CARBON OFFSETS IN FOREST AND LAND USE
Brent Sohngen (Ohio State University)
Paper prepared for the National Academy of Sciences Workshop on Assessing the Economic Impacts of Climate Change
April 15-16, 2010. Washington, D.C.
Since the 1980s, forests and agricultural soils have been widely considered as an important, and low cost, option to reduce net atmospheric greenhouse gas emissions ( Richards and Stokes, 2004). Recently, as the United States and international community have inched closer to making stronger legally binding commitments to reduce greenhouse gas emissions, policy makers have further recognized the potential benefits that forestry and other land based offsets can provide. If, as their promoters suggest, forest carbon offsets cost less than options in the energy sector, they may be able to reduce the overall costs of climate mitigation to society. Some studies have suggested that forestry carbon offsets can reduce the costs of stringent carbon mitigation policies by up to 40% (Tavoni et al., 2007; Sohngen, 2009).
Given the important role land use plays in mitigating climate change, this paper examines and reviews the current literature on carbon sequestration in forests and agriculture. The paper reviews in particular data, methods and results from a wide range of studies to provide estimates of the potential for land use options based on current knowledge. Given that a large share of the total body of work has been conducted in the forestry area, the report focuses more effort on forestry, but some review of the agricultural options is provided. The report then addresses several issues that have arisen in the implementation of land-based carbon offsets, namely issues like additionality, permanence, leakage, measuring, monitoring and verifying. These issues are important to consider regardless of whether the projects are forestry or agriculture based.
Methods Used to Estimate Costs
The paper begins with an examination of the methods that have been used to estimate the costs of carbon sequestration in forests or agriculture. To date, three general methods have been used to estimate the costs of carbon sequestration in forests and agriculture: bottom up/engineering approaches, econometric approaches, and dynamic optimization approaches. Bottom up/engineering approaches build up estimates by modeling the process and attaching costs and estimates of the carbon gains to various components of the process. They do not account for adjustments in market prices that might arise if the carbon sequestration programs are scaled up. Examples of bottom up models include Moulton and Richards (1990), Parks and Hardie (1995), and Sohngen and Brown (2008).
Econometric approaches rely on large cross sectional datasets, or possibly time-series data sets, and estimate specific economic relationships. Modelers often postulate particular models, and then estimate reduced form components of the broader model. For instance, the 2 model developed by Plantinga et al. (1999) estimates the share of land devoted to different land uses as a function of the returns to different uses, and other factors that influence land quality. Such a model can then be used to calculate a marginal cost curve by altering parameters in the modeling and assessing the resulting predictions of land use change. More recent models have used point data on specific locations and more spatially explicit methods to estimate the probability of land conversion across different uses (e.g. Lubowski et al., 2006). Econometric estimates have also been used to calculate the costs of carbon sequestration in agricultural soils (Pautsch et al., 2001 and Antle et al., 2007).
Optimization approaches focus on modeling the economic system typically by maximizing consumers and producers surplus. In the case of forestry, the optimization models adjust the stock of forests (and consequently the carbon in forests) by altering the age of timber harvest, management inputs, and timberland area. Adams et al. (1999) is an example of a forestry model applied to the United States, and Sohngen and Mendelsohn (2003) is
an example of a global forestry model. Optimization approaches have been widely applied to assess the costs of changes in forest management, e.g., increases in rotation ages or increases in management intensity. Similarly, they have been used to assess the costs of changes in management of agricultural land, e.g., adoption of conservation tillage, or changes in nitrogen fertilizer rates, for example, Murray et al. (2005), and Choi and Sohngen (2009).
There is debate in the literature over which methods are “best” (e.g., Stavins and Richards, 2005; Lubowski et al., 2006), but it is not likely possible to determine which methods are best, or even better, for estimating the costs of carbon sequestration. Each method handles different problems and can be used effectively under a given set of circumstances. For example, bottom-up studies can be very effective tools to get an initial sense for potential costs of different alternatives, particularly when data is limited. Econometric approaches, of course, have the benefit of producing estimates that allow calculation of statistical properties such as confidence intervals. Both econometric and bottom-up estimates, however, typically assume that input and output prices are exogenous, an assumption that may not be tenable under the fairly large land use change programs they seek to evaluate. Recent econometric approaches have developed process-based optimization approaches that utilize the econometric estimates within the context of an optimization model (e.g., Lubowski et al., 2006).
