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Cellulosic Biofuel Potential with Heterogeneous Biomass Suppliers: An Application to Switchgrass-based Ethanol John Miranowski Professor of Economics,

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Presentation on theme: "Cellulosic Biofuel Potential with Heterogeneous Biomass Suppliers: An Application to Switchgrass-based Ethanol John Miranowski Professor of Economics,"— Presentation transcript:

1 Cellulosic Biofuel Potential with Heterogeneous Biomass Suppliers: An Application to Switchgrass-based Ethanol John Miranowski Professor of Economics, Iowa State University with Alicia Rosburg, Assistant Professor, University of Northern Iowa Keri Jacobs, Assistant Professor, Iowa State University

2 Motivation Biofuel expansion U.S. RFS2 – 16 billion gallons of cellulosic biofuel by 2022 Economics of cellulosic biofuel differs from conventional fuel and first-generation biofuel Non-commoditized feedstock Location-specific economic trade-offs

3 Research Objectives 1. Develop a long run cost model of cellulosic biofuel production with local biomass suppliers and biofuel processors. 2. Identify marginal costs and biorefinery scales and locations of meeting biofuel targets (RFS2). 3. Evaluate policy and biofuel costs of meeting RFS2 with location differences in biomass production and processing costs.

4 Features of conceptual model Consider only long run costs prior to capital investment Account for economic tradeoff Economies in processing Diseconomies in feedstock procurement (e.g., transportation) Biomass supplies differ within and between local markets which dictate economies of biofuel processing Breakeven aggregate production is driven by the long run price of crude oil or gasoline

5 Application to switchgrass Biorefinery conversion Biochemical conversion of biomass to ethanol – Kazi et al. (2010) Conversion scale factor Assume processing plant runs at annual capacity Biomass production Potential land available for SG – CRD land use data (USDA) SG production costs and yields – Khanna et al. (2011) Storage and transportation cost assumptions – Rosburg & Miranowski (2011) Marginal opportunity cost of biomass cropland – CRP offers

6 Minimum ATC of SG ethanol by CRD

7 Trends in cost minimizing decisions As aggregate biofuel production expands, MC increases. 1. Processing plant capacity decreases 2. Biomass transportation distance and costs increase 3. Landowner participation rate decreases because Biomass yields decrease Suitable land for SG production decreases Land opportunity costs increase

8 Estimated ethanol supply curve from switchgrass

9 Market conditions to support biofuel production from SG 2016 RFS2 cellulosic biofuel mandate of 4.25 bgy EIA 2012 oil price forecasts for 2022 and 2035: $129 and $145 per barrel Note: Wholesale prices Production (bgy) Gasoline price ($/gallon)5.055.255.465.88 Oil price ($/barrel)147153158171 Gasoline price with tax credit ($/gallon)3.543.743.953.47 Oil price with tax credit ($/barrel)103109114127

10 Conclusions Local production environments play an important role in aggregate cost of cellulosic biofuel production. Biofuel production costs vary significantly across locations. Given SG land use assumptions, the cost of satisfying 2016 cellulosic biofuel mandate (4.25 bgy) is $5.25/gge.

11 Thank you! Comments or questions?

12 Extra slides

13 Empirical approach 1. Establish least-cost SG biofuel supply for each CRD and market supply curve based on aggregation of CRD least cost biofuel supplies. 2. Determine aggregate MC, along with biorefinery scales and locations, to meet RFS2 production goals.

14 Spatial variation in cost-minimizing decisions Heterogeneity between and within local biomass markets creates significant variation in the cost-minimizing decisions % of Total Production All biorefineries Average523518.63.73 Range9 – 11722 – 514 – 583.19 – 4.57 Top 25% of biorefineries8631123.3841% Bottom 25% of biorefineries3138314.1715%

15 Supply curve sensitivity Switchgrass YieldAvailable biomass cropland

16 Supply curve sensitivity Variable transportation cost Economies of scale

17 Supply curve sensitivity Alternative transportation models


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