Woody Feedstock Production for Bioenergy & Environmental - - PowerPoint PPT Presentation

Woody Feedstock Production for Bioenergy & Environmental Sustainability in the North Central United States

Ronald S. Zalesny Jr.

Team Leader, Research Plant Geneticist Genetics & Energy Crop Production Unit

Forest Service, United States Department of Agriculture Northern Research Station Institute for Applied Ecosystem Studies Rhinelander, WI 54501

Northern Research Station

Research Themes: 1) Forest Disturbance Processes 2) Providing Clean Air & Water 3) Sustaining Forests 4) Urban Natural Resource Stewardship 5) Natural Resources Inventory & Monitoring Genetics & Energy Crops Landscape Ecology Physiology

Genetics & Energy Crop Production Unit

Our objective is to use the link between energy, climate, & tree genetics to: 1) develop fast-growing tree crops as energy feedstocks; 2) develop sustainable forest biomass removal strategies; 3) understand climate change effects on natural & plantation forests; 4) fill critical knowledge gaps in 1), 2), & 3).

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Short rotation woody crops for fiber, energy, & phytotechnologies

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Ecological sustainability of using forest residues for energy

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Carbon sequestration & climate change adaptation of conifers

Energy

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Biofuels

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Bioenergy

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Bioproducts

Renewable Fuel Standard

Energy Independence & Security Act of 2007

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Annual production of 36 billion gallons of biofuels by 2022

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Ethanol production from corn capped at 15 billion gal yr-1

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Remaining 21 billion gallons from advanced biofuels

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16 billion gallons from cellulosic biofuels

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Seven-fold increase in current biomass production from 190 million dry tons to 1.36 billion dry tons

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DOE / USDA goal of replacing 30% petroleum consumption with biofuels by 2030

Perlack, R.D. 2005. Biomass as feedstock for a bioenergy and bioproducts industry: the technical feasibility of a billion-ton annual supply. DOE-USDA. DOE/GO-102995-2135. ORNL/TM-2005/66

Year

2008 2010 2012 2014 2016 2018 2020 2022

Biofuels Production (billion gallons)

5 10 15 20 25 30 35 40 Total Cellulosic Corn 36 16 15

Source: Renewable Fuels Association. http:// www.ethanolrfa.org/resource/standard

Energy

Forest bioenergy & bioproducts supply chain

15-Year-Old Poplar

Arlington (1995)

Hybrid Aspen

Ames

Hall, R.B. 2008. Woody bioenergy systems in the United States. NRS-GTR-P-31.

‘Crandon’ (P. alba × P. grandidentata)

* Discovered in 1950’s * 10.3 Mg ha-1 yr-1 at 6 yrs * 24.0 Mg ha-1 hr-1 at 10 yrs

32 Hybrids

* 17 to 26 Mg ha-1 yr-1 at 11 yrs * 190,000 to 300,000 sprouts ha-1

Why Poplars?

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Broad economic & environmental benefits

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Well-studied (silviculture, physiology, & genetics)

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Base populations exhibit tremendous diversity

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Grown on marginal lands not suitable for agriculture

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Very productive

Age of plantation (yrs)

2 4 6 8 10 12

Productivity (dt ac-1)

1 2 3 4 5 6 7

13.5 Mg ha-1

Why Poplars?

Realized Productivity Switchgrass 20 Mg ha-1 yr-1 Willow 18 Mg ha-1 yr-1 Poplar 16 Mg ha-1 yr-1

Depends on genotype × environment interactions

Potential Productivity

>22 Mg ha-1 yr-1

Additional Advantages

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Energy per biomass unit: 1.9×1010 to 2.0×1010 J Mg-1 (16.5 to 17.2 MBtu dt-1)

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Energy returned on energy invested (EROEI)

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Can be stored on the stump until harvest

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Harvest throughout the year

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Minimal fertilization

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Extended haul distances

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Used in crop rotations to improve soil tilth

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Elevated rates of soil carbon storage

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Superior genotypes replace existing clones

Cellulose 2 to 55 Willow 13 Poplar 12 Sugar Cane 8 Switchgrass 5.4 Soybean 2.5 Corn 1.34

Sources: 1.) http://ngm.nationalgeographic.com/2007/10/biofuels/biofuels-interactive. 2.) Schmer et al. 2008. Net energy of cellulosic ethanol from switchgrass. PNAS 105(2):464-469.

