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Overheads of truck transport in Australia: implications for biomass as feedstock for bio-energy.

1. Introduction

A comprehensive assessment of the potential for biomass harvesting to deliver value as an energy source requires the determination of the efficiency of each step in the value proposition, harvesting, transport, transformation, transport of the new product, waste treatment and nutrient replacement. For example, harvested biomass will generally need to be transported to facilities where transformation (perhaps dehydration or other pre-treatment, combustion or fermentation) can lead to usable energy products. Such efficiency needs to be assessed in terms of the carbon and/or energy delivered as well as the financial cost of achieving each step.

Failure to do so can lead to misconceptions, for example with carbon, about the potential of bioenergy to be carbon neutral (see, e.g. Searchinger et al. 2009). End-to-end assessments are also necessary for other enterprises such as the production and delivery of agricultural products (see, e.g. Ludemann, Howden, and Eckard 2016), but this note deals specifically with the bioenergy issue.

This analysis assesses the cost of truck transportation in Australia and the potential impact on the value of biomass transported for its carbon and/or energy content. Such assessments must be integral to the successful operation of transport companies, but this is an independent assessment based on national road transport statistics and operating costs. The objective is to evaluate the efficiency and cost of truck transport of biomass or embedded carbon and energy as a function of the distance travelled in Australia.

2. Operating costs and transported energy/carbon

Inclusive costs of operating trucks must be well known by companies for which truck transport is a part of their profitable businesses. Yet the author experienced difficulties in obtaining reliable data to assess the potential costs incurred in transporting biomass, for example, from the point of harvesting and/or collection to the site of conversion to usable energy. In part, this relates to the complex of factors that determine the ultimate costs of truck usage for specific tasks under specific circumstances. However, additionally, there appeared to be a reluctance of operators to share such information in a competitive sector. Eventually estimates were made using the online Calculator available from Freight Metrics (FMC) and prepared by A. Brown (see acknowledgements). The value of the FMC is that it attempts to be inclusive of all costs, profit margin, fuel, finance, depreciation, fixed costs, driver, tyres, maintenance and servicing.

Further, to provide realistic estimates of truck loading and distances travelled, the 2014 national statistics on truck usage (ABS 2015a) were used (Table 1). A limitation was that the categories of truck types in this analysis is broad, not allowing for the specific consideration of particular truck types, for example in the 'articulated' category.

In this document the energy content of materials were taken to be those shown in Table 2. The water content ofbiomass was given a nominal value of20%, unless otherwise indicated, and the carbon content of dry matter was taken to be 50% (molecular weight of carbon as a percentage of that of glucose).

This study excludes consideration of the appropriateness of existing road taxes in the context of infrastructure provision, or potential human health imposts of truck exhausts.

To provide a broad context, estimates of inclusive operating costs were made for five truck categories (Table 3) representing a range of truck sizes and using the following assumptions:

* Costs (1) were for newly purchased trucks and would be approximately 20% lower using vehicles purchased second-hand according to the FMC

* Daily operations were based on the national averages (ABS 2015a)asdefined in Table 1; all truck types were assumed to operate for 46 weeks each year; small and large trucks were assumed to operate 5 or 6 days per week respectively

* Current fuel costs were taken to be $1.20 per litre, appropriate at the time of calculation, and prior to the application of the National Diesel Rebate (

* An operating margin of 10% was used

* Depreciation was taken to be 13.3% per annum.

