Setting the emission payments on wood based bioenergy: Impacts of partial and optimal climate policies on the energy and forest sectors

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1 Setting the emission payments on wood based bioenergy: Impacts of partial and optimal climate policies on the energy and forest sectors Johanna Pohjola*, Finnish Environment Institute Jussi Lintunen, Natural Resources Institute Finland Jani Laturi, Natural Resources Institute Finland Jussi Uusivuori, Natural Resources Institute Finland June 18, 215 DRAFT PLEASE DO NOT CITE OR QUOTE Abstract Current climate policy gives incentives for substituting wood-based fuels for fossil fuels. The emission free treatment of wood-based biomass has however lately been questioned in the scientific debate. In addition, current policies do not promote carbon sequestration. This paper analyses the implications of optimal and partial climate policies on energy and wood markets as well as on the atmospheric carbon. In optimal policy, emissions from wood and sequestration are paid according to the optimal effective emission factors representing the true social costs of the use. Our partial policy gives correct incentives for fuel mix decision of energy producer but carbon sequestration is not subsidized. The calculations are performed with a detailed optimization model covering the forest and energy sectors. Both policies reduce the use of wood-based fuels and increase the use of fossil fuels compared to baseline reflecting current climate policy. Emission payments on wood-based fuels do not however cease their use as energy. Optimal policy increases notably carbon sequestration in the forests and thus reduces the atmospheric carbon more than the partial policy. On the other hand, timber market impacts are notable in the first periods increasing the costs of forest industries. Short and long run impacts of policies differ due to the adjustment in the energy sector and forest stock. Keywords: Climate policy, bioenergy, wood fuels, wood based emissions, carbon rents, effective emission factor *Corresponding author: Johanna Pohjola, Finnish Environment Institute (SYKE), johanna.pohjola@ymparisto.fi 1

2 1.Introduction Forests can be utilized in climate change mitigation by storing carbon into forests, i.e. by using them as carbon sink, and to provide wood for energy and material substitution. There is an obvious conflict between these two options. The debate on which one, substitution or sequestration, should have the priority has been going on since 199 s. Current policies, for example in Europe, give the incentives to substitute wood fuels by fossil fuels but not for carbon sequestration. Commonly, energy and climate policies consider bioenergy as greenhouse gas emission free. This is typically justified through carbon neutrality argument (e.g.lippke et al.,21; Sedjo, 211). Carbon neutrality argument stems from the fact that the biomass is renewable and the carbon released by biomass use is only recycling of carbon already in circulation. The emission free biomass has been recently contested due to the carbon leakage and the importance of time difference between uptakes and emissions. The latter argument refers to carbon debt generated by an instant release of carbon by biomass use and the following gradual absorption of carbon by slowly growing plants (e.g. Fargione et al., 28; Searchinger et al., 28; Cherubini et al., 211; Holtsmark, 212). A similar carbon debt argument has been proposed for the use of harvest residues as there is an instant release of carbon that would otherwise be released only gradually (e.g. Repo et al., 211). There is a large body of literature of economic assessments addressing the role of forests in climate change mitigation. Most of the models used cover only the supply of wood and thus do not take into account the possibility of using wood for input substitution. On the other hand, in some market or general equilibrium model analysis used to evaluate the costs and market adjustment of climate and energy policy targets, the substitution of wood for fossil fuels is modelled. However, to our knowledge the wood based emissions have not been taking into account in any detailed market level or economywide analysis of climate and energy policy targets. We base our analysis on the results by Lintunen and Uusivuori (214) by using their results on the optimal climate policy. In optimal policy, emissions from wood and removals by sequestration are paid according to the optimal effective emission factors representing the true social costs of the use. They illustrated the impacts of optimal policy setting by using a 2

3 comprehensive but stylized forest and energy sector equilibrium model with age-structured forest resources and detailed carbon cycle. This study expands their analysis by utilizing the detailed forest and energy sector optimization model calibrated to represent the markets, technologies and age-structured forest resources in Finland. Thus, we can study the changes of wood use in greater detail. In addition of optimal policy setting, we evaluate the impacts of partial policy that gives correct incentives for fuel mix decision of energy producer but carbon sequestration is not subsidized. 2. Model We utilize FinFEP (Finnish Forest and Energy Policy) model that is a partial equilibrium optimization model covering the forest and energy sectors. The model solves a competitive equilibrium with wood supply from a detailed forest inventory description and a detailed technological description of the wood using industries. The model integrates the supply and demand of wood in order to capture the strengthening link between energy and forest sectors. Figure 1 illustrates the model structure through a flow diagram. The model consists of five modules, namely energy processing, pulp and paper processing, wood-product processing, final good demand and forests. The modules of the model are linked with each other by the material flows between different processes. The processing modules have been used separately for policy analysis (see Kangas et al., 29, 211; Lintunen and Kangas, 21; Mäkelä et al., 211). 3