Top down, optimization models, on the other hand, model forest and land management directly, with feedbacks between output, output prices, and the intensity of management. To accomplish this, they are typically constructed to be much more aggregate than the econometric and bottom-up approaches. That is, the typical unit of observation may be a forest type in a specific region of the country (or multiple counties). As computer speeds have increased, modelers have been able to increase their level of disaggregation. The benefit of this approach is that as carbon sequestration policies are modeled, they have impacts on overall land use, which impacts output prices and resource costs. These are modeled explicitly in optimization approaches, allowing direct calculation of the opportunity costs of shifting land from one use to another.
There are relatively few direct comparisons of the approaches. Van Kooten and Sohngen (2007) conducted a meta-analysis of many different studies of carbon sequestration costs and found that methodological differences explained very little of the differences in marginal cost estimates. There is some limited evidence that optimization and econometric estimates are higher cost than bottom up studies, but these results are very dependent on functional form and thus not all that robust. Thus, across a range of 68 currently available studies, their results provide little evidence to support using one method over another to obtain more realistic costs.
Current Cost Estimates
Marginal cost functions for carbon sequestration in forests for three general regions of the world, as derived from IPCC (2007), are shown in Figure C.16. The largest potential exists in tropical countries, due to the carbon benefits (and low costs) of reducing deforestation. The potential in developed countries is fairly large as well, although it is driven by increased forest management. Table C.5 breaks out annual estimates for a number of studies by region and activity, including reduced deforestation, afforestation, and forest management, at a fixed carbon price of $15 per t CO2. These results indicate that around 4.1 billion t CO2 could be sequestered in global forests through various activities over the period 2020-2050 for $15 per t CO2.
At similar carbon prices, $15 per t CO2, national level estimates in the United States of the potential for conservation tillage on cropland to sequester carbon range from 8 t CO2 per year to 168 t CO2 per year (Lewandrowski et al., 2004; Murray et al., 2005). Both of these estimates utilize optimization approaches. The Lewandrowski et al. (2004) study is a single period optimization approach, while the Murray et al., (2005) approach is a multi-period, or dynamic, optimization approach.
A number of regional studies in the United States have examined carbon sequestration through conservation tillage on cropland as well, and they seem to suggest relatively high costs for this activity. Choi and Sohngen (2009) find that in Ohio, Indiana, and Illinois, around 4.1 million t CO2 per year could be sequestered on cropland for $15 per t CO2. These three states account for 26% of the total corn and soybean crop in the United States, so extrapolating these results nationally60 suggests a total potential of only 15.5 million t CO2 per year for $15 per t
TABLE C.5 Average Annual Potential Net Emissions Reductions Through Forestry for the Period 2020-2050
CO2 for the entire United States. Antle et al. (2007) come to a similar conclusion. Looking at 22 Midwestern U.S. states (encompassing the entire corn belt plus additional states further south and west), they find that for $14 per t CO2, 12.8 million t CO2 per year could be sequestered in corn and soybeans. The results from these and other regional studies (Antle et al., 2003; Pautsch et al., 2001) seem to imply that conservation tillage is a fairly high cost option.
Other types of offsets are possible in agriculture, for example by reducing nitrogen oxide and methane emissions. Estimates are most widely available for the United States. Within the United States, Murray et al. (2005) calculate that at $15/t CO2, 32 million t CO2 equivalent emissions could be reduced each year by optimizing N2O and CH4 uses and emissions on farms. A bottom up study by DeAngelo et al. (2006) estimates that the United States can reduce emissions through N2O and CH4 reductions in agriculture by a maximum of 42 million t CO2 per year (at costs as high as $54 per t CO2). A general equilibrium analysis by Golub et al. (2009) indicates that for marginal cost of $27 per t CO2, N2O emissions would be reduced by 59 million t CO2 per year in the United States, and CH4 emissions could be reduced by 22 million t CO2 per year.
Globally, the study by DeAngelo et al. (2006) suggests that an additional 580 million t CO2e per year of offsets can be generated from N2O and CH4 reductions for less than $54 per t CO2. Golub et al. (2009) suggest substantially higher global potential, with up to 1,000 million t CO2 per year of offsets from N2O and CH4 emission reductions for less than $27 per t CO2e. The scale of these offsets globally appears to be around 20% of the total available from offsets generated by forestry.
Data for Estimating Carbon Sequestration Costs
One of the key issues associated with estimating the costs of carbon sequestration in forestry lies with the data. Clearly developing good models and good estimates relies on having access to good data. In general, modelers and researchers have access to some of the best data available in the United States. The USDA Forest Service Forest Inventory and Analysis database (http://www.fia.fs.fed.us/) provides fairly accurate information on the stock of forests in the United States at a given time, and it is available freely to everyone via the Internet. Other developed countries have equally good inventory methods and statistics, but they typically do not provide the data to the public as easily for use in modeling and analysis (see Sohngen et al., 2009 for a description of some of those sources).
