**8. Discussion**

The review above demonstrates a number of methodological approaches as well as variations in data, data models, scale on which the methods are applied and the detail of calculations that are included. The purpose of this discussion is to elaborate on some of the main results and challenges that need to be addressed in future research.

Almost every study presents measures of the theoretical biomass potential to a certain degree. There is however a clear distinction between studies that do an initial measurement of forest biomass which could be referred to as the maximum or upper-bound biomass potential and studies that included a measure that reduces that potential to what will be considered usable as defined by Shi et al. (2008). Field measurements involving weighing biomass or using allometric equations based on tree height and diameter are complex and time-consuming but provide reliable estimates of that upper-bound biomass potential and provide forest or species-specific estimates. These case-specific values can then be used for large-scale or nationwide estimates of the forest biomass potential [53,71,72,84] that use these literature values with the modelled prediction on losses of the theoretical biomass potential. Inevitably, the accuracy of this combination decreases as research becomes more generalized. Using case-specific inventory data on the upper-bound biomass and generalizing this over larger, sometimes nationwide, areas give a doubtful indication of the theoretical biomass potential. It is, however, hard to say what is good or bad and often the level of accuracy is su fficient on a larger scale. This coarser resolution and large-scale are still relevant from a policy and planning point of view where it provides su fficient indication of biomass location and the possible potential. Alternatively, there are in-field measures of the usable biomass available like those referred to as the CRC for Forestry method described in the literature [63]. Methods like CRC for forestry, are applied after a timber harvest and give a better indication of the parts of the leftover biomass that could be collected for energy purposes, and reduce the level of assumption for the theoretical biomass potential. Sequentially, combining it with high accuracy growth models can predict future levels of biomass on a local scale, which then can be used as indicative measures of future potential, which will be used to establish renewable energy targets. Based on the available research around the theoretical biomass potential, there is no clear gap to identify. Future research should thus consider the level of accuracy that is required and the data that is available to guide the methodology. It is, however, worth noting that no method exists that measures only the amount of biomass that will be used for bioenergy and will be collected and transported. Even the CRC for Forestry method has an emphasis on "collectable" biomass; the results also indicate a lot of work goes into measuring biomass like cones, needles, leaves and twigs that are not feasible for collection. We sugges<sup>t</sup> that this might require an approach working top-down by determining the biomass that is suitable for conversion in the facility, will have higher gate price, can be transported and harvested with high e fficiency, to then determine what percentage of the total above-ground or post-timber harvest biomass this represents. To do this, the link between the theoretical biomass potential and the available, technological, economic and environmental biomass potential needs to be established in the Australian supply chain context. Another recommendation concerning the theoretical biomass potential is to use it as an instrument to inform policy in Australia and to adjust biomass-harvesting guidelines. Currently, none of the forestry guidelines including FSC and Responsible Wood is descriptive on the retention of forest biomass with respect to environmental, economic and social benefits.

Having been critical in some of the models used in the previous studies, it is worth recognizing that they provide direct insight into some of the planning issues regarding harvest and transport and thus the available biomass potential in relation to the theoretical biomass potential. More specifically, there is a particular emphasis being placed on the use of geographical data in combination with the literature or inventory data on the forest biomass. Some of the models that were used in the reviewed studies [70,71,76,78] make this exact connection as to how the cost of harvesting and transport a ffect the retention of biomass in the forest. Rather than looking at a steady-state situation of the forest, a method to assess the available biomass potential should look into changes in the biomass quantity over time as well as changes in the geographical location of biomass. Several studies can be found in the international literature, simulating changes in the supply of biomass-based on stand age, fire salvage or terrain [85–88]. If research wants to inform investors and if the location is pre-defined, high resolution of the geographical area and theoretical biomass potential should be combined to assess what is the available biomass potential. In addition to that, there is a need for performance values of the equipment, used along the supply chain. Although performed in just a handful of case studies in Australia, Gha ffariyan et al. (2017) summarize some of the operational costs of harvesting forest biomass equipment. For reference to transportation costs, some international models can be used as described by Strandgard et al. (2019). The assessment of the available biomass potential opens a whole new level of detail again, from di fferent harvesting technologies for the timber as well as the forest biomass, di fferent sizes and loads of trucks for transport, potential pre-treatment and storage to reduce cost and emission during the supply chain. Extensive modelling can be performed and numerous constraints can be added to the research model [2,9,22]. Although not as extensively researched as some studies in other countries or geographic areas, the biomass supply chain modelling research [70,71,76,78] that has been performed in cases in Australia is adequate to give an indication of the available biomass potential and to develop strategies in the commercial harvest of biomass for bioenergy production. Given the lack of commercial cases in Australia that e ffectively use forest biomass for bioenergy production, there is no established supply chain as a reference. Therefore, the word "optimisation" in research should be used carefully, as Australia aims to find a range of solutions rather than one lowest-cost or lowest emission solution. The type of optimization that can be performed is illustrated by Woo et al. (2018) where a plant location-optimization is performed based on the available resource and cost estimates of the supply chain. This type of research does address the biggest cost element of the supply chain which is transport [24] but is not a ffected by other elements, like harvesting or storage of the resource. Instead, the optimization is used as a planning and development tool to identify locations that are suitable for biomass conversion based on the availability of the resource, and thus paying respect to the theoretical and available biomass potential. Additionally, the network analysis of this study [78] delivers insight into the demand for energy which then leads into the technological and economical biomass potential. Similar approaches can be found in the international literature combining measures of the theoretical and available biomass potential [13,89,90]