Table 3 shows the estimated total operating costs of the selected truck types and how these costs reflect the various components of the operating budget. They demonstrate how, despite the lower operating cost ofvans, their poor capacity makes them expensive in terms of distance travelled and loading. It is appreciated that these costs can be no more than indicative of actual costs given that they represent broad national averages and will vary according to the assumptions made above and the operational conditions (see TIC 2015). However, they provide a clear indication of the cost relative to the value of the payload they may carry. To briefly explore this limitation, Table 3 shows an alternative estimate of the costs associated with the operation of the Curtain Sider B-Double category. Here, instead of using a daily operating ratio of 41 1/295 km (the national average for articulated trucks; ABS 2015a), we used a feasible alternative assumption (24/600) consistent with the figures in Table 1,that suggest, on average, trucks are loaded to approximately 50% of weight capacity. The latter reflects the failure to meet capacity loading on all trips due to demand, density of commodity transported and/or desirable levels of back-loading. This alternative is more akin to long, intra or interstate haulage and thus possible movement of biomass from collection to transformation. The comparison of the two scenarios shows the cost of operating per kilometre for the longer-range operation is approximately half, and per tonnage, approximately double, than for the shorter-range operation with, in percentage terms, a significant rise in the relative fuel and maintenance costs and concomitant fall in the costs of the financial investment. Thus, on balance the two alternative scenarios of truck use make only a small overall change to the actual costs per kilometre/tonne and in further discussions we will refer only to the initial case. The estimates of kilometre/tonne costs derived from the use of the FMS compare well with estimates of the Bureau of Infrastructure, Transport and Economics (BITRE 2011).

Table 3 shows that for the larger categories, financing of a truck represents roughly a third of the total operating costs, demonstrating the significant magnitude of the investment in operating a truck, particularly of the larger size. Wages for the driver and fixed costs each account for about a quarter of total costs. Fuel costs represent about 10% of total costs. For the rest of this discussion, we will consider only the light rigid and B-double truck types as being representative of smaller and larger truck options likely to be used in the transport of biomass (and many other commodities).

It is accepted that individual transport circumstances will vary from the average and that conditions will change over time and into the future. However, the underlying message is that there are significant costs associated with the application of truck transport and these are assessed in terms of the value of the commodity delivered.

3. Transporting biomass or incorporated carbon

Based on these cost estimates, Figure 1 shows the inclusive cost per unit of biomass transported as a function of the distance travelled for each of the two truck categories. If the cost of interest is that per unit of carbon, it will increase more than twice as rapidly with distance than for biomass, given that carbon is assumed for many forms of undried biomass to be approximately 40% of the biomass by weight. The cost of transport rises rapidly with distance for rigid trucks indicating that, from a financial perspective, this mode of transport is only suitable for short distances and for payloads of significant intrinsic value.

For rigid trucks, the cost for transporting biomass and carbon 500 km, is $672 and $1345 per tonne respectively. For articulated trucks, this comparison is $96 and $192 per tonne respectively.

Thus, if biomass is collected and transported by trucks for the purpose of carbon storage, the distance will by necessity need to be short given that the value of the carbon in biomass is likely to be less than $100 per tonne of carbon (during the operation of the Australian 'carbon tax' the price for 2012-2013 was $84 [tC.sup.-1] and for 2013-2014, $89 [tC.sup.-1]). (2) The price of carbon in the European Union Emissions Trading Scheme at the time of preparing this text was [euro]8.51 [tCO.sub.2e.sup.-1] (approximately $45 [tC.sup.-1] assuming all emissions are C[O.sub.2]). (3) The point at which the cost of transport equals the value of the carbon transported, if taken to be at the arbitrary value of $100 [tC.sup.-1], would be 37 or 260 km for the rigid and articulated truck categories respectively. Of course, other costs in the full value chain would mean these distances would need to be even smaller.

Alternatively, these transport costs can be compared with the value of traded biomass of approximately $4 per tonne for traded sugar cane for crushing, $202 per tonne of traded roundwood and $277 per tonne for traded wheat grain (ABS 2015b). The higher value of some of these commodities justifies the use of truck transport or in combination with rail transport for distances beyond 100 km. Indeed, it is also why trucks are not always used for cane transport. The average transport distance for sugar cane for crushing is less than 20 km. 'Sugarcane cannot be stored and it is expensive to transport low-density biomass and water (cane is ~75% moisture content and 14% sugars). The average cane transport distance is about 12 miles' (McLaren 2009).

A further comparison can be made with the wholesale cost of water (taken to be $2.6 [t.sup.-1] in Melbourne). Clearly, distribution of water via truck transport, except in emergencies, can never compete with much lower costs incurred via pipeline reticulation.

