Final Year Project Report

Air Pollution in the Built Environment
Name: Sean Mc Garry.
Degree: BSc. in Applied Physics.
Supervisor: Dr. Miriam Byrne.
Date: 04/04/2016

Table of Contents
1. Introduction 1 - 7
1.1 General Introduction 1 - 2
1.2 Particulate Matter
1.2.1 What is Particulate Matter 2
1.2.2 Sources of Particulate Matter 2
1.2.3 Health and Economic Impacts of Particulate Matter 3
1.2.4 EU Air Quality Guidelines 3
1.2.5 WHO Air Quality Guidelines 4
1.3 Common Methods of Indoor Ventilation
1.3.1 Natural Ventilation 4
1.3.2 Mechanical Ventilation 4
1.3.3 Hybrid Ventilation 5
1.4 Previous Studies on PM Interaction with Built Environments 5 - 7
2. Equipment and Area of Study 8 - 10
2.1 Aerocet 531 8 - 9
2.2 NUIGalway Engineering Building 10
3. Methodology 11 - 14
3.1 Routine Operating Procedure 11
3.2 Data Collection 12
3.3 Data Correction
3.3.1 Aerocet Inter-Comparison 12
3.3.2 Tubing Absorption Correction 13
3.4 Data Analysis 14

Contents Continued
4 Results 15 - 30
4.1 Road Side Particulate Matter Measurements
4.1.1 ‘Day A’ Measurements 15 - 16
4.1.2 ‘Day B’ Measurements 17 - 18
4.2 River Side Particulate Matter Measurements
4.2.1 ‘Day C’ Measurements 19 - 20
4.2.2 ‘Day D’ Measurements 21 - 22
4.3 Third Floor vs Third Floor Measurements
4.3.1 ‘Day E’ Measurements 23 - 24
4.3.2 ‘Day F’ Measurements 25 - 26
4.4 Ground Floor vs Ground Floor Measurements
4.4.1 ‘Day G’ Measurements 27 - 28
4.4.2 ‘Day H’ Measurements 29 - 30
5 Discussion 31 - 34
5.1 Influence of Height Above Ground on PM Count 31 - 32
5.2 Influence of Building Landscape on PM Count 32 - 33
5.3 Discussion of Errors 33
5.4 Limitations of Experiment 34
6 Conclusion 35
7 References 36 - 37
8 Acknowledgements 37
9 Appendices 38
10 Signed Copy of the Plagiarism Statement 40

Abstract
This study examines air pollution in the built environment. In particular, both vertical and
building landscape pollution profiles are determined for PM1, PM2.5, PM7, PM10 and TSP in
a location of diverse landscape. The vertical pollution profile compares data collected by two
Aerocet 531’s, for the ground floor versus the third floor of NUIGalway’s Engineering Building.
It is found that PM1 and PM2.5 concentrations are always higher on the third floor rather the
ground floor. Conversely, PM7, PM10 and TSP concentrations vary on which location has the
highest PM count. A building landscape pollution profile is then created which compares data
collected at the road side versus data collected at the river side. Results show that particulate
matter concentrations at ground level on the river side are higher in comparison to ground
level at the road side, however the converse is true for the third floor as third floor
concentrations were observed to be higher on the roadside. Furthermore, it is identified from
the results that vegetation, traffic and wind velocity have significant influences on the PM
concentration of an area.

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1. Introduction
1.1 General Introduction
In both healthcare and industry the study of particulate matter, with particulate matter often
being referred to as PM, has a very important role. Whether this role be in the designing of
ergonomic clean rooms that ensure particulate matter is kept as low as possible or in
monitoring how different thresholds of particulate matter damage human health, an in-depth
understanding of all aspects of particulate matter is of vital importance. Thus, in this
experiment, an in-depth examination and analysis will take place of how the concentration of
particulate matter varies with height above ground and also how the landscape around
buildings may influence the amount of PM in an area.
In order to understand the importance of this study one must recognise how damaging
particulate matter is to human health and how costly it is to economies around the world.
This information is covered extensively in section 1.2.3 ‘Health and Economic Impacts of
Particulate Matter’ below, however to summarise, particulate matter is the main
environmental factor contributing to premature death in the European Union resulting in
more than 450,000 premature deaths each year in the EU due to PM2.5 alone [1]. On a global
scale, the WHO estimates that in 2012, 3.7 million premature deaths were accredited to
particulate matter of 10microns or less. These figures make it clear that a better
understanding of how to reduce the amount of particulate matter that an individual is
exposed to has the potential to have a profound impact on positively influencing the health
of billions of people around the world.
Motivated by the above statistics, both the EU and WHO have published their own individual
‘Particulate Matter Guidelines’ (as can be seen in section 1.2.4 and 1.2.5). It is important to
note that these guidelines do not represent safe PM limits as it has been widely acknowledged
that no lower threshold of PM has yet been observed below at which no health damage
occurs[2]. Thus these directives have had their PM limits reduced a number of times over the
previous years.
In 2003, China saw an outbreak of the Severe Acute Respiratory Syndrome (often abbreviated
to SARS). This illness spread rapidly throughout many countries and in just nine months over
8,000 cases were reported with 774 of those resulting in death. As SARS was an airborne
disease it was extremely important to understand how it spread so rapidly, thus heavy
investments were made in order to understand its methods of dispersion. One conclusion of
this investment was that the degree of SARS to which a person was exposed, was directly
influenced by the height of the floor of the building which they lived in [3]. This conclusion
leads one to question that if the concentration of the SARS virus varied with height above
ground, then too would the concentration of all airborne particles, such as particulate matter.
In order to expand this theory further, a scientific approach was taken in which this
experiment was developed with its main objectives consisting of two separate phases. Phase
one focuses on the creation of a vertical air pollution profile, while phase two then uses the
same method in order to create a building landscape air pollution profile. These profiles will

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be formed using the data collected by two Aerocet 531’s, with the profiles then being
analysed in order to see if, and if so by what extent, do PM levels change with height above a
ground, and how the surrounding environment of an area may be used to reduce the amount
of ambient outdoor PM.
1.2 Particulate Matter
1.2.1 What is Particulate Matter:
Particulate matter, or PM as it is often abbreviated to, is a mixture of solid particles and liquid
droplets that are found in air. These particles come in many different shapes and sizes and
they are predominantly classified by the particles diameter with PM2.5 representing
particulate matter that is less than 2.5 microns in aerodynamic diameter and PM10
representing particulate matter that is less than 10 microns in aerodynamic diameter. ‘Figure
1.2.1- A’ below provides a good visual representation of how small PM actually is as it can be
seen that a single strand of hair is over 30 times large than PM2.5:
Figure 1.2.1- A: Scale diagram of various particles [4].
Particulate matter can be further classified as ‘fine particles’ and ‘inhalable coarse particles’.
Fine particles are made up of particulate matter with diameters of less than 2.5microns, while
inhalable coarse particles consist of particles ranging in size between 2.5 and 10 microns in
diameter [5].
1.2.2 Sources of Particulate Matter:
Particulate matter can be made up of many different chemicals. Particles emitted directly
from a source are referred to as ‘primary particles’, while particles formed through chemical
reactions are known as ‘secondary particles’ [6].

