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Analysis of the ecological footprint produced by machinery in
construction
Authors:
Freire Guerrero, Antonio (A)1
Marrero Meléndez, Madelyn (M)2
1
Univesity of Sevilla, Sevilla, Spain
2
Univesity of Sevilla, Sevilla, Spain
Abstract: The ecological footprint caused by construction machinery is analyzed in detail.
The following impacts are taken into account: fuel and electricity consumption; maintenance
and repairs; and finally the footprint of the machinery operator due to mobility, food intake,
and urban waste generation on the construction site.
All this analysis is based on the Andalusia Construction Costs Database, thus adding an
environmental indicator to this baseline by allowing the ecological footprint caused by the
use of various machines to be taken into account as part of the project budget.
KEY WORDS: Ecological footprint, machinery, construction cost database, budget
Introduction
Wackernagel and Rees created an indicator that evaluates the environmental footprint of
continents, countries, and regions, by defining the ecological footprint (EF) as "the area of
ecologically productive land (crops, pastures, forests and aquatic ecosystems) required to
produce the resources consumed and to assimilate the wastes produced by a given population
with a specific life level and indefinitely " [1].
The studies of Solis et al. [2] analyses the EF of building construction for the first time and
calculates the footprint generated by different impact sources: energy, water supply, food
consumption,
mobility,
building
materials,
waste,
and
built
land.
In the present work, the previously cited study is improved with a deeper and more detailed
analysis of the EF caused by construction machinery on site, during the earthworks,
foundations and structure construction, installations, and implementation by means of a
construction work classification system: the Andalusia Construction Costs Database (ACCD)
[3].
Andalusia Construction Costs Database
The ACCD is formed in a hierarchical structure. The levels that form the structure are no
more important than the relationships that connect them, since it is through these types of
bonds that it is possible to cross the structure in any direction, including ascending and
descending, without committing errors or losing intermediate information generated in the
processes. ACICS establishes a correspondence between each elemental code and the work
unit that it represents [4]. The work unit refers to a group of resources (material, labour,
and/or machinery) necessary to build an indivisible part of a building and also represents the
smallest component of the construction budget. Each work unit has a unique classification
code. ACICS divides all possible work units into large groups of elements with common
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characteristics. The highest level is the completely constructed building. The next divisions
are called chapters each of which represents a construction process: Demolition, Earthworks,
Foundation, Sanitation, Structure, Partition, Roof, Installation, Insulation, Finish, Carpentry,
Glass and Polyester, Coating, Decoration, Urbanization, Safety, and Waste Management.
Within this structure, the representation process needs a detailed description of each work
unit that refers to a set of resources (material, machinery or manual labor) necessary to
construct an indivisible unit which is then incorporated into the construction site. This
constitutes the smallest part in the classification and includes the following elements: a
measurement unit, its frequently-used name, the elements that integrate this work unit, the
corresponding construction methods, their reference norms and/or regulations, and
measurement criteria.
Each cost is identified by an alphanumeric code. The unit of measurement used in each
price criteria is established by the Association of Construction Database Writers [3, 5]. The
present analysis focuses on the basic costs of the machinery, the family code starts with the
letter M, Machinery and has the following subfamilies depending on the machine type: Aagglomerator, B-pumps, C-compressors, E-excavators and shovels, etc.; for example,
ME00400 is the code corresponding to an excavator with an engine of 67 kW. A total of 52
different items of construction machinery (45 fuel and 7 electric) have been analyzed in the
Andalusia Construction Costs Database and their corresponding EF, whose procedure is
described in the following sections is determined.
Machinery EF
From among the elements that produce an EF, two main sources can be identified: the
direct energy consumption by the machinery usage on the construction site (by its electric or
combustion engines) and the footprint generated by the employees who operate them.
The footprint caused by the machinery usage, which corresponds to the fuel or electricity
consumption linked to each machine depending on the engine power [6], is illustrated in the
flowchart shown in Figure 1, whereby the machinery working hours are transformed into an
ecological footprint.
The fuel consumption per hour can be summarized as follows [6]:
•
Oil: 0.15 to 0.20 litres consumed in 1 hour per kW installed.
•
Gasoline: from 0.30 to 0.40 litres consumed in 1 hour per kW installed.
The fuel consumption by the machinery in the ACCD can be established by differentiating
between whether the engine consumes diesel or gasoline, and by the corresponding power.
After obtaining the litres of fuel consumed per hour, the energy intensity of the fuel (MJ/l)
is assigned, which represents the energy produced per litre of fuel. The corresponding energy
productivity is then applied, which indicates the amount of land needed to produce 1 MJ of
energy, which in this case represents the hectares of forests necessary to absorb the emissions
of the fuel consumed:
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EFf =
∗
(1)
where: EFf is the footprint of (fossil) fuel consumption (ha); C is the fuel consumption
(litres); EI is the energy intensity (MJ/l); and P is the energy productivity of oil (MJ/ha).
