TY - GEN
T1 - A Spatial Model of the Biomass to Energy Cycle
AU - Möller, Bernd
N1 - ISSN ; -
PY - 2003
Y1 - 2003
N2 - A major source of biomass for energy production is the New Zealand forest industry, with 1.5 M tons of in-forest residues and additional 0.4 M tons as unused residues from sawmills. Transportation and handling are the main contributors for biomass costs at a specific consumer site, and they vary by location. This paper aims to contribute to the development of a biomass to energy evaluation and mapping system, using geographical information systems (GIS). A GIS-based in-forest residue model considers forest growth and choice of harvest method. Data from a sawmill survey is used to assess sawmill resi-dues. For both sources the costs of road transportation have been modelled using spatial cost allocation. As emphasis has been on using public data, the model is still a rough es-timate, which could be improved using forest industry data and refined algorithms. As a first result, the cost distribution and the costs of accumulated amounts of wood residues can now be calculated almost instantly for each location in the country. It is assumed that this approach will facilitate the assessment of future biomass markets.
AB - A major source of biomass for energy production is the New Zealand forest industry, with 1.5 M tons of in-forest residues and additional 0.4 M tons as unused residues from sawmills. Transportation and handling are the main contributors for biomass costs at a specific consumer site, and they vary by location. This paper aims to contribute to the development of a biomass to energy evaluation and mapping system, using geographical information systems (GIS). A GIS-based in-forest residue model considers forest growth and choice of harvest method. Data from a sawmill survey is used to assess sawmill resi-dues. For both sources the costs of road transportation have been modelled using spatial cost allocation. As emphasis has been on using public data, the model is still a rough es-timate, which could be improved using forest industry data and refined algorithms. As a first result, the cost distribution and the costs of accumulated amounts of wood residues can now be calculated almost instantly for each location in the country. It is assumed that this approach will facilitate the assessment of future biomass markets.
M3 - Article in proceeding
BT - Wasteminz Bioenergy Workshop 2003
T2 - Wasteminz
Y2 - 27 May 2003 through 27 May 2003
ER -