A Novel Approach to Estimating Greenhouse Gas Emissions from Federal Highway Construction Projects in Brazil

Abstract

In Brazil, the maintenance and expansion of the federal road network conflict with the country’s climate neutrality goals. The National Department of Transportation Infrastructure (DNIT), responsible for Brazil’s federal highways, lacks tools to assess and mitigate greenhouse gas (GHG) emissions from its projects, which can be achieved through the life cycle assessment (LCA) methodology. Additionally, the scarcity and insufficient quality of environmental data on Brazilian road materials led to using foreign databases in LCA studies conducted in Brazil, generating uncertainties in the results. This research aims to apply LCA to analyze the GHG emissions from highway projects developed by DNIT. The analysis covers the phases of material production, transportation, and construction. Additionally, this study investigates the influence of the leading project disciplines on the results and the differences in outcomes resulting from the use of local Portland cement compared to its equivalent produced in the United States of America (USA) and Europe. The results indicate that the materials production phase has the most significant impact on the project’s global emissions, contributing over 78% in all scenarios. The transportation phase accounts for more than 16% of global emissions, with the potential for greater contributions depending on project transportation distances. Environmental data showed that foreign cement increased the project’s global emissions by 7.31% (Europe) and 12.91% (USA), with the most significant differences observed in pavement disciplines. In all scenarios, the discipline of new pavement presented the highest unitary emissions, followed by the discipline of restored pavement, which showed average values 58% lower than the former, and earthworks. Other services, drainage, and special structures disciplines showed minimal influence on the results. In conclusion, this research proposes an approach to estimate the environmental impact of Brazilian federal highway projects, enabling early mitigation of GHG emissions during the design phase, focusing on critical disciplines and materials, and highlighting potential distortions associated with the use of environmental data from foreign cement in LCA studies of Brazilian highways. Finally, considerations are presented regarding improving and expanding the scope of the calculation methodology used in this study, allowing for a more comprehensive and accurate analysis of the environmental impacts associated with the Brazilian federal road network.

1. Introduction

Transportation infrastructure plays a crucial role in the economic and social advancement of any country, adapting to the growing demand for the movement of people and goods. In Brazil, the National Logistics Plan 2035 (PNL 2035) foresees investments of up to 246 billion dollars in transportation infrastructure by 2035, driving a projected 11% growth in Gross Domestic Product (GDP) [1].

On the other hand, the transportation sector not only influences economic and social aspects but also considerably impacts the environment. Estimates indicate that about 25% of global CO₂ emissions are attributed to transportation (including all modes of transport), with predictions of a 60% increase by 2050 if adequate interventions are not implemented [2]. The sector may surpass previous projections, representing a significant challenge to avoid undesirable climate changes [3,4,5].

The transportation sector’s environmental impact is even more relevant for emerging economies like Brazil, which plan significant investments in expanding and maintaining their transportation infrastructures [6]. Brazil’s transportation matrix is predominantly road-based, with approximately 1.72 million kilometers of federal, state, and municipal highways. Most of this total consists of unpaved roads (78.5%), representing considerable potential for expanding the national road network in the coming years [7]. Furthermore, the maintenance of existing roads in Brazil, totaling around 65 thousand kilometers at the federal level, increasingly demands the consumption of natural resources and industrial activities that can result in substantial environmental impacts [8].

The Brazilian government plans to invest around 13 billion dollars in the road transport sector by 2027, aiming to construct approximately 2.5 thousand kilometers of highways, in addition to measures to improve road safety and traffic flow on existing highways [9]. However, Brazil’s gross greenhouse gas (GHG) emissions continue to rise, reaching 2.4 billion tons in 2021 (a 12.2% increase from 2020), with the transportation sector being one of the main contributors, accounting for 203.8 million tons of CO₂ equivalent (CO₂ eq.) [10,11].

In this scenario, Brazil faces the challenge of reconciling road infrastructure development with goals to reduce GHG emissions, as established in Brazil’s Nationally Determined Contribution (NDC) to achieve carbon neutrality by 2050 [12]. One possible solution is applying the life cycle assessment (LCA) tool in managing Brazil’s highways, offering pathways to achieve this balance efficiently and transparently.

Conceptually, LCA can assess the potential environmental impact of a product or process by examining all inputs and outputs during its life cycle, from the manufacture of materials to the end of its useful life. Its methodological basis is distributed across two primary standards of the Brazilian Association of Technical Standards (ABNT): ABNT NBR ISO 14040 [13] and ABNT NBR ISO 14044 [14]. LCA does not have a specific scope and requires a significant effort throughout a highway’s life cycle, mainly due to the need to establish assumptions and consider specific local conditions [15].

The earliest records of studies related to the application of the LCA tool in the road sector date back to the late 1990s, with publications covering topics such as the analysis of low-carbon fuel standards for road vehicles [16], examination of transportation networks [17], analysis of pavement construction using different types of materials [18], evaluation of asphalt binder types and cement production [19,20], and the development of inventories related to key road inputs [21]. The leading scientific publications on using LCA in the road sector are in developed countries, emphasizing the United States of America, Canada, Italy, Switzerland, England, Spain, France, and Australia [22,23]. Among developing countries, China has the highest number of research studies on life cycle assessment on highways [24]. In contrast, Brazil still has a limited number of publications focused on its context, i.e., LCA studies that consider project design specifications, raw materials, industry technology, energy matrix, and other variables linked to the construction, maintenance, and operation chain of a highway in Brazil. Nevertheless, progress can be observed in research recently conducted in Brazil [25,26,27,28,29,30,31].

