mohdruhaizie.commohdruhaizie.com/.../mohdruhaizie_fyp_fullreport.docx · web viewfinal year...

FINAL YEAR PROJECT

PARTICULATE MATTER EXPOSURE COMPARISON IN INSPECTION BAYS AND OFFICES AT IMPORT LANE, SULTAN ABU BAKAR CIQ

COMPLEX, JOHOR

MOHD RUHAIZIE BIN RIYADZI2010282848

HS 223

PARTICULATE MATTER EXPOSURE COMPARISON IN INSPECTION BAYS AND OFFICES AT IMPORT LANE, SULTAN ABU BAKAR CIQ

COMPLEX, JOHOR

MOHD RUHAIZIE BIN RIYADZI

Project paper submitted in partial fulfilment of the

requirements for the award of the Bachelor in

Environmental Health And Safety (Hons.)

Faculty of Health Sciences

JANUARY 2015

Declaration

This project paper entitled “PARTICULATE MATTER EXPOSURE COMPARISON IN INSPECTION BAYS AND OFFICES AT IMPORT LANE, SULTAN ABU BAKAR CIQ COMPLEX” is a presentation of my original work. Wherever contributions of others are involved, every effort is made to indicate this clearly, with due reference to the literature, and acknowledgement of collaborative research and discussions.

This work was done under the guidance of Mr. Megat Azman bin Megat Mokhtar (Project Supervisor) at the Mara University of Technology (UiTM).

(MOHD RUHAIZIE BIN RIYADZI)

In my capacity as supervisor of the candidate’s project, I certify that the above statements are true to the best of my knowledge.

(Megat Azman bin Megat Mokhtar)

Date :

Supervisor’s Signature

Project entitled “PARTICULATE MATTER EXPOSURE COMPARISON IN INSPECTION BAYS AND OFFICES AT IMPORT LANE, SULTAN ABU BAKAR CIQ COMPLEX” was prepared by Mohd Ruhaizie bin Riyadzi and has been submitted to the Faculty of Health Sciences in fulfilment of the requirement for the Bachelor In Environmental Health and Safety (Honours).

Accepted to evaluated by:

………………………………………….

(Megat Azman bin Megat Mokhtar)

Project Supervisor

Date : …………………………………..

ACKNOWLEDGEMENT

I would like to take this opportunity to express my sincere gratitude to all who have contributed in this study.

Alhamdulillahi rabbil alamin... first of all, I would like to deeply praise to Almighty Allah S.W.T. for His blessing and blissfulness for allowing me to complete this report in time and presentably.

It is millions of appreciation to mama Mdm. Ruhani binti Mohamad and abah Mr. Riyadzi bin Ahmad Shah for bringing such a joy in my life via your continuous Doa and positive encouragement.

In particular, I wish to express my sincere appreciation to my supervisor, Mr. Megat Azman bin Megat Mokhtar, for encouragement, support and guidance. I am also very thankful to all lecturers for their advice and recommendation on completing my final project.

Also a lot of thanks to Mr. Rumainor bin Sarif, the Deputy Director of State RMC Gelang Patah and the rest of RMC KSAB workforce especially those in Import Lane during the monitoring conducted for giving this opportunity to be in your daily working experience.

Thank you to Mr. Azali bin Bachok and the rest of Bahagian Pengurusan Hartanah, Jabatan Perdana Menteri (Bangunan Sultan Iskandar) for permit us to enter this restricted facility.

Thank you to the Director of DOSH Johor especially Mr. Kamaruzaman, Mr. Zulfikar and Mr. Redzuan from IH (IAQ) Unit, for not only lends me the equipments but also experiences and knowledge.

ACKNOWLEDGEMENT

Thank you to all friends in District Health Office of Johor Bahru, Port Health Office of Tanjung Pelepas Port, Port Health Office Puteri Harbor and Kompleks Sultan Abu Bakar Health Office especially Senior Assistant Environmental Health Officer Solihan Md. Ali.

Thank you to Team Epjj JB: Nur Adilah & Siti Aishah

Finally, my appreciation and special thanks also goes to my beloved family especially to my wonderful wife and the best friend of my entire life, SITI MASHALIDA BINTI JOHAR for the challenge we’ve faced together, for the support and for the love you give me until now.

My appreciation to Mr. Johar bin Kanchil and Mdm. Suhana binti Tukiran, my parent in-laws and the rest of my family for being very supportive through-out these 4 and half years journey.

I hereby inspire this work to all of my sons

Muhammad Amru Hakim, Ahmad Ariffin Billah & Muhammad Haziq Syafi

It’s a long journey, but no matter where it’s begin, the important is how it ends

15 years, 2 courses, 2 campuses and yet ends with one

Bachelor Degree in Environmental Health & Safety (Honours)

Thank you.

TABLE OF CONTENTS

DECLARATIONS

ACKNOWLEDGEMENT

LIST OF TABLES

LIST OF FIGURE

ABSTRACT

CHAPTER ONE : INTRODUCTION

INTRODUCTION 1

PROBLEM STATEMENT 4

STUDY JUSTIFICATION 5

STUDY OBJECTIVES 5

GENERAL OBJECTIVE 5

SPECIFIC OBJECTIVE 5

HYPOTHESIS 6

CONCEPTUAL FRAMEWORK 7

CONCEPTUAL DEFINITION 8

OPERATIONAL DEFINITION 9

CHAPTER TWO : LITERATURE REVIEW

PARTICULATE MATTER AND HEALTH PROBLEM 11

PARTICULATE MATTER AND RELATIONSHIP WITH VEHICLES 12

CLASSIFICATION OF PARTICULATE MATTER GROUPS 13

EXPOSURES TO PARTICULATE MATTER 14

INDOOR-OUTDOOR EXPOSURES OF PARTICULATE MATTER 15

PREVENTION AND CONTROL METHODS 16

CHAPTER THREE : METHODOLOGY

STUDY LOCATION 19

STUDY DESIGN 20

STUDY VARIABLES 20

INDEPENDENT VARIABLES 20

DEPENDENT VARIABLES 20

CONFOUNDING VARIABLES 21

SAMPLING AND DATA COLLECTION 21

INSTRUMENTATION 24

DATA ANALYSIS 25

STUDY LIMITATION 25

CHAPTER FOUR : RESULT

RESULT REGARDING SPECIFIC OBJECTIVE (1): TO MEASURE AIR

QUALITY PARAMETERS IN OUTDOOR AND INDOOR SETTINGS

26

PARTICULATE MATTER WITH DIAMETER SIZE OF 10 MICRONS

AND SMALLER (PM10)

26


AND SMALLER (PM4)

31

PARTICULATE MATTER WITH DIAMETER SIZE OF 2.5 MICRONS

AND SMALLER (PM2.5)

33


AND SMALLER (PM1)

35

TOTAL PARTICULATE MATTER (PMTOTAL) 37

TOTAL VOLATILE ORGANIC COMPOUND (TVOC) 39

CARBON DIOXIDE (CO2) 42

OZONE (O3) 44

CARBON MONOXIDE (CO) 47

AIR TEMPERATURE (AT) 49

RELATIVE HUMIDITY PERCENTAGE (%RH) 51

AIR VELOCITY 53

CONCLUSION FOR THE RESULT OF SPECIFIC OBJECTIVE (1) 54

RESULT REGARDING SPECIFIC OBJECTIVE (2): TO COMPARE THE

PARTICULATE MATTERS CONCENTRATION BETWEEN THE

OUTDOOR AND INDOOR SETTINGS

56

CONCLUSION FOR THE RESULT OF SPECIFIC OBJECTIVE (2) 59

RESULT REGARDING SPECIFIC OBJECTIVE (3): TO IDENTITY THE

RELATIONSHIP BETWEEN PARTICULATE MATTER AND OTHER

PARAMETERS IN THE OUTDOOR AND IN THE INDOOR SETTINGS

61

RESULT REGARDING SPECIFIC OBJECTIVE (4): TO CALCULATE

PARTICULATE MATTER INDOOR-OUTDOOR (I/O) RATIO

63

CHAPTER FIVE: DISCUSSION 68

INDOOR-OUTDOOR (I/O) RATIO 72

COMPARING DATA WITH LEGAL REQUIREMENTS AND STANDARDS 73

CHAPTER SIX: RECOMMENDATION AND CONCLUSION 76

REGARDING THE VEHICLE 76

REGARDING THE BUILDING 77

REGARDING THE PEOPLE 79

CONCLUSION 80

REFERENCES 81

APPENDICES 86

LIST OF TABLES

Table 3-1 Sampling location in Import Lane, KSAB

Table 3-2 Sampling location sequence within three days of study conducted in

Import Lane, KSAB

Table 4-1 Results for each day TWA8hrs and TWA24hrs calculation from the PM10

concentration data obtained in Figure 4-1, and comparison with ICOP

IAQ 2010 and MAAQG, respectively.

Table 4-2 Results for each day TWA8hrs calculation from the TVOC

concentration data obtained in Figure 4-11, and comparison with

ICOP IAQ 2010

Table 4-3 Results for each day TWA8hrs calculation from the CO2 concentration

data obtained in Figure 4-13, and comparison with ICOP IAQ 2010

Table 4-4 Results for each day TWA8hrs calculation from the ozone

concentration data obtained in Figure 4-15, and comparison with

ICOP IAQ 2010 and MAAQG, respectively.

Table 4-5 Results for each day TWA8hrs calculation from the CO concentration


and MAAQG, respectively.

Table 4-6 Output results for descriptive statistics after analysis of Kruskal-Wallis

Non-Parametric Test (K-Independent Sample) has been run in SPSS.

Table 4-7 Output results for the Mean Rank

Table 4-8 Output results for the Test Statistics (Chi-Square, X2)

Table 4-9 Output results for the Frequency

Table 4-10 Output results for the Test Statistics (median)

Table 4-11 Spearman’s correlation output results. The table is been simplified to

fit the page

Table 4-12 Descriptive statistics output when the concentration of particulate

matter is separated in specific location settings with N=13 for each

setting

LIST OF FIGURES

Figure 1-1 Air Pollution Index used by Department of Environment Malaysia

Figure 1-2 Air Pollution Index in Johor in year 2013

Figure 1-3 Print-screen from GoogleMaps of a satellite view showing the location

of KSAB. Note: the light-orange lines is SecondLink Highway which

connecting Malaysia (to the left, upward) and Singapore (to the right,

downward).

Figure 1-4 Conceptual Framework


of KSAB (marked with the red downward arrow)

Figure 3-2 Import Lane of KSAB, consist inspection bay and offices

Figure 4-1 30-minutes averages PM10 concentration at different location within 3

days of study (upper horizontal redline: acceptable upper limit: 0.15

mg/m3, TWA8hrs (ICOP IAQ 2010, DOSH); 150 µg/m3, TWA24hrs

(MAAQG, DOE))

Figure 4-2 (Left) Histogram of the data distribution and normality curve; (Right)

Descriptive statistics table for PM10

Figure 4-3 30-minutes averaged PM4 concentration at different location within 3

days of study



Figure 4-5 30-minutes averaged PM2.5 concentration at different location within 3

days of study


Descriptive statistics table for PM2.5


days of study



Figure 4-9 30-minutes averaged PMTOTAL concentration at different location within

3 days of study


Descriptive statistics table for PMTOTAL

Figure 4-11 30-minutes averaged TVOC concentration at different location within

3 days of study (the horizontal redline: acceptable upper limit: 3 ppm,

TWA8hrs (ICOP IAQ 2010, DOSH))


Descriptive statistics table for TVOC

Figure 4-13 30-minutes averaged CO2 concentration at different location within 3

days of study (the horizontal redline: acceptable upper limit: C1000

ppm, TWA8hrs (ICOP IAQ 2010, DOSH))


Descriptive statistics table for carbon dioxide

Figure 4-15 30-minutes averaged ozone concentration at different location within

3 days of study (upper horizontal redline: acceptable upper limit: 0.05

ppm, TWA8hrs (ICOP IAQ 2010, DOSH); 0.06 ppm, TWA8hrs (MAAQG,

DOE))

Figure 4-16 Figure 4-16 (Left) Histogram of the data distribution and normality

curve; (Right) Descriptive statistics table for ozone

Figure 4-17 30-minutes averaged carbon monoxide concentration at different

location within 3 days of study (the horizontal redline: acceptable

upper limit: 10.0 ppm, TWA8hrs (ICOP IAQ 2010, DOSH); the

horizontal purple line 9.0 ppm, TWA8hrs (MAAQG, DOE))


