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  1. Assessing Bioenergy Potentials in Rural Landscapes Oludunsin TunrayoArodudu Alexey Voinov Iris van Duren

  2. Introduction Climate change challenges Depletion of global fossil fuel reserves Shortage of fossil fuel supply

  3. Research Problem Developing a more holistic approach for assessing bioenergy potential under an SEA framework Known measures of bioenergy potential • Available land • Some biomass are not grown on land • Biomass yield • Not a function of energy obtainable • Energy yield • Energy invested not considered • Money invested and gained • Susceptible to political and market mechanisms

  4. Alternative Approach:NEG/EROEI • Net Energy Gain (NEG) NEG = Energy Output - Energy Input Net Energy Gain becomes a loss when it is less than 0 & • Energy Return on Energy Invested (EROEI) EROEI = Energy Output / Energy Input Energy production activity becomes incapable of supporting continuous socio-economic function when EROEI is less than 3

  5. Scope of the study (Rural landscapes) Natural grasslands Crop residues Farm manure WHY? Surplus pasturelands • Relative benignity and favourability in terms of existing policy constraints: • Food security • Nature conservation: soil, water, biodiversity • Competitive use of biomass and well being of the local people

  6. Reasons for choice of crop and animal • For crops (Scarlat et al, 2010): Corn, Rye, Triticale, Wheat, Barley, Oat, Rapeseed • Availability in commercial quantity • Good Crop to Residue Yield • For animal (Fehrs, 2000): Beef Cattle, Dairy cattle, Pig, Chicken • large Population of animal • % collectable on barns and hard surfaces • For Grasses on Surplus pasturelands (Prochnow et al, 2009)- Alfalfa • Prevent a total change in ecosystem structure • Meet future fodder needs

  7. Factors influencing potential availability of biomass for bioenergy production • For Crop residue (Scarlat et al, 2010) • Use for soil conservation purposes • Use as substrates for mushroom (Wheat) • Use for animal beddings • For Animal waste (Fehrs, 2000) • % collectable on barns and hard surfaces • For Grasses (van Vuuren et al, 2010) • Use for animal beddings and animal feed

  8. Method: Combination of Life Cycle Inventory (LCI) and GIS • From the LCI: • List of energy inputs and outputs, biomass and energy conversion • models and coefficients • Estimation of Potential Biomass and Biomass Potentially • available for Bioenergy Production • Estimation of Energy Input and Output of the different • bioenergy production options • Estimation of NEG and EROEI of the different bioenergy • production options • From the GIS: • Estimation of area under natural grassland using GIS • coverages (LGN 6 Land cover map)

  9. ReSults: Percentage composition Manure by far has the largest biomass and bioenergy potential

  10. Results: Farm manure Large NEG, not necessarily high EROEI

  11. Result: Crop residue • Corn residues: • most energy efficient : High EROEI • most energy profitable: High NEG

  12. Results:Choice of grass harvest for bioenergy production • Natural grassland (Intermediate Harvest): Natural Grassland Management Policy in the Netherlands • Surplus Pasturelands (Late Harvest): Highest energy efficiency value (EROEI).

  13. Comparison of EROEI levels

  14. Evaluation of Overijssel’s bioenergy potential Extra 2PJ of biogas still exists.

  15. Conclusions • NEG/EROEI approach is quite holistic: • Opens up room for broad analysis of bioenergy potential issues • Alternatives: minimizing constraints and maximizing energy gains • Unconventional biomass sources • Farm scale wet anaerobic co-digestion technology • Better animal management options and farm structures • Energy efficiency component: EROEI • Accurate evaluation of bioenergy targets: NEG • Basis for stakeholder interactions

  16. Thank you!!!