Regarding LCA studies of highways conducted in Brazil, four striking characteristics have been identified [32]: (i) use of environmental data for materials produced in the USA and Europe, likely due to the lack of representative and reliable national data, particularly for inputs such as steel, Portland cement, and petroleum asphalt cement (PAC); (ii) use of international software as support for LCA calculations, even with the standard use of inputs and project solutions that do not meet the specifications of the National Department of Transportation Infrastructure (DNIT), thus not reflecting what is traditionally practiced on Brazilian highways; (iii) absence of analyses aimed at quantifying the degree of uncertainty of the results due to the quality of environmental data on inputs and the assumed boundary conditions in the studies; and (iv) prevalence of analyses limited to comparing the environmental impacts of rigid and flexible pavement solutions, thus not encompassing the impacts of other design disciplines, such as earthwork and special structures (bridges, viaducts, and tunnels).

In Brazil, the administration of federal highways is managed by DNIT, a federal government agency subordinated to the Ministry of Transportation. DNIT is responsible for establishing the primary technical standards for transportation infrastructure projects in the country, including regulations published by its Institute of Transportation Research (IPR) [33] and the Reference Cost System for Works (SICRO) [34], a system managed by DNIT and adopted by the public and private sectors as the primary national reference for the preparation of budgets related to transportation infrastructure. In addition to establishing budgeting rules, SICRO meets IPR specifications regarding project design and execution of road services. It also provides details in its database regarding the type of fuel and performance parameters of equipment used in road works execution. Regarding IPR standards, no specifications assess the environmental impacts of materials and engineering solutions in road projects, i.e., quantifying GHG emissions is not considered a normative criterion for the development of federal highway projects in Brazil.

In this context, the objective of this research is to develop a calculation model, named the LCA-BR Model, to estimate GHG emissions from Brazilian federal highway projects. This model utilizes LCA concepts and considers the stages of material production, transportation, and highway construction, as well as the technical specifications of DNIT (IPR and SICRO) and emission factors available in national and international public databases. Subsequently, the proposed model is applied in a case study to investigate the total carbon footprint of a highway project. In this case study, the analysis examines the impact of key design disciplines on the outcomes and the disparities in outcomes resulting from the utilization of local Portland cement compared to its counterparts produced in the USA and Europe. Cement was the only variable among the three scenarios, as it is the material with the highest quantity (approximately 78,000 tons) in the project selected for the case study. This suggests that cement may have a significant influence on the project’s GHG emission results.

2. Materials and Methods

The methodology employed in this research incorporated the standards of the Brazilian Association of Technical Standards (ABNT) (ABNT NBR ISO 14040 [13]; ABNT NBR ISO 14044 [14]) or their corresponding versions in the International Organization for Standardization (ISO), as well as the project design specifications for federal highways in Brazil, with a particular emphasis on the norms of the IPR [33] and the SICRO [34]. The methodology phases of this study include goal and scope definition, inventory analysis, impact assessment, and interpretation. The phases of the proposed methodology were used to develop the LCA model, which was then applied in a case study.

2.1. Goal and Scope Definition

As mentioned earlier, the main objective of this study is to develop an LCA model to assess GHG emissions associated with the material production, transportation, and construction phases of Brazilian federal highway projects, followed by the subsequent application of the developed model in a case study. GHG emissions are quantified and expressed in terms of CO₂ eq. The scope of the study encompasses the full project and the individual analysis of specific disciplines, including new pavement, restored pavement, earthworks, special structures, and drainage, as well as other services such as vertical, horizontal, and construction signage, complementary works like fences, road safety devices, and bus stop construction, as well as environmental and landscaping services.

2.2. System Boundaries, Inventory Data, and LCA Model Outputs

The system boundaries are defined by the unitary processes considered in the LCA study and were formulated to encompass the life cycle represented by the phases of material production, transportation, and construction. Figure 1 provides an overview of the system boundaries and the phases of the LCA-BR Model. These phases are divided into three: Phase 1—engineering data, Phase 2—environmental data, and Phase 3—LCA outcomes.

Figure 1 demonstrates that Phase 1—engineering data is responsible for organizing the data from the project budget into the Material (M), Transport (T), and Construction (C) LCA phases. This includes obtaining performance parameters of the equipment used in the project, the type of energy source consumed (fuels or electricity), the total productive hours of each piece of equipment, and the list of materials with their corresponding quantities. The descriptions associated with each of these LCA phases are as follows: Material (M): interpreted according to the definition given by ISO 14048 [35] as “cradle-to-gate”, this phase encompasses all operations necessary for the production of materials used in the project services, from the extraction of raw materials from nature to their final processing in the industrial facilities at the construction site or the production/commercialization center. All materials listed in the project, including the equipment used in their production, the transportation of raw materials extracted from nature to the industrial center, and internal factory transportation, are classified in this phase. Transport (T): includes all transportation operations necessary for the project execution, conducted after the materials leave the factories. Construction (C): comprises all operations carried out by equipment operating directly in the field, including machinery used in earthworks services, such as graders and excavators, and pavement construction, such as texture curing machines and pavers.

