The Effect of Carbonation after Demolition on the
Life Cycle Assessment of Pavements
by
Katelyn M. Rossick
Submitted to the
Department of Materials Science and Engineering
In Partial Fulfillment of the Requirements for the Degree of
Bachelor of Science
at the
MASSACHUSETTS INS1
OF TECHNOLOGY
Massachusetts Institute of Technology
June 2014
JUN 0 4 2014
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©2014 Katelyn M. Rossick. All rights reserved
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distribute publicly paper and electronic copies of these thesis documents in whole or in part
in and medium now known or hereafter created.
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)epartment of Material Science and Engineering
May 2, 2014
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-.
Certified by ................................ f
Joel Clark
Professor of Materials Systems
Thesis Supervisor
Accepted by .............................................
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I ' I
Jeffrey C. Grossman
Carl Richard Soderberg Associate Professor of Power Engineering
Chairman, Undergraduate Committee
E
The Effect of Carbonation after Demolition on the
Life Cycle Assessment of Pavements
by
Katelyn M. Rossick
Submitted to the Department of Material Science and Engineering on
May 2, 2014 in Partial Fulfillment of the Requirements for the Degree of Bachelor of Science in
Materials Science and Engineering
ABSTRACT
The high contribution of CO 2 emissions associated with pavements has driven research to assess
the life cycle of concrete versus asphalt structures and to develop a strategy to reduce the carbon
footprint. The life cycle of pavement has been studied with respect to CO 2 emissions in the use
phase of concrete as well as after the concrete is demolished. However, only a few have
considered the effects of CO 2 uptake in the carbonation process during the use phase, and even
fewer have studied the effects of carbonation after demolition. This work fills the gap between
estimates of carbonation in a life cycle assessment for pavements by considering the effects of
the storage method on the uptake of CO 2 after the concrete demolished. It is observed that how
the concrete is stored after demolition can have an influence on the CO 2 uptake of the structure.
There is also an increase in the amount of the CO 2 emitted during the calcination process that is
taken back up by the concrete structure during the carbonation process to a level of 6 - 30% from
previously predicted values of 5-10% which assume no carbonation after demolition. The
incorporation of carbonation after demolition into a comparative life cycle assessment between
asphalt and concrete pavement is used to better predict the pavement material with the lower
environmental impact considering variations in the climate zone, traffic level, maintenance
schedule, design life and analysis period.
Thesis Supervisor: Joel Clark
Title: Professor of Materials Systems
2
Table of Contents
1. Introd uction ..................................................................................................
2 . Theory ...................................................................................................
6
.. 7
3. Materials and Procedures...............................................................................14
4. Results and A nalysis......................................................................................25
5. Conclusions and Future Recommendations...........................................................33
6. A cknow ledgem ents........................................................................................35
7. R eferences................................................................................................
36
Table of Figures
Figure 1: Simplified model of the cement paste structure..............................................9
Figure 2: Carbonation schematic within concrete structure..........................................10
Figure 3: Systems boundary for pavement LCA......................................................16
Figure 4: Spread out concrete particles to obtain maximum CO 2 uptake...........................19
Figure 5: Schematic pyramidal frustrum ...............................................................
20
Figure 6: Illustrations of metrics used for comparative LCA...........................................22
Figure 7: Effect of storage method after demolition at time, t, on CO 2 uptake due to
carbonation for scenario I...................................................................
28
Figure 8: Effect of storage method after demolition on CO 2 uptake due to carbonation...........29
Figure 9: Comparison of LCAs for asphalt and concrete stored in pavement (EOL), pile 3 and
maximum configurations after demolition for a local highway (scenario 1...... .30
Figure 10: Comparison of LCAs for asphalt and concrete stored in pavement (EOL), pile 3 and
maximum configurations after demolition for a local highway (scenario 1...... .31
Figure 11: Comparison of LCAs for asphalt and concrete stored in pavement (EOL), pile 3 and
31
maximum configurations after demolition for a local highway (scenario I.......
4
List of Tables
Table 1: Size distributions of demolished concrete particles........................................18
Table 2: Dimensions of piles analyzed..................................................................19
Table 3: Overview of scenarios for roads studied.....................................................24
Table 4: Time for complete carbonation in years........................................................26
Table 5: Carbonation value comparison for use versus end-of-life phase.........................27
Table 6: Percent of CO 2 emitted during calcination that is reabsorbed by the concrete structure
due to carbonation .................................................................................
27
Table 7: Comparative LCA GWP results from 1 mile rigid and flexible pavement designs......32
5
1. Introduction
Over the past century, the world's climate has undergone significant changes, with the
effects of these changes detectable today. The Earth's average temperature has increased by
0.5C since the 1970s and is expected to increase a further 1.4-5.8 'C by the end of this century
[1]. Many of the effects of climate change, including changes in temperature, pollutant
concentrations, relative humidity, and precipitation could all have significant impacts on
infrastructure lifespan.
An estimated 2.0 billion tons of carbon dioxide have been emitted annually from the
worldwide production of ordinary Portland cement (OPC), corresponding to 7% of total global
anthropogenic CO 2 emissions [2]. The high contribution of CO 2 emissions associated with
concrete has driven research to assess the life cycle of concrete structures and develop a strategy
to reduce its consumption.
The quantity of CO 2 emissions is counteracted through the uptake of carbon dioxide into
the concrete structure, through a process called carbonation. The process occurs in the cement
phase of the concrete structure and happens throughout the use of concrete materials. Many have
studied the effects of carbonation with respect to the use phase of concrete structures, but
disregard the carbonation that continues after the structures are taken out of service and
demolished. Due to factors such as increased surface area, carbonation after demolition can
potentially lead to even higher values for the uptake of CO 2 [3]. The effects of carbonation after
demolition were therefore studied to quantify its significance in the overall life cycle assessment
(LCA) of pavements.