Descriptive statistics table for carbon monoxide

Figure 4-19 30-minutes averaged air temperature at different location within 3

days of study (the horizontal redline: acceptable range: 23.0 ⁰C –

26.0 ⁰C, (ICOP IAQ 2010, DOSH))


Descriptive statistics table for air temperature

Figure 4-21 30-minutes averaged relative humidity percentage at different location

within 3 days of study (the horizontal redline: acceptable range: 40 %

– 70 % (ICOP IAQ 2010, DOSH))

Figure 4-22 (Left) Histogram of the %RH data distribution and normality curve;

(Right) Descriptive statistics table for %RH

Figure 4-23 30-minutes averaged air velocity at different location within 3 days of

study (the horizontal redline: acceptable range: 0.15 m/s – 0.50 m/s

(ICOP IAQ 2010, DOSH))

Figure 4-24 (Left) Histogram of the air velocity data distribution and normality

curve; (Right) Descriptive statistics table for air velocity

ABSTRACT

In Sultan Abu Bakar CIQ Complex (KSAB), Johor, Royal Malaysia Customs (RMC)

and other government agencies (OGA) officers are placed in offices building next to

the inspection bays in either Import Lane or Export Lane. They’re facing hustle bustle

traffic of heavy-duty carriers (HDC), which most of them using diesel as fuel,

everyday. HDC especially the one using diesel is commonly known as the major

contributor to the particulate matter pollutions globally. A study has been conducted

in 3 days in Import Lane, involving 26 sampling locations (13 outdoors, 13 indoors),

generally to compare the concentration of PM indoor and outdoor, using TSI®

DustTrakTM DRX handheld device. For other air quality parameters, HP iPAQ 2010

Pocket PC is used to log data which is monitored using GrayWolf® DirectSense® IQ-

610 Indoor Air Quality Probe and AS-210 Telescoping Hotwire Probe. Each

measurement is done in 30-minutes with data logged every 2 minutes. Data obtained

is analysed using Mircosoft Excel 2010 for graph manipulation and IBM SPSS 16.0

statistic analysis. During peak hour, the concentration of PM (all type) is increased.

There is no statistically significant difference between concentration of PM indoor and

outdoor (p > 0.005), where the I/O ratio is ranged between 0.748 (PM10) and 0.795

(PM1), where as diameter of particles getting smaller, the I/O ratio become higher. In

this study, Spearman’s Correlation Test found that air temperature has significant

relationship with PM with strong, positive correlation (p < 0.001). For mitigation

measures, it is suggested administrative approaches is used against the HDC itself,

and combination of strategies as stipulated by Maroni (1998) against the buildings

environment. Air curtain is suggested to be used as air shield to hold pollutants in the

outdoor entering indoor environment.

Keyword: particulate matter, indoor settings, offices, outdoor environment, inspection

bay, heavy-duty carriers, entry-point enforcement workforce

ABSTRAK

Di Kompleks KIK Sultan Abu Bakar (KSAB), Johor, pegawai-pegawai Jabatan

Kastam Diraja Malaysia dan lain-lain agensi kerajaan (OGA) ditempatkan di

bangunan pejabat bersebelahan dengan ruang pemeriksaan, sama ada di laluan

import ataupun laluan eksport. Mereka berhadapan dengan kesibukan trafik

kenderaan-kenderaan berat yang kebanyakkannya menggunakan diesel sebagai

bahan bakar, yang diketahui menyebabkan pencemaran partikel secara global.

Kajian dijalankan selama 3 hari di laluan import, melibatkan 26 lokasi persampelan

(13 lokasi luaran, 13 lokasi dalaman), secara umumnya untuk membandingkan

konsentrasi partikel dalam udara luaran dan dalaman, menggunakan TSI®

DustTrakTM DRX, manakala untuk lain-lain parameter menggunakan HP iPAQ 2010

Pocket PC yang melog data dari GrayWolf® DirectSense® IQ-610 Indoor Air Quality

Probe dan AS-210 Telescoping Hotwire Probe. Setiap pengukuran dilakukan dalam

tempoh 30-minit dengan data dilog setiap 2 minit. Data yang diperolehi dianalisa

menggunakan Mircosoft Excel 2010 untuk manipulasi graf dan IBM SPSS 16.0 untuk

analisa statistik. Ketika waktu puncak, konsentrasi partikel (semua jenis) adalah

meningkat. Tiada perbezaan statistic yang signifikan dikenas antara konsentrasi

partikel dalam udara luaran dan dalaman (p > 0.005), dengan nisbah I/O di antara

0.748 (PM10) dan 0.795 (PM1), di mana semakin kecil saiz diameter partikel, nisbah

I/O semakin meningkat. Dalam kajian ini, Spearman’s Correlation Test menunjukkan

suhu udara mempunyai korelasi signifikan yang kuat dan positif dengan PM (p <

0.001). Sebagai langkah mengatasi masalah, dicadangkan pendekatan

administrative digunakan ke atas isu kenderaan berat dan kombinasi strategi

sebagaimana yang dicadangkan oleh Maroni (1998) untuk mengatasi masalah

berkaitan bangunan. “Air curtain” adalah dicadangkan untuk digunakan sebagai

perisai udara untuk menghalang kemasukan bahan cemar dari luar ke persekitaran

dalaman.

Keyword: particulate matter, indoor settings, offices, outdoor environment, inspection

bay, heavy-duty carriers, entry-point enforcement workforce

CHAPTER ONE

INTRODUCTION

Clean and fresh air to breathe has been concern since several decades ago. It’s even

a requirement as stipulate in the ancient yoga proverb “for breathe is life, and those

who breathe well, live longer”. Although this proverb is meant for the better breathing

techniques, it will be useless when someone breathe well, but breathe in unclean air.

Air is one of the medium used by pollutants and pathogens to enter human body

through route of entry known as inhalation. According to World Health Organization,

one of the environmental health risks is air pollution which is related to the

emergence of respiratory problem such as acute respiratory diseases including

asthma, allergy and irritation, strokes, lung cancer etc.

According to Ministry of Health Malaysia (2013), among ten principal causes of

hospitalization in Ministry of Health Hospital and private hospital in 2012, disease of

the respiratory system is ranked as second (12.08%). Disease of the respiratory

system is also ranked at the same spot among ten principal causes of death in

Ministry of Health Hospital and private hospital in 2012 (17.90%). Diseases of

respiratory problems are including lung cancer, breathing problem, sore throat and

irritating, influenza, tuberculosis etc. Most of the chronic disease related to the

respiratory are mostly due to breathing the unhealthy air (air pollution) as well as

unhealthy lifestyle including smoking.

Air pollution index (API) is set by Department of Environment Malaysia as the

indicator to evaluate how cleaness the ambient air everyday. The components that

formed the API are carbon monoxide (CO), ozone (O3), nitrogen dioxide (NO2) and

sulfur dioxide (SO2) and particulate matter (PM10). The indication of API is as follows:

API Air Pollution Level

0 - 50 Good

51 - 100 Moderate

101 - 200 Unhealthy

201 - 300 Very unhealthy

301 - 500 Hazardous

500+ Emergency

Figure 1-1 Air Pollution Index used by Department of Environment Malaysia

In Johor, there are four sampling stations to measure daily the volume of pollutant in

the air. These stations are located in Kota Tinggi, Larkin Lama (Johor Bahru), Muar

and Pasir Gudang (Johor Bahru). The API for Johor in year 2013 is as in Figure 1-2

above. In Larkin Lama which is closed to the centre and western region of Johor

Bahru, API for 300 days appears to be in “Good” conditions (API 0 – 50), while the

other 65 days, the API is “Unhealthy” (API 101 – 200).

Figure 1-2 Air Pollution Index in Johor in year 2013

One of the government facility located in western region of the Johor Bahru is Sultan

Abu Bakar Custom, Imigration & Quarantine (CIQ) Complex (abbreviate: KSAB)

(GPS: 1.377738, 103.599140). It’s a ground crossing checkpoint facility that play role

in controlling travellers and conveyances at the country border which connecting

Malaysia and Singapore through a highway route known as SecondLink (E3), which

is also managed by PLUS Berhad, instead of PLUS Highway (E2) itself.


of KSAB. Note: the light-orange lines is SecondLink Highway which

connecting Malaysia (to the left, upward) and Singapore (to the right,

downward).

According to the Properties Management Division, Prime Minister Department of

Malaysia, this border control facility is designed to accept a maximum of 200,000

vehicles daily, which 25% to 35% of the vehicles are estimated as heavy duty

carriers. The number of heavy duty carriers may reachs up to 40% of the total

number of vehicles in Friday, as it is the last weekday for official business hour in

Singapore.

All heavy duty carriers must be inspected for goods or consignments they’re carrying

either for importation to Malaysia purpose or exportation to Singapore purpose. The

inspection process including declaration of the goods carried, physical and sampling

examination by Royal Malaysia Customs (RMC) or other government agencies

(OGA), sealing of the conveyance cover and consignment released.

Problem Statement

Several RMC and OGA (such as Department of Health, Department of

Pharmaceutical Enforcement, Malaysian Quarantine and Inspection Services

(MAQIS) (a governmental body formed by combination of departments under Ministry

of Agriculture and Agro-Based Industry (MOA)) and Department of Wildlife Protection

etc.) offices is placed near to the inspection bays either in Import Lane or Export Lane

in KSAB. This is to ease the forwarding agents, importer or exporter representative as

well as officers from both RMC and OGA in declaring the consigment, conducting

examination and approving either exportation or importation.

As the offices is placed near the inspection bays, occupants inside may be exposed

themselves to the unclean and unhealthy air as well as noise which penetrated from

the outside. The exposure may be greater especially when they’re out to the

inspection bay. This unclean and unhealthy air may penetrate to the indoor settings

of these office thus affected the indoor air quality.

According to Brugge (2007), heavy weight carriers such as trucks are potentially

emitted higher concentration of pollutants compared to the light weight vehicles such

as cars, thus make it significant source of urban air contamination now days. As

nearer as someone to the source of contamination, the higher volume of exposure

will she or he get

This condition, sooner or later, may affecting the health of the exposed person

(Moller, 2014).

Study Justification

Department of Health in KSAB has undergone an assessment and evaluation by the

representative of International Health Sector, Disease Control Division, Ministry of

Health Malaysia in year 2012 in fulfilling the requirement of establishing core

capacities as stipulated in Annex 1 B of International Health Regulations (IHR) 2005.

One of the requirement is to ensure the travellers as well as workforce in entry point

is in clean and healthy environment, both in outdoor and indoor settings.

However, until today, the Indoor Air Quality Assessment haven’t been done, thus

there is no clue how does the working environment status in KSAB for both outdoor

and indoor settings.

Therefore, this study may help the governmental agencies including to understand

the level of exposure of air quality parameters especially particulate matter

concentrations faced by the officers, staffs and other people who have business

matter regarding with importation and exportation of consignments.

Study Objectives

(1) General Objective

To compare the exposures of particulate matter in the outdoor (inspection

bays) and in the indoor settings (offices) at Import Lane, Sultan Abu Bakar

CIQ Complex.

(2) Specific Objectives

a. To measure air quality parameters in outdoor and indoor settings

(PM10, PM4, PM2.5, PM1, PMTOTAL, TVOC, CO2, O3, CO, relative

humidity, air temperature and air velocity)

b. To compare particulate matter concentrations between the outdoor

and the indoor settings

c. To identify the relationship between particulate matter and other

parameters in the outdoor and in the indoor settings

d. To calculate the particulate matter indoor-outdoor (I/O) ratio

Study Hypothesis

(1) For specific objective (2) above, there will be no statistical significant

difference between particulate matter concentration in the outdoor and in

the indoor settings

(2) For specific objective (3) above, concentration of particulate matter may be

influenced with other air quality parameters in both outdoor and indoor

settings; and

(3) For specific objective (4) above, for overall, the concentration of particulate

matter in the outdoor may be greater than the particulate matter

concentration indoor.

Conceptual Framework

Figure 1-4 Conceptual Framework

Conceptual Defination

(1) Air pollution

As air is around everywhere and everytime, it is the most suitable medium

for pathogens and pollutants to caused adverse effect either on the health of

human, animal or even crops, but also built environment. In KSAB, officers

and other people works or have business matter within it compound as well

as travellers faced the exposure of variety of air pollutants either in the

indoor setting or the outdoor environment.

