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Lowering Barriers to Cost-Effective Restoration Lisa A. Wainger, PhD University of Maryland Center for Environmental Science US EPA Office of Research.

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Presentation on theme: "Lowering Barriers to Cost-Effective Restoration Lisa A. Wainger, PhD University of Maryland Center for Environmental Science US EPA Office of Research."— Presentation transcript:

1 Lowering Barriers to Cost-Effective Restoration Lisa A. Wainger, PhD University of Maryland Center for Environmental Science US EPA Office of Research & Development

2 The Costs and Benefit Analysis What are the best assumptions? 1.Mix of practices affects costs & benefits 2.Site and landscape features affect costs, effectiveness & benefits 3.Ecosystem services included / excluded from analysis affect benefit estimates 4.Program implementation choices affect costs

3 Acknowledgements Analysis primarily drawn from soon to be released report: An Optimization Approach to Evaluate the Role of Ecosystem Services in Chesapeake Bay Restoration Strategies Analysis Team RTI International – Marion Deerhake, George Van Houtven, Robert Beach, Ross Loomis, Mike Gallaher, Dallas Wood Abt Assocates – Isabelle Morin, Lauren Praesel, Viktoria Zoltay, David Mitchell, Ryan Stapler, Elena Besedin EPA Office of Research and Development – Jay Messer, Lisa Wainger, Rob Wolcott, Andrew Almeter Many others contributed ideas, data and information

4 Optimization Approach Key Questions 1.What mix of pollution-control projects provides the least cost way to achieve water quality goals in an impaired watershed 2.How does the consideration of “bonus” ecosystem services affect the desired mix of projects?

5 Summary of Optimization Analysis 1.Establish cost-effectiveness of grey & green practices 2.Evaluate availability of acres for implementation of green practices 3.Develop ecological production functions and benefit functions to value ecosystem services 4.Optimize to select the least-cost mix of practices meeting all 3 TMDL targets with / without bonus ecosystem services 5.Analyze sensitivity to assumptions 6.Quantify cost savings and ecosystem service benefits of alternatives

6 Some Important Caveats Analysis assumptions only partially constrained by current rules and policies Not a comprehensive set of BMPs – e.g., missing CAFOs, erosion control practices Not a comprehensive set of monetized benefits Benefit transfer does not consider changes in supply vs demand ≠ WTP Does not represent all social tradeoffs of choices; does not represent policy recommendations Short-term project = reliance on readily available data; intermediate level of model detail

7 Grey and Green Management / Restoration Practices Included Point Source BMPs POTW Advanced Nutrient Removal Industrial Advanced Nutrient Removal Nonpoint Source Urban Stormwater BMPs Extended Detention Ponds Bio-retention Planters Urban Forest Buffers Urban Grass Buffers Urban Wetlands Nonpoint Source Agricultural BMPs Forest Riparian Buffers Grass Riparian Buffers Conversion to Forest Land Retirement Livestock Exclusion Restored Wetlands Winter Cover Crops No-Till Agriculture Payment for Reducing Fertilizer Application (AFT)

8 What we know: Cost-Effectiveness of BMPs Varies by Location 8 Nitrogen runoff effect on Bay mainstem habitat quality by watershed Source: TMDL Executive Summary

9 How much spatial variability of costs did we capture with readily available data? Basin factors Variable runoff rates (county) Variable BMP removal effectiveness (GM region) Attenuation factors Variable nutrient delivery to Bay by location (HUC) “Effectiveness” factor based on Bay residence time (HUC) Cost Factors Opportunity costs = rental rates (state) Direct implementation costs = reimbursements (county/state) Availability of implementation locations (HUC)

10 Optimization Results Cost-effective Locations of Nitrogen & Sediment Reductions by Land-River Segment (Base Case)

11 Marginal Cost Curve for Achieving N target in Susquehanna Basin N reduction goal = 33.14 M lbs

12 Spatially Averaged Unit Costs Conceal Management Opportunities Marginal Cost ($) (cost of the last unit of nutrient reduction) Total Nutrient Reduction from 1985 Baseline 0 E3 Economies of scale Diminishing Marginal Returns

