Industrial Engineering ResearchGroup

Economic, social and environmental optimization of a forest biomass supply chain

Claudia Cambero, PhD Student

Dr. Taraneh Sowlati

April 16, 2013

2

VCO project Project Title: Economic, social and environmental optimization of forest biomass value chain in British

Columbia, Canada.

Project Start Date: January 2013 Estimated Completion Date: March 2015

Name of Principal Investigator:

Taraneh Sowlati

Institution:

University of British Columbia

Names of Co-Investigators:

Robert Kozak

Institution:

University of British Columbia

Names of Collaborators:

Jean Favreau, Denis Cormier, Jennifer O’Connor,

Mihai Pavel, Dominik Roser

Institution:

FPInnovations

Network Theme:

T3-F1 : VCO Network Research Theme 3-Integrated and collaborative planning; Focus area 1-Integrated

value chain planning. Support to themes T1-F2 and T2-F3

HQP (Ph.D., Master’s, PDF, Internship):

Ph.D.

Student name:

Claudia Cambero

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• “Forest products industry at a crossroads” (CFS, 2012)

• “The Bio-pathways project” (FPAC, 2010)

• Electricity

• Heat

• Transportation fuels

• Bio-chemicals

• Bio-materials

• Integrate the production of traditional and

Innovative products

• Maximize the value from wood fiber cfs.nrcan.gc.ca

Research motivation

The problem…

In order to maximize the value from the wood fiber, we need to:

• Find the best product/technology

• Find the best arrangement of the forest biomass supply chain

• Consider multiple factors:

- Economic

- Social

- Environmental

biv.com

wellonsfei.ca/en/is-biomass-green.aspx

4

Previous studies - assessment 5

Area Description Examples Drawbacks

Economic

feasibility

Estimate total production costs,

cost per unit of energy, net present

value or rate of return of forest

biomass supply chains from

biomass collection/harvesting to the

gate of the plant, or to its

conversion into a final product.

Scenario-based analysis.

• Danon et al. (2012) . Possibilities of

implementation of CHP in the wood industry in

Serbia

• Sarkar et al. (2011). Biofuels and biochemicals

production from forest biomass in Western

Canada

• Ghezzaz & Stuart, (2011). Biomass availability

and process selection for an integrated forest

biorefinery

Considered

single criteria &

did not find the

optimal design

of the value

chain

Environ-

mental

evaluation

Life Cycle emissions, resources

depletion and environmental

impacts of forest biomass supply

chains from biomass

collection/harvesting to its

conversion into a product (cradle-

to-gate) or to its final use (cradle-

to-grave). Scenario based analysis

• Steele et al. (2012). LCA of pyrolysis for bio-oil

production

• Pa et al. (2013). Evaluation of wood pellet

application for residential heating in BC based

on a streamlined LCA

• Tabata & Okuda (2012). LCA of woody

biomass energy utilization: case study in Gifu

Prefecture, Japan

Considered

single criteria &

did not find the

optimal design

of the value

chain

Social

evaluation

Social indicators included in multi

criteria analysis. Most used are

employment and “food-to-energy”

• Krajng & Domac, (2007). How to model

different socio-economic and environmental

aspects of biomass utilisation: Case study in

selected regions in Slovenia and Croatia

• Pavinen et al. (2010). A concept for assessing

sustainability impacts of forestry-wood chains

• den Herder et al. (2012). Sustainability impact

assessment on the production and use of

different wood and fossil fuels employed for

energy production in North Karelia, Finland.

Did not find the

optimal design

of the value

chain

Sustain-

ability

evaluation

Evaluate economic, social and

environmental factors of forest

biomass supply chains from

biomass harvesting/collection to its

conversion into a product or final

use. Scenario-based analysis.

Previous studies - optimization 6

Area Description Examples Drawbacks

Mathematical

programming

Use of LP or MILP models

to minimize cost or

maximize profit of the

supply chain, from biomass

collection/harvesting to the

gate of the plant or to its

conversion and sometimes

distribution.

Typical decisions are plant

location and capacity,

biomass supply area,

selection of technologies,

storage and logistic

decisions.

• Feppaz et al. (2004) Optimizing forest

biomass exploitation for energy supply at

a regional level

• Gunnarson et al. (2004) Supply chain

modelling of forest fuel

• Leduc et al. (2010) Optimal location of

lignocellulosic ethanol refineries in

Sweden

• Feng et al. (2010) Integrated bio-refinery

and forest products supply chain network

design using mathematical programming

approach

• Keirstead et al. (2012) Evaluating

biomass energy strategies for a UK eco-

town with an MILP optimization model

Did not consider

economic, social and

environmental objectives

simultaneously

Multi-

objective

optimization

Integration of economic ,

social and life cycle

environmental impacts for

the design of forest

biomass supply chains.

Typical decisions are

related to technology and

product selection.

