Methodology for Quantification and Identification of Environmental Aspect in Urban Infrastructure Projects in the Planning Phase

Abstract

The accelerated development of construction has positively boosted the economy but caused environmental pollution. The objective of this article was to propose a model to quantify and identify the causes of environmental aspects in urban infrastructure projects during the pre-construction phase. The methodology included ten environmental aspects and six construction activities, distributed in three phases: quantification, preparation of an inventory and identification of the main causes of environmental aspects. The results of projects A, B and C confirmed five environmental aspects with quantifications of the maximum normalized unitary ratios, namely greenhouse gas emissions with 1.00, 1.00 and 1.00; energy use with 0.99, 0.99 and 1.00; noise pollution with 0.84, 0.89 and 1.00; water use with 0.95, 1.00 and 0.96 and use of resources and raw materials with 1.00, 1.00 and 1.00, caused by the construction methods, machines, materials and environmental conditions of the urban infrastructure project. This proposal was the first initiative to analytically and previously investigate the environmental performance of future infrastructure works, assisting in the strategies of the pre-construction phase and improving the decision-making process regarding environmental issues in constructions. Finally, this initial effort may evolve to create opportunities to avoid, mitigate, reduce or accept the environmental effects in the infrastructure projects in developing countries.

1. Introduction

Developing countries needed strategic plans to build their megaprojects in construction and infrastructure [1]. However, the accelerated development of construction positively boosted the economy, while causing environmental pollution. The decline in the environmental impact of the construction industry is an important current issue [2]. Project design teams seek resilient solutions to the threats posed by construction on the natural environment [3]. Since 1990, the industry has shown more interest in sustainability [4], involving several areas of construction [5,6]. However, inadequate environmental information in planning documents is a limitation to decision makers in terms of strategic environmental assessment [7], in addition to uncertainties related to construction phase emissions [8]. Understanding social, environmental and economic interactions produces a better green economy in the infrastructure sector [9], thereby helping to permanently and progressively mediate the environmental impacts.

Methodologies for assessing sustainability were categorized and developed based on frameworks derived from international standards and guidelines [10]. In China, a methodology was developed to quantify environmental pollution from construction projects in an automated manner using MS Project^® (free version) [11]. Other methods emphasized the importance of quantifying environmental impacts and suggested a model for creating environmental management indicators [12,13]. Cao et al. [14] proposed a method for verifying the characteristics of environmental incidents using environmental risk management. Therefore, there is an imminent need to develop models capable of mapping and measuring current ecosystem services [15]. The use of quality management tools served to enhance research in identifying the causes of environmental impacts, such as cause and effect diagrams [16,17,18]; brainstorming sessions and questionnaires [19,20]; observation and characterization of the local operation process [21] and indicators [22,23]. The Ishikawa diagram was suggested to solve a situation where the goal or objective was placed at the head of the fish and the contributing factors were systematically categorized along the spine [24]. To identify the cumulative effects of environmental impacts, network diagrams were used to analyze causality in the context of environmental assessments [25].

Environmental assessment methods were most useful during the design phase due to their potential to mitigate environmental impacts [26]. This finding motivated the present research to develop an assessment method for the pre-construction phase. However, the establishment of theoretically optimal environmental impact assessments still faces practical challenges, such as technical limitations, resource constraints and the complexity of ecosystems [27]. Given the need for new environmental assessment models, this study justifies its proposal by offering an objective environmental assessment approach.

Thus, understanding the variables that influence the causes of environmental aspects was important for preparing predictive flexible models for each type of construction site. Opportunities arose to explore the phenomena that led to improvements in the operational and environmental performance of projects [28]. Predictive models provide essential information on urban ecosystems and reveal the unique characteristics of urban planning [29]. Studies on causal factors provide decision makers with proactive and reactive analyses and the possibility of improving the construction plan and minimizing problems during construction, but there is no strictly objective model capable of analyzing the most important environmental aspects. The aim of this study was to develop an environmental assessment methodology for urban infrastructure projects that would (i) quantify ten environmental aspects externalized by six main activities in the pre-construction phase, (ii) compare the environmental aspects in three real cases and create an environmental inventory, and (iii) identify the causes of environmental aspects. By identifying the causes of environmental impacts, it is possible for designers to reduce those during the pre-construction phase when modifications in the design are more effective and allow them to focus on the sustainable development goal of having more sustainable cities and communities. This article is divided into five sections. Section 1 presents a conceptual approach to the issue. In Section 2, the methodology is divided into three phases. Section 3 discusses the results, while 4 and 5 include the discussion and conclusions, respectively.

2. Literature Review

2.1. Sustainability

The term sustainable development is understood as the improvement of quality of life through healthy environments favorable social, economic, and environmental conditions for present and future generations [30]. The most widely adopted definition of sustainability comes from the Brundtland Commission, which describes it as development that meets the needs of the present without compromising future generations [31]. Thus, the economy, the environment, and social responsibility constitute the three pillars of sustainability [32,33]. Sustainable development expands opportunities to fulfill aspirations for a better life [34].

Sustainability in the construction industry was first introduced in the early 1990s [4]. During this period, sustainability became a key issue on the British government’s political agenda, which emphasized the need for research on the integration of social and environmental issues, explicitly including the construction industry [35]. Initially, sustainability was incorporated through the adoption of environmental management systems designed to address an organization’s environmental impacts [36].

Linear infrastructure projects cannot be effectively assessed using just any tool or methodology [12]. Assessments of civil infrastructure during the planning phase have become crucial for ensuring sustainability [37]. Traditional approaches to infrastructure projects have defined project success in terms of economic deliverables focused on schedule, budget, and quality, thus achieving economic benefits while generating adverse social and environmental impacts [38]. However, the concept developed in Agenda 21 at the 1992 Earth Summit extended urban development needs to a strategic level concerning environmental issues [12]. Research then began to assess the environmental impacts of infrastructure during the early stages of the life cycle [39].

2.2. Environmental Management Standards

The first environmental management standard, the British Standards Institution (BSI) 7750, was published in 1992 in England. That same year, the United Nations Conference on Environment and Development was held in Brazil [40].

In February 1993, the European Union introduced the Program Towards Sustainable Development, established by Regulation (EEC) No. 1836/93 [41,42]. Three years later, the International Organization for Standardization (ISO) published ISO 14001 [43], based on BSI 7750 [44], outlining the requirements for implementing environmental management systems in organizations. Following these standards, various studies on environmental management and environmental assessments were developed [44,45,46].

In the first decade of the 21st century, the International Organization for Standardization (ISO) not only revised previous standards but also introduced new ones, as one of the key drivers for companies to implement environmental management systems was the need to comply with environmental legislation [47].

ISO 14001 and ISO 14004 defined requirements, standards, and support for management systems [43,48]. Additionally, the International Organization for Standardization (ISO) published ISO 14010, which outlined general principles for environmental auditing [49]. In 2003, ISO 14015 was introduced, providing guidance on environmental assessments [50], while ISO 14021 specified the requirements for environmental declarations [51].

In the development of environmental performance assessment processes and tools, ISO 14031 and ISO/TR 14032 provided the framework [52,53]. Meanwhile, life cycle assessment (LCA) methodologies were introduced worldwide, and the ISO 14040, 14041, 14042, and 14043 standards established concepts, system boundaries, and assessment methods [54,55,56,57].