4. Transporting energy

The energy content of biomass is approximately 36 GJ [tC.sup.-1], or 14 GJ per tonne of wet biomass (assuming 20% water). Figure 2 shows the relationship between distance travelled and the cost of energy transported in the biomass for the two truck categories at their respective average loading. If the distance travelled is 500 km, the transport of energy at the operating costs of the trucks costs $37 and $5 GJ (-1) respectively. We can compare these costs with the wholesale value of electricity (taken here to be the annual average of 2014-2015 in the state of Victoria) of $30.35 MWhr (-1) (or $8.43 [GJ.sup.-1]). (4)

Clearly transport by the smaller, rigid trucks can deliver biomass with an energy content at a competitive price of retail electricity at only very small (less than 100 km) distances, even before considering other costs, or what represents an acceptable overhead on the wholesale value. Even for articulated trucks, the overheads would consume 63% of the value of the embodied energy at a distance of 500 km when compared to wholesale energy costs. Further, these are optimistic estimates in that they again ignore the issues of other overheads that would need to be considered in a full evaluation of the value chain.

Of course, such transport costs will apply to other commodities, and Figure 3, shows a comparison of cost versus energy content of other fuels: lignite, thermal coal and petroleum.

Alternatively, we can compare these costs with the value of energy in fuels taking the retail value of petroleum as $1.2 per litre; the wholesale value of electricity in Victoria as before; the traded value of thermal coal in 2014 as per ABS (2015b); and the average energy content of these fuels as in Table 2. Figure 3 also compares the residential cost of gas in energy terms. (5)

Again, smaller rigid truck transport, at all but the shortest distances, would be too costly for transport of all fuels, especially the low energy density lignite. Even for the high-energy density of petroleum, very long distance transport by articulated trucks of say, 1000 km, would consume about 13% of the retail dollar value of the cargo. These comparisons also make it clear why, for thermal coal, transport to a distribution terminal is usually provided by rail, with its much lower per kilometre/mass costs, albeit large infrastructure costs. (6)

Additional overheads would further erode the real value of the biomass in energy terms. For example, an additional overhead in the full value proposition might be the energy required to dry the transported biomass. This is approximately 2.25 GJ [t.sup.-1] of water or 0.45 GJ [t.sub.biomass][.sup.-1] (assuming 20% water content) which is about 3% of the energy transported per tonne. Thus, the transport of wet biomass incurs a penalty in the transport costs and a further penalty if drying the feedstock is required. This is clearly a limitation for the cane sugar for crushing where the water content is about 70%, requiring energy input of 1.5 GJ per tonne of the collected biomass, which is an overhead of 28% of the energy content of the sugarcane delivered. Such overheads may also be significant for other sources of biomass such as harvested algae.

5. Discussion

The analysis made in this note will replicate that made over and over in the transport industry in assessing charge-out rates for the transport of pay-loads. The success of that industry depends on this. Nevertheless, the author found key players in the trucking industry reluctant to provide estimates of per kilometre/tonne costs. Using the FMC provided us with the basis for assessing the potential role of biomass for carbon storage or as an energy source. The analysis is based on the statistical averages for the operation of two categories of trucks under Australian conditions and thus are indicative of real operations.

The key feature of the analysis is the operating costs of the two categories of trucks, light rigid and articulated, estimated to be 1.1 and 0.15 $ [km.sup.-1] [t.sup.-1], respectively. In the first instance this highlights large differences in the operating costs of the smaller versus that larger trucks per unit of mass transported.

The analysis shows that assessing the costs related to road transport in enterprises, such as agriculture or the potential use of biomass as an energy source, requires the balancing of the inclusive cost of the transport with distance and the static intrinsic value of the payload. This leads to a severe restriction on the distance that products can be transported unless their intrinsic value is high enough. In some cases, at least in the absence of alternative modes of transport, this may lead to the non-economic nature of an enterprise.