Sustainability

Short rotation woody crops are one of the most sustainable sources of biomass, provided we strategically place them in the landscape & use cultural practices that…

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Conserve soil & water

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Recycle nutrients

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Maintain genetic diversity

Hall, R.B. 2008. Woody bioenergy systems in the United States. NRS-GTR-P-31.

1990 1994 1996 *Uniformity within *Diversity among *4 ha clone-1

Long-Range Goal

Develop a protocol for identifying suitable testing & deployment sites of poplar energy production systems in the Midwest, USA (& beyond…)

Objectives

Zalesny, R.S. Jr., et al. 2012. An approach for siting poplar energy production systems to increase productivity and associated ecosystem services. For Ecol Manage (In press)

1. Identify eligible lands suitable for poplar deployment based on current land use, land ownership, & local soil characteristics 2. Determine temperature-precipitation gradients important to poplar growth 3. Establish sites for field reconnaissance within the suitable lands 4. Assess the validity of the outcomes from 1) & 2) by comparing available databases with field soils data (i.e., QA/QC) 5. Apply a process-based growth model (3-PG) to predict & map poplar productivity within the identified suitable lands 6. Assess the regional sustainability of potential poplar deployment within the eligible lands (current studies)

Objectives

Zalesny, R.S. Jr., et al. 2012. An approach for siting poplar energy production systems to increase productivity and associated ecosystem services. For Ecol Manage (In press)

1. Identify eligible lands suitable for poplar deployment based on current land use, land ownership, & local soil characteristics 2. Determine temperature-precipitation gradients important to poplar growth 3. Establish sites for field reconnaissance within the suitable lands 4. Assess the validity of the outcomes from 1) & 2) by comparing available databases with field soils data (i.e., QA/QC) 5. Apply a process-based growth model (3-PG) to predict & map poplar productivity within the identified suitable lands 6. Assess the regional sustainability of potential poplar deployment within the eligible lands (current studies)

Map Development

Constraints Considered

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Land cover class

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Land ownership

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Available water storage capacity

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Water deficit (P – PET)

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Soil texture

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Precipitation / temperature

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Flood frequency

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Depth to bedrock

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Patch size

Zalesny, R.S. Jr., et al. 2012. An approach for siting poplar energy production systems to increase productivity and associated ecosystem services. For Ecol Manage (In press)

Map Development

Final Constraints

CONSTRAINTS DEFINITION OF CONSTRAINTS USED National Land Cover Dataset (NLCD 2001) Grassland/Herbaceous, Pasture Hay, Cultivated Crops GAP Stewardship 2008 (Land Ownership) Federal, Tribal, State, County (excluded) Available Water Storage Capacity (SSURGO) ≥7 cm (assuming 0 to 50 cm depth, 0.15 fraction available water) Precipitation – Potential Evapotranspiration (PPET) PPET for the months of April and May combined Soil Texture (SSURGO) Clay Loam, Coarse Sandy Loam, Coarse Silty, Fine Sandy Loam, Gravelly Loam, Gravelly Sandy Loam, Loam, Loamy Coarse Sand, Loamy Sand, Mixed, Sandy Clay Loam, Sandy Loam, Sandy Over Loam, Silt Loam, Silty, Silty Clay Loam, Very Fine Sandy Loam

Eligible Lands

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373,630 ha MN = 249,990 ha

WI = 123,641 ha

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30.8% of study area

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Land cover 79.1% cultivated crops

17.8% pasture/hay 3.1% grassland

Field Reconnaissance

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143 sites MN = 84

WI = 59

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Most slopes 5% or less

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Acceptable drainage

MN = 70%

WI = 98%

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Acceptable erosion MN = 81%

WI = 85%

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Negligible stoniness

MN WI Corn 19% 49% Alfalfa 8% 17% Soybean 13% 19% Poplar 40% 8% Other 20% 7%

Poplar Productivity Within Eligible Lands

Zalesny, R.S. Jr., et al. 2012. An approach for siting poplar energy production systems to increase productivity and associated ecosystem services. For Ecol Manage (In press)

Poplar Productivity Within Eligible Lands

Zalesny, R.S. Jr., et al. 2012. An approach for siting poplar energy production systems to increase productivity and associated ecosystem services. For Ecol Manage (In press)

