Office of Research and Development National Risk Management Research Laboratory Air Pollution Prevention and Control Division June 5, 2013 S. Thorneloe, U.S. EPA Comparing Life-Cycle Impacts of Solid Waste Management Strategies

1 Resource conservation challenge (RCC) Goals –Prevent pollution and promote recycling and reuse of materials –Reduce the use of chemicals at all life-cycle stages –Increase energy and materials conservation 2020 Vision –Reduce wastes and increase the efficient sustainable use of resources RCC encourages move from “waste” management to “materials” management

Three Pillars of Sustainability 2

3 250 million tons of MSW as of 2008 (EPA, 2009) CompositionManagement

Illustration of boundaries for integrated waste management system Transfer Landfill Waste- to-energy Collection Ash Landfill Materials recovery for recycling and composting

Comparison of product & waste LCA Use/Reuse/Maintenance Integrated Waste Management Manufacturing Raw Materials Acquisition Boundary for Product LCA Boundary for LCA of MSW Boundary for Integrated MSW Management Source: Modified from White et al, Integrated Waste Management Manufacturing Raw Materials Acquisition Use/Reuse/Maintenance

6 Flow diagram for materials and waste management Materials Offset Analysis = Recycle process energy & emissions - Virgin process energy & emissions Energy Offset Analysis = Purchased energy & emissions – Generated energy & emissions offset

7 SMAR T Sustainable Materials And Residuals managemenT decision support tool (SMART-DST) Over ~100 studies conducted for regional, community, and national assessments of materials and discards management Assists in decision making to compare existing and new strategies by calculating the full costs, energy, and life-cycle environmental tradeoffs –Can tailor defaults to reflect differences in multiple sectors (i.e., residential, commercial, suburban) –Can identify optimal solutions with respect to cost or environmental emissions such as GHGs, energy, waste diversion targets –Can conduct sensitivity and uncertainty analysis on key model inputs

8 SMART-DST uses LCA Life-cycle methodology accounts for: –Direct emissions such as collection, transport, and waste management facilities (GHG Scope 1) –Indirect emissions from electricity consumption (GHG Scope 2) –Indirect emissions from fuel (e.g., coal extraction and processing) and materials (e.g., landfill liner) production (GHG Scope 3)

9 SMART-DST available to conduct life- cycle analysis for waste planning Computer software provides scientific comparison of options for materials and discards management that is credible, objective, and transparent. The SMART-DST –provides analysis of up to 26 individual materials (i.e., steel, aluminum, glass, paper, plastics) –considers differences in a region’s population density, energy offsets, infrastructure, proximity to facilities and waste composition, collection, and transport –calculates change in cost and environmental emissions as additional materials are included in a recycling program. Options can be interrelated: –Recycling vs waste combustion for paper and plastics –Composting vs landfill gas to energy for food or yard waste

Illustration Comparing Carbon Emissions and Energy Consumption for Plastics Management

Illustration Comparing Carbon Emissions and Energy Consumption for Cardboard Management

12 Outline for conducting a study Determine goals/objectives for study –To increase diversion rate? Decrease GHGs? Expand curbside collection? Determine least cost for discards management? –Boundary and scope definitions Data Collection –Waste generation and composition –Facility design and operating parameters –Transportation modes and distances –Electricity grid mix –Wages, energy prices, materials market prices, etc. Location-specific strategies –Residential and commercial waste –Least-cost and least environmental emissions scenarios Combinations of recycling, yard waste composting and combustion –Alternative strategies to consider “other” factors such as equity, political and economic feasibility, ability to site facility Sensitivity and uncertainty analysis

Example Studies Community –Anderson County, S.C. –Atlanta, Georgia –Edmonton, Alberta –Lucas County, Ohio –Madison, Wisconsin –Minneapolis, Minnesota –Portland, Oregon –Seattle, Washington –Spokane, Washington –Tacoma, Washington –Wake County, N.C. –U.S. EPA’s RTP Facility Regional –Great River Regional Waste Authority, Iowa –California –Delaware –Georgia –Hawaii –New York –Virgin Islands –Washington –Wisconsin –U.S. Navy Region Northwest –Greater Regional Vancouver  National – GHG Study for U.S. Conference of Mayors  Global – Study by the World Bank of 10 different communities of which 8 are in economically developing countries.

14 Summary  DST helps support the goals of the RCC moving us towards materials management - Identifies more efficient and sustainable options - Provides data needed to benchmark current operations and to identify options to improve environmental performance - Provides data to communicate environmental improvements  DST has been used in over 100 studies helping to inform management decisions  Web-accessible DST is available for use!  Next portion of webinar is live demonstration.

