**4. Available Biomass Potential**

In fifteen of the reviewed studies, the available biomass potential is measured or discussed (Table 1). An international study [25] reviews some previous research in Australia on the cost related to harvesting and forwarding of biomass from forest to roadside, primarily using time-motion-studies, and reference some of the following work in di fferent harvesting systems. Cost (USD/t), fuel consumption (L/t), and energy content (MJ/t) of slash bundling operations and total operational cost (USC/kWh) of a slash-bundler application to collect harvest residues in Eucalyptus plantation are measured using time-motion-studies [65]. The chipping cost (USD/t) and forwarding cost (USD/t) are analyzed using time-motion-studies on Bruks Chipper operations in Pine plantations [23,67]. Similarly, time-motion-studies in integrated harvest sites in Pine plantation were carried out to measure productivity and unit cost (AUD/m3) of harvesting and forwarding operations [69]. Walsh and Strandgard (2014) also used time-motion-studies to assess the productivity of harvest and extraction in a Fibreplus operation in Pine plantations. None of these studies assess the available biomass potential after potential losses that occur during transport.

Rodriguez et al. (2011) used a transportation model to calculate the costs of transporting logs and chips. Literature values were used for the costs of collection and processing of biomass in the field. This model incorporated fixed and variable (costs to estimate the average costs per tonne-km−<sup>1</sup> transport based on the one-way distance to destination and load mass. Fixed costs included capital depreciation, interest charges, labour, registration, insurance, repairs, maintenance, and salaries. Variable costs covered fuel, oil, and tyres. Using a 16–18 MJ/kg conversion, they estimated how much biomass energy

(MJ) was available before conversion. May et al. (2012) used the SimaPro model to estimate the energy use in forestry operations and included the establishment, management, harvesting and transport of logs. The analysis included calculations for transport, mean travel distance, load weight and fuel consumption and other materials. They presented an intermediate energy (MJ) value and used a 19.6 MJ/kg conversion rate for biomass chips. The BIOPLAN model [70] calculates the cost of the BSC and is based on the following factors: tonnes biomass, solid and lose volumes of biomass, truckloads, energy contents (17.38 MJ/kg), and costs of harvesting, extraction, chipping, storage and transportation. Woo et al. (2018) included the cost of transport and moisture content in a linear programming model to identify locations for new bioenergy facilities based on the available biomass potential. All of these modelling approaches include measures of the available biomass potential to the extent of what is technologically and economically harvestable.

Strandgard et al. (2019) reviewed the potential relevance to Australia of overseas supply chain models such as MCPLAN [24] and other measures of the available biomass potential (transport distance, load size, harvest rates and machine types). Ximenes et al. (2017) reviewed some considerations and conditions around different harvesting systems of CWD which result in the material either retained or captured for use. The remaining studies in Table 1 do not include any measures directly related to the available biomass potential other than the energy content of their respective resource and case study [48,74,77,79,81].