The standardization process significantly advanced environmental management worldwide. The increasing visibility of major environmental challenges, highlighted by international conferences, led to regulatory actions implemented by governments to mitigate the negative effects of construction activities. In parallel, standards and regulations were introduced to establish uniform procedures for environmental management globally and to encourage the development of environmental certification systems.

2.3. Environmental Certification Systems

Environmental certification systems were developed to evaluate the environmental control measures implemented by the construction industry. However, these systems were designed based on the climatic and regulatory conditions specific to each region [58] and prioritized particular environmental aspects relevant to each context [59].

Most certification systems for the construction industry have focused on energy consumption, water efficiency, material use, and indoor environmental quality [58]. Consequently, the need emerged for the development of decision-support systems regarding environmental issues to weigh and rank the established criteria [60]. These certification systems also include recommendations and promote the development of sustainable actions in buildings through the adoption of criteria and scoring frameworks [61], while also assisting and encouraging efforts to improve environmental quality and building performance [37].

Many commercial methods have been developed to assess the environmental performance of construction activities, including HKBEAM (Hong Kong Building Environmental Assessment Method), introduced by the Environmental Technology Center; LEED (Leadership in Energy and Environmental Design), offered by the U.S. Green Building Council; BREEAM (Building Research Establishment Environmental Assessment Method), proposed by the British Research Establishment in the United Kingdom; and HPBG (High-Performance Building Guidelines), established by the New York City Department of Design and Construction [62]. Other systems include CASBEE (Comprehensive Assessment System for Built Environment Efficiency), developed in Japan, and HQE (Haute Qualité Environnementale), developed in France [63].

However, LEED is an environmental rating and certification system designed for the U.S. construction industry. It was created in 1996 by the U.S. Green Building Council (USGBC), and in its current version for new constructions (LEED-NC) [64]. LEED criteria are distributed across six categories: sustainable sites, water efficiency, energy and atmosphere, materials and resources, indoor environmental quality, and an additional five credits allocated to the innovation and design process category [65].

Environmental certification systems contribute to the classification of projects. However, the qualitative criteria suggested by these systems constrain evaluations within a fixed framework. Additionally, subjectivity in audits—where the perceptions of internal and external auditors influence the completion of standardized checklists—introduces inaccuracies. Due to concerns over audit results, increasing efforts have been directed toward anticipating environmental aspects through the development of more objective and easily adaptable environmental assessment methodologies. In summary, certification systems have emerged with multiple objectives, including standardization, compliance, and the maintenance of environmental responsibilities. At the same time, they provide certifications to institutions, highlighting their environmental commitment and generating positive impacts on their public image.

2.4. Environmental Assessment Methodologies

Methodologies have been developed to identify indicators related to urban planning and construction projects [12]. However, there are few studies on the integration of environmental management aspects, especially in the construction planning phase [66]. It is urgent to establish a methodology for identifying sustainability indicators for project management. No standard or model has been observed for identifying such indicators that follows a technical-scientific methodology [12], probably due to the holistic and anthropocentric nature of sustainability, which has complicated attempts at objective analysis and evaluation [67].

Environmental management has become fundamental in the construction industry, and quantitative methods have been developed by various researchers. When analyzing the databases of the American Society of Civil Engineers and Compendex Ei, it was identified that only 2% of the articles provided quantitative methods in environmental management for the construction industry [66]. Fifteen years later, Araújo et al. [68] conducted a systematic review of the Web of Science database and also identified only 2.54% of the articles.

At the beginning of the 21st century, significant works directed toward infrastructure (urban planning) were published, particularly in 2000 in China, due to the pollution burden caused by the construction industry. A pollution index was proposed to quantify and identify the best construction plan in terms of environmental impact [11,66,69]. Two years later, a study on sustainable urban development was published, introducing a framework called BEQUEST, aimed at addressing sustainability issues in urban development [70]. In response to the concern of measuring and assessing sustainable urban projects, quantifiable, reproducible, and representative indicators were proposed for classifying urban developments [71].

In the building sector, a predictive methodology was applied in Europe to identify and assess environmental aspects in buildings using a matrix model based on selected environmental criteria [72]. Additionally, an online tool was developed to construct an environmental assessment benchmark [73]. Following this, new research employed multi-criteria decision support methods to weigh, classify, measure, and evaluate environmental issues in the construction industry applied to buildings [62,74,75,76,77]. Aiming to provide a theoretical and conceptual contribution, a process system was recommended to enable the description, measurement, and assessment of various building performance aspects by German researchers [78].

Despite the significant scientific outputs of the first decade of the 21st century, there was a lack of publications in developing countries, as knowledge and experiences belonged to research centers in countries with the world’s largest economies.

Starting in 2010, new, precise, and rigorous environmental assessments for infrastructure emerged. A methodology for identifying sustainability indicators by establishing a relative importance between existing indicators was proposed [12]. The following year, sustainability criteria were prioritized for application in urban planning processes, considering only stakeholder opinions [79]. In an effort to minimize environmental impacts, a model for the selection of construction methods was developed [80].

In 2016, a quantitative method for assessing the effectiveness of ecological indicators, based on three pillars—degrees of linkage, coverage, and representation—was proposed [81]. Due to the gap in the social dimension of sustainability, a system of social indicators for megaprojects was recommended [82]. Megaprojects have caused significant environmental impacts, and therefore there was a need to assess sustainability levels [37,38,83,84].

In Australia, a model was proposed to quantitatively analyze environmental impacts, mitigation costs, and timing in two hundred infrastructure construction projects [85]. In 2019, a method for assessing health risks from particulate matter suspended in the air due to infrastructure activities was developed as a decision-making tool for a construction company [86]. In 2020, a methodology applied in the pre-construction phase quantitatively assessed ten environmental aspects resulting from six infrastructure activities [87]. Currently, a direct and replicable approach was identified in the literature to quantify urban ecosystem services [15].

Research directed towards buildings between 2010 and 2021 included the social dimension, where an environmental assessment model using life cycle assessment (LCA) for construction processes was considered to assess damage to human health [88]. A method was proposed to investigate health impacts on people caused by construction projects [89]. Similarly, advances were observed in research that included stakeholder concerns and the worker safety risk levels [90,91].

A causal model for identifying environmental impacts was suggested to relate the causes of environmental impacts to construction activities [92]. The proposals for quantitative methodologies of environmental aspects, up to the present moment, have evolved by relating environmental criteria, such as budget and quantity objectively, and the severity criterion subjectively, using matrices for the integration of calculations [63].

An environmental sustainability assessment tool based on criteria for residential buildings in Iran was used to quantify the environmental impact of buildings [93]. In 2014, research developed an effective method for modeling and assessing complex, dynamic, and nonlinear interacting variables using computational simulation [94]. Two years later, an assessment model specifically for social housing was developed by applying a multi-perspective development process [95].

An index to identify environmental aspects in the pre-construction phase (feasibility study) demonstrated the importance of early identification of environmental issues and aided decision-making in later stages [96]. Another index for measuring sustainability was proposed, although it was calculated in the later stages of projects [97]. Gaps related to construction site location were filled by a construction site index called the Green Construction Site Index (GCSI) [13]. With the creation of several indexes, a composite index was used to evaluate the sustainability of a building and assess the building’s sustainability performance [98].

Research on environmental assessments in buildings continues to be published. In 2019, a decision-making tool for estimating environmental impacts and emissions at construction sites was presented to contractors in the sector [99]. In 2020, research assessed environmental aspects of urban infrastructure works by quantifying the severity and duration of environmental aspects [87]. Another study determined real-time monitoring indices of environmental pollutants at the construction site of a multi-family housing complex [100].