3
Secondary particles are predominantly formed through chemical reactions occurring in the
atmosphere and they represent the main constituent of fine particles (PM2.5 and smaller).
These fine particles often originate from sources of combustion such as vehicles, power
generation and industrial facilities. Here, emissions of organic gases, sulfur oxides and
nitrogen oxides undergo chemical reactions in the atmosphere resulting in the formation of
tiny particulates [7]. These particulates have the ability to travel great distances as they can
remain suspended in the atmosphere for long periods of time.
Inhalable course particles usually originate from activities which disturb soils and materials.
These activities include construction, mining, fires and road traffic. Examples of inhalable
course particles are dust, pollen and mould, while combustion particles, metals and organic
compounds are examples of fine particles.
1.2.3 Health and Economic Impacts of Particulate Matter:
The WHO estimates that ambient air pollution caused 3.7 million deaths worldwide in 2012
with this mortality predominantly being due to exposure of PM10 or smaller. This estimate
attributes particulate matter as the main contributing environmental factor to premature
death as it significantly increases the incidence of a wide range of diseases such as heart
disease, stroke, lung disease and various cancers. This healthcare issue has a direct effect on
many countries across the world as it results in higher healthcare costs, lower productivity
and increased sick days thereby occurring an estimated €330 -€940 billion total cost onto the
world’s economy annually [1].
1.2.4 EU Air Quality Guidelines:
‘Table 1.2.4’ below represents the particulate matter limits as set out by ‘The Ambient Air
Quality Directive’ report by the European Environment Agency. This directive sets out limits
for both short term and long term exposure to PM2.5 and PM10. This report also
acknowledges that the short term limit value for PM10 is the most regularly exceeded PM
limit in the European Union [8].
Table 1.2.4: EU Particulate Matter Guidelines [8]

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1.2.5 WHO Air Quality Guidelines:
As seen in ‘Table 1.2.5’ below, the WHO PM guidelines are much lower than the EU PM
Guidelines. Even at these lower PM limits, the WHO still advises that no threshold of
particulate matter has been identified at which below no health damage is observed. Thus
PM levels should be reduced to as little as possible.
Table 1.2.5: WHO Particulate Matter Guidelines [9]
1.3 Common Methods of Indoor Ventilation
1.3.1 Natural Ventilation:
Natural ventilation uses natural forces such as wind and thermal-buoyancy forces in order to
continuously move air through purpose built openings known as envelope air vents [10]. These
openings may include windows, doors and chimneys, which allow air to be transferred
between the indoor area and the environment outside. Many modern buildings are now so
well insulated that they are effectively air tight. This reduces the amount of ventilation which
may occur naturally, thus resulting in a significant decrease in natural ventilation methods
over the last decade.
1.3.2 Mechanical Ventilation:
Mechanical ventilation utilises fans in order to physically force the movement of a body of air
to or from an area. Depending on the requirements and cost constraints, these fans may be
directly installed in walls and windows, or else placed in purpose built air ducts.
In humid environments, a positive pressure mechanical ventilation system is most popular as
it decreases the amount of infiltration, and hence condensation, occurring in the building.
This positive pressure system consists of air being pumped into a building resulting in an
increase in indoor air pressure. Air is then forced to leave the area through openings in doors,
windows etc. in order to move outdoors to where the air pressure is lower. Conversely, a
negative pressure system is used in cold climates [10]. Furthermore, in an area in which
pollutants such as particulate matter is produced, negative pressure ventilation is again used
as this increases the rate at which pollutants are dispersed from the area.

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Mechanical ventilation does have a number of issues such as increasing the amount of noise
pollution, varying the temperature of the area to which it blows and also the need for a
constant electricity supply.
1.3.3 Hybrid Ventilation:
As the name suggests, hybrid ventilation utilises both mechanical and natural ventilation in
order be more efficient in terms of energy. Natural driving forces are the main method used
however if the natural ventilation flow rate is not sufficient, then mechanical ventilation
methods will temporarily be employed [10].
1.4 Previous Studies on PM Interaction with Built Environments
Various researchers have previously investigated vertical air pollution profiles in the built
environment. There are a number of these studies which are of particular interest to this
experiment:
A study carried out in 2003 in Beijing investigated how the concentrations of PM2.5 and PM10
varied at heights of 8m, 100m, 200m and 325m. The results from this experiment indicated
that PM2.5 displayed distinct layered structures which are accredited to the existence of fine
atmospheric layers over Beijing. These layers were made up of different temperature profiles
with this temperature profile determining the stability of each layer. The profile’s stability
was then found to be influencing the PM2.5 concentration level of the layer. Furthermore, it
was found that the PM2.5 and PM10 OC/EC (organic carbon to elemental carbon) ratio
concentrations were actually increased at higher levels of the vertical pollution profile in
comparison to lower levels. It was concluded that these higher ratios were due to the
transport of emissions, which were created by nearby industrial sources, into the region of
study. Overall however, PM2.5 was observed to be reduced by 25.2% at a height of 200m
versus 8m, while PM10 was reduced by over 30.3% over the same vertical distance [11].
A study carried out in 2000 in Hong Kong investigated the vertical dispersion of suspended
particulates in urban areas. To do this, two street-canyon locations were chosen at which PM
measurements were monitored up to a height of ten floors. In both street-canyon settings it
was observed that PM10 concentrations were found to decrease exponentially with height.
Furthermore it was identified that the rate of decrease for TSP, PM10 and PM2.5 with height,
was in decreasing order of TSP, PM10 and PM2.5 respectively. It was further concluded that
the height to width ratio of the street also had a considerable impact on the dispersion of all
PM sizes investigated [12].
A study carried out in 2006 in Sweden again investigated how pollution concentrations varied
with height in a street-canyon. Measurements were taken at heights of 10m and 32m for
PM10 and TSP. Like many studies it was observed that PM concentrations exponentially
decreased with an increase in height in a street-canyon setting [13].