In Phase 2—environmental data, information on emission factors (kg CO₂ eq./functional unit) related to the production process of materials (FEM), electricity generation by the National Interconnected System (NIS) (FEE), and fuel combustion during equipment operation activities (FEC) are incorporated into the LCA model inventory. For materials, it was chosen to select publicly accessible references whose environmental declarations have followed the recommendations of ABNT NBR ISO 14040 [13] and ABNT NBR ISO 14044 [14] standards or their equivalent versions published by ISO. Additionally, in the selection of FEMs, priority was given to environmental declarations that also followed the guidelines of ISO 14025 [36], ISO 21930 [37], EN 15804+A1 [38], and EN 15804+A2 [39] standards. For the calculation of FEE, national average data released by the Energy Research Company (EPE) [40] were considered, and for FEC, data published by the Environmental Company of the State of São Paulo (CETESB) [41] and by the Intergovernmental Panel on Climate Change (IPCC) [42] were considered. This latter factor was subdivided into FECgas (related to the combustion of Brazilian commercial gasoline) and FECdiesel (associated with the combustion of Brazilian commercial diesel).

In addition, for the selection of FEMs, the Pedigree Matrix proposed by Weidema [43] was considered (represented in the flowchart of Figure 1 by the designation “DQI Method”). This matrix employs five indicators to assess the quality of environmental data from LCA studies: source reliability, completeness, temporal correlation, geographical correlation, and technological correlation. These indicators are scored on a scale from 1 (lower quality) to 5 (higher quality), allowing a semi-quantitative evaluation of the environmental data quality in the inventory. In this study, FEMs with the best quality indices were selected.

Regarding the organization of inventory data in the LCA model, the factors FEE and FEC were included in the “background system”, as their estimates are based on parameters that vary over time and are not under the control of the processes of the project under study. The other inventory data (factor FEM and engineering data), being specific or satisfactorily representing the processes related to the selected project, were added to the “foreground system”, as indicated in the flowchart of Figure 1.

In Phase 3—LCA outcomes, the outputs of the LCA model are presented for the analysis scenarios of Brazil (BR), Europe (EUR), and the United States of America (USA). The only variable among the three scenarios is the FEM of cement, whose main characteristics are described below:

• Scenario BR

  -

  Type of cement: Portland CP II-F 32

  -

  Declarant: VOTORANTIM CIMENTOS

  -

  Geographic representativeness: Sobradinho, Distrito Federal-DF, Brazil

  -

  Temporal representativeness of inventory: 09/2022—09/2023

  -

  Type of environmental declaration: declaration without third-party validation

  -

  FEM_CEMENT-BR: 606 kg CO₂ eq./t of cement

• Scenario EUR

  -

  Type of cement: Portland Composite Cement CEM II

  -

  Declarant: CEMBUREAU (THE EUROPEAN CEMENT ASSOCIATION)

  -

  Geographic representativeness: Europe (average data)

  -

  Temporal representativeness of inventory: 2016

  -

  Type of environmental declaration: declaration with third-party validation

  -

  FEM_CEMENT-EUR: 683 kg CO₂ eq./t of cement

• Scenario USA

  -

  Type of cement: Blended cement types (IP, IS, IL, IT)

  -

  Declarant: PORTLAND CEMENT ASSOCIATION (PCA)

  -

  Geographic representativeness: USA (average data)

  -

  Temporal representativeness of inventory: 2019

  -

  Type of environmental declaration: declaration with third-party validation

  -

  FEM_CEMENT-USA: 742 kg CO₂ eq./t of cement

Efforts were made to establish the closest possible equivalence between the types of cement in the analysis scenarios based on information from the Brazilian Concrete Institute (IBRACON) [44] and Natalli et al. [45].

The LCA-BR Model’s results are expressed in terms of total emissions, measured in tons of CO₂ equivalent (t CO₂ eq.), and based on the functional units established in this study (t CO₂ eq./functional unit) (Section 2.3). Figure 2 contains the detailed calculation routines of Phase 3.

