Ultra-Low Carbon Emissions from Coal-Fired Power Plants through

Nov 6, 2015 - This study investigates a novel strategy of reducing carbon emissions from coal-fired power plants through co-firing bio-oil and sequest...
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Ultra-Low Carbon Emissions from Coal-Fired Power Plants through Bio-Oil Co-Firing and Biochar Sequestration Qi Dang,†,‡ Mark Mba Wright,*,†,‡ and Robert C. Brown†,‡ †

Bioeconomy Institute and ‡Department of Mechanical Engineering, Iowa State University, Ames, Iowa 50011, United States

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S Supporting Information *

ABSTRACT: This study investigates a novel strategy of reducing carbon emissions from coal-fired power plants through co-firing bio-oil and sequestering biochar in agricultural lands. The heavy end fraction of bio-oil recovered from corn stover fast pyrolysis is blended and co-fired with bituminous coal to form a bio-oil co-firing fuel (BCF). Lifecycle greenhouse gas (GHG) emissions per kWh electricity produced vary from 1.02 to 0.26 kg CO2-eq among different cases, with BCF heavy end fractions ranging from 10% to 60%, which corresponds to a GHG emissions reduction of 2.9% to 74.9% compared with that from traditional bituminous coal power plants. We found a heavy end fraction between 34.8% and 37.3% is required to meet the Clean Power Plan’s emission regulation for new coal-fired power plants. The minimum electricity selling prices are predicted to increase from 8.8 to 14.9 cents/kWh, with heavy end fractions ranging from 30% to 60%. A minimum carbon price of $67.4 ± 13 per metric ton of CO2-eq was estimated to make BCF power commercially viable for the base case. These results suggest that BCF co-firing is an attractive pathway for clean power generation in existing power plants with a potential for significant reductions in carbon emissions.

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INTRODUCTION According to data from the Environmental Protection Agency (EPA), the United States emitted approximately 6673 million metric tons of CO2-eq in the year 2013, and electricity generation accounted for almost one-third of greenhouse gas (GHG) emissions among all economic sectors.1 Emissions from the power sector were derived mostly from burning fossil fuels, primarily coal and natural gas. To reduce carbon pollution from the power sector, the U.S. government finalized the strategic Clean Power Plan in August of 2015. The plan aims at cutting the carbon pollution from the power sector by 32% from 2005 levels when it is fully in place in 2030.2 The U.S. government also empowered the EPA to issue final limits for new, modified, reconstructed, and existing power plants. The specific regulation for new coal-fired power plants set a restriction to 1400 lb CO2/MWh (0.635 kg/kWh).3 It stated that the final standard is achievable by new fossil-fuel-fired system generating units for all fuel types, under a wide range of conditions and throughout the United States.3 The flexibility of the rule allows each state to propose novel methods in their plans to cut carbon pollution under the Clean Power Plan in addition to choosing highly efficient technologies for the power plants, shifting to natural gas, or developing renewable power sources. For the sake of achieving this target, as well as enhancing energy security and maintaining environmental sustainability, exploring renewable energy, particularly bioenergy, is highly encouraged. Biomass has gained interest due to its important role in reducing carbon emissions, and it is expected to be an important energy source in the U.S. electricity mix under renewable portfolio standards.4,5 © 2015 American Chemical Society

Fast pyrolysis is an effective way to convert a variety of biomass feedstock into fuels. It is a thermochemical process that decomposes biomass into liquid (bio-oil), solid (biochar), and gas products.6,7 There is extensive research in both fast pyrolysis experimental methods and reaction models.8−11 Biooil from biomass fast pyrolysis can be a promising enabler of renewable power generation by overcoming biomass and coal co-firing limits.12,13 Whereas biomass and coal co-firing is often limited to about 20 wt % (biomass shares in total inputs on a mass basis) due to technical limitations in conventional boilers,14 bio-oil co-firing of over 30 wt % (bio-oil shares in total inputs on a mass basis) has been demonstrated at Iowa State University (ISU).15 Bio-oil can be blended with heavy fuel oil, light fuel oil, or natural gas in a variety of applications, including boilers, gas turbines, and other heat and power units. Fast pyrolysis also produces noncondensable gas (NCG) and solid biochar as byproducts. NCG is a low-energy density gas (about 6 MJ/kg) that can substitute for natural gas.16 The solid fast pyrolysis product, biochar, has several potential applications. Biochar is traditionally combusted to provide the process heat for fast pyrolysis and steam generation. However, in terms of reducing carbon emissions, biochar is considered to be more valuable and favorable as a soil amendment than as a fuel. When biochar is sequestered in soil as a soil amendment, it provides nutrients, improves water retention capacity, and Received: Revised: Accepted: Published: 14688

