sustainability
Article
Environmental Potentials of Asphalt Materials
Applied to Urban Roads: Case Study of the City
of Münster
Mayara S. Siverio Lima 1, * , Mohsen Hajibabaei 2 , Sina Hesarkazzazi 2 , Robert Sitzenfrei 2 ,
Alexander Buttgereit 3 , Cesar Queiroz 4 , Arnold Tautschnig 1 and Florian Gschösser 1
1
2
3
4
*
Department of Structural Engineering and Material Sciences, University of Innsbruck,
6020 Innsbruck, Austria; arnold.tautschnig@uibk.ac.at (A.T.); florian.gschoesser@uibk.ac.at (F.G.)
Department of Infrastructure, University of Innsbruck, 6020 Innsbruck, Austria;
mohsen.hajibabaei@uibk.ac.at (M.H.); sina.hesarkazzazi@uibk.ac.at (S.H.); robert.sitzenfrei@uibk.ac.at (R.S.)
Department of Mobility and Civil Engineering, 48155 Münster, Germany; buttgereit@stadt-muenster.de
The World Bank, Washington, DC 20433, USA; queiroz.cesar@gmail.com
Correspondence: mayara.siverio-lima@uibk.ac.at; Tel.: +43-512-507-63109
Received: 6 July 2020; Accepted: 27 July 2020; Published: 29 July 2020
Abstract: Life cycle assessment (LCA) tools have been used by governments and city administrators
to support the decision-making process toward creating a more sustainable society. Since LCA is
strongly influenced by local conditions and may vary according to various factors, several institutions
have launched cooperation projects to achieve sustainable development goals. In this study, we
assessed the potential environmental enhancements within the production of road materials applied
to the road network of Münster, Germany. We also compared traditional pavement structures used
in Münster and alternative options containing asphalt mixtures with larger amounts of reclaimed
asphalt pavement (RAP). Although the case study was conducted in Münster, the data collected
and the results obtained in this study can be used for comparison purposes in other investigations.
In the analysis, we considered all environmental impacts from raw material extraction to the finished
product at the asphalt plant. Two environmental indicators were used: non-renewable cumulative
energy demand (nr-CED) and global warming potential (GWP). The results show that using RAP
increases the consumption of energy but potentially decreases the environmental impacts in terms of
the nr-CED and GWP associated with the production of asphalt materials.
Keywords: life cycle assessment; asphalt mixtures; reclaimed asphalt pavement; environmental impact
1. Introduction
In 2015, the United Nations (UN) established a plan of action to improve the prosperity of
society. Titled Agenda 2030, this plan of action comprises 17 Sustainable Development Goals (SDGs),
which are political goals to ensure sustainable development on economic, social, and environmental
levels, addressing global challenges related to poverty, inequality, climate, environmental degradation,
and prosperity, as well as peace and justice. A sustainably built environment is one of the prerequisites
for the realization of the SDGs by 2030, wherein sustainable transport infrastructures and systems form
a core part of a future-oriented built environment. This is demonstrated in the detailed targets and
specifications in the SDGs. For example, SDG 11—“Sustainable Cities and Communities” specifies
“access to safe, affordable, accessible and sustainable transport systems for all” as a relevant SDG
target [1]. Urban road systems, with their network density and high traffic loads, need to contribute to
urban transport systems within the UN SDGs.
Sustainability 2020, 12, 6113; doi:10.3390/su12156113
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Despite the constant efforts to reduce the carbon footprint and make road constructions more
sustainable, road pavements still have a large contribution to environmental impacts within the
construction industry. In the UK, for example, roads consume around 25% of all materials extracted
from the ground [2,3] making them a significant target to improve sustainability.
It is a common sense that primary raw materials used to build pavements are scarce and the
world urgently requires a solution. The environmental impacts of using primary raw materials to
compose pavements occur not only due to the extraction process but also due to the transportation
since they are normally transported across long distances. On the other hand, the use of recycled
materials reduces the impacts of extraction and is more likely always available, which mitigates the
impacts of transportation.
The benefits of using recycled materials to compose asphalt mixtures are not only environmental
but also economical. The use of RAP is more cost-effective than using primary raw materials [4].
In terms of mechanical performance, studies have shown that asphalt mixtures with RAP perform
equally to regular ones [5–7].
Nevertheless, increasing the amount of RAP as the raw material used to compose asphalt mixtures
is still a challenge since authorities must be convinced and regulations need to be changed.
Over the past years, a variety of studies have been conducted, analyzing the environmental
sustainability of road infrastructure and specifically of road pavements by applying the life cycle
assessment (LCA) methodology [8–20]. Most of these studies evaluated the environmental impacts of
road pavements using a holistic approach over their entire life cycle or rather over a specific analysis
period [10–12,14,18,21]. Some of these studies focused specifically on the environmental influence of
maintenance strategies and policies [10–12,14,20].
An example of a holistic sustainability study of urban road infrastructure was conducted by
Trigaux et al. [18], who assessed the environmental and economic impacts of roads in residential
neighborhoods considering their whole life cycle (material production, pavement construction,
maintenance and replacement, usage by traffic, demolition, and end of life), including supply
infrastructure such as electricity supply and pipework. Gschösser [20,21] analyzed asphalt and
cement concrete pavements for highways and main roads over their entire life cycle, focusing on the
environmental and economic impacts of construction and maintenance processes, including material
production. Both studies demonstrated the strong influence of material production processes on the
overall environmental results, underlining the need to perform specific studies analyzing environmental
potential within the production processes of road materials, as shown in various studies [13,16–19].