6
2. Theory
2.1 Structure of Concrete
Concrete is a composite material made of water, aggregate, and cement. Cement absorbs
water and acts as a binder to hold the concrete together. A construction material on its own,
cement, when mixed with different ratios of aggregate and water, can achieve different
properties useful in structural applications. Cement is made from a mixture of limestone,
calcium, silicon, iron, aluminum, and other ingredients that are heated in large kilns to about
1450'C to form clinkers, small spherical particles roughly 2-3 cm in diameter [4]. The clinkers
are ground into a powder and gypsum is added, creating cement. When water is added to cement,
it triggers a chemical process hardening the material.
Limestone (CaCO 3) and clay or calcareous clay is the most important material in the
manufacture of cement with regards to carbon emissions in cement production [5]. The CO 2
comes from the calcination of the calcium carbonate during the production of the cement as
expressed in Equation 1.
CaCO 3 -+ CaO + CO 2
(1)
Cement makes up from 10% to 15% of the total mass of concrete; the exact quantity
varies depending on the type of concrete produced [4]. The aggregate and cement are mixed
thoroughly with water, starting the chemical reaction to harden and set the cement. Prior to
adding water, the concrete mix is placed into a mold so that the concrete will harden in a desired
shape.
The properties of concrete depend on the ratio of aggregate-to-cement-to-water in the
mix. The water-to-cement ratio must be controlled as too little water makes the concrete mix
difficult to work with, while too much weakens the final product [4]. Aggregate quantity and
7
type is also important, as it makes up more than 40% of a concrete mix [4]. If the aggregates are
large, less cement and therefore less water is required to create the concrete, resulting in a
stronger structure [4].
The composition of the concrete can is easily changed to obtain desired properties for a
variety of applications, making concrete a versatile material used in bridges, buildings, and
roads. Cement production requires a large amount of energy because of the high temperatures
required and outputs significant quantities of CO 2 during the calcination process, leading to
criticism for its contribution to CO 2 emissions. Recently research has pointed to understanding
the reverse process of calcination, carbonation, in which CO 2 uptake occurs in a concrete
structure to determine whether the process reabsorbs a fraction or potentially all of the CO 2
emitted during the calcination process.
To better understand the influence of the structure of the concrete on the rate of the
carbonation process and uptake of CO 2, the physical properties of the cement phase, the site of
carbonation, are discussed. Fresh cement paste is a plastic network of particles of cement in
liquid phase water. However, once the cement paste sets, its volume remains approximately
constant [4]. At any stage of hydration, the hardened paste consists of poorly crystallized
hydrates of various compounds (gel), crystals of Ca(OH)2 , unhydrated cement, and voids created
by the water-filled spaces [4]. These voids are called capillary pores and are part of a greater
network of free space along with interstitial voids contained within the gel, called gel pores. The
diameter of gel pores is about 3 nm while capillary pores are roughly one order of magnitude
larger as displayed in Figure 1 [4]. The network of pores facilitates the diffusion of reactants
needed for carbonation making their structure important in understanding the process.
8
Figure 1: Simplified model of the cement paste structure. Solid dots represent gel particles;
interstitial spaces are gel pores; spaces such as those marked C are capillary pores. Size of gel pores
is exaggerated 141.
2.2 Carbonation Reactions
Carbonation is the formation of calcium carbonate (CaCO 3) via chemical reactions in the
concrete. The creation of calcium carbonate requires carbon dioxide (CO 2 ), calcium phases (Ca),
and water (H 2 0). Carbon dioxide is present in the surrounding air, calcium phases (mainly
Ca(OH) 2 and calcium silicate hydrate) are present in the concrete, and water is present in the
pores of the concrete [6]. Equations 2, 3 and 4, describe the process of carbonation. The reaction
starts in the pores of the concrete structure, where carbon dioxide and water react to form
carbonic acid (H 2 CO 3 ).
C0 2 (g) + H20 -- H2 C0
3
(2)
The carbonic acid then reacts with the calcium phases in the concrete in Equation 3. Once
the Ca(OH) 2 has converted and is missing from the cement paste, hydrated calcium silicate
hydrate (CaO-SiO2*-H 2 0) will liberate CaO which will then also carbonate as shown in Equation
4 [6]. The pH of the concrete will fall from a value of 13 down to below 9 when the carbonation
process is completed, making it possible to determine the depth of carbonation within a sample
9
using a pH test [7]. A diagram depicting the carbonation reactions within the concrete structure is
displayed in Figure 2.
H2 CO +
H2 C0
3
(3)
Ca(OH) 2 -- CaCO + 21H20
(4)
+ CaO -- CaCO + H20
}
Carbonated
Layer
Un-carbonated
Layer
(B)
(A)
Figure 2: Carbonation schematic within concrete structure. (A) CO 2 (g)(red arrows) diffuses
through pore space in carbonated layer to reach uncarbonated layer. (B) CO 2 (g)(red arrows) in the
vacant pore space (white) and Ca(OH)2 (s)(green arrows) dissolve into the pore water (blue) coating
the pore walls and react to form CaCO 3 (s)[71.
2.3 Mechanisms of Concrete Carbonation
Carbonation requires both CO2 and water as displayed in Equation 2. Thus CO 2 from the
atmosphere must be supplied via diffusion to deeper areas of the concrete as the carbonation
depth increases with time. The water is inherently contained within the material, but the water
content can fluctuate depending on the environment of the concrete structure. The mechanisms
occurring in the water phase of cement depend on the solubility and speed of diffusion.