4 FORESTS WOOD RECYC- LING WOOD-PRODUCT PROCESSING SAWNWOOD, PLYWOOD AND BOARDS LIQUID BIOFUELS Logs Chips PELLETS Energywood Bark and dust Recycled wood ENERGY PROCESSING POWER AND HEAT Pulpwood PULP and PAPER PROCESSING Bark Waste liquors PULP AND PAPER TALL OIL ETC. FUELWOOD WASTE PAPER COLLEC- TION Primary production Waste paper Final product flows Intermediate product flows CLIMATE SERVICES, AMENITY ETC Final products Figure 1. Model structure. The processing modules of the FinFEP-model consist of input use decisions made by profit maximizing firms holding the processing facilities. The firms face product demand that is partly endogenous and partly determined through exogenous demand functions. The supply of inputs is mostly endogenous, through forest owner decisions and production decisions of the intermediate good producers. In addition, there is exogenous supply of imports and, for example, fossil fuels. The markets are assumed to be competitive and, therefore, all the firms are modeled as price takers. The processing facilities are aggregated at regional level. To obtain an accurate enough description of input-output flows the production technologies are based on input-output data. The variables are typically optimized as annual averages. However, demands of electricity and district heating have high intra-annual variation. Therefore, we model their production at subperiod levels that represent the different demand conditions. 4

5 The production processes modeled combine a large number of inputs into one or more outputs. For example, a pulp mill uses several inputs such as different kinds of wood inputs, chemicals, energy in a form of steam and electricity and labor. The products include bark, black liquor and other chemicals in addition to the pulp itself. As a second example, a CHPplant produces both heat and electricity through a technology dependent variety of fuels and labor. In addition, all the production processes are constrained by the machinery in place, which is summarized by the capital input. We model the machinery as a technology and each technology can be utilized in a number of processes. The capacity constraints are technology specific whereas the optimization of inputs is performed for each process. For each power plant technology, k, we use linear input-output transformation function y i = η ik x jk, (1) where amount y i of good i {electricity, heat} is generated through fuel use j x jk j, where index j denotes the fuels compatible with power plant technology k. Thus, parameter η ik presents the efficiency of the power plant. For energy generation, we further assume that the production costs may vary due to the mixture of fuels in combustion. This partial substitutability of the fuels is an important feature in co-firing of biomass with fossil fuels (see e.g. Lintunen and Kangas, 21). Although energy transformation is linear, the production function is non-linear enabling interior solutions in fuel use optimization. The input use in each technology is constrained by the maximum production capacity. The initial capacity is based on initial plant level data and for later periods the capacity develops endogenously through optimized level of investments and exogenous determined rate of depreciation. The investments on production capacity present the capital costs of production. The timber supply is based on optimized thinning and clear-cutting decisions by forest owners. The objective function consists of present value of harvesting revenue and Hartmantype amenity service streams (Hartman 1976). We assume three categories for forest owners and the categories differ by the weighting of amenity valuation in the objective function. The forest owner optimization is performed in a separate module that produces stationary harvest policies for the equilibrium path. These harvest policies are introduced in the equilibrium model and together with the forest resource data they produce stationary supply functions for timber. FinFEP model contains a detailed description of forest resources and their equations of motion. Thus, the development of forest resources is consistent with the harvesting 5