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A study in Finland further examined the vertical air pollution profile of a street-canyon.
Measurements were taken at heights of 1.5m and 25m above the ground. In this experiment
it was identified that both dispersion and dilution have a large role to play in the reduction of
PM concentrations. Unlike other experiments however, only a five factor decrease was
observed in PM concentrations between the two measuring points. Furthermore, chemical
reactions were seen to have played a considerable role in forming vertical aerosol
concentration gradients [14].
A study in New Zealand examined the relationship between temperature and PM
concentrations over a 400m height. It was observed that temperature increased with height
between 0-50m and then remained relatively constant. A correlation was then apparent that
PM concentrations decreased with increasing temperature and vice versa. This observation is
only a correlation however as there are too many external factors present, such as wind
speed, to imply causation [15].
An experiment in China in 2002 investigated the vertical and horizontal profiles of particulate
matter near roadways. The horizontal profile was created over a perpendicular distance of
228m to the road. A decrease of 7%, 9% and 10% of the maximum concentration was found
at a distance of 2m, 4m and 8m respectively from the road, however over the entire 228m
perpendicular distance this rate of decrease did not continue. Thus it was concluded that in
the horizontal pollution profile, no significant decreasing trend was found. In terms of the
vertical pollution profile, an 80%, 62% and 60% decrease was found in the concentrations of
PM1, PM2.5 and PM10 respectively when PM concentrations were compared between the
measurements taken at a height of 2m and 79m (with the 79m concentrations being lower
than the 2m concentrations) [16].
In 2006 an experiment was conducted in which the outdoor levels of PM10 were measured
at different heights of a multi-story building. The results of this study found that PM10
concentrations were higher for lower floor apartments in comparison to floors up high.
Furthermore, these differences in PM concentration were significantly greater in the winter
and the summer compared to the differences in spring and autumn [17].
A study conducted in New York in 2011 studied the relationship between the floor level of
the building which an individual lived in and their exposure to particulate matter. Although
admitting that other studies have found that PM2.5 decreases with height, the results of this
experiment found no such gradient existed [18]. Interestingly, the authors attribute this lack of
concentration gradient to the possibility of the study area being overwhelmed with
particulate matter due to numerous emission sources such as heavy traffic and long range
transported aerosols. This finding is not unique as many other studies have also shown no
finding of a significant vertical PM concentration gradient [19].
Based on this literature review, it is clear that knowledge gaps still remain regarding the
vertical pollution profile of particulate matter, particularly in high-rise buildings. It is this
knowledge gap which has framed the aims and objectives for the present study, which are:

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1. To create a vertical air pollution profile for PM1, PM2.5, PM7, PM10 and TSP on both
the river and road sides of NUIGalway’s Engineering Building.
2. To create a building landscape air pollution profile for PM1, PM2.5, PM7, PM10 and
TSP for both the ground and third floor of NUIGalway’s Engineering Building.
By achieving these objectives, the most health wise appropriate location to duct in air from
outside a building for the purposes of indoor ventilation will be identified. This ‘cleaner’ air
will ensure that inhabitants of a building are exposed to the lowest concentrations of
particulate matter possible. Furthermore, by determining how the environment around a
building may increase/decrease particulate matter levels, conclusions will be made on the
benefit of environmental features, such as areas of vegetation, which could be incorporated
into the future design plans of built areas. These two factors combined have the potential to
make a real positive impact on improving the health of populations across the world.

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2. Equipment and Area of Study
2.1 Aerocet 531
Figure 2.1- A: Aerocet 531 Particle Mass Counter [20]
In this experiment an Aerocet 531 (Figure 2.1- A), manufactured by MetOne, is used to
measure the particulate matter count of an area. This machine is an optical based
particulate mass counter which utilises laser light in order to determine the sizes and
volume of particulate matter in a region. A laser is the chosen light source as a laser beam
is composed of only one wavelength resulting in only one single colour of high-intensity
light [21].
On top of each Aerocet device there is a suction nozzle. This nozzle takes air from around
the machine and delivers it to a small chamber known as a viewing volume. Optics are
then used to focus and collimate the laser beam so that this viewing volume is illuminated.
Once this viewing volume is illuminated, the light may collide with any particulate matter
present thereby causing the incident light to scatter. Further optics are then used in order
to deliver this reflected/scattered light to a photodetector.
The photodetector is extremely sensitive to any incident light and as a small particle
scatters small pulses of light and big particles scatter big pulses of light, once a flash of
light is incident upon it, it emits an electric signal that is proportional in magnitude to the
size of the particle. An amplifier is then used to convert these signals to a proportional

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control voltage. A Pulse Height Analyser then examines these signals and thereby places
each value into the relevant sizing bin. An electronic circuit then examines the number of
signals in each bin before finally converting this information into particle data.
In order to reduce errors, the Aerocet 531 utilises a number of key techniques, the most
effective being to only use the center of the laser beam for illumination purposes. As seen
in ‘Figure 2.1- B’ below, the intensity of a laser beam follows a Gaussian distribution and
therefore is not perfectly uniform. Instead, its intensity decreases with increasing distance
from the beams center. To combat this, the Aerocet 531 employs a central beam method
which reduces the amount of errors in measurements by using only the central part of the
beam. In doing so, each particle is being hit with the same intensity of incident light. Thus
the magnitude of any scattered light can be directly compared as its magnitude is only
dependent on the particles size since the laser intensity is now uniform [21].
Figure 2.1- B: Gaussian profile of laser beam [22]

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2.3 NUIGalway Engineering Building
Figure 2.3-A: NUIGalway Engineering Building [23]
The NUIGalway Engineering Building was chosen as the study location for this experiment.
This was so for a number of reasons:
 The building is four floors in height which meant a vertical separation of
approximately 40m could be achieved between the two measurement locations.
 The left hand side of the building, as in ‘Figure 2.3- A’, is less than 10m distance
from a road.
 The right hand side of the building is immediately beside a small area of vegetation
and forestry which consists of a variety of plants and trees. The right hand side is
also less than 40m from the Corrib River.
 The building is in close proximity to a live weather station which is updated hourly.
These four factors meant that by choosing the Engineering Building as the experiment study
area, not only could the original objective to create a vertical air pollution profile be
achieved, but also the buildings diverse landscape meant that a building landscape air
pollution profile could too be created. Both sets of data could then be compared against
accurate weather records in order to see if any relationship existed between PM count and
weather.

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3. Methodology
3.1 Routine Operating Procedure
*Follow this ‘routine operating procedure’ each time the Aerocets are to be used.
**The ‘Menu’ button, ‘Enter’ button and navigational arrows are used to navigate through
the Aerocets system interface as well as to input all necessary settings onto the device.
1. Fully charge both Aerocets.
2. In order to clear any previously saved data on the Aerocets, navigate to the
‘Memory’ tab and then press the ‘Enter’ button twice. The screen will then
display the message ‘Memory is 100%’.
3. Input the settings in ‘Table 3.1’ below, into both Aerocets by using the navigation
buttons as explained in bold writhing above. There are two setting tabs on the
machine, one called ‘Sample Setup’ and the other named ‘Settings’:
Tab Sub Heading Option to be Chosen
Sample Setup Sample Mass
Op Mode Auto
Hold Time 001
Settings Volume Liter
Temperature C
Printer On
Table 3.1: Aerocet Input Settings
4. Place both Aerocets beside each other so that both machines are susceptible to
the same environmental conditions.
5. Attach the white cylindrical filter to the suction nozzle on the top left of the
Aerocet. Ensure that this filter is firmly in place.
6. Turn the Aerocets on and press the ‘Start’ button in order to begin the data
collection process.