10
Diffusion is controlled by concentration gradients. Carbonation relies on a process of
inward diffusion of carbon dioxide gas and carbonate ions. The transport mechanism for the
carbonation reaction consists of diffusion of a carbonate species in the aqueous phase and CO 2
gas in the connective pore system [8]. The transport of CO 2 gas occurs at a faster rate than the
ions, but the carbonation reaction still needs water to proceed [6]. Thus the ability to supply CO 2
for the reaction is limited by the ability of CO 2 to dissolve in the pore water so that it can react
with the calcium ions [6]. In past studies on steel slag carbonation, under certain conditions
diffusion of calcium ions towards the surface of the particle most likely determine the overall
reaction rate [9]. With increasing time, carbon dioxide continues to spread into the concrete and
at some distance near the concrete surface the system is gradually reaching saturation [10].
The carbonation reaction is thus a coupled mechanism where the environmental and
material properties of the concrete influence the speed of carbonation [6]. The porosity of the
concrete structure, affected by the size of the gel and capillary pores, affects the permeability of
CO 2 into the structure. The larger the pores of the concrete structure, the higher the carbonation
rate. The water content of the concrete also influences the porosity, as the carbonated layer will
be dense for low water content concrete [6]. As a result, the porosity influences both
mechanisms, ion and gas diffusion of CO 2 .
Gas diffusion is much faster than ion diffusion [8]. Thus the speed of carbonation also
depends on the humidity of the environment which influences how filled the connective pore
system is with liquid (water content). In dry concrete, the carbon dioxide can penetrate deeply,
but there is not enough water for the carbonation reaction. In fully water-saturated concrete only
the carbonate ions can diffuse and carbonation is slow. Thus there is an optimal balance between
11
the porosity of the carbonated layer and concrete and the water content within the pores, at which
the maximum rate of carbonation will occur [6].
More porous concrete tends to have an optimum at a higher degree of water saturation
than denser concrete. In general, a low water to binder ratio results in a denser alteration product,
resulting in a slow carbonation rate [6]. Carbonation in concrete pores almost only occurs at a
relative humidity between 40% and 90%. When the relative humidity in the pores exceeds 90%,
the carbon dioxide is not able to efficiently enter the pore, while when the relative humidity is
below 40%, the carbon dioxide is unable to dissolve in the water [6]. There will be an optimum
relative humidity value between 50-60% for an optimal carbonation rate [11].
Other factors influencing the rate of carbonation include temperature, surface area and
whether the structure is above or below the ground. Carbonation increases with increasing
temperature due to increases in the diffusion rates. The surface area of the structure also affects
the rate of diffusion as CO 2 has more sources of entry into the concrete. Today some applications
are below ground including material used as fill in ditches and utility trenches [6]. These areas
would have different exposure levels of CO2 than an above ground species as well as different
water contents if the structure were contained in the saturated zone, below the ground water
table.
2.4 Current Work on Effect of Carbonation on LCAs
The goal of a life cycle assessment is to describe the net balance of greenhouse gases in
the use of concrete as a building material, considering all sources of emissions and uptake. An
important material parameter to consider is the maximum possible quantity of CO2 that can be
converted into calcium carbonate considering the constraints of the material's structure and
properties. Research by Moller (1994), quantified the degree of carbonation achievable in
12
concrete as 75%, which was later confirmed by Villian et al (2006) [12,13]. This value is
essentially the binding efficiency of CO 2 to CaO within the cement structure. This assumption
has been taken into consideration in models investigating carbonation after service life and is
adopted in this model as well for after the concrete is demolished.
There is a balance to be achieved in carbonation models regarding what information,
including environmental and material properties, are important and what accuracy of CO 2 uptake
values are necessary. A recent paper by Yang et al. (2014) proposed a model for the carbonation
in recycled concrete structures that incorporates adjustments for different additives such as fly
ash into the concrete as well as environmental effects including the humidity [2]. Lagerblad et al.
(2006) on the other hand relies on a modified form of Fick's 2
Law and experimental values of
carbonation depth for different types of concrete of varying strengths and compositions to make
the model easily accessible with far less information about the concrete structure required to
make the calculation [8]. This is a potential benefit as it is sometimes too difficult to obtain all
the parameters needed for a more complex model, which also introduces the propagation of
errors across more variables.
The assessment of the life cycle of CO2 of concrete structures have been studied with
respect to CO 2 emissions in the use phase of concrete as well as after the concrete is demolished.
However, only a few have considered the effects of CO2 uptake in the carbonation process
during the use phase, and even fewer have studied the effects of carbonation after demolition.
Gajda et al. (200 1) estimated that the CO 2 uptake of concrete products by carbonation during
their service life corresponds to approximately 7.6% of the amount of CO 2 emitted from the
decarbonation of limestone during calcination. Lee et al. (2013) later stated a comparable
statistic that the CO 2 uptake does not exceed 5% of the CO2 emitted during the production of
13
concrete [14,15]. However, Pade and Guimaraes (2007) concluded that the CO 2 emitted during
calcination process could be completely reabsorbed if it is considered over the course of the
concrete's service life and after the concrete is demolished [16]. The conclusion that the CO 2
could be completely reabsorbed by Pade and Guimaraes assumed that the concrete was 100%
hydrated and that carbonation would occur across the entire surface area of the concrete [16].
These assumptions would be difficult to achieve in reality. Thus, this work aims to fill the gap
between estimates by considering the effects of the storage method on the uptake of CO2 after
the concrete is crushed and demolished.
Limitations in the ways that pavement LCAs are conducted and gaps in understanding are
also present. Many LCAs do not account for different sources of uncertainty such as inventory
data, pavement designs, or maintenance schedules. The characterization of uncertainty is
important as the current life cycle inventory (LCI) data is lacking partly due to the long analysis
periods inherent to such studies.
These limitations are addressed by analyzing a broad range of scenarios using a
probabilistic approach. In particular, it is important to understand how the scope of the analysis
affects the outcomes of comparative LCAs. In addition, the model is used to demonstrate how
the inclusion of carbonation after demolition affects the outcomes of comparative analyses of
two alternative pavement designs (concrete and asphalt) in different scenarios.