(2) Souce of air pollution

Commonly known, source of pollution can be either natural or

anthropogenic. In every of the sources, it can be categorised into two:

stationary source of mobile source. In KSAB, the major air pollution source

is due to the vehicles which crossed the terminal, where it is estimated

about this entry point facility can hold for about 200,000 maximum number

of vehicles daily. 25 – 35% or even 40% of these number of vehicles is

heavy duty carrier or heavy weight vehicles which play on important role in

import export industries across the land.

(3) Regulatory standards

For the ambient air pollution, the concentration of pollutants is measured

and then compared with Malaysia Ambient Air Quality Guidelines published

b y Department of Environment Malaysia. The parameters are ozone,

carbon monoxide, nitrogen oxides, sulfur dioxide, total suspended particles,

particulater matter (PM10) and lead, with the measurement period should be,

or equivalent to, ranged from 1 hour to 12 months. For indoor air quality, the

concentration of pollutants is measured and then compared with Malaysia

Ambient Air Quality Guidelines published b y Department of Environment

Malaysia. The parameters are ozone, carbon monoxide, carbon dioxide,

particulater matter (PM10) formaldehyde, total volatile organic compounds,

microbological contaminants (bacteria and fungi) and several physical

parameters (air velocity, air temperature and relative humidity), with the

measurement period should be, or equivalent to 8 hours.

Operational defination

(1) Heavy duty carrier or heavy weight vehicle

A vehicle used to carry importation or exportation purposed consignment

across the terminal either to Singapore or to Malaysia. The vehicle is

permitted to only driven through the designated lane (Importat Lane or

Exported Lane) and must not carry human. Every vehicle that enter the

inspection bay either just to crossed it to the exit route or parked in it or

surround it while the declaration of consignment have been made until

importation or exportation is permitted is count as 1, regardless the period

the vehicle stay in the inspection bay or surround it, either the engine in idle

mode or switched off.

(2) Measurement of outdoor environment

The measurement of outdoor environment must only be made under the

roof of the inspection bay although the facility is open to the ambient air (no

walls), but not to closed to the pillar and regardless to any vehicle parked

nearby. Measurement must be made in-situ where the average data is

obtained once the period of measurement is done per each location.

(3) Measurement of indoor settings

The measurement of outdoor environment must only be made inside the

office which is opposite right to the sampling location chosen and used for

the outdoor environment monitoring. The measurement must be made

starting within the interval 5 minutes after the end of each outdoor

environment. At each indoor location, instrument must be made in the

centre of the given space. Measurement must be made in-situ where the

average data is obtained once the period of measurement is done per each

location.

CHAPTER TWO

LITERATURE REVIEW

Particulate matter and health problem

In many literatures reviewed, particulate matter has been a focus and concern among

health environmentalists and occupational safety & health practitioners since

decades regarding air pollution issue.

According to World Health Organization and United States Environmental Protection

Agency, among six major air pollutants, particulate matter with diameter size of 10

micrometers or lesser has potentially harming human health with the association in

lung cancer, respiratory tract problem/disease, cardiovascular disease, asthma, and

premature death which is linked to the air pollution. The latest study by Moller et al

(2014) linked the latest concern among particulate matters, the ultrafine particulate

matter (particulate diameter size is less than 100nm or 0.1 microns, abbreviated as

UFP) with cardiovascular disease and lung cancer. According to Janssen et al

(2001), children who attending school near the motorway sometimes has been

brought to pay a visit in the emergency section in health care facilities/hospital due to

the exposure of fine particulate matter (diameter size 2.5 microns or less).

Among six WHO Regional Office worldwide, Western Pacific Regional Office (WPRO)

and South East Asia Regional Office (SEARO) faces the greatest challenges as

health impact due to air pollutants exposure become the greatest burden in the most

low and middle income countries in under both WHO entities supervision. Malaysia

and Singapore are among State Parties in WPRO.

Particulate matter and relationship with vehicle

As more study has been conducted, it is clear that transportation industry is the main,

important and significant sources for particulate matter pollution globally. According to

Weijers et al (2004), the increasing degree of urbanization which one of the indicators

is the increasing degree of development and number of industries as well as

transportation services and degree of traffic condition have a strong, positive

correlation with particulate matter pollution now days.

Among varieties of vehicle type, heavy duty carriers, also termed as heavy weight

vehicles or heavy diesel driven vehicle due most of this vehicle type fuelled by diesel

for power to move, are identified to be the major contributor to particulate matter,

nitrogen oxides and sulphur dioxide as well as carbon monoxide and tropospheric

ozone emission to the outdoor environment (Clark et al, 1999; Naeher et al, 2000;

Colvile et al, 2001; Charron et al, 2005; Brugge et al, 2007; Sheesley et al, 2008; &

Garshick et al, 2012).

Classification of particulate matter groups

U.S. EPA was firstly determined particulates which the size of 10 microns and smaller

as inhalable particles. Then, several researches determine that there variety of

particles size. According to Estokova and Stevulova (2012), particulate matter is

classified into several groups as accordance to their diameter size (particle size

distribution).

Inhalable particle is particulate matter with the diameter size of 10 and lesser. The

symbol used for this group of particle is PM10. It is also known as aerosol particulate.

This small size is an advantage to the particles to deposit in the deepest part of the

lungs (bronchioles and alveoli) (U.S. EPA). Another group is respirable particle, with

diameter of 4 microns or smaller, abbreviated with the symbol PM4.

Coarse particle is an identification of a group of particulate matter which have

diameter size larger than fine particles but smaller than inhalable particles (range

from > 2.5 μm to ≤ 10.0 μm) (Estokova and Stevulova, 2012).

Particle with diameter size of 2.5 and lesser is known as fine particulate, symbolised

with PM2.5. It can penetrate deeper up to alveolus, the gas exchange region in the

lung thus disturbing the process. According to Grau-Bove and Strlic (2013), PM2.5 is a

good indicator of the amount of anthropogenic particulate pollutants in urban ambient.

It has significant correlation with nitrogen oxides in emitted from vehicular exhaust

(Gillies et al, 2001). Another type of particle which is categorised as fine particles is

PM1 (diameter size of 1 micron or less), which is mostly originated from combustion

process and have high content of inorganic carbon compound.

Today, the smallest fraction of particulate matter is known as ultrafine particles (UFP).

It has a diameter size of 0.1 microns (100 nanometre) or less. The characteristic of

UFP such as high alveolar deposition fraction, insolubility, large surface area and

toxic constituents has ability to pass through cell membranes into the blood vessel,

migrate into other vital organ including the brain. UFP can carry carcinogens by

absorbing in it surface then deposit it at the destination organ (Moller, 2014).

Exposures to particulate matter

Higher concentration of particulate matter can be found as emission of vehicular

exhaust (higher in diesel driven heavy weight vehicle compared to the light weight

vehicle), as well as emission from industries, during traffic congestion and as a result

from re-suspension of roadside dust (Wahlina et al, 2001; Gillies et al, 2001; Marr et

al, 2004; Charron et al, 2005; Jones & Harrison, 2006; Brugge et al, 2007; Kaur et al,

2007; Sheesly et al, 2008; Thorpe & Harrison, 2008; Yu-Hsiang et al, 2012).

According to Weijers et al (2004), air movement and direction have significant

relationship with particulate matter exposure. People who live or at the downwind

level from the roadside (including highway) have exposed to more than 40% higher in

particulate matter concentration compared to those who lives in the busy urban

environment.

Indoor-outdoor exposure of particulate matter

According to WHO, indoor air quality is associates with the quality of the ambient air.

According to Lawrence et al (2004), the level of carbon monoxide concentration in

indoor settings has positive correlation with the outdoor concentration of carbon

monoxide. He suggests that there are no statistical significant differences between

both settings. Meanwhile, there is strong, positive correlation between particulate

matter and carbon monoxide (Kaur et al, 2007). Therefore, it is obvious that the

pollutants from outdoor may contaminate the indoor condition.

According to Chun & Bin (2011), pollutants from the outdoor enter the indoor

environment through several ways including direct entrance through any opening, or

through penetration in the wall cracks or leaks of infiltration through smaller gap

between joint and fixture of wall, ceiling etc. There are three parameters to determine

the relationship between indoor and outdoor concentration of particles: (1) I/O ratio;

(2) infiltration factor; and (3) penetration factor.

According to Grau-Bove & Strlic (2013), I/O ratio is widely used to describe the

condition between both settings. In their study they found that, due the aerodynamic

properties of the particulate matter based on their size, particulate matter with smaller

size will have higher I/O ratio. This also can be concluded that, when coming from the

same source, concentration of particulate matter with smaller diameter size are

higher in indoor setting compared to the larger diameter sized of particulate matter.

Prevention and control methods

Maroni (1998) suggest two main strategies which needs to be combined to achieved

indoor air quality control and improvement: (1) the built structure (the building itself)

needs to be designed and constructed properly; and (2) indoor air pollutants must be

controlled using one or combination of methods either control the source, having

adequate ventilation, cleaning the air or control the exposure group.

According to Kaur et al (2007), the best way to prevent and control the exposure of

air pollution is by avoiding the source that emitted it, such as avoid from being nearer

the construction area. However this seems impossible to be done in the area where

heavy vehicle is compulsory.

According to Bailey & Solomon (2004), in the seaport environment where not only

vessel emit the air pollutants but also the ground vehicle such as prime mover (PM)

or rubber tyre gantry (RTG), the mitigation measure should account wide range of

possibilities from the existing and cheaper to the investment and costly-required

control measures. They take an example of restricting all prime mover drivers from

idling or to switch off the haulier engine while stopping at designated parking area or

while waiting the order and to use low sulphur content of the diesel.

Wiejers et al (2014) suggest an air bending device to be install. As pollutants

movement is based on the wind direction and velocity, air bending device will divert

the pathway of the pollutant. Example of air bending device is suction pipe which is

suggested to be installed on the road surface where the lower pressure inside the

suction pipe will attract wind direction to it thus it can channel the pollutant to the area

where it exposure may not be significantly adverse to other around. More example of

air bending device is air curtain. Air curtain is mostly used in vector control program.

However the same principle may be applied in air quality control, where the higher

velocity of the air flown down shielding any opening from being penetrated or

infiltrated by lower air velocity from the proportioned direction.

More than that, in a regularly closed room where the number of door and window

opening activity is seldom occurred, the room may be sure to have a positive

pressure inside by promoting good ventilation and higher frequency of air change.

According to WHO, several preventive and control measures can be applied in air

quality control as follow:

1) Licensing source of emission. Before the license could be granted, the emitter

needs to be evaluated for the compliances toward cleaner air standard.

Emitter may not only require installing devices such as catalytic converter to

reduce carbon monoxide emission in exhaust system, but to ensure the

regular maintenance and self-monitoring. Based polluter pay policy and on the

data gathered through licensing activity, emitter may require paying tax on fuel

and carbon.

2) Where the place is suitable, the restriction of smoking in designated non-

smoking area need to be regulated as a law requirement and enforced to

uphold it.

3) The policy for regularly monitoring and control the indoor air quality standard

need to be applied as soon as possible. Currently, several country has already

regulate their own set of guideline regarding indoor air quality as to ensure

good practices regarding occupational safety, health and hygiene, but it is just

as a role of guideline. Once regulated as legislative document, it can be

enforced for better air to breathe in indoor setting.

4) Shifting to cleaner heavy duty vehicles and low-emission vehicle and fuels,

reduced sulphur content in the fuel.

5) More than that, a regulation needs to be setting up to require all vehicles,

especially heavy duty vehicle to turn off the engine once stop at any

designated parking.

CHAPTER THREE

METHODOLOGY

Study Location

KSAB is located in Bukit Kucing, Mukim Tanjung Kupang, at the western region of

Johor Bahru District, which is about 15 kilometres from Gelang Patah Town; 25

kilometres from Johor State New Administrative Centre (JSNAC) in Kota Iskandar,

Nusajaya; 40 kilometres from the centre of Johor Bahru metropolitan; and 50

kilometres from the Senai Airport. The GPS coordinate is 1.378066, 103.599218.


of KSAB (marked with the red downward arrow)

This complex can be accessed via the inner route of Jalan Tanjung Kupang – Gelang

Patah or via SecondLink Highway (E3). However, as this complex is restricted area,

the entrance connected with the inner route can only be accessed by authorised

personnel.