In 2021, a method for sizing green wall structures to reduce noise pollution was published [101]. The following year, a study in Malaysia investigated and selected low-carbon construction materials for construction projects [102]. A study specifically tailored for urban infrastructure projects was published, aiming to improve the performance of a neighborhood [20]. In the area of project management, a study was completed and published in 2024, which verified the applicability of Lean Construction tools in construction projects, critically analyzing and classifying them according to their impact on sustainability [103].

Now in 2025, two studies were released in the Web of Science database. The first was a scientometric analysis of life cycle sustainability assessment for buildings [10], and the second study developed a new framework for construction project managers using artificial intelligence, agility, and environmental performance, as the incorporation of artificial intelligence and environmental sustainability in construction management allowed for the identification of sustainable solutions with more assertive green approaches [28].

Unlike the first and second decades, this third phase has presented a disruptive level of scientific production. This demonstrates the importance and need for the creation of environmental assessment methodologies in construction projects with the goal of creating interoperability with current tools, software, and technologies.

3. Materials and Methods

The methodology was divided into three phases—quantification, inventory development and identification of the causes of environmental aspects—and applied in three real cases (Figure 1).

3.1. Quantification

Environmental aspects have been defined as the elements of the activities, products, or services of an organization that may interact with the environment [41,43]. It has been stated that an aspect is directly linked to an impact [46]. Urban environmental problems are phenomena that directly impact the environment of cities and can cause pollution, heat islands, thermal inversion inversions, acid rain, flooding, and landslides.

In this research, the most significant aspects were adopted, the quantifiable ones with the possibility of occurrence in real cases used for the quantification of the aspects. The selection of the ten environmental aspects was determined by applying the relative importance index presented in the previous research [87].

The first phase was to obtain three real urban infrastructure cases from an urban development company using the six standard construction activities. Initially, ten environmental aspects were selected: total suspended particles (TSPs), greenhouse gas emissions (GGE), noise pollution (NP), soil alteration (SA), soil pollution (SOILP), water pollution (WP), resource and raw material use (RRMU), construction and demolition waste (CDW), water use (WU) and energy use (EU). The environmental aspect values were calculated using the equations below.

A literature review on construction and sustainability identified ten general environmental aspects arising from construction projects [68]. Another study deepened the investigations and discovered a total of twenty-eight environmental aspects, to which a relative importance index (weighting) was assigned in order to identify the most relevant environmental aspects [87]. The ten most important environmental aspects, with real possibilities for quantification, were selected for the present methodology.

Next, the ten environmental aspects were calculated in the six construction activities: earthmoving (A-E), rainfall drainage systems (A-RDS), water supply system (A-WSS), electric energy system (A-EES), paving (A-P) and curbing (A-C). The methods used for absolute quantifications of the ten environmental aspects are described below (Data and calculations are presented in Supplementary Materials).

3.1.1. Total Suspended Particles

The emission factors were calculated for the three types of emissions (fuel consumption, traveling on an unpaved road, loading and unloading), as suggested by the Environmental Protection Agency [104]. The values of the previous year published on local environmental agency websites for the most unfavorable environmental situations were considered as follows: number of days of rainfall, surface sludge content, material moisture content and average wind speed in the region.

The TSPs were calculated based on TSP emission rates for each soil volume handled in construction activities, according to Jung et al. [86]. The total number of suspended particles in each activity was the sum of the results of Equations (1)–(4).

For each construction activity assessed, the amount of equipment and earth moved was recorded, as well as the fuel consumption for each activity. The fuel emission factor in grams per liter was identified by Jung et al. [86].

TSP Emission Rate during Fuel Consumption

(1)${TSP}_{fuel}={EF}_{TSPfuel}\times C_{fuel}$

where TSP_fuel is total suspended particles emitted by fuel consumption in grams; EF_fuel fuel emission factor in grams per liter; and C_fuel fuel consumption in liters.

An average transportation distance was established to quantify the TSP emission rate while traveling on unpaved roads, and the amount of material transported for construction activities calculated based on budget figures.

TSP Emission Rate Traveling on Unpaved Roads

(2)${TSP}_{traveling(dumptruck;unpaved)}={EF}_{trav}\times {No.}_{Km}$

where ${TSP}_{traveling(dumptruck;unpaved)}isthe$ total suspended particles emitted by a dump truck traveling on an unpaved road in grams; EF_travel the emission factor for traveling in grams per kilometer; and No._Km the number of kilometers traveled.

(3)${TSP}_{traveling(othervehicles;unpaved)}={EF}_{travel}\times {AMT}_{material}$

where ${TSP}_{traveling(othervehicles;unpaved)}$ is the total suspended particles emitted by other vehicles traveling on an unpaved road in grams; EF_travel the emission factor for other vehicles traveling on an unpaved road in grams per kilogram; and AMT_material the amount of material in kilograms.

In terms of quantifying the TSP emission rate for loading and unloading soil, the amount of material loaded and unloaded in the activities was calculated.

TSP Emission Rate for Loading and Unloading Soil

(4)${TSP}_{loadingandunloading}={EF}_{loadingandunloading}\times {AMT}_{material}$

where TSP_{loading and unloading} is the total suspended particles emitted by loading and unloading material in grams; EF_{loading and unloading} the emission factor for loading and unloading in grams per kilometer; and AMT_material the amount of material in kilograms.

3.1.2. Greenhouse Gas Emissions

The emission factors of materials and fuel were obtained from the studies of Akan et al. [105] and Yim et al. [106], who considered the same type of fuel for the three real cases, except for the emission factor of the material (Poly Vinyl Chloride (PVC) tubing of the water supply system), which was calculated using the simplified method EPA [107]. The total GGE of the activities considered the sum of the results of Equations (5) and (6).

Equation (5) demonstrates the greenhouse gas emissions incorporated into the manufacture of construction materials used in construction activities.

(5)${GGE}_{\left(material\right)}=\sum {AMT}_{material}\times {EF}_{ggemat}$

where GGE_(material) is total greenhouse emission in KgCO₂e incorporated into the manufacture of the material; AMT_material the amount of material in kilograms or cubic meters; and EF_ggematerial the greenhouse gas emission factor in kilograms of equivalent carbon dioxide per metric cube.

For Equation (6), budget information was used (amount of material transported) to determine fuel consumption in liters at the average distance transported in Km.

(6)${GGE}_{\left(transport\right)}=\sum \left({\displaystyle \frac{{Amt}_{material}\times C_{fuel}\times {Amt}_{Km}\times {EF}_{ggetransp}}{5m^{3}or6000Kg}}\right)$

where GGE_(transport) is the total greenhouse gas emissions in KgCO₂e during transport; Amt_material the amount of material in kilograms or cubic meters; C_fuel fuel consumption in liters per kilometer; Amt_Km the number of kilometers traveled; and EF_{gge transp} the greenhouse gas emissions factor in KgCO₂e per liter.

3.1.3. Noise Pollution

NP was calculated using the equations developed by Haron et al. [108] and noise pollution data of the equipment obtained from the study conducted by Lee et al. [109]. In order to determine the distance from the source to the receiver to predict noise pollution in the real cases, Google Earth aerial images of the real cases were analyzed, simulating the shortest distance between the source and receiver.

