Environmentally Impaired Property
Transaction Analysis
Combining Decision Trees and Monte Carlo Simulation
Timothy Havranek and Poh Boon Ung
October 2007
Agenda
• Background Information
• Modeling Process
• Decision Tree
• Results
Project Background and Objective
• Estimate probable remediation costs
• Work in support of purchase negotiations of an environmentally impaired
property
• Client is a property development company:
– Would acquire liability for historical environmental impacts
– Seeking strategic plan for least cost remediation in light of
uncertainties
– Planned to use estimate in support of lowering purchase offer
• Current property owner had filed Chapter 11 bankruptcy procedures
which complicated the negotiation process
Site Background
• Property was former metals processing plant
• Soil, groundwater, surface water, and wetlands impacted by lead,
arsenic and chromium
• Groundwater also impacted by petroleum hydrocarbons
• Property is over 150 acres in size and located near a major river
• Property could be redeveloped for industrial, commercial, or
municipal use
• Current owner under a consent order to perform environmental
cleanup
Decision Analysis Process
Decisi
on
Proces
s
Evaluation
&
Framin
g
Modelin
g
Sensitivity
Analysis
Decisio
n
Action
Plan
Framing Meeting for QDA
Site
Background
Stakeholder
Analysis
Action Items
Strategies
Shared
Vision of Path
Forward
Chance Events
Multi-Criteria
Analysis
Current Policies
Decisions
& Choices
Potential Remedial Alternatives
Groundwater
Soil
Surface Water
Free Product
Wetlands
Impermeable Wall
Soil / 6" Asphalt Cap
Dredge Basin
Trench Skimmer
System
Restoration
Reactive Barrier Wall
Engineered Cap
Dual Phase
Extraction System
Mitigation
Model Structure
• Capital and Operations & Maintenance (O&M) costs were
estimated using standard engineering costs forms
– Pert Distributions used to estimate uncertainties in
quantities, unit prices, installation year, and O&M durations
• Engineering costs sheets were linked to 30-year cash flow
model for each remedial technique
• Net Present Value for each remedial technique linked decision
tree and Monte Carlo simulation model
Benefits of Decision Tree
• Visual representation of available choices
• Valuable communication tool
• Helps organize alternatives
• Provides a working map of the project strategy
Estimating Individual Cost Components
Item
Description
Unit
Quant.
MIN
Quant.
ML
Quant.
MAX
Distribution
Unit Price
MIN
Unit Price
ML
Unit Price
MAX
Distribution
TOTAL
Capital Costs
1
Dewatering Control
Slurry Walls
Reactive Gates - Reactive Media
Reactive Gates - Sand
T&D of excavated material
Misc. Disposal
Day
50
100
150
100
$2,000
$2,000
$2,000
$2,000
$200,000
SF
18000
52500
67500
49250
$20
$25
$30
$25
$1,231,250
Ton
500
1500
1750
1375
$400
$600
$800
$600
$825,000
Ton
550
1650
1925
1513
$11
$11
$11
$11
$16,643
Ton
70
200
250
187
$120
$160
$200
$160
$29,920
LS
1
1
1
1
$10,000
$10,000
$10,000
$10,000
$10,000
Operation and Maintenance (O&M) Costs
Unit
Duration
MIN
Duration
ML
Duration
MAX
Distribution
Annual
Cost
Annual
Cost
Annual
Cost
Distribution
10
Replacement of PRB
YR
1
1
1
$1,612,000
$1,612,000
11
Monitoring
YR
30
30
30
$60,000
$55,000
2
3
4
5
6
7
8
9
Total Capital Costs
12
13
$2,312,813
YR
YR
$1,612,000 $1,612,000
30
$50,000
$55,000
TOTAL
Root of Decision Tree:
Groundwater and Soil Components
Offer Soil /Asphalt Cap
30.0%
Yes
$3.3
TRUE
Soil Remediation
$14.5
Engineered Cap
FALSE
$7.2
TRUE
Impermeable Wall
Impermeable Wall Fails
$3.8
$12.2
70.0%
No
$0
Groundwater Remediation
$12.2
Reactive Barrier
FALSE
$5.3
Link to Soil Rem
$12.7
Link to Soil Rem
$11.2
Middle Portion of Tree:
Soil and Surface Water Remediation
TRUE
Dredge Basin
$0.7
40.0%
Yes, Install
$4.5
Offer Soil /Asphalt Cap
TRUE
Surface Water Remediation
$12.8
Approved by Regulators
$14.5
No, Engineered Cap
60.0%
$7.2
Soil Remediation
$14.5
Engineered Cap
FALSE
$7.2
Link toSurface Water Rem
15.5
Link to Surface Water Rem
$15.54
Tree Terminal Nodes:
Wetland Issues
Yes
Yes - Peform Mitigation
50.0%
$0.0
Mitigation Approved?
