Defining Additionality
The professional lexicon of climate policy has an air of maturity. Melding climate science terminology, esoteric domain concepts, and countless three letter acronyms (TLAs), carbon wonks are known to dialogue in an inaccessible jargon so rich it may, to the uninitiated, appear to border on another language. Yes, by this hollow measure, climate policy would seem to have the trappings of more established professional fields. Yet, a cursory look at the definitions associated with carbon’s work bank rather nakedly underscores our discipline’s immaturity. Nowhere in climate policy is language and definition more confused than the concept of additionality.
Additionality, often called out as the very crux of many important climate programs, is simultaneously described as challenging, slippery, elusive, thorny, and even controversial. These charged adjectives are reflected in discourse on the topic, which ranges from highly acrimonious debate on the challenges of (often quite narrow) application (e.g., CDM EB E+/E- decisions) to altogether omission of additionality for fear of “having an additionality conversation.” Indeed, I don’t think it would be an overstatement to say that additionality is today considered notoriously difficult to discuss.
Perhaps the most overlooked dimension of the failure of the additionality dialogue is a crisis of definition. Definitions of additionality and the supporting concept of baselines utilize a range of ambiguous non-standard terminology. What’s more, cutting through the challenges of specific word choice, at a more basic level, definitions of additionality generically fall into a trap of a circular definition, identifying the same component as both cause and effect.
In a nod to the importance of additionality with respect to climate policy and in a further acknowledgement to the rather low point at which discourse on the topic currently sits, GHGMI has recently released a three-part discussion paper that aims to reinvigorate the additionality discussion by taking a step back and methodically considering the aspects that appropriate definitions must account for. The three papers are pithily summarized below; we hope that considering this topic from a different and more fundamental perspective provides the grounding necessary to foster a more productive dialogue on the topic. As such, we look forward to your comments.
What is Additionality? Part 1: A long standing problem
Part 1 looks at the history of the concept and addresses —and attempts to resolve—some of the problems with definitions used to date. The paper makes the bold claim that the way we have thought about additionality in the climate change policy and carbon markets community has been based on a circular definition. It then offers improved definitions of both additionality and baseline for use by scholars and offset program policy makers. (Download Part 1 here.)
What is Additionality? Part 2: A framework for a more precise definition and standardized approaches
Part 2 goes further by looking at the application of the additionality and baseline concepts to standardized approaches. This paper examines the issue at a theoretical level incorporating guidance from social science and program evaluation. It provides an intellectual framework for thinking about additionality and baselines when the key concept of a policy intervention is included. (Download part 2 here.)
What is Additionality? Part 3: Implications for stacking and unbundling
Part 3, lastly, applies the concepts developed above to the issue of offset credit stacking. It concludes with specific options of how to implement a credible additionality assessment process where a single project has the potential to earn more than one type of offset credit. (Download part 3 here.)
Together, we hope these papers will push the discussion on additionality forward after several years of what feels like stagnation.
All three parts of this discussion paper, as well as selected other GHGMI publications, are available for free download on our Research Publications page.
A version of this blog post appeared as a commentary in the March 19, 2011 edition of Thomson Reuters Point Carbon’s Carbon Market North America.
I’m not sure sure that asking “what would happen without the project?” is the common method of defining baseline, but your “what would happen without the policy?” is clearly the right question. It’s not so easy to answer though. Suppose I am thinking of putting a photovoltaic system on my roof and that it has a very small but positive present value. I “should” put it on without the subsidy, but there is no way of knowing whether I would or not. The practical solution would seem to be to put the burden on the regulatory authority. If they have no evidence that I would have installed PV w/o a subsidy, I should be granted the offset.
Things may be easier on a national level. It is possible to estimate (albeit w/ some assumptions) how much a country should invest in increasing its forest carbon even in the absence of an international forest agreement regarding carbon emissions and sequestration. But since the carbon baseline is arbitrary, why not set the baseline equal to the estimate? Now the country gets offset credits only for the amount they increase forest carbon over and above the estimated efficient amount.
Thanks James. Good comments. Although actually if you review the literature or just do a web search, actually what you will find is that “what would happen without the project” is very much the overwhelmingly common way of defining additionality with the carbon offset community.
And yes, predicting behavior is often complicated. If you are saying, though, that it is too complicated to do well enough. Then you are essentially saying offsets should not be used because they are impractical. That is a legitimate conclusion. But just saying additionality is difficult does not get us very far. The question is can we do baselines and additionality well enough to make offsets a reasonably useful policy mechanism relative to the other options.
And I would disagree that a baseline is always arbitrary. We do know some things and can predict some things with some confidence. It is not a complete guess.