1. Farrell article

2. Summary Evaluated potential effects of increased ethanol use Reviewed a number of previously published articles on corn ethanol Ethanol results in less petroleum usage, but minor differences in GHGE Need for additional research in environmental metrics

3. Summary Adjusted the studies to have equivalent bounds Corrected some of the data sources in the other articles Large scale use of ethanol would require cellulosic technology

4. Methods Checked data sources of 6 current reviews on corn based ethanol Looked at net energy, but highly dependent on system boundaries Finding intuitive and meaningful units besides net energy is needed

5. Methods Add coproduct credit Apply consistent system boundary (include effluent processing energy and neglecting laborer food requirements) Account for different energy types Calculate policy metrics (not sure what this is)

6. Sensitivity Analysis Most sensitive to coproduct allocation Corn ethanol produces valuable coproducts – Studies that showed a negative energy balance for corn ethanol assumed no coproducts

7. Results Ethanol significantly reduces petroleum usage Only 5 to 26% of the energy is renewable though GHG reduction was between a 20% increase and a 32% decrease Their results – Reduce petroleum by 95% on energetic basis – Reduce GHGE by 13%

8. Uncertainty Results Uncertainty analysis suggests results are good Variation in performance by location Given appropriate policy incentives, corn ethanol could be improved Only cellulosic ethanol appears to save GHGE

9. Supplemental Data Well laid out spreadsheet (go over briefly) LHV versus HHV – LHV energy – water is evaporated from the fuel during combustion – HHV energy – recovers energy in water vapor

10. Net Energy Value Different definitions in each study Don’t define nuclear or renewable electricity Ignore differences in energy quality Very sensitive to coproducts – Are coproducts subtracted from energy inputs – Are coproducts added to energy outputs – Results in a different ratio Makes net energy ratio difficult to use

11. Metrics GHGE / MJ fuel Petroleum inputs / MJ fuel Coal inputs / MJ fuel Natural gas inputs / MJ fuel Other energy inputs / MJ fuel X – is the variable of interest A – MJ energy per l of ethanol Calculations in terms of x/a

12. Agricultural Inputs Problems with lime application Inputs to farm machinery – Used an economic input output model from Carnegie Mellon University

13. Coproducts Anything that adds value should be counted as a positive impact Looked at process, market-based, and displacement Process method – Use a tool like ASPEN to model mass and energy in process – Allocate according to the process simulation

14. Coproduct Market Based – Allocates total energy according to the relative value Displacement method (system expansion) – Preferred method – according to some other studies Most comprehensive would be market based with the displacement

15. GHGE Use IPCC on global warming potential GHGE for nitrogen fertilizers shown in S-8 to S- 10 Assume small changes on unfarmed land into cultivation Some crop shifting Importing ethanol would cause some land use changes

16. Sensitivity Analysis Determined by 1% change in input parameter Major factors – Refinery energy – Farm yield – Refinery yield – Coproduct credit – Nitrogen energy – Nitrogen application rate

17. Sensitivity Analysis N 2 O big factor Two key implications – Any feedstock that relies heavily on nitrogen will not provide significant GHGE relative to gasoline – Relatively little petroleum is used for corn or cellulosic ethanol, so large reductions in petroleum consumption are likely