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Journal of Cleaner Production xxx (2013) 1e4

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Journal of Cleaner Production

journal homepage: www.elsevier .com/locate/ jc lepro

Note from the field

Estimation of albedo effect in pavement life cycle assessment

Bin Yu*, Qing Lu 1

Civil and Environmental Engineering, University of South Florida, 4202 E. Fowler Avenue, Tampa, FL 33620, USA

a r t i c l e i n f o

Article history:Received 7 February 2013Accepted 18 July 2013Available online xxx

Keywords:LCAPavementAlbedoCO2

* Corresponding author. Tel.: þ1 813 300 5735.E-mail addresses: yubin@mail.usf.edu (B. Yu), qlu@

1 Tel.: þ1 813 974 5822.

0959-6526/$ e see front matter � 2013 Elsevier Ltd.http://dx.doi.org/10.1016/j.jclepro.2013.07.034

Please cite this article in press as: Yu, B., Lu(2013), http://dx.doi.org/10.1016/j.jclepro.20

a b s t r a c t

In the modeling of life cycle assessment (LCA) of pavement, the usage module is un-avoidable to reachcomprehensive conclusions but far from perfect till date. Typically, the usage module consists of rollingresistance, albedo, lighting requirement, carbonation (for cement concrete pavement), leachate, andothers. None of the aforementioned components is well studied among the pavement community. Thisresearch makes contribution to better modeling of the albedo effect of pavements, a traditionally ignoredaspect. A time-dependent climatological model was developed to estimate the CO2 offset due to pave-ment albedo in the life cycle, in an either deterministic or probabilistic mode. A case study suggests thatthe albedo effect produces a non-negligible contribution to the life cycle inventory. Specifically, it reducesthe CO2-equivalent emission for the portland cement concrete pavement by 9.2% but increases 19.1% forthe hot mixture asphalt pavement.

� 2013 Elsevier Ltd. All rights reserved.

1. Introduction

Life cycle assessment (LCA) is a technique assessing the envi-ronmental impacts of a product or process from “cradle” to “grave”.Pavement system, a high energy and material demanding infra-structure, generate tremendousbut vagueamountof environmentalburdens within the life cycle. The rapid raw material depletion,growing energy consumption and stringent environmental protec-tion act spur the desire to design and build environmentally friendlypavements. Therefore, pavement communities have exhibited agrowing interest in evaluating the environmental burdens ofpavement infrastructures using the LCA model (Zapata andGambatese, 2005; Huang et al., 2009; Zhang et al., 2010). Typi-cally, a complete pavement LCA methodology consists of a series ofmodules that cover material input, transportation (or distribution),construction and maintenance (C&M), congestion due to C&M, us-age, and end-of-life (EOL) (Santero, 2009; Zhang et al., 2010; Yu andLu, 2012). Till date, none of these modules has beenwell developed,due to both the complexity of the pavement system and the shorthistory and limited efforts of research. As summarized by Santeroet al. (2011), pavement LCA studies are confronting the followingchallenges: functional unit comparability, system boundarycomparability, data quality and uncertainty, and life cycle inventory(LCI) and life cycle impact analysis scopes. The system boundary,literally, refers to how many modules are incorporated in the LCA

usf.edu (Q. Lu).

All rights reserved.

, Q., Estimation of albedo eff13.07.034

model and how well they are modeled. Among all the availablepavement LCA studies, the usagemodule,which covers carbonation,lighting, albedo, rolling resistance and leachate, etc., is seldomtouched but contributes significantly to the LCIs. Zhang et al. (2010)pioneered the research to investigate the roughness effect on thefuel economy and associated air pollutant emissions in the usagemodule. Loijos et al. (2013) initiated a study investigating the con-tributions frompavement roughness, carbonationof cement, albedoeffect and lighting requirement to the final LCIs. In general, currentstatus of study on usage module is far from perfect and there aremany research gaps needing to be filled. To the authors’ knowledge,only three pavement LCA studies considered albedo effect (Santero,2009; Yu and Lu, 2012; Loijos et al., 2013), a phenomenon describingthe ratio of reflected radiation to incident radiation, which can beconverted to corresponding amount of CO2mitigation. However, thethree studies used the same methodology and the albedo effectquantifications were rough, empirical and deterministic, as dis-cussed in detail in the subsequent section. The objective of thisstudy, therefore, is to improve the albedo effect estimation in thepavement LCA. This research includes three components: develop-ment and verification of a theoretical model, a case study, and anuncertainty analysis.