Equation (7) was used to calculate the sound pressure level in the receiver for only one piece of equipment and Equation (8) to calculate the sound pressure level of all the equipment used simultaneously in the construction activity. A range of construction equipment was specified for each construction activity.

(7)${Lp=Lw-20log}_{10}r-8+\Delta L$

where L_p is the sound pressure level in the receiver in decibels; L_w the sound pressure level at the source in decibels; r the distance from the source to the receiver in meters; and ΔL the variation in sound pressure level.

(8)${Laequ=10log}_{10}({10}^{{\displaystyle \frac{Lp1}{10}}}{+10}^{{\displaystyle \frac{Lp2}{10}}}+\dots +{10}^{{\displaystyle \frac{Lpn}{10}}})$

where L_{a equ} is the combined sound pressure level of the equipment in decibels, and L_p the sound pressure level in the receiver in decibels.

3.1.4. Soil Alteration

The method to calculate SA was developed by Li et al. [110], Qu and Long [111], and Wu et al. [112], and a soil alteration index was created by Araújo et al. [87] and adapted to each of the six construction activities.

(9)$SA=\left({\displaystyle \frac{A_{act}}{A_p}}\right)\ast 100$

where SA is soil alteration in percentage; A_act the area of construction activity in square meters; and A_p the area of preservation in square meters.

3.1.5. Soil Pollution

In this methodology, the authors considered two construction activities: rainfall drainage system and curbing, both via the on-site manufacture of concrete elements. With respect to SOILP, the calculation used was developed by Araújo et al. [87] and adapted from Eikelboom et al. [113]. The ratio between the total amount of fluid material in construction activity and the total area of the project was used.

(10)$SOILP={\displaystyle \frac{0.01\%\ast {Amt}_{material}}{A_t}}$

where SOILP is soil pollution in mg/m²; Amt_material the amount of material in milligrams; and A_t the total area in m².

3.1.6. Water Pollution

WP was determined using Equation (11), developed by Araújo et al. [87] based on Belayutham et al. [114]. For local rainfall (LR), the authors considered the maximum rainfall of the previous year published on the local environmental agencies’ websites. Next, a scale was created, where LR ≤ 50 mm (scale 0.2); 50 < Pl ≤ 100 mm (scale 0.4); 100 < Pl ≤ 150 mm (scale 0.6); 150 < Pl ≤ 200 mm (scale 0.8) and Pl > 200 mm (scale 1).

(11)$WP=\left[\left({\displaystyle \frac{A_{act}}{A_t}}\right)\ast LR\right]\ast 100$

where WP is water pollution in percentage; A_act the area of construction activity in square meters; A_t the total area of the project in square meters; and LR local rainfall.

3.1.7. Use of Resources and Raw Materials

For RRMU, the method adopted used life cycle assessment [55,56,57,115], which was improved by Thomas et al. [116]. Earthmoving was considered null, due to the nonexistence of construction materials.

(12)$RRMU={Amt}_{material}\ast Impactcoef.$

where RRMU is resource and raw material use in total impact; Amt_material the amount of material in kilograms or cubic meters; and Impact coef. (weighted impact) the impact coefficient in weighted impact in m³ or Kg.

3.1.8. Construction and Demolition Waste

The environmental aspect CDW was calculated in metric tons according to Li et al. [27]. For this quantification, CDW was calculated by Equation (13), inserting the amount of material from the real cases, and was used in the following indices of material losses: Li et al. [27] for concrete (rainfall drainage system and curbing) and sand (paving), and Mersiowsky [117] for PVC tubing (water supply system). In earthmoving, the index adopted was 100%, given that all the material was from soil dumping.

(13)$CDW={Amt}_{material}\ast LI(\%)$

where CDW is construction and demolition waste in metric tons; Amt_material the amount of material in metric tons; and LI the loss index in percentage.

The paving material consisted of cobblestone, which is widely used in Northeastern Brazil. However, there are no loss index values in international journals. Thus, the index was calculated using Equation (14), where the authors considered the amount of cobblestone used in the project as the theoretical value and the constant amount of cobblestone in the budget as the real amount.

(14)$LI\left(\%\right)=\left[\left({\displaystyle \frac{{Amt}_{material}-{AmtT}_{material}}{{AmtT}_{material}}}\right)\right]\ast 100$

where LI is the loss index in percentage; Amt_material the amount of real material in metric tons; and AmtT_material the theoretical amount of material in metric tons.

3.1.9. Water Use

In the methodology to quantify WU, water intensities were considered in liters per m³ for the manufacture of materials and water intensity in liters per m² or m³ needed to provide the services, according to McCormack et al. [118]; Souza et al. [119]; Waidyasekara et al. [120]; and Waylen et al. [121]. Water intensity in the PVC tube of the water supply system was considered to be null, due to the manufacturing process [122].

(15)$WU=\sum I_n\times {Amt}_{materialorservice}$

where WU is water consumption or use in liters; I_n water intensity in liters per m³ or Kg for materials (water used in manufacturing), In water intensity in liters per m² for the services (water used in soil compacting services during earthmoving and paving; and Amt_{material or service the} amount of material in m³ or service in m².

3.1.10. Energy Use

Energy use (EU) was calculated for the materials and transport, according to Paulsen and Sposto [123]; Teodoro [124]; Treloar [125]; and Treloar et al. [126]. Total energy use of the activity was the sum of the results of Equations (16) and (17).

In order to calculate EE_material, the materials contained in the construction activities of three real cases were considered. Earthmoving was deemed null, since no material was manufactured.

(16)${EE}_{material}=\sum {EEF}_i\times {Amt}_{material}$

where EE_material is the embodied energy in the manufacture of material in Mj; EEF (Mj/Kg) the embodied energy factor in the material in mega joules per kilogram; and Amt_material the amount of material in Kg.

To calculate EE_transp, the centers of gravity of the total area of the real cases were adopted as the average transport distances for the construction activities and the distance transported proportional to the transport capacity of the equipment. The energy consumption of load transport in mega joules per metric ton and kilometers was obtained from the study of Teodoro [124].

(17)${EE}_{transp}=\sum {Amt}_{material}\times {Amt}_{Km}\times {EC}_{transp.}$

where EE_transp is the embodied energy expended in Mj; Amt_material the amount of material in metric tons; Amt_Km (Km) the number of kilometers traveled; and EC_transp (Mj/t.Km) the energy consumed in load transport in mega joules per metric tons and kilometer.

3.2. Inventory

The methodology established to compile the inventory started with the absolute values of the severities of the environmental aspects of the projects and were transformed into unit values by dividing the absolute values of the environmental aspects by the number of construction activities. For the environmental noise pollution aspect, whose results were obtained by a logarithmic base 10 equation, the number of activities were transformed into log base 10. Equation (18) establishes the unit values for the severity of environmental aspects.

(18)$\mathrm{S}\mathrm{e}\mathrm{a}={\displaystyle \frac{I\text{'}1}{Aa!}}$

where Sea is the severity of the environmental aspect by unit activity, I’1 the total intensity of the environmental aspect and (I’1) and Aa the total amount of the construction activity by unit of corresponding measure.

At this time, two stages were conducted: the first was a normalized comparison of the environmental aspects between projects, and the second the development of an inventory using the descriptive measures of the projects.

In the first stage, the results of three projects were compared and the values obtained in Equation (19) normalized. The total severity of the environmental aspect was divided by the total maximum severity of the aspect for all the projects, and finally the results were normalized between 0 and 1. This allows comparison of each of the environmental aspects between projects. S ea norm is the severity of the normalized environmental aspect in unit values, according to Equation (20).

