Economic Approach to Assess the Forest Carbon Implications of

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Economic Approach to Assess the Forest Carbon Implications of Biomass Energy Adam Daigneault,*,† Brent Sohngen,‡ and Roger Sedjo§ †

Landcare Research, Auckland, New Zealand Agricultural, Environmental, and Development Economics, The Ohio State University, Columbus, Ohio, United States § Resources For the Future, Washington, DC, United States ‡

S Supporting Information *

ABSTRACT: There is widespread concern that biomass energy policy that promotes forests as a supply source will cause net carbon emissions. Most of the analyses that have been done to date, however, are biological, ignoring the effects of market adaptations through substitution, net imports, and timber investments. This paper uses a dynamic model of forest and land use management to estimate the impact of United States energy policies that emphasize the utilization of forest biomass on global timber production and carbon stocks over the next 50 years. We show that when market factors are included in the analysis, expanded demand for biomass energy increases timber prices and harvests, but reduces net global carbon emissions because higher wood prices lead to new investments in forest stocks. Estimates are sensitive to assumptions about whether harvest residues and new forestland can be used for biomass energy and the demand for biomass. Restricting biomass energy to being sourced only from roundwood on existing forestland can transform the policy from a net sink to a net source of emissions. These results illustrate the importance of capturing market adjustments and a large geographic scope when measuring the carbon implications of biomass energy policies.

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“clearing or cutting forest for energy... has the net effect of releasing otherwise sequestered carbon into the atmosphere just like... fossil fuels.” The second letter, by over 100 forest scientists,4 expressed concern over equating biogenic carbon emission with fossil fuel emission. It argued that such an approach that focuses on net smoke stack emissions independent of their feedstocks would encourage further fossil fuel energy production to the long-term detriment of the atmosphere. In addition to these statements by scientists, several analyses have now been conducted to examine the implications that wood used for biomass energy has on the carbon cycle. Two recent studies have concluded that when biomass energy or biofuels are produced with wood, carbon emissions to the atmosphere actually increase.5,6 The emission results from the loss of carbon in existing stocks of forests that are drawn down in order to meet new demands for forest resources. In the paper by Searchinger et al.,6 land use change can occur which shifts forests to perennials such as switchgrass, or other annual crops, that have lower carbon intensity per hectare. In either case, the avoided emissions from the energy that is displaced are not large enough to limit the carbon losses.

INTRODUCTION For centuries, the proportion of wood used as a primary energy source has been declining. The United States and Europe, however, are pushing ever more stringent renewable portfolio standards that will increase the demand for wood as a primary energy source and potentially reverse this trend, at least in some locations. According to the Center for Climate and Energy Solutions, 39 states now have adopted some form of renewable or alternative energy portfolio standard or goal that promotes the use of alternative energy.1 Many of the laws these states have adopted promote biomass energy as a renewable source of electricity production. In addition, policies like the Low Carbon Fuel Standard in California, or laws like the United States Energy Independence and Security Act of 2007, promote development of liquid fuels from woody biomass. With technological change in the fuel processing sector, demand for wood as an input into the liquid fuel system could increase in the future. When viewed as a renewable energy source, wood-based biomass has been treated as carbon neutral, such that when it is burned for energy, it does not release net carbon dioxide.2 This assumption of “carbon neutrality”, however, has been challenged. For example, in the fall of 2010 two noteworthy letters were sent to the Congress by eminent scientists examining the meritsor demeritsof biomass in the climate debate. The first, from about 90 scientists,3 questioned the treatment of all biomass energy as carbon-neutral, arguing that © 2012 American Chemical Society

Received: Revised: Accepted: Published: 5664

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forests. Because forestry competes with agriculture for land, the two markets interact via land supply functions. These land supply functions account for the costs of renting and maintaining land in forests, and are specified for each forest type in the model. They are constant in temperate regions, and they shift inward in tropical regions to simulate rising opportunity costs of land. The model has been updated for this analysis with demand functions for biomass energy in five regions of the U.S. (Northeast, South, North Central, West, and Pacific Northwest), that include forest-specific cost functions that average about $40/m3 for harvesting and transporting forest residues and industrial roundwood to meet these demands. The detailed description of the biomass sector of the timber model is provided in the SI. In addition to considering the international dimension, the model has a long (200 year) time horizon which allows us to accommodate the long time horizon of most timber investments. Although there are strong trends toward shorter rotation species in many parts of the world, shifts in harvesting patterns of longer rotation types in temperate or boreal zones induced by biomass energy policies could have important carbon consequences. Model projections are conducted for forest land use and management for the next two centuries although we only present the first 60 years in this paper. The long time horizon allows us to account for investment decisions that are ignored by other models (e.g., whether to plant plantations in anticipation of higher prices associated with biomass or biofuel mandates), and terminal conditions are imposed far enough into the future so as to not affect the study results over the period of interest. The analysis in this paper involves comparing carbon stored in the forest system in the baseline to carbon stored in the forest system under several alternative policy scenarios. In this case, the baseline ignores biomass energy demands, while the scenario includes biomass energy demand. With biomass energy demand, the market will adjust timber harvesting, management, land use, and consequently carbon storage. The change in carbon then is the difference in carbon stocks between the scenario and the baseline. The carbon stored in the forest system is measured as the carbon in ecosystems (including soil carbon and slash) and carbon in wood products. In scenarios that include demand for biomass energy, carbon may also be calculated as the reduction in emissions from the energy sector when biomass energy displaces traditional energy. Estimates of carbon stocks are presented every 5 years for the baseline and alternative policy scenarios. Mathematically, the change in carbon caused by the policy is a path of changes in the total forest carbon stock:

