1. Waste Management Planning in Two Areas of Middle and South of Italy, based on Material and Substance Flow Analysis Umberto ARENA a,b and Fabrizio Di Gregorio a,b a Department of Environmental, Biological and Pharmaceutical Sciences and Technologies – Second University of Naples, Caserta, ITALY b AMRA s.c.a r.l. – Analysis and Monitoring of Environmental Risk, Napoli, ITALY

2. A SUSTAINABLE WM PLANNING The decision making process over WM policy is a complex issue, which has to evaluate the environmental impacts, the technical aspects, the implementation and operating costs of each specific treatment and disposal option as well as the social implications. The process often involves accurate as well as missing data, expert evaluations as well as ill- defined and changing public opinions, and sometimes it is guided by preconceptions for or against a specific WM solution. The complexity of this framework greatly raised in the last two or three decades, as a consequence of increasing generation and complexity of solid wastes.

3. 11 Elements 15 Elements 60 Elements Growing complexity of goods (and waste) composition (e.g. information products ) Source: T. McManus, Intel Corp., 2006 (Courtesy T. Graedel) INTRINSIC TROUBLES for SUSTAINABLE RECYCLING

4. A SUSTAINABLE WM PLANNING A comprehensive and systemic, goal-oriented approach is needed to design an integrated and sustainable WM system. There is a general accordance about the final goals: i) protection of human health and the environment; ii) conservation of resources, such as materials, energy, and land; iii) after-care-free waste management, meaning that neither landfills nor WtE, recycling or other treatments leave problems to be solved by future generations; iv) economic sustainability of the whole cycle of MSW management, also in a welfare economy perspective.

5. In this framework of increasing generation and complexity of solid waste composition, the combination of two valuable tools, the MFA and the SFA, together with an environmental assessment method such as LCA, can efficiently support waste management decisions on both strategic and operating levels. In particular, it is greatly attractive the SFA ability to connect sources, pathways, and intermediate and final sinks of each chemical species in a specific process, as demonstrated by its utilization in the assessment of thermal treatments, recycling options and waste management scenarios. A SUBSTANCE ORIENTED APPRAOCH

6. System definition On site data and waste process data ( waste amount and composition, air and water emissions, co-products, etc.) Technical tools (material balances, energy balance, allocation models, etc.) Analytical tools Material Flow Analysis Substance Flow Analysis Life Cycle Analysis Life Cycle Costing Health RA Environmental RA WM Planning AIM of the WM PLANNING PROCEDURE

7. WASTE MANAGEMENT SCENARIOS and INPUT DATA

8. The waste management system is defined and developed according to: 1. minimize use of landfill and ensure that no waste that is biologically active or that contains mobilizable hazardous substances is landfilled 2. minimize operations entailing excessive consumption of raw materials and energy without yielding a real environmental advantage 3. maximize recovery of materials 4. maximize energy recovery, given that, in a LCA approach, energy recovery from waste allows decreasing consumption of fossil fuels and of overall emissions with respect to all energy conversion systems. A SCENARIO ANALYSIS

9. WM systems that are operating successfully worldwide demonstrated that: no one process is suitable for all waste streams no single waste management practice can handle the full array of waste types. The defined WM scheme should then utilize each of the fundamental waste management options for the extent that is adequate to the specific catchment area characteristics and compatible with the technical, economic and environmental performance of the specific option. They should include only technologies that are state-of- the-art and have already proven high reliability and sustainability, with known total costs for treatment and aftercare. A SCENARIO ANALYSIS

