Developing an Integrated Logistics Model for Beetle-killed Biomass

The 2nd Northwest Wood-Based Biofuels + Co-Products Conference, May 3-4, 2016, Seattle, WA

Woodam Chung, Hee Han, Nate Anderson

Background

• The ongoing outbreak of the mountain pine beetle has affected over 19 million hectares in the United States

• Beetle-killed wood represents a vast, high-density biomass feedstock resource for bioenergy and bio-based products

• BANR was launched as a USDA NIFA project to explore the use of beetle-killed and other forest biomass as a bioenergy feedstock

1

Background

2

Integrated Logistics Model?

3

The 3 Components

4

Biomass Allometric Equations

Cost Estimating

Models

Logistics Optimization

Component 1: Allometric Equations

5

Live

Dead

6

Live vs. Dead?

Component 1: Allometric Equations

7

Component 1: Allometric Equations

dbh (cm)

0 5 10 15 20 25 30 35 40

Bio

mas

s (k

g)

0

100

200

300

400

500

600

Dead treeLive treeAllometry for live treeAllometry for dead tree

(a) Total aboveground biomass

dbh (cm)

0 5 10 15 20 25 30 35 40B

iom

ass

(kg)

0

30

60

90

120

150

180

(b) Logging Residues

Dead treeLive treeAllometry for live treeAllometry for dead tree

dbh (cm)

0 5 10 15 20 25 30 35 40

Bio

mas

s (k

g)

0

10

20

30

40

50

60

(e) BranchDead treeLive treeAllometry for live treeAllometry for dead tree

dbh (cm)

0 5 10 15 20 25 30 35 40

Bio

mas

s (k

g)

0

10

20

30

40

50

60

(c) TopDead treeLive treeAllometry for live treeAllometry for dead tree

dbh (cm)

0 5 10 15 20 25 30 35 40

Bio

mas

s (k

g)

0

5

10

15

20

25

(d) BarkDead treeLive treeAllometry for live treeAllometry for dead tree

dbh (cm)

0 5 10 15 20 25 30 35 40

Bio

mas

s (k

g)

0

5

10

15

20

25

30

(f) Foliage

Dead treeLive treeAllometry for live treeAllometry for dead tree

Branch

• The amount of logging residues (top + branch + foliage) is significantly different between live and dead trees

Component 2: Harvesting Costs

8

Component 2: Harvesting Costs

9

Component 2: Harvesting Costs

10

Component 2: Harvesting Costs

• Feller-buncher productivity: Standing live > Standing dead > Downed • Live/Dead/Down has no effect on skidder, processor, delimber and loader

11

Cyc

le ti

me

(sec

)

Live only

Dead only

Downedonly

Live/Dead

Mixed w/ Downed

Component 2: Harvesting Costs

• Lop & Scatter vs. Whole-tree Harvesting

12

LS unit

Haul road

Landing

FBDL

LO

SK

Felling/ bunchingProcessing

Skidding

Sorting/ load ing

WT unit

Haul road

Landing

SkiddingFelling/ bunchin

g

Processing*Sorting/ load in

g

WT unit

LS unit

FBSK

LO DL

SK

Skidding

Component 2: Harvesting CostsSystem Machine Utilization

(%)

Machine SystemProductivity (BDT∙SMH -1)

Cost ($∙BDT-1)

Productivity (BDT∙SMH -1)

Cost ($∙BDT-1)

LS

Feller-buncher 60.0 29.29 4.91

19.70 28.27Delimber* 65.0 19.70 5.82Skidder 60.0 25.74 3.53Loader 65.0 26.31 3.01

WT

Feller-buncher 60.0 29.29 4.91

23.28 23.92Delimber* 65.0 23.28 4.93Skidder 60.0 25.07 3.63Loader 65.0 26.31 3.01

*Calculated for two delimbers : System bottle neck

10.0

20.0

30.0

40.0

50.0

60.0

70.0

180 330 480 630 780 930 1,080 1,230 1,380 1,530 1,680 1,830 1,980

LS WT

Syst

em c

ost (

$∙BD

T-1)

Avg. skidding distance (ft)

Study site (660 ft)

Delimber

Skidder

SkidderDelimber

Component 3: Logistics Optimization

• What would be the most cost-efficient biomass feedstock logistics for given residue pile locations?

