1. business and industrial
2. construction

Congrès annuel de la Société canadienne de génie civil
Annual Conference of the Canadian Society for Civil Engineering
Montréal, Québec, Canada
5-8 juin 2002 / June 5-8, 2002
MODELING THE IMPACT OF CONSTRUCTION PROJECTS ON URBAN
ENVIRONMENTS
A. Gilchrist, D. Cowan, and E.N. Allouche
Department of Civil and Environmental Engineering, The University of Western Ontario, London, Canada
ABSTRACT: A significant number of construction projects are performed in congested urban areas.
Often, the surrounding community finds these projects annoying due to noise, vibration, dust, light and
greenhouse gas emissions. This paper focuses on one type of irritant – noise. Noise generators on
construction sites are identified and mathematical relationships for predicting dissipation and attenuation
of sound waves are presented.
A deterministic model capable of predicting the maximum noise levels at pre-determined locations
around a construction site during each construction stage was developed. It was generated by the various
pieces of construction equipment. The Monte-Carlo simulation technique was used to predict the
likelihood of a particular noise level occurring at each location. The model also predicts the noise levels
when noise barriers are placed around the construction site thus providing a guide to the optimal
composition, geometry and location of such structures. The model is demonstrated via a case history –
the construction of an eight-storey parking garage at University Hospital in London, Ontario.
1.
INTRODUCTION
A significant number of construction projects such as the widening and rehabilitation of highways, urban
renewal construction, the renovation of office and residential buildings and utility construction take place in
congested urban areas. Such construction projects often create excessive noise levels and thus, are a
nuisance to the surrounding community.
Harris (1991) defined sound as a physical disturbance in a medium that is capable of being detected by
the human ear. However, not every sound can be considered noise. The Canada Transportation
Research Board (1999) defined noise as any sound that has the potential to annoy or disturb humans, or
cause adverse psychological or physiological effects on humans.
Noise and noise mitigation have been studied in detail in areas such as manufacturing, industrial
engineering and transportation. However, there has been little research for noise mitigation on
construction projects due to their temporary nature and the fact that they are conducted away from
densely populated urban centres. With the re-construction of many downtown areas the importance of
noise control for construction projects is becoming more evident. Current examples include the Boston
Central Artery project and the Toronto Waterfront rehabilitation project. However, modeling and mitigation
of noise in construction projects is more complicated than in industrial and transportation applications. The
type, number, location, and nature of noise generators are constantly changing depending on the type and
1
stage of construction. Thus, the construction of permanent expensive noise barriers is not an effective
solution. This paper presents a new approach for mitigation of construction noise, by developing the
capability to predict the noise level for a large number of locations placed around the perimeter of a
construction site during different stages of construction. Based on the information gained from this
approach, portable noise barrier systems can be relocated to various locations around the construction
site as noise at that location reach critical levels. Potential savings are particularly significant for large
linear construction projects such as highway rehabilitation or the construction of a light rail transit (LRT)
system or a subway line.
This paper discusses the theory behind the deterministic model created that is capable of predicting the
noise levels generated due to a given construction project in a particular urban setup. The model is
demonstrated using the case history of a newly built eight-storey parking garage structure at University
Hospital in London, Ontario. The results of this case study show that using a model to anticipate noise
levels for a given project could greatly assist in determining the need for sound barriers, their composition,
geometry, and location.
2.
MODEL DESCRIPTION
The following section describes a deterministic model designed to predict noise emission levels at
construction sites. The model can accurately predict noise levels at any number of locations surrounding
the perimeter of a construction site by accounting for many ‘real-life’ situations that may include: (a) a
varying number of noise levels from any number of noise sources of various types; (b) the size of the
construction site; (c) the type of noise barrier required; and, (d) the terrain where the construction activity
is taking place. The model is demonstrated via a case history - the construction of an eight-storey parking
garage in London, Ontario.
2.1
Theoretical Background
The model uses the following general equation to predict the resultant noise level from multiple sources:
f S ( ∑ 1 SO ) − A − B ≤ Lmax
i
where,
fS
i
So
A
B
Lmax
[1]
= synchronization function of construction equipment operating simultaneously
= number of pieces of construction equipment
= equipment noise emission
= attenuation of noise due to the distance traveled by the noise in open air
= anticipated reduction of noise due to the proposed barrier used
= maximum allowable noise limit defined by the city By-Law or contractor documents.
