green infrastructure – cost effectiveness at different...

Green Infrastructure – Cost Effectiveness at Different Scales

Franco Montalto, P.E. PhD

1

Low Impact Development in Houston, TXRice University, February 26, 2013

1767 2013

Gowanus CanalBrooklyn, NY

Superfund site10 CSOs on the canal1.1 million m3/y (290 MGY)50 events per year

Montalto et al 2007

Research Question

Can LID cost-effectively reduce CSOs to the Gowanus Canal?

4

Observation #1

For property owners, LID retrofits appeared more

expensive than conventional building improvements

5

Standard Turf

Rain Garden

Lower Cost Option

Total Initial Cost $84 $2,800 Standard Turf

Annual O&M Cost $36 $136 Standard TurfTotal Present Value

(discounted LCC including initial, periodic and salvage value) $649.06 $978.67 Standard Turf

Rain garden is more expensive in terms of initial, O&M, and TPV

Data derived from : 2009 Green Values National Stormwater Calculator (greenvalues.cnt.org), WERF tool, considering 50 year planning period

Turf vs Rain Garden(20 ft x 20 ft patch of private property)

Porous vs. Ordinary Concrete Sidewalk (500 ft x 10 ft segment of public ROW)

Porous pavement is more expensive in terms of initial, O&M, and TPV

Data derived from : 2009 Green Values National Stormwater Calculator (greenvalues.cnt.org), WERF tool, considering 50 year planning period

Standard Sidewalk

Porous Concrete

Lower Cost Option

Total Initial Cost $25,950 $30,000 Standard

Annual O&M Cost $145 $800 StandardTotal Present Value

(discounted LCC including initial, periodic and salvage value) $24,781 $50,803 Standard

Observation #2

New policies, cost-sharing arrangements, and/or

incentives will be necessary for LID to be widely implemented.

Sample Policy* (with carrots)• Local water utility provides grant to private

property owners to install LID on their property

• Grant amount = difference in life cycle costs between the LID and conventional surface

ex: homeowner pays for conventional roof but gets a green roof

* Most water utilities today are focusing LID investments on public ROW, not private property. LID on private property most often comes about through smaller grants or new regulations.

LID ScenariosOH007 sewershed, Gowanus Canal

Montalto et al 2007

0%

10%

20%

30%

40%

50%

0 10 20 30 40 50 60 70 80 90

Cost (Millions of $)

% R

educ

tion

in C

SO D

isch

arge

Small Tank

Medium Tank

Large Tank

Porous Pavements

Urban Brooks

Green Roofs

Comparison of “grey” and “green” approaches (implemented separately)

Montalto et al 2007

0%

10%

20%

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0 10 20 30 40 50 60 70 80 90

Cost (Millions of $)

% R

educ

tion

in C

SO D

isch

arge

Small Tank

Medium Tank

Large Tank

Porous Pavements

Urban Brooks

Green Roofs

Comparison of “grey” and “green” approaches (implemented separately)

Montalto et al 2007

Limited availability of implementation sites

0%

10%

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30%

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50%

0 10 20 30 40 50 60 70 80 90

Cost (Millions of $)

% R

educ

tion

in C

SO D

isch

arge

Small Tank

Medium Tank

Large Tank

Porous Pavements

Urban Brooks

Green Roofs

Comparison of “grey” and “green” approaches (implemented separately)

Montalto et al 2007

Green roofs cost more than a small tank

0%

10%

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0 10 20 30 40 50 60 70 80 90

Cost (Millions of $)

% R

educ

tion

in C

SO D

isch

arge

Small TankMedium Tank

Large Tank

Porous Pavements

Urban Brooks

Green Roofs

Montalto et al 2007

Comparison of “grey” and “green” approaches (implemented together)

0%

10%

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50%

0 10 20 30 40 50 60 70 80 90

Cost (Millions of $)

% R

educ

tion

in C

SO D

isch

arge

Small TankMedium Tank

Large Tank

Porous Pavements

Urban Brooks

Green Roofs

Montalto et al 2007

Comparison of “grey” and “green” approaches (implemented together)

LID appears more cost-effective

0%

10%

20%

30%

40%

50%

0 10 20 30 40 50 60 70 80 90

Cost (Millions of $)

% R

educ

tion

in C

SO D

isch

arge

Small TankMedium Tank

Large Tank

Sensitivity on Cost & Performance

Increasingly cost effective systems

Less cost effective systems

Montalto et al 2007

17

C LID System Installation Cost ($/m2) 0.1 0.3 0.5

172 194

Green Roof

215 54 / 32 65 / 43

Porous Surface (concrete/asphalt)

75 / 54 110 146

Rainwater Harvesting (unit: linear m)

183

LID is more cost effective than all tanks LID is cost effective when implemented after constructing a small tank LID is cost effective when implemented after constructing a medium sized tank LID might only be cost effective after construction of a large tank

