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Environ. Sci. Technol. 2009, 43, 750–756

Life-Cycle Assessment of Energy Use and Greenhouse Gas Emissions of Soybean-Derived Biodiesel and Renewable Fuels H O N G H U O , * ,† M I C H A E L W A N G , † CARY BLOYD,§ AND VICKY PUTSCHE‡ Center for Transportation Research, Argonne National Laboratory, 9700 South Cass Avenue, Argonne, Illinois 60549, and Center for Transportation Technologies and Systems, National Renewable Energy Laboratory

Received April 25, 2008. Revised manuscript received September 9, 2008. Accepted November 8, 2008.

In this study, we used Argonne National Laboratory’s Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation (GREET) model to assess the life-cycle energy and greenhouse gas (GHG) emission impacts of four soybeanderived fuels: biodiesel fuel produced via transesterification, two renewable diesel fuels (I and II) produced from different hydrogenation processes, and renewable gasoline produced from catalytic cracking. Five approaches were employed to allocate the coproducts: a displacement approach; two allocation approaches, one based on the energy value and the other based on the market value; and two hybrid approaches that integrated the displacement and allocation methods. The relative rankings of soybean-based fuels in terms of energy and environmental impacts were different under the different approaches, and the reasons were analyzed. Results from the five allocation approaches showed that although the production and combustion of soybean-based fuels might increase total energy use, they could have significant benefits in reducing fossil energy use (>52%), petroleum use (>88%), and GHG emissions (>57%) relative to petroleum fuels. This study emphasized the importance of the methods used to deal with coproduct issues and provided a comprehensive solution for conducting a life-cycle assessment of fuel pathways with multiple coproducts.

1. Introduction There has long been a desire to find alternative liquid fuel replacements for petroleum-based transportation fuels. Biodiesel has been the focus of biofuel production because of its potential environmental benefits and because it is made from renewable biomass resources (1). Biodiesel can be derived from various biological sources such as oil seeds and animal fats. In the United States, a majority of biodiesel is produced from soybean oil. In recent years, the sales volume for biodiesel in the United States has increased dramatically from about 2 million gallons in 2000 to 250 million gallons * Corresponding author tel: +1 630 252 4467; fax: +1 630 252 3443; e-mail: [email protected]. † Argonne National Laboratory. ‡ National Renewable Energy Laboratory. § Decision and Information Sciences Division, Argonne National Laboratory. 750

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in 2006. Biodiesel production was estimated to be 450 million gallons in 2007 (2). To date, transesterification of seed oils and animal fats has been the major technology for biodiesel production. Meanwhile, new process technologies to convert seed oils and animal fats to diesel fuel and gasoline have recently emerged. The CANMET Energy Technology Centre of Natural Resources Canada has developed a technology to convert seed oils and animal fats into a high-cetane, low-sulfur, dieselfuel blending stock called “SuperCetane” (3). UOP developed conversion processes based on conventional hydroprocessing technologies that are already widely deployed in petroleum refineries. The hydrogenation technologies use seed oils or animal fats to produce an isoparaffin-rich diesel substitute referred to as “green diesel” (4, 5). UOP also proposed a technology that can produce “green gasoline” by cracking seed oils and grease in a fluidized catalytic cracker unit (5). The diesel and gasoline produced from these processes are often referred to as renewable diesel and renewable gasoline. The physical and chemical properties of the new renewable fuels are similar to those of conventional petroleum, and the fuels are able to meet existing standards. Also, they can be delivered by using the existing fuel delivery infrastructure with no modifications, so they would be supported by international oil companies. In this article, we present a well-to-wheels (WTW) analysis of the energy and greenhouse gas (GHG) emission impacts of soybean-based biodiesel, renewable diesel, and renewable gasoline relative to those of petroleum diesel and gasoline. For this study, we expanded and updated the GREET (Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation) model developed by Argonne National Laboratory (see http://www.transportation.anl.gov/ modeling_simulation/GREET/index.html). Our analysis includes the following six fuel pathways: conventional gasoline, conventional low-sulfur diesel, soybean-based biodiesel (BD), soybean-based renewable diesel I (“SuperCetane,” RD-I), soybean-based renewable diesel II (“green diesel,” RD-II), and renewable gasoline (“green gasoline,” RG). We used conventional gasoline and diesel as the baseline fuels; our analysis was conducted for year 2010. We estimated consumption of total energy, fossil energy, and petroleum oil and emissions of GHGs (CO2, N2O, and CH4). Because there are a variety of coproducts produced from the production processes of the soybean-fuels, five different allocation approaches were employed to address the multiple coproducts. The objective of this study is to examine the environmental benefits of the new proposed renewable fuels and their impact on energy demand from a life-cycle point of view.

