1. Evaluation of agricultural systems across time and spatial scales. An extended LCA approach. Amalia Zucaro, Silvio Viglia and Sergio Ulgiati

2. Introduction

3. In times of depletion of fossil fuels and minerals reservoirs, agriculture is a potential source of food, fibers, energy, chemicals, materials, jobs and landscape protection ( multifunctional role ). Problems and Challenges 1. Introduction Focus is placed on agricultural systems in order to implement opportunities and synergies and suggest different scenarios at different scales, from local to regional and national. The concept of multifunctionality expresses the inescapable link of roles and functions of agriculture with social, economic and environmental aspects.

4. Materials and Methods

5. Life Cycle Assessment- LCA 2. Materials and Methods

6. Life Cycle Assessment- LCA 2. Materials and Methods

7. LCA - Life Cycle Assessment Processes & Products Processes, Products, & Complex Systems Extended LCA: SUMMA SUs tainability M ultimethod M ultiscale A pproach 2. Materials and Methods

8. SYSTEM BOUNDARY SUstainability Multimethod Multiscale Approach

17. Case studies

18. Urban System Agricultural System [...] Catalonia Finland Forestry Italy Scotland Lao Ulgiati et al., 2010 Material, energy and environmental performance of technological and social systems under a Life Cycle Assessment perspective Ecological Modelling. SUMMA Application: SMILE project 3. Case studies

19. The Italian agricultural sector across time and hierarchical levels:Country-Region-Farm (from 1985 to 2006) The Italian agricultural sector across time and hierarchical levels:Country-Region-Farm (from 1985 to 2006) 3. Case studies

20. Italian case study 3. Case studies

21. System diagram at National scales 3. Case studies

22. System diagram of agricultural sector 3. Case studies

23. System diagram of Farm 3. Case studies

24. Data collection: National scale FlowsUnit1985199320022006 Rainfallg/yr1.19E+179.71E+161.09E+171.03E+17 Total land croppedha/yr1.70E+071.50E+071.45E+071.37E+07 Fertilizers (N + PO4 + K2O)g/yr1.96E+121.98E+121.60E+121.48E+12 Nitrogen (N)g/yr1.01E+129.45E+118.51E+118.27E+11 Phosphate (PO4)g/yr6.10E+116.39E+114.27E+113.61E+11 Potassium (K2O)g/yr3.40E+113.91E+113.19E+112.94E+11 ElectricityJ/yr1.18E+161.66E+161.76E+161.98E+16 Water for irrigationg/yr7.89E+154.64E+153.41E+152.35E+15 Liquid fuelsJ/yr7.92E+161.04E+178.46E+169.60E+16 Machinerykg/yr2.58E+082.32E+082.25E+082.17E+08 Direct Laborhours/yr2.19E+092.00E+091.88E+091.75E+09 Direct Labor/yr4.58E+098.31E+091.61E+101.75E+10 Indirect labor (services)/yr3.43E+095.54E+096.46E+098.11E+09 Products Mass of agricultural production (dry matter)g d. m/yr1.25E+141.12E+141.03E+149.63E+13 Energy content of agricultural productionJ/yr2.02E+181.81E+181.66E+181.55E+18 Economic value of agricultural production/yr1.85E+102.26E+102.73E+102.53E+10 Agricultural residuest d.m./yr7.81E+067.01E+066.42E+066.02E+06 3. Case studies

25. Data collection: Regional scale FlowsUnit1985199320022006 Rainfallg/yr7.59E+155.56E+155.17E+154.88E+15 Total land croppedha/yr9.49E+057.42E+056.15E+056.03E+05 Fertilizers (N + PO4 + K2O), TOTALg/yr9.36E+107.80E+108.94E+107.29E+10 Nitrogen (N)g/yr5.95E+104.41E+105.25E+104.25E+10 Phosphate (PO4)g/yr2.53E+102.38E+102.53E+102.01E+10 Potassium (K2O)g/yr8.83E+091.01E+101.17E+101.03E+10 ElectricityJ/yr4.61E+147.49E+147.99E+148.87E+14 Water for irrigationg/yr4.42E+142.30E+141.53E+141.04E+14 Liquid fuelsJ/yr4.10E+155.37E+155.73E+156.74E+15 Machinerykg/yr1.42E+071.15E+078.94E+069.07E+06 Direct Laborhours/yr1.46E+081.11E+088.93E+078.10E+07 Direct Labor/yr3.07E+084.61E+087.68E+088.10E+08 Indirect labor (services)/yr1.99E+085.09E+083.20E+084.26E+08 Products Mass of agricultural production (dry matter)g d.m./yr1.19E+131.30E+135.27E+125.09E+12 Energy content of agricultural productionJ/yr1.98E+172.16E+178.54E+167.99E+16 Economic value of agricultural production/yr1.53E+091.72E+092.46E+092.22E+09 Agricultural residuest d.m.//yr7.44E+058.13E+053.30E+053.18E+05 3. Case studies

