Lowering Barriers to Cost-Effective Restoration
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Transcript of Lowering Barriers to Cost-Effective Restoration
Lowering Barriers to Cost-Effective Restoration
Lisa A. Wainger, PhDUniversity of Maryland Center for
Environmental ScienceUS EPA Office of Research & Development
The Costs and Benefit AnalysisWhat are the best assumptions?
1. Mix of practices affects costs & benefits2. Site and landscape features affect costs,
effectiveness & benefits3. Ecosystem services included / excluded from
analysis affect benefit estimates4. Program implementation choices affect costs
AcknowledgementsAnalysis 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
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?
Summary of Optimization Analysis
1. Establish cost-effectiveness of grey & green practices2. Evaluate availability of acres for implementation of
green practices3. Develop ecological production functions and benefit
functions to value ecosystem services4. Optimize to select the least-cost mix of practices
meeting all 3 TMDL targets with / without bonus ecosystem services
5. Analyze sensitivity to assumptions6. Quantify cost savings and ecosystem service benefits
of alternatives
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
Grey and Green Management / Restoration Practices Included
Point Source BMPs• POTW Advanced Nutrient
Removal• Industrial Advanced
Nutrient RemovalNonpoint 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
Nitrogen runoff effect on Bay mainstem habitat quality by watershed
Source: TMDL Executive Summary
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)
Optimization ResultsCost-effective Locations of Nitrogen & Sediment Reductions by Land-River Segment (Base Case)
Marginal Cost Curve for Achieving N target in Susquehanna Basin
0 5 10 15 20 25 30$0.00$0.50$1.00$1.50$2.00$2.50$3.00$3.50$4.00$4.50$5.00
AgUrbanPoint
N Reduction (millions of lbs)
Cost
($/l
b)
N reduction goal = 33.14 M lbs
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
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
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
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
50
0 100
Wetland Assessment Score
Poor Sub- Optimal
OptimalMarginal
% S
ites
/ Pe
rmits
0
Ambrose, et al. 2006
Sources of Benefit Uncertainty: Restoration / BMP Effectiveness
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 Base Case3a 3a
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)
Value of competing services inform tradeoffs
Private Crop Yields
Public Ecosystem
Services
A
B
Other ResultsCost of TMDL Compliance (N loads only)
by Geography of Trading Area
Tributary Bay-wide0
50
100
150
200
250
300
350
400
450
UrbanAgriculturePoint Source
million $
21
Fine-scale allocation of load reductions reduces ability of credit buyers to find low-cost sellers
Nitrogen runoff effect on Bay mainstem habitat quality by watershed
Source: TMDL Executive Summary
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.
Improving benefit assessmentsIdentifying 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
ConclusionsBenefits• 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