2. Life-Cycle Data and Assumptions GREET is capable of estimating the full fuel-cycle energy and emissions impacts of various alternative transportation fuels and advanced vehicle technologies. The GREET life-cycle analysis methodology and pathways for petroleum-based gasoline, petroleum-based diesel, and soybean-based biodiesel have been incorporated into the GREET model and were well documented before this study (6-8). For this study, we updated soybean farming simulations and expanded GREET to include pathways for RD and RG fuels, which will be the main focus in this section. System Boundary. Figure 1 illustrates the system boundary of this study. The four soybean-based pathways consist of six stages, as shown, three of which they have in commonssoybean farming, soybean transportation, and soy 10.1021/es8011436 CCC: $40.75

 2009 American Chemical Society

Published on Web 12/23/2008

FIGURE 1. System boundaries for well-to-wheels analysis in this study. oil extraction; the pathways differ in their fuel production processes and vehicle operations. As illustrated in Figure 1, the GREET WTW modeling boundary has two stages: wellto-pump (WTP) and pump-to-wheels (PTW). WTP stages start with fuel feedstock recovery and end with fuels available at refueling stations. PTW stages cover vehicle operation activities. Soybean Farming. According to survey data released by the U.S. Department of Agriculture (USDA) (9), the total energy use for soybean farming was estimated to be 22,000 Btu/bu, with 64% diesel, 18% gasoline, 8% liquefied petroleum gas (LPG), 7% natural gas, and 3% electricity (9). Fertilizer use values for soybean farming were assumed for 2010 on the basis of newly released USDA data (10): N at 61.2 g/bu, P at 186.1 g/bu, and K at 325.5 g/bu. The energy use and emissions for fertilizer manufacturing are simulated separately in GREET. N2O Emissions from Farming Lands. N2O, a potent GHG, is produced from nitrogen in the soil through (1) nitrification and denitrification processes and volatilization of nitrogen from the soil to the air (direct emissions), and (2) leaching and runoff of nitrate into water streams (indirect emissions). The sources of nitrogen inputs to soil for crop farming include fertilizer application, aboveground biomass left in the field after harvest, and belowground biomass. The total amount of nitrogen in soybean biomass that is left in soybean fields was estimated to be 201 g/bu, according to an Intergovernmental Panel on Climate Change (IPCC) document (11). N2O emission factors (the conversion rates from nitrogen in soil and water streams to N2O emissions to the air) are subject to great uncertainties. IPCC reported a conversion rate of 1.25% for direct N2O emissions in 1996 (12). Afterward, many studies showed that the N2O field measurements were lower than the IPCC 1996 value, and some inventory studies also concluded that the IPCC method may overestimate the N2O emissions (13, 14). On the basis of the studies, IPCC reduced the value from 1.25% to 1% (0.3-3%), by ignoring the nitrogen input to soil from biological nitrogen fixation by legume crops because of a lack of evidence (11). A recent study estimated a conversion rate of 3-5% on the basis of the global N2O balance, which is being debated (15). Considering the previous studies, we used the IPCC N2O emission factor of 1.325% for direct and indirect emissions (11). Production of Soybean-Derived Fuels. At soybean processing plants, soybean seeds are crushed, soy oil is extracted

TABLE 1. Inputs and Outputs of Soybean-Based Fuel Plants (lb or Btu/lb fuel) inputs and outputs soy oil (lb) electricity (Btu) methanol (lb) hydrogen (lb) NG (Btu) glycerin (lb) fuel gas (Btu) heavy oils (Btu) propane fuel mix (Btu) product gas (Btu) light-cycle oil (LCO) (Btu) clarified slurry oil (CSO) (Btu)