Figure 1- Flowchart for calculating the ecological footprint produced by energy consumption of machinery
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For the electricity consumption, a similar calculation is performed: all the working hours of
the electrical equipment on the construction site, and its corresponding engine power
determine the total kWh consumed.
The primary energy consumption can be determined from the efficiency of the power
production in Spain, which is 33% [7]. In this case, a specific productivity is established
depending on the energy source (coal, oil, natural gas, or nuclear power) according to data
provided by the Ministry of Industry [7]. All these steps are shown in the following equation:
EFf =
(2)
∑ ∗%
where: EFf is the ecological footprint of electricity consumption (ha); C is the consumption
(GJ); Pi is the energy productivity of the energy source “i” (GJ/ha); and % i is the percentage
of the source “i” in the energy mix.
The second analysis is the footprint left by the machine operators: food consumption,
waste generation, and mobility, as shown in Figure 2. The workers´ food is attributed to the
EF of the building construction since this activity takes place on the worksite, in the same
way as in the methodology developed by Domenech Quesada [8], where business meals are
allocated to the Corporate Ecological Footprint. To this end, the total number of manpower
hours worked for the entire construction project must first be calculated and this is obtained
from the project quantities. The footprint is calculated using Equation 3.
EFwfd =
(3)
where: EFwfd is the weighted ecological footprint of food (gha/year); EFm is the ecological
footprint expressed as gha/year/meal; hm is an 8 hours/meal. One meal per working day is
assumed; Nh is total number of hours worked.
Therefore, it is necessary to obtain the EFm of the various types of food that make up the
daily meal of every worker. The food generates four types of consumed land: pasture,
cropland, productive sea, and absorption forest. The absorption forest footprint or energy
footprint is generated by all types of food, due to their required processing and the energy
consumed therein. The EFm values per food type for a typical menu are calculated by SolisGuzman et al [9] by using natural productivity and the forest absorption of CO2 [8]. These are
summarized in Table 1. These values are used in the present analysis.
Productive land category EF/meal (gha/meal)
Cropland
0.0085
Pastures
0.0234
Productive sea
0.0159
Forest Absorption of CO2
0.0072
Table 1 - EF of workers’ meals: pasture, cropland, productive sea, and forest absorption
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Figure 2 - Flowchart for calculating the ecological footprint produced by the operator of the machinery
In order to analyze the worker mobility, the following hypotheses are established: the
construction site is located 30 km away from where the workers reside; every 4 workers share
a vehicle to go to work every day; and the working day lasts 8 hours. The fuel consumption of
the vehicles according to the distance determines the litres consumed, as in Equation 1, and
the EF is then determined [9].
The determination of the EF of the municipal solid waste (MSW) is based on statistical
data and on the energy intensity of the materials [9], now simplified and summarized in Table
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2. The coefficients (CRx) are defined as organic, paper, plastic, and glass waste, and the tons
(Gx) generated per worker.
Organic Paper Plastic Glass
CRx(gha/year/t)
0.3066 1.1450 0.5551 0.2961
Gx(t/worker/year) 0.227
0.108 0.057 0.036
Table 2- Weighted conversion rates for municipal solid waste
The total generation, Gi, of MSW in tons of each waste stream “i” is obtained by
multiplying the aforementioned statistical data, Gx, by the number of workers on the
construction site. Finally, the following expression is used for the determination of the total
footprint of the waste:
(4)
EFwws = ∑ CRxi ∙ Gi
where: EFwws is the weighted EF of the waste (gha/year); CRxi is the weighted conversion rate
(gha/year/t); and Gi is the waste generation (t).
Results
Figures 3 and 4 represent the results of the calculations of the ecological footprint of
various combustion and electric engine machinery, respectively.
Figure 3.- EF of fuel machinery
Figure 4. - EF of electrical machinery
Conclusions
The introduction of this procedure into the ACCD integrates, into a single computing
element, the two different processes of accounting in the forms of the economic and
environmental construction project budgets, thus enabling the agents involved in the building
process to make decisions both on an economic basis, principal argument for the use of the
construction data bases, and on an environmental basis. Thus, the present work presents a
procedure to calculate the footprint produced by the machinery on the construction site and to
include this footprint in the budget. This is performed with a flexible approach, oriented
towards future changes in the hypothesis, data sources used, or in the criteria and
specifications of the selected machines.
In future work, a similar analysis will be performed with the construction materials in the
ACCD, and the whole budget analysis will be completed.
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Acknowledgement
Fundación Mapfre. Ayudas a la Investigación Ignacio H. Ilarramendi. “Estudio de la
Huella ecológica de la transformación del uso del suelo”. 2014.
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