August 1, 2015 November 4, 2015 November 6, 2015 November 6, 2015 DOI: 10.1021/acs.est.5b03548 Environ. Sci. Technol. 2015, 49, 14688−14695

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Environmental Science & Technology

Figure 1. Simplified process flow diagram of corn stover fast pyrolysis and the BCF co-firing system for combined heat and power generation (heavy end fraction: 30 wt %, corn stover moisture content: 25 wt %, coal moisture content: 11.12 wt %, isentropic efficiencies of turbines: 85%).

reduces soil bulk density.17,18 It remains sequestered for hundreds of years, thus serving as a carbon sink.19 It is possible, therefore, to achieve negative GHG emissions in energy systems when sequestering biochar in soil instead of releasing it into the atmosphere. The literature has shown that there are several benefits of capturing biochar and returning it back to the soil.20,21 For example, biochar sequestration can inhibit nitrous oxide (N2O) and methane (CH4) emissions from the soil.21 Although several benefits of biochar have been documented, the mechanism for such processes is still unclear, and further investigation is needed. So far, the scientific research on biofuels shows a strong interest in the production of biofuels through biomass fast pyrolysis,22,23 while only a few studies focus on the environmental impacts of electricity generation by applying products from pyrolysis platform. Fan et al.24 investigated GHG emissions for power generation through pyrolysis processing different forest resources as biomass feedstock. GHG savings of 77%−99% were estimated from pyrolysis oil combustion compared with fossil fuel combustion for power generation. Huang et al.25 evaluated environmental impacts of co-firing biochar and coal for electricity generation using various indicators. With a co-firing ratio of 10% and 20%, GHG emissions were reduced by 4.2% and 8.7% for 1 kWh electricity generated in contrast to electricity generation by coal only. Pourhashem et al.26 analyzed GHG emissions and the cost trade-offs of producing bio-oil from fast pyrolysis and the subsequent electricity generation. Meanwhile, the scenario of burning biochar in coal power plant for power production was compared with biochar as a land amendment scenario in their study. We propose a novel strategy for reducing carbon emissions from coal-fired power plants based on the utilization of bio-oil and biochar from the fast pyrolysis of biomass. Part of the biooil is combined with coal to form a solid co-firing fuel without the usual problems of boiler derating and ash fouling usually associated with biomass co-firing. The biochar, an inevitable

product of pyrolysis usually considered of relatively low value, is applied to agricultural lands, where it sequesters carbon and builds soil fertility. Brown et al.27,28 have developed a pyrolysis system that recovers bio-oil as five stage fractions (SF) with distinctive physical and chemical properties. Each stage fraction can be utilized or upgraded individually according to its unique composition. In this work, bio-oil is separated as heavy-end, middle end, and light end fractions. The heavy ends are assumed to be blended and co-fired with bituminous coal to form a bio-oil co-firing fuel (BCF) compatible with existing coal-boiler systems to produce electric power. Large-scale experiments at ISU have proven that a combination of 30 wt % heavy ends and 70 wt % crushed coal has similar physical characteristics as traditional coal,15 which forms the basis of this study. Given its higher heating value and lower GHG emissions, BCF exhibits significant potential of reducing coal consumption in power generation systems. Therefore, a novel strategy of combing bio-oil with coal for electric power generation from existing power plants is proposed, and a new vision of sequestering biochar produced as soil amendment is adopted in this work. This approach provides a sustainable and economical pathway to meeting lifecycle carbon reduction targets in the power sector. This paper focuses on evaluating the GHG emissions of displacing coal via co-firing bio-oil heavy ends with coal for electric power production along with sequestering biochar as soil amendment. To identify the benefits of the proposed system, we also analyze the traditional application of biochar as boiler fuel for comparison. Widely used methodologies such as chemical process design using Aspen Plus, life-cycle assessment (LCA), and techno-economic analysis (TEA) are employed to evaluate the performances of different scenarios. In addition, this study employs sensitivity and uncertainty analysis to characterize key parameters and potential risks of the proposed systems. Environmental impacts of GHG emissions, as well as the economics and market viability of power generation from the 14689

DOI: 10.1021/acs.est.5b03548 Environ. Sci. Technol. 2015, 49, 14688−14695

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Environmental Science & Technology

Figure 2. System boundary of the biochar sequestration scenario for biomass fast pyrolysis and bio-oil co-firing fuel electricity generation.