Forest stocks, of course, are influenced both by biological and economic factors, each of which exert important influences on forest carbon and resulting carbon flow. These earlier studies focused entirely on biological factors and ignored the important policy and economic forces that influence forest stocks and whether biomass energy should be considered carbon neutral. Even some notable economic studies (e.g., 7) that have examined the indirect effects of biofuel policies have used simple life cycle analysis which did not fully account for forest dynamics. This paper uses modeling that links forest dynamics to economic markets and thus improves these earlier estimates. In so doing, the results of many of these earlier studies are reversed. Some of the economic factors that influence forest stocks include the time path for implementing a biomass energy policy, timber prices, costs of accessing and harvesting trees, transportation costs, land opportunity costs, and other factors. The level of forest investments and the timing of their impacts on carbon sequestration are likely to have particularly important implications.8 Furthermore, there is a consistent trend toward utilizing a broader array of shorter rotation species in timber production.9,10 In the past 40 years, the area of timber plantations globally has increased to over 120 million hectares, supplying around 30% of the world’s timber.11 This investment has slowed timber price growth globally, and it has reduced pressure on harvesting in natural forests, thereby reducing the costs of forest protection. There is evidence in some regions, however, that increasing values for timber plantations have in turn increased pressures to convert natural forests to plantations, resulting in net carbon emissions over a 30-year period (e.g., 12, 13). To properly quantify carbon flows associated with policy changes, economic models that can account for a range of influences on land use change must be utilized.

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MODEL AND DISCUSSION This paper presents the results of economic analysis of the effects of U.S. biomass energy policy on U.S. and global carbon stocks. Economic analysis recognizes that forest investment decisions are based on anticipated future market conditions as well as current conditions (e.g., prices). The analysis is conducted with a global economic model of forest and land use with carbon accounting routines. The model has been used widely for carbon sequestration analysis as well as for timber supply analysis (e.g., 11, 14−16). A global model is used because wood is an internationally traded commodity and policies in the U.S. could have influences well beyond the U.S. border. For instance, if biomass energy demands are met locally, more timber might be imported to meet traditional wood uses. The market and carbon influence of these changes are factored into this global model. A full description of the global forest and land use model, as well as the carbon accounting routines and many of the assumptions of the model, are provided in the Supporting Information (SI). The model maximizes the net present value of consumers’ surplus less the costs of production in forestry for 200 forest types that encompass 16 different regions of the globe. Forestry demand is represented by a single global demand function for industrial wood products that shifts out over time based on changes in income. The model endogenously solves timber prices, economically optimal age classes for timber harvests, economically optimal intensity of management, and the optimal area of land to maintain in

CCt = TFCSSt + ER St − TFCStB

(1)

where TFCS is the total forest carbon stock and ER is the emission reduction with the biomass scenario. The superscript “S” indicates the carbon stock is measured for the scenario and the superscript “B” indicates the carbon stock is measured for the baseline. The methods for measuring the total forest carbon stock are described in detail in the SI. Using eq 1 to assess changes in carbon when a policy shift occurs entails a substantial difference from most lifecycle analyses. First, this approach is dynamic and relies on measuring carbon across multiple time periods. With this method, we do not aggregate changes that occur in different time periods using discounting or other methods; we simply present the changes in specific time periods. Second, underlying the calculations of the total 5665

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Table 1. Summary of Modeled Biomass Scenarios scenario baseline, no biomass residues and forestland change no residues but forestland change residues but no forestland change no residues or forestland change high GDP high biomass demand high GDP and high biomass demand

average GDP growth (%/yr)

annual GDP growth (%)

U.S. biomass 2035 (Mm3)