The unit values of the severities of the environmental aspects of the six construction activities were added. Thus, the total unit result was obtained for each environmental aspect, according to Equation (19).

(19)$TotalSea=\sum _{n=1}^{6}Sea$

where total S aa is the total severity of the environmental aspect in unit values, obtained by the sum of severity values of each of the six activities analyzed.

(20)$Seanorm={\displaystyle \frac{Seatotal}{Seatotalmax}}$

where S ea norm is the severity of the normalized environmental aspect in unit values; S ea total the total severity of the environmental aspect for each project; S ea total max the total maximum severity of the environmental aspect, comparing the results of the three projects.

The second stage was to develop the inventory of the environmental aspects based on descriptive statistical measures, such as the mean, standard deviation and coefficient of variation. The statistical mean provided the central tendency, the standard deviation described the dispersion and helped understand the individual values, and the coefficient of variation made it possible to compare the variables of the measures in different units of environmental aspects [127]. The coefficient of variation was analyzed in order to accept the mean as an indicator. Variations between 0 and 33.33% were considered “extremely acceptable”, 33.33 and 50.00% “acceptable”, 50.00 and 100.00% “somewhat acceptable” and above 100.00% “unacceptable”.

In the future, the development of a tool using the calculation memory of this methodology will enable automatic calculations of the environmental performance of projects with interoperability between schedule and budget information. Information, queries, and diagnostics will be easily accessible, assisting engineers, researchers, and the entire construction sector community in making decisions for construction projects with a focus on the environmental dimension.

3.3. Identification of Causes

The ten environmental aspects externalized by the six urban infrastructure activities were studied based on the absolute values of the first stage of the methodology (quantification), the variations in unit comparison of their results analyzed and investigated using the descriptive statistics measures of the second stage (inventory) and the causes of the environmental aspects selected and confirmed. Applying the Ishikawa diagram helped obtain the causal relations of the four categories established in an organized, systematized and objective manner.

4. Real Cases

The three real urban development cases were applied in the method. All were assessed based on the same criteria, in terms of the projects, budgets and environmental characteristics of the regions. Table 1 presents the characterization of the projects assessed.

5. Results

5.1. Quantification

Factors such as the amount of material and/or services directly influenced five environmental aspects: GGE, SOILP, CDW, WU and EU. Since the emission factors incorporated into the materials and/or process directly induced GGE, TSP and EU, the type of material influenced environmental aspect quantification. The input data related to project design, such as construction area, preservation area and total area, affected the results of SA, SOILP and WP. The water intensity and embodied energy variables incorporated into the materials influenced the WU and EU values.

Table 2 presents the results of the validation of environmental aspect quantification of construction activities in the three projects analyzed with the ten environmental aspects in six construction activities.

5.2. Inventory Result

The results were calculated in unit scales to compare the environmental aspects of the three case studies selected to validate the methodology. Comparison of the three projects and their different results showed that the TSP of project B was lower than that found in projects A and C. The CDW of project A was higher than that obtained in projects B and C. The WP, SOILP and SA of project B was higher than that observed in the other two. The results show seven maximum environmental aspects for project B (TSP; EU; WU; CDW; RRMU; GGE; NP); six for project A (EU; WU; CDW; RRMU; GGE; NP) and six for project C (WU; EU; TSP; GGE; NP; RRMU) demonstrating the flexibility of the methodology for similar projects (Figure 2).

The descriptive measures of the inventory for TSP exhibited in the rainfall drainage, water supply and electric energy systems were extremely acceptable, with coefficients of variation of 23.11, 1.02 and 11.51%, respectively. Earthmoving obtained a coefficient of variation of 33.46%, which is in the acceptable range. Paving and curbing exhibited a coefficient of variation of 70.90 and 71.86% (somewhat acceptable). The coefficients of variation for GGE were extremely acceptable, with earthmoving obtaining the highest value (8.57%), and water supply the lowest (0%).

All the dispersion measures of NP for the six activities were extremely acceptable. For SA, earthmoving was unacceptable, with 158.13%, and the other activities were between 91.92 and 93.03% (somewhat acceptable). The SOILP results were calculated for two activities: rainfall drainage system and curbing, with 39.75% in both. The averages for formulating the RRMU and EU inventory were extremely acceptable, given the coefficient of variation between 0 and 13.53%. CDW and WU were somewhat acceptable and acceptable in earthmoving, with 78.70 and 106.17%, respectively, and extremely acceptable in the other construction activities. WP was unacceptable for earthmoving (147.23%) and somewhat acceptable in the other five activities, with results between 72.54 and 72.66% (Table 3).

5.3. Identifying the Causes of the Environmental Aspects

The information obtained in the quantifications (Table 2) and the results of the inventory (Table 3) was used to construct the Ishikawa diagram (Figure 3).

The first category of machines included the results of five causes: productivity, hours in use, fuel consumption, equipment weight and the sound pressure level. The findings provided insights for focusing efforts on construction site planning and the adoption of strategies for maintaining and renewing the construction equipment fleet, thereby improving productivity, and consequently reducing labor hours, fuel consumption, and noise pollution.

In the second category, related to materials, nine causes were identified: amount of material, TSP emission factor for the type of fuel, emission factor incorporated into the material, GGE emission factor for the type of fuel, impact factor of the material, manufacturing/construction process, water intensity to manufacture the material/process, and embodied energy in transport and manufacturing. The findings regarding the causes of material impacts can be minimized through the rational consumption of construction materials, a shift in the energy matrix (replacing fossil fuels), and modification to the construction material production process (particularly cement).

In the methods, only six causes were found: index of material losses, amount of suppressed area, selection of production type (in loco or pre-molded), project design (area distribution), distances from source to receiver, and number of kilometers traveled. The recognition of the causes related to construction methods stemmed directly from the project design combined with the planning of activity execution. It was observed that there was a lack of compatibility between these two factors in the sustainability of the projects.

The results of the last category, defined as environmental factors, revealed seven causes: number of days of rainfall, surface sludge content, average wind speed, material moisture content, soil permeability, groundwater level and atmosphere (temperature, relative humidity, air pressure). The findings related to the causes of environmental factors were integrated with fragility represented by the sensitivity of the natural environment at construction sites during infrastructure interventions. For example, an area with a dry climate and low precipitation (rain) could intensify the environmental aspect of “total suspended particles” during the execution of the works.

The decision to develop the model of the cause and effect of environmental aspects in infrastructures, from the pre-construction phase to the final stage, aimed to objectively represent the main elements responsible for these environmental aspects. The authors Perdicoúlis and Piper [25] reaffirmed the importance of identifying causal relationships to obtain accurate information, while Fuertes et al. [92] developed a causal model to achieve better levels of environmental performance.

Min et al. [128] emphasized that the proposals can enhance the understanding of construction projects through a structured analysis of how conflicts occur and what causes them. Guerin [17] acknowledged that root cause analysis information can be used predictively, as understanding vulnerabilities can help eliminate the negative outcomes of environmental impacts from construction, contributing to the improvement of construction project performance in the environmental dimension.

6. Discussion

The use of this methodology elsewhere resulted in different characteristics, which shall be presented in the results. The monitoring and measurement of environmental aspects throughout the construction phase and projects for comparison with the results obtained in the pre-construction phase may lead to new discoveries in these plans. As reported in ISO 15392 [129], the challenges of sustainable development are global, and strategies to address sustainability in construction should be expanded in context and content from region to region.