Given that carbon prices are more likely to be under $100 per tonne, at least for some years yet, and remembering that this is just the price attributable to the transport component of the full-value chain, it appears that the cost of transport will be a significant limitation to the use of harvested biomass if it must be transported to a place of storage. The point at which the cost of transport equals the value of the carbon transported, if taken to be at the arbitrary value of $100 [tC.sup.-1] ($27 [tCO.sub.2.sup.-1]), would be 37 and 260 km for the two truck categories respectively.

The value of biomass in terms of its embedded energy depends on its use (food, fibre and energy). One tonne of biomass is equivalent to about 0.4 tC, depending primarily on its water content, and contains 14 GJ. At the wholesale value of electricity (assuming all the energy is captured as electricity for wholesale), this would be worth $121 [t.sub.biomass.sup.-1] or at the retail value of petroleum, $378 [t.sub.biomass.sup.-1]. Thus, the transport costs using trucks represent a 100% overhead on the value of the energy as electricity when the distance travelled is equal to 90 and 629 km respectively for the two truck categories (or half of the value at 45 or 315 km). Alternatively, the cost of using trucks represents a 100% overhead on the value of the energy retailed at the value of petroleum when the distance travelled is equal to 281 and 1966 km respectively for the two truck categories (i.e. quarter of the value at 70 or 492 km). Thus, losses of the energy value of biomass effectively exclude the use of the smaller trucks unless the processing to useable energy is very close to the biomass sources. Even when using bigger trucks, the loss of the value of at least several per cent of the embedded energy is almost unavoidable within the transport system.

The comparison of such costs for other commodities demonstrates how this severely limits the use of truck transport of lignite or biomass especially if the latter is of high water content such as for sugar cane for crushing. It shows that for thermal coal, it is more usual to use train transport to the site of usage or shipping. For food commodities, truck transport costs are far from insignificant, but compensated for by the higher intrinsic value at the point of sale.

Such comparisons are no more than indicative, given that they only calculate the costs associated with the average operating costs of the trucks and ignore other costs in the full value chain. They also ignore the logistic issues concerning the potential that average distances are not relevant to the needs related to the geographic realities of the location of potential biomass feed stocks and energy processing.

The efficiency with which carbon or energy is transported by trucks, defined as the carbon or energy content of the fuel used compared with that in the transported load, can be estimated for an articulated truck using the average fuel consumption of 444 gC [km.sup.-1] (22.2 MJ [km.sup.-1]), assuming a load of 40.85 t (Table 1) and an energy content depending on the commodity transported. For the relatively high carbon and energy content-fuel, diesel, the fuel efficiency in both carbon and energy terms is about 1% of that transported over a 1000 km. For dry biomass, these figures in carbon and energy terms 2 and 3% respectively. Thus, in contrast to the limits imposed by the cost of transport, the transport of carbon or energy with respect to the fuel usage is very efficient.

When biomass is used as an energy source, such as in the proposed bioenergy with carbon capture process (BECCs; e.g. Chum et al. 2011; IEA 2012), the aim is to produce energy without emissions of carbon dioxide into the atmosphere. Such processes are unlikely to be entirely emissions-neutral, for several reasons, but importantly, the energy delivered at the end of the process is always going to be some fraction of the energy content of the original biomass. Energy will be lost in the harvesting, transport, feedstock preparation, conversion, transport to the site of use, combustion inefficiency, compression and transport to storage.

This analysis is indicative of the kinds of overheads that can lead to non-inclusive assessments of the use of biomass to be misleading. Other limitations to be assessed in an inclusive analysis of the potential of biomass energy include:

* Overheads related to harvesting, conversion to usable fuel, further transportation of that fuel to the point of use and the final inefficiencies of conversion to the desired amenity, for example electricity or liquid fuel. roots and non-reproductive aerial. For example, for all Australian agriculture, annual on-farm energy consumption is close to 1 x [10.sup.17] J [yr.sup.-1] (OCE 2015) or 10% of the energy content of all crop products.