The system boundary for the biochar sequestration scenario is shown in Figure 2. The alternative scenario is to combust the biochar, which increases power output but also increases GHG emissions. The LCA model for both scenarios is composed of five major steps: corn stover (biomass) production, transportation, pretreatment, fast pyrolysis, and steam and power generation. The inventory data for corn stover collection process is adapted from that of corn in the U.S. Life-Cycle Inventory (LCI) database in SimaPro. The energy consumed in the corn stover production process is allocated from corn production with a mass ratio of 39.6 wt % to match with the data of corn stover in the GREET 2013 model developed by Argonne National Laboratory (ANL)30 and literature values.31 Nitrogen fertilizer and quicklime are utilized in the corn production process as well as agrochemicals in the form of pesticides. Diesel and gasoline consumed by farm machinery are also taken into consideration. Electricity is consumed in the collection process as well. The effect of direct land-use changes for corn production due to different tillage practices is included in the U.S. LCI database and considered in the LCA model. We assume that corn stover pretreatment occurs at the fast pyrolysis plant gate. Corn stover collected in the field is transported to distributed pyrolysis plant over a distance of 48.3 km (30 mi) according to GREET. During the pretreatment process, electricity is consumed for grinding, and the specific energy requirement can vary greatly on the basis of equipment and feedstock conditions. The amount of heat and energy required for the fast pyrolysis process ranges between 230 to 1000 kJ/kg of biomass.32 In practice, the amount of energy required to thermally decompose biomass is not significant once the reactor is heated up to the desired temperature because fast pyrolysis is slightly endothermic.33 The heat can be provided by internally combusting NCG or a portion of biochar. In this paper, we assume that the energy needed for the pyrolysis plant including pretreatment and fast pyrolysis is 0.84 MJ for 1 kg dry biomass processed based on the research done by ISU, which is also consistent with the value in GREET.34 All of the biochar produced is either sequestered into the soil or combusted for electricity production. In both the biochar sequestration and the biochar combustion scenarios, electricity and light ends are the outputs. Detailed information about these assumptions is provided in Table 1. For BCF co-firing, bituminous coal is employed. Upstream processes, such as coal mining and transportation steps, are

BCF co-firing system, are determined. Target values of heavy end fraction in the co-firing process are proposed to meet the Clean Power Plan’s regulation for new coal-fired power plants. The results derived from this study could provide guidance and suggestions in energy policy decision-making.

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METHODS AND MATERIALS Power Generation Process Model. The overall process consists of a fast pyrolysis platform coupled with a combined heat and power (CHP) generation unit, which is designed using Aspen Plus software. The fast pyrolysis facility has a processing capacity of 2000 t (MT) of dry biomass per day. Corn stover is employed as the biomass feedstock in this study, and its properties are presented in Table S1. The established process model includes five technical areas, namely pretreatment, fast pyrolysis, solids removal, bio-oil recovery, and steam and power generation units. The power generation section is designed according to the plant design case of a subcritical pulverized coal combustion from the National Energy Technology Laboratory’s (NETL) report.29 The power generation process model is described in detail in Text S1. A total of two process models are designed because biochar can either be sequestered in soil as soil amendment (biochar sequestration scenario) or burned with BCF as coal substitute (biochar combustion scenario). The flow diagram of the biochar sequestration scenario is described in Figure 1 to illustrate the parameters of the overall process. Life-Cycle Assessment Model. This LCA study aims at quantitatively evaluating GHG emissions on a life-cycle basis by co-firing heavy end fraction of bio-oil and coal for power generation. To construct the LCA model, we employed SimaPro 7.3 using the IPCC 2007 method over a 100 year time horizon based on guidelines by the Intergovernmental Panel on Climate Change (IPCC). CO2, CH4, and N2O are regarded to be the major greenhouse gases. As IPCC reports indicate, GHGs have different global warming potentials; therefore, CO2, CH4, and N2O are given weighting factors of 1, 25, and 298 CO2-eq, respectively. Furthermore, the International Organization for Standardization specifies that environmental impacts should be reported in terms of a functional unit, which allows comparisons of impacts associated with different products. In this study, we assume a functional unit of 1 kWh electricity generated over the conversion pathway, and GHG emissions are reported as kg CO2-eq/kWh electricity produced. 14690