6 behavior. A more thorough description of FinFEP model is presented by Lintunen et al. (215). 3. Optimal carbon payments and effective emission factors The harvest residues left in the forest gradually decay and release their carbon content into the atmosphere as carbon dioxide. If the harvest residues are not left into the forest but they are collected and combusted, for example, in energy generation, the carbon is released instantly. If the social welfare is calculated using a positive time preference, the speed up of the carbon emissions can be considered as a negative externality linked to the energy use of harvest residues. Therefore, the optimal climate policy does not perceive harvest residue use as emission free. To handle the social cost caused by this kind of a carbon debt, Lintunen and Uusivuori (214) proposed a Pigouvian tax that is a product of an effective emission factor and the current social cost of carbon. In their approach, the emission factor set by the policy is not a true measure of the actual mass of carbon emitted, but a measure of the net present value of marginal social costs relative to the current carbon price. We call the emission factors used in the policy as effective emissions factor to distinct the NPV social costs from physical emissions. Lintunen and Uusivuori (214) analyzed a forest sector model with an emphasis on carbon cycle between forests and atmosphere and derived the effective emission factors to be used in an optimal climate policy. In a general form, these effective emission factors depend on the decay properties of the residue fraction but also on the discount factor used in the social welfare calculation and the time path of the social cost of carbon. Here we use the effective emission factors derived for a special case where the social cost of carbon stays timeinvariant from the current period onwards. Table 1. Policy instruments in the baseline and policy scenarios. Emission payments on fossil fuels Emission payments on wood-based fuels Carbon rents for forest owners BASELINE X PARTIAL X X OPTIMAL X X X 6

7 In this paper, we utilize the optimal carbon payments and effective emission factors derived in Lintunen and Uusivuori (214) by performing calculations for three policy scenarios: Baseline, Partial and Optimal, with policy instruments represented in the Table 1. The Baseline refers to the current state of the most of the climate policies: Emissions from fossil fuels face payments whereas wood-based bioenergy is considered as emission free and there are no carbon sequestration policies targeted on the forest management decisions of the forest owners. This baseline scenario is the basis for which the two other policy scenarios are contrasted. In the partial policy scenario, the emissions from wood-based bioenergy are acknowledged but the carbon sequestration aspect is omitted. Thus, there is a carbon payment on wood fuel use but there is no carbon payment scheme for sequestering carbon. The emission payments for harvest residues are implemented as in the Table 2 based on the effective emission factors that depend on the discount rate r, the decay rate δ DOM, and nominal emission factor for wood ε w. In addition, emissions from roundwood and by-products are paid according to their nominal emission factor. These policy instruments provide correct incentives for energy producer to assess the social carbon costs of wood energy use when choosing the profitmaximizing fuel mix. The policy does not promote carbon sequestration, but it reduces the preferred status of wood fuels and, thus, energy use of wood. Table 2. Unit carbon payments in partial and optimal scenarios. Baseline scenario has only the fossil fuel tax. The effective emission factor for harvest residues is calculated using timeinvariant social cost of carbon (Lintunen & Uusivuori 214). FUEL USE OPTIMAL POLICY PARTIAL POLICY Fossil ε f SCC ε f SCC Harvest residue ε w r δ DOM,d + r SCC ε w r δ DOM,d + r SCC Roundwood ε w SCC INPUT USE Roundwood Our optimal policy scenario refers to a more extensive carbon policy that encompasses all the wood use emissions as well as carbon sequestration by forest biomass. We follow here the 7

8 stock change method for carbon accounting (IPCC 26) and, thus, the forest carbon tax on forest owner is denoted as δ DOM,d [(H t + γ d H δ DOM,d + r t ) (1 + γ d ) G t ] ε w SCC, d where H t denotes the roundwood harvest yield, G t the volume growth of roundwood biomass and γ d the relative yield of harvest residues of category d (Lintunen and Uusivuori 214). There is a tax on harvests and on the generation of harvest residues of different types. The social cost of harvest residue carbon stocks is calculated for the case of a time-invariant social cost of carbon. In addition, there is a subsidy for carbon removals by the biomass growth. In the optimal policy scenario, not only the wood combustion emissions but also the emissions from roundwood use in forest industries are taxed. This happens indirectly as all the roundwood harvests are taxed in the forest owner policy. To avoid double counting, the roundwood use in energy sector is treated as emissions free (cf. Table 2). The optimal scenario studied here does not fully follow the policy derived by Lintunen and Uusivuori (214). Given the restrictions of the current modeling framework, we did not consider the carbon that is stored into the harvested wood product carbon pool nor did we apply emission taxes for non-renewable input use. If these effects could have been taken into account, they increase the competitiveness of roundwood use, especially in the case of wood product industry. d In our study, we specify three categories of harvest residues, namely small-diameter branches, small-diameter stems and stumps. The categories differ substantially with respect to their decay timescales. In the Figure 1, the effective emission factors for various types of harvest residues are represented. When calculating the emission factors, the values of decay rates are based on Repo et al (211), namely.1 for branches,.5 for small-diameter stems and.1 for stumps. These correspond to the decay timescales of 1, 5 and 1 years. With discount rate of 3 % used in our policy calculations, the effective emission factors and thus the cost of emissions for branches and small-diameter stem are lower than the one for natural gas, as seen in Figure 1. For stumps, the emission factor is higher than the one for natural gas but lower than the ones for coal and peat. 8

