter-linkages, interactions and trade-offs between sectors, e.g. decarbonised electricity and the implications for choice of measures in end use sectors.
• A degree of in-built optimism about the extent of savings that could be achieved by some measures as they assume maximum effectiveness and/or take-up, including the policy measures in the baseline projection. This optimism has not been borne out historically. For example, many years of energy efficiency programmes in the households sector have not yet achieved full uptake of cost-effective measure such as cavity wall insulation because of a range of non-technical barriers, and improvements in engine technology have mainly led to increased vehicle performance, comfort and safety rather than reduced fuel consumption.

The total reduction for Group 1 through to Group 5 is about 75% of the 1990 emissions considered in this study ⁶¹ - hence achieving an 80% reduction would appear to require all of the measures included in Groups 1 to 5 plus new measures that will become available or feasible in the period up to 2050. The measures in Groups 1 to 3 together deliver around 63% emissions reduction on 1990 levels ⁶¹.

Figure 23 Cumulative effect of measures in each group defined in the main text compared to 1990 emissions, the 2050 baseline and an 80% cut in 1990 emissions

The following chart shows the residual emissions after all the measures in Groups 1 through to 5 have been applied to the 2050 baseline.

Figure 24 Residual GHG emissions in 2050

This highlights that the sectors with significant residual emissions in 2050 are Transport (mainly aviation and marine sources) and agriculture.

The costs determined for Group 1 measures are £5 million, subsequent measures in Group 2 increase the total cost to £600 million, while the cost in 2050 of achieving an emissions reduction of about 63% by implementing Group 1-3 measures is estimated to be about £1.7 billion ⁶² expressed in 2005 prices.

Figure 25 Cumulative costs as each group defined above is brought into the analysis

This impact covers just the cost of implementing the identified measures and does not taken into account the wider economic and societal costs and the wider potential benefits. It is not possible to give a reliable estimate of the additional costs of measures to reduce emissions beyond 63% as many of the measures in Groups 4 and 5 are very uncertain at this stage.

The shape of Figure 23 and Figure 25 are sensitive to the assumptions made about technology choice in the electricity generation sector, although the overall conclusions are less sensitive. Our analysis here implicitly assumes all electricity is generated from coal with CCS at a carbon removal efficiency of 90%. This is because CCS is a Group 1 measure while significant support for emerging renewables falls in Group 2. If we were to make the assumption that all electricity will be generated from renewable sources then the net carbon emissions after implementing Group 2 and subsequent measures would fall, but the costs would increase. In practice, of course, it is much more likely that electricity will be generated in a range of ways in 2050, including both renewables and coal with CCS.

5.3 Problematic measures

A number of measures considered in the sector chapters have not been included in the above listings as a result of specific issues relating to their implementation (see Table 43).

Table 43 List of measures subject to specific problems in implementation

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