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tion and biochar combustion scenarios have been established on the basis of the different applications of biochar. Sensitivity analysis of the heavy end fraction of BCF on the total power production is explored for both scenarios. By varying the heavy end fraction of BCF from 10% to 60% with a step of 5%, eleven different cases within each scenario are investigated and the detailed inputs and outputs of them are presented in Table S4. Biomass input to the pyrolyzer is assumed constant at 2000 (dry) MTPD, and the coal input for the heat and power generation section is adjusted to achieve the desired heavy-end bio-oil fraction for BCF production (the heavy end fraction is defined as the mass share of the heavy ends in the total mass inputs of coal and the heavy ends). Increasing the heavy end fraction from 10% to 60% reduces coal consumption from 6147 to 455 MTPD. The electric power output from the biochar sequestration scenario decreases linearly from 695 to 119 MW with coal consumption, while that for biochar combustion scenario decreases from 721 to 145 MW. The energy efficiencies of the co-firing power generation system (the ratio of the energy content of total power output to the energy inputs of coal, heavy ends, middle ends, NCG, and biochar from biomass pyrolysis) decrease from 28.2% to 26.2% for biochar sequestration. The overall facility efficiencies, which include the energy content of biochar and light ends as output, increase from 33.1% to 53% with increasing amounts of bio-oil co-fired in the power generation system. Turbine efficiencies, corn stover moisture content, and coal moisture content are chosen to investigate the sensitivity of total electric power output to changes in each of the parameters. Certain ranges are given to each of the parameter (heavy end fraction: 10% to 60% with a step of 5%; turbine efficiencies: 75% to 95% with a step of 5%; corn stover moisture content: 10% to 40% with a step of 5%; coal moisture content: 5% to 20% with a step of 5%). The results of this analysis are presented in Figure 3. The base point corresponds

Table 1. Life-Cycle Inventory Data of Key Raw Materials and Energy Resources for The BCF Co-Firing System item

unit

value

source

corn stover production, transportation, and conversion nitrogen fertilizer g/kg corn produced 16.9 U.S. LCI quicklime g/kg corn produced 30.5 U.S. LCI pesticides g/kg corn produced 0.288 U.S. LCI diesel mL/kg corn 6.86 U.S. LCI produced gasoline mL/kg corn 1.88 U.S. LCI produced electricity consumption Wh/kg corn 12.2 U.S. LCI produced truck transport to pyrolysis km/kg corn stover 48.3 GREET plant delivered pyrolysis plant power MJ/kg corn stover 0.84 literature consumption pyrolyzed report36 coal production and transportation coal mining electricity consumption Wh/kg coal produced 38.7 U.S. LCI coal transportation U.S. LCI by barge km/kg coal delivered 126.6 U.S. LCI by diesel-powered km/kg coal delivered 6.76 U.S. LCI combination truck by diesel-powered train km/kg coal delivered 1043 U.S. LCI

considered. It is assumed that coal is transported by train, truck, and barge with corresponding transport distances of 1043, 6.76, and 126.6 km, respectively. As for electricity production from bituminous coal alone, the data from the U.S. LCI database in SimaPro features a GHG emission of 1.05 kg CO2-eq/kWh of electricity produced.35 It should be stated that the environmental burden from the corn stover production process can be distributed to all the products from fast pyrolysis by mass or energy allocation method. Because all of the products from fast pyrolysis except light ends are utilized in the following combined heat and power generation section, the mass and energy allocation cases introduce most of the upstream indirect emissions. The case with no allocation to the SF5 (light ends) is analyzed as well when we assume light ends are coproduced in the process, and we do not allocate the upstream emissions of corn stover production to it, which means all of the upstream emissions of corn stover production are incorporated into the overall process due to the utilization of the rest of the products. For all the three different cases, the light end is an output product in the BCF system, and the carbon contained in there is sequestered instead of releasing to the atmosphere. In addition, the light ends can be potentially used on some pavement materials to produce cement, which indicates the carbon within the light ends can still be sequestered in this regard. Techno-Economic Analysis Model. The economics of producing bio-oil and co-firing BCF in a combined heat and power facility is evaluated using TEA. This study estimates the capital and operating costs associated with the construction and operation of the conversion facility to determine the minimum electricity-selling price (MESP) to achieve a 10% internal rate of return (IRR) over a 20 year plant life. The detailed description of TEA assumptions can be found in Text S2 and Table S3.