The value used for the equipment emissions coefficient (So) was selected from a database that was
compiled by the authors for more than sixty types of construction equipment, both new and used (Cowan,
2002). Some of the So values are shown in Table 1.
Table 1. Equipment Emission Coefficient (So)
So New
Distance from Point Source
So Used
Construction Equipment
(dB)
(m)
(dB)
Air Compressor
73
76 - 80
15
Auger Drill Rig
83
85
15
Backhoe
75-80
83 - 88
15
:
:
:
:
2
The air attenuation value (A) is obtained using the following dissipation equation (Harris, 1991):
A = ADIV + AAIR + AGROUND + AMISC
[2]
where,
ADIV
= attenuation due to geometrical divergence
AAIR
= attenuation due to the air absorption
AGROUND = attenuation due to the ground absorption
AMISC = attenuation that was not covered in any of the above parameters
Geometrical divergence (ADIV) is the spherical dispersion of acoustic energy in the free field at a point
source. The attenuation of an ideal point source due to divergence is given by Wilson (1989):
L2 – L1 = 20log (r1/r2)
(dB)
[3]
where L2 and L1 are the noise levels (dB) corresponding to distances r2 and r1 (metres), respectively, as
illustrated in Figure 1.
Figure 1. Illustration of Geometrical Divergence Parameters
Air absorption (AAIR) tends to be quite small and can be neglected at short distances (e.g., distances less
than several hundred metres) except for very high frequencies. Thus, for the case of construction projects
in urban environments, AAIR can be considered negligible.
Ground absorption (AGROUND) largely depends on the type of ground surface the noise is traveling over.
When calculating the attenuation due to the ground surface, it is important to consider the hardness of the
ground surface and the distance traveled by the noise. Ground attenuation is quite complicated to
calculate, however a simplified equation can be derived if the following assumptions are made:
• The propagation occurs over ground that is nearly all acoustically soft.
• The noise spectrum is particularly broad and smooth, as occurs frequently for major noise sources
that consist of many different contributing sources (e.g. urban construction projects).
• The noise spectrum contains no prominent frequency components.
• Only the A-weighted sound level at the receiver position is of interest (A-weighted scale refers to
the spectrum of sound that a human ear can detect, Canada Transportation Research Board,
(1999)).
The associated simplified general equation given by Harris (1991) is:
AGROUND = 4.8 – (2hm / r2) · (17 + 300 / r2)
[4]
3
where hm is the mean height of the propagation path (metres) and r2 is the distance between the source
and the receiver (metres).
Miscellaneous attenuation (AMISC) refers to attenuation that is not covered by the other terms such as
reflection from tall buildings (AREFLN) and propagation through areas of houses (AHOUSING). The term AREFLN
may be calculated using the values given in Figure 2.
Hard Ground (asphalt, concrete)
(rr – rd) << all λ
(rr – rd) >> all λ
-3
-2
-1
-6.0
0
1
rr/rd
10
Figure 2. Values for AREFLN (after Harris, 1991)
where rd is the distance from the source height to the receiver height (metres) and rr is the length of the
reflected sound path from the noise barrier to the receiver.
The term AHOUSING accounts for the reflection of the sound waves in dense areas of housing, including
suburban and urban areas. An approximation of this value is given by:
AHOUSING = 0.1 B Sb
[5]
where B is the housing density along that path in square metres of house floors by square metres of
ground and Sb is the length of the sound path through the housing area in metres.
The synchronization coefficient (S) is obtained by comparing two noise source levels at a time and adding
a predetermined value to the highest noise source as described by Thumann & Miller (1976). This process
is known as the branch method and the values to be added are found in Table 2.
Table 2 Values To Be Added to the Highest Noise Level (after Pelton, 1993)
Difference Between Sound
Sources
Correction Factor to be Added to
Higher Decibel Sound Sources
0 OR 1 dB
3 dB
2 OR 3 dB
2 dB
4 TO 7 dB
1 dB
8 OR 9 dB
0.5 dB
10 dB AND UP
0 dB
A noise barrier at a construction site has a finite length and height so the barrier cannot stop all noise.