BD

RD-I

inputs 1.04 1.51 46.0 134.4 0.10 0.030 888

RD-II

RG

1.17 93.8

2.23 185.6

0.032 105

coproducts 0.213 7084 3608 1096 6314 4737 5460

from the crushed seeds, and crude soy oil is refined. Detailed calculations of energy use during soy oil extraction are given in ref 6. BD is produced through the transesterification process, in which soy oil is combined with alcohol (ethanol or methanol) in the presence of a catalyst (sodium hydroxide) to form ethyl or methyl ester and coproduce glycerin. Parameters of BD plants were obtained from refs 16 and 17. Note that BD obtains fossil carbon from methanol, which is assumed to be produced from natural gas; in the meantime, soy oil gives the same amount of biogenic carbon to glycerin. Both were taken into account in calculating GHG emissions. Unlike the case for BD production, in which process mass and energy balances are readily available from commercial operating facilities, facility mass and energy balances for RD and RG production are either unavailable or available only from limited pilot plant operations that may not reflect mature commercial operating conditions. For the purpose of this study, the National Renewable Energy Laboratory (NREL) developed initial mass and energy balances by using the ASPEN process simulation model for the three types of renewable fuels examined in this study. Details of the differences among the renewable fuels and NREL’s ASPEN simulations were documented in ref 18. Table 1 lists the inputs and outputs of soybean-based fuel plants. As shown in the table, soybean-derived fuels have various coproducts. Fuel Use in Vehicles and Fuel Properties. Soybeanderived diesel and gasoline were assumed to be used in 100% pure form in vehicles with compression-ignition, directVOL. 43, NO. 3, 2009 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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TABLE 2. Properties of the Four Soybean-Based Fuels fuel

lower heating value (Btu/gal)

density (lb/gal)

carbon content (%)b

oxygen content (%)

petroleum gasolinea petroleum diesel a BD a RD-I (3, 18) RD-II (4, 5, 18) RG (5, 18)

113,600 129,490 119,550 117,060 122,890 116,000

6.2 7.1 7.4 6.2 6.5 6.2

84.0 87.1 77.6 87.1 87.1 84.0

NA 0.0 11.0 0.0 0.0 NA

a From the GREET model. b Because of the carbon content of RD fuels is assumed as that of petroleum-based diesel, and the of RG is assumed to be the same as leum-based gasoline.

a lack of data, to be the same carbon content that of petro-

injection engines, and with spark-ignition engines, respectively. We assumed that BD vehicles have the same fuel economy (19, 20) and the same CH4and N2O emissions as conventional diesel vehicles. Because of the lack of testing data for RD-I, RD-II, and RG, we assumed that their fuel economy and N2O and CH4 emissions are the same as their conventional counterpart. Table 2 presents the properties of the soybean-based fuels (3-5, 18).

3. Methods of Calculating Co-Product Credits for Biofuels The objective of calculating the credit allotted for coproducts in life-cycle analysis is to fairly address the energy and emission burdens of the primary product, especially when the coproducts have value in the marketplace. Two methods that are commonly used are the displacement method and the allocation method. With the displacement method, 100% of the energy and emission burdens go to the primary product, and a conventional product is assumed to be displaced by the coproduct. The life-cycle energy and emissions that would have been used and generated during the production of the displaced product are counted as credits for the coproduct. The allocation method allocates the feedstock use, energy use, and emissions between the primary product and coproducts on the basis of mass, energy content, or economic revenue. In this study, various coproducts are produced, including protein products (such as soy meal), industrial feedstock (such as glycerin), and energy products (such as propane fuel mix and heavy oils). We employed five approaches to address the coproduct issues: (1) the displacement approach; (2) an energy-based allocation approach; (3) a market-valuebased allocation approach; (4) hybrid approach I, which employs both the displacement method (for soy meal and glycerin) and the allocation method (for other energy coproducts); and (5) hybrid approach II, which is exactly like hybrid approach I except that it address soy meal with a market-value-based allocation method. The process of producing soybean-based fuels involves two subsystems (soy oil extraction and fuel production). In this study, the allocation approach considers the two stages as a whole system, and the hybrid approaches address the two stages separately. Figure S1 (where “S” refers to Supporting Information) illustrates the two system levels in detail. With the displacement approach, soybean-based glycerin is assumed to replace petroleum-based glycerin (21, 22). Soy meal, which is primarily used as a livestock feed, is assumed to replace soybeans, of which one use is animal feed. Other energy coproducts are assumed to replace similar energy forms on the basis of their energy value. Table 3 lists the products that are to be displaced by the coproducts and the energy use and GHGs emissions per unit of the displaced 752