To reduce the environmental impacts of road material production, the main focus is the application
of alternative raw materials and enhanced production processes. In this context, Gschösser [13],
for example, assessed the potential reduction of environmental impacts within asphalt production
processes with lower mixing temperatures due to the lower moisture contents of the applied aggregates
and the application of foam bitumen. The partial substitution of primary raw materials (bitumen
and mineral aggregates) with reclaimed asphalt pavement (RAP) and the connected environmental
influence was analyzed. Farina et al. [19] performed an LCA, analyzing different types of asphalt
mixtures containing recycled materials, such as crumb rubber from scrap tires, and RAP, comparing
the results with standard paving materials. The literature review by Balaguera et al. [15] reported
RAP, fly ash, and polymer as the most frequently applied alternative raw materials used within
asphalt materials [16,17]. Balaguera et al. showed that most of the material studies focused on road
materials for pavements with high traffic loads (e.g., highway pavements) and that the most frequently
analyzed environmental indicators for road material LCA are non-renewable cumulative energy
demand (nr-CED) and global warming potential (GWP).
The results of the analyzed LCA studies showed that the environmental performance of asphalt
materials depends on numerous factors, being strongly influenced by local conditions. The City
of Münster (Germany) is embracing Agenda 2030 into its strategic policies and aspires to enhance
the environmental performance of its urban road network within the next few years. Therefore,
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the Department of Mobility and Civil Engineering of the City of Münster (Germany), together with
the Münster University of Applied Sciences joined the Horizon2020 research project SAFERUP!
(Sustainable, Accessible, Safe, Resilient and Smart Urban Pavements, funded by the European Union),
wherein a specific environmental analysis for road pavements and materials applied within the urban
road network of Münster was performed in cooperation with the University of Innsbruck (Austria).
The first part of this research cooperation focused on the environmental potential within the production
of road materials applied to the Münster road network.
The road network in Münster is exclusively formed of asphalt pavement. Based on the experience
of the Department of Mobility and Civil Engineering of the City of Münster, we used the case study
presented in this paper to examine alternative asphalt production scenarios based on the application
of RAP as a raw material. The performed LCA study was based on test series and production data
from a representative asphalt plant in the Münster region (one of the main asphalt suppliers of the
City of Münster). The plant already produces particular asphalt mixtures containing RAP but has
been encouraged (mainly by the City of Münster) to intensify the application of RAP, and to further
enhance its production process from an environmental point of view. The potentials for the alternative
production scenarios were determined on the pavement level, i.e., for the complete pavement structure
with all its different layers and different asphalt types. Thereby, all pavement types applied in the road
network in the City of Münster were analyzed.
2. Road Materials and Pavements
In our LCA study, we applied the cradle-to-gate approach considering environmental impacts
and potential improvements from raw materials extraction to the finished products at the asphalt
plant. Thus, construction, use, maintenance, and demolition phases were not considered in the study.
The data used to characterize the evaluated road materials and pavements were provided by the
Department of Mobility and Civil Engineering of the City of Münster and the analyzed asphalt plant.
2.1. Current Situation in Münster
The construction strategies applied to the urban road network of the City of Münster generally
follow the German Guideline (RStO 12) entitled “Guidelines for the standardization of pavement
structures of traffic areas” [22].
Depending on the traffic load, the pavement consists of three to four different layers: surface,
binder (not applied to low traffic loads), base, and subbase (in this study called “unbound” because,
in Münster, only unbound mineral aggregates are applied for the subbase) (Figure 1). The pavement
is placed on a compacted subgrade whose thickness depends on the gradient of the road and the
characteristics of the terrain. The subgrade consists of unbound mineral aggregates for all pavement
variants and was not considered in this study.
Figure 1. General pavement structure applied in Münster [23].
In Münster, three different classifications of roads are generally distinguished: main roads
(MR), main access roads (MAR), and residential roads (RSDT). The Münster road network contains
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approximately 1200 km of roads, of which 80% are classified as residential roads, 13% as main roads,
and 2–3% as main access roads. The rest is classified as private road. The pavement structure generally
depends on the traffic load applied to the road section. The specifications (load class, materials,
and structure) of the road pavement currently used within the Münster road network are listed in
Table 1. Although the Münster road network does not contain motorways (MW), pavement for
motorways was also analyzed in this study for comparisons with the other types of pavement.
Table 1. Current pavement specifications of the City of Münster.