Noise travels over and around the barriers; thus the barrier can only reduce a small proportion of the total
4
noise emitted. The noise reduced by the barrier is known as transmission loss (TL) and the noise reduced
by the paths over and around the barrier is known as insertion loss (IL). Noise reduction by TL is much
larger than the reduction by IL, thus TL can be neglected. Equation [1] shows the noise reduction due to
the barrier (B) that can be computed from the following equation:
20 f

(a − d ) − Aground
IL = 10 log  3 +
343


[6]
where f is the frequency (Hz), a represents the distance over the barrier (Figure 3) and d is the distance
between the receiver and the source.
Figure 3. Insertion Loss Calculation for Barriers of Finite Length (after Harris, 1991)
The noise transmission paths a, b and c are calculated using Eq: [6]. For paths b and c the AGROUND term
is neglected and the three transmission paths are then synchronized at the receiver using the branch
method.
The noise equation does not consider atmospheric conditions or wind effects. The propagation of sound
close to the ground for horizontal distances less than about 100m is essentially independent of
atmospheric conditions. In urban construction, noise levels of concern are usually at relatively short
distances.
The sum of the factors listed in Eq: [1] should be less than or equal to the maximum permitted noise level
as outlined by the by-law of the city in which the construction is taking place or as outlined in the contract
document. A list of maximum permitted noise values as stated by various Canadian and USA
municipalities can be found in Cowan (2002).
2.2
Case Study – Eight-Storey Parking Garage
The parking garage structure is located on the campus of the University of Western Ontario, just north of
University Hospital, on the southeast corner of Windermere and Western Roads in London, Ontario. It was
important to the hospital that the construction of the parking garage would not interfere with normal
operations. The administration were very concerned that operating rooms located closest to the
construction site on the bottom floor of the hospital (north-east corner, see Figure 4) would experienced
vibrations during compaction processes. Also, a concern was expressed regarding the general level of
noise created at the hospital due to construction. The objective of modeling this project was to ensure the
maximum noise level at the hospital would not exceed 70 dB, a mid-range value for the maximum
allowable noise levels permitted by the municipalities covered in this research.
5
2.3
Model Setup
A deterministic model for predicting urban construction noise was created by integrating Microsoft Excel
and C++ programming software. The program uses the mathematical relationships described in Section
2.1, and information from the equipment noise emissions database to predict the noise values around a
construction site. The model requires user input regarding site layout; type and sequence of construction
activities; type of equipment used during each activity; and the operating noise emission level as well as
the probability of being in one of three operating states (operating, idle, or inactive) and approximate
position in the construction site of each piece of equipment during each activity. The equipment is placed
on the site plan in the approximate location where it would operate during each stage of construction. The
program starts with the first construction activity in the project schedule and randomly determines the
operating status of each machine (operating, idle, or inactive) depending on predetermined probabilities.
The noise level for each piece of equipment is obtained from the database and is a function of its
operating status. Noise levels from all sources are then adjusted for dissipation due to the distance
traveled. The values for ground attenuation needed to complete this calculation were also compiled and
stored in a database. If a noise barrier is located in the line of sight between the source node and the
receiving node, the noise level is again adjusted to account for the anticipated level of noise reduction due
to insertion losses. The noise from all source nodes is then synchronized using the branch method to yield
the resultant noise level at the receiving node. The above algorithm is repeated for each receiver node at
the construction site for five hundred simulation cycles using the Monte-Carlo simulation technique. The
resultant noise level at each receiving node from each cycle is stored and sorted in ascending order to
create the noise level histogram for each node. The program carries out the above described calculations
for each stage of the construction process.
The construction of the parking garage was divided into six stages: excavation, foundation, concrete
curtains, columns, slabs, and roof. Schedule information was derived from the project Gantt chart. Ellis
Don Construction acting as the construction manager for the project, provided the required information
regarding the type and number of pieces of all equipment used during each stage of construction. This
information is summarized in Table 3. The modeling of the excavation stage is described in detail in the
following sections.
Table 3 Equipment Used in the Construction of University Hospital Parking Garage.