• Čuček et al. (2011) Total footprints-based

multi-criteria optimisation of regional

biomass energy supply chains

• You et al. (2012) Life cycle optimization of

biomass-to-liquid supply chains with

distributed-centralized processing

networks

• Santibanez-Aguilar et al. (2011) Optimal

planning of a biomass conversion system

considering economic and environmental

aspects

Did not integrate

decisions on: biomass

types and sources,

preprocessing and

conversion facilities

location, type and size,

and product type,

addressing economic

performance, social and

environmental life cycle

impacts

Develop a model that optimizes economic, social and environmental aspects of a forest biomass supply chain.

Research objective

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• Perform a Life Cycle Assessment of value alternatives for forest biomass utilization in a region

• Optimize the design of the forest biomass value chain considering the economic, social and environmental factors simultaneously

• Apply the model to a case study in BC

Grave

Approach Cradle

Nat

ura

l Res

ou

rces

an

d E

ner

gy

Emis

sio

ns

and

Was

te

washingtondnr.wordpress.com; Microsoft Clip Art; biv.com; paperadvance.com; cfs.nrcan.gc.caz

MODELING FRAMEWORK

Life Cycle Assessment LCA

Environmental evaluation 1

8

Multi Objective Optimization MOO

Supply chain design 2

MODELING FRAMEWORK

Approach

Life Cycle Assessment LCA

Environmental evaluation 1

Biomass procurement

Transportation and Pre-

processing Conversion

Final markets

Enviro

nm

ent

Econ

om

y So

ciety

Economy Max. profit

(NPV)

Society Max. direct jobs (# of new jobs)

Environment Min. GWP

(CO2 equivalents)

9 washingtondnr.wordpress.com; wellonsfei.ca/en/is-biomass-green.aspx; Microsoft Clip Art; biv.com; paperadvance.com; cfs.nrcan.gc.caz

Multi Objective Optimization MOO

Supply chain design 2

MODELING FRAMEWORK

INPUTS • Available biomass, • Potential value alternatives, • Potential location of facilities, • Estimated demand

Approach

Life Cycle Assessment LCA

Environmental evaluation 1

OUTPUTS Analysis of trade-offs among economic, social and environmental aspects

Objective 1 $NPV

Ob

ject

ive

2 #

Jo

bs Pareto

optimal

10

Source: http://www.for.gov.bc.ca/hts/tsa/tsa29/map.gif

Case study: Williams Lake TSA

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Interior BC One of the largest TSA in BC

Largely affected by MPB 4.9 million hectares

AAC: 5.7 million cubic meters

Source: http://www.for.gov.bc.ca/hfp/mountain_pine_beetle/

mid-term-timber-supply-project/Williams%20Lake%20TSA.pdf

Major Centers or Mill Locations

Private Lands or Indian Reserves

Parks, Ecological Reserves

TFL, Community Forests or Woodlots

Timber Harvesting Land Base

Case study: Williams Lake TSA

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• Population: 300 • Lots of biomass • Current sawmill owned by

First Nation (West Chilcotin Forest Products)

• Local electricity by diesel generators

• Interested in bio-energy • Large potential for new

products (e.g. pyrolysis, pellets)

• Population: 100 • Forestry 2nd economic

activity • Current sawmill owned by

First Nation (River West Forest Products)

• 50% of electricity by diesel generators

• Interested in bio-energy and new products (e.g. pellets)

• Population: 12,000 • Forestry 1st economic

activity • Hosts lumber, plywood,

veneer, pellet and chip mills.

• Most efficient bio-power plant in North America

• Limited availability of low cost logging residues

• Interested in district heat • Potential for pellet mill

expansion

Case study: alternatives

Region Potential locations

Technologies Products and Markets

Williams Lake TSA

Anahim Lake

Combined heat and power

• Heat for local supply

• Power for local supply

Pelletization

• Local domestic use

• Export through Bella Coola

• Export through Williams Lake

Pyrolysis • Local supply

• Williams Lake

Hanceville

Combined heat and power

• Heat for local supply

• Power for local supply

Pelletization • Export through Williams Lake

Williams Lake

District heating • Local heat supply Pelletization • Export

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The model

Objective function: max NPV; max created jobs; min GWP

Subject to: • Residues availability • Capacity (conversion) • Demand • Flow constraints (conversion) • Logic constraints (conversion)

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Continuous variables

Set of potential technologies

K

Set of biomass sources

I

Set of potential markets

M

Supply chain configuration Set of potential plant locations

J

Set of potential products

L

Anahim production Hanceville production

Williams Lake production

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Binary variables

Aggregated cutting blocks (2000)

Hanceville

Bella Coola

Anahim

Hanceville

Pelletization

Williams Lake

District Heating

Williams Lake

Anahim

Pyrolysis

CHP Heat

High quality pellets

Power

Pyrolysis bio-oil

Low quality pellets

CHP

Project progress

16

Year Milestones/Deliverable Expected

Delivery Date 2013

• Review of the literature on studies relevant to optimization,

LCA, and multi-objective optimization of forest biomass supply

chain. Write a review paper.