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7. Allow the Aerocets to run for a period of five minutes until the particulate matter
(pm) count for each size of particle is ‘0.000 mg/L’.
8. Now simultaneously remove the filters from each Aerocet.
3.2 Data Collection
In order to collect the relevant data, carry out the procedure as outlined in the ‘Routine
Operating Procedure’. Once this procedure has been followed, connect the piece of plastic
tubing to the suction nozzle of the Aerocet. Place the Aerocet inside its metal case and leave
the machine in the desired location for the required period of time.
As the Aerocet is collecting data, ensure to keep an accurate hourly account of weather
parameters such as rainfall, wind speed, wind direction, solar irradiance, relative humidity
and temperature. This will allow a comparison to be made between particulate matter count
and weather.
Once the data has been collected, use the COMET software, as provided by MetOne, in order
to retrieve the data from the Aerocet. This will save the data as a ‘.txt’ file. Then use an Excel
spreadsheet and the ‘LOOKUP’ and ‘INDEX’ functions in order to organise the data into a
format which can be readily analysed.
3.3 Data Correction
3.3.1 Aerocet Inter-Comparison:
In order to calibrate the two Aerocets against a known standard, the machines have to be
returned to the manufacturer, MetOne, in the U.S.A. This may not be possible due to
experimental time constraints.
As this experiment is focused on how particulate matter count varies with height and/or
landscape, the machines do not need to measure the EXACT amount of particulate matter in
an area so long as each machine gives the same reading as the other, under the same
environmental conditions. Thus, if sending the Aerocets back to the U.S.A. is not feasible, one
possible method of ensuring that the Aerocets meet the requirements of this experiment is
to carry out a machine inter-comparison.
To do this, place both Aerocets beside each other so that they are both susceptible to the
same environmental conditions and then carry out the procedure as outlined in the ‘Routine
Operating Procedure’. Once done, leave the Aerocets beside each other to un-interruptedly
collect data for a period of at least 2 hours. Ensure that the area in which the Aerocets are
left has variable environmental conditions as this will allow one to best observe how the
readings vary between the two machines for different particulate matter counts. Also ensure
that the area at which the Aerocets are left is exposed to all particulate matter sizes, i.e. PM1,
PM2.5, PM5, PM7 and PM10, as otherwise the machines may give a reading of ‘0’ for some
PM sizes which is not useful for inter-comparison purposes.

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For the purposes of this experiment, it was clear by analysing the data that the following ratios
were the best approximation to use when making an inter-comparison correction to the
collected data, with Aerocet 2 being taken as the standard:
Machine Inter-Comparison PM1 PM2.5 PM7 PM10 TSP
Ratio Aerocet 2 vs Aerocet 1 1.0000 2.2069 1.5357 1.3547 1.4442
Table 3.3.1: Table displaying the ratio of measurements taken by Aerocet 2 compared to the
measurements taken by Aerocet 1 under the same environmental conditions.
3.3.2 Tubing Absorption Correction
The plastic tubing used in this experiment is ‘SMC TO604 NYLON E.NJ3’ with an internal
diameter of 3mm.
As plastic tubing must be connected to the suction nozzle of the Aerocet, it is important to
quantify how much/if any particulate matter is absorbed by the tubing for each size of
particulate matter.
To do this, place both Aerocets beside each other so that they are both susceptible to the
same environmental conditions and then carry out the procedure as outlined in the ‘Routine
Operating Procedure’ section. Once done, connect a 0.8m piece of the tubing to the Aerocet
and allow the Aerocet to collect data for a period of 10 minutes. Upon the 10 minutes been
up, immediately replace the 0.8m length of tubing with tubing of length 0.5m and again allow
the Aerocet to collect data for a period of 10 minutes. Repeat this process for tubing of lengths
0.25m, 0.1m, 0.05m, 0.025m, and 0m (no tubing).
Once all of the relevant data has been collected, use Excel to determine the difference
between the mass of the particulate matter absorbed for each length of tubing. Use these
results to create a graph of ‘PM Absorbed’ vs ‘Length of Tubing’. For the purposes of this
experiment absorption was only found to be significant for PM10 and TSP (Total Suspended
Particles) with the absorption per length of tubing as displayed in the graph below:

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Figure 3.3.2: Graph depicting the amount of particulate matter absorbed per length
of tubing for PM10 and TSP.
3.4 Data Analysis
As over the duration of the experiment more than one hundred hours of data is taken, it is
extremely difficult to notice any possible trends when the data is displayed in spreadsheet
format. Thus, the best method of analysing the data is to visually display the data in graphical
form. In order for simple comparison of results, each graph should only display the data for
one particular size of particulate matter. Error bars should also be included on all data points
as this allows one to quickly evaluate how accurate each measurement is.

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4. Results
4.1 Road Side Particulate Matter Measurements
4.1.1 ‘Day A’ Measurements (24/02/2015):
Figure 4.1.1- PM1: Particulate
Matter Count for PM1.0 from
9:00 am to 16:00pm on the
Road Side of the NUIGalway
Engineering Building.
Figure 4.1.1- PM2.5:
Particulate Matter Count for
PM2.5 from 9:00 am to
16:00pm on the Road Side of
the NUIGalway Engineering
Building.
0
2
4
6
8
10
12
14
16
18
8 9 10 11 12 13 14 15 16
Mass(µg/m^3)
Time of Day
Road DayA- Pm2.5
Ground Pm2.5
Third Pm2.5
-0.5
0
0.5
1
1.5
2
2.5
9 10 11 12 13 14 15 16
Mass(µg/m^3)
Time of Day
Road DayA- Pm1.0
Ground Pm1.0
Third Pm1.0

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Figure 4.1.1- TSP: Particulate
Matter Count for TSP (Total
Suspended Particulate) from
0
5
10
15
20
25
30
9 10 11 12 13 14 15 16
Mass(µg/m^3)
Time of Day
Road DayA- Pm7.0
Ground Pm7.0
Third Pm7.0
0
5
10
15
20
25
30
9 10 11 12 13 14 15 16
Mass(µg/m^3)
Time of Day
Road DayA- Pm10.0
Ground Pm10.0
Third Pm10.0
0
5
10
15
20
25
30
35
9 10 11 12 13 14 15 16
Mass(µg/m^3)
Time of Day
Road DayA- TSP
Ground TSP
Third TSP

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4.1.2 ‘Day B’ Measurements
Matter Count for PM1.0 from 9:00
am to 16:00pm on the Road Side
of the NUIGalway Engineering
Building.
Figure 4.1.2- PM2.5: Particulate
am to 16:00pm on the Road Side
of the NUIGalway Engineering
Building.
0
2
4
6
8
10
12
14
8 9 10 11 12 13 14 15 16
Mass(µg/m^3)
Time of Day
Road DayB- Pm2.5
Ground Pm2.5
Third Pm2.5
0
0.5
1
1.5
2
2.5
9 10 11 12 13 14 15 16
Mass(µg/m^3)
Time of Day
Road DayB- Pm1.0
Ground Pm1.0
Third Pm1.0