Figure 3. Sensitivity of power output to changes in key parameters for the biochar sequestration scenario (the parameter set of base point: heavy end fraction of 30 wt %, turbine efficiencies of 85%, corn stover moisture content of 25 wt %, and coal moisture content of 11.12 wt %).

to a parameter set of heavy end fraction of 30%, turbine efficiencies of 85%, corn stover moisture content of 25%, and coal moisture content of 11.12%. Changing the heavy end fraction by ±66.7% results in a power output variation of 202.5% and −40.4%, which indicates that heavy end fraction is the most influential factor to total power export among the

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RESULTS AND DISCUSSION BCF Co-Firing Power Generation Process Model. As discussed previously, Aspen Plus models of biochar sequestra14691

DOI: 10.1021/acs.est.5b03548 Environ. Sci. Technol. 2015, 49, 14688−14695

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Environmental Science & Technology specified range. A range of turbine efficiencies from 75% to 95% are investigated, and the efficiencies are set simultaneously for high-pressure, medium-pressure and low-pressure turbines. The power output changes ±11% linearly when varying turbine efficiencies by ±11.8%. The power output exhibits a variation of 2.7% and −3% with corn stover moisture content changing by ±60%. To further investigate the impacts of these four key parameters on the total power output simultaneously, we set a combination of different parameter values. The results of combinations of 1540 cases are tracked and collected using Aspen Simulation Workbook, and a Response Surface Method (RSM) is employed to identify the impact of multiple variables simultaneously by fitting all the data sets. The data sets are incorporated into a regression model, which can be used as a surrogate for the electric power generated. The regression models of both scenarios can be found in Table S5, and the RSM results are presented in Text S3. Life-Cycle Greenhouse Gas Emissions. As discussed, heavy ends, middle ends, light ends, biochar, and NCG are produced in the fast pyrolysis process, and the environmental burdens can be allocated to all products by either mass or energy distribution. Meanwhile, light ends are not utilized in the combined heat and power generation section; therefore, the case of no allocation to light ends, as well as mass allocation and energy allocation cases, are analyzed within both the biochar sequestration scenario and the biochar combustion scenario. The detailed data are included in Tables S6 and S7, respectively. The life-cycle greenhouse gas emissions of the biochar combustion scenario is presented in Text S4. Results of the Biochar Sequestration Scenario. The sensitivity analysis results of heavy end fraction on GHG emissions are presented in Figure 4a; the turbine efficiencies, corn stover moisture, and coal moisture content are kept the same as the base point (turbine efficiencies: 85%, corn stover moisture content: 25%, and coal moisture content: 11.12%). We can see that with the heavy end fraction varying from 10% to 60%, GHG emissions are reduced from 1.01 to 0.264 kg CO2-eq/kWh electricity produced for the mass allocation case, while they decrease from 1.01 to 0.279 kg for the energy allocation case and drop from 1.02 to 0.321 kg for no allocation to SF5. Given that U.S. bituminous coal power plants have a GHG emission of 1.05 kg CO2-eq/kWh electricity produced, GHG emission reductions of 3.8% to 74.9%, 3.8% to 73.4%, and 2.9% to 69.4% are obtained in the corresponding cases as indicated in Figure 4b. These results suggest that differences in estimates for GHG emissions among the three allocation methods are smaller with lower heavy end fraction and increase proportionally with the heavy end fraction. Moreover, the emission results of mass and energy allocation are similar to each other. Mass allocation yields slightly lower GHG emissions than the energy allocation, while the result of no allocation to SF5 is a little higher compared with the other two. To meet EPA’s regulation for new coal-fired power plants, which represents 0.635 kg CO2-eq/kWh, we predict the required heavy end fraction of BCF to be 34.8%, 35.4%, and 37.3% for mass allocation, energy allocation, and no allocation to SF5 case, respectively. The GHG emissions of unit processes in EPA target cases are provided in Figure S2. Sensitivity Analysis. A total of nine key parameters from the base case are examined in the sensitivity analysis to identify the most influential parameters on the GHG emissions. The

Figure 4. Sensitivity analysis of heavy end fraction of BCF on (a) GHG emissions and (b) GHG emission reductions in the biochar sequestration scenario.

specified mass allocation case in the biochar sequestration scenario (heavy end fraction: 35%, turbine efficiencies: 85%, corn stover moisture content: 25%, and coal moisture content: 11.12%) is designated as the base case. The sensitivity of GHG emissions as shown in Figure 5 indicates that the heavy end fraction has a remarkable impact on GHG emissions within ±20% of its base value. Turbine efficiencies are varied by ±10% to keep lower and higher limit values within the investigated range. Turbine efficiencies have significant effect on GHG emissions with positive impacts at higher values, followed by the carbon sequestration rate by biochar, which is defined as the carbon sequestered in the total carbon content of pyrolysis feedstock. Electricity consumption in the pretreatment and pyrolysis processes represent a relatively impactful effect on GHG emissions, followed by corn stover moisture content and transport distance. Quicklime and nitrogen fertilizer provided during the corn-production process have very little influence on GHG emissions because a small ratio of upstream material and resource and energy inputs are allocated to corn stover in this study. Uncertainty Analysis. Uncertainty analysis is conducted in this work to predict the ranges of expected GHG emissions by incorporating probability distributions of selected parameters associated with unit processes. All of the selected parameters including their uncertainty distributions and ranges can be found in Table S8. As mentioned previously, 1540 cases for each scenario are simulated using an optimized Aspen Plus model to generate a RSM of the electric power output. The objective function derived from the RSM is introduced into SimaPro for calculating the distribution of GHG emissions. 14692