Historically, this complex and SecondLink Highway was officially opened in January

2, 1998 to ease the traffic problems between Malaysia and Singapore at Tanjung

Puteri CIQ Complex (Johor Causeway). It’s a new link between Malaysia (at

Kampung Tanjung Kupang) and Singapore (at Tuas). The opening ceremony was

officiated by Prime Minister of Malaysia at that time, Datuk Seri Dr. Mahathir

Mohamad (now Tun).

Study Design

This is a cross-sectional study in which the data is collected from several samples at

one point in time and then by comparing the difference between characteristic found

in all samples, a conclusion is made of (Leslie G.P. and Mary P.W., 2009).

Study Variables

(1) Independent Variable

a. Location of the sampling point either in the outdoor environment or in

the indoor settings

b. Days either it is on Singapore’s weekdays (working days) and

weekends (non-working days).

(2) Dependent Variable

a. In-situ parameters of ambient air quality and indoor air quality:

i. Particulate matters (PM10, PM4, PM2.5, PM1 & PMTOTAL)

ii. Carbon dioxide (CO2)

iii. Carbon monoxide (CO)

iv. Ozone (O3)

v. Total volatile organic compound (TVOC)

vi. Air temperature

vii. Air velocity

viii. Relative humidity

(3) Confounding Variable

a. Number of vehicle, other than heavy weight vehicle, used by the officers

and agents, crossing the study location.

b. Number of people and their activities near the measurement instrument

c. The condition of mechanical ventilation air conditioning (MVAC) system,

either cleaned or not, functioning or switches off etc.

d. The environmental influences such as weather, ambient dust etc.

Sampling and data collection

(1) There are 10 sampling locations which were visited during this study, which 5

are in the outdoor environment (inspection bays) and another five in the

indoor-settings (offices).

(2) All probes are set to be at the same height as breathing area in sitting

position (approximately 1 metre height from the floor level).

(3) Each sampling is done for average 30-minutes (grab sampling techniques,

ICOP IAQ 2010 - Methodology) at each sampling location where the duration

of sampling is set for 30-minutes, with data is logged for every 2 minutes and

time constant is 3 seconds.

(4) Prior to each sampling, TSI DustTrak DRX is set to zero calibration using

Zero Filter. Other instrument is already under factory calibration (1 year

period) with new calibration date is on July 2015.

(5) The data log is downloaded into the computer for analysis using TSI®

TrakProTM Software for particulate matter concentration

(6) The analysis is done using SPSS Version 16.0 for statistical analysis and

Mircosoft Office 2010 for graph manipulation.

Location remark Name of the location Position

AAt the pillar, between Bay 04 and Bay 05 OutdoorIn the office of Unit Taksiran Kastam Import Indoor

BAt the pillar, between Bay 06 and Bay 07 OutdoorIn the office of Kaunter Pemeriksaan Kastam Import Indoor

CAt the pillar, between Bay 08 and Bay 09 OutdoorIn the office of Kaunter Juruwang Kastam Import Indoor

DAt the pillar, between Bay 10 and Bay 11 OutdoorIn the office of Bilik Sisihan Borang Kastam Import Indoor

EAt the pillar, between Bay 12 and Bay 13 OutdoorIn the office of Urusetia Kastam Import, Seksyen Jaminan Bank Indoor

Table 3-1 Sampling location in Import Lane, KSAB

Date Time Starts Location Sequence

04/12/201410.30 am E12.14 pm A1.43 pm E

05/12/2014

8.52 am A10.14 am C11.36 am A5.02 pm D6.22 pm B7.40 pm A

07/12/2014

8.58 am D10.20 am A6.04 pm D7.50 pm A

Table 3-2 Sampling location sequence within three days of study conducted in

Import Lane, KSAB

Figure 3-2 Import Lane of KSAB, consist inspection bay and offices

EDCB

A

A

Instrumentation

(1) TSI® DustTrakTM DRX model 8534 (handheld) with Zero Filter

(2) HP iPAQ 210 Pocket PC

(3) GrayWolf® DirectSense® IQ-610 Indoor Air Quality Probe

(4) GrayWolf® DirectSense® AS-201 Telescoping Hotwire Probe

(5) Tripod or Moveable Cabinet

(6) TSI® TrakProTM Software

(7) Microsoft Excel 2010

(8) IBM SPSS 16.0

(9) Equipment & What-to-do Checklist

(10) Simple Interview Question Checklist

(11) Camera

(12) Extension Wire and Power Source

(13) Alkaline Batteries

Data Analysis

(1) Graph manipulation – Microsoft Excel 2010

(2) Statistical analysis – IBM SPSS 16.0

Study Limitation

(1) Time limitation for to get the equipment, study execution (short time permission

given), analysis and report writing

(2) Monitoring equipment limitation: only managed to get a set of instrument, does

limit the simultaneously reading.

CHAPTER FOUR

RESULT

Result regarding specific objective (1) of this study: to measure air quality

parameters in outdoor and indoor settings (particulate matter (PM10, PM4, PM2.5,

PM1 and PMTOTAL), total volatile organic compounds (TVOCs), carbon dioxide

(CO2), carbon monoxide (CO), ozone (O3), relative humidity percentage (%RH),

air temperature (AT) and air velocity (AV))

Particulate Matter with diameter size of 10 micron and smaller (PM10)

Figure 4-1 30-minutes averages PM10 concentration at different location within 3


mg/m3, TWA8hrs (ICOP IAQ 2010, DOSH); 150 µg/m3, TWA24hrs

(MAAQG, DOE))

Figure 4-1 above shows the concentration of particulate matter (PM10) where each is

30-minutes measurement averaged in the outdoor (green bar) and in the indoor

settings (blue-black bar). Among all data captured, measurement done between

December 5, 2014 on 5.00 pm until 8.49 pm in the same day returned the highest

concentration compared to others, in both outdoor and indoor settings (column Day 2,

the first 3 sub-columns from the right (location D1, B1 and A3).

The highest concentration of PM10 in the outdoor is 0.142 mg/kg, captured on 30-

minutes measurement starting December 5, 2014 on 6.02 pm at the pillar between

Bay 06 and Bay 07 (column Day 2, location B1), followed by measurement started on

7.40 pm in the same day at the pillar between Bay 04 and Bay 05 (column Day 2,

location A3) with the concentration value of 0.139 mg/kg. Another data which can be

considered as higher is found during measurement started earlier at 5.02 pm in the

same day with value of 0.122 mg/kg. The measurement is done at the pillar between

Bay 10 and Bay 11 (column Day 2, location D1). From the observation during this

study, it is found that this fluctuation of the PM10 concentration is due to the increasing

number of heavy duty vehicle either park in or just crossed away, the inspection bays,

where it is estimated the total number of heavy duty vehicle is about 100 (40 bays X 2

heavy duty vehicles, plus with availability of 20 parking lots around the inspection

bays).

Except the obvious three higher concentrations as written above, other

concentrations for PM10 in the outdoor settings are scattered between the range of

0.020 mg/kg and 0.048 mg/kg. The lowest concentration for PM10 in the outdoor is

0.020 mg/kg which is measured at the pillar between Bay 04 and Bay 05 (column

Day 3, location A2) on December 7, 2014, started 7.50 pm.

In the indoor settings, the highest PM10 concentration is also found in same three

locations as in the outdoor (column Day 2, location D1, B1 and A2) within the same

period of the highest PM10 in the were outdoor found. However, the real highest PM10

value is found in inside the office of Bilik Sisihan Borang Kastam Import (column Day

2, location D1) with the concentration value of 0.120 mg/kg, on December 5, 2014

started at 5.44 pm. The concentration is decreased to 0.097 mg/kg inside the office of

Kaunter Pemeriksaan Kastam Import (column Day 2, location B1) which is started at

7.02 pm on the same day. About more than an hour later, the concentration of PM10

in the indoor settings is decreased to 0.081 mg/kg inside the office of Kaunter

Taksiran Kastam Import (column Day 2, location A3). In other locations within those 3

days, the concentration were found to be ranging from the lowest concentration value

of 0.013 mg/kg (column Day 3, location A2) which is measured on December 7, 2014

starting 8.27 pm; to the highest concentration value of 0.040 mg/kg (column Day 2,

location A2) which is measured on December 5, 2014 starting 9.35 am.

By referring Figure 4-1, it is found that the concentration of PM10 in the outdoor

settings are greater compared to the value of PM10 in the indoor settings at almost all

measurements done with the largest gap between both settings is in column Day 3,

location A3 which is measured on December 5, 2014 starting 7.40 pm with 41.727%

in differences, and smallest gap are found in column Day 1, location E2 which is

measured on December 4, 2014 starting 1.43 pm with the difference of 8.333%.

The only spot where I found the concentration value of PM10 in indoor settings is

greater than the concentration value in the outdoor is in column Day 2, location A2 on

December 5, 2014 starting at 11.36 am. During this measurement, I found the

concentration value of PM10 at the pillar between Bay 04 and Bay 05 is 0.034 mg/kg,

which is lesser than the concentration value of PM10 in the office of Kaunter Taksiran

Kastam Import where the value of PM10 found there is 0.040 mg/kg (slightly higher).

Day

PM10 (Outdoor) PM10 (Indoor)

Concentration in TWA24hrs

Acceptable upper limit in

MAAQG, DOE



ICOP IAQ 2010, DOSH

Day 1 0.002 mg/kg150 µg/m3

(0.15 mg/m3)

0.004 mg/kg0.15 mg/m3Day 2 0.011 mg/kg 0.025 mg/kg

Day 3 0.003 mg/kg 0.006 mg/kgNote: Unit conversion: 1 mg/kg = 1 mg/m3

Table 4-1 Results for each day TWA8hrs and TWA24hrs calculation from the PM10

concentration data obtained in Figure 4-1, and comparison with ICOP

IAQ 2010 and MAAQG, respectively.

Comparison between the data shown in Figure 4-1 after calculated for TWA8hrs and

TWA24hrs equivalent, for indoor and outdoor comparison with the related standards,

respectively, is as in Table 4-1 above.

Using SPSS software, descriptive statistic analysis is conducted to evaluate the data

distribution normalities. As shown in Figure 4-2, it is found that the mean for PM 10

concentration is 0.05008 with standard deviation (SD) is 0.03450, while the median is

0.03450. For the histogram, it is found that the normality curve is skewed to the left

(positive skew). The distribution of the data is not normal.

Statistics

PM10

N Valid 26

Missing 0

Mean .05008

Median .03450

Std. Deviation .039549

Skewness 1.455

Std. Error of Skewness .456

Percentiles 25 .02400

50 .03450

75 .05625





days of study

Figure 4-3 shows almost the same pattern as Figure 4-1. However, the highest value

of the outdoor PM4 concentration is 0.139 mg/kg, where it is lower than the highest

value of the outdoor PM10 concentration at the same measurement location and

session. The lowest outdoor PM4 concentration value is 0.019 mg/kg, also at the

same measurement location and session.

For the indoor setting, the highest PM4 concentration value is 0.0119 mg/kg (column

Day 2, location D1, where at this point, it is found that the outdoor concentration also

has a similar value), while the lowest PM4 concentration value is 0.013 mg/kg (column

Day 3, location A2).

At this moment, there is no suitable standard in Malaysia to be referred to compare

either the PM4 concentration found is comply or otherwise, both for ambient and

indoor air quality.

Statistics

PM4

N Valid 26

Missing 0

Mean .04850

Median .03300


Skewness 1.464



50 .03300

75 .05475




distribution normalities. As shown in Figure 4-4 above, it is found that the mean for

PM4 concentration is 0.04850 with standard deviation (SD) is 0.039047, while the

median is 0.03300. For the histogram, it is found that the normality curve is skewed to

the left (positive skew). The distribution of the data is not normal.

Particulate Matter with diameter size of 2.5 micron and smaller (PM2.5)

Figure 4-5 30-minutes averaged PM2.5 concentration at different location within 3

days of study


of the outdoor PM2.5 concentration is 0.137 mg/kg, where it is lower than the highest


session. The lowest outdoor PM2.5 concentration value is 0.017 mg/kg, also at the


For the indoor setting, the highest PM2.5 concentration value is 0.0119 mg/kg (column

Day 2, location D1) while the lowest PM2.5 concentration value is 0.013 mg/kg

(column Day 3, location A2). In these two locations, data shown that there are no

differences in the highest and lowest concentration of PM2.5 and PM4. At the same

point as the highest concentration value of PM2.5 in indoor setting, the concentration

value for the outdoor is slightly lower.