Shading Key

LID Cost MetricLID Performance metric

Sensitivity Analysis

Urban brooks

18

C LID System Installation Cost ($/m2) 0.1 0.3 0.5

172 194

Green Roof

215 54 / 32 65 / 43

Porous Surface (concrete/asphalt)

75 / 54 110 146

Rainwater Harvesting (unit: linear m)

183

Outcome #1: LID is more cost effective than all tanks

0%

10%

20%

30%

40%

50%

0 10 20 30 40 50 60 70 80 90

Cost (Millions of $)

% R

educ

tion

in C

SO D

isch

arge

Small TankMedium Tank

Large Tank

Urban brooks

19

C LID System Installation Cost ($/m2) 0.1 0.3 0.5

172 194

Green Roof

215 54 / 32 65 / 43

Porous Surface (concrete/asphalt)

75 / 54 110 146

Rainwater Harvesting (unit: linear m)

183

Outcome #2: LID cost effective after a small tank

0%

10%

20%

30%

40%

50%

0 10 20 30 40 50 60 70 80 90

Cost (Millions of $)

% R

educ

tion

in C

SO D

isch

arge

Small TankMedium Tank

Large Tank

Urban brooks

20

C LID System Installation Cost ($/m2) 0.1 0.3 0.5

172 194

Green Roof

215 54 / 32 65 / 43

Porous Surface (concrete/asphalt)

75 / 54 110 146

Rainwater Harvesting (unit: linear m)

183

Outcome #3: LID cost effective only after med-large tanks

0%

10%

20%

30%

40%

50%

0 10 20 30 40 50 60 70 80 90

Cost (Millions of $)

% R

educ

tion

in C

SO D

isch

arge

Small TankMedium Tank

Large Tank

Urban brooks

The next generation of research questions

• Hydrologic Effectiveness: o How well will ultra-urban LID systems actually be able to

reduce runoff?

• Scaling Up: o What specific challenges need to be overcome for LID to

be cost effective at the watershed scale?

Hydrologic Effectiveness

GI Monitoring NetworkThe Sustainable Water Resource Engineering Lab at Drexel University

New York City sites Philadelphia sites

Nashville Greenstreet(Queens, NY)

Bioretention Bed #1 = 145 m2 (1560 ft2)Total catchment area = 475 m2 (5113 ft2)Hydraulic loading ratio = 3:1Curbcut inletOverflow to catchbasinLocal soils are sandy

26

Nashville GreenstreetPerformance during Superstorm Sandy

• 33 mm (1.3 in) rain measured onsite

• 147 m3 (39,000 gallons) of street and sidewalk runoff (~10x as much as expected)

Cumulative rain

Flow through flume

27

Nashville GreenstreetPerformance during Superstorm Sandy

• Negligible ponding• No overflow to sewer

2828

Nashville GreenstreetPerformance during Superstorm Sandy

• Several periods of rapid infiltration detected in lysimeter

• Virtually all of the 152 m3 (40,101 gallons) of rain and runoninfiltrated

29

Nashville GreenstreetPerformance during Superstorm Sandy

Outlier (30 cm)

• Upper soils got wet, then drained by gravity, with further evaporation during subsequent 6 day dry spell

• Very small impact on VMC below 30 cm

30

Nashville GreenstreetPerformance during Superstorm Sandy

• Small (5 cm) but detectable temporary increase in regional water table elevation

• After peak rain intensity, water table drops (as quickly as it rose)

31

Nashville GreenstreetPerformance during Hurricane Irene

• 163 mm (6.4 in) rain measured onsite

• Greater ponding depths observed

• Overflows brief• Infiltration still rapid

Cumulative rain

Ponding depth

Two brief periods of overflow

1009080706050403020100Ann

ual P

erce

nt re

tent

ion

High performance(80-100%)

Medium performance(30-80%)

Low performance(20-30%)

All monitored GreenstreetsAnnual percent retention

All Greenstreets(20-100%)

Variability due to:1) Precipitation amount &

distribution2) Inlet efficiency3) Engineered volume of

surface depressions4) Infiltration capacity5) Hydraulic loading ratio

Time (two months)

Lysi

met

er M

ass

Alley Pond Park (ecological reference)

Colfax (surrounded by curb)

Nashville (catchment:bioretention ratio = 3:1)

Greenstreet ComparisonsSite-to-site and Site-to-park

Time (two months)

Lysi

met

erM

ass

Evaporation = reduction in mass over dry spells

Nashville shows the greatest reduction in mass (e.g. accelerated evaporation)

Annual averages:Nashville 2.3 mm/dColfax: 1.96 mm/dAlley Pond: 0.58 mm/d

By irrigating with stormwater we can accelerate ET over reference conditions, (accelerating heat loss as well since 1 gm = 595 calories)