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Figure 5. Sensitivity analysis of key parameters on GHG emissions of the biochar sequestration scenario.

generation. The LCA results suggest that replacing coal with BCF in existing coal-fired power systems has a potential for reducing life-cycle GHG emissions. The TEA estimates that the projected electricity price from the overall system is competitive, although it is higher than the U.S. industrial electricity price in 2014, and the co-firing technology has not been demonstrated commercially. At the current technical level, economic incentives, tax credits, and subsidies are required to financially support and promote biofuel and biopower technology. A carbon price is an economically suitable way to support GHG emissions reduction targets. In this study, we estimate the required carbon price on the basis of the electricity price difference between our projected value and the U.S. industrial electricity price divided by the life-cycle GHG emission savings. Existing bituminous coal power plants emit an average GHG emissions of 1.05 kg CO2-eq/kWh,35 and the U.S. industrial electricity price is 7.01 cents/kWh in the year 2014.37 The mass allocation case of the biochar sequestration scenario calculated GHG emissions ranging from 0.21 to 0.77 kg/kWh and electricity prices varying from 8.77 to 14.90 cents/kWh. For the base case, the minimum carbon price value required to make BCF power generation competitive has a value of $67.3 ± 13 per ton. The uncertainty distribution of carbon price is illustrated in Figure S4. The carbon price derived from our study is higher than those presented in established carbon markets (between $12 and $20 during the past three years).38 This suggests that BCF technology could be a competitive carbon emission reduction agent if a viable carbon market exists. Further research should be explored to determine the economic and environmental potential of BCF power generation as a carbon mitigation strategy.

GHG emission distributions resulting from 10 000 Monte Carlo simulations are obtained after incorporating all of the data sources into SimaPro. Figure 6 represents the generated results of three allocation cases, respectively, within each scenario. Center lines represent

Figure 6. GHG emissions of the (a) biochar sequestration scenario and (b) biochar combustion scenario.

median values, while the edges of the boxes stand for 25% quantile and 75% quantile, and the lower and upper fences show the minimum and maximum value of the distributions, respectively. Mass and energy allocation distributions observed in Figure 6a,b have smaller median values and tighter ranges compared to the case of no allocation to SF5. Trade-Offs between Environmental and Economic Impacts. We investigate both the environmental impacts and the economic feasibility (presented in Text S5) to gain a better understanding of the trade-offs inherent in a corn stover fast pyrolysis and BCF co-firing system for electric power

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ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.est.5b03548. Additional details on the power generation process model, techno-economic analysis model, RSM results of BCF co-firing power generation process model, life-cycle greenhouse gas emissions of the biochar combustion 14693