The expressions EM and EE in Figure 2 represent the equations used to obtain the deterministic values of emissions, both in terms of total emissions (t CO₂ eq.) and unit emissions (t CO₂ eq./functional unit), related to the production of materials and the operation of equipment in the project, respectively. The formulations of these equations are detailed as follows:

$$EM=\sum _{i=1}^n{FEM}_i\times {QM}_i\times {10}^{-3}$$

(1)

FEM_i is the emission factor related to the production process of each material (in kg CO₂ eq/unit of reference material), and QM_i is the quantity of the material present in the full project and discipline groups (in units of reference material).

$$EE={EE}_{elet}+{EE}_{comb}$$

(2)

EE_elet and EE_comb are the emission values (in t CO₂ eq. or t CO₂ eq./functional unit) associated with the operation activities of equipment powered by electricity generated by the National Interconnected System (NIS) and national commercial fuels (diesel or gasoline), respectively. The formulations of these two expressions are presented below.

$${EE}_{elet}={\sum }_{i=1}^n {QHe}_i\times {Pe}_i\times FEE\times {10}^{-3}$$

(3)

${QHe}_i$ is the total quantity of operating hours of each equipment that uses electricity as its energy source (in hours), Pe_i is the nominal power of the equipment (in kW), and FEE is the emission factor related to electricity generation by the NIS (in kg CO₂ eq./kWh).

$${EE}_{comb}={\sum }_{i=1}^n{\sum }_{j=1}^2{{ QHc}_i\times Pc}_i\times {CC}_i\times {{FEC}_j\times 10}^{-3}$$

(4)

${QHc}_i$ is the total quantity of operating hours of each equipment that uses fuel as its energy source (in hours), Pc_i is the nominal power of the equipment (in kW), CCi is the average fuel consumption by the equipment (in L/kWh), and FECj is the emission factor of fuel combustion during the equipment operation activities (in kg CO₂ eq./L).

The unit emission results were obtained by dividing the total emission values by the total linear extension of the selected project for the full project and the following disciplines: earthwork, pavement restoration, new pavement, drainage, and other services (i.e., vertical, horizontal, and construction signage, complementary works such as fences, road safety devices, and bus stop construction, and environmental and landscaping services). For the discipline of special structures, the unit emission was obtained by dividing the corresponding total emission value by the total area of the deck to be executed in the project. The calculation routine presented in Figure 2 was applied individually to the three analysis scenarios: BR, EUR, and USA. The calculations were performed in Microsoft Excel (version 2405), with programming developed in Visual Basic for Applications (VBA) supporting them.

2.3. Functional Units

The results of the LCA model are linked to two functional units. The first functional unit is represented by the construction of a Brazilian federal highway class I-A, 1 km long, in a flat region, with a design speed of 80 km/h, featuring a duplicated roadway (two independent roadway lanes, each with two lanes, with individual widths of 3.60 m), with an accumulated volume of commercial vehicles in the 20th year of 17,000,000. This functional unit was applied to the results of the full project and the discipline groups: earthwork, pavement restoration, new pavement, drainage, and other services. The second functional unit refers to the special structures discipline and consists of 1 m² of special structure deck constructed on a Brazilian federal highway class I-A.

2.4. Overview of the Case Study

Figure 3 shows the linear diagram detailing the pavement solutions of the DNIT executive project for the highway BR-080/DF (DNIT n°484/2022-00) [46]. The construction of BR-080/DF is divided into two distinct phases. The initial phase, which is the subject of this study, covers the segment from km 0 to km 24.6, while the subsequent phase will be carried out between km 24.6 and km 40.3.

Table 1. Main parameters of the BR-080/DF project.

Parameter	Feature
Highway project class (DNIT, Brazil):	I-A (dual roadway, partial access control).
Type of region:	Predominantly flat with a maximum superelevation of 10%.
Cross-sectional type:	Two independent roadways, each with 2 lanes with individual widths of 3.60 m. Outer shoulder width of 3.0 m, inner shoulder width of 1.20 m, and variable central median width with an average of 8.0 m.
Service life of pavements:	20 years.
Total volume of commercial vehicles over the project service life of pavements:	17,000,000, with 18% buses and 82% trucks.

Source: DNIT [46].

summarizes the characteristics of the main parameters of the BR-080/DF project.

3. Results and Discussion

3.1. Phase 1—Engineering Data

The LCA-BR Model for the BR-080/DF project considered 32 materials and 101 pieces of equipment, partially represented in

Table 2. A partial list of materials from the BR-080/DF project considered in the LCA-BR Model according to the LCA phase, full project, and disciplines. Supplementary Table S1 contains all 32 road materials.

Code SICRO	Description	LCA Phase	Unit	Quantities
				FP	EW	PR	NP	SS	D	OS
M1954	Portland Cement CP II—32—bulk	M	t	58,185	-	17,292	39,759	1132	-	-
M0424	Portland Cement CP II—32—bag	M	t	20,541	-	-	12,651	533	4532	2825
M1943	Petroleum Asphalt Cement—30/45	M	t	2029	-	1947	20.43	-	-	61
M0003	CA 25 Steel	M	t	1368	-	412	946	9.78	-	-
M0191	Crushed Stone 1	M	t	263,026	-	32,704	128,619	2995	95,691	3015
M0946	ASTM A572 Grade 50 Profile Steel	M	t	683	683	-	-	-	-	-
M0004	CA 50 Steel	M	t	1394	-	167	383.47	436.83	351.08	56.08
M0082	Washed Medium Sand	M	t	60,286	-	-	32,069.84	3635	14,510	10,070
M0192	Crushed Stone 2	M	t	142,169	-	27,977	86,046	398.84	21,469	6278
M1968	Semi-malleable metal guardrail	M	m	18,822	-	-	-	-	-	18,822
M0028	Medium Sand	M	t	107,283	-	43,286	63,596	-	-	400

Acronyms: FP—full project, EW—earthworks, PR—pavement restoration, NP—new pavement, SS—special structures, D—drainage, OS—other services.

and

Table 3. A partial list of equipment from the BR-080/DF project considered in the LCA-BR Model according to the LCA phase, full project, and disciplines. Supplementary Table S2 contains all 101 pieces of road equipment.