3. Materials and Procedures
3.1 Pavement Life Cycle Assessment
The LCA model reflects the impacts associated with the construction of a road, given that
it will be constructed and contains five main phases - material extraction, construction of the
14
pavement, use phase, rehabilitation, and finally end-of-life [17]. These five phases can be further
broken down into more specific components that are used to calculate the impact of the road
throughout its life cycle as seen in Figure 3. Most of the phases are consistent with typical
material extraction, manufacturing and construction processes, however the use phase uses a
differential effect, by calculating a burden relative to a baseline [18].
One of the use phase aspects is pavement-vehicle interaction (PVI), which accounts for
the extra fuel consumption in vehicles on the road caused by the change in the structural and
surface properties of the pavements [18]. This model takes into account the effect of pavement
properties on the fuel economy of vehicles, which can have a significant impact especially on
high volume roads [19]. PVI can be broken down further into fuel losses due to changes in
roughness and fuel losses due to the deflection of the pavement. The latter is calculated based on
a model, which uses a mechanistic approach to predict the deflection of the road over its lifetime
as a function of the structural properties of the pavement and translates the deflection to an
associated increase in the fuel loss relative to a fully rigid pavement [20]. The roughness is
characterized using the international roughness index (IRI) and a prediction of its value is
calculated from the software Pavement-ME based on calculations specified by the MechanisticEmpirical Pavement Design Guide (MEPDG) [21,22]. This output is compared to an initial
roughness value to determine the change in roughness over time and is translated into a value of
extra fuel consumption [23]. Variables of the road such as the traffic level and climate conditions
can cause the PVI to be significant to the global warming analysis [20].
15
- Albedo
e
Carbonation
- Lighting
* Pavement-Vehicle
Interaction
- Extraction &
- Onsite equipment
production
" Transportation
- Traffic Delay
o Roughness
o Deflection
- Removal/milling
- Landfilling
- Transportation
- Carbonation
* Materials
- Construction
* Traffic Delay
Figure 3: Systems boundary for pavement LCA 1181.
Albedo, another use phase activity, takes into account the effect of the solar reflectance of
the pavement. At certain degrees of reflectivity, the pavements can reflect some of the incoming
solar radiation back into space [18]. This increase in the radiative forcing of the earth's surface,
in turn affects the global warming potential. The estimation of albedo requires a baseline value of
reflectivity with respect to which equivalent carbon dioxide of pavement due to radiative forcing
is calculated based on the assumption that a value of zero is fully absorbent and one is fully
reflective [19]. The average reflectivity of the earth is 0.33 and is used as the baseline value in
the calculation [20].
Lighting the roads provides an energy demand to the use phase. The properties of the
surface material of the pavement influence how much and what type of lighting, which is often
specified by the state US Department of Transportation and its environmental impact is
calculated based on those values in the model [17].
16
The effects of the carbonation of concrete during the use and end-of-life phases were
calculated using a model developed by Lagerblad and will be discussed further (2006) [8]. The
end-of-life phase in this model takes into account the demolished concrete is completely
landfilled as recycling introduces the need for many specific assumptions based on the process.
3.2 Model for the Carbonation of Concrete During End-of-Life Phase
The way the material is landfilled or stored after demolition is studied in the model to
determine its affects on carbonation. Carbonation during the end-of-life phase was quantified by
using the model by Lagerblad for the use phase as seen below in Equation 5, where mco, is the
mass (Mg) of CO 2 taken up through carbonation (2006) [8].
X M0
Mcoz = dc X A X pconcrete XMcementiconcreteX nCaO/cement
0/ceentMCao
The density of the concrete,
mcement/concrete,
Pconcrete
xE
(5)
(in Mg/m 3 ), mass ratio of cement in the concrete,
molar mass of CO 2, Mco2 (in g/mol), and molar mass of CaO, Mcao (in g/mol) are
all material properties of the specific concrete used in each pavement. It is assumed that the mass
ratio of CaO (mcao/cement) to cement is 0.65 and the maximum amount of carbonation is capped
in the literature at 75% of the CaO in the cement, which is represented in the binding efficiency
of CO 2 to CaO (E = 0.75) [17]. Crushing and exposing concrete to air at the end of its service life
dramatically improves the speed of carbonation making carbonation efficiencies of 75%
theoretically achievable [16]. To account for the demolition of the concrete, compared to the use
phase, several assumptions were made. The depth of carbonation, dc (in m), was calculated using
data for the carbonation depth versus time from demolished concrete samples and the
relationship in Equation 6, a simplified version of Fick's second law of diffusion. The value of
17
the rate factor was determined to be k=1.58 (in m/years1 /2 ) by fitting the data for carbonation
depth to a square root of time dependence curve and assuming no carbonation until the pavement
is in service [3,6,7]. The rate factor varies based on the strength of the concrete (which is related
to the permeability), the exposure to the environment, the cement content, the water-to-cement
ratio, cement alkali content, and the relative temperature and humidity of the surrounding
environment [14].
(6)
dc = kNtime
The demolished concrete will have a different surface area than the use phase concrete.
First, it is assumed that the demolished concrete particles arc spherical with a size distribution
based on data from Pommer and Pade in Table 1 [3].
Table 1: Size distributions of demolished concrete particles 131.
Average Diameter (m)
Percentage
Sizes (mm)
<1
20
0.001
1-10
30
0.005
10-30
45
0.020
>30
5
0.050
After the in service life, the carbonation has reached a depth, de, into the pavement. It is
assumed that the volume that includes this depth has reached a binding efficiency of CO 2 to CaO
of 75% and is considered fully carbonated.
The method of storing the demolished concrete after demolition was also considered in
the model. The particles were first considered as spread out so that no two particles were
touching on a flat surface (Figure 4). It is further assumed that one-third of the surface area of
these spherical particles will be in contact with the ground. This creates the upper bound or
18
maximum values for CO- emissions achievable.
Figure 4: Spread out concrete particles to obtain maximum CO 2 uptake 121.
