Biomass resources maps
This data set contains spatial raster files, plotting biomass resources for the Australian states. Data type: .tif files Spatial resolution: 5x5 km Projection: "+proj=utm +zone=56 +south +datum=WGS84 +units=m +no_defs +ellps=WGS84 +towgs84=0,0,0" Biomass types: (a) Bagasse (bagasse), as remaining feedstock following the extraction of sugar from sugarcane (b) Forestry (native and plantation forestry) resides, summarizing woody biomass sources from forestry (harvest residues) or timber product residues or by-products from sawmills (offcuts, sawdust), as well as recycled wood from municipal waste, commercial waste (e.g. pallets) and residues from construction, demolition sources and from native and plantation forests (c) Stubble residues (cropping), describing crop straw from standing stubble (of wheat, oats, barley, triticale, sorghum, canola, lupins, oil seeds and legumes). These low-moisture feedstocks (moisture content ≤ 50%) can for example be used for steam generation from direct combustion and thermal conversion into electricity in Rankine cycle power plants. Due to the limited research scope, this study does not consider high-moisture feedstocks (e.g. animal waste and livestock residues), for anaerobic digestion (AD). Australian states: New South Wales (NSW), Queensland (QLD), Western Australia (WA), Northern Territory (NT), Victoria (VIC), Tasmania (TAS) and South Australia (SA). The Australian Capital Territory (ACT) is, due to its small size, combined with New South Wales (NSW). To our knowledge, the new biomass site database is the most comprehensive compilation of prospective biomass sites, based on up-to-date biomass resources maps at high spatial resolution. By considering the real-world spatial constraints, this new data set allows for a more realistic description of biomass usage in high-renewable energy supply models to better understand the potential of bioenergy in Australia.
Steps to reproduce
These high resolution biomass resource maps were generated with consideration for underlying land use types by employing a dasymetric modelling approach. This approach seeks to disaggregate low resolution data to a higher spatial resolution using available land use data. Used data sources/materials: The dasymetric model used in this study was developed in R (https://www.r-project.org/) utilising the following data sets: • Low-resolution biomass data for the jurisdictions across Australia was published recently as part of the Australian Biomass for Bioenergy Assessment (ABBA) initiative. This data was centralised in a national database and extracted for this study from the Australian Renewable Energy Mapping Infrastructure (AREMI) data platform (https://nationalmap.gov.au/). Biomass quantities from the AREMI data platform are available at different spatial scales depending on the biomass type. These spatial scales are part of the Australian Statistical Geography Standard. The statistical area 2 (SA2) scale is equivalent roughly to the suburb scale, consisting of populations between 3,000 - 25,000 people. The statistical area 4 (SA4) scale reflects labour markets and consist of populations between 300,000 - 500,000 people. • Land use data was obtained from the Australian Land Use and Management (ALUM) classification system.