Motorway
Load Class
Material
Thickness (cm)
Bk 100-T
SMA 8 S
AC 22 BS
AC 32 TS
Unbound
3
9
14
50
SMA 8 S
AC 22 BS
AC 32 TS
Unbound
OR
SMA 8 S
AC 22 BS
AC 32 TS
Unbound
OR
AC 8 DS
AC 22 BS
AC 32 TS
Unbound
3
8
14
45
SMA 8 S
AC 16 BS
AC 22 TS
Unbound
OR
AC 8 DS
AC 16 BS
AC 22 TS
Unbound
OR
AC 8 DS
AC 22 TN + 40%RAP
Unbound
3
5
10
45
AC 8 DN
AC 22 TN + 40%RAP
Unbound
OR
AC 8 DN
AC 22 TN + 40%RAP
Unbound
3
10
45
Bk 32-T
Main Roads
Bk 10-T1
Bk 10-T2
Bk 3.2-T1
Main Access Roads
Bk 3.2-T2
Bk 1.8-T
Bk 1.0-T
Residential Roads
Bk 0.3-T
3
8
10
45
3
8
10
45
3
5
10
45
3
12
45
3
8
39
Surface layer
Binder layer
Base layer
Unbound
The load classes (Bk, “Belastungsklasse” in German) of the pavements shown in Table 1 are based
on the traffic load in terms of 10-ton axle passages (e.g., 10 to 32 million for Bk 32). The letter “T” in
the load class abbreviation indicates a traditional pavement type, which is currently applied within
the Münster road network. Pavement options within the load classes are distinguished as T1, T2, etc.
Later on, pavement types with modified asphalt mixtures containing RAP are indicated as M1, M2, etc.
The asphalt layers of the analyzed road pavements consist of stone mastic asphalt (SMA) and asphalt
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concrete (AC) mixtures. The nomenclature of these asphalt mixtures is explained in Figure 2. Since
SMA mixtures are exclusively applied as the surface layer, the identification as “D” is not included in
the specific abbreviations.
Figure 2. Nomenclature of asphalt materials [24,25].
As mentioned above, the analyzed asphalt plant was one of the main suppliers for the road
network of the City of Münster and was already producing asphalt mixtures containing RAP, which
were already being partially applied (e.g., AC 22 TN with 40% RAP). However, the goal of the
Department of Mobility and Civil Engineering of the City of Münster is to increase the RAP content
within the different asphalt mixtures to a maximum without deteriorating the technical characteristics
of the specific mixtures.
2.2. Asphalt Production Scenarios
Table 2 describes the asphalt mixtures analyzed in this study. The RAP content variations were
defined in cooperation with the asphalt producer, which needs to guarantee the technical equivalency
of the RAP asphalt mixtures. The asphalt plant can be characterized as a batch mixing plant that
applies the cold recycling method for the production of RAP asphalt mixtures, i.e., RAP is added
batchwise in ambient temperature to the already heated mineral aggregates, which requires additional
heat (depending on the RAP content) to further heat up the RAP for the mixing process. Table 2 lists
the densities and the mixing temperatures of the produced asphalt mixtures.
Table 2. Specification of the asphalt mixtures analyzed.
Material
Surface
Layer
Binder
Layer
TE
Base
Layer
Temperature (◦ C)
Aggregates and RAP (Cold Recycling)
SMA 8 S
AC 8 DS
AC 8 DS + 50% RAP
AC 8 DN
AC 16 BS
AC 16 BS + 10% RAP
AC 16 BS + 30% RAP
AC 16 BS + 50% RAP
AC 22 BS
AC 22 BS + 15% RAP
ACm22 BSC + 30%
t RAP
t
m
AC 22 TS
AC 22 TS + 10% RAP
L
m 22WTS +C 30% 100
AC
RAP t
AC 22 TN + 40% RAP
AC 32 TS
AC 32 TS + 60% RAP
AC 32 TN + 60% RAP
C
190
190
310
190
190
210
250
310
190
220
280
t
t
m
190
210
m
W 250 m
290
190
330
330
C
W
t
C
Mixing
170–180
170–180
160–170
170–180
170–180
170
170
160–170
165–180
165–180
165–180
t
155–180
155–180
t 155–180
100
155–180
170
155–180
155–180
Density (kg/m3 )
1
2452
2474
2489
2470
2509
2509
2508
2508
2561
2561
2489
2537
2537
2393
2372
2537
2383
2383
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The analyzed asphalt plant produces about 150,000 tonnes of asphalt per year, for which almost
98% of the heating energy required is sourced from coal and the remaining 2% is from light fuel oil.
The asphalt producer is able to provide an overall annual amount of coal and fuel oil consumed in its
plant (2018), which allows calculating the heating energy demand per average ton of asphalt produced,
as shown in Table 3.
Table 3. Energy demands for average asphalt mixture produced in the analyzed plant.
Inputs of Asphalt Production
Electricity
Heat (light fuel oil)
Heat (coal)
Diesel, internal transports
16.02 MJ/t
2.84 MJ/t
277.23 MJ/t
8.53 MJ/t
The amount of energy necessary to heat the aggregates and to perform the mixing process varies
with the percentage of RAP (Table 2), the moisture content, and the initial temperature of the raw
materials, thereby significantly influencing the environmental impacts of asphalt production.
Since the production data from the asphalt plant do not allow the determination of the specific
heat energy demands for the different asphalt mixtures, we decided to use Equation (1) [26], which
calculates the specific thermal energy (TE) demanded to produce each asphalt mixture analyzed.
M
P
mi × Ci × (tmix − t0 ) + mbit × Cbit × (tmix − t0 ) + mrap × Crap × (tmix − t0 )+
TE = M i=0
M
M
P
P
P
mi × Wi × Cvap × (tmix − 100)
mi × Wi × Wi +
mi × Wi × Cw × (100 − t0 ) + Lv ×
i=0
i=0
i=0
× (1 + CL) (1)
To perform the calculations and verify the results, a computer program (Excel, Microsoft, USA)
was used. The variables and values of the parameters to be used in the applied formula are presented
in Tables 4 and 5, which are based on values in the literature [26–29] as well on the specific conditions
found at the asphalt plant located in Münster.