Greenstreet ComparisonsSite-to-site and Site-to-park

VegetatedCourtyard

Backyard

Urban Park

Courtesy of USDA NRCS

Other permeable surfacesConventional urban green spaces

Courtesy of Tatiana Morin

Courtesy of Tatiana Morin

Without guards With guards

Other permeable surfacesTree pits

Porous Asphalt

Porous Rubberized

Safety Materials

PorousPavers

Concrete

Porous Standard

Courtesy of USDA NRCS

Other permeable surfacesPermeable pavements

Results(n=139)

Alizadehtazi et al (in revision)

Conventional spaces (parks and tree pits without guards) displayed the lowest infiltration capacity

Porous concrete consistently presented the highest infiltration capacity

Infiltration capacity > median intensity of regional 15 minute rainfall intensity

Challenges of Scaling Up

0

20

40

60

80

100

0 5 10 15 20 25

% re

duction in ann

ual run

off

Year

0

2000

4000

6000

8000

0 5 10 15 20 25

TOTA

L CO

ST: N

PV (k $)

Year

Runoff reduction Program costModeling Performance Modeling Cost

Scale up metrics over time

0

20

40

60

80

100

0 5 10 15 20 25

% re

duction in ann

ual run

off

Year

0

2000

4000

6000

8000

0 5 10 15 20 25

TOTA

L CO

ST: N

PV (k $)

Year

? ?

Uncertainty due to climate, physical performance metrics

Uncertainty due to unit costs of GI installations

Rate and extent of adoption

Runoff reduction Program cost

Scale up metrics over time Uncertainty

0

20

40

60

80

100

0 5 10 15 20 25

% re

duction in ann

ual run

off

Year

0

2000

4000

6000

8000

0 5 10 15 20 25

TOTA

L CO

ST: N

PV (k $)

Year

? ?

Uncertainty due to climate, physical performance metrics

Uncertainty due to unit costs of GI installations

Rate and extent of adoption

Runoff reduction Program cost

Scale up metrics over time Uncertainty

0

20

40

60

80

100

0 5 10 15 20 25

% re

duction in ann

ual run

off

Year

0

2000

4000

6000

8000

0 5 10 15 20 25

TOTA

L CO

ST: N

PV (k $)

Year

? ?

Uncertainty due to climate, physical performance metrics

Uncertainty due to unit costs of GI installations

Rate and extent of adoption

Runoff reduction Program cost

Scale up metrics over time Uncertainty

Stormwater wetland projects

Streetscape bioswales

Lot level strategies (planters, stormchambers, cisterns)

Square feet of catchment area

Con

stru

ctio

n C

ost

Greater catchment area, greater economy of scale

but with change in GI system typology

Stormwater wetland projects

Streetscape bioswales

Lot level strategies (planters, stormchambers, cisterns)

Square feet of catchment area

Con

stru

ctio

n C

ost

Wetland projects

Streetscape bioswales

Lot level stormwatermanagement

Square feet of catchment area

Con

stru

ctio

n co

st p

er s

quar

e fo

ot c

atch

men

t

Wetland projects

Streetscape bioswales

Lot level stormwatermanagement Greater catchment area, lower

unit costs

but with change in GI system typology

Square feet of catchment area

Con

stru

ctio

n co

st p

er s

quar

e fo

ot c

atch

men

t

0

20

40

60

80

100

0 5 10 15 20 25

% re

duction in ann

ual run

off

Year

0

2000

4000

6000

8000

0 5 10 15 20 25

TOTA

L CO

ST: N

PV (k $)

Year

? ?

Uncertainty due to climate, physical performance metrics

Uncertainty due to unit costs of GI installations

Rate and extent of adoption

Runoff reduction Program cost

Scale up metrics over time Uncertainty

Why is it hard to predict the rate and extent of LID adoption?

• Unmapped physical heterogeneities

• Institutional complexity

• Unpredictable community perceptions and potential for involvement

Unmapped physical heterogeneity

Setbackso From foundations, property lines, curbs, and underground

utilities

Subsurface conditionso Bedrock, high water table, low permeability or contaminated

soils, root systems of existing trees

Surface conditionso Parking spots and driveway curb cutso Sidewalk widths

Institutional complexity

LID in the public right-of-wayo Inter-agency coordination

LID on private propertyo Regulations for new constructiono Incentives for retrofitso Enforcement?o Impacts on water bills?

