To evaluate government policy in more detail we need to be able to determine the relative effects of different trends, technological changes or policy measures. This type of analysis can help to show the impacts of different policy instruments, and can be performed in retrospective and in forward-looking modes. Such an analysis of individual policies is data and labour intensive, so it is considered here as an advanced part of policy analysis.
|Figure 29: Breakdown of the effects
of environmental policies on
greenhouse gas emissions in the
EU-15 (MNP/RIVM, 2004)
Consider the environmental state issue of the atmospheric concentration of CO2 in the context of the European Union. One of the key pressures on this environmental state is the emission of greenhouse gases. Figure 29 presents an example in which the effects of different policies on greenhouse gas emissions are analysed for the EU-15 in the period 1990–2001 along with an estimate of the level of greenhouse gas emissions in the absence of different type of policies (Harmelink and Joosen 2004).
Greenhouse gas emissions in the EU-15 were more or less constant on the same level during the period 1990–2001 (EEA, 2003). It is estimated that in the absence of policies in the period 1990–2001, greenhouse gas emissions would have risen by 4.7 per cent.
The following policies are analysed in this example:
- Renewable energy policies.
- Landfill gas policies.
- Best available technologies for adipic acid production.
- Cogeneration (combined heat-power) policies.
- Efficiency improvements in the built environment.
- Common Agricultural Policies.
The effects, in terms of CO2-equivalent attributed, are sensitive to assumptions with respect to the reference case. The choice of the reference is arbitrary, and therefore always must be described, because other references may result in other outcomes (and other conclusions) (to be further detailed).
Figure 29 also illustrates the “distance to future policy targets” by including baseline projections and comparing them with the EU policy target under the Kyoto Protocol. It indicates how much emission reduction needs to be achieved with additional measures to realise this emission target.
The most simple and therefore most commonly used method to compare the effects on the level of emissions of different changes is to compare all of these changes with the same baseline. The baseline is defined as “what would have happened if the changes had not occurred.” Or, in other words, “what will happen if these changes don’t occur.” Because the answer to this question is always hypothetical, often the easiest answer is chosen: nothing will happen in the production-structure.
|Figure 30: Electricity production by
source 1990-2000 (in PJ electricity)
For example, when one wants to evaluate the effect of the increase of nuclear energy, the average emission factor of the production of electricity of the base year is multiplied by the electricity production of nuclear plants for a specific year. This comparison can also be made for other changes and measures, for example the increase in renewable energy or the increase in cogeneration.
This method is easy to use, and it gives a good insight into the scale of the effect of changes and how the measures relate to one another. However, it’s not really reflecting all complexities. A nuclear power plant is a source of base load electricity (producing a steady, constant power source), as opposed to other power sources, such as wind generators, which only operate when the wind blows. When such differences are taken into account, one can get a better sense of the real impacts of different approaches. This type of analysis will be more realistic, but it takes considerably more time and data to do.
The fact that a variety of changes and measures occur simultaneously is a complicating factor when analysing the effectiveness of policy because it makes it more difficult to distinguish between the effects of individual measures. Because results will depend on the method chosen, measures have to be interpreted with caution. We can present some alternative methods for analysis and illustrate which methods can be used under which conditions.
The emission of CO2
by the electricity generation sector in the Netherlands (Figure 31) is an example that illustrates such an analysis.
Emission of CO2 by the electricity generation sector in the Netherlands
Since 1990, electricity production has risen at a faster rate than the amount of CO2 emitted during the generation of this electricity. The question is, how this can be explained and what role has policy played in this change?
Since the end of the 1980s, Dutch policy has been to encourage energy savings and reduce CO2 emissions. In 2000, total electricity production in the Netherlands was 377 PJ, having risen from 282 PJ in 1990. For the purpose of this analysis, the electricity production is divided into:
- central generation by companies primarily engaged in electricity generation;
- decentralized generation by companies for whom electricity generation is a secondary task, mainly CHP;
- remaining decentralized generation by companies for whom electricity generation is a secondary task, all non-CHP units;
- renewable generation (wind, solar, etc); and
- net imports (balance of imported and exported electricity).
Comparing Figures 30 and 31 we can see that electricity production is rising much faster than the CO2 emissions. The possible causes of this decoupling are:
- import of electricity;
- increased production of electricity by decentralized CHP plants;
- more efficient generation by central power stations;
- shift in fuel mix by the central power stations; and
- increase in renewable electricity generation.
|Figure 31: CO2 emissions by energy
There are various methods to determine the effects on CO2
emissions of the above trends. The method of the individual trend is already described in the previous section. However, if a number of trends occur simultaneously they will influence each other.
Composition/decomposition methods assume the simultaneous occurrence of various trends, the outcome being sensitive to the sequence chosen. A number of conclusions can be drawn about the applicability and utility of these methods. Several methods to evaluate changes and measures exist. All give different results and one is not better than the other, so it is very important that when presenting the results the method chosen is also explained.