2. Model establishment

The variation of planet surface albedo influences the radiativeforcing (RF), which is quantified as the rate of energy change perunit area of the globe as measured at the top of the atmosphere(Kumar, 2011), and is closely linked to the CO2 concentration. For a

ect in pavement life cycle assessment, Journal of Cleaner Production

Table 1Estimates of RF due to surface albedo change.

Literature RF (W/m2)a Note CO2 per m2 (kg)

Akbari et al. (2009) �1.27 Directly given �2.55Menon et al. (2010) �1.63 Directly given �3.26Barbes et al. (2012) �1.12 Inferred by the authors,

eastern U.S. basedNA

Hatzianastassiouet al. (2004)

�2.14 Inferred by the authors,mean global value

NA

a The value is estimated per m2 of surface area of 0.01 albedo increase.

B. Yu, Q. Lu / Journal of Cleaner Production xxx (2013) 1e42

25- to 50-year period, Akbari et al. (2009) calculated an offset of2.55 kg CO2 due to an increase of 0.01 in surface albedo per squaremeter and of 4.9 kg CO2 for the “decadal to centennial time scale”.Their calculations are based on the main results of climatologicalmodels characterized by different initial assumptions, and ignoreany time dependence. In the previous three LCA studies that esti-mated the albedo effect, the constant value of �2.55 kg CO2 wasused (negative means reduction) (Santero, 2009; Yu and Lu, 2012;Loijos et al., 2013). There are a few concerns associated with thisapproach, as discussed by Susca (2012). First, since the two values(�2.55 kg CO2 and �4.9 kg CO2) are calculated from different butoverlapped time spans, it is difficult to select a reliable value to usein a pavement LCA. Second, the approaches by Akbari et al. for CO2offset estimation (i.e., based on climatological models and withouttime dependence) are not well justified. Third, adopting a singleCO2 reduction value (i.e., �2.55 kg or �4.9 kg) cannot differentiatethe variation within short terms (e.g. 20-year and 30-year). Toresolve the time independence issue, this research traces back tothe very beginning to establish a time-dependent relationshipamong albedo, RF, and CO2, based on the available work by Birdet al. (2008), Muñoz et al. (2010), and Susca (2012).

The fundamental function describing the relationship of RF andCO2 is given as (Muñoz et al., 2010):

CO2ðtÞ ¼ A� RF� ln2� Pco2 �Mco2 �mairAearth � DF2x �Mair � AFðtÞ (1)

where A is the area affected by the change of surface albedo (m2);RF is to be further linked to albedo (W/m2) (Here RF refers to thevalue at the top of the atmosphere); PCO2

is the reference CO2partial pressure (383 ppmv); MCO2

is the molecular weight of CO2(44 g/mol); mair is the total mass of atmosphere (5.148 � 1015 Mg);Aearth is the surface area of Earth (5.1 �1014 m2); DF2x is the RF dueto the doubling concentration of CO2 (þ3.7W/m2 according to IPCC(2007));Mair is the molecular weight of dry air (28.95 g/mol); AF (t)is a time dependent variable, through which the time-dependenteffect is assigned, and t is time (year).

The fraction of CO2, f (t), decays with time after the emission andthe function is approximated as (Joos et al., 2001):

f ðtÞ ¼ 0:217þ 0:259e�t=172:9 þ 0:338e�t=18:51 þ 0:186e�t=1:186

(2)

Given a time span of t years, the AF (t) is linked to f (t) throughEq. (3):

AFðtÞ ¼

Zt

0

f ðtÞdt

t(3)

In this sense, AF (t) is the arithmetic mean of f (t). After estab-lishing the link between RF and CO2, the next step is to connectalbedo and RF. Literature review finds that the RF estimates vary, assummarized in Table 1.

The relationship between RF and albedo (a) reads:

0:01a ¼ RFhW=m2

i(4)

By substituting the default values of involved variables and Eq.(2) through Eq. (4) into Eq. (1), the following equation (Eq. (5)) isobtained.