10. THE MSW WM SCHEME

11. MSW COMPOSITION MSW composition %C, %Cl, %F, %H, %O, %N, %S, % Cd, mg/kg Cr, mg/kg Hg, mg/kg Pb, mg/kg ash, % moisture, % LHV, MJ/kg Organic fraction 35.015.490.200.002.5113.620.760.031.80120.057114.8962.494.85 Paper25.030.970.110.004.6534.070.370.031.90250.047117.8022.0010.84 Glass6.00.430.030.020.011.080.870.132.603700.00743096.431.00-0.02 Plastics15.060.610.670.009.298.210.720.0416.001200.0721706.4514.0025.63 Metals3.00.420.180.010.020.831.040.084.408000.23230096.431.00-0.02 Aluminum1.00.420.180.010.020.831.040.080.95800.263796.431.00-0.02 Wood and textiles 4.039.320.050.005.1433.161.530.082.25197.50.027220.52.7418.0014.92 Bulky waste and WEEE 11.021.970.520.003.5616.740.940.1457.006301.846023.6332.508.06 TOTAL100.026.290.270.004.0317.780.730.0510.2152.70.3186.717.033.99.7

12. THE THREE MSW WM SCENARIOS Waste fractions Organic fraction PaperGlassPlasticsMetalsAluminum Wood + Textiles Bulky waste and WEEE Total in MSW, %35.025.06.015.03.01.04.011.0100 SCENARIO SSL 35% Interception Efficiency, % 40.044.055.025.030.0 15.010.0 35% Separate Collection Waste, t/d140.0110.033.037.59.03.06.011.0349.5 Unsorted Residual Waste, t/d210.0140.027.0112.521.07.034.099.0650.5 SCENARIO SSL 50% Interception Efficiency, % 65.050.065.045.035.0 20.017.5 50% Separate Collection Waste, t/d227.5125.039.067.510.53.58.019.3500.3 Unsorted Residual Waste, t/d122.5125.021.082.519.56.532.090.8499.7 SCENARIO SSL 65% Interception Efficiency, % 80.065.090.060.055.0 25.028.2 65% Separate Collection Waste, t/d280.0162.554.090.016.55.510.031.0649.5 Unsorted Residual Waste, t/d70.087.56.060.013.54.530.079.0350.5

13. THE COMPOSITION of SSC and URW SSC: Source Separation and Collection URW: Unsorted Residual Waste

14. MFA and SFA of WM OPTIONS

15. RECYCLING CHAIN – sorting&recycling residues MSW fractions SSL 35%SSL 50%SSL 65% SR, %RR, %SR+RR, %SR, %RR, %SR +RR, %SR, %RR, %SR +RR, % Organic fraction 20.09.725.722.09.727.624.09.729.5 Paper 5.011.015.46.511.016.88.011.018.1 Glass 6.00.06.014.00.014.016.00.016.0 Plastics 35.025.551.640.025.555.344.025.558.3 Metals 6.09.514.96.09.514.96.09.514.9 Aluminum 15.016.529.015.016.529.015.016.529.0 Wood and textiles 13.55.017.813.55.017.813.55.017.8 Bulky waste and WEEE 10.0 19.012.0 22.614.0 26.0 TOTAL 14.79.522.8 19.09.827.0 20.9 9.928.8

