If the American Clean Energy and Security Act of 2009 works its way through the Senate and onto President Obama´s desk, it will mark a significant paradigm shift for the value we place on carbon emissions and uptake. As part of the developing legislation, large emitters would be required to pay for their emissions using a cap and trade scheme (explained here and here). For such a system to work, government regulator must have an accurate means of accounting for both carbon emissions and carbon storage and sequestration.
Much of the groundwork for a carbon accounting system has already been put in by government agencies and organizations such as WRI, which has been integral in creating a standardized carbon accounting framework called The Greenhouse Gas Protocol. In the emerging carbon market, which could be valued in the trillions of dollars, there will be winners and losers, and the agencies tasked with administrating the market will no doubt run into rule-breaking in the forms of underreporting and misleading accounting. Market regulators will need to take advantage of both the traditional carbon accounting tools, which can be efficient and accurate if correctly employed, and new remote sensing technology, which holds the potential for providing detailed environmental data.
Past remote sensing technology hasn't been able to measure carbon dioxide at policy relevant scales. However, as satellite based sensors progress and innovative data analysis techniques are refined, remote sensing approaches to monitor the carbon cycle could play a central role in regulating the carbon market.
Dr. Anna Michalak, an environmental engineer from the University of Michigan, has developed with her colleagues a new method for tracking the sources and sinks of atmospheric carbon dioxide. In order to better understand how their method could affect policy and provide data for carbon markets, I asked Dr. Michalak for her assessment of the state of the science, and what it could mean for the future of carbon monitoring.
How might your research and the techniques which you´ve developed aid policy makers and administrative agencies?
The research that we do allows us to use atmospheric measurements of carbon dioxide, together with our understanding of wind and weather patterns, to trace the carbon back to its sources and sinks around the world. Sinks, or uptake, of carbon takes place both on land and in the oceans. These natural components of the carbon system can also become sources, or releases, of carbon for certain locations and periods. The main sources of carbon to the atmospheric, however, are human emissions from fossil fuel burning and other activities.
What is unique about the methods that we have developed, which are based on a framework called geostatistical inverse modeling, is that they allow us to directly merge the atmospheric data with other information, such as satellite observations of the Earth surface. This has three huge benefits. First, we can estimate the sources and sinks directly at much finer, and therefore more policy-relevant, spatial scales, which is what is needed if these methods are to be used in support of carbon policy or management. Second, unlike existing method, our tools do not require us to start with a "first guess" of all the sources and sinks. Research has shown that the choice of this "first guess" has a big impact on the final estimates, so we really need to get away from these assumptions if inverse modeling tools are going to be used to verify or evaluate emissions reductions or carbon sequestration. Third, our methods are the only ones that have been applied to all carbon sources and sinks, including sources from human activities.
More generally, the tools that we have developed are helping scientists and policy makers to understand why, how, and where plants, oceans, and people are releasing or taking up carbon. This is important both for the development and verification of effective carbon management policies, and for predicting how the carbon cycle, and therefore climate, will change in the future.
Another way to think about these methods is that, as more atmospheric measurements become available, they will allow us to pinpoint emissions and uptake of carbon everywhere in the world, based on measurement downwind from the locations where these sources and sinks are taking place.
| We are handed a partially stirred cup of creamy coffee, which is the atmosphere, and asked to trace back where and when the cream, or the carbon in our case, was initially added to the cup. |
How do you anticipate administrative agencies might balance/compliment traditional carbon accounting methods with observation and modeling data?
Traditional carbon accounting methods rely on reporting of carbon emissions. While this is an excellent first step, what is also needed is a set of tools for verifying that the emissions, or emissions reductions, that are being reported are accurate. This is where observations and modeling come in. Because we can calculate what the effect of the reported emissions would be on downwind concentrations of carbon dioxide, we can also use these same downwind measurements to infer whether the reported emissions are correct.
This will be helpful for evaluating emissions reductions from industry and other human activities, but also for strategies that are even more difficult to evaluate. For example, how do we know how much carbon is being taken up from the atmosphere if we plant a certain number of acres of forest? It is not practical to measure every tree, but we can measure the net impact of the new forest on atmospheric concentrations of carbon dioxide, and then use the tools that we have developed to calculate the uptake of carbon enabled by this activity.
