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Albert-Ludwigs-Universität Freiburg

U. Flores, D. Jaeger Chair of Forest Operations | Albert-Ludwigs Universität Freiburg

Availability and utilization costs of forest woody biomass for bioenergy in Mexico

49th International Symposium on Forestry Mechanization

04 – 07 September 2016 Warsaw University of Life Sciences

Outline

Forestry and energy generation in Mexico

Is there potential availability for energy generation from woody biomass in Mexico?

Technical availability and utilization costs of woody biomass for energetic use in Mexico

What is next?

18.09.2016 Availability and utilization costs of forest woody biomass for bioenergy in Mexico 2



Source: INEGI, 2012

Cloud forest Rain forest

Tropical evergreen forest

Savana Tropical deciduous forest Thorn forest Arid tropical scrub

Boreal forest

Pine-Oak forest Chaparral Mesquite grassland

Desert


Forest yield: 8 m3/ha/year Harvesting productivity:

- 10-15 m3/ha - 50-60 m3/ha (Torres, 2004)


7 6,7 6,4 6,5 7

6,3 5,8 5,6 5,5

5,9 6 5,7

0

1

2

3

4

5

6

7

8

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Millio

n o

f m

3r

Years

National Timber Production (2003-2014)

Source: SEMARNAT, 2014

Bioenergy

18.09.2014 Professur für Forstliche Verfahrenstechnik | Uni Freiburg 5 Source: Secretaría Nacional de Energía, 2013

Table 1.


To develop a methodology for holistically evaluating the feasibility of supplying energy from decentralized bioenergy plants for woody forest biomass in Mexico


Theoretical: Theoretically available biomass for energetic use (m3 and ton).

Technical: Technically available biomass for energetic use (m3 and ton) and technical energy potential (PJ).

Economic: Economic potential of biomass for energetic use ($/m3).

Table 2. Variable sets Variable set one Variable set two Variable set three Variable set four

1. Forest productive area (ha) 1. Terrain Slope (%) 1. Net heating value (kJ/kg) 1. Labor cost from harvesting and extraction ($)

2. Available tree species 2. Soil degradation (%) 2. Energy demand (TJ) 2. Labor cost from machine operation ($)

3. Annual average increment (m3/year) 3. Mechanization level (%) 3. Basic density (ton/m3) 3. Road maintenance and

construction cost ($)

4. Production (m3/year) 4. Transportation cost ($)

5. Round wood production from sawmills (m3/year) 5. Technical support cost ($)


Regional case study:

North: Durango and Chihuahua Central-south: Michoacán, Oaxaca, Puebla, Veracruz, Chiapas,

Guerrero, Jalisco and State of Mexico


1) A spatial approach is carried out with i as the analyzed specie out of a n number of species in a j region

Availability and utilization costs of forest woody biomass for bioenergy in Mexico 9

Table 3. Theoretical available woody biomass from harvesting residues

n=3 i

j Pine Oak Fir

North 590,570 117,273 0

Durango Chihuahua Central-south 379,324 85,855 36,036

Michoacan Oaxaca Puebla Veracruz Chiapas Guerrero Jalisco State of Mexico Total 969,894 203,128 36,036


18.09.2016


2) Equations to account the availability of woody biomass as well as extraction limits equations are developed

Availability and utilization costs of forest woody biomass for bioenergy in Mexico 10


18.09.2016



3) GIS spatial analysis are used to analyze terrain conditions in order to calculate sustainability constraints


Source: qgis.org, 2015





4) Monte Carlo simulations are developed to estimate production cost from utilization and transportation






4) Monte Carlo simulations are developed to estimate production cost from utilization and transportation

5) A biomass energy flow chart is presented for tracing biomass production involving source and end use.





Analyzed sources

Analyzed species

Outcomes

Potentials

Research modules

Availability and appropriateness of

lignocellulose biomass

Forest management for

bioenergy supply Energy output

Theoretical potential Technical potential

Economic potential

Harvesting residues, non-extracted stands residues and sawmill residues

Pine, oak and fir

Theoretical biomass for energetic use (kg)

Technical biomass for energetic use (kg) Technical energy potential (TJ)

Economic potential of biomass for energetic use ($)

Sustainable potential


Numerical modeling is carried out estimating biomass availability according to sustainability constraints. - Slope percentage: It constraints biomass availability according to

forested areas up to 35% slope.