16. RECYCLING CHAIN MFA for plastic, metals and aluminium

17. RECYCLING CHAIN MFA for paper

18. INTEGRATED AD TREATMENT MFA for organic fraction

19. THERMAL TREATMENT Combustion MFA for unsorted residual waste

20. THERMAL TREATMENT Gasification MFA for unsorted residual waste

21. THERMAL TREATMENT Combustion and Gasification SFA for zinc element

22. MFA and SFA ofALTERNATIVE WM SCENARIOS

23. MFA of WM SCENARIOS

24. Scenario SSL 35%SSL 50%SSL 65% Mass of Waste to Landfill, % entering MSW from sorting&recycling chain 0.71.22.2 0from biological treatment 3.66.38.2 from thermal treatment 17.013.810.7 Total 21.3 20.9 Volume of Waste to Landfill, m 3 /d (% entering MSW ) from sorting&recycling chain 10.820.332.8 from biological treatment 60.0104.7137.5 from thermal treatment 101.482.464.0 Total 172.2 (8.3) 207.4 (10.0) 234.3 (11.2) Energy Net Production, GWh/y Electric energy 125.8108.192.4 Thermal energy (in cogeneration) 312.9264.6210.8 Total 438.7372.7303.2 Lost and Available Feedstock Energy, GWh/y (% entering waste energy ) converted in electric and thermal energy 770.3 (78.1) 691.1 (70.1) 612.5 (62.1) lost in landfill 44.6 (4.5)68.5 (6.9)84.9 (8.6) Recovered Materials, t/d (% entering MSW ) Glass 31.033.545.4 Plastics 19.532.541.2 Metals 12.817.627.8 Aluminum 2.73.45.3 Paper 93.0104.0133.1 Textiles 2.5 3.3 4.1 Wood 4.26.28.7 Compost 24.338.546.1 Total 190.0 (19.0) 239.0 (23.9) 311.7 (31.2)

25. WM SCENARIOS feedstock energy analysis 6.9% 70.1% 23.0%

26. SFA of WM SCENARIOS – C analysis 8.4% 68.4% 23.1%

27. SFA of WM SCENARIOS – C analysis Scenario SSL 35%SSL 50%SSL 65% Carbon to Landfill, t/d (% input C ) from sorting&recycling chain 0.8 (0.3)1.4 (0.5)2.2 (0.8) from biological treatment 11.0 (4.2)18.3 (7.0)23.0 (8.7) from bottom ash 2.0 (0.8)1.7 (0.6)1.5 (0.6) from APC residues 0.9 (0.3)0.8 (0.3)0.7 (0.3) Total14.7 (5.6)22.2 (8.4)27.4 (10.4) The amount of greenhouse gas is reduced as a consequence of high recycling rates (which in turn depend on the SSL and the best practices of separate collection and recycling process): the carbon that is reutilized in the form of compost (from integrated biological treatment), polymers (from plastic recycling chain) and cellulose (from paper recycling chain) is not landfilled and will not contribute to greenhouse gases. The energy produced by thermal treatment and, for a lesser extent, by the AD process, replaces other energy sources so consequently reducing the related environmental burdens. Moreover, about a half of the energy produced by WtE and AD plants derives from non fossil fuels, and then does not contribute to climate change.

28. SFA of WM SCENARIOS – Cd analysis Cadmium to Landfill, g/d (% input Cd )SSL 35% SSL 50%SSL 65% from sorting&recycling chain 898 (8.9)1,577 (15.6)2,536 (25.1) from biological treatment 249 (2.5)405 (4.0)499 (4.9) partial total1,147 (11.4)1,983 (19.6)3,035 (30.0) from bottom ash 831 (8.2)721 (7.1)589 (5.8) from APC residues 7,477 (74.0)6,488 (64.2)5,293 (52.4) Total9,455 (93.6)9,193 (91.0)8,917 (88.3) Cadmium in recycled product, g/d (% input Cd ) Glass81 (0.8)87 (0.9)118 (1.2) Plastics312 (3.1)521 (5.2)660 (6.5) Metals56 (0.6)78 (0.8)122 (1.2) Aluminum3 (0.03) 5 (0.05) Paper177 (1.8)198 (2.0)253 (2.5) Textiles5 (0.05)7 (0.07)9 (0.09) Wood4 (0.04)6 (0.06)8 (0.08) Compost2 (0.02)4 (0.04)5 (0.05) Total 640 (6.3)903 (8.9)1,179 (11.7)