9 Figure 1. Effective emission factors for different decay rates and discount rates. 4. Data and assumptions used in the policy calculations Data: TBA The policy and baseline calculations are performed with carbon prices of 15 or 3 /t CO 2. The discount rate of 3 % is used when calculating the effective emission factors. This is consistent to discount rate used in calibration of the forest supply sector. The scenarios are run for 1 periods that are 5 years long. 5. Results 5.1 Impacts on wood market Optimal policy implies considerably larger shock to the wood markets than partial policy. In the partial policy, policy instruments are targeted only on the wood used as energy, while in the case of optimal policy, policy instruments cover all roundwood and forest residues. In the optimal policy, carbon rents paid to the forest owners postpone their harvests thus reducing the timber supply. Some forest owners might even give up the fellings thus having income only from carbon rents. After implementing the policy, the fellings drop notably 9

10 % % especially in the case of price of carbon of 3 /t CO 2 (Figure 3). Lower levels of fellings increase gradually the forest stock. Since the initial rotation periods are below the MSY rotations of 9 years, the growth of biomass increases with its size. Therefore, harvests can be gradually increased and the long term impact on fellings is moderate. Reduced supply increases the prices of wood substantially after launching the optimal policy especially in the case of 3 carbon price (Figure 4 for price of pulpwood). Price impact diminishes over time with increased wood supply potential. In the case of partial policy, emission payments for wood-based fuels decrease their demand and nearly cease the use of pulpwood in the production of energy, thus reducing the price of pulpwood (Figure 4) and decreasing the fellings (Figure 3) yrs from start of the policy OPTIMAL15 OPTIMAL3 PARTIAL15 PARTIAL3 Figure 3. Impact (as percentage change) on fellings for optimal and partial policies with carbon prices of 15 and 3 /t CO 2. The policy scenarios are compared with BAU scenario with same price of carbon and with same time period OPTIMAL15 OPTIMAL3 PARTIAL15 PARTIAL3 yrs from start of the policy Figure 4. Impact (as percentage change) on price of pulpwood for optimal and partial policies with carbon prices of 15 and 3 /t CO 2. The policy scenarios are compared with BAU scenario with same price of carbon and with same time period. 1

11 5.2. Impacts on the fuel-mix in the energy sector Partial policy implies emission payments to the use of wood-based fuels, thus reducing their competitiveness against fossil fuels compared to baseline. In the short term, the existing capacity set limits to the substitution possibilities but new investments allow more flexibility. Total use of wood-based fuels is reduced compared to BAU scenario by 2 % (1 TWh) immediately, by 9 % (8 TWh) after 2 years of implementing the policy and by 12 % (12 TWh) after 45 years, when emission payments are based on the carbon price of 15 euros (Figure 5). The figures are 2 % (2 TWh), 15 % (14 TWh) and 2 % (21 TWh) for carbon price of 3 euros, respectively (Figure 5). In addition, emission payments based on the effective emission factors affect the competitiveness between wood-based fuels as emission payments are lower for harvest residues than for pulpwood and by-products whose emissions are paid according to nominal emission factor from burning. The supply and demand curves also differ between wood-based fuels. The supply of pulpwood and derived supply for harvest residues are price-sensitive while the domestic supplies of by-products are obtained as fixed shares of production of sawnwood and pulp and only imports of chips are pricesensitive. In the demand side, pulpwood is mainly used as raw material for forest residues while harvest residues, by-products and black liquor can only be used as fuels in the production of energy. Impacts on the uses of different wood-based fuels are represented in the Figure 7 measured as changes in energy units. Most of the reduction in the use of woodbased fuels is obtained by decreasing the use of pulpwood that is not profitable to use as fuel at all in the case of carbon price of 3 euros. The use of forest residues remains near the BAU level by reducing less than 5 % (1 TWh) after 45 years of implementing the policy. The use of by-products decreases by 1-18 % (2-4 TWh) in the case of carbon price of 3 euros with largest impact in the short run. On the other hand, the use of black liquor increases slightly compared to the BAU scenario as the decrease in price of pulpwood implies the slightly higher level of production in the pulpmills. Emission payments reduce the efficiency in the production of power and heat. Thus the increase in the use of fossil fuels exceeds the reduction in the use of wood-based fuels. The impacts on the uses of different fossil fuels are represented in the Figure 7 measured as changes in energy units. The use of fossil fuels is 4-22 % (4-14 TWh) or 8-46 % (6-24 TWh) above the BAU scenario, for prices of carbon of 15 or 3 euros (Figure 6). In the case of emission payments based on carbon price of 15 euros, the use of coal is increased most 11