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am to 16:00pm on the Road Side of
the NUIGalway Engineering Building.
am to 16:00pm on the Road Side of
Figure 4.1.2- TSP: Particulate Matter
Count for TSP (Total Suspended
Particulate) from 9:00 am to
16:00pm on the Road Side of the
NUIGalway Engineering Building.
0
5
10
15
20
9 10 11 12 13 14 15 16
Mass(µg/m^3)
Time of Day
Road DayB- Pm7.0
Ground Pm7.0
Third Pm7.0
0
5
10
15
20
9 10 11 12 13 14 15 16
Mass(µg/m^3)
Time of Day
Road DayB- Pm10.0
Ground Pm10.0
Third Pm10.0
0
5
10
15
20
25
9 10 11 12 13 14 15 16
Mass(µg/m^3)
Time of Day
Road DayB- TSP
Ground TSP
Third TSP

19
4.2 River Side Particulate Matter Measurements
4.2.1 ‘Day C’ Measurements (03/03/2016):
Figure 4.2.1- PM1: Particulate Matter
Count for PM1.0 from 9:00 am to
16:00pm on the River Side of the
am to 16:00pm on the River Side of
0
5
10
15
20
25
9 10 11 12 13 14 15 16
Mass(µg/m^3)
Time of Day
River DayC- Pm2.5
Ground Pm2.5
Third Pm2.5
-0.5
0
0.5
1
1.5
2
2.5
9 10 11 12 13 14 15 16
Mass(µg/m^3)
Time of Day
River DayC- Pm1.0
Ground Pm1.0
Third Pm1.0

20
Particulate) from 9:00 am to 16:00pm
on the River Side of the NUIGalway
0
5
10
15
20
25
30
35
40
9 10 11 12 13 14 15 16
Mass(µg/m^3)
Time of Day
River DayC- Pm7.0
Ground Pm7.0
Third Pm7.0
0
5
10
15
20
25
30
35
9 10 11 12 13 14 15 16
Mass(µg/m^3)
Time of Day
River DayC- Pm10
Ground Pm10.0
Third Pm10.0
0
5
10
15
20
25
30
35
40
9 10 11 12 13 14 15 16
Mass(µg/m^3)
Time of Day
River DayC- TSP
Ground TSP
Third TSP

21
4.2.2 ‘Day D’ Measurements (07/03/2016):
Building.
Figure 4.2.2- PM2.5 Particulate
Building.
0
2
4
6
8
10
12
9 10 11 12 13 14 15 16
Mass(µg/m^3)
Time of Day
River DayD- Pm2.5
Ground Pm2.5
Third Pm2.5
-0.1
0
0.1
0.2
0.3
0.4
0.5
9 10 11 12 13 14 15 16
Mass(µg/m^3)
Time of Day
River DayD- Pm1.0
Ground Pm1.0
Third Pm1.0

22
Building.
Particulate) from 9:00 am to
0
5
10
15
20
25
9 10 11 12 13 14 15 16
Mass(µg/m^3)
Time of Day
River DayD- Pm7.0
Ground Pm7.0
Third Pm7.0
0
5
10
15
20
25
9 10 11 12 13 14 15 16
Mass(µg/m^3)
Time of Day
River DayD- Pm10
Ground Pm10.0
Third Pm10.0
0
5
10
15
20
25
30
9 10 11 12 13 14 15 16
Mass(µg/m^3)
Time of Day
River DayD- TSP
Ground TSP
Third TSP

23
4.3 Third Floor vs Third Floor Measurements
4.3.1 ‘Day E’ Measurements (29/03/2016):
15:00pm on the third floor of the
Figure 4.3.1- PM2.5: Particulate Matter

24
15:00pm on the Third Floor of the
15:00pm on the Third Floor of the
on the Third Floor of the NUIGalway

25
4.3.2 ‘Day F’ Measurements (31/03/2016):

26
Count for PM7.0 from 8:00 am to 15:00pm
on the third floor of the NUIGalway
Figure 4.3.2- TSP: Particulate Matter Count
for TSP (Total Suspended Particulate) from
8:00 am to 15:00pm on the third floor of

27
4.4 Ground Floor vs Ground Floor Measurements
4.4.1 ‘Day G’ Measurements (02/04/2016):
am to 17:00pm on the third floor of

28
on the third floor of the NUIGalway

29
4.4.2 ‘Day H’ Measurements (03/04/2016):

30
Figure 4.4.2- PM7: Particulate Matter Count
for PM7.0 from 10:00 am to 17:00pm on
the third floor of the NUIGalway
Figure 4.4.2- TSP: Particulate Matter Count
for TSP (Total Suspended Particulate) from
10:00 am to 17:00pm on the third floor of

31
5. Discussion
5.1 Influence of Height above Ground on PM Count- Ground Floor vs Third Floor
Day A: As seen in section 4.2.1, all PM sizes follow a similar profile. At 09:00am all PM
concentrations are very high in comparison to the concentrations for the rest of the day. Also
at 09:00am, as seen in ‘Figure 4.1.1- PM2.5’, the ground floor concentrations for PM2.5 are
78% higher than those for the third floor. Furthermore, at this time, the ground
concentrations of PM2.5 are 5µg/m3 more than the WHO PM2.5 annual mean guidelines [9].
In all graphs, concentration decreases throughout the day except between 12-13:00pm
where a slight increase is observed. In ‘Figure 4.1.1- PM10’ the third and ground floor PM10
concentrations are 25% and 21% higher respectively than the WHO annual PM10 guidelines
[9].
Day B: The concentrations of all PM sizes again have very similar profiles throughout the
entire day as can be seen in section 4.1.2. For PM2.5, a 125% increase in concentration levels
can be seen in ‘Figure 4.1.2- PM2.5’ on the ground floor between 08-10:00am while on the
third floor only a 31% increase is seen for the same time period. Also at 10:00am, the ground
floor PM2.5 concentration is 92% higher than the third floor level. This 92% difference
remains relatively constant until 14:00pm. A concentration increase for all PM sizes is
observed between 12-14:00pm. These times when concentration increases reflects the times
of the day at which traffic increases significantly.
Day C: As seen by all graphs in section 4.2.1, the concentrations of all PM sizes are initially
relatively high at 09:00am in comparison to the concentrations from 09-12:00pm. A decrease
then occurs until 12:00pm at which point the concentration again begins to rise until
observations stop at 15:00pm. ‘Figure 4.2.1- PM2.5’ shows that PM2.5 concentrations are
constantly greater on the ground floor, while for PM10 and TSP the converse is true and
instead, third floor PM10 and TSP counts are larger than those on ground level.
Day D: As seen by all graphs in section 4.2.2, the profiles for the third floor concentrations for
each PM size are extremely similar. PM2.5 on the ground floor also shares this common
profile. As observed in ‘Figure 4.2.2- PM7’, ‘Figure 4.2.2- PM10’ and ‘Figure 4.2.2- TSP’, the
ground floor concentration profiles for PM7, PM10 and TSP are all the exact same as each
other. These three profiles fluctuate periodically between 10am-14:00pm with the highest
concentrations being found at 13:00pm. At all times, the concentrations of each PM size are
within the limits of both the WHO and EU PM concentration guidelines [10].
Vertical Pollution Profile Discussion: On the riverside on Day D, the concentration for all PM
sizes were greater on the ground floor versus the third floor. It is believed that this higher
ground concentration is occurring due to the presence of vegetation such as plants and trees
around the area of the riverside of the Engineering Building. This vegetation is effectively
trapping any particulate matter that may be present in the ground floor region thus increasing
the relative PM concentration. The third floor however sits above the vegetation. Thus,
particulate matter is free to move away from the vicinity of the third floor area thereby
reducing its concentration level. As day D was very calm, this process of vegetation ‘trapping’
was the dominant factor in determining how PM was dispersed and distributed. The trapping
effect of vegetation has been concluded by numerous studies [24][25][26], with one study of