The pile method, in contrast, stacks the concrete particles in the shape of a pyramidal
frustum to calculate the surface area (Figure 5). The surface area of the pile is changed to
determine its effects on the CO 2 uptake by varying the base size of the pile. Three different pile
dimensions were analyzed by selecting the length of a side of the bottom base and the length of a
side of the top base. The height of the structure was then varied to maintain a constant volume
for one mile of pavement for each type road studied. The values for these dimensions are below
in Table 2, with the height changing depending on the road thickness and number of lanes. The
values for both of these methods are then compared to the values of carbonation achieved if the
pavement were to remain intact beyond the analysis period of the road.
The values obtained for the uptake of carbonation during the use phase and after
demolition are then compared to the CO2 emitted during the calcination process during the
production of concrete, so that comparisons may be made to literature on the efficiency of the
carbonation process. The results will also be incorporated into the complete life cycle analysis
for pavements to determine the impact of including carbonation after demolition in the model.
Table 2: Dimensions of piles analyzed.
Top Base
Bottom Base
(M)
(M)
5
20
Pile 1
Pile 2
200
1
Pile 3
400
200
19
w
.....................
- ...........
...........
-
Figure 5: Schematic of a pyramidal frustum.
3.3 Probabilistic Approach
A complete description of the probabilistic pavement LCA methodology can be found in
[18]. There are three primary steps in this approach, which are summarized here: uncertainty
characterization and propagation, probabilistic assessment, and scenario analysis. The analysis
assesses the effect of including carbonation during the end-of-life phase in concrete pavements
on the decision of asphalt versus concrete pavements. Asphalt, due to its many layers and low
cement percentage is assumed to have negligible effects due to carbonation in the comparison in
terms of global warming potential (GWP) based on factors calculated by the Intergovernmental
Panel on Climate Change (IPCC). The specific LCI data for all activities in the model are
described in supporting document online [24].
3.3.1 Uncertainty Characterization and Propagation
Given the scope and nature of life cycle assessment, significant uncertainty is associated
with much of that data. For the analyses presented here, probability distributions have been
associated with most modeling parameters. These distributions were characterized either from
available empirical data or expert estimates based on the ecoinvent guidelines [25]. This includes
20
the parameters used to describe pavement design and maintenance, other LCI data, and the
impacts of upstream processes (such as electricity generation or truck transportation). More
information on the uncertainty characterizations for the parameters used in this study can be
found in supporting document [24].
Monte Carlo simulation is performed to propagate the parameter uncertainty into the
estimated life cycle GWP using a computational LCA model we have developed. In each run of
the simulation, a set of parameter samples are drawn from their corresponding distributions, and
the life-cycle GWPs are calculated for both concrete and asphalt pavement designs
simultaneously. Where appropriate, a common sample is used for both designs to account for the
natural correlation that would exist across two alternative designs constructed in the same
location. The calculations are repeated N times, resulting in N realizations of GWP. From these
realizations, the statistical characteristics of GWP can be estimated. The results presented here
are based on 10,000 simulations for each scenario [26].
3.3.2 Comparative Assessment
To statistically compare environmental impacts, in our case the GWP of two alternative
pavement designs, we make use of a comparison indicator CIGwp defined as the normalized
difference between two alternatives, CIGWP = ((ZGWP.
B - ZGWP, A)/ZGWP, A) x
100%, where
ZGWP,i
is
the GWP of alternative i. CIGwP> 0 means design A has lower GWP than design B for a specific
simulation. As a probabilistic measure of comparison, we introduce a metric which characterizes
the likelihood that one design has lower impact than another across all simulations:
(CGwp>O). This metric
P measures the relative difference in the performance
statistical manner. By comparing
P to a prescribed threshold,
P= P
of two designs in a
a decision-maker can identify that
design A is better than design B, B better than A, or that no conclusion is justified. This
21
threshold is a decision parameter, selected by the decision-maker, which controls the level of risk
associated with the decision. To discuss the results presented here, we use a threshold of 0.9.
This number was chosen because it seemed to provide a reasonable balance between the need for
providing actionable guidance (i.e., a lower threshold which increases the ability to identify a
preferred alternative) with the risk of incorrectly identifying the preferred alternative (i.e., a
higher threshold). (Note that alternatively one can look at 1 - P as the likelihood that design B
has lower impact than design A). If P is greater than the threshold 0.9 (or less than 0.1), we
consider the difference between the two alternatives as statistically significant [26].
a.1
AP
X 100%
AB-=
pA
U.;
-Design A
Design B
)= 0.6
=PCGWP
4
1A
1AB
ZGWP
0
CIGJ = ((Z
6
,,- ZWPA/ZGJ
A)X 100%
(b)
(a)
IL
LL I
01
> 0.9
CIo.,
0
/ < 0.1
-7%
6%
CGWP = (W(Z , 6 -
Z4W,A)/ZGW,A) X 100%
(c)
CIGW = ((ZGwp,-
0
ZGWP,A)/ZGWP, A) X 100%
(d)
Figure 6: Illustrations of metrics used for comparative LCA. (a) Difference between design
A and B impact relative to design A using the mean values; (b) The likelihood that design A
has lower impact than design B, i.e. P = P (CIGwp> 0) = 0.6, indicating a statistical tie
between the two designs; (c) Design A has statistically significant lower impact than design
B, i.e. P = P (CIGwp> 0) = 0.95. CI. = 6% means the maximum statistically significant
difference is 6%; (d) Design B has statistically significant lower impact than design A, i.e. p
= P (CIGwp> 0) = 0.05. CI, = -7% means the maximum statistically significant difference is
7% [26].
In addition to the metric
p is 0.9 (or 0.1), denoted as CI,.
P, we also calculate
the value of the comparison indicator when
This value represents the maximum statistically significant
difference between the two alternatives. The CI, metric is only meaningful when a statistically
significant difference exists (i.e., when
P is greater than 0.9 (or less than 0.1).