þ0:01a ¼ 1:087� RF� t0:217� t � 44:78� e�t=172:9 � 6:26e�t=18:51 � 0:22� e�t

Please cite this article in press as: Yu, B., Lu, Q., Estimation of albedo eff(2013), http://dx.doi.org/10.1016/j.jclepro.2013.07.034

3. Model validation

The model needs to be verified before use. The publications byAkbari et al. (2009) and Menon et al. (2010) are used as references.Given a time horizon of 50 years, Akbari et al. used a RF valueof �1.27 W/m2 and found that a 0.01 increase of surface albedo perm2 of surface area produces a reduction of 2.55 kg CO2, while Eq. (5)calculates a reduction of 2.45 kg CO2; Menon et al. used a RF valueof �1.63 W/m2 and estimated a reduction of �3.26 kg CO2, whileEq. (5) calculates a reduction of�3.15 kg CO2. It can be seen that theestimates of Eq. (5) match closely with the results in the selectedliterature for a 50-year range. Such precision is deemed sufficientfor the current pavement LCA studies.

4. Case study

The data in the LCA study performed by Zhang et al. (2010), inwhich the albedo was not considered, are used here for the casestudy to quantify the albedo effect. In the original paper, thefunctional unit was set as an overlay pavement section of 10 kmlong and four lanes wide (two lanes in each direction). In each di-rection, the widths of the inner paved shoulder, main lanes, andoutsider paved shoulder are 1.2 m, 3.6 � 2 m, and 2.7 m, respec-tively. Thus, the total pavement area is A ¼ (1.2 þ 3.6 � 2 þ 2.7) �10,000 � 2 ¼ 2.22 � 105 m2.

The albedo of pavement is a significant parameter to be iden-tified. Albedo of pavement changes with time. Cement concretepavement witnesses a reduction of albedo due to weathering andabrasion while the opposite is true for asphalt pavement. Thetypical ranges of albedo for different pavements are listed in Table 2(American Concrete Pavement Association, 2002). In the subse-quent section, both deterministic and probabilistic methods areused to calculate the offset CO2 due to pavement albedo.

5. Deterministic calculation

In Zhang et al.’s study, three rehabilitation plans were investi-gated, including PCC overlay, hot mixture asphalt (HMA) overlay,and engineered cementitious composites (ECC) overlay. Since it isunclear about the albedo property of the ECC option, the formertwo options are studied. According to the original paper, within a40-year life span, the PCC option and the HMA option werereconstructed at the 20th and 21st year, and it is assumed that thenewly constructed overlays restore the albedo to their initial values.One thing needs to be emphasized is that each overlay option isplaced over an old PCC pavement. Thus the old PCC pavement with

=1:186 þ 51:26½kg CO2� (5)

ect in pavement life cycle assessment, Journal of Cleaner Production

Table 4Sensitivity analysis of critical input parameters.

Inputparameter

RF (W/m2) Albedo

BenchmarkPCC

The PCCoption

The HMAoption

Range �2.14 to �1.12a 0.20e0.30 0.20e0.40 0.05e0.15

a The RF range is determined by Table 2.

Table 2Albedo of pavement surfaces.

Pavement type Albedo

New Weathered

Asphalt 0.05e0.10 0.10e0.15Gray portland cement concrete (PCC) 0.35e0.40 0.20e0.30White PCCa 0.70e0.80 0.40e0.60

a By special design, PCC pavement can have a high albedo by using lighter cement,aggregate, and sand (Kaloush et al., 2008).

B. Yu, Q. Lu / Journal of Cleaner Production xxx (2013) 1e4 3

an assumed albedo of 0.25 is set as the benchmark. Mean RF valuein Table 1, �1.54 W/m2, is used in the deterministic calculation.

