Abstract
Operationalizing a Global Carbon Observing and Analysis System (www.geocarbon.net) would provide a sound basis for monitoring actual carbon fluxes and thus getting quantities right when pricing carbon – be it in a cap-and-trade scheme or under a tax regime. However, such monitoring systems are expensive and—especially in times of economic weakness—budgets for science and environmental policy are under particular scrutiny. In this study, we attempt to demonstrate the magnitude of benefits of improved information about actual carbon fluxes. Such information enables better-informed policy-making and thus paves the way for a more secure investment environment when decarbonizing the energy sector. The numerical results provide a robust indication of a positive social value of improving carbon monitoring systems when compared to their cost, especially for the more ambitious climate policies.
Highlights
The current knowledge about climate change is plagued by uncertainties
Following the approach outlined in Kryazhimskiy, Obersteiner, and Smirnov (2008) and Chladná, Moltchanova, and Obersteiner (2006), we introduce the possibility to invest an arbitrary amount into an improved monitoring system at the beginning of the planning horizon, which will result in a decrease in the resulting carbon price volatility
We see that with an expansion of monitoring equipment, the CO2 price variance decreases and so does the price triggering the lower carbon technology. Note that both are independent of the stabilization level we are investigating, while this does matter for the timing of investment into CO2 capture and storage (CCS)
Summary
The current knowledge about climate change is plagued by uncertainties. There are major uncertainties about climate sensitivity and about the thermal lag of the climate system In this study we focus on the question of how the investment decisions into carbon-neutral technologies are affected by future CO2 price uncertainty and to which extent a decrease in CO2 price volatility affects the resulting investment cost and behavior and the success of the policy to decarbonize the energy sector This serves to quantify the economic value from having a better monitoring system, i.e. we can use these estimates to derive the benefits (or the maximum investment cost that can be justified) of an observing system as well. Evaluation of a network example As an example, we define an observational network that consists of 41 sites collecting monthly samples of the atmospheric CO2 concentration and 10 sites providing direct flux measurements on an hourly time resolution, covering all PFTs that are available to BETHY over Europe Both component networks are described by Kaminski et al (2012), where they are, respectively, denoted as “flask” and “flux”.
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