26. Data collection: Local scale UnitLemon FarmOlive FarmGrape Farm Rainfallg/yr9.11E+096.67E+098.54E+09 Total land croppedha/yr1.00E+00 Fertilizers (N + PO4 + K2O), TOTALg/yr1.98E+051.40E+051.85E+05 Nitrogen (N)g/yr8.00E+041.40E+057.50E+04 Phosphate (PO4)g/yr4.50E+040.00E+005.50E+04 Potassium (K2O)g/yr7.25E+040.00E+005.50E+04 ElectricityJ/yr1.33E+090.00E+00 Water for irrigationg/yr1.31E+092.00E+060.00E+00 Liquid fuelsJ/yr6.02E+096.19E+097.34E+09 Machinerykg/yr1.46E+042.55E+041.50E+04 Direct Laborhours/yr7.00E+026.56E+027.57E+02 Direct Labor/yr7.00E+036.56E+037.57E+03 Indirect Labor (services)/yr4.18E+031.33E+031.78E+03 Products Mass of agricultural production (dry matter)g dry matter/yr3.15E+062.32E+062.96E+06 Energy content of agricultural productionJ/yr1.38E+105.94E+103.87E+10 Economic value of agricultural production/yr1.65E+043.50E+033.60E+03 Agricultural residuest dry matter/yr1.80E+003.60E+001.48E+00 Year 2006 3. Case studies

27. Data comparison: National-Regional-Local FlowsUnitItaliaCampaniaLemonOliveGrape Rainfallg/yr7.50E+098.10E+099.11E+096.67E+098.54E+09 Total land croppedha/yr1.00E+00 Fertilizers (N + PO4 + K2O), TOTALg/yr1.08E+051.21E+051.98E+051.40E+051.85E+05 Nitrogen (N)g/yr6.03E+047.05E+048.00E+041.40E+057.50E+04 Phosphate (PO4)g/yr2.63E+043.34E+044.50E+040.00E+005.50E+04 Potassium (K2O)g/yr2.14E+041.71E+047.25E+040.00E+005.50E+04 ElectricityJ/yr1.45E+091.47E+091.33E+090.00E+00 Water for irrigationg/yr1.72E+081.73E+081.31E+092.00E+060.00E+00 Liquid fuelsJ/yr7.00E+091.12E+106.02E+096.19E+097.34E+09 Machinerykg/yr1.58E+011.46E+011.46E+042.55E+041.50E+04 Direct Laborhours/yr1.28E+021.34E+027.00E+026.56E+027.57E+02 Direct Labor/yr1.28E+031.34E+037.00E+036.56E+037.57E+03 Indirect labor (services)/yr5.92E+027.07E+024.18E+031.33E+031.78E+03 Products Mass of agricultural production (dry matter)g d.m./yr7.03E+068.45E+063.15E+062.32E+062.96E+06 Energy content of agricultural productionJ/yr1.14E+111.33E+111.38E+105.94E+103.87E+10 Economic value of agricultural production/yr1.85E+033.68E+031.65E+043.50E+033.60E+03 Agricultural residuest d.m.//yr4.39E-015.28E-011.80E+003.60E+001.48E+00 Year 2006 3. Case studies

28. Results & Discussion

29. Results and Performance Indicators Italy: National case study 4. Results and Discussion

30. National scale over time Results and Performance Indicators 4. Results and Discussion

31. Results and Performance Indicators Regional scale over time 4. Results and Discussion

32. Comparison across scales Results and Performance Indicators 4. Results and Discussion

33. Synergies

34. DECOIN Toolkit

35. ITALY Level n+2 Level n+1 Level n Level n-1 Other Sectors in Italy Agricultural Sector in Italy Other Agricultural Areas Agricultural Sector in Campania OlivesVineyardLemons Other Crops Integration SUMMA - MuSIASEM (Multi-Scale Integrated Analysis Societal Ecosystem Metabolism) 5. Synergies

36. Agricultural sector year 2006 MJ TET GDP = TET THA GDP THA Campania (regional scale)= 6.28 MJ/ Campania = 186 MJ/hr Campania = 27 /hr MJ TET GDP = TET THA GDP THA Italy (National scale) = 10.48 MJ/ Italy = 152 MJ/hr Italy = 14 /hr 5. Synergies

37. MJ TET GDP = TET THA GDP THA Lemon (local scale) = 3.06 MJ/ Lemon = 72 MJ/hr Lemon= 24 /hr Agricultural sector year 2006 MJ TET GDP = TET THA GDP THA Olive (local scale) = 7.76 MJ/ Olive = 41 MJ/hr Olive = 5 /hr MJ TET GDP = TET THA GDP THA Grape (local scale) = 8.69 MJ/ Grape = 41 MJ/hr Grape = 5 /hr 5. Synergies

38. Integration SUMMA-ASA (Advanced Sustainability Analysis) Decomposition CO 2 emissions are determined by CO 2 intensity of the economy (CO 2 /GDP) economic activity (GDP) 5. Synergies

39. ASA decomposition ASA decomposition can be deepened TPES is primary energy supply FEC is final energy consumption CO2/TPES is CO2 intensity of primary energy use TPES/FEC is intensity of energy system FEC/GDP is energy intensity of production 5. Synergies

40. ASA decomposition of emergy indicators from Campania region 6. Synergies

41. Conclusion

42. SUMMAry of results The conventional LCA approach was improved (SUMMA) for Complex Systems assessment (firms, farms, production sectors, economies) Focus can be placed on different steps, time & spatial scales, and development levels Quantitative and qualitative performance indicators are designed, as a basis for policy choices Identification of bottlenecks and limiting factors is made easier Integration with MuSIASEM and ASA allows societal constraints investigation, identification of drivers of change, and finally allows alternative scenario designs. 6. Conclusion

43. Thank you for your attention! amalia.zucaro@uniparthenope.it