For the PCC pavement, the average albedo value before thereconstruction at the 20th year is set as 0.3 and the resulting CO2

amount is:

CO2 ¼ ð0:3� 0:25Þ0:01

� 1:087� ð�1:54Þ � 20� 220000�0:217� 20� 44:78� e�20=172:9 � 6:26e�20=18:51 � 0:22� e�20=1:186 þ 51:26

� ¼ �2735 tonne

The resulting CO2 after the reconstruction at the 20th year untilthe 40th year is

CO2 ¼ ð0:3� 0:25Þ0:01

� 1:087� ð�1:54Þ � t � 220000�0:217� t � 44:78� e�t=172:9 � 6:26e�t=18:51 � 0:22� e�t=1:186 þ 51:26

� ���t¼40

t¼20¼ �402 tonne:

Thus the overall offset CO2 is 3137 tonne. Following the similarfashion, for the HMA option, the average albedo for the 1st �21stand 22nd �40th year spans is set at 0.10. The resulting additionalCO2 release for the HMA option is 9413 tonne. The original CO2-eqivalent emission for the two options within the life cycle and thevalues due to the albedo effect are compared in Table 3.

As seen in Table 3, the albedo effects for the HMA option and thePCC option are opposite, giving credit to the latter one due to higheralbedo value. Also, the albedo effects pose non-negligible in-fluences on the LCIs. In Zhang et al.’ study, they did not providespecific values for each module in the life cycle. However, a closeobservation reveals that the impact from albedo is higher thanthose from construction, distribution, and EOL modules. Therefore,the albedo effect is desired to be well quantified to further improvethe pavement LCA modeling.

PCC HMA0

3000

6000

9000

12000

15000ennotni,egna

Rytn iatrecn

Udn

Mean=-4586Std=7464

6. Probabilistic calculation

As noted, predetermined values (e.g. RF, albedo of pavement)are used in the deterministic calculation. This subsection relaxesthe constraint and investigates the uncertainty range of the albedoeffect through Monte Carlo simulation. The use of Monte Carlosimulation allows the estimation of the impact of the variability ofRF, albedo values of benchmarked PCC pavement, the overlay PCC

Table 3Life cycle and albedo effect of the two options (in tonne CO2-equivalent).

Item LCI by Zhang et al. (2010),a Albedo effect Proportion (in %)

PCC 49,896 �3137 �6.3HMA 51,786 þ9413 þ18.2

a The value is in English unit and converted to metric one.

Please cite this article in press as: Yu, B., Lu, Q., Estimation of albedo eff(2013), http://dx.doi.org/10.1016/j.jclepro.2013.07.034

option, and the HMA options. Uniform distributions are assumedfor all the involved variables, as shown in Table 4.

After 10,000 runs of the Monte Carlo simulation, the obtainedresults are depicted in Fig. 1.

As can be observed from Fig. 1, compared to the benchmarkedPCC pavement, the newly designed PCC option decreases and the

HMA option increases the CO2 emission. The mean CO2 quantitiesfor the two options byMonte Carlo simulation are higher comparedto the deterministic ones, especially for the PCC option (�9.2% and19.1%, respectively). This is because a conservative albedo value of0.3 is assigned to the PCC option in the deterministic calculation.The uncertainty range of the PCC option is wider than that of theHMA options due to a wider albedo range. In general, the albedoeffects pose non-negligible impacts on the LCIs.

In the concrete application, the developed climatological model(Eq. (5)) is convenient to be implemented but the benchmarkalternative needs to be determined carefully. For instance, fornewly built pavement, it is the original topographical background(earth, woods, etc.) while the old pavements for rehabilitation

-12000

-9000

-6000

-3000Mean=9871Std=3265

OCtesff

Onae

M2

a

The Two Maitenance Plans

Fig. 1. Mean offset CO2 and the uncertainty range for the PCC and HMA options.

ect in pavement life cycle assessment, Journal of Cleaner Production

B. Yu, Q. Lu / Journal of Cleaner Production xxx (2013) 1e44

projects. And it is recommended to use probabilistic method toobtain both “central estimate” and uncertainty range.

7. Summary

LCA has gained growing attention among the pavement com-munity and witnessed a rapid development in recent years. How-ever, for the involved modules that constitute the pavement LCAmethodology, none is well developed, especially for the usagemodule. This research contributes to better modeling of one branchof the usage module, namely, albedo. A meteorological modeltranslating the albedo effect to CO2 was built. Compared to theprevious pavement LCA studies that considered the albedo effect,the established model allows a time-dependent estimation, eithervia a deterministic or a probabilistic method. A case study wasperformed, indicating the non-negligible impact of albedo. Theestablished model can be readily used by future practitioners tofurther improve the pavement LCA study.

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ect in pavement life cycle assessment, Journal of Cleaner Production