12 (measured in energy units) as they can be used in the same boilers. In addition, there is excess capacity in coal power plants. Higher carbon price increases the costs of co-firing plants such that it is mainly profitable to invest to new power plants using natural gas. The additional cost for wood-based fuels affect differently the uses of peat and coal although both fuels are co-fired with wood. This is likely to be explained by the fact that peat is needed to produce district heat for inland. The optimal policy with carbon rents affect all wood used both energy and raw material for forest industry. Thus overall impacts are considerably larger than in the case of partial policy as prices of wood-based fuels and roundwood are considerably increased by lower supplies when fellings and productions of sawmill and pulpmills providing by-products and black liquor decrease. Incentives for energy producers to change the fuel mix are mainly due to the increased prices of wood-based fuels. For harvest residues, the emission payments in the power plants reduce their demand. In the case of optimal policy, dynamics is mainly due to the adjustment of timber stock. Optimal policy reduces the use of wood-based fuels by 6-25 % (4-23 TWh) or % (21-44 TWh) compared to BAU scenario in the cases of carbon prices of 15 or 3 euros (Figure 5). The impacts on the fuel mix are largest in the medium term (after 2 years after implementing the policy) when the prices of wood-based fuels are yet considerably higher than in BAU scenario and adjustments have already taken place in the production of energy. The use of all domestic wood-based fuels decreases in the case of optimal policy (Figure 7). For by-products the impact is smallest due to the increased imports of chips. In the case of optimal policy, increase in use of fossil fuels (Figure 6) is considerable less than the decrease in the use of wood-based fuels as optimal policy decreases the total use of fuels. The use of fossil fuels is -19 % (-12 TWh) or 1-4 % (1-24 TWh) above the BAU scenario for carbon prices of 15 or 3 euros. The fuel-mix of fossil fuels is similar than in the case of partial policy (Figure 7). 12

13 TWh TWh yrs from start of the policy OPTIMAL15 OPTIMAL3 PARTIAL15 PARTIAL3 Figure 5. Impact on the use of wood-based fuels for optimal and partial policies with carbon prices of 15 and 3 /t CO 2. The results are presented as difference in fuel uses (TWh) between optimal / partial policy and BAU scenarios with same price of carbon and with same time period OPTIMAL15 OPTIMAL3 PARTIAL15 PARTIAL yrs from start of the policy Figure 6. Impact on the use of fossil fuels for optimal and partial policies with carbon prices of 15 and 3 /t CO 2. The results are presented as difference in fuel uses (TWh) between optimal / partial policy and BAU scenarios with same price of carbon and with same time period. 13

14 TWh TWh 1 PARTIAL15-BAU Forest residues Pulpwood By-products Black liquor Coal Peat Gas from start of the policy PARTIAL3-BAU Forest residues Pulpwood By-products Black liquor Coal Peat Gas from start of the policy 14

15 TWh TWh 8 OPTIMAL15-BAU Forest residues Pulpwood By-products Black liquor Coal Peat Gas from start of the policy 15 OPTIMAL3-BAU Forest residues Pulpwood By-products Black liquor Coal Peat Gas from start of the policy Figure 7. Impact on the fuel-mix in the production of power and heat with carbon prices of 15 and 3 /t CO 2. The results are presented as difference in fuel uses (TWh) between optimal or partial policy scenario and BAU scenario with same price of carbon and with same time period. 5.3 Impacts on the prices of electricity and heat Both policies shift the supply curves of electricity and heat upwards as emission payments imply additional costs in the production. In optimal policy also prices of wood assortments 15