Code SICRO	Description	LCA Phase	Unit 1	Quantities
				FP	EW	PR	NP	SS	D	OS
E9667	Dump truck—14 m3	T	h	86,197	86,197	-	-	-	-	-
E9579	Dump truck—10 m3	T	h	76,509	46	20,361	40,960	475	-	14,664
E9506	Dump truck—6 m3	T	h	22,287	-	6302	-	-	-	15,984
E9571	Tank truck—10,000 L	T	h	7916	7180	143	565	-	-	27
E9592	Flatbed truck—15 t	T	h	8405	7.70	1060	4635	746	-	1954
E9515	Hydraulic excavator—1.56 m3	C	h	5511	5502	-	-	-	-	9
E9145	Concrete dump truck: 7 m3	T	h	5722	-	1206	4515	-	-	-
E9685	Sheep’s foot roller of 11.6 t	C	h	8381	7834	-	521	-	-	25
E9686	Flatbed truck with crane—20 t.m	T	h	4839	-	-	-	-	1139	3699
E9044	Concrete plant—150 m3/h	M	h	2348	-	396	1905	20	12	14
E9524	Grader—93 kW	C	h	3963	2869	491	370	-	85	146

Note ¹ Represents the total operating time of the equipment, i.e., when the equipment is with the engine running and in service. Acronyms: FP—full project, EW—earthworks, PR—pavement restoration, NP—new pavement, SS—special structures, D—drainage, OS—other services.

, respectively.

The BR-080/DF project materials and equipment included in the LCA-BR Model inventory are the most significant in quantities. Combined with their corresponding emission factors (detailed in Section 3.2), they represent 95% or more of the project’s total CO₂ eq. emissions.

3.2. Phase 2—Environmental Data

Table 4. A partial list of materials from the BR-080/DF project with their respective FEM and quality indicators (IQDs). Complete environmental data for all 32 materials are in Tables S5–S8.

Code SICRO	Description	FEM (kg CO2 eq./Unit 1)	DQIs 2	Context
M1954 M0424	Portland Cement CP II—32	606.00	4,5,5,5,5	Brazil
	Portland Composite Cement CEM II	683.00	4,4,3,2,2	Europe
	Blended cement types (IP, IS, IL, IT)	742.00	5,4,4,2,2	USA
M1943	Petroleum Asphalt Cement—30/45	637.00	4,5,3,2,3	USA
M0003	CA 25 Steel	1840.00	5,5,4,3,4	Brazil
M0191	Crushed Stone 1	4.89	5,5,4,2,4	USA
M0946	ASTM A572 Grade 50 Profile Steel	3330.00	5,5,4,3,4	Brazil
M0004	CA 50 Steel	1840.00	5,5,4,3,4	Brazil
M0082	Washed Medium Sand	3.63	5,5,4,2,4	USA
M0192	Crushed Stone 2	4.88	5,5,4,2,4	USA
M1968	Semi-malleable metal guardrail	87.90	5,5,4,2,4	Italy
M0028	Medium Sand	3.63	5,5,4,2,4	USA

Note ¹ Table 2 and Supplementary Table S1 show the units associated with each material. Note ² The reported IQD values are chronologically associated with the following indicators: source reliability, completeness, temporal correlation, geographical correlation, and technological correlation. A value of “1” represents the poorest quality, and a value of “5” represents the best quality of the environmental data.

presents a partial list of materials included in the LCA-BR Model inventory, with their respective FEM, the results of the semi-qualitative analysis performed by the IQD method, and the geographical context associated with the environmental data.

Table 4 shows that the FEMs in the LCA-BR Model have both national and international origins, as there are no publicly accessible local references for all inventory materials that meet the regulatory requirements for Phase 2 environmental data (Section 2.2). Nevertheless, the selected FEMs have high national representativity among the 32 materials. In the BR scenario, inputs with national FEMs include bulk and bagged cement, CA-50 steel, CA-25 steel, and ASTM A572 profiles, together accounting for approximately 84% of the total emissions from materials. Cement produced in the BR-080/DF project region alone accounts for 74% of this total. The FEMs for other priority materials come from sources in Australia, Italy, and USA.

The environmental data of the LCA-BR Model are complemented by the FEE (

Table 5. Emission factor related to electricity generation by the National Interconnected System (NIS).

Factor	Unit	Value	Observation	Reference
FEE	Kg CO2 eq./kW h	0.035	The adopted value represents the average relative to the period from Jan/2023 to Jul/2023. 1 The values disclosed by EPE consider only the contribution of the following GHGs: CO2, CH4, and N2O.	Database consulted: EPE [40]. Calculation methodology details: EPE [47].

Note ¹ Period with the most recent data available at the time of the inquiry.