U.S. biomass 2055 (Mm3)

harvest residues

forestland area constrained

1.6 1.6 1.6

1.6 1.6 1.6

none 146 146

none 171 171

no yes no

no no no

1.6

1.6

146

171

yes

yes

1.6

1.6

146

171

no

yes

2.4 1.6 2.4

2.4 1.6 2.4

146 292 292

171 342 342

yes yes yes

no no no

Second, there is an important question about the responsiveness of land use to the biomass policy. The land use supply functions described above and in the SI control land use change in general, and assume that land use is responsive to biomass policy. Given the debate that has occurred in the literature on the responsiveness of land use to biomass policies (e.g., 6), we include two scenarios that assume that investments can be made to expand forestland in response to biomass energy demands, and two scenarios that assume that forestland area is unresponsive. The nonresponsive land use scenario may also mirror the Energy Independence and Security Act (EISA), which limits the use of woody biomass material from lands converted specifically to produce biomass energy after the policy was enacted in 2007. Our constrained land scenarios fix all land types at their baseline levels, thus prohibiting conversion of any land into plantations to produce biomass energy. This provides a test for the importance of forest investments on the resulting carbon fluxes. Note, however, that in the constrained land case, investments in forest management can still increase forest density and carbon sequestration on existing timberlands. For the biomass energy scenarios, the projections are based on forecasts of regional bioenergy consumption from the U.S. Energy Information Administration Annual Energy Outlook 2010 (AEO 2010) “Reference Case”.18 A series of adjustments were made to modify the aggregate bioenergy projections in AEO2010 to focus only on the hypothetical effects of producing energy from woody biomass. First, all bioenergy produced in the initial period is assumed to come from woody biomass. Second, all bioenergy produced in the major U.S. timber producing regions of the South, Pacific Northwest, and West are assumed to come from woody biomass for all periods, while demand for woody biomass in the Northeast and North Central regions is expected to grow at roughly half the projected rate for total biomass-based energy in the region. This is because we assume that a large portion of the demand in these regions will likely be met by other sources of biomass such as agricultural residues or energy-crops, while regions that have large forest stocks will continue to be the main source of biomass. Finally, because AEO only has projections up to 2035, we allow regional biomass demand to grow at projected rates until 2050 and remain constant at the 2050 demand level for the remaining periods of the simulation. Additional details are provided in the SI. The sensitivity analysis considers several additional scenarios that adjust key assumptions about the demand for roundwood and biomass energy. First, we consider the possibility that

forest carbon stock in either the baseline or the scenarios are a range of behavioral changes that are mediated by market price signals. Life cycle analysis accounts neither for the baseline, nor the adjustments in carbon stocks resulting from market activities. The forestry model tracks the age class, growing stock volume, and harvest of over 200 different forest types in 16 different regions of the world. The carbon accounting routines are described in ref 14 and the SI. For this analysis, we calculate total ecosystem carbon in aboveground and belowground plant material, and soil carbon. We also track carbon stored in timber products and decay starting from our initial period, 2010. We do not account for inherited emissions from historical wood product harvests. This analysis also tracks GHG emissions from fuel used to harvest and transport wood to be processed. In addition to counting carbon in forests and wood products, we also calculate the reduction in carbon emissions from the wood energy that displaces (i.e., offsets) fossil fuel energy. To calculate the reduction in emissions, we assume that biomass energy from forests offsets the emissions from electricity using the average carbon intensity of coal-based electricity in the United States in 2009, as that is what biomass is most likely to displace. For this paper, we assume that 1 m3 of timber produces approximately 850 kWh and offsets 0.94 t CO2 in a power plant with 33% efficiency. This is based on the assumption that 1 m3 of timber with a moisture content of 50% produces 8.8 MMBtu of energy, offsetting the combustion of 0.33 tons of coal with an average energy content of 26.7 MMBtu/ton and carbon content of 77%, or 2.83 tons CO2/ton coal. These calculations are included separately in our results so readers can see the impact of these reductions in emissions. Several policy scenarios are examined in this paper and compared to a baseline case with no bioenergy policy. A sensitivity analysis with additional increases in the demand for roundwood and biomass energy was also conducted. The biomass energy scenarios are delineated by two critical issues. First, we assess whether harvest and use of forest residues (i.e., slash) affects the economic efficiency or the carbon implications of biomass energy. Thus, two of the scenarios assume that up to 50% of available forest residues can be removed and used for biomass energy, and two of them assume that residues are not allowed to be utilized by markets. These with and without residue cases are considered because there is a policy debate not only about whether residues should be used due to the nutrient and other ecological benefits provided by leaving the residues on-site, but also that some regional RPS requirements would be primarily met by the felling of whole trees. 5666

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Table 3. U.S. Wood Consumed (Million m3/Year) for Bioenergy under the Energy Information Administration Annual Energy Outlook17 Projections for the Scenario With and Without Residues Included in the Policy, and Forest Land Area Unconstrained (Part a) and Forest Land Area Constrained (Part b)

future incomes rise much more rapidly over the coming century than our baseline projection. It is possible that if demand for wood is greater in the future, wood will become scarcer, and adding biomass energy demand will have greater impacts on forests. As noted above, in the baseline our average rate of increase in GDP per capita is 1.6% per year. For this sensitivity scenario, we assume that GDP per capita rises at an average rate of 2.4% per decade. We then assess the implications of adding biomass energy demand to this scenario with greater global wood demand. Second, we test an assumption that regional biomass energy demand in the U.S. itself rises more rapidly; specifically, we double the biomass energy demand from the projections discussed in the previous paragraph. We test the influence of significantly higher biomass energy demand for both rates of annual growth in global GDP per capita. A summary of the key assumptions for the modeled scenarios is listed in Table 1.