16 % % are higher due to the reduced supply. Optimal policy shifts also demand curve downwards as the increase in wood prices weakens the profitability of forest industries and decrease their input demands. 2 Electricity yrs from start of the policy OPTIMAL15 OPTIMAL3 PARTIAL15 PARTIAL Heat OPTIMAL15 OPTIMAL3 PARTIAL15 PARTIAL yrs from start of the policy Figure 8. Impact (as percentage change) on the prices of electricity and heat for optimal and partial policies with carbon prices of 15 and 3 /t CO 2. The policy scenarios are compared with baseline scenario with same price of carbon and with same time period. Both partial and optimal policies increase the price of heat compared to the baseline while the price of electricity is lower in policy scenarios (Figure 8). At first sight unexpected impact on the price of electricity is explained by the links between electricity and heat markets due to the combined heat and power plants. The implementation of emission payments on woodbased fuels increases costs in power plants producing heat more than in combined heat and 16

17 power plants. This is due to the fact that plants producing heat uses only wood while CHP plants wood is co-fired with peat and coal. Thus some production of heat is shifted to CHP plants that increase the supply of electricity. Thus there is also downward shift of supply curve of electricity that exceeds the upward shift due to the cost increase. This implies the lower price and the higher use of electricity in the case of partial policy than in the case of baseline policy. 5.4 Impacts on the atmospheric carbon The total impact of policies on the carbon stock in the atmosphere consists of impacts on forest biomass carbon stock change, soil carbon stock change and emissions from fossil fuels (Figures 9 and 1). The forests act as carbon sink in all the scenarios examined, namely BAU, partial and optimal scenarios in the case of Finland. Optimal policy with carbon rents based on the carbon price of 15 or 3 euros provide forest owners the strong incentive to increase the carbon sink. The size of carbon sink diminish over time as the growth of forests decreases when growing stock is increased and fellings are recovered to some extent. In the partial policy, forest owners face no incentive to increase the sequestration. The emission payments for producers of energy however lead to lower price for pulpwood that improves the profitability of sequestration. The impact is however considerable lower compared to optimal policy because only small amount of pulpwood is used as fuel. The dynamics in the case of partial policy differ also from optimal policy because the impact in carbon sink increases over time. Also the soil carbon stock change is positive in all scenarios. In the optimal policy, the soil carbon stock is smaller than in the partial policy as the lower level of fellings provide less harvest residuals into the soil carbon stock. The emissions of fossil fuels are increased due to both optimal and partial policy. Partial policy implies the higher use of fossil fuels in the long run then optimal policy. The net impact is positive for both optimal and partial policies. The increase in emissions from fossil fuels is considerably smaller than the increase in carbon sink especially in the case of optimal policy. This is explained by the fact that carbon rents increasing the carbon 17

18 milj. t CO2 million tons of CO2/yr sink are set on the total amount of roundwood of which only small part was used as energy in the baseline scenario and thus need to be replaced with fossil fuels Forest biomass carbon stock change Soil carbon stock change Fossil fuel emission impact Net impact -5-6 Figure 9. Impact of optimal policy with carbon price of 3 /t CO 2 on the atmospheric carbon compared with BAU scenario Forest biomass carbon stock change Soil carbon stock change -5-1 Fossil fuel emission impact Net impact Figure 1. Impact of partial policy with carbon price of 3 /t CO 2 on the atmospheric carbon compared with BAU scenario. 18

