Presented at the Australasian Forest Wood Products Conferences

Presented at the: Australasian Forest & Wood Products Conferences: Residues to Revenues. Rotorua, October 12 -13 and Melbourne, October 17 -18, 2005. Quantifying the availability and volume of the forest resides resource B. Hock, P. Nielsen, S. Grigolato, J. Firth, B. Moeller, T. Evanson Scion, Rotorua, New Zealand Dept of Land Agricultural and Forest Systems, University of Padua, Italy Dept of Development and Planning, Aalborg University, Denmark

Logging residues for energy production Energy prices are increasing Interest is growing in the use of in-forest residues as a sustainable energy resource Consider woody biofuel as a forest product • Assess the volume available • Optimise the logistic of the supply chain • Minimise the supply cost

Biomass supply from forest plantations Two models are being developed · National availability and cost supply model · Within-forest ” ” ”

National availability and cost supply model Model overview The location of forests, the transportation network, possible cogen plant locations and other spatial issues are mapped. The information is analysed within raster GIS. Techniques include cell-to-cell functions, neighborhood statistics and zonal geometry. The results are intensity maps or distributions of site-specific costs.

National availability and cost supply model Calculating the transport cost · The accumulated travel distance from a point location determines the transportation costs along the road network to that point. · This example visualizes the cost of transportation across a region.

Estimated annual forest residue availability TLA

National availability and cost supply model Costs of biomass at site · The site-specific amount and cost of biomass are calculated by overlaying inforest residues and transport costs. · The result is a distribution of biomass amounts and costs, which is unique for each location relative to a planned bioenergy plant.

Availability and cost of residues at 4 locations

Within forest availability and cost supply model A model was developed in collaboration with Carter Holt Harvey Forests Ltd. The case study was based on the Kinleith Forest, in the North Island of New Zealand, complimented by National Exotic Forest Description (NEFD) regional yield tables

Biofuel as a product: some issues Logging residues are unevenly distributed geographically and in time Volume of residues at landings is influenced by the characteristics of the logging operation (eg. harvesting methods, equipment capacity, terrain characteristics) Extraction of residues is affected by road types and density

The within-forest chain Volume at harvest Residue at landings Transportation of residue to hogger Chipping by hogger Transportation of chips to cogen Volume and cost at cogen plant

Methodology The within-forest availability and cost supply model The components: Calculate potential amount of logging residue Assign logging residue to landings Select hogger site locations Determine transportation network Minimise overall costs

Logging residue availability NEFD Database Forest Database Investigate variables that affect availability forest stand data topography Approximate the volume of logging residue for the next 17 years. forest productivity data

Logging residue availability NEFD Database Kinleith Database Forest stand data calculation Silvicultural Regime • analysis • only radiata pine considered Area • year of establishment • tending history • proposed felling year Total Recoverable Volume (TRV) • • import yield tables to GIS calculate block area evaluate the TRV for each block determine the logging residue for each block

Logging residue availability TRV m 3/ha Logging residues Volume m 3/ha Drying period 1 year Logging residues Weight tonne/ha Residue calculation As percentage of TRV (Depends on logging method) Volume (m 3) * 0. 75 t/m 3 = weight (tonnes)

Logging residue availability Results Total Recoverable Volume (m 3/year) Yearly average: 943 000 m 3 Logging residue availability (tonnes/year) Yearly average: 21 500 - 28 200 tonnes Yearly average per hectare: 0. 6 tonnes/ha - 0. 8 tonnes/ha

Logging residue availability Results The graph shows how availability varies over time. For example, there are two periods when supply falls below 10, 000 tonnes per year.

Assigning logging residue to landings To calculate logging residue at each landing: • locate landings (12 700) • define the catchment area for each landing • overlay the logging residue • sum the logging residue for each landing • repeat for each year

Assigning logging residue to landings Location of landings with assigned residues 2006 2007 2008 Residues (red dots) vary over time and across the forest

Location of hogger sites GIS – based analysis Reclassify roads according to their carrying capacity Road type Capability Hogger site Public Chips No Forest sealed or unsealed Residue or chips Yes Forest stub or track Residue No

Location of hogger sites Selection criteria: • Must be associated with roads suitable for chip trucks • Must have a minimum area of 5000 m 2

Location of hogger sites Selection criteria • Must be no closer than 20 km to adjacent hogger sites Superskid sites - 40 Superskid sites - 15

Transportation network · Network analysis to determine the minimum cost route between each landing and the hogger sites · Similarly for the routes between hogger sites and cogen plant

Minimum cost calculations · Define variables: 4 Maximum distance between landing and hogger site 4 Minimum residues at landing · Run minimum cost calculation Insert data Define scenarios Perform calculation results

Results Variables: maximum distance 8000 m – 9000 m residue at landing >0 in intervals of 12. 5 tonne legend

Conclusions • the availability of residue depends not only on volume, but also on the transportation cost to the power plant • a large number of variables need to be considered including drying, in–forest logging distribution, transport and chipping techniques • GIS based models are effective tools for Decision Support Systems (DSS)