6
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Roof
2
2
6
2
2
2
1
1
1
1
1
1
Slabs
Electric Crane
Excavator
Dump Truck
Concrete Truck
Concrete Pumps
Concrete Vibrator
Bull Dozer
Dynapac Roller
Compressor
Sandblasting Equipment
Jackhammer
Saw
Columns
No. of Units
Foundation
Concrete
Curtains
Equipment List
Excavation
Stage
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Using the blueprints of the site layout, a plan view of the construction site was re-created to scale using
AutoCad 2000. The equipment used in the excavation stage was placed on the construction site in the
approximate locations where they would be operating during the actual excavation. The equipment was
assumed to be stationary since the deterministic model is currently unable to account for the movement of
the machines throughout the site during construction.
The total noise created from the construction site was computed at four perimeters located 60m, 80m,
100m, and 120m from the approximate centre of the construction site. Each perimeter consisted of 12
equally spaced nodes for a total of 48 receiver locations. A Monte-Carlo simulation was implemented in
Microsoft Excel using the above-mentioned procedure to determine the maximum noise level at the 48
receiving nodes during the excavation stage. Each machine had a possibility to be in one of three states:
‘operating’, ‘idle’, or ‘inactive’. The predetermined probability of a given machine being in a particular state
was determined based on a comprehensive literature review and consultation with industry experts. The
probability of each machine being in a given state during each cycle was based on a random number
generated by the model that was between 0 and 1. For example, a random value of 0.56 for excavators
during the excavation stage implies an ‘operating’ status, while 0.81 and 0.96 refers to the ‘idle’ and
‘inactive’ states, respectively. The noise level of an ‘operating’ machine was obtained from the equipment
noise emissions database. If the machine was in an ‘idle’ state, the noise level taken was the operating
level less 20 decibels. If the machine was ‘inactive’ the noise level assigned was zero.
The dissipation equation (Eq: 2) was applied to each machine using the distance between the machine
creating the noise and the location of interest. Once all the noise levels were corrected for distance at the
receiving node, the synchronization portion of the noise equation was employed to combine the noise
levels from all sources into a single noise level at the receiver. Five hundred noise levels were computed
for each receiving node. The values chosen for each receiving node were the largest of the five hundred
noise emission values recorded for that specific node (e.g. worst case).
Five hundred simulation cycles were performed on each receiving node. From a theoretical point of view,
there are X3 potential outcomes of noise level at each receiving node depending on the state of each
piece of equipment, where X represents the number of pieces of equipment used during each stage of
construction. The decision to perform five hundred runs was based on the desire to obtain a statistically
significant data set that will enable the determination of the underlying distribution for the noise level at
each receiving node.
2.4
Model Predictions
If no barrier is utilized (baseline scenario) the worst case noise level at the hospital’s main door is
approximately 82 dB. Over the entire site, the maximum noise levels range from 73 dB to 97 dB measured
at distances between 60m to 120m from the approximate centre of the construction site. The assessment
revealed that anticipated noise levels will exceed the maximum allowable value of 70 dB at the hospital
main entrance at all times by as much as 14 dB. Thus, it was decided to simulate the placement of noise
barriers in front of the University Hospital main building.
Two barrier configurations were considered in an effort to find the optimal barrier design that will maximize
the barrier’s effectiveness and minimize its cost. Barrier Type 1 was a 90m long, 5m high, and 20cm thick
post and panel pre-cast concrete barrier with steel I-beams. The barrier was placed on the far side of the
internal road, away from the hospital. The second barrier considered was of the same type and
dimensions as barrier 1, except that it had a total length of 130m and extended northward along the
adjoining internal road. Figure 4 shows noise level values for the critical receiving nodes as a result of the
three scenarios simulated.