with residue scenario

year

RESULTS AND DISCUSSION For the baseline case, we assume that global average income per capita rises at 2.4% per year, but that the rate of increase slows Table 2. Baseline Timber Prices and Global Roundwood Output million hectares

year

output (million m3/yr)

global forest area

global industrial plantations

U.S. forest area

2015 2020 2025 2030 2035 2040 2045 2050 2055 2060

$142.35 $146.60 $149.25 $151.90 $156.25 $160.60 $161.95 $163.30 $164.40 $165.50

1,992 2,027 2,085 2,142 2,206 2,269 2,331 2,393 2,471 2,550

3,497 3,528 3,499 3,470 3,447 3,424 3,416 3,407 3,401 3,396

79 87 89 91 92 94 95 97 98 99

207 213 216 219 219 220 221 222 222 222

without residues total bioenergy consumption

total bioenergy consumption (roundwood substitution)

53.2 58.0 61.7 65.4 66.7 68.1 71.1 74.1 77.3 80.6

80.4 91.6 112.7 133.8 146.9 160.0 165.8 171.5 171.7 172.0

78.9 90.4 111.9 133.4 146.5 159.6 165.1 170.7 170.8 171.0

55.2 59.6 61.6 63.5 64.2 64.9 68.4 71.8 73.6 75.4

80.0 91.3 112.6 133.8 146.8 159.7 165.1 170.5 171.0 171.4

78.3 89.9 111.5 133.1 145.6 158.1 163.4 168.7 168.6 168.4

residue consumed for bioenergy

a: forestland area unconstrained 2015 27.2 2020 33.7 2025 51.0 2030 68.4 2035 80.2 2040 92.0 2045 94.7 2050 97.4 2055 94.4 2060 91.4 b: forestland area constrained 2015 24.8 2020 31.7 2025 51.0 2030 70.3 2035 82.6 2040 94.8 2045 96.8 2050 98.7 2055 97.4 2060 96.0

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roundwood price ($ per m3 )

timber consumed for bioenergy (roundwood substitution)

at 0.9% per year. As a result, income per capita rises at 1.6% on average over the century. This is consistent with historical growth rates in world GDP per capita in the last century.19 Under this baseline scenario timber prices rise by 0.4% per year between 2015 and 2060 (Table 2). This represents slower growth in prices than over the past century, but rates that are consistent with recent decades.17 The modeled price trends

Figure 1. Baseline regional timber harvests. 5667

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Table 4. Change in Roundwood Production and Net Imports (Million m3/Year) U.S. roundwood production year

baseline

change in roundwood production

change in net imports

with residues

without residues

with residues

without residues

0.8 0.8 4.9 8.9 11.5 14.1 15.7 17.3 16.3 15.3

21.9 27.1 31.5 35.9 34.7 33.6 39.3 45.1 38.7 32.3

60.2 70.0 81.4 92.8 95.3 97.8 89.5 81.2 86.7 92.3

0.3 0.3 −0.3 −1.0 1.3 3.7 4.2 4.7 4.6 4.5

5.9 14.0 36.8 59.6 68.0 76.5 76.9 77.3 76.4 75.6

49.2 60.7 84.8 108.9 116.8 124.8 128.7 132.6 131.9 131.2

a: forestland area unconstrained 2015 460.8 −0.4 2020 473.7 −0.3 2025 452.9 8.3 2030 432.0 16.8 2035 449.9 22.8 2040 467.8 28.8 2045 492.7 25.8 2050 517.6 22.9 2055 532.7 29.9 2060 547.8 37.0 b: forestland area constrained 2015 460.8 2.6 2020 473.7 2.1 2025 452.9 2.8 2030 432.0 3.5 2035 449.9 4.7 2040 467.8 6.0 2045 492.7 6.0 2050 517.6 6.0 2055 532.7 4.2 2060 547.8 2.4

Table 6. Baseline U.S. Carbon Stocks (Billion tons CO2), Including Above- and Below-Ground Stocks, Soil Carbon, Carbon Stored in Timber Products, and With (Part a) or Without (Part b) Carbon from Electricity Offsets change in carbon stocks − unconstrained land year

U.S. forest area

change

with residues

without residues

a: carbon from electricity offsets excluded 2015 188.0 −0.1 0.1 2020 191.0 −0.2 0.2 2025 194.1 0.2 0.2 2030 197.2 0.6 0.2 2035 199.4 1.1 0.5 2040 201.5 1.5 0.8 2045 203.1 1.5 0.9 2050 204.7 1.6 1.0 2055 206.2 2.0 1.0 2060 207.7 2.4 1.0 average annual 40.1 16.4 flow (million tons CO2/yr) b: carbon electricity offsets included 2015 188.0 0.1 0.3 2020 191.0 0.2 0.5 2025 194.1 0.9 0.8 2030 197.2 1.5 1.1 2035 199.4 2.2 1.6 2040 201.5 2.8 2.1 2045 203.1 3.0 2.3 2050 204.7 3.2 2.6 2055 206.2 3.6 2.6 2060 207.7 4.0 2.6 average annual 67.2 43.4 flow (million tons CO2/yr)