The proposed methodology constitutes a first approach to quantifying the environmental aspects of infrastructure projects. It is important to emphasize that the implementation of this methodology throughout the construction lifecycle (pre-construction; construction; use/maintenance; demolition) shall promote a comprehensive analysis of environmental impacts. Furthermore, applying the methodology to other types of infrastructure projects has the potential to broaden the investigation of the causes of environmental impacts and provide new information. According to Fernández-Sanchez and Rodrigues-Lopes [12], infrastructure projects have not been practically evaluated by any tools or methodologies regarding their sustainability, and there is an urgent need to incorporate sustainable development into both urban planning and construction projects.

The causal model of the environmental aspects of infrastructures in the pre-construction phase aimed at objectively representing the main elements causing environmental aspects. A systematic review showed the ten primary environmental aspects: total suspended particles (TSPs), greenhouse gas emissions (GGE), noise pollution (NP), soil alteration (SA), soil pollution (SOILP), water pollution (WP), resource and raw material use (RRMU), construction and demolition waste (CDW), water use (WU) and energy use (EU) [68]. The causes of environmental pollution, the sharp increase in resource consumption and other problems stemmed from the rapid advancement of the construction industry. These statements corroborated Homaei and Hamdy [130], which found an increase in the frequency and severity of extreme events due to climate change.

The tool enabled the creation of the first database of three projects, corroborating Kim et al. [131], who developed a database of building site accidents and applied analysis of variance and cross tabulation to identify the causes. Dos Santos, Carvalho and Brandstetter [132] stated the importance of developing integration tools with collaborative efforts during the design phase, which should be incorporated into BIM (Building Information Modeling). According to Elhag [103], it was effective and efficient management methodologies that improved construction performance in terms of economic, social and environmental sustainability.

The first environmental aspect—TSP—confirmed that earthmoving was induced by environmental conditions, such as number of days of rainfall, wind speed, amount of surface sludge on unpaved roads, under the conditions of project conception and average transport distances. Fedorova et al. [133] reported the influence of information on rainfall intensity, wind pressure rate and drop size in atmospheric pollution. Hong et al. [100] underscored that the main cause of TSP emissions at building sites occurs is earthmoving using heavy equipment (excavators, earth augers, dump trucks cranes, etc.), and that wind, atmosphere and dust were the variables indicated to measure this environmental aspect. Jung et al. [86] demonstrated that dust concentration at building sites changed according to wind frequency and direction and terrain obstacles. Thus, wind speed influenced the quantification of TSP emission factors in the three real cases. As such, the rationality, planning and sizing of machine operating processes are measures needed both environmentally and economically. For Voordeckers et al. [134], air pollution in the urban canopy layer represented a high risk to the human population.

In the case of GGE, the causal factors that strengthened the results were type of fuel and the material manufacturing process, which prompted the adoption of significant KgCO₂e emission factors, in addition to project design conditions, which included factors such as distance traveled and amount of material. This corroborates Zhang et al. [135], who considered the construction industry as one of the greatest producers of carbon emissions. Kennedy et al. [9] described the serious global consequences of the increased atmospheric concentrations of anthropogenic greenhouse gases caused by fossil fuel consumption and cement manufacture. This was corroborated by Saif et al. [136], who stated the importance of infrastructure project management in reducing the carbon footprint throughout the project’s execution. According to Lim, Tae and Roh [137] several policies were implemented to promote sustainable construction aimed at reducing greenhouse gas emissions from the construction sector. However, Shan et al. [138] considered financing for innovations in green technologies and renewable energy sources necessary to directly reduce carbon emissions in the natural environment.

NP was influenced by the amount and level of sound pressure emitted by the equipment, as well as the local geographic conditions of the projects, defined by the distance from the source (equipment) to the receiver (neighbor) with the absence of physical barriers. This was confirmed by Attal et al. [101], who demonstrated the benefits of green barriers (vegetation) in minimizing environmental noise. Earthmoving in projects A, B and C caused the most pollution, with 70.86, 67.74 and 76.76 dB, respectively. The values exceeded the 50 dB limit established by the Brazilian Association of Technical Guidelines [139], via Brazilian Regulation no. 10.151/2000, indicated for urban residential areas during the daytime. Hong et al. [100] described the construction plan and climate variables as the factors that affected noise emissions at building sites.

The project designs influenced the results of SA, where the ratio between the construction and preservation areas determined the soil alteration of all six construction activities, demonstrating that earthmoving caused significant soil alteration, with 74.80, 213.45 and 26.76% in projects A, B and C, respectively. According to Lehmann [20], the process of designing urban projects was often based on intuitions, assumptions and personal preferences. Despite the absence of studies that quantified soil alteration, few researchers have conceptually addressed the importance of the issue. Honeck et al. [140] and Pereira et al. [141] reported that urbanization has serious consequences for biodiversity and ecosystems, and Jost et al. [142] affirmed that improper soil use has had irreversible repercussions. Pauleit et al. [23] considered that an increase in constructed surfaces replaced green spaces, and Domingo et al. [143] reported that impermeabilization is a new challenge for sustainable urban development. However, Halonen et al. [144] confirmed in their research that cities could be healthier through better urban planning and design. Nevertheless, according to Olazabal and Gopegui [145], the evaluation of the adaptation planning of current urban projects revealed concerning results.

As for SOILP, construction activities that involved handling construction materials at the building site were more likely to contaminate the soil. Thus, factors such as the amount of material handled in milligrams and total area of the project were the main causal factors. This corroborates Cao et a. [14], who described environmental incidents involving toxic substances that entered into contact with the air, water and soil via pollutant discharge, environmental disasters, production accidents and other problems. According to Guerin [16,21], soil contamination may contain metals, in addition to organic contaminants, demonstrating that landslides occur predominantly in the earthmoving area of the building site.

The three causal factors of WP identified were local rainfall, the methods used in the construction plan such as total vegetation suppression influenced by the construction area, and total project area. Guerin [16] found that contaminants that seeped into the soil posed a safety risk and contributed to groundwater pollution. Kennedy et al. [9] observed that urban vegetation absorbs pollution, improves quality of life and mitigates the effects of climate in cities during storms and heat waves, which have important impacts on the environment.

Given that the RRMU was calculated using life cycle assessment, the causal factors were related to the type of material employed, thereby influencing the coefficient of environmental impact stipulated by the life cycle inventory of the material and the amount used in the project. Muthukannan et al. [146] described the environmental pollution caused between raw material extraction and packaging. Feese et al. [147] studied the life cycle at building sites and found that the construction phase consumed the most energy and emitted the most CO₂, associated primarily with the transport of concrete. According to Chan, Masrom and Yasin [102], the construction sector was the largest global consumer of materials contributing significantly to climate changes. However, Fulton et al. [148] found that carbon compensation can be achieved, thereby reducing the environmental impact of construction. Capelleveen et al. [149], stated that one effective way to accelerate sustainable development was by reducing the use of primary resources.

A number of studies related the causes of waste generation with inadequately designed projects [150,151,152,153,154,155,156], and construction methods [157]. This study found that earthmoving caused the largest amount of soil dumping as construction waste, thereby providing opportunities to reduce CDW through project rationalization.