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products (21, 23-26). Table 4 presents the allocation ratios for the energy and emission burdens between primary products and coproducts for the four soybean pathways. The energy content and market value of all products involved in this study are given in Table S1.

4. Results and Analysis Figures 2-5 present WTW total energy use, fossil energy use, petroleum energy use, and GHG emissions. Note that these results are based on 1 million Btu of fuel produced and used. Given the fact that fuel consumption by diesel engines could be 15-20% less than consumption by gasoline engines per distance traveled, to compare WTW results on a per-mile basis, researchers could reduce energy use and GHG emissions for the four diesel fuel options. Total Energy Use. With the displacement approach, soybean-based fuels offer 6-25% lower total energy use than petroleum diesel or gasoline per million Btu, except in the case of RD-II, for which WTW total energy increases by 29% relative to conventional diesel. The two allocation approaches show good agreement with each other, with very similar results (1-4% difference). With the two allocation approaches, soybean-based fuels have 13-18% higher total energy use than petroleum diesel or gasoline. Although hybrid approach I for the renewable fuels is the integration of the displacement and allocation approaches, it gives the highest total energy use results. The reason is illustrated in Figure S2. The energy use results of hybrid approach II are lower than those of hybrid approach I, indicating that the marketvalue-based approach could allocate more energy burden to soy meal than would the displacement approach. The rank of the five approaches, which is determined by the feature and amount of the coproducts, is different across the fuels. For instance, the RD-II energy use results for the five allocation approaches are very similar, primarily because RD-II has fewer coproducts and the approaches used to address them thus have a smaller effect on the results. Fossil Energy Use. All soybean-derived fuels offer significant reductions (52-107%) in fossil energy use, which result from the fact that soybeans, as the feedstock for the four renewable fuel options, are a nonfossil feedstock. Soybean-based fuelsseven those with a certain amount of fossil energy input when they are used as process fuels during soybean farming and fuel production processesscan still achieve substantial reductions in fossil energy use. Like the results for total energy use, the results for fossil energy use vary on the basis of the allocation method applied. With the displacement approach, RG can reduce WTW fossil energy use by 107% when compared with petroleum gasoline. The reason for this reduction is that large quantities of coproducts produced with RG were assumed to displace fossil energy (see Table 3), resulting in a large credit in fossil energy savings for RG. Biodiesel, RD-I, and RD-II can achieve WTW fossil energy reductions of 84%, 90%, and 55%, respectively. With the allocation and hybrid approaches, the reduction ratios are around 63-71% and 52-61%, respectively. Petroleum Use. Soybean-derived fuels offer significant oil savings. Petroleum energy used in the soybean-based fuel cycle comes entirely from the WTP stage, primarily from diesel fuel used for farming equipment and for the trucks and locomotives needed to transport feedstock and fuel. For soybean-based fuels, PTW petroleum use is zero. All of the four soybean-derived fuels can save more than 88% of petroleum use. With the displacement approach, for each million Btu of fuel produced and used, RG reduces petroleum use by 148% compared with petroleum gasoline, and soybean-based diesel fuels reduce petroleum use by 99-106% relative to petroleum diesel. Like fossil energy use, the petroleum use associated with RG is low, because RG has