- Soil degradation: Physical and chemical soil degradation represented by compaction and fertility of soil are assessed.

- Mechanization level: It covers a productivity assessment of harvesting operations given equipment, slope percentage at felling site and diameter at breast height (DBH) of the stand to be felled.


Technical availability of woody biomass for energetic use in Mexico

16

Theoretical available biomass residues from harvesting for north and central-south regions by specie

(1993-2013) (m3)


17 Theoretical availability of woody biomass nationally produced by source, specie and region



There is a loss of 602,200 m3 due to the applied sustainability constraints


19

Technical availability of woody biomass constrained by soil degradation,

slope percentage and mechanization level (m3)

Pine Oak Fir Total

Harvesting residues

(m3)

North 374,674 74,401 - 449,075 Central-south 257,080 58,187 24,423 339,689 Total 631,753 132,588 24,423 788,764

Non-extracted stands

(m3)

North 749 1,245 - 1,995 Central-south 810 1,346 846 3,001 Total 1,559 2,591 846 4,996

Sawmill residues (m3)

North 914,119 49,000 - 963,120 Central-south 587,140 35,873 55,618 678,631 Total 1,501,259 84,874 55,618 1,641,750

TOTAL DOMESTIC 2,435,510



Technical availability of woody biomass constrained by soil degradation, slope

percentage and mechanization level (m3)

Pine Oak Fir Total

Harvesting residues (m3) 631,754 132,588 24,423 788,764

NE stands residues (m3) 1,559 2,591 846 4,996

Sawmill residues (m3) 1,501,259 84,874 55,618 1,641,750

Total domestic 2,435,510

Sawmill Imports 3,319,775

TOTAL 5,755,285

Monte Carlo simulation results according to cost for the north region

Cost (MXN/m3)

Harvesting residues

Non-extracted stands

residues Sawmill residues

Min 150.34 196.82 98.47

Max 759.49 852.33 526.10

Mean 445.63

(34.12 USD/m3) 529.71

(40.55 USD/m3) 312.29

(23.91 USD/m3) Standard dev. 106.93 111.06 89.48

Range 609.15 655.50 427.63

Standard error 0.81% 0.69% 0.83% Number of simulations (N) 7,852 8,242 10,784

Monte Carlo simulation results according to cost for the central south region

Cost (MXN/m3)

Harvesting residues

Non-extracted

stands residues Sawmill residues

Min 82.42 109.11 132.51

Max 1,552.94 1,808.46 895.17

Mean 814.68

(62.37 USD/m3) 978.74

(74.94 USD/m3) 582.76

(44.62 USD/m3) Standard dev. 240.07 250.55 163.29

Range 1,470.52 1,699.34 762.65

Standard error 0.67% 0.37% 0.44% Number of simulations (N) 17,232 17,900 15,096

Mean values of analyzed costs for north and central south region



Breakdown of biomass production for energetic use showing residues origin from the 10 analyzed provinces



Biomass energy flow chart for the regional case study based on 10 provinces involving analyzed species and sources


Technical available forest woody biomass for energetic use (ton)

Pine Oak Fir Total

North 628,007 92,239 0 720,246 Central-south 411,529 70,600 30,737 512,866 Sawmill

imports 1,616,730

TOTAL 1,039,536 162,839 30,737 2,849,842


Technical available energy from forest woody biomass (PJ)

Pine Oak Fir Total

North 10.29 1.56 - 11.85

Central-south 6.61 1.14 0.49 8.25

Sawmill imports 25.86

TOTAL 16.90 2.70 0.49 45.96

What is next?

New techniques for forest operations could positively impact extraction limits

Modeling cable yarding technique results in additional 321,881 m3

Increase of managed forest areas within a time frame, are to be addressed using the proposed methodology

Modeling has repercussions on decision making regarding forestry and bioenergy supply chains


Thank you


Ulises Flores Chair of Forest Operations Albert-Ludwigs Universität Freiburg [email protected] +49 761 203 3790

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