* Biomass is a finite commodity, which humans already utilise. Haberl et al. (2007)suggested that humans already appropriate 24% of all terrestrial net primary production (NPP) for varioususes(seealsoRojstaczer, Sterling, and Moore 2001). This, for example, places in serious doubt the conclusion that 10% of the UK's future energy could come from biomass (CCC 2011). It also questions Chum et al. (2011) conclusion that 'biomass for energy by 2050 could be in the range of 100-300 EJ',orthe International Energy Agency Bioenergy Strategic Plan (IEA 2012)thatclaimsthatby 2050, bioenergy might account annually for the production of 250 EJ of primary energy. The latter would, if achieved, demand 12% of the global capacity of the biosphere to capture solar energy, 2100 EJ, (7) even if it is assumed that this can be converted with 100% efficiency to usable energy for humans. Field (2001) concluded that 'insuring a sustainable future entails sharing NPP with a great host of other species'. The vast majority of NPP is required by the heterotrophic organisms that abound in all ecosystems. Human appropriation of carbon/energy in biomass is in direct competition with biodiversity.

* The removal of biomass for energy purposes may be partially a balanced process in terms of carbon, but this is not the case for phosphorus and nitrogen or some other trace elements. Thus, there are serious questions about the sustainability of such processes or at least their true cost.

* Solar energy is captured by most autotrophs with a maximum efficiency of 3.5% (Calvin Cycle plants; Zhu, Long, and Ort 2008). Thus, biomass is about five times less efficient in using land area than photovoltaic collectors with consequences for both the cost of investment in property and the impact on other land uses. Unlike biomass, photovoltaics directly produce usable and transmittable energy.

* Wind farms will be about as efficient in generating energy per unit area (8) as biomass, again with the added advantage of directly generating transportable electrical energy and with the bonus of being able to be co-located with other land use purposes.

* Biomass removed from any ecosystem, natural or agricultural, will be in competition with, and possibly at the expense of, other potential uses, food, species conservation, fibre or the energy/trace nutrient support of the wider heterotrophic organisms within the ecosystem.

These and other potential limitations, or at least issues to be more carefully addressed, are why the UK Gallagher Report (Gallagher 2008) urged that 'The introduction of biofuels should be significantly slowed'.

6. Conclusions

This analysis shows the following:

* The cost of operating large Articulated trucks in Australia is about 0.15 $ [km.sup.-1] [t.sup.-1] compared with Heavy Rigid trucks of about 1.35 $ ([km.sup.-1]) [t.sup.-1].

* Such costs become important, if not limiting, when the value of the commodity is sufficiently low per tonne of carbon or per unit of energy content. This can result from relatively high inclusive costs of operating the trucks compared with the relatively low value of, for example, traded sugar cane, coal, or carbon, and/or competitive energy sources, such, as electricity.

* Biomass varies in terms of its water, carbon and energy content, but, by and large, the cost of truck transport represents a significant impediment to the use of biomass as an energy source if the distance the biomass needs to be transported, for modification to a usable form or consumption, is greater than a few hundred kilometres. Such distances are likely to be significantly lower as transport costs are but one cost in the full value proposition for bioenergy.

* The overall efficiency and cost of the use of biomass for energy/carbon should be evaluated across all steps in the value proposition, on-farm overheads, harvesting, transport, conversion, transport and usage. An examination of all of these steps was beyond the scope of this analysis.

Despite this an enormous international effort is being directed at the implementation of various biofuel-technologies, as reflected in government subsidies and research investment, private-sector business and research investments and a plethora of international conferences and scientific journals. The reason for this dichotomy of views concerning the potential of bioenergy is unclear and discussed by Pearman (2013). Without more careful and holistic examinations of the full value chain and interacting factors, such as other human and hetero-trophic needs for biomass, enthusiastic entrepreneurial or political support for such options might turn out to be a wasteful and even dangerous diversion.


(1.) All costs are in Australian dollars.

(2.) Clean Energy Regulator: Last accessed, 10 January 2018.

