Pavement Surface Characteristics and Sustainability

2011 Road Profiler User’s GroupReno, NV

Ting Wang, In-Sung Lee, Alissa Kendall,

John Harvey (presenter), Chang-Mo Kim, EB Lee,

Motivation

• Reduce energy use – national policy objective

• Reduce greenhouse gas emissions– California state law

• Achieve these goals by the most cost-effective policies possible– Prioritize based on $/benefit

California’s AB32 framework(reaffirmed by voters November 2010)

• AB32 requires– 2020 GHG emissions at 1990 levels– 2050 GHG emissions at 0.2 x 1990 levels

Transportation 38% of 2004 GHG

Refineries and cement plants significant parts of Industry (20% of 2004 GHG)

3

Objectives of Project• Develop LCA model for state highway and local

road networks– Initial models using available data sources– Update as develop regional databases

• Use model to answer questions regarding GHG ($/ton CO2e) and fuel use (net reductions):

– Rolling resistance– Design life– Recycling vs local materials, transportation

costs– Alternative rehabilitation strategies

The Pavement Life CycleThe Pavement Life Cycle(compatible with ISO 14040)(compatible with ISO 14040)

Materials

Construction

Use

Maintenance & Rehabilitation

End-of-Life

Materials extraction and production

Traffic delay

Onsite equipment

Transportation

Rolling resistanceCarbonationLightingAlbedoLeachate

Adapted from: Santero, N. (2009). Pavements and the environment: A life-cycle assessment approach. Ph.D. Thesis, UC Berkeley.

Sponsors:Sponsors:

Additional Sponsors:Additional Sponsors:

Collaborators:Collaborators:

Additional Support Provided by:Additional Support Provided by:

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Workshop on LCA for Pavement, Davis, CA, May 2010Discussions and UCPRC approach downloadableat www.ucprc.ucdavis.edu/p-lca

Basic Approach by UCPRC forApplication to State, Local Networks

• Divide network into categories based on factorial• Case studies for categories with sensitivity analyses

– IRI and MPD (for MIRIAM) – Materials (type, production method, etc.)– Hauling distance– Traffic levels and congestion– Fleet composition over time (new vehicle technologies)

• Initial assumption: surface type doesn’t change– Except RHMA vs HMA, PCC vs CSA cement– Consider LCA effects of changing surface type after

models completed

Factorial for LCA for California State and Local Networks

Factorials Possible ValueRoad type Rural road; urban roadRoad grades Flat road; mountainous roadRoad access type Restricted access; unrestricted accessTraffic level Different levels of AADT and AADTT,

categorizedPavement surface type Asphalt pavement;

Cement concrete pavementPavement surface characteristics

Different levels of IRI and MPD, categorized

Pavement Treatment Different treatment options

Models: Materials and construction

• Materials production and plant emissions: – Existing databases & studies– review by CNCPC, APACA

• Off-Road equipment– OFFROAD: California’s off-road equipment

emission inventory• On-Road equipment

– EMFAC: California’s on-road vehicles emission inventory

• Equipment and hours– CA4PRS: Caltrans construction schedule analysis

tool• Road user delay

– CA4PRS (not yet implemented)9

Models: Use Phase

• MOVES– MOtor Vehicle Emission Simulator– US EPA’s current official model for estimating

air pollutant emissions from cars and trucks– Can consider speed profiles

• HDM-4– Highway Development and Management Model– Steady speed fuel use– Relationship between pavement surface

characteristics (MPD, IRI) and rolling resistance– Developed by World Bank, recently calibrated

with fuel use instrumentation on North American vehicles by Imen & Chatti (Michigan State Univ), through NCHRP 01-45

10

Pavement – Rolling Resistance – Energy

• HDM-4 model (World Bank; Imen & Chatti)– Surface characteristics:

– Rolling Resistance:

• MOVES model (US EPA)– Vehicle power demand (VSP):

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2 2 0 1 2 3CR Kcr a a Tdsp a IRI a DEF

212

. . .

( ) 1

b

a D front w i R

P Air resist Inertial and Gradient resist Rolling resist

C A v v v M a g grade v C Mg v

Fr = CR2*FCLIM*[b11Nw+CR1(b12M+b13v2)]Fr = CR2*FCLIM*[b11Nw+CR1(b12M+b13v2)]

Update MOVES parameter

• MOVES parameter from dynamometer test

• Proportionally increase from dynamometer to real-world pavement:

2

2 3

. . .