At this moment, there is no suitable standard in Malaysia to be referred to compare

either the PM2.5 concentration found is comply or otherwise, both for ambient and

indoor air quality.

Statistics

PM2.5

N Valid 26

Missing 0

Mean .04769

Median .03250


Skewness 1.460



50 .03250

75 .05375


Descriptive statistics table for PM2.5



PM2.5 concentration is 0.04769 with standard deviation (SD) is 0.038847, while the





days of study


of the outdoor PM1 concentration is 0.131 mg/kg, where it is lower than the highest


session. The lowest outdoor PM1 concentration value is 0.015 mg/kg, also at the


For the indoor setting, the highest PM1 concentration value is 0.0116 mg/kg (column

Day 2, location D1) while the lowest PM1 concentration value is 0.013 mg/kg (column

Day 3, location A2).

It’s now obvious that there are three different spots where the outdoor PM1

concentration value is lower (or slightly lower) than the indoor PM1 concentration

value. Based on Figure 4-7, the locations are in column Day 1 (location E2), column

Day 2 (location A2) and column Day 2 (location D1).


distribution normalities. As shown in Figure 4-8 below, it is found that the mean for

PM1 concentration is 0.04558 with standard deviation (SD) is 0.037718, while the



Statistics

PM1

N Valid 26

Missing 0

Mean .04558

Median .02950


Skewness 1.444



50 .02950

75 .05100



Total Particulate Matter (PMTOTAL)

Figure 4-9 30-minutes averaged PMTOTAL concentration at different location within 3

days of study

Based on the Figure 4-9 above, the highest concentration value of PMTOTAL for

outdoor settings is found in column Day 2, location B1 (at the pillar between Bay 06

and Bay 07) which is measured on December 5, 2014 starts at 6.22 pm with the

concentration value of 0.144 mg/kg. For the indoor settings, the highest concentration

value of PMTOTAL is 0.124 mg/kg measured on December 5, 2014 starts at 5.02 pm in

column Day 2, location D1 (inside the office of Kaunter Pemeriksaan Import Kastam).

In this same spot, I found that the concentration value for outdoor setting (at the pillar

between Bay 10 and Bay 11) is the same.

The lowest concentration value for both indoor settings and outdoor settings is found

in column Day 3, location A2 measured on December 7, 2014 starting 7.50 pm and

ends at 8.57 pm. The concentration values are 0.021 mg/kg (outdoor) and 0.014

mg/kg (indoor).

The concentration value of PMTOTAL for indoor settings is appeared three times to be

higher or slightly higher than the PMTOTAL concentration value in outdoor settings. The

three locations are column Day 1, location E2 measured on December 4, 2014 starts

at 1.43 pm (indoor concentration value is 0.026 mg/kg (inside the office of Urusetia

Import Kastam, Seksyen Jaminan Bank) and outdoor concentration value at the pillar

between Bay 12 and Bay 13 is 0.025 mg/kg); column Day 2, location A2 which is

measured on December 5, 2014 starts at 11.36 am (indoor concentration value is

0.046 mg/kg (inside the office of Urusetia Taksiran Kastam Import) and the outdoor

concentration value at pillar between Bay 04 and Bay 05 is 0.035 mg/kg); and at

column Day 3, location D1 which measured on December 7, 2014 starts at 8.58 am

(indoor concentration value in the office of Bilik Sishan Borang Kastam Import is

0.040 mg/kg and outdoor concentration value at pillar between Bay 10 and Bay 11 is

0.037 mg/kg).



PMTOTAL concentration is 0.05288 with standard deviation (SD) is 0.040288, while the



Statistics

PM Total

N Valid 26

Missing 0

Mean .05288

Median .03650


Skewness 1.400



50 .03650

75 .06050


Descriptive statistics table for PMTOTAL

Total Volatile Organic Compound (TVOC)

Figure 4-11 below shows the value of TVOC founds in the study locations. The

highest value for TVOC in the outdoor settings is found at the pillar between Bay 04

and Bay 05 with the concentration value is 38.97 ppm followed by slightly lower

concentration (38.96 ppm) found at the pillar between Bay 10 and Bay 11, both is

measured on December 7, 2014, starting from 6.04 pm. The lowest TVOC

concentration in outdoor settings is found at the pillar between Bay 10 and Bay 11

(2.13 ppm) measured on December 5, 2014 starts at 5.02 pm. For indoor settings,

the highest value is found on December 7, 2014 after measurement starts at 6.04 pm

in the office of Bilik Sisihan Borang Kastam Import (5.06 ppm). The lowest value of

indoor settings for TVOC is 1.21 ppm, measured in the office of Unit Taksiran Kastam

Import on December 7, 2014 starts at 1020 am.

Figure 4-11 30-minutes averaged TVOC concentration at different location within 3

days of study (the horizontal redline: acceptable upper limit: 3 ppm,

TWA8hrs (ICOP IAQ 2010, DOSH))

The values of TVOC are looks a like to be closer between indoor settings and

outdoor settings from the results obtained from measurement done on December 5,

2014 started 10.55 am until 7.32 pm (column Day 2, location C1 until location B1).

The values of TVOC in outdoor settings are ranged from 2.13 ppm and 2.99 ppm,

while the indoor settings TVOC value ranged from 1.16 ppm and 1.40 ppm.

Comparison between the data shown in Figure 4-11 after calculated for TWA8hrs

equivalent, for indoor TVOC concentration with the related standards, is as in Table

4-2 below.

DayTVOC (Indoor)

Concentration in TWA8hrs Acceptable upper limit in ICOP IAQ 2010, DOSHDay

1 0.593 ppm

3 ppmDay 2 0.553 ppm

Day 3 0.732 ppm

Table 4-2 Results for each day TWA8hrs calculation from the TVOC concentration


Statistics

TVOC

N Valid 26

Missing 0

Mean 7.4377

Median 3.0850

Std. Deviation 1.05511E1

Skewness 2.413


Percentiles 25 1.9375

50 3.0850

75 7.4875


Descriptive statistics table for TVOC



TVOC concentration is 7.4377 with standard deviation (SD) is 0.105511, while the



Carbon dioxide (CO2)

Figure 4-13 30-minutes averaged CO2 concentration at different location within 3

days of study (the horizontal redline: acceptable upper limit: C1000

ppm, TWA8hrs (ICOP IAQ 2010, DOSH))

As shown in Figure 4-13, at all time during this study conducted, CO2 values in the

indoor settings are higher compared to the CO2 values at the outdoor settings. The

highest CO2 value is 760 ppm measured in the indoor settings is in the office of Bilik

Sisihan Borang Kastam Import which is measured on December 5, 2014 started at

5.44 pm. At the same time, the value of CO2 at outdoor settings at the pillar between

Bay 10 and Bay 11 is 595 ppm. The highest CO2 value for outdoor settings is 606

ppm, measured on December 5, 2014 at 6.22 pm at the pillar between Bay 06 and

Bay 07, while the lowest CO2 value for both indoor and outdoor settings is measured

on December 7, 2014 started 7.50 pm until 8.57 pm with the value at the pillar

between Bay 04 and Bay 05 is 414 ppm and the value in the office of Unit Taksiran

Kastam Import is 531 ppm.


equivalent, for indoor CO2 concentration with the related standards, is as in Table 4-3

below.

DayCO2 (Indoor)

Concentration in TWA8hrs Acceptable upper limit in ICOP IAQ 2010, DOSHDay

1 114.225 ppm

C1000 ppmDay 2 260.688 ppm

Day 3 145.438 ppm

Table 4-3 Results for each day TWA8hrs calculation from the CO2 concentration




carbon dioxide concentration is 575.65 with standard deviation (SD) is 90.324, while

the median is 574.00. For the histogram, it is found that the normality curve is slightly

skewed to the left (positive skew). The magnitude of the skewness is 0.291, which is

closer to the 0 (absolute normal distribution). The distribution of the data is slightly

normal.

Statistics

Carbon Dioxide

N Valid 26

Missing 0

Mean 575.65

Median 574.00

Std. Deviation 90.324

Skewness .291



50 574.00

75 643.25


Descriptive statistics table for carbon dioxide

Ozone (O3)

Figure 4-15 shows the ozone concentration value in both settings. The averaged

ozone concentration value for indoor settings are found only at two measurements

done December 5, 2014 started 5.02 pm until 7.32 pm in the office of Bilik Sisihan

Borang Kastam Import and in the office of Kaunter Pemeriksaan Kastam Import,

where the concentration value is same at 0.01 ppm. For outdoor settings, the value

of ozone is ranged from the lowest (0.00 ppm) until the highest (0.03 ppm).

Figure 4-15 30-minutes averaged ozone concentration at different location within 3


ppm, TWA8hrs (ICOP IAQ 2010, DOSH); 0.06 ppm, TWA8hrs (MAAQG,

DOE))

Day

O3 (Outdoor) O3 (Indoor)



MAAQG, DOE



ICOP IAQ 2010, DOSH

Day 1 0.003 ppm 0.06 ppm 0.000 ppm 0.05 ppm

Day 2 0.004 ppm 0.001 ppmDay 3 0.002 ppm 0.000 ppm

Table 4-4 Results for each day TWA8hrs calculation from the ozone concentration

data obtained in Figure 4-15, and comparison with ICOP IAQ 2010 and

MAAQG, respectively.


equivalent, for indoor and outdoor comparison with the related standards,




ozone concentration is 0.0062 with standard deviation (SD) is 0.00941, while the

median is 0.0000. For the histogram, it is found that the normality curve is slightly


closer to the 0 (absolute normal distribution). The distribution of the data is slightly

normal.

Statistics

Ozone

N Valid 26

Missing 0

Mean .0062

Median .0000


Skewness 1.509



50 .0000

75 .0100


Descriptive statistics table for ozone

Carbon monoxide (CO)

Figure 4-17 30-minutes averaged carbon monoxide concentration at different

location within 3 days of study (the horizontal redline: acceptable upper

limit: 10.0 ppm, TWA8hrs (ICOP IAQ 2010, DOSH); the horizontal purple

line 9.0 ppm, TWA8hrs (MAAQG, DOE))

The value of carbon monoxide concentration is shown in Figure 4-17 above. The

maximum value of CO is captured in column Day 1, location A1 on December 4, 2014

started from 12.14 pm until 1.33 pm for both indoor (in the office of Unit Taksiran

Kastam Import) and outdoor settings (at the pillar between Bay 04 and Bay 05). The

values are 17.3 ppm (outdoor settings) and 4.0 ppm (indoor settings). At all times

during this study, the value of CO for outdoor settings are higher compared to CO

value for indoor settings, except from December 5, 2014 started from 10.14 am until

6.14 pm, where the value for both settings is 0.0 ppm. Meanwhile, a measurement

done on December 5, 2014 started at 6.22 pm found that the value of CO in the

indoor settings (in the office of Kaunter Pemeriksaan Kastam Import: 0.1 ppm) is

slightly higher than the value of CO in the outdoor settings (at the pillar between Bay

06 and Bay 07: 0.0 ppm).

Day

CO (Outdoor) CO (Indoor)



MAAQG, DOE



ICOP IAQ 2010, DOSH

Day 1 2.206 ppm 9.0 ppm 0.334 ppm 10.0 ppm

Day 2 0.181 ppm 0.013 ppm

Day 3 1.181 ppm 0.119 ppm

Table 4-5 Results for each day TWA8hrs calculation from the CO concentration data

obtained in Figure 4-17, and comparison with ICOP IAQ 2010 and

MAAQG, respectively.


equivalent, for indoor and outdoor comparison with the related standards,






the left (positive skew). The magnitude of the skewness is 2.255, which is away from

absolute normal distribution. Therefore the distribution of the data is not normal.

Statistics

Carbon Monoxide

N Valid 26

Missing 0

Mean 2.485

Median .500


Skewness 2.255


Percentiles 25 .000

50 .500

75 2.575


Descriptive statistics table for carbon monoxide

Air temperature (AT)

Based on Figure 4-19 below, the value of the air temperature in outdoor settings is

ranged between the lowest 23.0 ⁰C (at the pillar between Bay 05 and Bay 05) as

measured on December 7, 2014 started from 7.50 pm, and the highest 32.5 ⁰C (at

the pillar between Bay 06 and Bay 07) as measured on December 5, 2014 started

from 6.22 pm. The range of air temperature in indoor settings is from 21.7 ⁰C (in the

office of Unit Taksiran Kastam Import) as measured on December 7, 2014 started

from 7.50 pm, and the highest is 27.6 ⁰C (in the office of Bilik Sisihan Borang Kastam

Import) as measured on December 5, 2014 started from 5.44 pm.