Table 5. Global and U.S. Forest Area (Million Hectares) under Alternative Scenarios, Unconstrained Forest Land Base (No Table Is Shown for the Constrained Land Case since Forest Areas Remain the Same As the Baseline) global forest area

baseline

change in carbon stocks − constrained land with residues

without residues

−0.1 −0.2 −0.5 −0.7 −0.8 −0.8 −1.0 −1.2 −1.2 −1.3 −21.3

0.0 0.1 −0.1 −0.3 −0.2 −0.1 0.0 0.0 −0.3 −0.6 −10.1

0.1 0.2 0.2 0.1 0.3 0.5 0.5 0.4 0.4 0.3 5.7

0.2 0.5 0.5 0.6 0.9 1.2 1.4 1.6 1.3 1.0 16.3

change

year

baseline

with residues

without residues

baseline

with residues

without residues

2015 2020 2025 2030 2035 2040 2045 2050 2055 2060

3,497.2 3,528.2 3,499.1 3,469.9 3,447.2 3,424.4 3,415.8 3,407.1 3,401.4 3,395.6

8.0 15.9 18.2 20.4 19.5 18.5 16.5 14.5 17.7 20.8

12.4 24.8 26.8 28.8 27.2 25.6 22.5 19.3 20.2 21.1

207.2 212.7 215.9 219.0 219.5 220.0 220.9 221.8 222.1 222.5

3.5 7.1 9.0 10.9 11.6 12.3 12.6 12.9 13.1 13.4

1.6 3.1 3.9 4.8 4.9 5.0 4.2 3.4 3.1 2.9

forest area declines by about 100 million hectares by 2060are less than rates of net forest change in recent decades estimated by FAO.20 The small net change globally, though, masks deforestation processes calculated by the model. For example, we calculate about 4 million hectares of annual gross deforestation in tropical regions in the coming decades. Total U.S. biomass energy demand in the scenarios amounts to an additional 80 million m3 per year of timber (either roundwood or residues) being converted into energy by 2015. This amounts to around 17% of current U.S. roundwood timber harvests (Table 3). Our analysis shows that demand is expected to rise to around 170 million m3 per year by 2050 (4%/yr), or about 33% of the projected U.S. roundwood harvests. If policy allows residues to be utilized for biomass energy, the residues play a very important role, amounting to over 65% of the wood used for biomass energy in 2015, and remaining important throughout the simulation period. If policy does not allow residues, all of the wood used for energy must come either from additional production of timber within the U.S., substitution with other traditional roundwood uses, or imports from other regions of the globe. Harvesting additional timber from the forest to meet biomass energy demands has a high opportunity cost, and thus there is little new timber harvesting in the United States to meet immediate biomass energy needs (Table 4). In the next 10 years, most of the wood used for biomass energy comes from residues (if they are allowed by policy), substituting lower-value

suggest that a future without biomass energy demands is one in which timber supplies will be relatively bountiful. Global timber production in the baseline expands by about 30%, from almost 2.0 billion m3 per year in 2010 to over 2.5 billion m3 per year in 2060 (Table 2). One important trend in timber markets is the continued drive toward establishing shortrotation timber plantations for industrial wood production, in particular in subtropical regions. In this model, the area of fastgrowing plantations devoted to timber production increases by 20 million hectares in the next 40 years. Most of the increase in timber output globally occurs in China and the emerging plantation areas of the rest of the world region (Figure 1). Our estimates of net global forest loss in the coming decades 5668

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Table 7. Baseline Global Carbon Stocks (Billion Tons CO2), Including Above- and bBelow-Ground Stocks, Soil Carbon, Carbon Stored in Timber Products, and With (Part a) or Without (Part b) Carbon from Electricity Offsets change in carbon stocks − unconstrained land year

baseline

with residues

without residues

a: carbon from electricity offsets excluded 2015 3278.4 0.0 0.2 2020 3303.0 −0.1 0.5 2025 3321.4 0.5 1.1 2030 3339.8 1.1 1.7 2035 3346.5 1.8 2.7 2040 3353.2 2.4 3.6 2045 3352.6 2.6 4.3 2050 3352.0 2.9 5.0 2055 3352.4 3.3 5.4 2060 3352.8 3.7 5.9 average annual 61.8 98.2 flow (million tons CO2/yr) b: carbon from electricity offsets included 2015 3278.4 0.2 0.4 2020 3303.0 0.4 0.8 2025 3321.4 1.2 1.7 2030 3339.8 2.0 2.6 2035 3346.5 2.8 3.7 2040 3353.2 3.7 4.9 2045 3352.6 4.1 5.7 2050 3352.0 4.5 6.6 2055 3352.4 4.9 7.0 2060 3352.8 5.3 7.5 average annual 88.9 125.2 flow (million tons CO2/yr)