15 Media Citations Science Matters – Research at the U.S. EPA – e-matters/april2010/scinews_energy- from-waste.htmhttp://epa.gov/ord/sciencenews/scienc e-matters/april2010/scinews_energy- from-waste.htm New York Times – – ence/earth/13trash.html?hphttp:// ence/earth/13trash.html?hp

16 Selected list of journal publications Kaplan, P. O.; Ranjithan, S. R.; Barlaz, M.A. (2009) Use of Life Cycle Analysis To Support Solid Waste Management Planning for Delaware. Environmental Science and Technology, 43 (5), Kaplan, P. O.; DeCarolis, J.; Thorneloe, S. (2009) Is It Better to Burn or Bury Waste For Clean Electricity Generation? Environmental Science and Technology, 43, (6), Thorneloe, S. A.; Weitz, K.; Jambeck, J. (2007) Application of the U.S. decision support tool for materials and waste management. Waste Management, 27, Jambeck, J., Weitz, K.A., Solo-Gabriele, H., Townsend, T., Thorneloe, S., (2007). CCA-treated Wood Disposed in Landfills and Life-cycle Trade-Offs With Waste-to-Energy and MSW Landfill Disposal, Waste Management, Vol 27, Issue 8, Life-Cycle Assessment in Waste Management. Kaplan, P.O., M.A. Barlaz, and S. R. Ranjithan (2004) A Procedure for Life-Cycle-Based Solid Waste Management with Consideration of Uncertainty. J. of Industrial Ecology. 8(4): Weitz K.A., Thorneloe S.A., Nishtala S.R., Yarkosky S. & Zannes M. (2002) The Impact of Municipal Solid Waste Management on Greenhouse Gas Emissions in the United States, Journal of the Air and Waste Management Association, Vol 52,

17 Available documentation Collection Model –Dumas, R. D. and E. M. Curtis, 1998, “A Spreadsheet Framework for Analysis of Costs and Life-Cycle Inventory Parameters Associated with Collection of Municipal Solid Waste,” Internal Project Report, North Carolina State University, Raleigh, NC. ( ) Transfer Stations – Separation of recyclables and discards –Nishtala, S. and E. Solano-Mora, 1997, “Description of the Materials Recovery Facilities Process Model: Design, Cost and Life-Cycle Inventory,” Project Report, North Carolina State University, Raleigh, NC. ( ) Treatment including refuse derived fuel, waste-to-energy, yard- and mixed-waste composting –Nishtala, S., 1997, “Description of the Refuse Derived Fuel Process Model: Design, Cost and Life-Cycle Inventory,” Project Report, Research Triangle Institute, RTP, NC. –Composting process model: –Harrison, K. W.; Dumas, R. D.; Barlaz, M. A.; Nishtala, S. R., A life-cycle inventory model of municipal solid waste combustion. J. Air Waste Manage. Assoc. 2000, 50, Disposal including traditional and wet landfills and ash landfill –Camobreco, V.; Ham, R; Barlaz, M; Repa, E.; Felker, M.; Rousseau, C. and Rathle, J. Life-cycle inventory of a modern municipal solid waste landfill. Waste Manage. Res –Eleazer, W. E.; Odle, W. S.; Wang, Y. S.; Barlaz, M. A., Biodegradability of municipal solid waste components in laboratory-scale landfills. Environ. Sci. Technol. 1997, 31(3), –Sich, B.A. and M. A. Barlaz, 2000, “Calculation of the Cost and Life Cycle Inventory for Waste Disposal in Traditional, Bioreactor and Ash Landfills,” Project Report, North Carolina State University, Raleigh, NC. ( )

18 Available documentation (Cont.) Background process models to account for energy/electricity consumption and offsets, and remanufacturing of recyclables –Dumas, R. D., 1997, “Energy Consumption and Emissions Related to Electricity and Remanufacturing Processes in a Life-Cycle Inventory of Solid Waste Management,” thesis submitted in partial fulfillment of the M.S. degree, Dept. of Civil Engineering, NC State University. –Energy process model: –Remanufacturing process model: Decision Support Tool, Optimization and Alternative Strategy Generation –Harrison, K.W.; Dumas, R.D.; Solano, E.; Barlaz, M.A.; Brill, E.D.; Ranjithan, S.R. A Decision Support System for Development of Alternative Solid Waste Management Strategies with Life-Cycle Considerations. ASCE J. of Comput. Civ. Eng. 2001, 15, –Solano, E.; Ranjithan, S.; Barlaz, M. A.; Brill, E. D. Life Cycle-Based Solid Waste Management ­ 1. Model Development. J. Environ. Engr. 2002, 128, –Solano, E.; Dumas, R. D.; Harrison, K. W.; Ranjithan, S.; Barlaz, M. A.; Brill, E. D. Life Cycle-Based Solid Waste Management ­ 2. Illustrative Applications. J. Environ. Engr. 2002, 128, –Kaplan, P.O., 2006, “A New Multiple Criteria Decision Making Methodology for Environmental Decision Support,” Doctoral Dissertation, Dept. of Civil Engineering, North Carolina State University. –Manual: –Tool Website: Uncertainty Propagation and Sensitivity Analysis Tools –Kaplan, P. O., 2001, “Consideration of cost and environmental emissions of solid waste management under conditions of uncertainty,” MS Thesis, Dept. of Civil Engineering, North Carolina State University. –Kaplan, P. O.; Barlaz, M. A.; Ranjithan, S. R. Life-Cycle-Based Solid Waste Management under Uncertainty. J. Ind. Ecol. 2004, 8,