Figure 4-19 30-minutes averaged air temperature at different location within 3 days

of study (the horizontal redline: acceptable range: 23.0 ⁰C – 26.0 ⁰C,


Statistics

Air Temperature

N Valid 26

Missing 0

Mean 26.288

Median 26.000


Skewness .465



50 26.000

75 28.225


Descriptive statistics table for air temperature






closer to absolute normal distribution (0). Therefore the distribution of the data is

slightly normal.

Relative humidity percentage (%RH)

Figure 4-21 30-minutes averaged relative humidity percentage at different location

within 3 days of study (the horizontal redline: acceptable range: 40 % –

70 % (ICOP IAQ 2010, DOSH))

As shown in Figure 4-21 above, it is found that the relative humidity percentage

(%RH) is higher in the outdoor setting compared to the indoor setting. The maximum

value of %RH is 97.9%. The %RH value is found to be more than 80.0% during rainy

day or slightly after, while the %RH value is found more than 90.0% during heavy rain

day. The minimum value of %RH is 48.4%.

Statistics

Relative Humidity

N Valid 26

Missing 0

Mean 68.885

Median 64.800


Skewness .665



50 64.800

75 77.400

Figure 4-22 (Left) Histogram of the %RH data distribution and normality curve;

(Right) Descriptive statistics table for %RH






closer to absolute normal distribution (0). Therefore the distribution of the data is

slightly normal.

Air velocity (AV)

Figure 4-23 30-minutes averaged air velocity at different location within 3 days of

study (the horizontal redline: acceptable range: 0.15 m/s – 0.50 m/s


Based on Figure 4-23, the air velocity for outdoor settings is ranged from the slowest

(0.05 m/s) to the fastest (22.6 m/s) while the air velocity for indoor setting is ranged

from the slowest (0.00 m/s) to the highest (0.29 m/s). At average of all time, the

velocity is higher in the outdoor settings compared to the indoor settings.





the left (positive skew). Therefore the distribution of the data is slightly normal.

Statistics

Air

Velocity

N Valid 26

Missing 0

Mean 1.030

Median .070


Skewness 5.082


Percentiles 25 .018

50 .070

75 .295

Figure 4-24 (Left) Histogram of the air velocity data distribution and normality curve;

(Right) Descriptive statistics table for air velocity

Conclusion for the result of specific objective (1)

Using the monitoring instruments as declared in Chapter 3 for in-situ air quality

measurement in both outdoor and indoor settings, the specific objective (1) is fulfilled

for the listed air quality parameters. In all three days of monitoring, 26 sampling

activities has been in ten different locations which have been visited (outdoor –

inspection bay; and indoor - offices) at the Import Lane of KSAB.

The focused parameter, particulate matters, especially PM10 has been found not

violating the standards (MAAQG and ICOP IAQ 2010), either during the 30-minutes

averaged measurement or after been calculated for TWA8hrs and TWA24hrs, for indoor

air quality and ambient air quality, respectively. The particulate matter concentration

is seems to be higher in both settings as influenced by the increasing number of

heavy duty vehicles either crossed-by or parked at the inspection bay.

By using descriptive statistic analysis, it is found that all of the data are not normally

distributed, although some parameters showing skewness is below +1.0 and slightly

closed to the 0 (the closest value of skewness is about +0.2). Therefore, in further

analysis of determining the significant different between indoor and outdoor, non-

parametric analysis will be more suitable instead of using t-test.

Specific objective (2): to compare the particulate matters concentration

between the outdoor and indoor settings

As all of the data have positive skewness with value of more than 0, significant

different analysis is done using Kruskal-Wallis Non-Parametric Test (Kruskal-Wallis H

Test) using SPSS version 16.0. This is alternative test for One-way ANOVA is data is

distributed normally. Location setting is set for grouping variable, which the group is

defined as 1 (outdoor setting) and 2 (indoor setting). The output result generated as

follow:

Descriptive Statistics

N Mean Std. Deviation Minimum Maximum

Percentiles

25th 50th (Median) 75th

PM10 26 .05008 .039549 .013 .142 .02400 .03450 .05625

PM4 26 .04850 .039047 .013 .139 .02275 .03300 .05475

PM2.5 26 .04769 .038847 .013 .137 .02250 .03250 .05375

PM1 26 .04558 .037718 .012 .131 .02075 .02950 .05100

PM Total 26 .05288 .040288 .014 .144 .02575 .03650 .06050

TVOC 26 7.4377 10.55112 1.16 38.97 1.9375 3.0850 7.4875

Carbon Dioxide 26 575.65 90.324 414 760 497.00 574.00 643.25

Ozone 26 .0062 .00941 .00 .03 .0000 .0000 .0100

Carbon

Monoxide26 2.485 4.5509 .0 17.3 .000 .500 2.575

Air Temperature 26 26.288 2.9619 21.7 32.5 23.875 26.000 28.225

Relative Humidity 26 68.885 14.8105 48.4 97.9 57.825 64.800 77.400

Air Velocity 26 1.030 4.4040 .0 22.6 .018 .070 .295

Location Setting 26 1.50 .510 1 2 1.00 1.50 2.00

Table 4-6 Output results for descriptive statistics after analysis of Kruskal-Wallis

Non-Parametric Test (K-Independent Sample) has been run in SPSS.

Ranks

Location Setting N Mean Rank

PM10 Outdoor Setting 13 15.85

Indoor Setting 13 11.15

Total 26

PM4 Outdoor Setting 13 15.73Indoor Setting 13 11.27Total 26

PM2.5 Outdoor Setting 13 15.58Indoor Setting 13 11.42Total 26

PM1 Outdoor Setting 13 15.42Indoor Setting 13 11.58Total 26

PM Total Outdoor Setting 13 15.31Indoor Setting 13 11.69Total 26

TVOC Outdoor Setting 13 18.38Indoor Setting 13 8.62Total 26

Carbon Dioxide Outdoor Setting 13 7.85Indoor Setting 13 19.15Total 26

Ozone Outdoor Setting 13 16.81Indoor Setting 13 10.19Total 26

Carbon Monoxide Outdoor Setting 13 16.12Indoor Setting 13 10.88Total 26

Air Temperature Outdoor Setting 13 16.69Indoor Setting 13 10.31Total 26

Relative Humidity Outdoor Setting 13 18.46Indoor Setting 13 8.54Total 26

Air Velocity Outdoor Setting 13 19.35

Indoor Setting 13 7.65

Total 26

Table 4-7 Output results for the Mean Rank

Test Statisticsa,b

PM10 PM4 PM2.5 PM1 PM

Total

TVOC Carbon

Dioxide

Ozone Carbon

Monoxide

Air

Temperature

Relative

Humidity

Air

Velocity

Chi-

Square2.455 2.217 1.919 1.648 1.456

10.60

414.212 6.442 3.175 4.534 10.941 15.258

df 1 1 1 1 1 1 1 1 1 1 1 1

Asymp.

Sig..117 .136 .166 .199 .228 .001 .000 .011 .075 .033 .001 .000

a. Kruskal Wallis Testb. Grouping Variable: Location Setting

Table 4-8 Output results for the Test Statistics (Chi-Square, X2)

Frequencies

Location Setting

Outdoor Setting Indoor Setting

PM10 > Median 9 4

<= Median 4 9PM4 > Median 8 4

<= Median 5 9PM2.5 > Median 9 4

<= Median 4 9PM1 > Median 9 4

<= Median 4 9PM Total > Median 8 5

<= Median 5 8TVOC > Median 9 4

<= Median 4 9Carbon Dioxide > Median 2 11

<= Median 11 2Ozone > Median 8 2

<= Median 5 11Carbon Monoxide > Median 9 4

<= Median 4 9Air Temperature > Median 8 5

<= Median 5 8Relative Humidity > Median 11 2

<= Median 2 11Air Velocity > Median 12 1

<= Median 1 12

Table 4-9 Output results for the FrequencyTest Statisticsa

PM10 PM4 PM2.5 PM1 PM

Total

TVOC Carbon

Dioxide

Ozone Carbon

Monoxide

Air

Temperature

Relative

Humidity

Air

Velocity

N 26 26 26 26 26 26 26 26 26 26 26 26

Median .03450 .03300 .03250 .02950 .03650 3.0850 574.00 .0000 .500 26.000 64.800 .070

Exact

Sig..115 .238 .115 .115 .434 .115 .001 .041 .115 .434 .001 .000

a. Grouping Variable: Location Setting

Table 4-10 Output results for the Test Statistics (median)

Conclusion from the result obtained in fulfilling the specific objective (2):

Based on Table 4-8 above, it is found that there are statistically significant differences

found between the location settings and (1) TVOC (X2(1)=10.604, p=0.001, with

mean rank TVOC of 18.38 for the outdoor and 8.62 for the indoor setting); (2) carbon

dioxide (X2(1)=14.212, p=0.000, with mean rank carbon dioxide of 7.85 for the

outdoor and 19.15 for the indoor setting); (3) relative humidity (X2(1)=10.941,

p=0.001, with mean rank relative humidity of 18.46 for the outdoor and 8.54 for the

indoor setting); and (4) air velocity (X2(1)=15.258, p=0.000, with mean rank air

velocity of 19.35 for the outdoor and 7.65 for the indoor setting).

For the focused parameters in this study, particulate matters, it is found that there are

no statistically significant differences between location settings and particulate

matters: (1) PM10 (X2(1)=2.455, p=0.117, with mean rank PM10 of 15.85 for the

outdoor and 11.15 for the indoor setting); (2) PM4 (X2(1)=2.217, p=0.136, with mean

rank PM4 of 15.73 for the outdoor and 11.27 for the indoor setting); (3) PM2.5

(X2(1)=1.919, p=0.166, with mean rank PM2.5 of 15.58 for the outdoor and 11.42 for

the indoor setting); (4) PM1 (X2(1)=1.648, p=0.199, with mean rank PM1 of 15.42 for

the outdoor and 11.58 for the indoor setting); and (5) PMTOTAL (X2(1)=1.456, p=0.228,

with mean rank PMTOTAL of 15.31 for the outdoor and 11.69 for the indoor setting).

Ozone concentration, carbon monoxide and air temperature are also found not

statistically significant different with the location settings, outdoor and indoor,

respectively.

For particulate matter, it is found that the gap of differences of particulate

concentration and location settings is become larger when the diameter size of the

particulate matters become smaller (p-value ranged from 0.117 for PM10 to 0.199 for

PM1), while based on the mean rank, the concentration become lesser the diameter

size of the particulate matter become smaller for the outdoor (from 15.85 for PM10 to

15.42 for PM1), but vice-versa for the indoor setting (from 11.15 for PM10 to 11.58 for

PM1).

Hypothesis testing for objective (2):

H0: μA ≠ μB (p < 0.005) HA: μA = μB (p < 0.005)

It is found that p-value > 0.005 for particulate matter, thus accept HA.

Specific objective (3): to identify the relationship between particulate matter

and other parameters in the outdoor and in the indoor settings

Spearman’s Non-Parametric Correlation Test is used to analyse the correlation

between particulate matters concentration and the other air quality parameters.

Correlations

PM10 PM4 PM2.5 PM1 PM Total

Spearman's rho TVOC Correlation Coefficient -.176 -.198 -.213 -.244 -.215

Sig. (2-tailed) .391 .333 .295 .230 .291

N 26 26 26 26 26

Carbon Dioxide Correlation Coefficient .248 .262 .290 .307 .304

Sig. (2-tailed) .222 .196 .151 .128 .131

N 26 26 26 26 26

Ozone Correlation Coefficient .341 .325 .280 .253 .309

Sig. (2-tailed) .089 .105 .165 .213 .125

N 26 26 26 26 26

Carbon Monoxide Correlation Coefficient -.377 -.400* -.428* -.479* -.410*

Sig. (2-tailed) .057 .043 .029 .013 .037

N 26 26 26 26 26

Air Temperature Correlation Coefficient .682** .688** .706** .724** .657**

Sig. (2-tailed) .000 .000 .000 .000 .000

N 26 26 26 26 26

Relative Humidity Correlation Coefficient -.210 -.229 -.253 -.282 -.263

Sig. (2-tailed) .303 .260 .212 .163 .194

N 26 26 26 26 26

Air Velocity Correlation Coefficient .339 .344 .333 .334 .264

Sig. (2-tailed) .090 .085 .097 .095 .192

N 26 26 26 26 26

**. Correlation is significant at the 0.01 level (2-tailed).

*. Correlation is significant at the 0.05 level (2-tailed).

