05 June 2016
CO2 emissions trading schemes—which allow factories, businesses, or even countries to trade emissions allowances—were created to reduce emissions in the most cost‑efficient manner. Those emitters for whom the costs of cutting emissions are high would trade with others where the costs are low, meeting the same climate targets but at a lower price.
However, carbon markets have been floundering. This is in part because of substantial unknowns about how much greenhouse gas is being emitted and how much it will cost to reduce it. “These are major uncertainties” says IIASA researcher Tatiana Ermolieva. "We created a prototype model of a carbon market that shows that if emitters could reduce them it would be of great benefit.”
“Let’s say trader A is looking to buy carbon credits from trader B. Trader A works out how much they are willing to pay based on their average emissions. But if their emissions turn out to be higher they must buy more permits at a later date to fulfill their climate targets. Because they can no longer buy in advance the prices are higher.”
If trader A had been able to predict their emissions more precisely they would have been able to buy closer to the right number of credits in the first place, saving money. Countries or factories can do this by investing in more research or better monitoring equipment which can reveal more exactly how much they emit.
Reducing uncertainties also creates a more stable, forward‑thinking market. Investing in emissions reductions technology requires traders to take the long view, calculating that in five or ten years, when the equipment is paid off, they will be in a better position. Under a more stable market, traders may decide that their money is better spent on abatement technologies, ultimately driving more sustainable solutions for emissions reductions.
Text by Daisy Brickhill
Ermoliev Y, Ermolieva T, Jonas M, Obersteiner M, Wagner F, Winiwarter W (2015).
Integrated model for robust emission trading under uncertainties: Cost‑effectiveness and environmental safety. Technological Forecasting and Social Change 98:234–244.
Last edited: 22 August 2017
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