32
notable interest being “Vegetation and Urban Environment” which determined that forested
areas can reduce atmospheric dust by 75% in comparison to non-forested areas [24].
Contrary to Day D’s results, on Day C, PM10 concentrations were higher on the third floor
rather than the ground floor on the river side. As can be seen in the ‘Day C- Weather’ table in
the Appendices, Day C was slightly windier than Day D. It is likely that this added wind
provided enough energy in order to allow the fluidization velocity of PM10 to be sufficient
enough to vertically displace PM10 to the third floor so that concentrations there were higher
than at ground level. Supporting this fluidization velocity theory is a number of papers which
show that the greater the velocity of the gas which a particle is suspended in, the greater the
particles fluidization velocity, and thus the greater it moves vertically [27]. Overall it is believed
that wind dominated dispersion was the main process influencing PM distribution on day C,
with the ‘trapping’ processes of vegetation having a lesser effect.
In both Day A and B, PM2.5 is higher on the ground floor of the road side due to the rate of
generation of PM2.5 by vehicles being much greater than the rate at which PM2.5 was being
dispersed. This led to an accumulation of PM2.5 at ground level making the air at the third
floor clean in comparison.
Overall, from examining the results of the vertical air pollution profile, PM2.5 was always in
greater concentration on the ground floor versus the third floor. Occasionally PM7, PM10 and
TSP were greater on the third floor, however due to PM2.5 being the most damaging to
health, air should be ducted in to a building from the third floor height for the purposes of
indoor ventilation.
5.2 Influence of Building Landscape on PM Count- Road Side vs River Side
Day E: The profiles of all PM sizes, except PM1, in section 4.3.1 are very similar. An increase
in concentration occurs between the hours of 08-09:00am and 11-12:00pm. PM10 exceeds
the WHO PM10 annual concentration guidelines by 9µg/m3 at 12:00pm. At all times, for all
PM sizes, the road side third floor concentrations are greater than those at the river side.
Day F: The profiles for all PM sizes are again extremely similar to each other as can be seen in
section 4.3.2. A large increase can be seen for the concentration of all PM sizes between 11-
12:00pm and 13-14:00pm. Again, roadside concentrations are greater than those at the
riverside.
Day G: As can be seen by all graphs in section 4.4.1, all PM concentrations increase from 10-
11:00am while a decrease occurs between 11am-16:00pm. From 16-17:00pm an increase in
concentration levels is again seen but this time on the roadside only. The PM concentration
for PM7, PM10 and TSP are all greater on the river side throughout the day. PM2.5 however
is greater on the roadside. Although these measurements were taken on a Sunday one would
think that they would be relatively low especially considering that traffic in NUIGalway is
quietest on Sundays. This is not the case however as at 11:00am, concentrations for the river
side are 9.5, 41, 48 and 50µg/m3 for PM2.5, PM7, PM10 and TSP respectively. After this time,
concentration levels uniformly decrease throughout the day. This appears to be a ‘freak’ spike
in concentration which may have been caused by a temporary switch in wind direction.

33
Day H: As can be seen by ‘Figure 4.4.2- PM7’, ‘Figure 4.4.2- PM10’ and ‘Figure 4.4.2- TSP’,
PM7, PM10 and TSP all have the same profiles to each other. These profiles increase in
concentration from 11-12:00pm and 14-16:00pm. Each of these profiles show that
concentrations for PM7, PM10 and TSP were greater on the river side versus the road side.
‘Figure 4.4.2- PM2.5’ is quite unique. This graph shows that the profiles for the river and road
side vary quite considerably with the road side showing higher levels of PM2.5 throughout
the day.
Building Landscape Pollution Profile Discussion: Third floor concentration measurements
indicate that PM concentration for all PM sizes is greater on the roadside. It can be considered
that for PM7, PM10 and TSP, this is due to particulate matter been trapped near to the ground
by vegetation at the riverside as is discussed in section 5.1. This would limit the amount of
PM that reaches the third floor on the river side, thereby making the third floor road side
concentrations greater in comparison.
The measurements for PM2.5 indicated that PM2.5 is greater on the roadside on both the
ground and third floor in comparison to the ground and third floor on the river side. All
evidence suggests that this is due to the contribution of traffic to PM2.5 levels.
PM7, PM10 and TSP are greater on the ground floor at the riverside in comparison to the
ground floor at the road side. Again, this is due to the ‘trapped’ effect which vegetation has
on PM. Conversely to the effect which this trapped occurrence has on the third floor, PM
concentrations instead increase on the ground floor as the vegetation is now causing PM to
build up in the ground floor region as the PM finds it difficult to escape past the plants and
trees. This leads to an accumulation of PM at ground level thereby increasing the ground level
PM concentration.
Overall, from examining the results it has being shown that trees and plants increase the PM
concentration of an area situated at ground level, however above the vegetation a noticeable
decrease in PM levels occur. Roads have also been identified as factors which increase the
PM concentrations of nearby areas.
For the purposes of indoor ventilation, air ducts should be kept as far away from roads as
possible and vegetation should be planted beneath the location at which air is to be ducted
in to a building as this will significantly reduce the amount of particulate matter that is present
in the air above.
5.3 Discussion of Errors
In this experiment there existed a number of possible errors.
Absorption of particulates by the plastic tubing attached to the Aerocet’s suction nozzle was
of major concern. This was counteracted by using as little tubing as possible and ensuring that
the tubing contained no bends which would slow down the airs speed as it passed through
the tube. As the air slows it is more likely to be absorbed hence it was important to keep the
air’s velocity uniform and constant.
As the Aerocet 531 is an optical particle counter, errors may occur if the machine is not kept
still. This is so as when the machine moves, so too does the optics inside. This results in the