) and the FECs (

Table 6. Emission factors related to fuel combustion during equipment operation activities.

Factor	Fuel	Value (kg CO2 eq./L)
FECgasolina-m	Gasoline (blend)	2.096
FECdiesel-m	Diesel oil (blend)	2.621

). It should be noted that the estimated FECs in this research use emission parameters for mobile equipment as the basis for calculation [41,42]. Therefore, due to the lack of a national reference to estimate this emission factor for SICRO stationary equipment, the values in Table 6 were used in the LCA-BR Model without distinguishing between mobile and stationary equipment that uses fuel as an energy source.

The detailed calculations associated with the FECs in this research are provided in the Supplementary Materials (Memorials S1 and S2).

3.3. Phase 3—LCA Outcomes

3.3.1. Total Emissions

Table 7. Total CO₂ eq. emissions according to LCA phases and scenarios (in t CO₂ eq.).

Discipline	LCA Phase and Scenario					Global Value
	M	M	M	T	C
	BR	EUR	USA	All Scenarios		BR	EUR	USA
Full Project	65,334	71,396	76,040	15,365	2261	82,960	89,022	93,667
Earthworks	2283	2283	2283	6785	975	10,044	10,044	10,044
Pav. Restoration	15,608	16,940	17,960	2000	195	17,804	19,136	20,156
New Pavement	37,245	41,281	44,373	4184	340	41,770	45,805	48,897
Special Structures	1948	2076	2174	95	173	2216	2344	2443
Drainage	4075	4424	4692	77	147	4300	4649	4916
Other Services	4174	4392	4558	2221	430	6826	7044	7211

Acronyms: M—Material, T—Transportation, C—Construction.

presents the total CO₂ eq. emission results according to the LCA phases, analysis scenarios, full project, and its disciplines. It also describes the global emission values associated with each project discipline and analysis scenario, representing the sum of the total CO₂ eq. emissions of their LCA phases.

Table 7 shows that the differences among the three scenarios are solely related to the Material phase, driven by the discrepancies in the FEM values of CP II-F 32 cement produced in Brazil compared to its counterparts in Europe and the USA. Analyzing the values for the Material phase reveals that the primary differences between the scenarios lie within the disciplines of new pavement construction, pavement restoration, and drainage. These project disciplines contain a higher proportion of cement in their cost compositions, contributing to the most significant relative differences in the LCA results.

Regarding the total CO₂ eq. emission values, Table 7 shows that the full project in the BR scenario has the lowest value among the three scenarios, totaling 82,960 tons. Using the Brazilian scenario as a reference, the EUR scenario shows 89,022 tons, representing an increase of 7.31%. The USA scenario records 93,667 tons, an increase of 12.91% compared to the BR scenario.

New pavement is also observed as the project discipline with the most significant differences in total CO₂ eq. values between the scenarios. Using the BR scenario as a baseline, the new pavement in the EUR scenario is 9.66% higher, while in the USA scenario, this increase is 17.06%. As previously mentioned, this behavior is related to the higher proportion of cement in the cost compositions of this discipline’s subsystem. The LCA results tend to reflect the differences in FEM values for the cement used in the scenarios analyzed.

Figure 4 shows the relative contribution of project disciplines to the total CO₂ eq. emissions by the LCA phase.

It is observed that disciplines related to pavement predominately contribute to the total CO₂ eq. emissions in the Material phase. Considering the average between the three scenarios, new pavement accounts for 57% of the total emissions of this phase, followed by pavement restoration with 24%. These two disciplines account for approximately 81% of the total CO₂ eq. emissions of the Material phase of the BR-080/DF project.

Regarding the Material phase, Figure 4 shows that the drainage and other services disciplines each contribute approximately 6%, totaling 12% of this phase’s total CO₂ eq emissions. Additionally, it is noted that the special structures, despite having significant proportions of cement and steel in their cost compositions (inputs with high FEM values), contribute only 3.5% of the total emissions for the Material phase. This behavior is explained by the low representation of the special structures discipline in the overall quantities of the BR-080/DF project. The earthwork discipline contributes approximately 3.5% of the total CO₂ eq. emissions for the Material phase, influenced by the use of metal profiles (ASTM A572 Grade 50 Profile Steel—Table 2) in the construction of embankments on soil with low load-bearing capacity.

From Figure 4, it is noted that the CO₂ eq. emissions for the Transportation phase are led by the earthwork discipline (44.4%) and new pavement (27%), followed by other services (14%) and pavement restoration (13.5%). The special structures and drainage disciplines have meager individual contributions in this phase, each contributing less than 1%. The dominance of the earthwork discipline in this phase is justified by the nature of its services, such as transporting materials from borrow pits to construction fronts, where the average transport distance (ATD) reaches 61.56 km for one of the borrow pits indicated in the project. For the new pavement discipline, the predominance is explained by the transportation of large quantities of materials, such as steel (with an ATD of 60.4 km) and cement (with an ATD of 65.6 km), from supplier centers to the construction site or service fronts in the field. This reasoning can be extended to the other services and pavement restoration disciplines, although with lower materials volumes than new pavement, and thus lower contributions to the total CO₂ eq emissions for the Transportation phase.