1( ) 1

2

1

b

R a D front w i

i

P Rolling resist Air resist Inertial and Gradient resist

C Mg v C A v v v a g grade M v

A v B v C v a g grade M

v

2 2 0 1 2 3

2 2 0 1 1.02 0 0.28 2 0 3 0

0 1 2 3

0 1 0.28

updated pavement

default dynamometer

A CR Kcr a a Tdsp a IRI a DEF

A CR Kcr a a a a

a a Tdsp a IRI a DEF

a a

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Case Study 2 (Finished):Concrete CPR B on rural/flat

freeway10 mile (16 km) segment in need of rehabRural freeway4 lanes, southboundAADT: ~80,000; ~25% trucks

Cars Trucks IRILane 1 (Inner) 38% 0.2% 3Lane 2 34% 8% 3Lane 3 16% 42% 3.5Lane 4 (Outer) 13% 49% 4

Compare:- Do Nothing- 10 year CPR B

-Type III, CSA cement13

Construction Scenario

Treatment Design life Material Smoothness

CPR B with 3% slab replacement and grinding the entire lane

10 yrs

Type III Rapid Strength Cement (3.2 Mpa in 4 hours)

Smooth Rehab (-2σ)Medium Smooth Rehab (mean)Less Smooth Rehab (+2σ)

Calcium Sulpho-Aluminate (CSA) Cement (2.8Mpa in 4 hours)

Smooth Rehab (-2σ)Medium Smooth Rehab (mean)Less Smooth Rehab (+2σ) 14

Concrete IRI over 10 years: Lane 1

0

50

100

150

200

250

300

0.0

1.0

2.0

3.0

4.0

0 1 2 3 4 5 6 7 8 9 10

IRI

(in

/mi)

IRI

(m/k

m)

Year

Lane 1: Do NothingLane 1: Less Smooth Rehab (+2σ)Lane 1: Medium Smooth Rehab (Mean)Lane 1: Smooth Rehab (-2σ)

15

Grinding

0

50

100

150

200

250

300

0.0

1.0

2.0

3.0

4.0

0 1 2 3 4 5 6 7 8 9 10

IRI

(in

/mi)

IRI

(m/k

m)

Year

Lane 4: Do NothingLane 4: Less Smooth Rehab (+2σ)Lane 4: Medium Smooth Rehab (Mean)Lane 1: Smooth Rehab (-2σ)

Concrete IRI over 10 years: Lane 4

16

Grinding

Concrete Mean Texture Depth (MTD) Progression

From: Shreenath Rao and James W. Mack, Longevity of Diamond-Ground Concrete Pavements, Transportation Research Record, Vol 1684, 1999

17

0.0

0.2

0.4

0.6

0.8

1.0

1 2 3 4 5 6 7 8 9 10

MT

D (m

m)

Year

Rehabilitated Lanes

Do Nothing

Energy in Use Phase with 0 & 3% Traffic Growth (US unit)

18

1.2E+7

1.4E+7

1.5E+7

1.7E+7

1.8E+7

1.5E+9

1.7E+9

1.9E+9

2.1E+9

2.3E+9

2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021

Equ

ival

ent G

asol

ine

(gal

)

Tot

al E

nerg

y (M

J)

Year

3% Traffic growth + Do Nothing + No fuel economy improvement

3% Traffic growth + Do Nothing + Fuel economy improvement

0% Traffic growth + Do Nothing + Fuel economy improvement

0% Traffic growth + Less Smooth Rehab + Fuel economy improvement

0% Traffic growth + Medium Smooth Rehab + Fuel economy improvement

0% Traffic growth + Smooth Rehab + Fuel economy improvement

-4.7E+6

-2.7E+6

-6.9E+5

1.3E+6

3.3E+6

5.3E+6

-1.5E+8

-5.0E+7

5.0E+7

1.5E+8

2.5E+8

3.5E+8

4.5E+8

5.5E+8

6.5E+8

Material Production Construction Use

Eq

uiv

alen

t Gas

olin

e (L

)

Tot

al E

ner

gy S

avin

g C

omp

ared

to D

o N

oth

ing

(MJ)

Phase

3% Traffic growth: Smooth Rehab compared to Do Nothing

3% Traffic growth: Medium Smooth Rehab compared to Do Nothing

3% Traffic growth: Less Smooth Rehab compared to Do Nothing

0% Traffic growth: Smooth Rehab compared to Do Nothing

0% Traffic growth: Medium Smooth Rehab compared to Do Nothing

0% Traffic growth: Less Smooth Rehab compared to Do Nothing

10-year energy savings from materials (Type III), construction, use phase compared to “Do

Nothing”

PCA Stripple Huntzinger

0

19

Cumulative energy savings from materials (Type III), construction, use phase compared to “Do Nothing”

Construction

20

-1.6E+6

3.4E+6

8.4E+6

1.3E+7

1.8E+7

-5.0E+7

5.0E+7

1.5E+8

2.5E+8

3.5E+8

4.5E+8

5.5E+8

6.5E+8

2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Eq

uiv

alen

t Gas

olin

e (L

)

Cu

mm

ula

tive

En

ergy

Sav

ing

Com

par

ed to

Do

Not

hin

g (M

J)

Year

3% Traffic growth: Smooth Rehab compared to Do Nothing

3% Traffic growth: Medium Smooth Rehab compared to Do Nothing

3% Traffic growth: Less Smooth Rehab compared to Do Nothing

0% Traffic growth: Smooth Rehab compared to Do Nothing

0% Traffic growth: Medium Smooth Rehab compared to Do Nothing

0% Traffic growth: Less Smooth Rehab compared to Do Nothing

Case Study 1 (Finished):Asphalt overlay on rural/flat

freeway10 mile (16 km) segment in need of rehabRural freeway2 lanes, southboundAADT: 34,000; ~35% trucks