34
light scattered by particulates not focusing 100% accurately on the photodetector thus
resulting in the photodetector giving a false reading. This error was kept as low as possible by
surrounding the Aerocet with insulation and placing it on a steady surface away from any
noticeable vibrations.
As the aim of the experiment was to determine which locations had the lowest concentrations
of particulate matter, it was important that both Aerocets were giving the same readings for
the same environments. Thus an Aerocet inter-comparison took place as described in section
3.3.1. This ensured that the relevant corrections could be made to any collected data so that
the measurements taken by each Aerocet could be accurately compared.
5.4 Limitations of Experiment
In this experiment there were a number of key limitations. The most limiting of these factors
were undoubtedly time constraints and instrumentation.
This experiment took place over ten weeks with a significant amount of this time spent on
fixing considerable software issues which existed with the equipment. This greatly reduced
the already little amount of time which was available to collect data. Future experiments
should take place over a sufficient time period which includes a number of contingency days
in order to cater for problems which may arise. Also, in order to develop a cast iron
hypothesis, results should be taken at each desired location for period of weeks if not months.
This would allow one to confidently compare many results against each other so that firm
conclusions can be made.
As for this experiment only two Aerocet particle counters were available for use, a multi-level
vertical pollution profile could not be formed. Instead measurements could only be taken for
two heights simultaneously. Ideally, a minimum of four particle counters would be necessary
in order to take the measurements needed to create a vertical pollution profile which
compared many different heights. This would allow one to accurately quantify how
particulate matter concentration varies at each height increment, thus allowing one to
examine if a possible trend exists.
As particle counters such as the Aerocet 531 do not count every particle in a given volume it
is important to understand that any measurements taken only indicate the PM concentration
for that specific area. In reality, this concentration may vary quite considerably at nearby
locations as particles do not tend to distribute evenly but instead may accumulate inside
turbulent flow, stay in laminar flows, stick to surfaces and rise in warm air. Thus it is very
important that measurements are taken at various locations.
Overall, future experiments should take measurements for at least four different heights
simultaneously over a period of months. This process should be repeated at a number of
different locations in order to examine how results vary. Weather and traffic parameters
should also be monitored in order to see how they too affect the pollution profile of an area.
Ideally, these results should then be used to create a computer simulation in order to
compare further results against.

35
6. Conclusion
To conclude this study, it is clear that the objectives of this experiment were achieved. Both
vertical and building landscape air pollution profiles were successfully determined for the
river and road side of NUIGalway’s Engineering Building with these profiles complimenting
the results of previous studies in this subject area.
In particular, there are a number of conclusions from this experiment which are of notable
interest:
 Road traffic significantly increases the particulate matter concentration of nearby
areas.
 Areas of vegetation increases the particulate matter concentration of regions that are
at the same height level as the vegetation. The converse of this happens for regions
above the vegetation, which sees particulate matter concentrations decrease
significantly.
 Wind speed has a significant influence on the vertical pollution profile of an area
with stronger winds increasing the vertical displacement of particulate matter in
comparison to the vertical displacement caused by weaker winds.
Overall, from the evidence provided in this study, it is clear that for the purposes of indoor
ventilation, air should be ducted in to a building from a third floor height rather than at
ground floor level, on the side of the building which is as far away from roads as possible.
Furthermore, areas of vegetation should be planted beneath the location from which air is to
be ducted.

36
7. References
[1] European Environment Agency. 2014, “Air Quality in Europe- 2014 Report”, Page 14.
[2] Brunekreef, Bert, and Stephen T. Holgate. "Air pollution and health." The
lancet 360.9341 (2002): 1233-1242.
[3] Yu, Ignatius TS, et al. "Evidence of airborne transmission of the severe acute respiratory
syndrome virus." New England Journal of Medicine 350.17 (2004): 1731-1739.
[4] Image courtesy of http://www.urbangreenbluegrids.com/air/
[5] Monn, Christian, and Susanne Becker. "Cytotoxicity and induction of proinflammatory
cytokines from human monocytes exposed to fine (PM 2.5) and coarse particles (PM 10–2.5)
in outdoor and indoor air." Toxicology and applied pharmacology 155.3 (1999): 245-252.
[6] “Emissions of Primary Particles and Secondary Particulate Matter Precursors”. European
Environment Agency. Available at http://www.eea.europa.eu/data-and-
maps/indicators/emissions-of-primary-particles-and-1 . Date Accessed 02/03/2016.
[7] Pandis, Spyros N., et al. "Secondary organic aerosol formation and
transport." Atmospheric Environment. Part A. General Topics 26.13 (1992): 2269-2282.
[8] European Environment Agency, “Air quality in Europe- 2015 report”, Page 20.
[9] World Health Organisation, “WHO Air quality guidelines for particulate matter, ozone,
nitrogen dioxide and sulfur dioxide- Global Update 2005”, Page 8.
[10] Santamouris, Matheos, and Francis Allard. Natural ventilation in buildings: a design
handbook. Earthscan, 1998.
[11] Chan, C. Y., et al. "Characteristics of vertical profiles and sources of PM 2.5, PM 10 and
carbonaceous species in Beijing." Atmospheric Environment39.28 (2005): 5113-5124.
[12] Chan, L. Y., and W. S. Kwok. "Vertical dispersion of suspended particulates in urban area
of Hong Kong." Atmospheric Environment 34.26 (2000): 4403-4412.
[13] Janhäll, Sara, Peter Molnár, and Mattias Hallquist. "Vertical distribution of air pollutants
at the Gustavii Cathedral in Göteborg, Sweden." Atmospheric Environment 37.2 (2003): 209-
217.
[14] Väkevä, M., et al. "Street level versus rooftop concentrations of submicron aerosol
particles and gaseous pollutants in an urban street canyon."Atmospheric Environment 33.9
(1999): 1385-1397.
[15] McKendry, Ian G., Andrew P. Sturman, and Johannes Vergeiner. "Vertical profiles of
particulate matter size distributions during winter domestic burning in Christchurch, New
Zealand." Atmospheric Environment 38.29 (2004): 4805-4813.
[16] Wu, Ye, et al. "Vertical and horizontal profiles of airborne particulate matter near major
roads in Macao, China." Atmospheric Environment 36.31 (2002): 4907-4918.

37
[17] Jo, Wan-Kuen, and Joon-Yeob Lee. "Indoor and outdoor levels of respirable particulates
(PM 10) and carbon monoxide (CO) in high-rise apartment buildings." Atmospheric
Environment 40.32 (2006): 6067-6076.
[18] Jung, Kyung Hwa, et al. "Effects of floor level and building type on residential levels of
outdoor and indoor polycyclic aromatic hydrocarbons, black carbon, and particulate matter
in New York City." Atmosphere 2.2 (2011): 96-109.
[19] Qin, Y.; Kim, E.; Hopke, P. The concentrations and sources of PM2.5 in metropolitan
New York City. Atmos. Environ. 2006, 40, 312–332.
[20] Image courtesy of http://www.metone.com/particulate-aero531.php
[21] PMeasuring, “Basic guide to particle counters and particle counting”. Available at
http://www.pmeasuring.com/wrap/filesApp/BasicGuide/file_1/ver_1317144880/basicguide
.pdf . Date Accessed 19/03/2016.
[22] Image courtesy of http://www.crystalaser.com/laser/laser6.html
[23] Image courtesy of http://www.nuigalway.ie
[24] Zulfacar, Asadullah. "Vegetation and urban environment." Journal of the Urban
Planning and Development Division 101.1 (1975): 21-33.
[25] McPherson, E. G., and D. J. Nowak. "Value of urban greenspace for air quality
improvement: Lincoln Park, Chicago." Arborist News 2.6 (1993): 30-32.
[26] Freer-Smith, Peter. "Air pollution and forests interaction between air contaminants and
forest ecosystems: By William H. Smith. Springer-Verlag, Berlin, 1990. 618 pp. Price: DM198·
00." (1990): 94-95.
[27] Zhou, J., et al. "Particle velocity profiles in a circulating fluidized bed riser of square
cross-section." Chemical Engineering Science 50.2 (1995): 237-244.
Acknowledgements
I would sincerely like to thank the following people for their contribution towards achieving
the objectives of this experiment:
My project supervisor, Dr.Miriam Byrne, for her guidance, support, insight and
encouragement throughout the duration of the experiment.
James Nallen, from NUIGalway’s department of Physics, and Mike Putnam and Troy
Frederickson, from MetOne, for their extensive support in fixing considerable software
issues.
Aodh Dalton and Edward Kilcullen, from NUIGalway’s department of engineering, who were
so facilitating in supervising my use of NUIGalway’s Engineering Building.