DOI: 10.1021/acs.est.5b03548 Environ. Sci. Technol. 2015, 49, 14688−14695

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(8) Luo, Z.; Wang, S.; Liao, Y.; Zhou, J.; Gu, Y.; Cen, K. Research on biomass fast pyrolysis for liquid fuel. Biomass Bioenergy 2004, 26 (5), 455−462. (9) Meier, D.; van de Beld, B.; Bridgwater, A. V.; Elliott, D. C.; Oasmaa, A.; Preto, F. State-of-the-art of fast pyrolysis in IEA bioenergy member countries. Renewable Sustainable Energy Rev. 2013, 20, 619− 641. (10) Calonaci, M.; Grana, R.; Barker Hemings, E.; Bozzano, G.; Dente, M.; Ranzi, E. Comprehensive kinetic modeling study of bio-oil formation from fast pyrolysis of biomass. Energy Fuels 2010, 24 (10), 5727−5734. (11) Papadikis, K.; Gu, S.; Bridgwater, A. V.; Gerhauser, H. Application of CFD to model fast pyrolysis of biomass. Fuel Process. Technol. 2009, 90 (4), 504−512. (12) Brammer, J. G.; Lauer, M.; Bridgwater, A. V. Opportunities for biomass-derived “bio-oil” in European heat and power markets. Energy Policy 2006, 34 (17), 2871−2880. (13) Chiaramonti, D.; Oasmaa, A.; Solantausta, Y. Power generation using fast pyrolysis liquids from biomass. Renewable Sustainable Energy Rev. 2007, 11 (6), 1056−1086. (14) Sami, M.; Annamalai, K.; Wooldridge, M. Co-firing of coal and biomass fuel blends. Prog. Energy Combust. Sci. 2001, 27 (2), 171−214. (15) Friend, A. Development of a Co-Firing Fuel from Biomass-Derived Binder and Coal. Ph.D. Dissertation, Iowa State University, Ames, IA, 2013. (16) Mullen, C. A.; Boateng, A. A.; Goldberg, N. M.; Lima, I. M.; Laird, D. A.; Hicks, K. B. Bio-oil and bio-char production from corn cobs and stover by fast pyrolysis. Biomass Bioenergy 2010, 34 (1), 67− 74. (17) Brown, T. R.; Wright, M. M.; Brown, R. C. Estimating profitability of two biochar production scenarios: slow pyrolysis vs fast pyrolysis. Biofuels, Bioprod. Biorefin. 2011, 5 (1), 54−68. (18) Laird, D. A.; Brown, R. C.; Amonette, J. E.; Lehmann, J. Review of the pyrolysis platform for coproducing bio-oil and biochar. Biofuels, Bioprod. Biorefin. 2009, 3 (5), 547−562. (19) Kauffman, N.; Dumortier, J.; Hayes, D. J.; Brown, R. C.; Laird, D. A. Producing energy while sequestering carbon? The relationship between biochar and agricultural productivity. Biomass Bioenergy 2014, 63, 167−176. (20) Roberts, K. G.; Gloy, B. A.; Joseph, S.; Scott, N. R.; Lehmann, J. Life Cycle Assessment of Biochar Systems: Estimating the Energetic, Economic, and Climate Change Potential. Environ. Sci. Technol. 2010, 44 (2), 827−833. (21) Gaunt, J. L.; Lehmann, J. Energy balance and emissions associated with biochar sequestration and pyrolysis bioenergy production. Environ. Sci. Technol. 2008, 42 (11), 4152−4158. (22) Han, J.; Elgowainy, A.; Dunn, J. B.; Wang, M. Q. Life cycle analysis of fuel production from fast pyrolysis of biomass. Bioresour. Technol. 2013, 133, 421−8. (23) Dang, Q.; Yu, C.; Luo, Z. Environmental life cycle assessment of bio-fuel production via fast pyrolysis of corn stover and hydroprocessing. Fuel 2014, 131, 36−42. (24) Fan, J. Q.; Kalnes, T. N.; Alward, M.; Klinger, J.; Sadehvandi, A.; Shonnard, D. R. Life cycle assessment of electricity generation using fast pyrolysis bio-oil. Renewable Energy 2011, 36 (2), 632−641. (25) Huang, Y. F.; Syu, F. S.; Chiueh, P. T.; Lo, S. L. Life cycle assessment of biochar cofiring with coal. Bioresour. Technol. 2013, 131, 166−71. (26) Pourhashem, G.; Spatari, S.; Boateng, A. A.; McAloon, A. J.; Mullen, C. A. Life cycle environmental and economic tradeoffs of using fast pyrolysis products for power generation. Energy Fuels 2013, 27 (5), 2578−2587. (27) Pollard, A. S.; Rover, M. R.; Brown, R. C. Characterization of bio-oil recovered as stage fractions with unique chemical and physical properties. J. Anal. Appl. Pyrolysis 2012, 93, 129−138. (28) Rover, M. R.; Johnston, P. A.; Whitmer, L. E.; Smith, R. G.; Brown, R. C. The effect of pyrolysis temperature on recovery of bio-oil as distinctive stage fractions. J. Anal. Appl. Pyrolysis 2014, 105, 262− 268.

scenario, and techno-economic analysis results. Tables showing ultimate (dry basis) and proximate analysis (wet basis) of corn stover, biochar, and bituminous coal; product yields, mass, and energy distributions for bio-oil stage fractions (SF), non-condensable gas (NCG), and bio-char from corn stover fast pyrolysis; installation factors for estimating capital costs on the basis of equipment costs; key inputs, outputs, and energy metrics of bio-char sequestration and bio-char combustion scenarios; regression models of bio-char sequestration and bio-char combustion scenarios; life-cycle GHG emissions of the biochar sequestration scenario; lifecycle GHG emissions of the biochar combustion scenario; input parameter ranges and distributions for uncertainty analysis; capital costs and operating costs of the base case; and estimated electricity price for different cases of the biochar sequestration scenario. Figures showing the impacts of heavy end fraction and turbine efficiencies and corn stover and coal moisture content on the total power output, GHG emissions distribution of unit process in the biochar sequestration scenario, sensitivity analysis of heavy end fraction of BCF on GHG emissions and GHG emission reductions in the biochar combustion scenario; and probability density of minimum carbon price required to make the BCF electricity competitive with the U.S. industrial electricity price. (PDF)