$12.8
No - Perform Restoration
Wetlands Remediation
$12.8
Restoration
FALSE
0.00%
$0.3
$12.9
$0.3
$13.1
75.0%
3.04%
$0.0
$12.7
$12.8
No
TRUE
1.01%
Restoration Req. after Mit.
$0.2
Mitigation
25.0%
50.0%
4.05%
$0.3
$12.9
PrecisionTree / @RISK Settings
Net Present Value: Frequency Histogram
*
Distribution based on values of one sampled path per iteration and decisions follow current optimal path
X <=$9.0 M
5%
10%
X <=$17.6 M
95%
Mean = $12.4 Million
9%
8%
Probability
7%
6%
5%
4%
3%
2%
1%
0%
$6
$8
$10
$12
$14
Cost in $ Millions
$16
$18
$20
$22
Net Present Value: Risk Profile
*
Distribution based on values of one sampled path per iteration and decisions follow current optimal path
X <=$9.0 M
5%
100%
X <=$17.6 M
95%
Mean = $12.4 Million
90%
Cumulative Probability
80%
70%
60%
50%
40%
30%
20%
10%
0%
$6
$8
$10
$12
$14
Cost in $ Millions
$16
$18
$20
$22
Output Statistics (cost in millions)
*Results based on values of one sampled path per iteration and decisions follow current optimal path
Mean
Standard Deviation
Mode
5.0%
10.0%
15.0%
45.0%
50% (Median)
55.0%
85.0%
90.0%
95.0%
$12.4
$2.5
$12.3
$9.0
$9.3
$9.6
$12.0
$12.2
$12.4
$15.3
$16.0
$17.6
Net Present Value: Frequency Histogram
*
Distribution based on values of one sampled path per iteration and decisions may change (based on expected values)
60%
X <=$11.2 M
5%
X <=$13.7 M
95%
Mean = $12.4 million
50%
Probability
40%
30%
20%
10%
0%
$10
$11
$12
$13
$14
Costs in $ Millions
$15
$16
$17
Output Statistics (cost in millions)
* Results
based on values of one sampled path per iteration and decisions may change (based on expected values)
Mean
Standard Deviation
Mode
5.0%
10.0%
15.0%
45.0%
50% (Median)
55.0%
85.0%
90.0%
95.0%
$12.4
$0.8
$12.1
$11.2
$11.4
$11.6
$12.2
$12.3
$12.4
$13.2
$13.4
$13.7
Net Present Value: Frequency Histogram
* Distribution based on expected value of model per iteration and decisions follow current optimal path
X <=$11.3
5%
14%
X <=$13.8
95%
Mean = $12.5 Million
12%
Probability
10%
8%
6%
4%
2%
0%
$10
$11
$12
$13
Cost in $ Millions
$14
$15
$16
Output Statistics (cost in millions)
* Results based on expected value of model per iteration and decisions follow current optimal path
Mean
Standard Deviation
Mode
5.0%
10.0%
15.0%
45.0%
50% (Median)
55.0%
85.0%
90.0%
95.0%
$12.5
$0.8
$12.5
$11.3
$11.5
$11.7
$12.3
$12.4
$12.5
$13.3
$13.5
$13.8
Sensitivity Analysis on Impermeable Wall Failure Probability
Expected NPV $ Millions
$15
$14
$13
$12
$11
$10
10%
20%
30%
40%
50%
60%
70%
Probability of Impermeable Wall Failure
1 : Impermeable Wall
2 : Reactive Barrier
80%
90%
13.5
13-13.5
13
12.5-13
12-12.5
12.5
11.5-12
12
11-11.5
11.5
81%
63%
46%
28%
10%
11
28%
10%
Cap Approval
Probability
46%
63%
10.5
81%
Expected NPV
$ Millions
Two Way Sensitivity Analysis on Probabilities
10.5-11
Impermeable
Wall Failure
Probability
Results and Conclusions
• Important to apply appropriate settings in modeling process
– Internal management and understanding
– Negotiation process
• Sensitivity analysis useful to identify decision break-points
• Results are being used in negotiations process; client is actively using the results
in negotiations to buy the site
• Decision tree analysis assisted in:
– Identifying optimum strategy
– Communicating path forward
– Determining the response and potential effects to chance outcomes
• Combination of Monte Carlo simulation and decision tree analysis provides
additional insights into range of potential outcomes