14

Grinding here?or

Slash forwarding to where?

Component 3: Logistics Optimization

• Two alternative systems for forest residue recovery operation

15

1) In-woods grinding system Grinder cost ↑, Truck cost ↓Grinder move-in cost

2) Slash forwarding system Grinder cost ↓, Truck cost ↑No grinder move-in

Concentration Yard

Component 3: Logistics Optimization

Slash forwarding system

CYPlant

Slash Pile

Node hierarchy on forest roads- Landing: a location that forest residues could be piled- Concentration yard: a location that has access to chip vans- Bioenergy plant: the destination of ground residues for bioenergy production

- Landing: a place that forest residues could be piled- Concentration yard: a place that has access to chip vans- Bioenergy plant: the destination of ground residues for bioenergy production

Component 3: Logistics Optimization

In-woods grinding system

CYPlant

Concentration Yard

Node hierarchy on forest roads

Slash Pile

- Landing: a place that forest residues could be piled- Concentration yard: a place that has access to chip vans- Bioenergy plant: the destination of ground residues for bioenergy production

Component 3: Logistics Optimization

In-woods grinding system

CYPlant

Concentration Yard

Node hierarchy on forest roads

Slash Pile

Component 3: Logistics Optimization

• Mixed Integer Programming (MIP) approach

19

Component 3: Logistics Optimization

• Mixed Integer Programming (MIP) approach

20

Conventional Logistics

Bioenergy plant

Road speed60 mph40 mph15 mph

Forest stands

0 2 41Miles

2 4miles

0 1

Total cost: $240,711 Unit cost: 43.4 $/BDT Con. yard locations: 0 On-site processing locations: 52

3,088 BDT

418 BDT

2,142 BDT

3,506 BDT

2,142 BDT

Grinder’s location

Flow of ground residues

Optimized

Bioenergy plant

Road speed60 mph40 mph15 mph

Forest stands

0 2 41Miles

2 4miles

0 1

Total cost: $162,223 Unit cost: 29.2 $/BDT Con. yard locations: 2 On-site processing locations: 2

1,269 BDT

1,420 BDT

2,142 BDT

817 BDT

1,269 BDT

2,689 BDT

2,142 BDT

3,506 BDT

Grinder’s location

Flow of slash residues

Flow of ground residues

Integration – A Case Study

• Study forest (Colorado State Forest, CO)• Total area: 36,428 acres

23

C o l o r a d o

Integration – A Case Study

• Criteria: Lodgepole pine; Slope < 30%; average skidding distance < 2,000 ft

24

Integration – A Case Study

• Estimated logging residues

25

Integration – A Case Study

• Cost difference between WT and LS (WT – LS)

26

Average cost: $40.1/ BDT (-$4.9 ~ $240.2/ BDT)

Integration – A Case Study

• Optimized Logistics

27

Average cost: 20.5 $∙BDT-1

Concentration yards: 2 On-site processing location: 1

Grinder’s location

Flow of slash residues

Flow of ground residues

0.0

5.0

10.0

15.0

20.0

25.0

30.0

Conventional Optimized

27.4

20.5

(25.2%)

14,336 BDT

16,236 BDT

6,742 BDT

1,900 BDT

1,900 BDT

6,742 BDT

Concluding Remarks

• New allometric equations, new harvesting cost and new logistics optimization approach allow estimation of more realistic beetle-kill biomass supply and costs – addressing the existing uncertainties and knowledge gaps

• ‘Years since dead’ likely affect harvesting costs, timber product mix and therefore project net revenue – will be studied in collaboration with other task teams in BANR

• The logistics model will be further integrated with the downstream supply chain to incorporate facility locations and end-user products for minimum costs and maximum value recovery

28

29

Thank youQuestions?

Acknow ledgement : This project was supported by the Agriculture and Food Research Initiative Competitive Grant no. 2013-68005-21298 from the USDA National Institute of Food and Agriculture.