Biomass Potential of Tree Species for Biofuel Production in Southeast

Queensland

Patrick Mason and Doug George

School of Agriculture and Food Sciences, University of Queensland, Gatton, Queensland, Australia 4343

Abstract. Eight Eucalypt and one Casuarina species were planted in April 2013 in South-East Queensland

and evaluated in March and June 2014 for tree volume production, as a measure of potential biomass for

biofuel production. Trees were evaluated for stem diameter and height to enable calculation of volume. E.

grandis (DAFF) showed the highest volume accumulation in June 2014. Gompertz growth equations were

used to predict long-term (10 years) volume potential. Both the E. grandis accessions performed best; other

species that plateaued earlier may be best coppiced sooner to increase biofuel production over time.

However, predictions need to be treated cautiously in view of the assumptions made and potential for the

adverse environments to affect growth.

Keywords: Biofuel, Biomass, Eucalypts, Casuarina.

1. Introduction

Australia relies heavily on fossil fuels in order to provide combustible molecules to yield energy for a

number of processes (Shepherd 2011) [1]. Due to the finite nature of fossil fuels, it can be expected that

depletion of this resource is a certainty in the near future. Additionally, the combustion of hydrocarbons

yields gaseous carbon molecules, which have been implicated as one of the primary causes of global

warming (Fenning et al. 2008) [2]. Owing to these realities, a number of technologies are currently being

developed as viable alternatives to fossil fuel extraction (Shepherd 2011) [1].

One such technology of great promise is the production of biofuels derived from plant material. Biofuels

created from cereal, sugar, and oil seeds are known as first generation biofuels, as they were the first types of

biofuel produced, and have been used in various processes for over 100 years (Demirbas 2009) [3]. First

generation biofuels are produced by the process of fermentation of sugars and starch into ethanol and, for oil

seeds, the extracted oil can essentially be used directly or synthesized into compounds that are similar to

diesel (Naik 2010) [4].

Despite the promise that first-generation biofuel production holds, there are major issues impeding

development and inhibiting them from becoming a comprehensive replacement for fossil fuels. One such

problem is the emergence of the food vs. fuel debate; which has arisen due to the uncertainty surrounding the

possible impact of using feed/food crops on food availability and prices (Chen 2013) [5]. In the analysis by

Sims et al. (2010) [6] of new and existing biofuel technologies, they indicate that many authorities agree that

specific first generation biofuels are responsible for past increases in commodity prices within many

countries.

In addition to the issues regarding the possibility of increased food costs, and likely shortages as a result

of first generation biofuel production, there are other matters limiting their future:

The requirement of government subsidies to combat high production and processing costs in order to

compete with petroleum products (Chen 2013) [5]

Corresponding author. Tel.: + 61 7 5460 1308; fax: +61 7 5460 1324.

E-mail address: d.george@uq.edu.au.

2015 2nd International Conference on Geological and Civil Engineering

IPCBEE vol. 80(2015) © (2015) IACSIT Press, Singapore

DOI: 10.7763/IPCBEE. 2015. V80. 15

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Widely varying assessments of net greenhouse reductions once land-use change is taken into account

(OECD 2008) [7]

According to sustainability studies done by the sustainable biofuels consensus, ethanol produced by

sugar cane is the only first generation biofuel process that meets current sustainability criteria; in reference to

greenhouse emissions, energy expenditure ratios and monetary costs (GBEP 2008) [8]

Requires the same land type as crops used for food, animal and fibre production (Searchinger

2008)[9].

The concern surrounding first generation biofuels has stimulated interest in the development of 2nd

generation biofuel technologies produced from non-food biomass (Shepherd 2011) [1]. The biomass used

within 2nd

generation technologies are collectively called ligno-cellulosic feedstocks (Sims et al. 2010) [6].

Lignocellulose consists predominantly of cellulose (35- 50%), hemicellulose (20- 35%), and lignin (5- 30%)

(Zavrel 2009) [10].