13 The Geography of Ecosystem Service Benefits 13 1.Where do benefits accrue? headwaters - oceans 2.How effective is the restoration? 3.How many ecosystem services “users” are affected? 4.How much is each service user affected? sensitivity to environmental change substitutability

14 Estuarine and Near-Shore Benefits of Chesapeake Bay TMDLs TMDLs designed to protect: Migratory fish spawning and nursery Shallow-water Bay grass Open-water fish and shellfish Deep-water seasonal fish and shellfish Deep-channel seasonal refuge Resulting water-quality related Ecosystem Service Benefits: Health and safety (+air) Recreational opportunities (swimming, boating, fishing) Commercial fishing Visual and olfactory aesthetics Property value support Non-use benefits of aquatic species / ecosystems Water treatment cost savings

15 Terrestrial and Upstream Ecosystem Service Benefits (Bonus ES) Recreational opportunities - (waterfowl hunting, game hunting, trout fishing, birding, hiking, upstream boating) Aesthetic benefits - (open space, freshwater quality) Health (air quality improvements) Property value support (non-Bay adjacent) Flood risk reduction Climate change risk mitigation (carbon sequestration, GHGs) Amenity-derived economic support Educational support (distributed natural sites) Non-use benefits of species and ecosystems (bog turtle, brook trout) Red = Valued in optimization analysis

16 50 0 100 Wetland Assessment Score Poor Sub- Optimal Optimal Marginal % Sites / Permits 0 Ambrose, et al. 2006 Sources of Benefit Uncertainty: Restoration / BMP Effectiveness

17 Optimization Results Cost Offsets from Ecosystem Services Alternative Scenarios: Base Case & 3a (2:1 offset ratios) $218 M/yr $90 M/yr $1.46 B/yr $1.17 B/yr $1.49 B/yr $1.16 B/yr $301 M/yr $63 M/yr Both Scenarios: Basin level load reductions & 10% transaction costs on offsets Base Case 3a

18 Summary of Cost Offsets from Ecosystem Service Benefits For the “base case” bonus ecosystem services return at least $90M/yr of the $218M/yr gross costs to achieve the TMDL The least net cost solution increases those costs to $310 M/yr, but reduces the net social costs from $128 to $63 M/yr But solutions would result in retirement of approximately 1.7 M acres of working ag land (including half of the cropland in the basin)

19 Value of competing services inform tradeoffs Private Crop Yields Public Ecosystem Services A B

20 Other Results Cost of TMDL Compliance (N loads only) by Geography of Trading Area million $

21 Fine-scale allocation of load reductions reduces ability of credit buyers to find low-cost sellers 21 Nitrogen runoff effect on Bay mainstem habitat quality by watershed Source: TMDL Executive Summary

22 Non-monetized co-benefits The EO targets restoring 58 sub-watersheds to healthy status for brook trout – the base scenario restores 122 sub-watersheds. The 30,000 acre wetland EO strategic target could be met for an additional $6 M/yr or 3% of estimated costs.

23 Improving benefit assessments Identifying where changes in supply are likely to generate benefits % native range preserved Benefit / Utility (population viability) 30% Non-use service benefits are enhanced by improvements in conservation status

24 Improved Efficiency from Joint Production of Multiple Ecosystem Service Benefits As Suggested by Optimization Analysis 0 TMDL Program costs Benefits $X $X + $238 M $300 M Downstream Benefits Only Upstream + Downstream Benefits 24

25 Conclusions Benefits Joint production of upstream + downstream ecosystem services could reduce net program costs – Simple analysis suggests ~40% of costs offset (base case) Quantifying potential changes in ES benefits that can’t be monetized augments the benefits picture Costs Accounting for performance risk greatly increases costs (high model sensitivity to offset/trading ratios) TMDL Program rules can affect costs (e.g., larger areas for offset / trading are likely to reduce costs) Unit costs can be misleading if they hide economies of scale and diminishing marginal returns


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