In the Construction phase, Figure 4 shows that the earthwork discipline stands out in total CO₂ emission, contributing 42.5% of its total value. Following this, other services (18.5%) and new pavement (15%) occupy the second and third places in terms of contribution to this phase’s total CO₂ eq emissions. These proportions are related to differences in the performance of field equipment and the volumes of services associated with each project discipline, reflected in the total operating hours and, consequently, the total fuel consumption by the equipment operating in the field.

Figure 5 represents the contributions of the LCA phases to the total emissions of the full project. In contrast, Figure 6 shows the average influence of the LCA phases on the total emissions of each discipline.

Figure 5 illustrates the differences in the contribution of LCA phases to the total CO₂ eq. emissions of the BR-080/DF project. It is noticeable that the Construction phase has a relatively low contribution compared to the other phases, with an average across the three analyzed scenarios of 2.5%. The Transportation phase, primarily governed by the operation of dump trucks with capacities of 14 m³ and 10 m³ (Table 3), exhibits a contribution to the total CO₂ eq emissions of the project ranging from 18.5% (BR scenario) to 16.4% (USA scenario).

Although there are differences regarding pavement solutions and highway design classes, it can be stated that the proportions between the LCA phases in this research are close to those described in the literature [48,49,50,51]. However, the actual contributions of the Transport and Construction phases to the total emissions of the BR-080/DF project may be higher. Initially, this is because the operational performance parameters of the SICRO equipment [34] used in this research refer to new equipment with updated technologies, which may not correspond to reality in Brazilian construction sites. Secondly, the assumptions adopted in the second phase of this research methodology do not consider the uncertainties inherent in the operating conditions of the equipment, such as the influence of the type of terrain (natural or paved bed) and the irregularities of the road surface on the average fuel consumption, which could increase the total CO₂ eq. emissions of these two LCA phases.

Figure 6 shows the influence of the Material phase on the total emissions of the disciplines of new pavement, restored pavement, special structures, drainage, and other services is evident. Regarding the discipline of earthworks, its emissions are predominantly governed by the Transport phase at 67.6%, the Material phase at 22.7%, and the Construction phase at 9.7%.

Regarding the earthworks discipline, it is essential to consider the contribution of the Material phase to its total CO₂ eq emissions, which probably does not follow the pattern observed in other road projects with similar characteristics. The BR-080/DF project involves the occasional construction of embankments with driven piles and metal profiles, which increases the percentage of the Material phase in this discipline.

The emissions related to the special structures discipline in this study should also be interpreted with caution and reinforce the observation from the previous paragraph, mainly if used in comparison with other case studies. This is due to the variability of interventions and the types of structures planned in the BR-080/DF project, which involves widening an existing structure and constructing three others: a viaduct, a bridge, and a pedestrian walkway. Therefore, the results (total and unit) of CO₂ eq. emissions from the special structures discipline in this study may be different from those of other studies, especially those that only involve the construction of new bridges or viaducts.

3.3.2. Unit Emissions

Table 8. Unitary CO₂ equivalent emissions according to LCA phases and scenarios (in t CO₂ eq./func. unit).

Discipline	Func. Unit		LCA Phase and Scenario				Global Value
		M	M	M	T	C
		BR	EUR	USA	All Scenarios		BR	EUR	USA
Full Project	km	2653.68	2899.90	3088.56	624.09	91.83	3369.61	3615.83	3804.49
Earthworks	km	92.72	92.72	92.72	275.60	39.62	407.95	407.95	407.95
Pav. Restoration	km	633.97	688.05	729.50	81.27	7.93	723.17	777.25	818.69
New Pavement	km	1512.80	1676.71	1802.31	169.98	13.80	1696.57	1860.49	1986.09
Special Structures	m2	0.97	1.03	1.08	0.05	0.09	1.10	1.16	1.21
Drainage	km	165.53	179.70	190.57	3.14	5.98	174.64	188.81	199.68
Other Services	km	169.55	178.38	185.15	90.25	17.47	277.27	286.10	292.87

Acronyms: M—Material, T—Transportation, C—Construction.

presents the results of CO₂ eq. emissions per unit for the full project and its disciplines, that is, the emission values relative to the functional units established in the methodology of this research (Section 2.3). This involves re-displaying the results from the previous section, divided by the total length of the BR-080/DF project (24.60 km). The special structures discipline is the only exception, with its value divided by the total area of the newly constructed bridge deck (2018.18 m²). There are also the global unit emission values of CO₂ eq., which are the sum of the unit emissions from the LCA phases of each analysis scenario, organized according to the full project and its disciplines.

The results highlight the new pavement as the primary source of unitary global CO₂ eq. emissions from the project, with values of 1696.57 t CO₂ eq./km in the BR scenario, 1860.49 t CO₂ eq./km in the EUR scenario, and 1986.09 t CO₂ eq./km in the USA scenario. These results present a similar order of magnitude to those observed in the literature. Although a direct comparison is not possible due to differences in pavement layer thicknesses, ADTs of the projects, and variations in environmental data sources, a similar study conducted by Souza [50]—which used a system with parameters from the SICRO equipment at that time—found a value of 1725 t CO₂ eq./km for the new rigid pavement discipline, considering the production phases of Materials, Transportation, and Construction.