Ligno-cellulosic materials derived directly from plants present far higher yields than those produced

from sugar, oils and starch used in the production of first generation biofuels (Fenning et al. 2008) [2]. Such

ligno-cellulosic feedstock materials include by-products from agricultural/forestry processes (cereal, straw,

sugar cane bagasse, forest residues), wastes (organic solid municipal wastes), and other feedstocks (short

rotation tree crops, high biomass yielding grass species). Of all the aforementioned feedstocks, one of the

most promising is an intensive short-rotation tree crop system (Gonzalez et al. 2011) [11]. Tree crops can

produce significant amounts of ligno-cellulose without incurring the cost of intensive inputs, or the use of

valuable farmland. Within Australia, various Eucalypt species have been identified as possible short rotation

tree crops for use in bio-ethanol production (Shepherd 2011) [1].

The aim of this trial was to study the ability of a number of Eucalypt species and a Casuarina species to

produce biomass (determined by tree volume) suited to the Lockyer Valley environment in South-east

Queensland, Australia.

2. Materials and Methods

2.1. Treatments

Eucalypts

Hybrid Corymbia variety: cross between Corymbia torelliana and Corymbia citriodora. 2 genotypes

have been isolated from this cross, cloned and named as Corymbia clones 11 and 39. Sourced from Clonal

Solutions Pty Ltd. (North Queensland)

Eucalyptus grandis: 2 accessions sourced from the Department of Agriculture, Forestry and

Fisheries Queensland and Department of Primary Industries, NSW.

Eucalyptus dunnii

Corymbia citriodora subsp. variegata

Corymbia haemastoma sm.: sourced from the local area (Lockyer Valley)

Eucalyptus moluccana

Casuarina

Casuarina cunninghamiana

2.2. Locale

The trial was located at the Horticultural fields (GPS co-ordinates S27.541, E152.335) at the Gatton

Campus of the University of Queensland. The soil is classed as a black vertosol and is considered as highly

productive horticultural land. The climate is humid, sub-tropical with average rainfall of 880 mm annually

and minimum and maximum temperatures of 13.8°C and 26.4°C respectively.

2.3. Trial design and Plot Size

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The trial consisted of 9 tree species with 4 replications in a complete randomised block design. Plots

consisted of single rows 15 m long and 4 m wide with trees spaced 1 m apart in the row.

2.4. Culture

Seed of all species except Clones 11 and 39 and Casuarina cunninghamiana was planted in the UQ

Gatton Nursery in January 2013. Seedlings were transplanted in the field on beds covered with plastic mulch

in April 2013 together with the clonal material and C. cunninghamiana. Seedlings were irrigated as needed

at the rate of 6-8 litres per hour for 2 hours per day by drippers placed underneath the mulch.

2.5. Data Collection

Through the use of a flexible tape, tree stem diameter (0.4 m height) was measured. Methodology can be

ascertained from Queensland Department of Forestry website (Agroforestry 1999) [12]. Tree height was

measured using a tape measure and an optical reading clinometer. Measurements on 5 trees/plot were made

in March and June 2014. Tree volume was calculated using the diameter measurement at 0.4m (stump

height), and tree height. Through the use of a simple conical calculation an accurate estimate of the Live

Tree Volume can be obtained (Agroforestry 1999) [12].

Conical formula:

2

0.5

3

x Diameterat stumpheight x x Heightof treeTree Volume

The Gompertz growth equation was chosen to as the most appropriate growth curve equation due to the

simplicity of application and its ability to create a relatively accurate sigmoidal curve for biological growth.

As the optimal age in eucalypts for coppicing is 9 years, the predicted growth of all tree species was

calculated. As the growth prediction is such a long-term value, the growth of each tree species at 1 year of

growth was also calculated to ensure accuracy.

The Gompertz growth equation is as follows:

0

rty y e

Where r= rate of growth, y0=initial measurement, t=time and e=exponential

This equation was transposed so as to be relevant to the data collected

Where y=observed volume, A=maximum tree volume, B=intercept, C=Slope, t=Time and

exp=exponential function

The maximum tree volume used in this equation was derived from the various references (below), which

describe average maximum height and stem diameter. The ‘A’ value was calculated using the conical

formula.