Table 4. Values of the parameters used in Equation (1).
Parameter
Cbit
Ci
Cw
Cvap
Crap
Wi
Lv
CL
t0
tmix
mbit
mi
mrap
Specific heat coefficient of bitumen (50/70)
Specific heat coefficient of aggregates
Specific heat coefficient of water (10 ◦ C)
Specific heat coefficient of water vapor
Specific heat coefficient of RAP
Water content of aggregates
Latent heat of vaporization of water
Casing loss factor
Ambient temperature
Maximum temperature of aggregates & RAP
Mass of bitumen
Mass of aggregates and filler
Mass of RAP
2.09
0.86
4.19
1.83
0.86
3
2256
4.5
12
various
various
various
various
kJ/(kg·◦ C)
kJ/(kg·◦ C)
kJ/(kg·◦ C)
kJ/(kg·◦ C)
kJ/(kg·◦ C)
%
kJ/kg
%
◦C
◦C
kg
kg
kg
Note: The Ci value is for diabase aggregates [26–29].
The bitumen used to produce the asphalt mixtures includes polymer modified bitumen (PMB) for
stone mastic asphalt mixtures and 50/70 bitumen for asphalt concrete mixtures. However, in Equation
(1), only an average value of the specific heat coefficient is applied for both types of bitumen based
on Santos et al. [26]. The asphalt producer uses two types of rock for aggregates and filler, diabase
and limestone, but for the calculation of the heat demand, only the specific heat coefficient of diabase
aggregates was applied because we assumed that the major part used within the asphalt mixtures is
diabase aggregates.
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Table 5. Variable parameter values.
Surface
Layer
Binder
Layer
Base
Layer
Material
Temperature
(tmix )
Aggregates (mi )
SMA 8 S *
AC 8 DN
AC 8 DS
AC 8 DS + 50% RAP
AC 16 BS
AC 16 BS + 10% RAP
AC 16 BS + 30% RAP
AC 16 BS + 50% RAP
AC 22 BS
AC 22 BS + 15% RAP
AC 22 BS + 30% RAP
AC 22 TS
AC 22 TS + 10% RAP
AC 22 TS + 30% RAP
AC 22 TN + 40% RAP
AC 32 TS
AC 32 TS + 60% RAP
AC 32 TN + 60% RAP
190
190
190
310
190
210
250
310
190
220
280
190
210
250
290
190
330
330
802
834
843
459
896
832
640
472
919
779
637
909
818
636
537
909
372
378
Mass, kg/ton Produced
Bitumen (mbit )
RAP (mrap )
69
61
59
33
44
38
30
20
41
34
26
41
35
27
22
41
17
11
Filler (mi )
0
0
0
500
0
100
300
500
0
150
300
0
100
300
400
0
600
600
125
105
98
8
60
30
30
8
40
37
37
50
47
37
41
50
11
11
Note: * SMA 8 S contains 4 kg of cellulose, which was not considered in the heat demand calculation.
The initial temperature of the raw materials was assumed to be the average annual temperature
of the plant in Münster, which is 12 ◦ C. This average value, however, excludes the temperature of the
two coldest months (January and February) because the asphalt plant stops operations to perform
necessary maintenance during this period.
In Santos et al. [26], tmix is the mixing temperature of an asphalt mixture. In this paper, tmix is
the maximum temperature achieved, as required for the heating of the aggregates and RAP. Since the
demand of heat rises with the amount of RAP, Equation (1) was used to model the specific production
scenario of each asphalt mixture analyzed in this study. Although the temperature used in the formula
is the one applied to heat aggregates and RAP, the formula considers the overall amount of energy
required for the whole production process [26].
The casing loss factor (CL) represents the thermal energy radiated to the atmosphere and not used
to heat the mixture components [29]. This parameter varies from plant to plant depending on the
mixing equipment (e.g., parallel flow, double barrel, dual drum) and temperatures used to heat raw
materials and to perform the mixing process. Since the asphalt producer was not able to provide an
accurate value, the CL was determined by adjusting the average heat energy demand from the formula
results (averaged for all asphalt mixtures analyzed) to the average heating energy provided by the
producer, i.e., 280.08 MJ/ton (Table 3, coal + light fuel oil).
The electricity demand and diesel used for internal transport are the average amounts provided
by the asphalt producer (Table 3) and can be found in the Tables S1–S3, where all relevant inputs and
outputs used within the production process are given.
2.3. Pavement Structures
To evaluate the environmental performance of asphalt mixtures containing RAP, the pavement
structures in Table 1 were compared with traditional asphalt mixtures (as shown in Table 1) and
modified asphalt materials (maximum amount of RAP, Table 2) (Tables S4 and S5).
3. Life Cycle Assessment (LCA)
3.1. Goal and Scope
We aimed to identify environmental potential within the production of asphalt mixtures applied
to urban pavement in Münster.
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For the LCA study, we applied the cradle-to-gate approach; therefore, all life cycle phases from raw
material acquisition to the finished product in the asphalt plant were analyzed (i.e., A1–A3) [25,30,31].
RAP is a secondary raw material; thus, all environmental burdens before it reaches end of waste status
were not included in the analyzed system boundaries [32]. The transport from the demolition site
to the recycling (= asphalt) plant and further required crushing processes were included in the RAP
upstream processes. As the crushing process occurs in the asphalt plant, no further material transports
are required. Figure 3 shows the system boundaries and phases considered in the analysis.
