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Preparatory Analysis of Uncertain Emission Changes

Preparatory analysis of emission changes (emission signals) allows generating useful information beforehand to ascertain how great the uncertainties could be depending on the level of confidence of the emission signal, or the signal one wishes to detect, and the risk one is willing to tolerate in meeting an agreed-on emission limitation or reduction commitment. It is generally assumed that the emissions path between the base year and commitment year/period is a straight line or of low dynamical order. Historical emissions are typically not taken into consideration. Preparatory analysis of emission signals can be kept highly flexible in order to meet a number of conditions ranging from signal quality (defined adjustments, statistical significance, detectability, etc.) to the way uncertainty is addressed (trend uncertainty or total uncertainty). It is this knowledge of the required quality of reporting vis-à-vis its underlying uncertainty that one wishes to have at hand before negotiating international environmental treaties such as the (post-) Kyoto Protocol.

In addition, preparatory analysis of emission changes exhibits another useful asset; it can also be used to monitor the success of a country in reducing its emissions along a prescribed (e.g., linear) emissions target path between its base year and commitment year/period, which opens up a range of policy-relevant applications.

Overview of FOR’s research on preparatory analysis of uncertain emission changes:

Overview over six preparatory emissions change analysis techniques:

We compare six techniques to analyze the uncertainty in the emission changes that Annex B countries under the Kyoto Protocol agreed to realize by 2008/12:

Jonas et al. (2010): Clim. Change, 103(1 –2), 175 –213
Supporting Material: Mathematical background and numerical results

Overview of IIASA studies

that apply preparatory techniques to analyze and monitor uncertain emission changes of both Annex B countries to the Kyoto Protocol and EU Member States. more

Emissions change–uncertainty monitoring applied: The EU-27 Member States as of 2005:

The EU releases its official greenhouse gas inventories with a time lag of two years and more. The 2005 emissions change–uncertainty monitoring is based on the EU greenhouse gas inventory 1990–2005 released in 2007. The 2006 emissions change–uncertainty monitoring, based on the EU greenhouse gas inventory 1990–2006, will be available soon. more

Impact of uncertainty on compliance and emission trading:
The starting point for this educational exercise is the Kyoto Protocol to the United Nations Framework Convention on Climate Change. The exercise centers on an interactive tool which allows assessing changes in greenhouse gas emissions in lieu of their uncertainties. The tool helps a user get a grip on uncertainty and understand the impact of uncertainty on I) compliance and II) the amount of emission permits that can be traded under the Kyoto Protocol. more

Research issues of interest that emerged in the past:

More on a stochastic technique to detect uncertain emission changes:

FOR put one of the techniques to analyze uncertain emission changes, the verification (more correctly: detection) time concept, on a stochastic basis. In general, deterministically and stochastically determined verification times differ—stochastic verification times tend to be greater (more conservative). This difference can, but need not, matter. This work is pursued in close collaboration with IIASA's IME (Integrated Modeling Environment) Project. Our insights so far are documented in/by:

Hudz (2003): Background paper (IR-02-066)
Hudz et al. (2003): An educational tour
Ermolieva et al. (2007): Background paper and presentation

Grasping the change in uncertainty:

It is generally assumed that our knowledge of uncertainty in the commitment year/period will be as good as today's, in relative terms. Preparatory emissions change analysis techniques allow factoring in the change in uncertainty. Such a change can be due to learning and/or result from a structural change in the emitters. Being able to estimate the change in uncertainty is an important step further in setting appropriate emission reduction targets. Forthcoming material:

Hamal (2010): Background paper (IR-10-003)
Marland et al. (2009): J. Ind. Ecol., 13(1), 4–7

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Last updated: 11 December 2010

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