1. 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 and Agricultural and Forest Systems, University of Padua, Italy Dept of Development and Planning, Aalborg University, Denmark Presented at the: Australasian Forest & Wood Products Conferences: Residues to Revenues. Rotorua, October 12-13 and Melbourne, October 17-18, 2005.

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

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

4. National availability and cost supply model 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. Model overview

5. 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.

6. Estimated annual forest residue availability TLA

7.  The site-specific amount and cost of biomass are calculated by overlaying in-forest 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. Costs of biomass at site National availability and cost supply model

8. Availability and cost of residues at 4 locations

9. 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 Within forest availability and cost supply model

10. 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

11. 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

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

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

14. NEFD Database Kinleith Database Forest stand data calculation Areayear of establishment tending history proposed felling year Silvicultural Regime analysis only radiata pine considered 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

15. Volume (m 3 ) * 0.75 t/m 3 = weight (tonnes) TRV m 3 /ha Drying period 1 year As percentage of TRV (Depends on logging method) Logging residues Volume m 3 /ha Logging residues Weight tonne/ha Residue calculation

16. Results Total Recoverable Volume (m 3 /year) Logging residue availability (tonnes/year) Yearly average: 21 500 - 28 200 tonnes Yearly average per hectare: 0.6 tonnes/ha - 0.8 tonnes/ha Yearly average: 943 000 m 3 Logging residue availability

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

18. 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

19. 200820062007 Location of landings with assigned residues Assigning logging residue to landings Residues (red dots) vary over time and across the forest

20. Location of hogger sites Road typeCapabilityHogger site PublicChipsNo Forest sealed or unsealed Residue or chips Yes Forest stub or track ResidueNo Reclassify roads according to their carrying capacity GIS – based analysis

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

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

23. 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

24. Minimum cost calculations  Define variables:  Maximum distance between landing and hogger site  Minimum residues at landing  Run minimum cost calculation Insert data Perform calculation results Define scenarios

25. Results legend Variables: maximum distance 8000 m – 9000 m residue at landing >0 in intervals of 12.5 tonne

26. 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)