19 6. Conclusions Current climate policy gives incentives for substituting wood-based fuels for fossil fuels. The emission free treatment of wood-based biomass has however lately been questioned in the scientific debate. In addition, current policies do not promote carbon sequestration. This paper analyses the implications of optimal and partial climate policies on energy and wood markets as well as on the atmospheric carbon. In optimal policy, emissions from wood and carbon sequestration are paid according to the optimal effective emission factors representing the true social costs of the use. Our partial policy gives correct incentives for fuel mix decision of energy producer but carbon sequestration is not subsidized. Our results showed that current policies are likely to lead to excessive use of wood fuels. Setting the emission payments to solid wood biomass did not however cease their use in the production of heat and power. With the current climate policy, the use of wood-based was 2-35 % higher than optimal level and consequently the use of fossil fuels 8-16 % lower than optimal level. The partial policy with incentives for energy producers suggested in this paper implied the fuel-mix that were closer to optimal one than current one. However, also in the case of our partial policy, the use of wood-based fuels were 8-23 % above the optimal level, with highest difference in 15-2 years after implementing the policy. The use of fossil fuels were -5 % too low during the first 3 years and afterwards too high when the profitability of wood-based fuels improves. Obviously, the quantitative results depend on the economic, technological and ecological features that differ between countries as well as on the assumptions of the model. The magnitude of the impact depends on the point of time after launching the policy. In the optimal policy, the long term impacts were smaller than short term ones due to the increasing forest stock that allowed the level of fellings recover to some extent. On the other hand, for partial policy, impacts on the fuel-mix were strengthened in the long term as the gradual adjustment in the energy sector through investments. Both partial and optimal policies increased the price of heat compared to the baseline while the price of electricity was lower in policy scenarios. At first sight unexpected impact on the price of electricity is explained by the links between electricity and heat markets due to the combined heat and power plants. 19

20 Optimal policy increased notably carbon sequestration in the forests and thus reduced the atmospheric carbon more than the partial policy. On the other hand, timber market impacts were notable in the first periods increasing the costs of forest industries. Therefore optimal carbon policy could be implemented gradually in order to avoid the disturbances in the timber market that would not be politically acceptable. Partial carbon policy with emission payments on forest bioenergy provided smaller net emissions into the atmosphere than current policy and could be preferable to current carbon policy incentives. In our calculations with single-country market model, we assumed that policies were implemented only in Finland. The optimal policy increases the production costs in the forest industry thus weakening their international competitiveness. The assumption of unilateral implementation strengthen the impact of carbon rents on the carbon sink compared to multilateral implementation of policy. Unilateral policy would imply the carbon leakage as fellings were increased in the countries exporting wood to the country under policy. References Cherubini, F., Peters, G. P., Berntsen, T., Strømman, A. H., and Hertwich, E. (211). CO2 emissions from biomass combustion for bioenergy: atmospheric decay and contribution to global warming. GCB Bioenergy, 3(5): Fargione, J., Hill, J., Tilman, D., Polasky, S., and Hawthorne, P. (28). Land clearing and the biofuel carbon debt. Science, 319(5867): Hartman, R The harvesting decision when a standing forest has value. Economic inquiry, 14(1), Holtsmark, B. (212). Harvesting in boreal forests and the biofuel carbon debt. Climatic change, 112(2): Kangas, H.-L., Lintunen, J. and Uusivuori, J.(29). The cofiring problem of a power plant under policy regulations. Energy Policy 37(5):

21 Kangas, H-L., Lintunen, J., Pohjola, J., Hetemäki, L.& Uusivuori, J Investments into forest biorefineries under different price and policy structures. Energy Economics, 33(6), Lintunen, J. and Kangas, H.-L. (21). The case of co-firing: The market level effects of subsidizing biomass co-combustion. Energy Economics 32(3): Lintunen, J. and Uusivuori, J. (214). On the Economics of Forest Carbon: Renewable and Carbon Neutral But Not Emission Free. FEEM, Nota di Lavoro Lintunen, J., Laturi, J. and Uusivuori, J Finnish Forest and Energy Policy model (FinFEP) A Model Description. Mimeo. Natural Resources Institute Finland. Lippke, B. et al. (21). Letter to chairman Boxer et al. U.S. Congress. July 2. Mäkelä, M., Lintunen, J., Kangas, H.-L. and Uusivuori, J. (211). Pellet promotion in the Finnish sawmilling industry: The cost-effectiveness of different policy instruments. Journal of Forest Economics 17: Repo, A., Tuomi, M., and Liski, J. (211). Indirect carbon dioxide emissions from producing bioenergy from forest harvest residues. GCB Bioenergy, 3(2): Searchinger, T., Heimlich, R., Houghton, R. A., Dong, F., Elobeid, A., Fabiosa, J., Tokgoz, S., Hayes, D., and Yu, T.-H. (28). Use of us croplands for biofuels increases greenhouse gases through emissions from land-use change. Science, 319(5867): Sedjo, R. (211). Carbon neutrality and bioenergy: A zero-sum game? Resources for the Future Discussion Paper