(3.) Last accessed, 10 January 2018.

(4.) Prices at the time of preparing this manuscript from Last accessed, 10 January 2018.

(5.) A discussion of the comparison with gas prices is beyond the scope of this article, a topic that is complicated by the rapid rise in costs of gas and the significant price difference (DIIS 2016) between states both industrially (Victoria, $5.7 [GJ.sup.-1],Queensland, $12.0 [GJ.sup.-1]) and residentially (Victoria, $18 [GJ.sup.-1], Queensland, $60 [GJ.sup.-1]).

(6.) These comparisons are based on the inclusive costs to be borne by truck or train operators. They assume that vehicle registration fees cover all infrastructure costs otherwise borne by the community. A discussion of this assumption is beyond the purview of this analysis.

(7.) Taking the annual net primary production of the global terrestrial biosphere to be 58 Gt of carbon per year (Ito 2011).

(8.) Assuming 2 MW turbines spaced approximately seven times the blade diameters apart and generating only about 30% of their rated capacity.


The author is indebted to Kieren Gardner and Sari Mackay of GrainCorp Limited for guidance in directing the author to this resource and to Adrian Brown of Freight Metrics ( for his assistance in understanding and utilising the Calculator.

Disclosure statement

No potential conflict of interest was reported by the author.

Notes on contributor

Graeme I Pearmana was chief of CSIRO Atmospheric Research, 1992-2002. He contributed over 200 scientific papers primarily on aspects of the global carbon budget. He is now a consultant, Adjunct Senior Research Fellow at Monash University and Professorial Fellow, Melbourne University. He was elected to Fellowship of the Australian Academy of Science, the Academy of Technology and Engineering, the Royal Society of Victoria and the Australian Meteorological and Oceanographic Society.


ABS. 2015a. Survey of Motor Vehicle Use. Technical Paper 9208.0. Australian Bureau of Statistics, Canberra, Australia.

ABS (2015b). Value of Agricultural Commodities Produced, Australia, 2011-12. Australian Bureau of Statistics, Cat. No. 75030,

Amthor, J. S. 2010. "From Sunlight to Phytomass: On the Potential Efficiency of Converting Solar Radiation to Phyto-Energy." New Phytologist 188: 939-959. doi:10.1111/j.1469-8137.2010.03505.x.

BITRE(2011).TruckProductivity:Sources, TrendsandFuture Prospects. Report 123, Bureau of Infrastructure, Transport and Regional Economics 2011, Canberra: ACT. 93.

BREE. 2012. Energy in Australia, 2012, 122. Canberra: Bureau of Resources and Energy Economics, Department of Resources, Energy and Tourism, Australian Government.

CCC. 2011. Bioenergy Review, 97. UK: Committee on Climate Change.

Chum, H., A. Faaij, J. Moreira, G. Berndes, P. Dhamija, H. Dong, B. Gabrielle, et al. 2011. "Bioenergy." In IPCC Special Report on Renewable Energy Sources and Climate Change Mitigation, edited by O. Edenhofer., R. Pichs-Madruga, Y. Sokona, K. Seyboth, P. Matschoss, S. Kadner, T. Zwickel, et al. Cambridge, United Kingdom and New York, NY, USA: Cambridge University Press.

DIIS. 2016. Gas Price Trends Review. Revision 1. Prepared by Oakley Greenwood Pty Ltd with EMS and MDQ Consulting, for Commonwealth of Australia. Department of Industry, Innovation and Science Energy Division, Canberra, Australia. ISBN: 978-1-925092-65-3, (online).

Elfadil, A. D., and M. K. Mohamed. 2015. "Effect of Dry-Off Period and Crushing and Extracting Delays on Sugarcane Quality and Productivity." Transactions on Industrial, Financial and Business Management 3: 5.

FAO (2000). The Multifunctional Character ofAgriculture and Land: The Energy Function. Background Paper 2; Bioenergy. National Resources Management and Environment Department. FAO Corporate Document Repository. Accessed

Field, C. B. 2001. "Sharing the Garden." Science 294: 2490-2491. doi:10.1126/science.1066317.