AUTHOR INFORMATION

Corresponding Author

*Phone: 515-294-0913; e-mail: [email protected]. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS

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REFERENCES

The authors acknowledge the support of EPSCoR funding from the National Science Foundation (grant no. 420-17-12-600000) to this project. We also thank Iowa Energy Center for providing the planning grant to develop carbon negative energy at Iowa State University (grant no. 14-001-OG).

(1) Sources of greenhouse gas emissions from the United States Environmental Protection Agency website; http://www.epa.gov/ climatechange/ghgemissions/sources/electricity.html (accessed May 8, 2015). (2) Overview of Clean Power Plan; http://www2.epa.gov/ cleanpowerplan/fact-sheet-overview-clean-power-plan (accessed August 8, 2015). (3) EPA Fact Sheet; http://www.epa.gov/airquality/cpp/fs-cpsoverview.pdf. (accessed August 8, 2015) (4) Biomass Supply for a Bioenergy and Bioproducts Industry, Report ORNL/TM-2011/224; Oak Ridge National Laboratory: Oak Ridge, TN, 2011. (5) Comparative Analysis of Three Proposed Federal Renewable Electricity Standards, Report NREL/TP-6A2−45877. National Renewable Energy Laboratory: Golden, CO, 2009. (6) Bridgwater, A. V. Review of fast pyrolysis of biomass and product upgrading. Biomass Bioenergy 2012, 38, 68−94. (7) Dang, Q.; Luo, Z.; Zhang, J.; Wang, J.; Chen, W.; Yang, Y. Experimental study on bio-oil upgrading over Pt/SO42‑/ZrO2/SBA-15 catalyst in supercritical ethanol. Fuel 2013, 103, 683−692. 14694

DOI: 10.1021/acs.est.5b03548 Environ. Sci. Technol. 2015, 49, 14688−14695

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Environmental Science & Technology (29) Cost and Performance Baseline for Fossil Energy Plants Vol. 1: Bituminous Coal and Natural Gas to Electricity, Report DOE/NETL2010/1397; National Energy Technology Laboratory: Pittsburgh, PA, 2013. (30) Wu, M.; Wang, M.; Huo, H. Fuel-Cycle Assessment of Selected Bioethanol Production Pathways in the United States, Report ANL/ESD/ 06−7; Argonne National Laboratory: Lemont, IL, 2006. (31) Kim, S.; Dale, B. E.; Jenkins, R. Life cycle assessment of corn grain and corn stover in the United States. Int. J. Life Cycle Assess. 2009, 14 (2), 160−174. (32) Ringer, M.; Putsche, V.; Scahill, J.. Large Scale Pyrolysis Oil Production - a Technology Assessment and Economic Analysis, Report NREL/TP-510−37779; National Renewable Energy Laboratory: Golden, CO, 2006. (33) Boateng, A. A.; Daugaard, D. E.; Goldberg, N. M.; Hicks, K. B. Bench-scale fluidized-bed pyrolysis of switchgrass for bio-oil production. Ind. Eng. Chem. Res. 2007, 46 (7), 1891−1897. (34) GREET Model from Argonne National Laboratory; https:// greet.es.anl.gov/ (accessed February 5, 2015). (35) U.S. Life Cycle Inventory Database; http://www.nrel.gov/lci/ (accessed February 5, 2015). (36) Wright, M. M.; Daugaard, D. E.; Satrio, J. A.; Brown, R. C. Techno-economic analysis of biomass fast pyrolysis to transportation fuels. Fuel 2010, 89, S2−S10. (37) U.S. Energy Information Administration; http://www.eia.gov/ electricity/monthly/epm_table_grapher.cfm?t=epmt_5_3 (accessed July 5, 2015). (38) California Carbon Dashboard; http://calcarbondash.org/ (accessed May 8, 2015).

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NOTE ADDED AFTER ASAP PUBLICATION This paper was published ASAP on November 25th, 2015 with a typographical error in the main text and with incorrect Supporting Information. The corrected version and corrected Supporting Information were reposted on November 30th, 2015.

14695

DOI: 10.1021/acs.est.5b03548 Environ. Sci. Technol. 2015, 49, 14688−14695