WU showed that the causal factors were the water intensities used in the production of construction elements and volume of water in earthmoving and paving for soil compaction and the sand bed, respectively. Bardhan [158] reported that construction materials were large water consumers in manufacturing processes, via extraction and processing. Waidyasekara et al. [120] and Roșca et al. [159] observed that rational water use at building sites was hindered by the low cost of the resource.

Regarding EU, the causal factors embodied energy in the production of materials and energy consumed in the transport of loads, depending on the type of material and fuel, respectively. Also considered were the project design conditions in the planning phase, material selection, construction logistics related to receiving and applying materials in the construction activities established. Vanek [160] found that transport energy consumption had a lower impact than that of product manufacturing, corroborating the findings of Galadanci, Ianakiev and Kromanis [161], who had already pointed out the need for low energy consumption to increase the energy efficiency of buildings.

The inventory enabled the creation of the first database based on three infrastructure projects. This corroborates the findings of Kim et al. [131], who developed a database of accidents in highway construction projects and applied variance analysis and cross-tabulation to identify the causes. Nahuelhual et al. [162] identified land cover changes using satellite imaging systems which were applied in a linear regression model to estimate landscape changes.

The inventory confirmed the flexibility of the methodology applied in three different projects, where some environmental aspects were directly and indirectly influenced by environmental factors, obtaining high standard deviations and coefficients of dispersion. According to Ke, Zhagh and Philbin [163], there was an urgent need to understand the dynamics in construction project management to adopt innovative strategies and approaches to the challenges of the construction sector, ensuring successful project delivery. However, other environmental aspects that were not affected by the environmental factors of projects recorded lower dispersion. It was confirmed that they cannot be assessed linearly, thereby strengthening the concept of specific characteristics of the industry in developing their products: unicity, singularity, temporality and several external factors. Rumane [164] cited problems such as non-routine, non-repetitive personalized activities and different locations for construction activities. Woodward [165] found that construction management, in projects or execution, is significantly different from that of most industries.

The cause-and-effect diagram demonstrated an association between machines, methods, materials and environmental factors in quantifying the ten environmental aspects. This study shows the causes of environmental aspects in machines, where the real productivity, weight and number of hours in use influenced fuel consumption. The methods revealed that project design had an impact on the number of kilometers traveled and the distance from source to receiver. The construction method affected material losses for the ten aspects. Although Kolaventi et al. [18] also used an Ishikawa diagram, they applied it only to the waste produced in the civil construction industry in India. The present study broadened the use of the Ishikawa diagram to several environmental aspects produced at building sites aimed at contributing to the sustainable development of the construction industry. According to Huang et al. [166], ecological and sustainable development is a trend in the construction and infrastructure sectors.

The materials selected had important consequences in quantifying environmental aspects, due to the production mechanisms that interfered in the fuel emission factors, emission factors incorporated into the materials, impact factors, water use intensity in production, energy consumption embodied in manufacturing, construction and the amount of material. Beckford [24] considered materials as one of the main categories in the Ishikawa diagram, and Yahya and Halim Boussabaine [167] observed significant raw material consumption in the construction industry. For Markou, Sinnott and Thoma [168], the implementation of technologies such as the Internet of Things (IoT), blockchain, artificial intelligence and big data analysis provided practical solutions to optimize supply chain processes, promoting more sustainable practices.

In terms of the environmental factors, number of rainfall days, surface sludge content, average wind speed, material moisture content, soil permeability, groundwater level and atmosphere (temperature, humidity and air pressure) caused the variations in total suspended particles, soil and water pollution, corroborating Fuertes et al. [92], who described the correlation between work site and environmental impacts.

7. Conclusions

A methodology to quantify and identify the causes of the environmental aspects of urban infrastructure projects during the pre-construction phase was presented. The method calculated and identified the causes of ten environmental aspects and six construction activities, providing a quantitative and qualitative forecast of environmental aspects, in addition to applying the method in three urban infrastructure projects objectively, without depending on the judgment of stakeholders. The main advantage of the methodology was the creation of a systematic structure to quantify and identify the causes and develop an inventory of the environmental aspects with the use of objective information to measure the performance of urban infrastructure projects.

The real cases were analyzed, and an environmental impact inventory was created of six urban infrastructure activities (earthmoving, draining, water supply system, electric energy system, paving and curbing) in order to quantify ten environmental aspects. Earthmoving obtained the maximum score in five environmental aspects—TPS, NP, SA, WP and CDW—and was classified as the activity with the greatest potential for environmental degradation. The electric energy system obtained the minimum score in seven environmental aspects: TSP, SA, SOILP, WP, RRMU, CDW and EU, representing the activity with the lowest environmental impact.

The present study reveals the importance of understanding environmental aspects in terms of their quantitative and qualitative dimensions. This method offers the possibility for future advances in database development with easy-to-access internet information and rapid and accurate environmental assessments, thereby providing relevant information to the scientific, political and business community.

Author Contributions

Conceptualization, A.G.d.A. and R.P.P.; methodology, A.G.d.A. and R.P.P.; validation, A.G.d.A., A.D.G., A.M.P.C. and R.P.P.; formal analysis, A.G.d.A.; investigation, A.G.d.A.; resources, A.G.d.A.; data curation, A.G.d.A.; writing—original draft preparation, A.G.d.A.; writing—review and editing, A.G.d.A.; supervision, A.G.d.A., A.D.G., R.P.P. and A.M.P.C. All authors have read and agreed to the published version of the manuscript.

Data Availability Statement

The original contributions presented in the study are included in the article and Supplementary Materials, further inquiries can be directed to the corresponding author.

Acknowledgments

This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior–Brazil (CAPES)—Finance Code 001. This study was also funded in part by the Polytechnic School of the University of Pernambuco. The authors would also like to thank the anonymous reviewers for all the valuable suggestions that enhanced the contribution of this paper.

Conflicts of Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work.

Footnotes

Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Figures and Tables

Figure 1 Methodological summary. Source: The authors.

Figure 2 Unit environmental aspects. Source: The authors.

Figure 3 Cause and effect diagram of the environmental aspects. Source: The authors.

Table 1

Project characterization—real cases.

Project Description	Project A		Project B	Project C
City/State	Santana do	Ipanema/AL	Arapiraca/AL	Estância/SE
Number of lots	847 units		614 units	771 units.
Total area	300,000.00 m2		190,000.00 m2	415,732.00 m2
Area of the lots	174,236.64 m2		119,512.93 m2	163,733.15 m2
Green area	71,945.34 m2		24,794.46 m2	198,797.58 m2
Area of the highway system	53,818.02 m2		45,692.61 m2	53,201.27 m2
Earthmoving (E)	191,461.24 m3		20,340.32 m3	104,399.08 m3
Rainfall drainage systems (RDS)	6698.00 m		967.61 m	1575.53 m
Water supply system (WSS)	6698.00 m		5378.00 m	4976.00 m
Electric energy system (EES)	222 units		155 units	130 units
Paving (P)	53,243.18 m2		31,878.00 m2	39,138.85 m2
Curbing (C).	13,590.00 m		9278.00 m	11,393.96 m

Note: Values adopted: natural soil density: 1800 Kg/m³; concrete density: 2400 Kg/m³; cobblestone density: 3086.42 kg/m³; PVC density: 1380.00 Kg/m³. Activities: materials and unit volume: (E): natural soil and 1 m³/m³; (RDS): concrete shackles and 0.134 m³/m; (WSS): PVC tubing and 1.40596 Kg/m; (EES): concrete post and 1519.98 Kg/unit; (P): sand and cobblestone and 0.04 m³/m² and 384 Kg/m², respectively; (C): curb (concrete) and 0.0639 m³/m. Source: Developed by the authors based on the projects provided by the company.