Maximum tree value

Corymbia hybrids: 50 m tall and 2.0 m stem diameter (McMahon 2010) [13]: Volume=52.3599 m3

Eucalyptus grandis: 55 m tall and 2.0 m stem diameter (Boland 2006) [14]: Volume=57.596 m3

Eucalyptus dunnii: 50 m tall and 1.7 m stem diameter (Boland 2006) [14]: Volume=37.83 m3

Corymbia citriodora subsp. variegata: 40 m tall and 1.3m stem diameter (McMahon 2010) [13]:

Volume=17.698 m3

Corymbia haemastoma sm.: 35 m tall and 1.5 m stem diameter (McMahon 2010) [13]:

Volume=20.617 m3

Eucalyptus moluccana: 25 m tall and 1 m stem diameter (CQFA 2012) [15]: Volume=6.545 m3

Casuarina cunninghamiana: 25 m tall and 1 m stem diameter (Boxshall 2011) [16]: Volume=6.545

m3

exp exp

Ay

B Ct

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3. Results and Discussion

A one-way analysis of variance was conducted to measure the influence of tree species on average

volume at 14 months of age. Results showed there was a significant difference in volumetric growth rates

between species (Fig. 1). In June 2014, DAFF E. grandis showed the highest mean of 0.08, followed by E.

dunnii 0.051. Corymbia haemastoma displayed a much larger increase over the measurement period than

other species; if this continues, this may indicate potential for higher production long term. E. moluccana had

the lowest value of 0.006.

Fig. 1. Volume accumulation of tree species between April 2013 (time of planting) and June 2014.

Fig. 2. Volume growth curve for 10 years of growth, calculated using the Gompertz growth equation.

Biomass accumulation predicted by the Gompertz growth formula for a 10-year period (Fig. 2) indicated

that DAFF sourced E. grandis to have the largest volume accumulation over the 10-year period (55.94 m3).

This was followed by the NSW sourced E. grandis (54.39 m3) with Corymbia clones 39 (49.1 m

3) and 11

(48.5 m3) next highest. The lowest predicted accumulators of volume were Casuarina cunninghamiana (6.40

m3) and E. moluccana (5.28 m

3).

Long-term growth curves tended to relate closely to the size of maximum allocated value and this may

limit the reliability of the prediction curves. This was clear in tree types of the same species which were

found to have considerably different growth rates in their first 12 months of growth (Fig. 1). For example, at

the end of the 10 year growth curve, the Corymbia hybrids (clones 11 and 39) displayed similar biomass

accumulations, due to the allocation of the same asymptote.

Predictions derived from use of the Gompertz growth curve must be treated cautiously, not only due to

the limitation of the use of maximum values, which would be affected by environmental conditions at the

location where measured, but also the result of various other factors such as climatic change, climatic

extremes, seasonal variation, predation, pathogenesis, and changes in soil solution (Zeide 1993; Petrauskas

2007) [17], [18]. Despite the plethora of issues surrounding the prediction of tree volume, there is a major

advantage to using this robust growth curve calculation, as it illustrates likely physiological differences and

limitations among each species. For example an E. grandis stand (average max height of 55m) will most

likely have more accumulated volume than say Casuarina cunninghamiana (average maximum height 30m)

due to their physical differences (Boland 2006)[14]. 75

The use of sigmoidal growth functions; even with limited available data, can display likely differences in

growth between different species. Thus coppicing rotations can be changed in accordance with attainment of

maximum tree volumes. This will ensure the logarithmic growth rates are maximized, and the decay period

at the end of growth is minimized. In future research of lingo-cellulosic feedstocks in the Lockyer Valley,

further study needs to be undertaken in order to calculate asymptotes based on a wider range of

environmental conditions, if growth models are used.

4. Acknowledgements

We thank Mr Alan Lisle for statistical analysis of data and Dr David Lee (DAFF and University of

Sunshine Coast) for assistance in species selection. QAAFI and the Queensland State Government provided

funding.

5. References

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