TABLE 3. Energy and GHGs Emissions of the Displaced Products energy and GHG emissions of the displaced products (Btu or g/lb of final fuel) product soy meal glycerin fuel gas heavy oil propane fuel mix product gas LCO CSO

product to be displaced

replacement basis

a

soybeans petroleum-based glycerinc natural gasa residual oila LPGa natural gasa diesel fuela residual oila

b

protein content mass energy value energy value energy value energy value energy value energy value

total d

4735 8405 7593 3960 1251 6768 5599 5993

fossil d

4632 7332 7590 3952 1243 6765 5584 5981

petroleum d

2993 987 30 3766 30 2552 5138 5699

GHGs 524d 587 490 345 92 437 450 523

a The energy use and emissions resulting from production of these products are already simulated in GREET and can be readily used. b The displacement ratio of soy meal to soybeans is determined by protein content. The literature reports a protein content of 44-50% in soybean meal and 35-40% in soybeans (21, 23). This study assumed that soy meal contains 48% protein and soybeans contain 40%, indicating that 1 lb of soy meal can replace 1.2 lb of soybeans. c Petroleum-based glycerin uses propylene, chlorine, and sodium hydroxide as raw materials. The amount of raw material needed to produce one pound of synthetic glycerin was determined on the basis of refs 21, 24 and 25, and the production data for raw material were taken from the Eco-Profile life-cycle inventory (26), which reports the amount of petroleum, natural gas, and electricity used as feedstocks and process fuels. GREET was used to generate the upstream energy use and emissions for these fuels. Production of synthetic glycerin requires little energy, so this energy is not addressed in our analysis. d In Btu or g/lb of soy oil.

TABLE 4. Allocation Ratios between Primary Products and Co-Products product or co-product energy-value-based allocation (%) primary fuel coproducts market-value-based allocation (%) primary fuel coproducts hybrid approach I & II: second subsystem (%) primary fuel coproducts hybrid approach II: first subsystem (%) primary fuel coproducts

BD

RD-I

RD-II

RG

42.9 32.2 57.1 67.8

44.7 55.3

24.1 75.9

45.7 39.4 54.3 60.6

47.4 52.6

29.9 70.1

NA NA

63.7 36.3

94.5 5.5

53.1 46.9

42.1 42.1 57.9 57.9

42.1 57.9

42.1 57.9

a large amount of coproducts that are assumed to replace petroleum fuels, providing large petroleum savings credits (see Table 3). With the allocation approaches, petroleum use among the four soybean-based fuels is very similar; all have usage about 88-92% lower than that of conventional petroleum fuels. Unlike the results for total energy use and fossil energy use, WTW petroleum use for hybrid approach I is lower than that for the allocation approach and hybrid approach II for the three renewable fuels, which is because the production process for renewable fuels uses very little petroleum, so petroleum use allocated to the coproducts is very small. On the other hand, farming of soybeanss assigned to be displaced by soy mealsconsumes large amounts of diesel fuel and gasoline and results in lower petroleum use for hybrid approach I because of the petroleum credit from soy meal. GHG Emissions. The calculation of CO2-equivalents is accomplished by using the global warming potentials (GWPs) advocated by the IPCC: 1 for CO2, 25 for CH4, and 298 for N2O (27). When the displacement approach is used, all four soybean-based fuels can achieve a modest to significant reduction in WTW GHG emissions (64-174%) versus petroleum-based fuels. The reason that RD-I and RG can achieve a much larger reduction in GHG emissions (-130% and

-174%) is because they have a significant amount of coproducts and because the production and combustion of the replaced fuels (natural gas, diesel fuel, and residual oil) could release large amounts of GHGs. With the allocation approach, soybean-based fuels achieve a modest reduction in GHG emissions (57-74%). The results from using the hybrid approaches are similar to the results obtained from using the allocation approach. Previous studies reported a 72-80% reduction in WTW GHG emissions for BD (4, 17) and an 84-85% reduction for green diesel (4) when a mass allocation approach was used. These reductions were higher than those in our study, 66-68% for BD and 74% for RD-II, when the two allocation approaches were used. The major reason is that using energyvalue-based and market-value-based approaches can allocate more of the energy and emission burden to the primary product than does the mass-based allocation approach, because soy oil and BD have a higher energy value and market value per pound than soy meal and glycerin, respectively (see Table S1). Hill et al. obtained a reduction ratio of 41% for BD from using a hybrid approach that combined the mass allocation approach for soy meal and the displacement method for glycerin (22); our study obtained a ratio of 100% from using hybrid approach II. This difference is probably caused by the differences in the yield of glycerin in the Hill et al. study (0.08 lb/lb of BD) and in our study (0.213 lb/lb of BD).