38
Appendices
‘Day A- Weather’: Weather conditions for Day A
‘Day B- Weather’: Weather conditions for Day B
Time Temp(°C) Wind
(m/s)
Wind
Dir.
Humidity
(%)
Pressure(
mBar)
Rainfall(
mm)
Solar
Iradiance
(W/m2
)
8:15-9:00 2.5 0.4 SE 83 1021.8 0 138
9-10:00 4.5 0.4 SSE 79 1021.6 0 142
10-11:00 6.4 1.5 SE 78 1021.5 0 168
11-12:00 7 2.6 S 78 1021.3 0 287
12-13:00 7.4 2.7 SSE 76 1020.6 0 380
13-14:00 8.9 3.6 SE 72 1019.9 0 452
14-15:00 6.9 3.8 SE 71 1019.6 0 435
15-16:00 6.9 3.6 S 71 1019.6 0 433
Day A- Weather
Time Temp(°C) Wind
(m/s)
Wind
Dir.
Humidity
(%)
Pressure(
mBar)
Rainfall(
mm)
Solar
Iradiance
(W/m2
)
8:15-9:00 6 5.5 N 80 1010 0 264
9-10:00 6.1 6.4 NNW 80 1009 0 314
10-11:00 7.1 4.7 WNW 78 1011 0 611
11-12:00 7.8 4.6 NNW 76 1012 0 632
12-13:00 8.3 4.2 NNW 69 1012 0 661
13-14:00 8.9 4.1 NNW 67 1012 0 546
14-15:00 8.5 4.3 NNW 71 1012 0 432
15-16:00 8 2.3 WNW 74 997 0 328
Day B- Weather

39
‘Day C- Weather’: Weather conditions for Day C
‘Day D- Weather’: Weather conditions for Day D
Time Temp(°C) Wind
(m/s)
Wind
Dir.
Humidity
(%)
Pressure(
mBar)
Rainfall(
mm)
Solar
Iradiance
(W/m2
)
8:15-9:00 6.5 5.8 SSE 91 1003 0 119
9-10:00 6.6 5.8 SSE 91 1004 0 121
10-11:00 6.9 4.6 NNE 90 1005 0 169
11-12:00 6.9 4.9 NNE 90 1003 0 259
12-13:00 6.8 4.7 NNE 92 1000 0 340
13-14:00 6.5 4.6 NNE 92 998 0 355
14-15:00 7 4.2 WNW 94 998 0.1 128
15-16:00 8 2.3 WNW 74 997 0 328
Day C- Weather
Time Temp(°C) Wind
(m/s)
Wind
Dir.
Humidity
(%)
Pressure(
mBar)
Rainfall(
mm)
Solar
Iradiance
(W/m2
)
8:15-9:00 6.8 3.5 NNW 74 1015 0 294
9-10:00 6.9 3.6 NNW 73 1015 0 317
10-11:00 7.4 2.5 NNE 72 1015 0 495
11-12:00 7.8 3.8 NNW 67 1016 0 621
12-13:00 8.4 4.1 NNW 61 1015 0 588
13-14:00 8.7 4.5 NNW 58 1015 0 533
14-15:00 8.8 5.1 NNW 61 1015 0 196
15-16:00 8.8 3.8 NNW 59 1015 0 121
Day D- Weather

40
Example of Data Summary for Day A and Day B
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Lookup ValuePM1 PM2.5 PM7 PM10 TSP Lookup ValuePM1 PM2.5 PM7 PM10 TSP
8.15-09:00 0 2.3448 4.2232 4.5721 7.2211 8.15-09:00 0.3125 2.25 5.375 6.1875 9.25
9-10:00 2.4 14.566 23.113 22.962 25.346 9-10:00 2.45 8.3 22.45 25.8 26.85
10-11:00 1 10.483 20.655 20.998 23.757 10-11:00 1 5.65 19.1 22.15 23.15
11-12:00 0.1 5.6276 12.593 12.734 14.298 11-12:00 0.05 2.4 9.2 10.55 11.05
12-13:00 0 2.5379 4.6071 5.0801 5.5602 12-13:00 0 0.9 3.4 3.85 3.9
13-14:00 0.05 2.5379 5.4518 5.7575 6.2823 13-14:00 0 0.6 3.4 3.8 3.8
14-15:00 0 0.2207 3.3786 3.3868 3.8272 14-15:00 0 0.25 2.55 3.1 3.2
15-16:00 0 0.1103 2.6875 2.7771 3.1051 15-16:00 0 0.45 2.4 2.75 2.85
Lookup ValuePM1 PM2.5 PM7 PM10 TSP Lookup ValuePM1 PM2.5 PM7 PM10 TSP
8.15-09:00 0.0625 4.2759 6.9107 6.9428 10.11 8.15-09:00 0 3.125 11.313 11.813 12.625
9-10:00 0.15 7.7241 11.902 11.176 12.131 9-10:00 0.15 4.25 11.65 12.15 11.95
10-11:00 0.25 9.1586 14.129 13.276 14.37 10-11:00 0.15 4.9 13.2 13.8 14.05
11-12:00 0.15 9.1586 13.745 12.87 14.009 11-12:00 0.15 4.85 12.35 12.95 13.05
12-13:00 0.1 8.6069 13.591 13.005 13.937 12-13:00 0.05 4.45 11.4 11.8 12.05
13-14:00 0.05 9.3793 14.973 14.292 15.598 13-14:00 0.1 5.15 13.55 14.35 14.5
14-15:00 0.6 11.145 17.046 15.985 17.547 14-15:00 0.3 5.85 15.9 16.65 16.85
15-16:00 0.2 6.6207 10.059 9.8216 12.204 15-16:00 0.8 5.55 11.8 12.35 18.3
G Road DayA Third Road DayA
G Road DayB Third Road DayB

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