Gallagher, E. (2008). The Gallagher Review ofthe Indirect Effects of Biofuels production. E. Gallagher, Chair, UK Renewable Fuels Agency. St Leonards-on-Sea, East Sussex, UK. 91pp.

Haberl, H., K. H. Erb, F. Krausmann, V. Gaube, A. Bondeau, C. Plutzar, S. Gingrich, W. Lucht, and M. Fischer-Kowalski. 2007. "Quantifying and Mapping the Human Appropriation of Net Primary Production in Earth's Terrestrial Ecosystems." Proceedings of the National Academy ofSciences 104 (31): 12942-12947. doi:10.1073/pnas.0704243104.

IEA (2012). A Policy Strategy for Carbon Capture and Storage. Information Paper. International Energy Agency. 56.accessed

Ito, A. 2011. "A Historical Meta-Analysis of Global Terrestrial Net Primary Productivity: Are Estimates Converging." Global Change Biology 17 (10): 3161-3175. doi:10.1111/j.1365-2486.2011.02450.x.

Ludemann, C. I., S. M. Howden, and R. J. Eckard. 2016. "What Is the Best Use of Oil from Cotton (Gossypium Spp.) And Canola (Brassica Spp.) For Reducing Net Greenhouse Gas Emissions- Biodiesel, or as a Feed for Cattle?" Animal Production Science 56: 442-450. doi:10.1071/AN15453.

McLaren, J. (2009). Sugarcane as a Feedstock for Biofuels. Page 11 of An Analytical White Paper, prepared for the National Cane Growers Association, by StrathKirn Inc.

OCE (2015). Australian Energy Update. Office of the Chief Economist, Department of industry and Science. Associated data tables accessed

Pearman, G. I. 2013. "Limits to the Potential of Bio-Fuels and Bio-Sequestration of Carbon." Energy Policy 59C: 523-535. doi:10.1016/j.enpol.2013.04.064.

Rojstaczer, S., S. M. Sterling, and N. J. Moore. 2001. "Human Appropriation of Photosynthetic Products." Science 294: 2549-2552. doi:10.1126/science.1064375.

Searchinger, T. D., S. P. Hamburg, J. Melillo, W. Chameides, P. Havlik, D. M. Kammen, G. E. Likens, et al. 2009. "Fixing a Critical Climate Accounting Error." Science 326: 527-528. doi:10.1126/science.1178797.

TIC (2015). National Guidelines for Transport System Management in Australia. Road Parameter Values (PV2). Steering Committee. Transport and Infrastructure Council. Department of Infrastructure and Regional Development, Canberra.accessed

Zhu, X.-G., S. P. Long, and D. R. Ort. 2008. "What Is the

Maximum Efficiency with Which Photosynthesis Can Convert Solar Energy into Biomass?" Current Options in Biotechnology 19: 153-159. doi:10.1016/j.copbio.2008.02.004.

Graeme I. Pearman (a,b)

(a) Australian-German Climate and Energy College, Melbourne University, Melbourne, Australia; (b) Graeme Pearman Consulting Pty Ltd, Melbourne, Australia

CONTACT Graeme I. Pearman *


Received 10 January 2018

Accepted 29 April 2018
Table 1. Summary of the average use of three categories of trucks in
Australia during 2014. Energy and carbon fuel usages were weighted by
the proportion of the fuels used (ABS 2015a). The water content of
biomass was given a nominal value of 20% and the carbon content 50% of
dry matter. Number of figures not indicative of precision of values.