7
R oa
d
Inte
rna
l
Barrier Type 2
22
21
(77,77,73)
(82,72,69)
34
46
Barrier Type 1
(84,84,84)
(83,83,78)
(76,75,71)
Construction
Fence
Parking Garage
33
Hospital
(85,85,85)
20
(82,80,79)
Critical
Nodes
(82,72,69)
32
Internal Road
(79,77,77)
45
44
NOTATION
( No Barrier, Barrier 1, Barrier 2 )
Operating Rooms
Node No
Figure 4. Noise Levels for Critical Receiving Nodes for Scenarios:
No Barrier and Barriers Type 1and 2
While the overall maximum noise level is of interest, more significant is the maximum noise level for
critical nodes (i.e., closest to the hospital) during each of the construction stages. The predicted maximum
noise levels for the critical nodes have been graphed as a function of construction stage, and are shown in
Figures 5 to 7. The nodes that exceed the maximum allowable noise level at any stage of construction
can be identified using the figures. Benefits in terms of noise reduction for each barrier alternative at each
of the nodes during any given stage of construction can also be examined using the figures. For example,
the two most critical nodes (33 and 45), both exceeded the 70dB limit with no barrier system installed
during all six stages of construction. When barriers were simulated, the maximum noise level was reduced
below the allowable limit with the exception of Stage One of construction for the case of barrier Type 1.
8
90
Max. Noise
Level = 84 dB
Max. Noise
Level = 81 dB
85
Noise
Level
(dB)
80
75
Max.
Allowable
70 dB
70
65
60
55
12
34
Stage of
Construction
50
5
6
Node 20
Node 22
Node 32
Node 33
(Critical)
Node 34
Node 44
Node 45 Node 46
(Critical)
Receiver
Figure 5. Noise Level for Critical Receiving Nodes - No Barrier
Max. Noise
Level = 72 dB
Noise
Level
(dB)
90
Max. Noise
Level = 72 dB
85
80
75
Max.
Allowable
70 dB
70
65
60
55
12
34
5
Stage of
Construction
50
6
Node 20
Node 22
Node 32
Node 33
(Critical)
Node 34
Node 44
Node 45 Node 46
(Critical)
Receiver
Figure 6. Noise Level for Critical Receiving Nodes - Barrier Type 1
90
Max. Noise
Level = 70 dB
Max. Noise
Level = 69 dB
85
Noise
Level
(dB)
80
75
Max.
Allowable
70 dB
70
65
60
55
1
2
3
4
5
Stage of
Construction
50
6
Node 20
Node 22
Node 32
Node 33
(Critical)
Node 34
Node 44
Node 45
(Critical)
Node 46
Figure 7. Noise Level for Critical Receiving Nodes - Barrier Type 2
9
Receiver
Further analysis was conducted for the noise level at node 33 (closest to the hospital’s main doors). The
noise level at that location was calculated to be 72 dB using barrier Type 1 and 69 dB using barrier Type
2, as shown (Figure 4). Thus, implementing Type 2 noise barrier, a reduction of 13 dB was achieved
resulting in an acceptable noise level at the hospital, as per the maximum allowable value stated in
Section 2.2. For the case when no barrier is used, predictions from most runs in the Monte-Carlo
simulation fit in the 79 – 81 dB category. Most runs for barrier 1 and barrier 2 predict noise levels between
70 – 72 dB and 64 – 66 dB, respectively (Figure 8). Thus, while barrier 2 provides a higher level of
compliance, barrier 1 may be acceptable as most values are within the acceptable range (70dB),
particularly when considering the substantial cost saving associated with the shorter length of the
structure (90m instead of 130m).
300
W ithout Barrier
Barrier Type 1
Frequency
250
Barrier Type 2
200
150
100
50
0
60
- 63
63
- 66
66
- 69
69
72
72
- 75
75
- 78
78
- 81
81
84
Noise Level (dB)
Figure 8. Noise Levels at Node 33 Performing 500 Simulation Cycles for each Scenario
3.
SUMMARY
Major annoyances associated with construction projects include noise, vibrations, light, dust, and
greenhouse gas emission. Identifying methods and techniques for mitigating such problems is a crucial
requirement for serving the public, for conducting business in a responsible manner and for meeting
relevant contract requirements.
This project describes a deterministic model for predicting the maximum noise level that can be expected
in the vicinity of construction operations. The model uses the branch method together with noise and
dissipation equations developed in the areas of transportation and industrial engineering to estimate the
instantaneous noise level in 48 pre-determined receiver nodes established around the construction site.