In this context, the results demonstrate that LCA studies of highways, when investigating pavement disciplines (new and restored), focus on critical design disciplines for the global warming environmental indicator. However, the results also show that the earthwork discipline is a relevant variable concerning CO₂ eq. emissions and should not be underestimated in these studies. Despite ranking third in terms of unitary emissions in the BR-080/DF project, the actual value of the earthwork discipline may be even higher, considering the conservative assumptions employed in the methodology of this research regarding operating conditions and performance parameters of SICRO equipment, as described in the previous section.

Furthermore, the result of the earthwork discipline is directly impacted by the ADTs between the soil quarries and the field service fronts. For example, a 100% increase in the current ADT value of 33.77 km of the soil quarries in the BR-080/DF project would raise the unitary emission of this discipline by 68%, resulting in 683.55 t CO₂ eq./km. In this simulation, the earthwork (with 407.95 t CO₂ eq./km) and pavement restoration disciplines show similar values in the BR scenario, which would result in an equivalence in contribution to the total project emissions. This reinforces the importance of considering earthwork in LCA studies of highways.

The disciplines of other services, drainage, and special structures are ranked in the fourth, fifth, and sixth positions in terms of unitary emissions of CO₂ eq. The first two show averages among the three scenarios of 285 t CO₂ eq./km and 187.71 t CO₂ eq./km, respectively, with slight differences between the absolute values of the scenarios. The special structures discipline also demonstrates a slight variation among the absolute values of the three scenarios, with an average unitary emission among the scenarios of 1.16 t CO₂ eq./m².

Finally, analyzing the values in Table 8 related to the full project, it is observed that the BR scenario exhibits the lowest global unitary emission of CO₂ eq. among the investigated scenarios, totaling 3369.61 t CO₂ eq./km. The percentage differences between the result of the BR scenario and the other scenarios follow the percentages already reported in the previous section, meaning there was an increase in the global unitary emission of the project by 7.31% in the EUR scenario and 12.91% in the USA scenario. These differences demonstrate the high sensitivity of the deterministic result of the LCA-BR Model to variations in the FEM value of cement.

4. Conclusions

The LCA-BR Model proposed in this research and applied in a case study enabled the achievement of the previously established objectives. The study’s main conclusions are described below.

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The BR scenario has the lowest total CO₂ eq. emissions for the full project and its disciplines, followed by the EUR scenario, and finally, the USA scenario, which had the highest emissions. The variations in results stem from different FEMs of cement.

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The Material phase significantly contributed to the total CO₂ eq. emissions of the full project, followed by the Transportation phase. On the other hand, the Construction phase had minimal contributions in all scenarios.

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In the Material phase, the disciplines of new and restored pavement are responsible for approximately 81% of the total emissions of this phase. This demonstrates the importance of pavement disciplines in the total emissions of the investigated project and helps understand the behavior of highway LCA studies found in the literature, which often prioritize these disciplines in their studies.

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The Transportation phase is the second-largest LCA phase in contribution to the total CO₂ eq. emissions of the full project. Depending on the project’s ADTs, it can also play a significant environmental role. This suggests that this phase should not be underestimated in highway LCA research. Additionally, the conservative assumptions used in this research to calculate equipment emissions suggest that the results for the Transport and Construction phases may be higher, further reinforcing the importance of transportation in these studies.

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The results of unitary CO₂ eq. emissions maintained the ranking order of the scenarios, with the BR scenario presenting the lowest emissions, followed by the EUR and USA scenarios. In all scenarios, the discipline of new pavement presented the highest unitary CO₂ eq emissions, followed by the disciplines of restored pavement, which showed average values 58% lower than the first, and earthworks.

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The disciplines of other services, drainage, and special structures ranked fourth, fifth, and sixth in terms of unitary CO₂ eq. emissions, respectively, with less significant values.

It should be noted that due to the lack of a real system reflecting the current conditions of the selected project execution and the limited number of national studies with a scope similar to this research, the forecasts obtained from the developed LCA-BR Model have not been fully validated. This gives the results of this study a theoretical nature. Furthermore, the results of this research should be understood as indicative of a specific situation and not representative of all Brazilian federal highway projects with concrete rigid pavement solutions.

Finally, despite the progress achieved with the proposed ACV-BR Model, which incorporates national parameters for the design of Brazilian federal highways (SICRO and IPR specifications), it is imperative to consider expanding its scope to include the maintenance and restoration (M&R), use, and end-of-life phases of highways. This expansion should consider the evolution of functional and structural parameters of pavements over time, as well as the influence of traffic and maintenance plans on GHG emissions. Additionally, the enhancement of the model should be evaluated to reflect the influence of the quality of environmental data on its results, expressing them in probabilistic terms with an associated margin of uncertainty. This probabilistic and more comprehensive approach to the highway life cycle will provide a holistic and improved understanding of environmental impacts, contributing to more sustainable decision-making in the Brazilian road infrastructure sector.