• Identification and characterization of the case study in

collaboration with FPInnovations

March 2013

June 2013

2014

2014

• Development of the Life Cycle Assessment (LCA) model:

1. Model development

2. Verification and validation

3. Analysis of results and identification of major findings

4. Sensitivity analysis

5. Write a paper

• Development of Multi Objective Optimization (MOO) model:

1. Model development and solution

2. Verification and validation

3. Analysis of results and identification of major findings

4. Sensitivity analysis

5. Write a paper

March 2014

Dec. 2014

2015 Final report to VCO March 2015

Next steps

• Gather data/ information

• Develop the LCA model

• Develop the MOO model

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18

Acknowledgements

Dr. Taraneh Sowlati taraneh.sowlati@ubc.ca Claudia Cambero cambero.claudia@gmail.com

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Questions?

References

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• Canadian Forest Service CFS. (2012). Industry: a sector in transition. Retrieved October/12, 2012, from http://cfs.nrcan.gc.ca

• Čuček, L., Varbanov, P. S., Klemeš, J. J., & Kravanja, Z. (2012). Total footprints-based multi-criteria optimisation of regional biomass energy supply chains. Energy, 44(1), 135-145.

• Danon, G., Furtula, M., & Mandić, (2012) M. Possibilities of implementation of CHP (combined heat and power) in the wood industry in Serbia. Energy, (0)

• den Herder, M., Kolström, M., Lindner, M., Suominen, T., Tuomasjukka, D., & Pekkanen, M. (2012). Sustainability impact assessment on the production and use of different wood and fossil fuels employed for energy production in North Karelia, Finland. Energies, 5(11), 4870-4891.

• Feng, Y., D'Amours, S., LeBel, L., & Nourelfath, M. (2010). Integrated bio-refinery and forest products supply chain network design using mathematical programming approach. ( No. 50). Montreal: CIRRELT .

• FPAC. (2010). Transforming Canada's forest products industry: Summary of findings from the future bio-pathways project. ( No. 1).Forest Products Association of Canada. Retrieved February 14, 2013 from http://www.fpac.ca/index.php/en/value-pathways/

• Freppaz, D., Minciardi, R., Robba, M., Rovatti, M., Sacile, R., & Taramasso, A. (2004). Optimizing forest biomass exploitation for energy supply at a regional level. Biomass and Bioenergy, 26(1), 15-25.

• Ghezzaz, Hakim & Stuart. Paul (2011). Biomass availability and process selection for an integrated forest biorefinery. Pulp & Paper Canada, 112(3), 19-26.

• Gunnarsson, H., Ronnqvist, M., & Lundgren, J. (2004). Supply chain modeling of forest fuel. European Journal of Operational Research, 158(1), 103-123.

• Keirstead, J., Samsatli, N., Pantaleo, A. M., & Shah, N. (2012). Evaluating biomass energy strategies for a UK eco-town with an MILP optimization model. Biomass and Bioenergy, 39(0), 306-316.

References

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• Krajnc, N., & Domac, J. (2007). How to model different socio-economic and environmental aspects of biomass utilisation: Case study in selected regions in Slovenia and Croatia. Energy Policy, 35(12), 6010-6020.

• Leduc, S., Starfelt, F., Dotzauer, E., Kindermann, G., McCallum, I., Obersteiner, M., & Lundgren, J. (2010). Optimal location of lignocellulosic ethanol refineries with polygeneration in Sweden. Energy, 35(6), 2709-2716.

• Pa et al. (2013). Evaluation of wood pellet application for residential heating in BC based on a streamlined life cycle analysis. Biomass and Bioenergy, 49, 109-122

• Päivinen, R., Lindner, M., Rosén, K., & Lexer, M. J. (2012). A concept for assessing sustainability impacts of forestry-wood chains. European Journal of Forest Research, 131(1), 7-19.

• Santibanez-Aguilar, J. E., Gonzalez-Campos, J. B., Ponce-Ortega, J. M., Serna-Gonzalez, M., & El-Halwagi, M. M. (2011). Optimal planning of a biomass conversion system considering economic and environmental aspects. Industrial & Engineering Chemistry Research, 50(14), 8558-8570.

• Sarkar, S., Kumar, A., & Sultana, A. (2011). Biofuels and biochemicals production from forest biomass in western Canada. Energy, 36(10), 6251-6262.

• Steele, P., Puettmann, M.E., Kanthi, V., & Cooper, J. E. (2012). Life-cycle assessment of pyrolysis for bio-oil production. Forest Products Journal, 62 (4), 326-334.

• Tabata, T., & Okuda, T. (2012). Life cycle assessment of woody biomass energy utilization: Case study in Gifu prefecture, Japan. Energy, 45(1), 944-951.

• You, F., & Wang, B. (2011). Life cycle optimization of biomass-to-liquid supply chains with distributed–centralized processing networks. Industrial & Engineering Chemistry Research, 50(17), 10102-10127.