Table 8. Sensitivity Analysis on Carbon Storage (Billion Tons CO2) in Above- and Below-Ground Components, Plus Storage in Products (Land Use Change Is Unconstrained and Residues Are Allowed to Be Consumed)

change in carbon stocks − constrained land with residues

without residues

−0.3 −0.7 −0.7 −0.8 −1.2 −1.7 −2.6 −3.5 −2.9 −2.4 −39.3

−0.1 −0.3 −0.7 −1.2 −1.3 −1.5 −1.7 −2.0 −2.2 −2.3 −39.1

−0.1 −0.3 −0.1 0.1 −0.2 −0.4 −1.1 −1.9 −1.3 −0.7 −12.2

0.1 0.1 −0.1 −0.3 −0.2 −0.2 −0.3 −0.4 −0.5 −0.7 −12.1

year

base GDP

change in carbon stocks − base GDP

change in carbon stocks − high GDP

base AEO biomass demand

2× AEO biomass demand

a: global carbon stocks 2015 3278.4 0.0 2020 3303.0 −0.1 2025 3321.4 0.5 2030 3339.8 1.1 2035 3346.5 1.8 2040 3353.2 2.4 2045 3352.6 2.6 2050 3352.0 2.9 2055 3352.4 3.3 2060 3352.8 3.7 average annual 61.8 flow (million tons CO2/yr) b: U.S. carbon stocks 2015 188.0 −0.1 2020 191.0 −0.2 2025 194.1 0.2 2030 197.2 0.6 2035 199.4 1.1 2040 201.5 1.5 2045 203.1 1.5 2050 204.7 1.6 2055 206.2 2.0 2060 207.7 2.4 average annual 40.1 flow (million tons CO2/yr)

roundwood materials (e.g., low value pulp), or from cheaper imports. Over the longer run, the forest industry can respond by investing in new timber plantations and harvesting capacity, so that total harvesting expands in response to the increased biomass energy demands. This can be clearly seen by comparing the output response in the unconstrained and constrained land cases in Table 4. Domestic timber harvesting in the U.S. rises substantially more in the unconstrained land use scenario, while the expansion in net imports into the U.S. is greatest in the constrained land use scenario. In addition to changes in harvesting patterns and net imports, biomass energy demands affect timber prices. The global timber price rises 1−2% if residues are allowed to be used by biomass energy markets and forestland is not constrained, and 7% if residues are not allowed and forestland area is constrained. Clearly, allowing residues and new investments in timberlands for biomass energy will reduce the costs of meeting the biomass energy mandates. Additionally, accounting for international timber harvests and imports to meet increases in domestic demand for wood reduces the price impacts faced by U.S. consumers. Higher timber prices lead to new investments in forestry, and in particular in new forestlands in the unconstrained land scenario. By 2015, forestland area expands by 8−12 million hectares, and by 2030, it expands 20−28 million hectares, with the largest increases occurring under the scenario that does not allow residues to be utilized (Table 5). When residues are

2× AEO biomass demand

high GDP

base AEO biomass demand

0.3 0.5 1.5 2.5 4.0 5.5 5.8 6.0 7.0 8.0 133.3

3279.9 3306.0 3329.1 3352.3 3366.3 3380.3 3388.6 3396.9 3402.7 3408.6 -

−1.1 −2.3 −3.1 −4.0 −0.1 3.7 10.4 17.1 8.6 0.1 1.7

−0.1 −0.2 2.0 4.1 4.8 5.6 5.1 4.6 7.2 9.6 160.0

−0.1 −0.1 0.2 0.5 1.6 2.8 2.3 1.7 2.2 2.8 46.7

188.1 191.3 195.7 200.1 204.3 208.4 211.8 215.1 217.5 220.0 -

0.0 0.0 0.4 0.9 1.1 1.4 1.3 1.4 2.2 2.9 48.3

0.1 0.1 0.1 0.1 0.7 1.5 1.4 1.4 2.1 2.7 45.0

included in the policy, most of the increase in forest area occurs in the United States. Residues are an economically efficient coproduct with timber that are supplied locally, so when they are included in U.S. policy, landowners in the U.S. will expand forest areas to produce timber for timber markets, timber for biomass energy, and residues for biomass energy. For the United States, total ecosystem carbon rises in the baseline as forest area increases, the average age of forests increases, and management intensifies over time (Table 6). When demand for biomass energy is considered, carbon in forest ecosystems and traditional timber products increases by nearly 40 million tons of CO2 per year on average if residues can be used for energy production and land is unconstrained. The importance of land investments to the carbon results is highlighted by the reduction in stocks with or without residues when land is constrained. When offsets for electricity production are considered, however, these potential increases are turned to reductions in net carbon emissions ranging from 6 to 67 million tons of CO2 per year on average, regardless of how residues or land use change are treated in policy (Table 6). A more complete carbon accounting includes fluxes that arise from changes to carbon stocks and carbon product flows inside and outside the U.S. This is particularly important in our modeling approach since we allow imports to meet U.S. timber and/or biomass energy demands. When the net effects on 5669