5. Discussion The results of the displacement approach are influenced significantly by the extent of the energy intensity and carbon intensity of the products chosen to be displaced. Using displacement for soy meal could introduce uncertainties because soy meal can displace many kinds of fodder and each fodder could have different energy and carbon intensities. Meanwhile, the choice of displaced products is limited by the availability and accuracy of the life-cycle energy and emission data of the products. In this work, soybeans are a good option so far because those data for soybeans are well simulated in the GREET model. When the choice is between the displacement method and the allocation method, the displacement method tends to be chosen if the uncertainties and difficulties associated with it are solved, because it can reflect the energy use and emissions actually saved as a result of the coproducts VOL. 43, NO. 3, 2009 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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FIGURE 2. Well-to-wheels total energy use: 1, displacement; 2, energy-value-based allocation; 3, market-value-based allocation; 4, hybrid I; 5, hybrid II.

FIGURE 3. Well-to-wheels fossil energy use: 1, displacement; 2, energy-value-based allocation; 3, market-value-based allocation; 4, hybrid I; 5, hybrid II. replacing other equivalent products. Nevertheless, the ceptable choice, although the fluctuation of prices could allocation approaches have been more widely used, affect the results. In addition, the allocation method is a because they are less data-intensive and less challenging better choice than the displacement method if the amount than the displacement approach. The energy-value-based of the coproducts is relatively large in comparison to the allocation method is a favorable choice for a system in amount of the primary product, because the displacement which the value of all the primary product and coproducts method could generate distorted results for the primary can be determined on the basis of their energy content, product, as can be seen in the case of RG, the WTW fossil such as the production processes of renewable fuels. If a and petroleum use of which are negative. “nonenergy” coproduct is involved and there are difficulties By integrating the displacement method and the associated with using the displacement approach, the allocation method, hybrid approaches can choose the most market-value-based allocation method could be an acreasonable allocation method for every coproduct. Hybrid 754

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FIGURE 4. Well-to-wheels petroleum energy use: 1, displacement; 2, energy-value-based allocation; 3, market-value-based allocation; 4, hybrid I; 5, hybrid II.

FIGURE 5. Well-to-wheels GHG emissions and emission changes relative to conventional fuels: 1, displacement; 2, energy-value-based allocation; 3, market-value-based allocation; 4, hybrid I; 5, hybrid II. approaches are the most preferable for a complicated comparison system like our study. We introduced two hybrid approaches in order to examine the possible uncertainty associated with the displacement method for soy meal. In terms of GHG emissions, the results of the two hybrid approaches are very close, indicating that the uncertainty associated with using soy meal to displace soybeans would be in an acceptable range. The method used to calculate coproduct credits is a crucial issue in biofuel (e.g., corn-based ethanol) life-cycle assessments that should be carefully addressed. Extensive efforts have been made to identify the most reasonable approach for dealing with the coproducts of biofuel. This study, by demonstrating and evaluating five different allocation ap-

proaches, provides a comprehensive solution for the lifecycle assessment of fuel pathways with multiple coproducts.

Acknowledgments This work was sponsored by DOE’s Office of Energy Efficiency and Renewable Energy. Argonne National Laboratory is a DOE laboratory managed by UChicago Argonne, LLC, under Contract DE-AC02-06CH11357. We are grateful to our DOE sponsor, Linda Bluestein, for her support and input to this study. We also thank Robert McCormick and Caley Johnson of the National Renewable Energy Laboratory for their insights to this study. VOL. 43, NO. 3, 2009 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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Supporting Information Available Data on energy content and market value of primary products and coproducts, analysis of the two system levels of soybeanbased fuels, and analysis of the differences in the results of the allocation approaches. This information is available free of charge via the Internet at http://pubs.acs.org.

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