Figure 3. System boundaries in this study.
The analysis was first carried out on material level and then on pavement level. The functional
unit used in this study was 1 kg of asphalt mixture produced at the asphalt plant analyzed and one
square meter of road pavement.
3.2. Life Cycle Inventory (LCI)
The LCI quantifies relevant inputs and outputs of the analyzed product systems. The primary
data, i.e., the data directly connected with the asphalt production (amount of raw materials, energy
sources, waste outputs, etc.), were collected by questionnaires answered by the asphalt producer and
the Department of Mobility and Civil Engineering of the City of Münster. The specific heat demands
for the asphalt mixtures were determined using Equation (1) in Santos et al. [26]. Relevant output
data, which could not be provided by the producer, were obtained from the literature [20]. Transport
distances consider the location of the specific suppliers of the plant (aggregates 205 km, bitumen
112 km, and filler 205 km). The distance from the average demolition site in Münster to the asphalt
plant (i.e., C2, RAP transportation) was set to 25 km. All materials are transported by a five-axle lorry
that meets the EURO 6 emission standard requirements [33]. The vehicle weighs approximately 14 tons
and has a maximum load capacity of 26 tons. The fuel used is biodiesel and the consumption is about
0.18 L/km when empty and 0.32 L/km when fully loaded.
All inputs and outputs were modelled using SimaPro 9.0 software [34] and the Ecoinvent 3.5
database [35]. Although the analyzed asphalt mixtures contained different types of bitumen, SimaPro
provides only one average dataset for bitumen, which was used to model all asphalt mixture LCIs.
The mineral aggregates were modeled with the dataset for crushed gravel. The filler applied for all
asphalt mixtures was milled limestone, for which the corresponding Ecoinvent dataset was applied.
The LCIs of all analyzed asphalt mixtures are listed in Tables S1–S3.
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3.3. Life Cycle Impact Assessment
The Intergovernmental Panel on Climate Change (IPCC) 2013 method [36] and the Cumulative
Energy Demand (CED) V1.11, based on the method published by Ecoinvent version 2.0 and expanded
by Pré Consultants for raw materials and available in the SimaPro database, were used for the life
cycle impact assessment. To assess the environmental impacts of asphalt production, the following
impact indicators were chosen [32]: Global Warming Potential—GWP (kg CO2 equivalent) [36] and
Non-renewable Cumulative Energy Demand—Nr-CED (MJ equivalent) [34,35].
To verify the reliability of the environmental results, a Monte Carlo simulation was performed
by applying the pedigree matrix method proposed by Ecoinvent [35,37]. To calculate the standard
deviation for every LCI entry, the pedigree matrix was based on six factors (i.e., reliability, completeness,
temporal correlation, geographical correlation, further technological correlation, and sample size).
Therefore, a random value within an uncertainty range (1–5) was specified for every inventory entry as
shown in Tables S1–S3.
To calculate the standard deviations, we used a lognormal uncertainty distribution with a 95%
confidence interval. For each comparison, 1000 runs were calculated to form an adequate uncertainty
distribution [35,37,38].
4. Results
4.1. Asphalt Materials Results
Table 6 and Figure 4 show the environmental impacts (GWP—Global Warming Potential and
Nr-CED—Non-renewable Cumulative Energy Demand) associated with the production of the asphalt
mixtures analyzed.
Table 6. Asphalt mixtures results.
Material
Surface Layer
Binder Layer
Base Layer
SMA 8 S
AC 8 DS
AC 8 DS + 50% RAP
AC 8 DN
AC 16 BS
AC 16 BS + 10% RAP
AC 16 BS + 30% RAP
AC 16 BS + 50% RAP
AC 22 BS
AC 22 BS + 15% RAP
AC 22 BS + 30% RAP
AC 22 TS
AC 22 TS + 10% RAP
AC 22 TS + 30% RAP
AC 22 TN + 40% RAP
AC 32 TS
AC 32 TS + 60% RAP
AC 32 TN + 60% RAP
nr-CED (MJ eq/kg)
GWP (kg CO2 eq/kg)
4.21
3.69
2.23
3.79
2.93
2.60
2.13
1.58
2.78
2.38
1.95
2.78
2.45
1.98
1.71
2.78
1.39
1.09
0.07
0.06
0.05
0.06
0.06
0.05
0.05
0.04
0.06
0.05
0.05
0.06
0.05
0.05
0.05
0.06
0.04
0.04
In general, Figure 4 shows that the production of asphalt mixtures to be applied in the surface
layers has a greater environmental impact than the asphalt materials used in binder and base layers
because the bitumen is responsible for a large share of gas emissions and the more bitumen in the
asphalt mixture, the greater the environmental impact.
Considering the asphalt materials without RAP, the production of AC 8 DS and AC 22 BS produced
fewer environmental impacts amongst the options used for surface and binder layers. For the base
layers, both asphalt materials AC 22 TS and AC 32 TS generated the same impact regarding nr-CED
and GWP indicators.