The Monte-Carlo simulation method is used to predict 500 possible outcomes using random determination
of the operation status of the various pieces of equipment involved. The model enables the determination
of the need for noise control measures to protect critical locations around the construction site as well as
the evaluation of the effectiveness of these measures. In addition, the model’s predictions can be used to
ensure compliance with relevant health and safety regulations regarding aural protection for the
construction workers.
Due to the limitations of the software, as well as the need for a simple equation to determine noise
emission levels, the following assumptions were made:
• Each machine was assumed to be an older piece of equipment (i.e. higher noise emissions)
10
•
•
•
•
Each machine emitted sound at a frequency of 1000 Hz.
The source height for all construction equipment and all receiver nodes was one metre high.
The location of the construction equipment and the probabilities of the operating status of the
equipment.
Because the case studied was a small construction site, minor variables that require large open
spaces, such as the attenuation due to air and atmospheric conditions, were neglected.
From a practical/economical point-of-view, the model described in this paper could be particularly useful
for linear construction/rehabilitation projects such as inter-city highway rehabilitation projects or the
construction of a new subway line or a light railway transit (LRT) system. A finite number of portable
barrier systems are used in such projects to control noise along the path of the project. The model can be
used to identify where and when these systems are needed, thus optimizing their utilization while
preventing unnecessary expenses (i.e., rental of more systems than actually needed).
4.
FUTURE WORK
Future research in this area will focus on more accurate prediction by eliminating some of the above
stated assumptions as well as enhancing the model’s user friendliness by implementing the model within
a commercial simulation environment. Finally, verification of the model is currently underway, with a field
monitoring program of noise levels generated by the construction of a nine-storey parking garage at the
Westminster Hospital Campus in London, Ontario.
5.
ACKNOWLEDGEMENTS
The authors would like to thank Mr. Alfonso Balassone of Ellis Don Construction for his assistance during
this project. The financial support of NSERC (Research Grant 227667RG) is gratefully acknowledged.
6.
REFERENCES
Canada Transportation Research Board, (1999). NCHRP Synthesis 218 – Mitigation of Nighttime
Construction Noise, Vibrations, and Other Nuisances.
Cowan, Darryl. (2002). Modeling the Impact of Construction Projects on Urban Environments. Proposed
Undergraduate Civil Engineering Thesis. The University of Western Ontario, London, ON.
Harris, Cyril. (1991). Handbook of Acoustical Measurements and Noise Control. McGraw-Hill, Inc.
Pelton, Howard. (1993). Noise Control Management. New York: Van Nostrand Reinhold.
Thumann, Albert & Miller, Richard. (1976). Secrets of Noise Control. Atlanta, Georgia: The Fairmount
Press Inc.
Wilson, Charles. (1989). Noise Control. New York: Harper & Row,
11
2e Conférence
spécialisée
en génie
des matériaux
Congrès
annuel de
la Société
canadienne
de génie civil
de la Société canadienne de génie civil
Annual Conference
of the Canadian Society for Civil Engineering
nd
2 Material Specialty Conference
of the Canadian Society for Civil Engineering
Montréal, Québec, Canada
5-8
juin 2002
/ June
5-8, 2002
Montréal,
Québec,
Canada
5-8 juin 2002 / June 5-8, 2002
MODELLING THE IMPACT OF CONSTRUCTION PROJECTS ON
URBAN ENVIRONMENTS
E.N. Allouche, A. Gilchrist, D. Cowan
Department of Civil and Environmental Engineering, The University of Western Ontario, London, Canada
ABSTRACT: A significant number of construction projects are performed in congested urban areas.
Often, the surrounding community finds these projects annoying due to noise, vibration, dust, light and
greenhouse gas emissions. This paper focuses on one type of irritant – noise. Noise generators on
construction sites are identified and mathematical relationships for predicting dissipation and attenuation
of sound waves are presented.
A deterministic model capable of predicting the maximum noise levels at pre-determined locations around
a construction site during each construction stage was developed. It was generated by the various pieces
of construction equipment. The Monte-Carlo simulation technique was used to predict the likelihood of a
particular noise level occurring at each location. The model also predicts the noise levels when noise
barriers are placed around the construction site thus providing a guide to the optimal composition,
geometry and location of such structures. The model is demonstrated via a case history – the construction
of an eight-storey parking garage at University Hospital in London, Ontario.
12