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Figure 2. Change in forest carbon stocks from baseline.

the demand for biomass, these higher prices substantially enhance investments in wood and increase annual forest carbon by an average of 930 million tons CO2 globally and by 205 million tons in the U.S. relative to the baseline GDP scenario. Interesting dynamic effects occur when biomass demand is added to the high GDP scenario as well. Initially, carbon stored in the ecosystem and products measured at the global level falls relative to the baseline, but after 2040 the level of forest carbon stocks remains at or above the baseline. Increasing the demand for both roundwood and biomass incentivizes even earlier investment, and global forest carbon levels rise above the baseline from 2025 onward. Thus, higher overall demand for wood does prove more costly to make investments initially in forest resources in order to expand production for biomass energy, although these investments are made efficiently and forest resources expand over time. This finding mirrors the original baseline results which showed that in the first decade forest carbon would fall modestly, although with the higher GDP per capita growth, the reduction in carbon is initially stronger. The results from this sensitivity analysis emphasize the fundamental results of the analysis. Biomass energy demand can increase total carbon stored in ecosystems and forest products. The global effects are not very sensitive to the scale of biomass demand itself, but the results are sensitive to assumptions about the rate of growth of GDP per capita. This modeling approach illustrates how biomass energy demand affects timber markets and forest carbon fluxes (Figure 2). Unlike typical life-cycle approaches, we utilize a dynamic model of forest and land use management. The model is global, allowing using it to incorporate the effects of shifts that occur nationally and internationally. Our results show that biomass energy demand in the U.S. increases timber prices and increases

carbon stocks are measured globally, our results suggest that biomass energy policy using forests as a supply source will reduce net emissions by up to 98 million tons CO2 per year when land is not constrained, and electricity offsets are not counted (Table 7). If land is constrained, biomass energy policy could lead to an increase in net carbon emissions, even with energy offsets. If land is unconstrained, as is likely the case globally where many low-cost sites for forest expansion exist, biomass energy policy in the U.S. will reduce net carbon emissions by up to 125 million tons CO2 per year on average. This level amounts to up to a 5% change in emissions for the entire U.S. electric power sector.21 Estimates for the forest carbon storage from the sensitivity analysis that increases the demand for roundwood and biomass are listed in Table 8. Results indicate that a doubling of biomass demand increases carbon in both the ecosystem and harvested wood products relative to the initial baseline scenario. Whereas higher biomass demand increases harvests within forests, it also spurs more investment in forests domestically and internationally. These new investments increase carbon in forest ecosystems and traditional timber products between 133 and 160 million tons CO2 per year on average globally relative to the two GDP scenarios with no biomass demand. There is a market cost to this additional increase in bioenergy demand though, as wood product prices increase by around 2.6% on average relative to the original AEO biomass demand scenario for the baseline GDP growth case, and by around 3.2% relative to the initial level of biomass demand when comparing it under the higher GDP growth assumption. Increasing wood product demand by adjusting the global per capita GDP growth rate causes wood products prices to increase about 11% relative to the baseline demand case, even if there is no demand for biomass. As with the case of doubling 5670