Sustainability 2020, 12, 6113
0.08
nr-CED [MJ eq/kg]
5.00
4.00
0.06
3.00
0.04
2.00
0.02
1.00
0.00
SMA 8 S
AC 8 DS
AC 8 DS + 50% RAP
AC 8 DN
AC 16 BS
AC 16 BS + 10% RAP
AC 16 BS + 30% RAP
AC 16 BS + 50% RAP
AC 22 BS
AC 22 BS + 15% RAP
AC 22 BS + 30% RAP
AC 22 TS
AC 22 TS + 10% RAP
AC 22 TS + 30% RAP
AC 22 TN + 40% RAP
AC 32 TS
AC 32 TS + 60% RAP
AC 32 TN + 60% RAP
0.00
GWP [kg CO2 eq/kg]
10 of 18
SURFACE
BINDER
nr-CED [MJ eq/kg]
BASE
GWP [kg CO2 eq/kg]
Figure 4. Results of asphalt mixtures concerning Non-renewable Cumulative Energy Demand (nr-CED)
and Global Warming Potential (GWP) indicators.
Despite the greater amount of energy required by asphalt materials with RAP, due to the heating
strategy used in the asphalt plant, the more RAP included, the lower the environmental burden
associated with the production of asphalt mixtures per both GWP and nr-CED indicators. This occurs
because the more RAP used, the fewer raw materials (e.g., aggregates and bitumen) and processes are
required to produce the asphalt mixtures.
The use of higher RAP contents potentially reduces nr-CED by 47% and GWP by 25% for surface
and binder layers, and approximately 61% nr-CED and 30% GWP for the base layers.
The comparison of asphalt mixtures applied to binder layers with the same amount of RAP,
such as AC 16 BS and AC 22 BS with 30% RAP or within base layers, e.g., AC 32 TS and AC 32 TN
with 60% RAP, indicated similar impacts concerning GWP. For nr-CED, however, the production of
AC 22 BS with 30% RAP instead of AC 16 BS with 30% RAP potentially reduces the impact by 8.6%,
whereas the production of AC 32 TN with 60% RAP instead of AC 32 TS with 60% RAP lowers the
environmental burden by 22%.
In Figure 5, the environmental loads per nr-CED results are divided into different categories,
considering the impacts of raw materials and processes caused by the mixtures during
asphalt production.
As shown in Figure 5, the bitumen is mainly responsible for the environmental burden associated
with the production of asphalt mixtures due to the energy and resources required for its extraction and
manufacturing processes.
Asphalt mixtures with RAP require less bitumen, which automatically reduces the impact
attributed to the bitumen in terms of nr-CED. However, increasing the RAP content increases the
amount of heating energy required, due to the cold recycling method applied by the asphalt producer.
Transportation was the category second most affecting the nr-CED results. The higher the amount
of bitumen and aggregates, the higher the transportation impact due to the distances the raw materials
must be transported to the asphalt plant. As the RAP is sourced from the demolition of Münster roads,
the distance for its transportation has little influence on nr-CED.
Figure 6 shows the impacts of asphalt production in terms of GWP. Figures 5 and 6 show that the
use of RAP, aggregates extraction, and electricity have the least influence on the entire environmental
impact caused by the production of asphalt materials.
Base
nr-CED [MJ eq/kg]
Binder
Surface
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SMA 8 S
AC 8 DN
AC 8 DS
AC 8 DS + 50% RAP
AC 16 BS
AC 16 BS + 10% RAP
AC 16 BS + 30% RAP
AC 16 BS + 50% RAP
AC 22 BS
AC 22 BS + 15% RAP
AC 22 BS + 30% RAP
AC 22 TS
AC 22 TS + 10% RAP
AC 22 TS + 30% RAP
AC 22 TN + 40% RAP
AC 32 TS
AC 32 TS + 60% RAP
AC 32 TN + 60% RAP
0%
Aggregates
Bitumen
20%
RAP
40%
Eletricity
60%
Heating
80%
Transport
100%
Others
Binder
Base
GWP [kg CO2 eq/kg]
Surface
Figure 5. Nr-CED results (%). Environmental impacts of asphalt mixtures divided into different categories.
SMA 8 S
AC 8 DN
AC 8 DS
AC 8 DS + 50% RAP
AC 16 BS
AC 16 BS + 10% RAP
AC 16 BS + 30% RAP
AC 16 BS + 50% RAP
AC 22 BS
AC 22 BS + 15% RAP
AC 22 BS + 30% RAP
AC 22 TS
AC 22 TS + 10% RAP
AC 22 TS + 30% RAP
AC 22 TN + 40% RAP
AC 32 TS
AC 32 TS + 60% RAP
AC 32 TN + 60% RAP
0%
Aggregates
Bitumen
RAP
20%
40%
60%
80%
100%
Eletricity
Heating
Transport
Others
Figure 6. GWP results (%). Environmental impacts of different categories of asphalt mixtures.
Heating is responsible for a greater share of the impact for asphalt materials composed of higher
percentages of RAP. For example, heating is responsible for approximately 50% of all impact generated
by the production of AC 32 TS with 60% RAP and AC 32 TN with 60% RAP in terms of GWP.
In general, transportation is responsible for approximately 20% of the GWP. Bitumen and heating
are responsible for 15%–30% of impact depending on the amount of RAP and bitumen used to produce
the asphalt materials. Therefore, the higher the RAP content, the higher the heating and the lower the
bitumen. The higher the bitumen content, the less heating required.
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4.2. Pavement Structure Results
Table 7 shows the nr-CED and GWP results attributed to the traditional and modified structures.