Table 2

Quantification of environmental aspects.

Description of Activities	Total Suspended Particles (TSPs)—Dust			Greenhouse Gas Emissions (GGE)			Noise Pollution (NP)
	(g)			(KgCO2e)			(dB)
	Project A	Project B	Project C	Project A	Project B	Project C	Project A	Project B	Project C
A-E	3092,263.15	161,764.65	1,458,627.49	279,157.83	26,346.32	129,269.90	70.86	67.74	76.76
A-RDS	53,846.90	5612.17	14,697.19	384,395.35	55,742.66	90,294.97	61.46	58.40	67.51
A-WSS	5083.54	4041.33	3816.60	17,477.43	14,033.09	12,984.13	61.46	58.40	67.51
A-EES	1587.34	955.46	1009.94	59,801.02	41,740.63	35,005.80	61.83	58.79	67.55
A-P	262,144.07	19,846.06	184,115.51	143,261.11	83,192.48	101,176.61	54.06	51.06	60.11
A-C	23,640.40	1913.93	19,123.43	372,501.98	254,042.21	311,879.34	51.05	48.05	57.10
Description of Activities	Soil Alteration (SA)			Soil Pollution (SOILP)			Water Pollution (WP)
	(%)			(mg/m2)			(%)
	Project A	Project B	Project C	Project A	Project B	Project C	Project A	Project B	Project C
A-E	74.80	213.45	26.76	0.00	0.00	0.00	3.59	16.71	7.68
A-RDS	8.94	3.75	0.76	718.03	163.78	121.88	0.625	0.428	0.318
A-WSS	3.72	8.68	1.00	0.00	0.00	0.00	0.179	0.679	0.287
A-EES	0.13	0.27	0.03	0.00	0.00	0.00	0.00	0.00	0.00
A-P	74.00	128.57	19.69	0.00	0.00	0.00	3.55	10.07	5.65
A-C	5.67	11.22	1.72	695.81	750.05	420.97	0.272	0.879	0.493
Description of Activities	Resource—Raw Material Use (RRMU)				Waste (CDW)
	(total impact)				(t)
	Project A	Project B	Project C		Project A	Project B		Project C
A-E	0.00	0.00	0.00		69,677.15	3145.89		6831.65
A-RDS	7.147 × 10−9	1.03248 × 10−9	1.6811 × 10−9		30.96	4.47		7.28
A-WSS	5.345 × 10−10	4.27926 × 10−10	3.9594 × 10−10		0.18	0.15		0.14
A-EES	4.759 × 10−10	3.32309 × 10−10	2.7871 × 10−10		0.00	0.00		0.00
A-P	5.491 × 10−7	3.28726 × 10−7	4.036 × 10−7		816.28	488.72		600.05
A-C	6.926 × 10−9	4.72834 × 10−9	5.8067 × 10−9		30.01	20.49		25.16
Description of Activities	Water Use (WU)				Energy Use (EU)
	(L)				(Mj)
	Project A	Project B	Project C		Project A	Project B		Project C
A-E	161,454.06	137,077.92	159,603.81		3241,499.60	326,737.67		1607,567.88
A-RDS	112,191.25	16,207.50	26,390.00		3327,247.19	479,974.74		815,138.25
A-WSS	0.00	0.00	0.00		661,203.93	530,671.75		491,192.65
A-EES	17,575.00	12,270.83	10,291.67		543,881.90	379,190.02		317,890.53
A-P	632,684.42	374,757.77	460,116.31		687,586.83	484,889.38		456,888.81
A-C	108,720.00	74,223.75	91,151.25		3224,118.26	2198,078.92		2815,493.39

Source: The authors.

Table 3

Environmental aspects inventory.

Description of Activities		Total Suspended Particles (TSPs)			Greenhouse Gas Emissions (GGE)			Noise Pollution (NP)			Soil Alteration (SA)			Soil Pollution (SOILP)
	Unit	(g)			(KgCO2e)			(dB)			(%)			(mg/m²)
		MEAN	SD	C. V.	MEAN	SD	C. V.	MEAN	SD	C. V.	MEAN	SD	C. V.	MEAN	SD	C. V.
A-E	m³	1.27 × 101	4.25	33.46	1.33 × 100	0.11	8.57	1.48 × 101	1.23	8.29	3.71 × 10−3	0.01	158.13	0.00	0.00	*
A-RDS	m	7.72 × 100	1.79	23.12	5.74 × 101	0.15	0.27	1.89 × 101	2.59	13.68	1.90 × 10−3	0.00	93.03	1.18 × 10−1	0.05	39.75
A-WSS	m	7.59 × 10−1	0.01	1.02	2.61 × 100	0.00	0.00	1.67 × 101	1.40	8.42	7.90 × 10−4	0.00	93.01	0.00	0.00	*
A-EES	unit	7.03 × 100	0.81	11.51	2.69 × 102	0.05	0.02	2.84 × 101	3.10	10.93	8.57 × 10−4	0.00	91.92	0.00	0.00	*
A-P	m²	3.42 × 100	2.42	70.90	2.63 × 100	0.06	2.10	1.20 × 101	0.98	8.22	1.98 × 10−3	0.00	92.97	0.00	0.00	*
A-C	m	1.21× 100	0.87	71.86	2.74 × 101	0.02	0.07	1.28 × 101	1.07	8.34	5.92 × 10−4	0.00	92.92	5.63 × 10−2	0.02	39.75
Description of Activities		Water Pollution (WP)			Resource—Raw Material Use (RRMU)			Waste (CDW)			Water Use (WU)			Energy Use (EU)
	Unit	(%)			(total impact)			(t)			(L)			(Mj)
		MEAN	SD	C. V.	MEAN	SD	C. V.	MEAN	SD	C. V.	MEAN	SD	C. V.	MEAN	SD	C. V.
A-E	m³	3.05 × 10−4	0.00	147.23	0.00	0.00	*	1.95 × 10−1	0.15	78.70	3.04 × 100	3.22	106.17	1.61 × 101	0.77	4.76
A-RDS	m	2.46 × 10−4	0.00	72.66	1.07 × 10−12	0.00	0.00	4.62 × 10−3	0.00	0.03	1.67 × 101	0.00	0.00	5.03 × 102	12.12	2.41
A-WSS	m	7.02 × 10−5	0.00	72.54	7.96 × 10−14	0.00	0.00	2.76 × 10−5	0.00	2.42	0.00	0.00	*	9.87 × 101	0.02	0.02
A-EES	unit	0.00	0.00	*	2.14 × 10−12	0.00	0.00	0.00	0.00	*	7.92 × 101	0.00	0.00	2.45 × 103	2.41	0.10
A-P	m²	1.76 × 10−4	0.00	72.60	1.03 × 10−11	0.00	0.00	1.53 × 10−2	0.00	0.00	1.18 × 101	0.07	0.62	1.33 × 101	1.79	13.53
A-C	m	5.27 × 10−5	0.00	72.60	5.10 × 10−13	0.00	0.00	2.21 × 10−3	0.00	0.01	8.00 × 100	0.00	0.00	2.40 × 102	5.79	2.41

Note: * C.V.: coefficient of variation not determined due to the presence of a null mean, given the absence of environmental aspects in the respective project activity; SD: standard deviation. Source: The authors.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/buildings15081328/s1.

References

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