Passenger TrucksInner Lane 77% 9%Outer Lane 23% 91%

Compare:- Do Nothing-10 year rehab

-HMA, RHMA 21

Construction Scenarios: Case Study 1

HMA Type

Design life Treatment Cross Section Smoothness

HMA 10 Years Mill & Overlay

45 mm (0.15’) Mill + 75 mm (0.25’) HMA with 15% RAP

Smooth RehabLess smooth Rehab

RHMA 10 years Mill & Overlay

30 mm (0.1’) Mill + 45 mm (0.15’) RHMA

Smooth RehabLess smooth Rehab

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Asphalt IRI Scenarios over 10 years*

* 1st draft from empirical data, needs review and modeling

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

1 2 3 4 5 6 7 8 9 10

IRI

(m/k

m)

Year

Smooth Rehab: Ln1 Smooth Rehab: Ln2

Less Smooth: Ln1 Less Smooth: Ln2

Do Nothing: Ln1 Do Nothing: Ln2

23

Asphalt MPD Progression from CA data*

(For rehabilitated lanes)

* 1st draft from empirical data, needs review and modeling

0

0.2

0.4

0.6

0.8

1

1.2

1 2 3 4 5 6 7 8 9 10

MP

D (m

m)

Year

HMA: Ln1 HMA: Ln2

RHMA: Ln1 RHMA: Ln2

24

-1.6E+6

-6.3E+4

1.4E+6

2.9E+6

4.4E+6

5.9E+6

7.4E+6

-5.0E+7

0.0E+0

5.0E+7

1.0E+8

1.5E+8

2.0E+8

2.5E+8

Feedstock Energy Material Production

Construction Use

Equ

ival

ent

Gas

olin

e (L

)

Tot

al E

nerg

y Sa

ving

Com

pare

d to

Do

Not

hing

(M

J)

Phase

3% Traffic growth: Init. IRI=1 compared to Do Nothing

3% Traffic growth: Init. IRI=1.67 compared to Do Nothing

0% Traffic growth: Init. IRI=1 compared to Do Nothing

0% Traffic growth: Init. IRI=1.67 compared to Do Nothing

10-year energy savings from materials, construction

(HMA), and use phase compared to “Do Nothing”

USLCI Athena

Stripple Ecoinvent

25

0

-1.6E+6

-6.3E+4

1.4E+6

2.9E+6

4.4E+6

5.9E+6

7.4E+6

-5.0E+7

0.0E+0

5.0E+7

1.0E+8

1.5E+8

2.0E+8

2.5E+8

2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Equ

ival

ent

Gas

olin

e (L

)

Cum

mul

ativ

e E

nerg

y Sa

ving

Com

pare

d to

D

o N

othi

ng (

MJ)

Year

3% Traffic growth: Init. IRI=1 compared to Do Nothing

3% Traffic growth: Init. IRI=1.67 compared to Do Nothing

0% Traffic growth: Init. IRI=1 compared to Do Nothing

0% Traffic growth: Init. IRI=1.67 compared to Do Nothing

Cumulative energy savings from materials, construction

(HMA), and use phase compared to “Do Nothing”

Construction

0

26

Acknowledgement

• Thanks to California Department of Transportation and University of California for research funding

• This project is part of a larger pooled-effort program called “Miriam”, partnering with 8 European National Highway Research Laboratories– Studying pavement rolling resistance

Disclaimer

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The contents of this presentation reflect the views of the authors, who are responsible for the facts and accuracy of the data presented herein. The contents do not necessarily reflect the official views or policies of the State of California, the Federal Highway Administration, the University of California, the MIRIAM project or its sponsors, the International Society for Concrete Pavements, or the International Society for Asphalt Pavements. This presentation does not constitute a standard, specification, or regulation.

Questions?

Supply Curve

• First-order quantitative “what-if” analysis• Prioritizing Climate Change Mitigation Alternatives:

Comparing Transportation Technologies to Options in Other Sectors, Lutsey, N. (2008)

Initial cost

Net costs = initial cost + direct energy saving benefits

Bang for your buck metric: $/ton CO2e vs CO2e reduction

Details: Future Work

• Finish the rest of the case studies• Finish the application to California’s

network• Include the effect of construction work

zone traffic and traffic congestion (urban cases)

• Perform sensitivity analysis on parameters such as RR range, materials, traffic closure, etc.

• Apply the result to the Cost-Effectiveness curve

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Future Work (Cont’d)

• Investigate the dissipated energy on asphalt, composite, semi-rigid pavement

• Investigate the macro-texture progression of concrete pavement

• Investigate the effect of congestion on rolling resistance impact

• Investigate the overall rolling resistance on composite and semi-rigid pavement

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