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(5) Walket, T., Ed.; Cardellichio, P.; Colnes, A.; Gunn, J.; Kittler, B.; Perschel, R.; Recchia, C.; Saah, D.; Walker, T. Massachusetts Biomass Sustainability and Carbon Policy Study: Report to the Commonwealth of Massachusetts Department of Energy Resources; Natural Capital Initiative Report NCI-2010-30; Manomet Center for Conservation Sciences: Brunswick, ME, 2010; 182 pp. (6) Searchinger, T. D.; Hamburg, S. P.; Melillo, J; Chameides, W; Havlik, P; Kammen, D. M.; Likens, G. E.; Lubowski, R. N.; Obersteiner, M; Oppenheimer, M; Robertson, G. P.; Schlesinger, W. H.; Tilman, G. D. Fixing a Critical Climate Accounting Error. Science 2009, 326 (5952), 527−528. (7) Hertel, T. W.; Golub, A.; Jones, A. D.; O’Hare, M.; Plevin, R. J.; Kammen, D. M. Effects of US maize ethanol on global land use and greenhouse gas emissions: Estimating market-mediated responses. BioScience 2010, 60 (3), 223−231. (8) Sedjo, R. A. Carbon Neutrality and Bioenergy: A Zero Sum Game?; Discussion paper 11-15; Resources For the Future: Washington, DC, April 2011. (9) Sedjo, R. A. The Comparative Economics of Plantation Forestry: A Global Assessment; Resources for the Future/Johns Hopkins Press: Baltimore, MD, 1983. (10) Cubbage, F.; Koesbanda, S.; MacDonagh, P.; Balmelli, G.; Olmos, V. M.; Rubilar, R.; de la Torre, R.; Hoeflich, V.; Murraro, M.; Kotze, H.; Gonzalez, R.; Carrerro, O.; Frey, G.; Turner, J.; Lord, R.; Huang, J.; MacIntyre, C.; McGinley, K.; Abt, R.; Phillips, R. Global timber investments, wood costs, regulation, and risk. Biomass Bioenergy 2010, 34 (12), 1667−1678. (11) Daigneault, A. J.; Sohngen, B.; Sedjo, R. A. Exchange Rates and the Competitiveness of the United States Timber Sector in a Global Economy. Forest Policy Econ. 2008, 10 (2008), 108−116. (12) Sohngen, B.; Brown, S. The Influence of Conversion of Forest Types on Carbon Sequestration and other Ecosystem Services in the South Central United States. Ecol. Econ. 2006, 57, 698−708. (13) Alig, R. A.; Butler, B. J. Projecting Large-Scale Changes in Land Use and Land Cover for Terrestrial Carbon Analyses. Environ. Manage. 2004, 33 (4), 443−456. (14) Sohngen, B.; Sedjo, R. A. Potential Carbon Flux from Timber Harvests and Management in the Context of a Global Timber Market. Climatic Change 2000, 44, 151−172. (15) Sohngen, B.; Mendelsohn, R. An Optimal Control Model of Forest Carbon Sequestration. Am. J. Agric. Econ. 2003, 85 (2), 448− 457. (16) Kindermann, G.; Obersteiner, M.; Sohngen, B.; Sathaye, J.; Andrasko, K.; Rametsteiner, E.; Schlamadinger, B.; Wunder, S.; Beach, R. Global cost estimates of reducing carbon emissions through avoided deforestation. Proc. Natl. Acad. Sci. 2008, 105 (30), 10302−10307. (17) Haynes, R. W. Emergent Lessons from a Century of Experience with Pacific Northwest Timber Markets; Gen. Tech. Rep. PNW-GTR-747; U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station: Portland, OR; 45 pp. (18) Energy Information Administration. Annual Energy Outlook 2010; DOE/EIA-0383(2010); U.S. Department of Energy, Energy Information Administration, Office of Integrated Analysis and Forecasting: Washington, DC, 2010; 231 pp. (19) Historical Statistics of the World Economy; http://www.ggdc. net/MADDISON/oriindex.htm. (20) United Nations Food and Agricultural Organization. Global Forest Resources Assessment; FAO: Rome, 2010; 340 pp. (21) U.S. Environmental Protection Agency. Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990−2009; EPA 430-R-11-005; Office of Atmospheric Programs: Washington, DC, 2011; 459 pp.

harvests, but that the scope for increasing harvests initially in the U.S. is limited. As a consequence, imports into the U.S. will increase to help meet the overall demand for wood products and biomass energy. Although demand for wood increases, the total carbon maintained in forests also increases because higher wood prices lead to new investments in forest stocks. These investments in new timber plantations occur both within the U.S. and globally and for varying levels of increases in demand for wood. Recent policies have suggested that the land that can be used to supply biomass for energy and liquid fuels should be constrained, and when we test that scenario, we find that investments in new wood production decline, and biomass energy from forest feedstocks could instead lead to an increase in net carbon emissions. Regardless of whether land is constrained or residues are allowed to be used for biomass energy, if offsets from the production of electricity are considered, then biomass energy production with a forest feedstock will lead to a reduction in net greenhouse gas emissions. These results illustrate the importance of capturing market adjustments when measuring the carbon implications of biomass energy policies.

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ASSOCIATED CONTENT

S Supporting Information *

Appendix describing the global forest and land use model utilized in this paper. The first section shows the equations and parameters for the baseline model without the biomass components. The biomass components are then introduced into the model in the last section. This material is available free of charge via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]; phone: +64 (0) 9 574 4138; mail: Landcare Research, 231 Morrin Road, St Johns, Auckland 1072 New Zealand. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This work was funded by the Resources For the Future Forestry Program. We also appreciate financial support for model development from the U.S. Environmental Protection Agency Climate Change Division, the U.S. Environmental Protection Agency Office of Transportation and Air Quality, the U.S. Department of Energy, and the Ohio Agricultural Research and Development Center. All ideas and opinions expressed in this paper, however, are those of the authors alone.

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REFERENCES

(1) Center for Climate and Energy Solutions, Renewable and Alternative Portfolio Standards. http://www.c2es.org/what_s_being_ done/in_the_states/rps.cfm. (2) Intergovernmental Panel on Climate Change. 2006 IPCC Guidelines for National Greenhouse Gas Inventories; Volume 4, Chapter 12; Harvested wood products. Pingoud, K.; Skog, K.; Martino, D.L.; Tonosaki, M.; Xiaoquan, Z.; Ford-Robertson, J. Intergovernmental Panel on Climate Change, 2006; 33 pp. (3) Schlesinger et al. Letter to Speaker Pelosi, et al. U.S. Congress. May 17, 2010. (4) Lippke et al. Letter to Chairman Boxer, et al. U.S. Congress. July 20, 2010. 5671

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