Data for estimating carbon sequestration costs in developing countries have been derived from FAO in many circumstances (UN FAO, 2006). Waggoner (2009) illustrates the many problems associated with using the FAO (and many other sources) as a source of data. His data indicates relatively massive potential errors in nearly all estimates of existing forest areas and carbon stocks globally, particularly those currently derived by FAO in tropical countries. For developed, temperate countries, his results indicate that methods have been developed to reduce errors to some extent, but that these errors still could have important consequences. Further, he calculates that the cost of the U.S. forest inventory is about $0.24 per hectare of forestland. Based on this estimate, extrapolating these methods globally to the roughly 3.5 billion hectares of forests out there could cost $800 million per year.
There are other datasets available in developed countries. For instance, in the United States, the National Resources Inventory conducted by the U.S. Department of Agriculture has been widely used by researchers over the years (http://www.nrcs.usda.gov/technical/NRI/). This dataset is collected on farm plots in 5-year intervals. The USDA changed their methodologies in the late 1990s, so the newer datasets are not consistent with older datasets and this presents some problems for long-term analysis, but nonetheless, good data on land uses at present continues to be widely available to researchers.
When considering land use (and not the stock of carbon on forests or the exact type of crop) it is possible to use satellite imagery. The study by Waggoner (2009) suggests that these methods are not yet perfected, although they do provide hope that it will be possible to use them widely in the future to at least pin down the forest area in a given area. It may take longer to develop estimates of the forest stock based on satellite imagery, but of course this technology is coming along.
Carbon Project Implementation Issues
Although the estimates of models suggest that forest and agricultural carbon are relatively low cost compared to other sources, a number of important implementation issues are likely to hinder their widespread adoption. In fact, these issues already seem to have had an effect. For example, the Kyoto Protocol in 1997 included a fairly significant role for forests in the text, but during the course of implementing the agreement, the role for forests has been minimal. Key questions emerged about whether forest carbon credits could be shown to be “real,” “additional,” and “permanent.” Countries were able to include credits from afforestation and forest management (to some extent) in their national allocations, but despite estimates of reasonably low costs, these credits have been a small part of the total. Credits also were supposed to be tradable across country boundaries through the Clean Development Mechanism (CDM), but this mechanism has not worked well for forestry actions. Avoided deforestation thus has not been pursued, despite the large economic potential estimated by various models.
Failing to implement the full range of activities that are possible can have economic implications. A recent paper by Rose and Sohngen (2010), for instance, examined the effects of not allowing credits for avoided deforestation, either in the short-term or in the long-term. Their results show, not surprisingly, that incomplete forestry policies are inefficient. That is, policies that never allow avoided deforestation as an option may cause exceedingly large leakage (Figure C.17). Society can limit the extent of the inefficiency, however, by agreeing in the future to develop more comprehensive programs. Thus, if society just delays the implementation of alternative options like forest management and avoided deforestation, then there will still be some leakage, but leakage will be greatly reduced, particularly in the long run (see Figure C.17).
The surprising scale of potential forestry sequestration raises questions about whether or not these estimates are even realistic. The cost estimates in Figure C.16 imply that society could sequester up to 151 billion tons CO2 in forests by 2030 by shifting management, and by converting into forests an additional 376 million hectares (globally) of land that would otherwise be used for crops. Changes of this scale imply changing land use on 18-19 million hectares per year, or stopping 11 million hectares per year of tropical deforestation, and afforesting in the temperate zone by 7-8 million hectares per year. Society does not have much experience with government programs this large, let alone with programs like this that have been successful. Developing carbon sequestration programs certainly could introduce large transaction costs in the form of broker fees, measuring and monitoring fees, handling fees, insurance fees (including possibly self-insurance), etc. It is important to consider just how society could design a program to actually obtain carbon and to keep these transaction costs at the lowest possible level.
Measuring, Monitoring, and Verification
A forestry carbon sequestration or emission reduction program can only work if a valid system of measuring, monitoring and verifying (MMV) carbon credits on the landscape can be developed and implemented cost-effectively. The article by Waggoner (2009) described above suggests that there is fairly little hope for the emergence of a global measuring and monitoring system that may be effective, but the reality may be more hopeful than his study implies. Waggoner indicates that the United States spends $72 million per year on its USDA Forest Service Forest Inventory and Analysis Program. This program measures, to a reasonable degree of statistical “certainty,” both the extent of forests and the quantity biomass and carbon in the forests. For the 256 million hectares of forestland in the United States (USDA Forest Service, 2008), this suggests measuring and monitoring costs of around $0.28 per hectare per year.