Poplar Productivity Within Eligible Lands

Zalesny, R.S. Jr., et al. 2012. An approach for siting poplar energy production systems to increase productivity and associated ecosystem services. For Ecol Manage (In press)

Integrated Studies: Regional Sustainability

Enterprise Budgets Landowner Preferences

Bemidji Warren Ulen Granite Falls Milaca Belgrade Lamberton Fairmont Mondovi Lancaster Rhinelander Escanaba Arlington Ames Waseca

Poplar Carbon Study Field Locations

10-yr-old plantations (×4)

Design: 10 clones × 4 trees/clone = 40 trees/site Clones: C916000, C916400, C918001, DN34 (aka Eugenei), NC13563, NC13624, NC13649, NC14018, NM2, NM6

20-yr-old plantations (×11)

Design: 2 clones × 4 trees/clone = 8 trees/site Clones: DN34 (aka Eugenei); DN182 (aka Raverdeau)

Key: Coppice plantations (×2)

Design: 1 clone × 4 trees/clone = 4 trees/site Clone: Crandon

Sutherland Kanawha

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Soil carbon sequestration & greenhouse gas emissions

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Aboveground carbon stocks

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Biochemical conversion to liquid fuels

Integrated Studies: Regional Sustainability

Enterprise Budgets Landowner Preferences Carbon Implications

Integrated Studies: Regional Sustainability

Enterprise Budgets Landowner Preferences Carbon Implications Productivity Modeling

Headlee, W.L., Zalesny, R.S. Jr., Donner, D.M., Hall, R.B. Using a process-based model (3-PG) to predict & map hybrid poplar biomass productivity in Minnesota & Wisconsin, USA. (manuscript accepted with revisions on 5/31/12; revised manuscript submitted on 6/26/12).

SUSTAINABILITY

Provisioning Services Regulating Services Cultural Services Supporting Services

Ecosystem Services & Pillars of Sustainability

Thank you!

Acknowledgements I thank Dr. Gary Kling and the Congress’ organizing committee for the invitation to speak today.

Contact Information

• Dr. Ronald S. Zalesny Jr.

Team Leader, Genetics and Energy Crop Production Research Plant Geneticist U.S. Forest Service Northern Research Station Institute for Applied Ecosystem Studies 5985 Highway K Rhinelander, WI 54501, USA Phone: +1 715 362 1132 Cell: +1 715 490 1997 Fax: +1 715 362 1166 rzalesny@fs.fed.us http://www.nrs.fs.fed.us/people/Zalesny http://www.nrs.fs.fed.us/units/iaes/focus/energy_climate_genetics/

Contribution of Poplar Biomass?

Zalesny, R.S. Jr., et al. 2012. An approach for siting poplar energy production systems to increase productivity and associated ecosystem services. For Ecol Manage (In press)

Table 5 Total standing aboveground dry biomass (Tg) of natural forests on private lands in Minnesota and Wisconsin, USA (2007 to 2011; DBH > 2.54 cm) (data from Woudenberg et al., 2011) (A.) and potential of poplar on suitable lands at the end of a 10-year rotation as predicted using three yield scenarios with 3-PG (B.). (A.) Tree Species Group Minnesota Wisconsin Minnesota + Wisconsin Cottonwood and Aspen 44.0 33.4 77.5 Noncommercial Hardwoods 3.0 4.8 7.9 Commercial Hardwoodsa 130.7 295.5 426.2 Softwoodsb 34.4 68.1 102.5 Total 212.2 401.8 614.0 (B.) Yield Scenarioc Minnesota Wisconsin Minnesota + Wisconsin Generalist (SSURGO) 23.7 12.1 36.2 Specialist (Site) 28.2 14.7 43.3 Specialist (SSURGO) 27.5 14.7 42.6

aCommercial hardwood species include: ash, basswood, beech, black walnut, hard maple, hickory, red

• aks, soft maple, white oaks, and yellow birch (Woudenberg et al., 2011).

bSoftwood species include: balsam fir, eastern hemlock, eastern white and red pines, jack pine, and

spruces (Woudenberg et al., 2011).

cSee Materials and Methods for details about the three yield scenarios tested with 3-PG.

7% of Total Standing Biomass 53% of Cottonwood/Aspen Biomass