Table 4-11 Spearman’s correlation output results. The table is been simplified to fit

the page

From the Spearman’s rank-order correlation output (which the table has been

simplified to suit the page), the correlation between particulate matters (each type)

and the other air quality parameters are obtained.

There are strong, positive correlations between each type of particulate matter and

air temperature, which are statistically significant (PM10: rs(24)=.682, p=.000; PM4:

rs(24)=.688, p=.000; PM2.5: rs(24)=.706, p=.000; PM1: rs(24)=.724, p=.000; and

PMTOTAL: rs(24)=.657, p=.000).

Between each type particulate matters and TVOC, as well as with relative humidity,

the correlation is weak and negative. The other parameter which has negative

correlation with each type of particulate matters is carbon monoxide. However, it is a

moderate correlation, not weak.

Between each type particulate matters and carbon dioxide, the correlation is positive,

ranged from weak to slightly moderate as according to the particulate diameter size

from smaller to larger. However, with the ozone, the correlation is also positive but

the strength of the correlation is from moderate to weak as according to the

particulate diameter size. With air velocity, the correlation is moderate and positive.

However, except for correlation between each type of particulate matter and air

temperature, all other correlations are not statistically significant.


H0: rA = rB (p < 0.005) HA: rA ≠ rB (p > 0.005)

It is found that p-value < 0.005 only for correlation between particulate matter

and carbon dioxide, thus accept H0 for correlation with carbon dioxide, but the

p-value > 0.005 for particulate matter correlation with other pollutants,

therefore reject H0 for correlation between particulate matters and other

pollutants.

Specific objective (4): to calculate particulate matter indoor-outdoor (I/O) ratio

The formula for indoor-outdoor ratio is as follow:

I/Ox =Indoor particulate matter concentration (PMx)

Outdoor particulate matter concentration (PMx)

where x is category of particulate matter, which is 10, 4, 2.5 and 1

The I/O ratio calculation will be used the mean value for each concentration in the

specific location settings.

Statistics

PM10

Outdoor

PM10

Indoor

PM4

Outdoor

PM4

Indoor

PM2.5

Outdoor

PM2.5

Indoor

PM1

Outdoor

PM1

Indoor

PM Total

Outdoor

PM Total

Indoor

N Valid 13 13 13 13 13 13 13 13 13 13

Missing 0 0 0 0 0 0 0 0 0 0

Mean .05731 .04285 .05531 .04169 .05400 .04138 .05108 .04008 .05892 .04685

Median .03700 .02900 .03600 .02800 .03400 .02800 .03300 .02700 .03900 .03100

Std. Deviation.044724 .033840 .044141

.03357

9.043936 .033577 .042567

.03296

1.045383 .035256

Variance .002 .001 .002 .001 .002 .001 .002 .001 .002 .001

Minimum .020 .013 .019 .013 .017 .013 .015 .012 .021 .014

Maximum .142 .120 .139 .119 .137 .119 .131 .116 .144 .124

Table 4-12 Descriptive statistics output when the concentration of particulate matter

is separated in specific location settings with N=13 for each setting

Therefore:

I/O ratio for particulate matter (PM10):

I/O10 =Mean of overall indoor particulate matter (PM10)

Mean of overall outdoor particulate matter (PM10)

I/O10 =0.04285

0.05731

I/O10 = 0.748

For PM10, the I/O ratio is indicates from this study the indoor concentration of PM10 is

74.8% of the outdoor concentration of PM10




I/O4 =0.04169

0.05531

I/O4 = 0.754



I/O ratio for particulate matter (PM2.5):

I/O2.5 =Mean of overall indoor particulate matter (PM2.5)

Mean of overall outdoor particulate matter (PM2.5)

I/O2.5 =0.04138

0.05400

I/O2.5 = 0.766

For PM2.5, the I/O ratio is indicates from this study the indoor concentration of PM2.5 is

76.6% of the outdoor concentration of PM2.5




I/O1 =0.04008

0.05108

I/O1 = 0.785



I/O ratio for particulate matter (PMTOTAL):

I/OTOTAL =Mean of overall indoor particulate matter (PMTOTAL)

Mean of overall outdoor particulate matter (PMTOTAL)

I/OTOTAL =0.04685

0.05892

I/OTOTAL = 0.795

For PMTOTAL, the I/O ratio is indicates from this study the indoor concentration of

PMTOTAL is 79.49% of the outdoor concentration of PMTOTAL


H0: I/OPM < 1 HA: I/OPM > 1

It is found that I/OPM < 1 therefore accept H0. However, the degree 20% in

difference can be considered as small, thus this hypothesis may not be

conflicting the hypothesis for specific objective (2).

CHAPTER FIVE

DISCUSSION

By referring to Figure 4-1, Figure 4-3, Figure 4-5, Figure 4-7 and Figure 4-9, all types

of particulate matter concentrations have almost the same pattern of exposures. The

highest peak for particulate matter exposure in outdoor settings, based on those

figures is at pillar between Bay 06 and Bay 07 measured on December 5, 2014

started at 6.22 pm until 6.52 pm (column Day 2, location B1) (PM 10 = 0.142 mg/kg,

PM4 = 0.139 mg/kg, PM2.5 = 0.137 mg/kg, PM1 = 0.131 mg/kg, PMTOTAL = 0.144

mg/kg), while the lowest particulate matter exposure in outdoor settings, based on the

figures is at pillar between Bay 04 and Bay 05 measured on December 7, 2014

started at 7.50 pm until 8.20 pm (column Day 3, location A2) (PM 10 = 0.020 mg/kg,

PM4 = 0.019 mg/kg, PM2.5 = 0.017 mg/kg, PM1 = 0.015 mg/kg, PMTOTAL = 0.021

mg/kg).

For particulate matter exposure in indoor settings, the highest peak is found during

the measurement done inside the office of Bilik Sisihan Borang Kastam Import

measured on December 5, 2014 started at 5.44 pm until 6.14 pm (column Day 2,

location D1) (PM10 = 0.122 mg/kg, PM4 = 0.119 mg/kg, PM2.5 = 0.118 mg/kg, PM1 =

0.113 mg/kg, PMTOTAL = 0.124 mg/kg), while the lowest exposure found during

measurement inside the office of Kaunter Taksiran Kastam Import measured on

December 7, 2014 started at 8.27 pm until 8.57 pm (column Day 3, location A2) (PM10

= 0.013 mg/kg, PM4 = 0.013 mg/kg, PM2.5 = 0.013 mg/kg, PM1 = 0.012 mg/kg, PMTOTAL

= 0.014 mg/kg).

Based on these figures, it is found that at all time, the particulate matter exposures

are higher at the outdoor settings compared to indoor settings, except during

measurement done in column Day 2, location A2 on December 5, 2014 started on

11.36 am until 12.41 pm, the particulate matter exposure in outdoor settings is lower

than the particulate matter in indoor settings (PM10in, PM10out = 0.040 mg/kg, 0.034

mg/kg; PM4in, PM4out = 0.039 mg/kg, 0.033 mg/kg; PM2.5in, PM2.5out = 0.038 mg/kg,

0.032 mg/kg; PM1in, PM1out = 0.037 mg/kg, 0.030 mg/kg; PMTOTALin, PMTOTALout = 0.046

mg/kg, 0.035 mg/kg). Based on my observation, during the 30-minutes measurement,

the period of the door which is opposite to the inspection bay left opened was about

11 minutes, whiles the frequency of the door opened and closed is 8 times.

As for general, according to Grau-Bove & Strlic (2013), the indoor particulate matter

concentration is generally a reflection of the outdoor concentration. However, when

there are sources of contamination such as wood burner, cooking stove or even

smoking activities, the concentration of the indoor settings may be higher than the

concentration of the outdoor settings.

From Table 4-10, it is found that the only air quality parameter which is significantly

correlated with particulate matter is air temperature. The strong, positive correlation

reflects that when there is small difference (increment) in air temperature it will

influence the huge increment in particulate matters concentration.

Thus, a calculation to determining the size of gap between the indoor and outdoor

value of the temperature and other particulate matters at each sampling location is

done. From the result, smaller differences between indoor and outdoor air

temperature promote higher number of I/O ratio.

For other parameters, it is learnt that the value of total volatile organic compound

(TVOC), carbon monoxide (CO), ozone (O3), temperature, relative humidity and air

speed are also higher at the outdoor settings rather than in indoor settings. However,

only the value of carbon dioxide (CO2) is found higher in indoor settings compared to

the outdoor settings at all time.

As all of the data have positive skewness with value of more than 0, significant

different analysis is done using Kruskal-Wallis Non-Parametric Test (Kruskal-Wallis H

Test). The result shows that there are no statistically significant differences between

the outdoor and the indoor concentration of particulate matters, ozone, carbon

monoxide and air temperature. However there are statistically significant differences

in TVOC and carbon dioxide concentrations, as well as in relative humidity

percentage and air velocity (p < 0.005).

For particulate matter, it is found that the gap of differences of particulate

concentration and location settings is become larger when the diameter size of the

particulate matters become smaller (p-value ranged from 0.117 for PM10 to 0.199 for

PM1), while based on the mean rank, the concentration become lesser the diameter

size of the particulate matter become smaller for the outdoor (from 15.85 for PM10 to

15.42 for PM1), but vice-versa for the indoor setting (from 11.15 for PM10 to 11.58 for

PM1).

To understand relationship and correlation between each category of particulate

matters and other parameter, a Spearman’s correlation analysis has been done.

From the Spearman’s rank-order correlation output (which the table has been

simplified to suit the page), the correlation between particulate matters (each type)

and the other air quality parameters are obtained.

There are strong, positive correlations between each type of particulate matter and

air temperature, which are statistically significant (PM10: rs(24)=.682, p=.000; PM4:

rs(24)=.688, p=.000; PM2.5: rs(24)=.706, p=.000; PM1: rs(24)=.724, p=.000; and

PMTOTAL: rs(24)=.657, p=.000).

Between each type particulate matters and TVOC, as well as with relative humidity,

the correlation is weak and negative. The other parameter which has negative

correlation with each type of particulate matters is carbon monoxide. However, it is a

moderate correlation, not weak.

Between each type particulate matters and carbon dioxide, the correlation is positive,

ranged from weak to slightly moderate as according to the particulate diameter size

from smaller to larger. However, with the ozone, the correlation is also positive but

the strength of the correlation is from moderate to weak as according to the

particulate diameter size. With air velocity, the correlation is moderate and positive.

However, except for correlation between each type of particulate matter and air

temperature, all other correlations are not statistically significant.

Indoor-Outdoor (I/O) Ratio

From the calculation conducted, it is found that the ratios are as follow:

I/O for PM10 = 0.748

I/O for PM4 = 0.754

I/O for PM2.5= 0.766

I/O for PM1 = 0.785

I/O for PMTOTAL = 0.795

The concentration of all type particulate matters in indoor settings is ranging from

74.8% to 79.5% of their concentration in the outdoor settings. Therefore, it is obvious

that the outdoor particulate matter volume is higher compared to the indoor

particulate volume, however, the difference is small (ranged from 20% to 25%), thus it

is proven that there is no statistically significant difference between the indoor and the

outdoor particulate matters concentration.

Based on the findings found by Grau-Bove & Strlic (2013), it is proven that particulate

matter concentration ratio between indoor and outdoor, based on the mean value, is

greater when the size of the particulate diameter is lesser.