Notes from Philadelphia…

Neighborhood Statistics:Area: ~ 175 hectares10,363 lots18.5% of lots are vacant75% of lots are residential82% of surface imperviousPop: 21,20035% below poverty line82% Af. Am. 10% Asian

Residents & Resident Owners

Local NGOs & informal associations

Blocks, Streets, & Parcels

PWD

Other govtagencies

Non-resident owners &

speculators

Local institutions (churches, schools, etc)

Global agent Local agent set Reactive set

Cos

t sca

ling

Lear

ning

cur

veP

artn

ersh

ips

PWD decision sequencing (sample)

Collect information

Social network

Local conditions

Assess information

Values

Trust

Decide (stochastic)

Index

Constraints

Inform

Social network

Physical environment

Property owner decision sequencing

LID in the public right of way only

1

Frac

tion

gre

ened

Years

Target

Limited options Limited uncertainty Limited benefits

LID in the public right of way only

LID in the public right of way AND on publicly owned vacant land

1

2

Frac

tion

gre

ened

Frac

tion

gre

ened

Years

Years

Target

Target

Path dependency (early implementation of cost effective projects on vacant land spreads the money further)

Development of privately owned green infrastructure banks

Potential big winner

LID in the public right of way only

LID in the public right of way AND on publicly owned vacant land

1

2

3

Frac

tion

gre

ened

Frac

tion

gre

ened

Frac

tion

gre

ened

Years

Years

Years

Target

Target

Target

61

• Porous pavements nice, but smooth surfaces only please (for easy snow shoveling!), and cover those tree pits with gratings…

• Individual vacant lots in the middle of the block should be redeveloped; corner and clustered vacant lots should be greened

• Street trees and sidewalk planters are good, but don’t block store windows or make it difficult for motorists to see around corners!

• You want to use my backyard for what…?

• You expect who to maintain all this…?

• How do GI jobs go to the local workforce (and not outside contractors)?

• Why should I believe that this new green program be successful when other government programs have failed in making a difference?

• Who will be part of the decision making (the newcomers? Or me?)

• Are you experimenting on us? Please just fix the sewer problems!

• We have never worked together before. Why should we do that now?

• Green infrastructure…?!? We need affordable housing!

Community perceptions

62

Observation:Community dynamics could

work both for or against LID… how do we get a better handle

on this?

Mediated Modelingpremise

Involve stakeholders early

Reduce uncertainty

Build consensus

o Free and web-basedo Built in selection of 30 different LID strategies for

parcels and 16 for streetso Built-in stochastic rainfall generatoro Robust hourly water balance calculations over all rainfall

realizationso Phased life cycle costing algorithm driven by built in

database of national costs

LIDRALow Impact Development Rapid Assessmentwww.lidratool.org

Urban Hydrologic Response Units (UHRUs)

Roof

Driveway Yard

HP-009 (Bronx, NY)

GI Selector tool (parcel)

GI Selector tool (street)

LID scenarios developed with local stakeholders

1. Green roof, Rain garden, Permeable Pavement Driveway and Downspout disconnect roof to rain garden on public housing sites

2. Bio-swale and tree pits on streets3. Permeable pavement on parking lots4. Combined scenario

Sample runoff reduction results

Runoff reduction ratio per year

Annual volume of reduced runoff

Ann

ual v

olum

e of

redu

ced

runo

ff (m

3 )

Years

Sample LCC cost results (NPV)Annual expenditures during initial construction phase

Cumulative NPV of entire program to date

1st generation O&M

Ann

ual c

osts

(kila

-dol

lars

)

Cum

ulat

ive

cost

s (k

ila-d

olla

rs)

1st replacements plus O&M

Residual value of GI portfolio at year 30

HP-009 Sample ResultsRunoff reduction from ROW bioswales“Slow and Steady… “ “Get ‘em all in fast… “

Ann

ual v

olum

e of

redu

ced

runo

ff (m

3 )

Years

Ann

ual v

olum

e of

redu

ced

runo

ff (m

3 )

Years

Run

off r

educ

tion

ratio

Run

off r

educ

tion

ratio

After 30 years, both implementation strategies achieve identical runoff reduction (~2.3%), but….

HP-009 Sample ResultsProgram costs for ROW bioswales (NPV)“Slow and Steady… “ “Get ‘em all in fast… “

Years

Ann

ual c

osts

(kila

-dol

lars

)

Years

Cum

ulat

ive

cost

s (k

ila-d

olla

rs)

But at really different costs ($1.4 million vs $2.4 million) in 2013 dollars(Note: y-axes of left and right charts on different scales)

Ann

ual c

osts

(kila

-dol

lars

)

Cum

ulat

ive

cost

s (k

ila-d

olla

rs)

Concluding remarks• LID is an effective site-scale strategy for

managing stormwater (and achieving other urban sustainability goals)

• Assessing cost-effectiveness at the watershed scale, however, is non-trivial

• Recommendation: • Involve stakeholders early to achieve consensus on a

path forward. • Though the path will be uncertain (and will need to be

revised many times), all parties will feel invested, increasing certainty that a solution will be feasible

New York Daily News, 2009

Thanks!

Franco Montalto, PE PhDfam26@drexel.edufmontalto@edesigndynamics.com