اثرات اقتصادی سیاست انرژی زیستی در ایالات متحده و اروپا: یک رویکرد تعادل عمومی با تمرکز بر زیست توده جنگل

Renewable energy is an option for many countries simultaneously seeking to reduce dependence on imported petroleum and to reduce greenhouse gas (GHG) emissions that contribute to climate change. Forestry can play a role in environmental policies, such as renewable portfolio standards for bioelectricity, renewable fuel standards for biofuels, and forest carbon sequestration. This paper models interactions and interdependencies between bioelectricity and biofuel production, particularly from forest biomass. A global computable general equilibrium (CGE) model is used to measure the economic effects of bioenergy production from forest products, forest residues, and dedicated energy crops. The land use and emissions impacts on the global economy of revenue-neutral GHG mitigation policies are evaluated. Results show that mandated bioenergy production can substantially reduce carbon dioxide (CO2) emissions, especially through fossil fuel substitution in the electricity sector. Although emissions reductions from bioenergy production in the transportation fuel sector are less dramatic than those in the electricity sector, biofuels also have lower emissions rates than petroleum-based transportation fuels.

What changes in global supply, demand, price, land use and greenhouse gas (GHG) emissions result from the introduction of climate and energy policies that encourage bioenergy production, particularly from forest biomass? This is the question that motivates this research. Today, renewable energy is a desired option for many countries to simultaneously reduce dependence on imported petroleum and reduce GHG emissions that contribute to climate change. According to the United States Department of Energy (US DOE), bioenergy (i.e. renewable energy made from biological sources such as trees, dedicated energy crops, or waste from wood processing, agriculture, livestock, or municipalities) is considered a sustainable feedstock for the production of bioenergy [1]. The US DOE also cites a variety of woody biomass feedstocks that contain the organic polymers cellulose, hemicelluloses, and lignin, that can be converted to biofuels, bioelectricity, and biochemicals [2]. In that nearly one-third of the land area in the world was forest as of 2005, forests offer great potential for generating these lignocellulosic feedstocks [3]. In an attempt to answer the question that prompts this research, we add a variety of details to the recursively dynamic computable general equilibrium (CGE) framework of the Future Agricultural Resources Model (FARM). We include the joint production of forest, lumber, and paper residues to accurately account for the changes in price and supply for woody biomass. We introduce renewable electricity sectors, renewable transportation fuel sectors, and a dedicated energy crops sector to better account for producer demand for intermediate inputs in bioenergy production.1 We model bioenergy policies to generate renewable certificate prices that convey the cost to subsidize renewable electricity and transportation fuels. Additionally, because land use competition between forestry, dedicated energy crops, and agriculture is an important factor in bioenergy production, we incorporate the GTAP Land Use database to further explore land use change. Greenhouse gas emissions are examined by relating the production quantity of energy sectors to carbon dioxide (CO2) emissions using emissions factors. 1.1. Previous literature Bioenergy is a type of renewable energy made from biological sources, whether that is dedicated energy crops, trees, or waste from agriculture, wood processing, and municipalities. According to the US DOE [4], “biomass is an attractive petroleum alternative because it is a renewable resource that is more evenly distributed over the Earth's surface than finite energy sources, and may be exploited using more environmentally friendly technologies.” The Billion Ton Study [5] and the Billion Ton Update [6] examine the potential for biomass feedstocks in the United States. Specifically, forests are thought to have considerable potential for biomass production from the utilization of rotten wood from standing forest, logging residues, residues from thinning to improve forest health, direct conversion to fuelwood, and urban wood residues. Additionally, Daigneault et al. [7] find that bioenergy can be a net carbon sink if forest biomass is not limited to commercial roundwood production. In terms of modeling the potential of bioenergy production for climate change mitigation, Hertel et al. [8] argue that land use analysis is important in climate change research because land use affects patterns and changes in greenhouse gas emissions, while climate change affects land use through changes in precipitation and temperature. The authors find that computable general equilibrium (CGE) models are better able to analyze the economics of land use because partial equilibrium models solely focus on an adjustment of prices in land-using sectors to obtain equilibrium, while CGE models are designed to examine the tradeoffs of supply and demand in the entire economy. The original Future Agricultural Resources Model (FARM) developed by Roy Darwin is described as the earliest CGE model to study land use and land cover in the context of climate change [8]. Other CGE models that have been used to analyze equilibrium effects of bioenergy production, land use change, and greenhouse gas emissions include: various GTAP models [9], [10], [11], [12] and [13], LEITAP [14], AgLU 2x [15], USAGE [16], MIT EPPA [17], MIT IGSM [18], and ENVISAGE [19]. In an attempt to add to previous research on the subject, we include more recent renewable energy policies as well as additional disaggregated economic sectors. The EPPA model used by Reilly and Paltsev [17] is also a recursive dynamic CGE model, but modeled the Climate Stewardship and Innovation Act proposed to encourage cap and trade of GHGs in the United States. However, the Act failed to pass through the Senate in 2003, 2005, and 2007. Therefore, we model only existing renewable energy policies in the United States and Europe. In terms of agroforestry aggregation, we use 12 agricultural sectors, a forestry sector, and an additional sector for dedicated energy crops. In terms of bioenergy aggregation, unlike previous GTAP bioenergy models, we include five renewable electricity sectors and three renewable fuel sectors to give detail on potential sources of bioenergy production.