Trucks            km [yr.sup.-1]  km [day.sup.1]

Light commercial      16,100            70
Rigid                 20,000            87
Articulated           81,300           295

Trucks            t [yr.sup.-1]  t [trip.sup.-1]  t [day.sup.-1]

Light commercial         51           0.353           0.22
Rigid                  2244           5.65            9.76
Articulated          11,276          24.74           40.85

                       Fuel consumption
Trucks            lt/100 km  Petrol/diesel, lt

Light commercial    12.1       2084/3080
Rigid               28.4         12/2635
Articulated         56.9          0/4448

                          Fuel equivalence
Trucks            (MJ [km.sup.-1])  (gC [km.sup.-1])

Light commercial        4.1                80
Rigid                  11.1               222
Articulated            22.2               444

Table 2. Values used for the energy densities of various fuel types.
Values will vary with different origins of the fuel, but these serve
as illustrative in this study.

Fuel                        tC t-          tC           GJ
                        [fuel.sub.-1]  [TJ.sup.-1]  [tC.sup.-1]

Dry biomass               0.50 (a)         28         36 (a)
Sugarcane for crushing    0.15 (b)         28         36
Diesel                    0.86             19         53
Thermal coal              0.75 (d)         28         36
Lignite                   0.65 (d)         71         15
Gasoline                  0.90 (d)         20         51
LPG                       0.82 (d)         16         61

Fuel                        GJ t-                         MJ
                        [fuel.sup.-1]  L [tt.sup.-1]  [lt.sup.-1]

Dry biomass                18 (a)       NA             NA
Sugarcane for crushing      5           NA             NA
Diesel                     46 (d)       1182 (d)       39 (d)
Thermal coal               27           NA             NA
Lignite                    10 (d)       NA             NA
Gasoline                   46 (e)       1360 (e)       34 (e)
LPG                        50 (e)       1890 (e)       26 (e)

(a) Based on carbon content of carbohydrate such as glucose; dry matter;
(b) Amthor (2010); FAO (2000);
(c) Elfadil and Mohamed (2015), water in sugar cane;
(d) BREE (2072;

Table 3. Estimated average total cost of operating selected truck
types in Australia, inclusive of fuel, finance, depreciation, fixed
costs, driver, tyres, maintenance and servicing. Based on the Freight
Metrics Calculator (FMC).Costs are in Australian dollars. GVM: Gross
Combination Mass

                               Assumed daily
                                                    Annual operating
                               Delivery  Distance        cost
Truck type                     (t)       (km)              $

Van                             0.2       70        169,428
Light rigid, > 12 [t.sub.GVM]  10         87        189,099
Heavy rigid,                   10         87        237,453
>16.5 tGVM
Flat deck single               41        295        383,411
Skel B-double                  41        295        439,796
Curtain sider single           41        295        385,332
Curtain sider B-double         41        295        460,360
For comparison
Curtain sider B-double         24        600        543,406

                                                      Costs (%) due to:
                               Principle,               Fixed costs,
Truck type                     interest,                insurance,
                               depreciation (a)  Wages  accountancy (b)

Van                             8                49     41
Light rigid, > 12 [t.sub.GVM]  15                44     38
Heavy rigid,                   29                35     32
>16.5 tGVM
Flat deck single               34                26     24
Skel B-double                  36                22     24
Curtain sider single           34                26     24
Curtain sider B-double         38                21     23
For comparison
Curtain sider B-double         32                18     19

                               Costs (%) due to:           Cost
Truck type                     tyres,                           $/km/
                               service (c)   Fuel  $/km   $/t   t

Van                             1             1    11.7   3720  53.15
Light rigid, > 12 [t.sub.GVM]   1             2    10.5     94   1.08
Heavy rigid,                    1             3    13.2    118   1.35
>16.5 tGVM
Flat deck single                5            11     5.2     38   0.13
Skel B-double                   6            13     6.0     43   0.15
Curtain sider single            5            11     5.3     38   0.13
Curtain sider B-double          5            12     6.3     45   0.15
For comparison
Curtain sider B-double         10            21     3.70    91   0.15

(a) Includes in finance are principle, interest and depreciation
(b) Insurance, accountancy, etc.
(c) Tyres, maintenance and service
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Title Annotation:ARTICLE
Author:Pearman, Graeme I.
Publication:Australian Journal of Multi-disciplinary Engineering
Geographic Code:8AUST
Date:Aug 1, 2018
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