These concepts are
depicted in Figure 6 [26].
Finally, we calculate the percent difference in the means of the GWP distributions for the
two alternatives, Art, which is defined in Figure 6a. This is used for comparison with the CI,
value because it can be considered as the conventional metric for comparing life cycle impacts in
deterministic LCAs. The differences in means, however, do not provide any infornation on the
statistical significance of the difference between alternatives [26].
3.3.3 Scenario Analysis
While the probabilistic approach propagates uncertainty for most parameters, the impact of
some parameters or framing decisions on the outcomes of LCA are more suited to analysis
through individual scenarios. The different scenarios were created based on combinations of the
climate zone, traffic life, maintenance schedule, design life, and analysis period [26]. The traffic
level is based on the typical average annual daily truck traffic (AADTT) and is considered for a
rural local highway, state highway and an urban interstate highway. The maintenance schedule is
derived from the MEPDG prediction of pavement distress over time including distresses such as
roughness, rutting, cracking and faulting [26]. The design life is defined as the time to the first
rehabilitation or when a percentage of the concrete will need to be replaced.
An independent pavement design firm (Applied Research Associates) created functionally
equivalent flexible (asphalt in the top layer) and rigid (concrete in the top layer) pavement
23
designs and maintenance schedules for each scenario using the Pavement-ME software and
associated MEPDG models. Details on the designs and the maintenance schedules are in
supporting document [24]. The pavement design firm made every effort to make sure the designs
and maintenance schedules are functionally equivalent, but there are certainly other solutions
available for these contexts. As such, the outcomes of these analyses are intended to be
meaningful but not definitive [26]. The functional unit in all analyses is one center-lane mile of
pavement. Roads at the local, state and interstate levels were examined using the model
described for carbonation after demolition to determine its effect on the life cycle assessment
(Table 3).
Table 3: Overview of scenarios for roads studied (DL = design life, AP = analysis period). Two
analyses were conducted for each case outlined in the table: one including carbonation after
demolition and one excluding carbonation after demolition. The scenarios were also varied based
Traffic Level
2-Direction
AADTT
on their storage method after demolition.
LTPP Climate Zone
Wet Freeze
(Missouri)
Dry No Freeze
(Arizona)
Dry Freeze
(Colorado)
Wet No Freeze
(Florida)
AP5
(N/A)
(N/A)
(N/A)
2. DL=30,
3. DL=30,
4. DL=30,
5. DL=30,
AP=50
AP=50
AP=50
AP=50
6. DL=30,
AP=50
7. DL=30,
AP=50
8. DL=30,
AP=50
9. DL=30,
AP=50
Local
Street/Highway
(Rural)
1. DL=3O,
AADTT = 300
State Highway
(Rural)
AADTT = 1,000
Interstate
(Urban)
AADTT = 8,000
24
Each scenario was analyzed for the following storage conditions after the use phase:
original road structure without demolition (Pavement (EOL)), the three piles of varying base
dimensions (Pile 1, Pile 2 and Pile 3), and if the concrete was spaced out to achieve maximum
carbonation (Maximum Spread or Maximum).
4. Results and Analysis
The results of the model for CO 2 uptake after demolition were calculated and
incorporated into the LCA analysis for the nine scenarios. To start, the times to reach full
carbonation, assuming a maximum of 75% carbonation due to limitations of the cement
structure, were calculated for each of the scenarios and storage methods, and are shown below in
Table 4. Significant differences were present in the time to carbonation depending on how the
material was stored after demolition. Full carbonation was possible within merely 5 years if the
samples were laid out completely in the pavement (EOL) conditions, compared to thousands and
even millions of years if the piles created a low enough surface area. There is an increase in time
required for full carbonation as the roads go from local (scenario 1) to state (scenario's 2 through
5) to interstate (scenario's 6 through 9) for the pavement (EOL), pile 1, and pile 2 storage
methods. However, as the surface area approaches a maximum exposed amount for demolished
concrete in pile 3 and maximum storage methods, the time to reach full carbonation for each of
the scenarios takes approximately 1000 years and 5 years for pile 3 and maximum respectively.
As the maximum surface area conditions were approached, the effect of total volume of concrete
due to more lanes and thicker road conditions has less of an effect on the time for carbonation.
Looking at shorter time-scales is relevant to the more immediate impacts of the
carbonation after demolition. Thus, the amount of CO 2 taken up by the concrete in different
phases, as well as different scenarios and storage methods are shown below in Table 5. The
25
pavement (use) phase in the table shows the CO2 uptake for the concrete for its service life while
the pavement (EOL) represents the CO 2 uptake if the pavement was kept in place for the next
fifty years. Upon comparison, you can see the square root of time dependence on the carbonation
as it takes longer for the CO 2 and ions to diffuse within the pavement structure, so less
carbonation is achieved during the end-of-life phase.
Scenario
1
2
3
4
5
6
7
8
9
Table 4: Time for complete carbonation in years.
Time (Years)
Pavement
(EOL)
Pile 1
Pile 2
Pile 3
4010000
328000
1100
15600
16700
4960000
349000
1020
1030
19000
5070000
354000
14600
5130000
341000
1010
1030
356000
21300
5130000
367000
1010
31300
5460000
1010
31300
5460000
367000
1000
5390000
364000
25800
360000
1000
20900
5310000
Maximum
Spread
5.16
4.80
4.84
4.75
4.82
4.72
4.73
4.72
4.71
A high level of carbonation is still achieved in the pavement (EOL) storage method
versus the CO 2 uptake in pile 1 and pile 2. If the demolished concrete is stacked with even
greater surface area, there is a potential for levels of CO 2 uptake an order of magnitude greater
than those observed in piles I and 2. However, it is unreasonable to leave the concrete more
spread out than the road due to the amount of space required. Thus a series of reasonable
stacking methods could be investigated over time to maximize the levels of carbonation
achieved. The results of CO 2 uptake for a local road (scenario 1) at various time points within the
fifty years for the different stacking methods is displayed in Figure 7. By leaving the pavement
or demolished concrete in the pavement (EOL) or pile 3 configurations, significant CO 2 uptake is
achievable within the first ten years. Thus even leaving the pavement in these higher surface area
26
configurations for a year or less before moving to a lower surface area configuration would have
a significant impact on the total carbonation.