Figure 7 depicts the data in a chart.
Structure
MW
MR
MAR
nr-CED [MJ eq/m²]
RSDT
nr-CED (MJ eq/m2 )
GWP (kg CO2 eq/m2 )
2061.62
1333.25
1978.14
1272.46
1695.82
1139.91
1659.78
996.28
1493.62
1162.27
1457.58
1018.64
1179.68
1175.77
762.89
796.37
681.79
700.62
45.40
37.58
43.17
35.57
37.56
31.64
37.22
30.30
33.29
29.50
32.95
28.16
30.32
27.58
23.71
22.61
21.57
19.50
BK 100-T
BK 100-M
BK 32-T
BK 32-M
BK 10-T1
BK 10-M1
BK 10-T2
BK 10-M2
BK 3.2-T1
BK 3.2-M1
BK 3.2-T2
BK 3.2-M2
BK 3.2-M3
BK 1.8-T
BK 1.8-M
BK 1.0-T
BK 1.0-M
BK 0.3-T
2500
50
2000
40
1500
30
1000
20
500
10
0
MW
MR
nr-CED [MJ eq/m²]
BK 0.3 - T
BK 1.0 - M
BK 1.0 - T
BK 1.8 - M
BK 1.8 - T
BK 3.2 - M3
BK 3.2 - M2
BK 3.2 - T2
BK 3.2 - M1
BK 3.2 - T1
BK 10 - M2
BK 10 - T2
BK 10 - M1
BK 10 - T1
BK 32 - M
BK 32 - T
BK 100 - M
BK 100 - T
0
GWP [kg CO2 eq/m²]
Table 7. Pavement structures results.
MAR
RSDT
GWP [kg CO2 eq/m²]
Figure 7. Nr-CED and GWP results for different pavement structure.
Figure 7 shows that the higher the traffic load designed for the road, the greater the environmental
burden associated with the pavement structure. Therefore, the production of asphalt mixtures used to
compose Bk 100 structures potentially have a greater impact than Bk 32, and Bk 32 should have greater
impacts than Bk 10. In general, the asphalt materials used for traditional motorway structures have a
66% greater impact in terms of nr-CED than Bk 0.3 structures and around 57% more in terms of GWP
due to the greater amount and quality of raw materials demanded.
The traditional structures have more of an environmental impact compared with the modified
alternative. The production of asphalt materials to create modified structures instead of traditional
ones can lower the nr-CED up to 42% and 19% in terms of GWP.
The environmental burden associated with the Bk 100-M is 35% lower in nr-CED and 17% lower
in GWP compared with Bk 100-T. The Bk 100-M structure potentially has less of an impact than Bk 32-T
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MAR
RSDT
nr-CED [MJ-eq/m²]
MR
MW
and almost the same impact as Bk 32-M. Hence, even with the higher amount of road materials required
to compose motorway roads, the results demonstrated that the process of choosing less impactful road
materials to construct each layer can considerably decrease the overall impact associated with road
pavement construction.
In the MR category, the pavement structure Bk 10-M2 had the least impact. In the MAR
category, Bk 3.2-M2 produced less impact than the other options for both indicators. The alternative
Bk 3.2 structures (i.e., M1 and M2) performed slightly better than the structure tested by Münster
(i.e., Bk 3.2-M3), decreasing the nr-CED by 31% and GWP by 15% compared with the traditional option
(i.e., Bk 3.2-T1), whereas Bk 3.2-M3 reduced the impacts per nr-CED by 21% and per GWP by 9%.
Figures 8 and 9 show the environmental burdens associated with each layer in terms of nr-CED
and GWP indicators. Despite the higher thickness, the unbound layer produced less of an impact
of production within all asphalt materials. As observed in Figure 5, the nr-CED results were highly
influenced by bitumen. Therefore, due to the lack of bitumen, the unbound layer had a minor
contribution to the impact results.
BK 100 - T
BK 100 - M
BK 32 - T
BK 32 - M
BK 10 - T1
BK 10 - M1
BK 10 - T2
BK 10 - M2
BK 3.2 - T1
BK 3.2 - M1
BK 3.2 - T2
BK 3.2 - M2
BK 3.2 - M3
BK 1.8 - T
BK 1.8 - M
BK 1.0 - T
BK 1.0 - M
BK 0.3 - T
0%
Surface Course
20%
Binder Course
40%
60%
Base Course
80%
100%
Unbound Course
Figure 8. Nr-CED impact contribution of pavement layers.
In general, the base layer had major environmental impacts due to its thickness and raw materials
used. The greater the thickness, the higher amount of raw materials and the higher the amount of
bitumen, which is the road material that affects nr-CED values the most. The asphalt material modelled
for base layers has a lower RAP content in comparison with the surface and binder layers, which also
influenced the results since the environmental burden attributed to the surface and binder layers is
directly related to the amount of RAP used to compose the asphalt mixtures.
As shown in Figure 6, transportation has a considerable influence on the impacts caused by the
production process. Thus, most of the impact of the unbound layer in Figure 9 is due to its composition
of 100% aggregates, sourced from outside Münster.
The impact caused by the different layers in terms of GWP (Figure 9) depends on the amount of
RAP and bitumen used to produce asphalt materials. As heating considerably influenced the GWP
results, the layers designed with asphalt materials and RAP are responsible for a larger share of the
environmental influence than in the nr-CED results.