In regards to the technological biomass potential the study by Woo et al. (2018), is perhaps the most comprehensive to find in Australia, even though no selection of conversion technology or sensitivity was applied. The method they use allows for additional measures of the technological biomass potential and has been used widely in the industry [13,90–92]. Network analysis based on spatial information can be used to identify the location for bioenergy conversion based on biomass availability and cost attributes of the supply chain. The assessment of the biomass potential of a regional network should be considered carefully when expanded to larger scales. Additionally, network analysis can be used to identify the size of the processing plant based on demand, technology and supply as well which is demonstrated in several case examples in New Zealand [14], Finland [93], Mozambique [94] and the USA [95,96]. The method is a streamlined combination of geographic information systems, mathematical modelling and network analysis that aligns in a decision support system. This is where some of the gaps in research become very apparent for Australia. The number of studies that assess the technological, economic and environmental biomass potential is significantly lower than the studies identifying the theoretical and available biomass potential discussed earlier (Figure 1). A couple of studies tested the sensitivity of an established biomass conversion technology [48,79], and do well in comparing the technology with a reference fossil conversion system which indicated gains of carbon emission and economic return over time. However, it is hard to draw conclusions from these two cases. It is imperative to have cases looking at specific conversion technology and efficiency to use in combination with planning and decision support systems to assess the large-scale technological potential of forest biomass. An example case study from the international literature [97], looks at the sensitivity of minimum energy recovery and thermal energy production constraints to impose that the amount of renewable energy produced meets the demand of the catchment area.

In addition to what Voivontas et al. (2001) introduced as the theoretical, available, technological and economical biomass potential, this review introduces the environmental biomass potential. One can assume the environmental biomass potential flows from the technological biomass potential in similarity with the economical biomass potential. Rather than having an economic output, the environmental biomass potential pays respect to carbon emissions resulting from the use of forest biomass for bioenergy. As argued in the literature [17,22], the use of forest biomass for bioenergy should consider economic and environmental constraints in order to assess its feasibility. Out of the three studies that had an economical and environmental element in their research [5,53,79], two studies were able to provide simultaneous measures of the displaced emissions and the provided energy [53,79]. Other than a potential energy production for distribution, there was no information on the cost of energy production, or cost-savings compared to a reference scenario as performed by Rodriguez et al. (2011). Whether performed separately or combined, one could argue that the use of LCA and value chain optimization provides a solution to address the potential of forest biomass from an economical and environmental point of view [8,98]. Australian studies by May et al. (2012) and England et al. (2013) estimated the embodied energy used and emissions from cradle to gate in the Australian forestry context. Their research emphasizes the difference between LCA as a means of assessing emission and energy associated with wood products including alternative uses, compared to life cycle inventory and cradle-to-gate inventory providing emissions associated with forest supply chain [84]. Thus, there is a need for a clear definition of the forest biomass for bioenergy system when it comes to assessing the economic and environmental value. Good research examples in Australia are available however not on the use of forest biomass for bioenergy. Several international studies can be found capturing constraints for the theoretical, available, technological, economic and environmental biomass potential [10,99,100]. A reference case study in Australia is research by Murphy et al. (2015) and Hayward et al. (2015) on the economics and sustainability of producing aviation fuels from energy crops in Queensland Australia. Their research indicates some of the future challenges of the industry, which include the expansion of case studies on a larger scale to make it reliable and sustainable. This challenge confirms findings in this review where we identify a need to use some of the case-specific data in combination with modelling to provide estimates on a larger or nationwide scale. A second challenge is to demonstrate that the industry can satisfy community demand and compels with sustainability expectations. Indeed, one of the findings of this review is to come up with a more comprehensive design and planning solutions for the forest biomass supply chain and the establishment of new conversion facilities. This is where the use of geospatial data and modelling comes in place to develop a decision support system that not only satisfies the supply but also lives-up to demand sustained energy production. Another recommendation is the need for full LCA to determine the total carbon footprint. However, defining the limit of LCA is important and can be challenging. Bioenergy projects in Australia are fairly new and thus the total effect on the energy market is ye<sup>t</sup> to be discovered, especially in the long term. In addition, the adverse effect on the timber industry and other industries that deliver biomass feedstock needs to be considered. The last challenge that has relevance to the use of forest biomass for bioenergy is the risk of uncertainty of the supply chain and its elements. Future research has to bridge this gap mainly through securing the supply chain and finding a long-term supply of biomass for energy production. This finding enforces the need to make connections between the theoretical, available, technological, economic and environmental biomass potential once again.