Table 5: Carbonation value comparison for use versus end-of-life phase.
Scenario
1
2
3
4
5
6
7
8
9
CO2 Uptake due to Carbonation [Mg]
50 years after Demolition
50 years
Pavement
(Use)
Pavement
(EOL)
Pile I
Pile 2
Pile 3
Maximum
Spread
31.63
63.08
61.40
59.19
42.79
85.96
85.96
82.87
88.32
22.48
44.83
43.64
42.07
30.41
61.09
61.09
58.90
62.77
1.29
2.41
2.48
2.13
1.83
4.37
4.37
3.83
3.67
4.51
9.08
9.39
7.98
6.94
16.84
16.84
14.73
14.09
78.13
167.81
174.36
146.86
129.24
321.90
321.89
280.45
267.03
413.78
821.71
852.57
719.26
628.44
1529.83
1530.59
1340.07
1284.56
80
:Q
-
60
40
20
04
0
U
2
0
- c~1
I
I
---
--
-1.
V
V
---
--
Cl
0
0
V
t=25 years
t=10 years
t=50 years
Figure 7: Effect of storage method after demolition at time, t,
on CO 2 uptake due to carbonation for scenario 1.
27
When comparing across all road types, there is a trend observed with local, rural state,
and urban interstate roads as seen in Figure 8. There is an increase in CO 2 uptake due to mere
increases in the volume of cement present in the roads, but the increase is more substantial for
packing methods with larger surface areas exposed. In other words, the stacking method is less
significant when it comes to the smaller roads, as there is not as much material available for
carbonation and it becomes easier to expose more of the surface area. The trend would vary
depending on how much road was being assessed, but holds true for the mile comparison in the
paper. Thus, it is more important to consider the stacking method on interstate roads versus local
roads and implementing a method to maximize the surface area during storage becomes crucial.
Another important parameter to consider is how much of the CO 2 emitted during the
calcination process is taken back up by the cement structure during the carbonation process. The
results for the ratio of the use phase (50 years) plus the end-of-life phase (50 years after
demolition) compared to the calcination during production are shown below in Table 6. Again it
is observed, similar to the conclusion of Pade and Guimaraes (2006), that all of the CO 2 emitted
will be taken back up into the structure by around 50 to 60 years after demolition if the concrete
is completely spread out [16]. Even though the assumptions made in this paper about how much
surface area is exposed are more reasonable than the maximum set by Pade and Guimaraes, this
assumption is still unrealistic due to the amount of space necessary to achieve this level of
carbonation. Thus taking into consideration that the concrete will most likely be stacked after
demolition, we can develop a range of carbonation values from 6 to 30% for during the use and
end-of-life phases, with 1 to 20% coming from carbonation during the end-of-life phase. The low
side of the estimate falls close to the predictions of Gajda et al. (2001) and Lee et al (2006), who
only considered carbonation in the use phase. However, depending on the type of road, stacking
28
to achieve more efficient CO 2 uptake, could realistically raise the percentage to a value close to
the pile 3 conditions of 30%.
350
UPavement (EOL)
300
" Pile 3
C250
200
150 0.
100 50 -
Q
0
I
-
1
2
3
4
6
5
7
8
9
Scenario
Figure 8: Effect of storage method after demolition on CO 2 uptake due to
carbonation for all scenarios.
Table 6. Percent of CO 2 emitted during calcination that is reabsorbed by the concrete structure
due to carbonation (50 years use + 50 years end-of-life).
Scenario
1
2
3
4
5
6
7
8
9
Pavement
(Use + EOL)
15.0%
13.2%
12.4%
14.0%
11.7%
9.0%
9.0%
9.8%
10.9%
Pile 2
10.0%
8.8%
8.3%
9.3%
8.0%
6.3%
6.3%
6.7%
7.4%
Pile I
9.1%
8.0%
7.5%
8.5%
7.1%
5.5%
5.5%
6.0%
6.6%
29
Pile 3
30.4%
28.3%
27.9%
28.6%
27.6%
25.0%
24.9%
25.2%
25.8%
Maximum
Spread
100%
100%
100%
100%
100%
99.0%
99.0%
98.8%
99.6%
The values obtained for carbonation were further analyzed in the scope of the entire life
cycle assessment process, with the changes in the CO 2 output observed for the local, state, and
interstate roads when carbonation during the end-of-life phase is included (Figures 9-11). In all
three cases, it decreased the end of life (EOL) impact, as well as the total impact. Depending on
the storage method of the material after demolition, the impact on the total, is enough to drop the
total GWP value of concrete below asphalt. In the local case (scenario 1), only the maximum
case decreases the value of the total low for concrete below the asphalt total, but in the state and
interstate cases (scenario 5 and 8 respectively), pile 3 and the maximum both have values of
GWP below that of asphalt. Therefore, it is important to consider the probabilistic analysis of the
life cycle assessment to determine whether these differences are statistically significant enough
to say that either concrete or asphalt is preferable based on the net CO2 emissions.
2400
EAsphalt
-
Concrete - Use plus Pavement (EOL)
1900
* Concrete - Use plus Pile 3
SConcrete - Use plus Maximum
14UU
900
400
I
-10 0
Total
Initial const.
Use
IM&R
-~
EOL
Figure 9: Comparison of LCAs for asphalt and concrete stored in pavement (EOL), pile 3
and maximum configurations after demolition for a local highway (scenario 1).