The United States has around 156,540 million t CO2 stored in forests, including above and below ground stocks as well as soil stocks. This means that the costs to measure each ton of CO2 are well less than $0.01 per t CO2. Of course, we are interested in the change in carbon (e.g., the annual sequestration or emission), not the stock, per se. Current estimates of stock changes in forests in the United States are around 650 million t CO2 sequestered each year. This would imply that the costs of measuring carbon changes currently are around $0.11 per t CO2. The $ per hectare number is probably most useful since the measurement program will be essentially the same regardless of the total tons and regardless of the change in tons.
The measurement cost estimates made with the USDA Forest Inventory and Analysis data are far less than those of made by Antle et al. (2003) and Antinori and Sathaye (2007), who suggest that measuring carbon in biological systems could cost around $1-2 per t CO2. Antle et al. (2003) considered soil carbon sequestration, so this may explain to some extent their higher costs. Their results do not consider a program of measurement quite at the same scale as the USDA Forest Service FIA results, but they do show that costs will decrease if larger areas are included in the measurement scheme and economies of scale can be found. The estimates made by Antinori and Sathaye (2007) come from actual carbon sequestration projects, so they likely reflect the relatively large costs of putting infrastructure in place to do measurements where it was not in place before.
In reality, society will ultimately need both sorts of measurements, i.e., national scale systems that are relatively cheap on a per hectare basis, but which provide overall information on the direction and scale of carbon stocks, as well as specific surveys of forests that have been included in a “carbon project.” Obviously, individuals who buy carbon offset credits from specific locations have great interest in knowing whether the carbon actually resides in those locations (not to mention the interest society has in knowing this). They may be willing to pay to install the infrastructure to conduct the local carbon surveys every 1-5 years to detect either changes in carbon storage or maintenance of the sink.
Other Transactions Costs
Other types of transactions costs may have important impacts in the market as well. Given the sheer number of actors in the land using sectors, aggregators who work with individual landowners to create carbon assets are likely to emerge. These aggregators will bundle the carbon assets of individuals with carbon assets of other individuals and then sell those bundles to people who value them. There may be several layers of “bureaucrats” in the middle, between the landowners and those who value the credits, and each of these steps will cost some money.
It is not yet clear how large or important the costs of this bundling activity will be. In a developing country context with many small landholders, Cacho and Lipper (2007) suggest that transactions costs for the buyers alone could be $5-$7 per ton CO2, including MMV costs. Sohngen (2008) looks at the Conservation Reserve Program (CRP) in the United States, which has changed land use on over 12 million hectares in the United States since the early 1980’s, and finds that transactions costs of that program, ignoring MMV costs, would amount to less than $2 per t CO2. In the case of the CRP program, the transactions costs include the costs of the government office-workers and engineers who do the work that aggregators do. These two studies give a reasonably useful assessment of the range of potential transactions costs of $2-$7 per t CO2.
Implications of MMV and Other Transactions Costs
MMV and transactions costs will raise the overall costs of carbon in forestry and land use type projects, but the implications will depend on carbon prices themselves. Obviously, if the market price is only $5 per t CO2, then a $7 per t CO2 transaction cost will prevent forestry or land use activities from participating. In reality though, carbon prices will probably be far higher. A recent analysis by Sohngen (2009) examines the potential role of transaction costs on sequestration. That study linked a large scale global land use model with the most recent version of the DICE model of Nordhaus (2008). In one scenario, benefits and costs were balanced to determine the optimal set of carbon prices over time. The author assumed no transaction costs and a 20% transaction cost, whereby 20% of the value of each permit would be “eaten up” by brokers. The 20% transaction cost basically shifts the marginal cost curve for each activity upwards by 20% at each location, as shown in Figure C.16.
The results of the analysis indicate that for this “optimal” scenario, the 20% transaction cost would have little effect on carbon prices, but it would reduce the annual sequestration in the forestry sector. The reduction averages about 14% over the century. Transaction costs do have important implications for carbon sequestration in carbon policy in that total sequestration is projected to be lower, but these transactions costs do not suggest that the level of carbon sequestration should be zero.
Additionality and Leakage
Much is made of additionality. Additionality is a problem because it is virtually impossible to determine, or know, what actions landowners will undertake with their land before a carbon project is implemented. We can perfectly well observe what they did with their land after the fact, but not before. The carbon we are actually interested in saving on the landscape, though, is the carbon that someone actually will release into the atmosphere. Paying individuals who would not otherwise have released carbon to hold it raises the total costs of a carbon sequestration program.