MR
MAR
RSDT
GWP[kg CO2-eq/m²]
MW
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BK 100 - T
BK 100 - M
BK 32 - T
BK 32 - M
BK 10 - T1
BK 10 - M1
BK 10 - T2
BK 10 - M2
BK 3.2 - T1
BK 3.2 - M1
BK 3.2 - T2
BK 3.2 - M2
BK 3.2 - M3
BK 1.8 - T
BK 1.8 - M
BK 1.0 - T
BK 1.0 - M
BK 0.3 - T
Surface Course
0%
20%
Binder Course
40%
60%
80%
100%
Base Course Unbound Course
Figure 9. GWP impact contribution of pavement layers.
4.3. Monte Carlo Analysis
Figure 10 shows the probability that the environmental impacts of the traditional asphalt mixtures
is higher or lower compared to asphalt mixtures with the highest content of RAP. Figure 10 also
provides a comparison with asphalt materials without RAP.
Figure 10. Monte Carlo simulation of asphalt materials.
According to Figure 10, the asphalt materials containing higher amounts of RAP have lower
environmental impacts than the traditional materials. The comparison between traditional asphalt
materials applied to surface and base layers showed similar performances. The AC 22 BS used within
binder layers performed slightly better than AC 16 BS.
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Figure 11 shows the Monte Carlo simulations applied to traditional and modified structures that
potentially perform better for each group of traffic load. The results showed that pavement structures
containing asphalt materials with higher amounts of RAP have a higher probability of producing less
of an impact on the environment than the traditional structures used within Münster pavements.
Figure 11. Monte Carlo simulation of pavement structures.
5. Conclusions and Future Works
In this study, we analyzed the environmental impacts associated with the production of asphalt
mixtures applied to urban pavements in Münster and identified the benefits of using recycled materials,
such as reducing the carbon footprint of road pavement constructions.
The results show that, despite the high amount of heating energy required due to the cold
recycling method applied by the Munster asphalt plant, that increasing the amount of RAP reduces the
environmental impacts during the production of asphalt mixtures.
The use of larger amounts of recycled raw material to compose the asphalt mixtures does not only
reduce the impacts of primary raw material extraction but also the impacts caused by transportation.
The transportation distances were reduced from an average of 160 km to 25 km. If we consider the
average of CO2 -emission recommended by McKinnon [39,40] for road transport operations (62 g
CO2 /tonne-km), the use of RAP to produce asphalt mixtures can lower the emissions by up to 217.62 kg
CO2 /tonne-km.
The results additionally indicated that asphalt mixtures without RAP applied to surface (i.e., AC
8 DS and AC 8 DN) and base layers (i.e., AC 22 TS and AC 32 TS) perform similarly. Within the binder
layer, the AC 22 BS has lower environmental burdens than AC 16 BS.
In general, the pavement structures designed to support lower traffic loads have minor
environmental impacts due to the reduced demand for raw materials. The structures with reduced
environmental impact potential are the combination of asphalt materials with the highest amount
of RAP as possible. For main access roads, the structure Bk 3.2-M2 produces a lower environmental
burden than the other Bk 3.2 structures; for main roads, Bk 10-M2 has a higher environmental impact.
The data used in this paper represent the reality in Münster and may not be applicable to other
situations. The modified structures suggested in this study include asphalt materials that potentially
have lower environmental impacts and may not be suitable for real application since local regulations
must be considered in pavement design. Nevertheless, the findings provide guidance on how to apply
Sustainability 2020, 12, 6113
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life cycle assessment to evaluate the environmental impacts of asphalt production and can provide the
basis for comparison with similar cases.
Despite all benefits presented, to calculate the total advantages of using RAP, it is necessary to
evaluate the lifetime of pavements composed with asphalt mixtures with a higher content of RAP and
include this variable in a future ‘cradle-to-grave’ analysis.
In this study, we only considered the production phase to evaluate the environment impacts
of the asphalt mixtures. Therefore, to fully evaluate the sustainability of the road network in
Münster, we intend to perform a cradle-to-grave and cradle-to-cradle analysis and include construction,
maintenance, demolition, and end of life phases in future works.
Supplementary Materials: The following are available online at http://www.mdpi.com/2071-1050/12/15/6113/s1.
Table S1: Surface layer inputs; Table S2: Binder layer inputs; Table S3: Base layer inputs; Table S4: Amount
of material needed to compose traditional structures; Table S5: Amount of material needed to compose
modified structures.
Author Contributions: All authors have contributed for the current paper. Data collection, writing—original
draft preparation, M.S.S.L., F.G., A.B., and C.Q.; supervision, project administration, funding acquisition, A.B.,
C.Q., A.T., and F.G.; writing—review and editing, M.H., S.H., R.S., A.B., C.Q., A.T., and F.G. All authors have read
and agreed to the published version of the manuscript.
Funding: This project has received funding from the European Union’s Horizon 2020 research and innovation
program under the Marie Sklodowska-Curie grant agreement no. 765057.
Acknowledgments: This study is part of the SAFERUP! Project, an innovative training network devoted to
develop safe, accessible, and urban pavements. The authors appreciate the support provided by the Road
Construction Department from Münster, as well as the company Oevermann (asphalt plant) for the collaboration.
Conflicts of Interest: The authors declare no conflicts of interest.
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