The most remarkable finding was the magnitude of CO2 emissions reduction from renewable electricity policies relative to renewable transportation fuel policies. In the United States, CO2 emissions intensity of the economy declined −11% in Scenario 1 (RPS), but only −1.5% in Scenario 2 (RFS/BD) when compared to the base case (Scenario 0). In Europe, the CO2 emissions intensity declined −6.9% in Scenario 1, but only −1.8% in Scenario 2. We believe these results occur for two reasons. First, renewable energy mandated as a percentage of total energy consumption for the RPS and electricity is always higher than the RFS or BD and transportation fuel. Second, a reduction in coal consumption leads to a greater decline in CO2 emissions than a reduction in petroleum consumption. The results show that in the current policy situation, where renewable portfolio standards for electricity coexist with renewable transportation fuel standards, the RPS mandates are higher than RFS mandates on a percentage basis. In the United States, for example, the RPS mandated that approximately 7.3% of total electricity be renewable (averaged across all states and the District of Columbia) in 2012, while the RFS mandated only 5.4% of total transportation fuels be renewable in the same year. This trend of the RPS mandating a larger percentage of renewables than the RFS or BD continues until the end of the timeframe studied (2054) in both the United States and Europe. In addition, coal (the primary energy source in electricity production) has a higher carbon intensity than petroleum (the primary energy source in transportation fuel production). As a result, displacing a joule of energy from coal electricity with renewables translates to a larger reduction in CO2 emissions than displacing energy from petroleum-based transportation fuels. It is important to note that the analysis focuses on the emissions changes in the production of renewable electricity and transportation fuel, although studies have shown that the combustion of retail ethanol and biodiesel typically leads to emissions reductions when compared to conventional petroleum gasoline and diesel as well [44]. Moreover, our analysis only examines bioenergy policies that currently exist in the United States and Europe, and we make no presumption about their effectiveness in GHG emissions reductions compared to various carbon neutral mitigation policies. In this context, the results indicate that existing renewable electricity policies have a more substantial impact on emissions reductions than do existing renewable fuel policies. In regards to policy implications, we conclude that both renewable energy policies impact land use, emissions, supplies, and prices. Each of the policy scenarios includes the addition of energy crops which, in combination with an increase in forest land use, reduces agricultural land. This phenomenon may cause concern for food crop production, as seen by the controversies surrounding conventional ethanol production from corn, sugarcane, and sugar beets. It is important to also consider the externalities of renewable energy policies, such as the impacts on rural farm communities or low-income energy consumers. Perhaps future economic research on other aspects of bioenergy policy would better address these specific issues. The FARM model, like other large CGE models, can overgeneralize economic sectors and biological processes that can play an important role in analyzing bioenergy policy. However, these shortcomings do not detract from the fact that the FARM model is capable of dynamic, economy-wide, global economic analysis. Ultimately, our economic analysis finds that emissions reductions can come from bioenergy production because bioenergy can have lower emissions rates than energy from fossil fuels [45]. Given that forests account for nearly one-third of global landmass, they provide a potential source for bioenergy production. We find in our analysis of renewable energy policies in the United States and Europe that forest biomass, in conjunction with other renewable sources, provides mitigation potential through fossil fuel substitution in the electricity and transportation fuel sectors. The results of the model indicate that even in the presence of a dedicated energy crop sector, forestry and forest products play an important role as a feedstock in bioenergy production.