29. SFA of WM SCENARIOS – Pb analysis Lead to Landfill, g/d (% input Pb ) SSL 35%SSL 50%SSL 65% from sorting&recycling chain 10,181 (5.5)16,316 (8.9)26,699 (14.5) from biological treatment 1,210 (0.7)1,980 (1.1)2,454 (1.3) partial total11,391 (6.2)18,296 (10.0)29,152 (15.8) from bottom ash 64,943 (35.3)51,778 (28.1)26,414 (14.4) from APC residues 53,064 (28.8)42,308 (23.0)21,583 (11.7) Total 129,397 ( 70.3) 112,382 ( 61.1) 77,150 ( 41.9) Lead in recycled product, g/d (% input Pb ) Glass13,339 (7.2) 14,422 (7.8)19,505 (10.6) Plastics3,316 (1.8)5,532 (3.0)7,008 (3.8) Metals29,334 (15.9)40,533 (22.0)63,922 (34.7) Aluminum6,137 (3.3)7,878 (4.3)12,192 (6.6) Paper1,023 (0.6)1,144 (0.6)1,464 (0.8) Textiles217 (0.1)289 (0.2)362 (0.2) Wood837 (0.5)1,241 (0.7)1,743 (0.9) Compost287 (0.2)454 (0.2)544 (0.3) Total 54,489 (29.6)71,493 (38.9)106,740 (58.0)

30. WM SCENARIOS comparison

32. A significant reduction in the requirement of landfill volume can only be achieved if the URW is sent to waste-to energy process. The scenarios with high energy recovery provide that A significant reduction in the requirement of landfill volume can only be achieved if the URW is sent to waste-to energy process. The scenarios with high energy recovery provide that energy produced by carbon oxidation is full utilized energy produced by carbon oxidation is full utilized inorganic materials are mainly concentrated in the residues of WtE plants inorganic materials are mainly concentrated in the residues of WtE plants hazardous organic compounds are completely destroyed. hazardous organic compounds are completely destroyed. The results suggest that the optimal source separation level should be lower than 65%, on the basis of the high amounts of toxic substances that can be found in the recycled products as well as the huge quantities of sorting and recycling residues, the difficulty of obtaining very high interception levels and the remarkable costs. The results suggest that the optimal source separation level should be lower than 65%, on the basis of the high amounts of toxic substances that can be found in the recycled products as well as the huge quantities of sorting and recycling residues, the difficulty of obtaining very high interception levels and the remarkable costs. CONCLUSIONS

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34. A procedure for goal-oriented WM planning has been proposed to provide a knowledge basis for MSW management decision makers. A procedure for goal-oriented WM planning has been proposed to provide a knowledge basis for MSW management decision makers. It is based on the extensive utilization of MFA and SFA, in the framework of a LCA approach and together with a scenario analysis. The proposed procedure appears as a powerful tool- box to compare alternative waste management technologies and scenarios, even though the obtainable results are just a part of the input data to the decision making process, which should further take into account a variety of economic and social aspects The proposed procedure appears as a powerful tool- box to compare alternative waste management technologies and scenarios, even though the obtainable results are just a part of the input data to the decision making process, which should further take into account a variety of economic and social aspects. CONCLUSIONS

35. The study shows the benefits afforded by the introduction of high quality household source separation and collection, biological treatment of the organic fraction coming from this separate collection and thermal treatment of unsorted residual waste: landfill mass and volume are drastically reduced, greenhouse gas emissions are reduced, toxic organic materials are mineralized, heavy metals are concentrated in a small fraction of the total former MSW volume, and the accumulation of atmophilic metals in the APC residue allows new recycling schemes to be designed for metals. The study shows the benefits afforded by the introduction of high quality household source separation and collection, biological treatment of the organic fraction coming from this separate collection and thermal treatment of unsorted residual waste: landfill mass and volume are drastically reduced, greenhouse gas emissions are reduced, toxic organic materials are mineralized, heavy metals are concentrated in a small fraction of the total former MSW volume, and the accumulation of atmophilic metals in the APC residue allows new recycling schemes to be designed for metals. The results also indicate that the MBT plant is a not sustainable choice, particularly in a catchment area where the landfill volume must be saved as much as possible. The results also indicate that the MBT plant is a not sustainable choice, particularly in a catchment area where the landfill volume must be saved as much as possible. CONCLUSIONS