30
4400
3900
" Asphalt
*
3400
2900
2400
1900
1400
900
400
-100
Concrete - Use plus Pavement (EOL)
" Concrete - Use plus Pile 3
*
Total
Initial const.
Concrete - Use plus Maximum
M&R
Use
EOL
Figure 10: Comparison of LCAs for asphalt and concrete stored in pavement (EOL), pile 3
and maximum configurations after demolition for a state highway (scenario 5).
13900
" Asphalt
11900
9900
*
Concrete - Use plus Pavement (EOL)
"
Concrete - Use plus Pile 3
" Concrete - Use plus Maximum
7900
5900
3900
1900
-100
U1
Total
Use
Initial const.
M&R
_
EOL
Figure 11: Comparison of LCAs for asphalt and concrete stored in pavement (EOL), pile 3
and maximum configurations after demolition for a interstate highway (scenario 8).
31
Table 7: Comparative LCA GWP results from 1 mile rigid and flexible pavement designs
with DL= 30, AP= 50, and MEPDG-derived maintenance schedule. Metrics in table: A [=
%difference at means; P = P (CIGwp> 0); CI. = CI @ P = 0.9 or 0.1 depending on P value; black
background means flexible design has statistically significant lower impact; grey background
means rigid design has statistically significant lower impact
I
Traffic Level
I
2-Direction
AADTT
Local
Street/Highway
Full-scope
(Rural)
Carbonation
EOL
State Highway
(Rural)
AADTT = 1,000
Interstate
(Urban)
AADTT = 8,000
I
9
Scenario 1.
Scenario 7.
Scenario 5.
Wet Freeze
(Missouri)
Dry No Freeze
(Arizona)
Wet No Freeze
A[1,
AADTT = 300
Climate Zone
fLTPP
T
P,
CI"
Ai,
~3, CI,
(Florida)
All,
P,
CI,
N/A
N/A
17%, 0.88, (N/A)
exclutded
7%, 0.75, (N/A)
Full-scope
Carbonation
N/A
N/A
3%, 0.63, (N/A)
EOL
excluded
Full-scope
Carbonation
N/A
N/A
13%, 0.89, (N/A)
EOL
excluded
The results of the probabilistic analysis are found in Table 7 for the pile 3 storage
conditions. Based on the
P values,
the local road (scenario 1) and interstate (scenario 7) both
were shown to be statistically significant in favor of the rigid or concrete design when
carbonation in the end-of-life phase was included. This was not the case when the carbonation
was excluded in the model as
P was not greater than 0.9, at a value
of 0.88. In addition,
carbonation did have an effect on the state road (scenario 5), however, the increase from P=0.63
to 0=0.75 was not enough to make concrete pavement statistically significant over asphalt. The
32
differences in the means of asphalt and concrete, A t, increased, meaning that the impact is lower
for concrete when parameters including climate, traffic levels and maintenance levels are varied.
The comparison indicator, CI, shows that the maximum statistically significant difference
between using concrete and cement is only 2% in the local road and interstate. Although,
concrete is in favor, other realizations about CO 2 uptake and emissions could make the decision
no longer statistically significant.
5. Conclusions and Future Recommendations
While these calculations do not take into account all the factors that determine the rate of
carbonation, they consider the most important driving forces for the process, including diffusion
of CO2 and the structure of the cement in the concrete. It is observed that how the concrete is
stored after demolition can have the greatest influence on the CO 2 uptake of the structure and the
overall life cycle assessment. While it maybe unrealistic to leave concrete spread out for five
years, it is important to consider that even setting out the concrete in a manner similar to this for
a year or even a month before stockpiling could greatly improve the carbon footprint of the
pavement LCA in not only roads, but also other cement structures. It would be interesting to
study if changing the storage method was feasible by assessing the cost and carbon dioxide
emissions associated with the process.
Carbonation after demolition also raises the amount of the CO2 emitted during the
calcination process that is taken back up by the cement structure during the carbonation process
to a level of 6 - 30% for during the use and end-of-life phases. The percentage falls between
those previously predicted by Pade and Guimeraes (2007) as well as Gajda et al. (2001). Further
studies into the carbon dioxide distribution within a stockpile and how the size of the demolished
33
particles effects this value would help to increase the certainty of any predicted value, along with
more research on the carbonation depth observed in demolished concrete.
The effects of carbonation on corrosion of reinforced concrete structures were not
addressed in this work. However, carbonation makes the metal reinforcements more susceptible
to corrosion factors as it decreases the pH, which in turn can cause cracking and damage to a
structure. Therefore, in the future, it would be important to assess the cost of damages on a
monetary and environmental basis due to the failure via the cracking and corrosion of concrete, a
process accelerated by carbonation.
The comparison between using asphalt and concrete was shown to be statistically
significant when carbonation during the end-of-life phase was included in the life cycle for the
diffusion of CO 2 into the structure. This was based on Fick's 2 "ndLaw, but did not consider how
the distribution of CO2 within the space between each of the demolished particles would affect
the diffusion. The concept of the additional empty space was addressed by using experimental
data to determine a k-value, but the k-value encompassed other material and environmental
conditions. Incorporating the effect of a CO 2 gradient directly into the model, would help to
further validate the impact of carbonation on the life cycle assessment of pavements. Other areas
of improvement include the incorporation of materials and construction practices that are not
conventional such as the use of lower impact materials including Portland limestone cement and
different methods of recycling materials that lessen the environmental impact. By making a
model more specific to these lower impact methods, detailed information would be required
about the material and process which is sometimes lacking or difficult to quantify in the life
cycle of pavements. However, as research in these areas progress, it will become important to
take non-conventional factors into consideration in the life cycle assessment of pavements.
34
5. Acknowledgements
I would like to thank Randolph Kirchain, Jeremy Gregory, Joel Clark, Xin Xu, and Arash
Noshadravan for their help and guidance throughout the research and writing of this work.
35
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