The marginal cost estimates above assume that society is able to determine which carbon is additional. Society may choose to pay for all carbon that is stored, not only the incremental storage, but it still must know how much carbon is additional, and therefore an offset that can be credited. Determining which carbon is additional for each carbon contract will require substantial effort. Examples of methods have been undertaken for a number of carbon projects to date (Antinori and Sathaye, 2007; Sohngen and Brown, 2004), and for entire countries (e.g., Murray et al., 2005), so it is plausible to determine baselines and additionality, but this task may be costly.
Leakage is likely to be a far more important problem for carbon sequestration for a number of reasons. First, it is unlikely that all countries will be able to move quickly to national level carbon accounting, and it is even more unlikely that the carbon accounting most countries do will be suitable immediately for measuring leakage within a country. Thus, many countries or regions will experience leakage within their boundaries. Second, it is unlikely that all countries will enter into a global climate treaty at the same time. Because some countries remain outside the scope of the regulatory regime, and because some countries will develop programs that are geographically limited in scope, leakage will occur. Empirical estimates of leakage illustrate the seriousness of the problem. Estimates from the project level indicate that leakage could range from 10-90% (Murray et al., 2007). Sohngen and Brown (2004) found a slightly smaller range of leakage for a carbon sequestration project in Bolivia, but leakage of 20-50% was still prevalent. A recent paper by Sun and Sohngen (2009) suggests that leakage could be nearly 100% in the near-term under a global policy that seeks to set aside forests with high carbon potential.
From an efficiency standpoint, leakage is the most important problem for carbon sequestration policies. Within-country leakage is probably the easiest to deal with because international negotiators can link cross-border payments to the establishment of measurement and monitoring programs that will ensure that leakage is counted. Thus, while it may not be possible to control leakage in all countries, countries that do engage in carbon sequestration could be required to develop adequate MMV systems that allow for leakage detection before they are allowed to sell carbon permits internationally.
Cross-border leakage will be more difficult to handle because it is unlikely that all forested countries will engage in climate policy and in carbon sequestration programs. Thus, some countries could remain out of the
system and leakage could occur in those countries as timber and agricultural commodity prices respond to carbon trading. The question here is whether international negotiators can design an international system that engages a large share of forested countries in it. Given that all estimates currently point to leakage potentially being very large, it is important to examine ways in which we can increase the number of countries who will become part of any international carbon sequestration program.
This paper examines the potential for carbon sequestration as a low cost option to mitigate global climate change. A number of different types of models have been developed to estimate carbon sequestration costs. The literature in forestry is fairly well developed with numerous estimates made internationally in the last 20-30 years. The literature in agriculture is less well developed, although more and more studies are being conducted over time. Estimates presented in this paper suggest that around 4.1 billion t CO2 per year could be sequestered in forests through a range of activities for $15 per ton CO2. Around 23% of the carbon would be derived from afforestation, followed by 30% from forest management, and the remainder (47%) from avoided deforestation. Avoided deforestation occurs primarily in tropical countries, so a large share of the total mitigation potential in the forestry sector is derived from activities that occur in developing, tropical countries. Results from one international study on N2O and CH4 mitigation in agricultural found that for $27 per t CO2, an additional 1.0 billion t CO2 emissions could be reduced in the agricultural sector.
The results of the studies that have been conducted so far depend on a variety of data sources that are of varying quality. Data for developed countries, in particular the United States, appears to be fairly widely available for researchers to use. Internationally, there are some question marks around the data sets that need to addressed over time. These improvements in datasets could equally benefit economic estimates of costs of carbon sequestration and they could also improve the actual carrying out of carbon sequestration contracts (e.g., the MMV requirements).
While forestry and land use carbon mitigation have been discussed widely in the literature, they have only been used in actual policy settings sparingly. For instance, carbon credits through forest sequestration are part of the Kyoto Protocol, but have so far seen limited use. Furthermore, the Kyoto Protocol severely limits the type of land based credits that can be included. Some studies have shown that such limitations may have serious efficiency consequences, potentially eliminating a large share of the benefits. For instance, one study showed that if afforestation is the only policy option considered, leakage could be 100% in the short- term, and up to 50% in the long-term. The extent of leakage can be minimized by moving towards more comprehensive programs over time.
Other types of implementation issues are equally pressing and important. The paper discusses many of them, including additionality and baselines, leakage, and MMV. The paper presents some results indicating that transactions costs, which would include the costs of developing and implementing MMV systems and calculating baselines and additionality, do reduce the total amount of carbon that could be sequestered, but they do not appear to be large enough to suggest that we should not pursue land based options.
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