In summary, observations and modeling can form a system for evaluating and verifying data from carbon inventories and accounting. Given that we are talking about billions of tons of carbon, which could easily be worth hundreds of billions of dollars in a future global carbon market, it is imperative that we have an objective and quantitative way of verifying that the world is getting its money´s worth!
What spatial resolution are you hoping to achieve 5,10, 20 years from now, and how might advances in the technology change your understanding of the carbon cycle?
This is a tricky question, because there is always a tradeoff between resolution and uncertainty. I could give you estimates at a 1 meter resolution globally today, but the uncertainties would be so high that the numbers would not be useful to you, or to anyone trying to use the information in support of policy. Therefore, the real question is, at what resolution does the uncertainty get so high that the estimates are no longer helpful in a practical setting? I think that the honest answer to that question today, if we think of the Earth as a whole, is something on the order of continental scale.
A few regions around the world, North America and Europe most notably, have much more extensive monitoring networks, so that we can support estimates at finer scales. My group currently has a project funded by NASA, for example, where we estimate sources and sinks of carbon for all of North America at a one degree resolution, which is about a 60 mile resolution. The uncertainties are still relatively high, so we then aggregate our estimates to scales on the order of 500 miles to get more conclusive results. One of the nice features of our approach is that it gives you very "honest" answers, in the sense that it can accurately tell you something about the uncertainties associated with your estimates.
The key down the road comes down to having more observations, and continuing to do research on methods that can best integrate all these data. There are several keys to this, including expanding the current atmospheric monitoring network, developing satellites that can measure carbon dioxide from space, and expanding observations of other variables that are important for understanding the natural component of the carbon cycle.
In 5 years, I hope that we will have at least two satellites in space making continuous observations of carbon dioxide. Japan recently launched GOSAT, which is the first satellite designed for making carbon dioxide observations from space. The U.S. recently lost the Orbiting Carbon Observatory (OCO), which was designed to make highly accurate observations of carbon dioxide at very fine spatial scales, shortly after launch. There are ongoing discussions about the possibility of rebuilding this instrument. NASA is also currently developing a satellite called ASCENDS, which would be a laser-based instrument for measuring carbon dioxide from space. In about 5 years, I am very hopeful that at least one of these instruments will be in space. This would allow us to estimate sources and sinks of carbon on scales that really do become relevant to international agreements and policies. The scales that I predict that we will be able to tackle would be the country scale for larger countries (e.g. United States, Russia, China), and continental scales for regions with smaller countries (e.g. European Union).
In 10 years, some of the early carbon dioxide sniffing satellite will likely be retired, replaced by newer and better sensors that will further help us to zero in on individual regions.
In 20 years, I foresee that we will have a coordinated global carbon dioxide observing system, that will integrate a constellation of carbon dioxide observing satellites and an
| we will be able to conclusively verify specific emissions reduction targets |
In developing this new approach, have you been surprised by any of your findings?
Before we developed the geostatistical inverse modeling tools, the conventional wisdom was that you needed to start with a first guess of the sources and sinks of carbon everywhere and all the time, because there was not enough information in the available data to estimate these carbon releases and uptakes independently. I actually partially agreed with this view, and thought that our method would provide an honest answer based only on the available data, but that the price would be much higher uncertainties on the estimates. It turned out, however, that the method is able to really leverage the information content of all of our available data sources, to the point where the uncertainties are actually lower than previous methods in many cases, and we still manage to avoid many of the assumptions that went into these earlier approaches. In other words, the methods performed even beyond our own expectations!
One nice example of this is that when we estimate carbon fluxes over North America, we can clearly identify the carbon uptake in the Midwest agricultural belt in the summer. This is quite a small-scale feature that I would not have guessed that we could easily identify it. Another example is that our methods are actually able to differentiate among different existing fossil fuel inventories, and identify the better ones based on the information content of the atmospheric data.
Smokestack image credit: Ian Britton
Satellite image credit: NASA
Carbon map credit: Sharon Gourdji and Anna Michalak, University of Michigan