Comparing data with legal requirement and standards

For outdoor settings, the volume of air pollutant can’t be compared with Malaysian

Ambient Air Quality Guidelines, Department of Environmental Malaysia because the

guidelines required the measurement to be averaging for ozone (0.10 ppm for 1 hour

and 0.06 ppm for 8 hours); carbon monoxide (CO) (30.0 ppm for 1 hour and 9.0 ppm

for 8 hours) and particulate matter (PM10) (150 μg/m3 for 24 hours and 50 μg/m3 for 12

month), while the measurement done during this study is only 30 minutes per location

per time. However by converting the concentration value accordance to the

requirement, it is found that:

(1) Based on TWA8hrs, the carbon monoxide concentration is very far lower than

the acceptable limit in the standards (Day 1 = 2.2 ppm; Day 2 = 0.2 ppm;

and Day 3 = 1.2 ppm);

(2) Based on TWA8hrs, the ozone concentration is very far lower than the

acceptable limit in the standards (Day 1 = 0.003 ppm; Day 2 = 0.004 ppm;

and Day 3 = 0.002 ppm);

(3) Based on TWA24hrs, the PM10 concentration is very far lower than the

acceptable limit in the standards (Day 1 = 0.002 mg/kg; Day 2 = 0.011

mg/kg; and Day 3 = 0.003 mg/kg);

For measurement in indoor setting, the time weighted average 8-hours (TWA8hrs) for

each parameter per day is calculated, and then compared with the standard set in

Industry Code of Practice Indoor Air Quality 2010, Department of Occupational Safety

& Health Malaysia. From the calculated TWA8hrs it is found that:

(1) None of the respirable particulates (PM10) is found to be exceeded 0.15

mg/m3 acceptable limit, based on TWA8hrs.

(2) The value of total volatile organic compound is exceeds the acceptable limit

of 3.0 ppm on December 4, 2014 (3.160 ppm) and nearly exceed the limit

on December 7, 2014 (2.928 ppm). However based on TWA8hrs none of the

TVOC concentration exceeds the limit.

(3) None of the carbon dioxide (CO2) level exceed acceptable limit of C1000

ppm, based on TWA8hrs.

(4) None of the ozone (O3) level exceed acceptable limit of 0.05 ppm, based on

TWA8hrs.

(5) None of the carbon monoxide (CO) level exceeds the acceptable limit of 10

ppm, based on TWA8hrs.

(6) Only temperature in December 4, 2014 (22.8 ⁰C) is less than acceptable

range of 23 – 26 ⁰C.

(7) None of the relative humidity found to be exceeded or less than acceptable

range of 40 – 70%.

(8) Air speeds in all three days of study (December 4, 2014 (0.02 m/s);

December 5, 2014 (0.07 m/s); and December 7, 2014 (0.02 m/s) are less

than acceptable range of 0.15 – 0.50 m/s.

CHAPTER SIX

RECOMMENDATION AND CONCLUSION

Regarding the vehicle

It is suggested a massive campaigns need to be done from the national level to the

bottom strata to encourage fleet industries to shift into cleaner fuel substances in

vehicle power generation, such as by using low-sulphur content diesel, as well as to

use appropriate device, such as the use of three-way (oxidation-reduced) catalytic

converter to reduce the pollution emission (Faiz, A et al, 1996; Bailey & Solomon,

2004; WHO)

Heavy vehicle is suggested to be licensing and the renewal must be done annually.

Prior to the new license issued, a regular monitoring and maintenance in ensure

cleaner emission needs to be conducted. Unlicensed heavy duty vehicle needs to be

banned from the road (WHO).

The government of Singapore has already amended a new smoke emission limit for

vehicle fuelled with diesel entering the country from Malaysia, from 50 HSU to 40

HSU effectively July 1, 2014. This is a serious approach at the national level, which

can be followed by Malaysia Government. To ensure the HSU level below the

acceptable limit, several recommendations has been published by Department of

Environment Malaysia to all vehicle owner: (1) adhere to recommended maintenance

schedule; (2) undergo periodic smoke inspection; (3) service the fuel injector as well

as the fuel pump for every 20,000 km mileage; and (4) overhauled engines every

100,000 km mileage (DOE Malaysia, 2014).

Last but not least, as suggested by Bailey D and Solomon G, there is a need to

regulate the requirement for the driver to reduce speed once approaching near the

inspection bay and offices as well as switching off the engine while parked in the

inspection bay or any other area around, regardless the duration the vehicle stopping

in the parking area.

Regarding the building

According to Maroni (1998), the proper design and construction of building is

important strategy to gain better indoor air quality. As the building is already existed,

the second strategy needs to be implemented appropriately. The first step is to

control the source. As the source in Import Lane is coming from the outdoor

environment, the penetration and the infiltration of the pollutants need to be

minimized as far as practicable. Door and windows need to be kept close at all time

an only opened during entering or exiting the room. Cracks and fractures on the wall

need to be plastered. As the offices in Import Lane, KSAB use fresh air via Water

Cooling Package Unit (WPCU), it is important to shield the fresh air intake with

appropriate and adequate air pollution air pollution filter or absorbent.

Secondly, there are requirement to keep the indoor air well ventilated. Well ventilated

condition means a good air change, where there is input from the fresh air, circulating

the indoor setting and then exhausted the contaminated air to the outside. The best

way to maintain well ventilation is by opening the door and windows, which seems to

be contrast with the above statement regarding pollution source elimination, in case

of Import Lane, KSAB. Therefore, an engineering approach is used, with the

installation of air curtain. According to Paul and Tiwari (2014), air curtain which is

mounted on the of the doorway not only play a role as insect shield, but also can

prevent outdoor air infiltration, thus avoiding dust and air pollutants from entering the

indoor settings. This energy efficient technology helps in achieving a better indoor

comfort, thus supplying indoor fresh air for well and adequate ventilation.

The third approach in Maroni’s second strategies is to clean the air. There are

varieties of air cleaners in the markets, ranging from cheaper-table top instrument to

the expensive-whole floor coverage device. Most of the cleaners are only suitable in

wiping off particles in the air, but not the gases pollutants. Gases pollutant can only

be eliminated by diluting the concentration. One of the important indicator that

showing the air in one area is cleaned is through the absent of the dust on the ceiling

and wall surface as well as no webbing on the surfaces.

As for the last approach, controlling the exposure group, the occupant in the area

needs to located at the appropriate setting such as not under the exhaust sump or in

the contamination pathway of the room air, where this sump is design to collect all

contamination in the room air and returned it to the system. During this study, I have

noticed one RMC Officer in the office of Urusetia Kastam Import, Seksyen Jaminan

Bank, always keep tissues in her hand. From the interview done, I found that she has

been transferred to this Section in June 2014. Since then she experience sneezing,

eye and throat irritation and several other symptoms of Sick Building Syndrome. She

admitted since positioned in the section, she have taken days of medical leave due to

discomfort condition she experience. During visit to her desk, the DOSH Officer who’s

accompanied me during the first day of measurement, and I immediately found that

the table she’s position is in the pathway of contamination sump. A briefing has been

given to her and her colleague and suggesting her to adjust her position into the right

place.

Last but not least, regular monitoring is suggested to be conducted to ensure at all

time, the condition is not compromising the health status of the occupant.

Regarding the people

As the concentration of particulate matter in the indoor settings have no significant

difference with the outdoor particulate matter concentration, the officers from RMC as

well as OGA may face and breathing this contaminated air daily during working time.

Although wearing the personal protective equipment such as face mask may be

suitable during conducting the inspection in the bay, the best way to prevent adverse

effect is to implement the Maroni’s strategies in achieving good indoor air quality.

Conclusion

The study area, Inspection Bays and offices at Import Lane, KSAB, is a well known

and designated to be the pathway of all vehicles type which are involved in carrying

consignment (in this case, import consignments from Singapore into Malaysia). The

majority of the vehicles are heavy duty carriers or heavy weight carriers which of

them using diesel as fuel. From the monitoring results obtained, there are no

statistically significant differences in the particulate matters concentration between

the outdoor environments and in the indoor settings. The I/O ratio is vary from 0.748

for PM10, 0.754 (PM4), 0.766 (PM2.5) to 0.785 for PM1. The ratio is higher when the

diameter size of the particles is smaller. However, the difference of 20% is small

compared to the ability of the pollutants to travel, influenced by the air direction and

velocity. The concentration during peak hour usually in the evening up to quarter of

the night is found to be closer to the acceptable limit stipulate in relevant guideline.

The mitigation measures rely on the three components, regarding the vehicles as the

source of the pollution; regarding to the building; and regarding to the exposed group

itself. Regarding to the vehicles, the administrative approaches by regulating several

requirements may be the best to suit the elimination and isolation of the pollution

sources. Regarding the building and the exposed group, Maroni’s combination of

strategies may be the best to ensure well condition to promote good indoor air

quality. The use of air curtain, an engineering approach is strongly suggested to be

implemented to shield the outdoor pollutants from entering the indoor settings.

REFERENCES

Bailey, D. & Solomon, G. (n.d.). Pollution prevention at port: clearing the air. Environmental

Impact Assessment Review .

Brugge, D. et al. (2007). Near-highway pollutants in motor vehicle exhaust: A review of

epidemiologic evidence of cardiac and pulmonary health risks. Environmental Health

, 6 (23).

(2000). Chapter 7.3 Particulate Matter. In Air Quality Guidelines - Second Edition.

Copenhagen: WHO Regional Office for Europe.

Charron, A. & Harrison, R.M. (2005). Fine (PM2.5) and Coarse (PM2.5-10) Particulate Matter

on a heavily trafficked london highway: sources and processes. Environmental

Science Technology , 39 (20), 7768-7776.

Clark, N.N. et al. (1999). Field measurement of particulate matter emissions, carbon

monoxide, and exhaust opacity from heavy-duty diesel vehicles. Journal of the Air &

Waste Management Association , 49 (9), 76-84.

Colvile, R.N. et al. (2001). The transport sector as a source of air pollution. Atmospheric

Environment , 35 (9), 1537-1565.

Department of Environment Malaysia. (n.d.). Retrieved from Official Air Pollution Index of

Department of Environment: http://apims.doe.gov.my/apims/2012/index.php

Department of Environment Malaysia. (n.d.). Retrieved from New Smoke Emission Limit for

Diesel Vehicles Entering Singapore:

http://www.doe.gov.my/portalv1/en/info-umum/had-baru-pelepasan-asap-bagi-

kenderaan-diesel-yang-memasuki-singapura/314311

Department of Environment Malaysia. (n.d.). Retrieved from Air Quality:

http://www.doe.gov.my/portalv1/en/info-umum/kuality-udara/114

Department of Environment Malaysia. (n.d.). Retrieved from Indoor Air Quality:

http://www.doe.gov.my/portalv1/en/info-umum/english-indoor-air-quality/125

Estokova, A. & Stevulova, N. (2012). Investigation of suspended and settled particulate

matter in indoor air. InTech , 455-480.

Fairus M-D. et-al. (2011). Preliminary Assessment of Indoor Air Quality in Terrace Houses.

Health and the Environment Journal , 2 (2), 8-14.

Faiz, A et al. (1996). United Nations. Retrieved from Air Pollution from Motor Vehicles:

Standards and Technologies for Controlling Emissions:

http://www.un.org/esa/gite/iandm/faizpaper.pdf

Garshick, E et al. (2008). Lung Cancer and Vehicle Exhaust in Trucking Industry Worker.

Environmental Health Perspective , 116 (10), 1327-1332.

Garshick, E. et-al. (2012). Lung cancer and elemental carbon exposure in trucking industry

workers. Environmental Health Perspectives , 120 (9), 1301-1306.

Gillies, J.A. et al. (2001). On-road particulate matter (PM2.5 and PM10) emissions in the

Sepulveda Tunnel, Los Angeles, carlifornia. Environmental Science Technology , 35

(6), 1054-1063.

Grau-Bove, J. & Strlic, M. (2013). Fine particulate matter in indoor cultural heritage: a

literature review. Heritage Science , 1 (8).

GrayWolf Sensing Solutions. (n.d.). Retrieved from AdvancedSense DirectSense IAQ:

http://www.wolfsense.com/pdf/GrayWolf-Indoor-Air-Quality-IAQ-Meter-Brochure-

lo.pdf

GrayWolf Sensing Solutions. (n.d.). Retrieved from DirectSenseAir Air Velocity Meters:

http://www.wolfsense.com/air-velocity-meter.html

Industry Code of Practice on Indoor Air Quality 2010. (2010). Putrajaya: Department of

Occupational Safety & Health Malaysia.

Janssen, N.A.H. et al. (2001). Assessment of exposure to traffic related air pollution of

children attending schools near motorways. Atmospheric Environment , 35 (22),

3875-3884.

Jones, A.M. & Harrison, R.M. (2006). Estimation of emission factors of particle number and

mass fractions from traffic at a site where mean vehicle speeds vary over short

distances. Atmospheric Environment , 40 (37), 7125-7137.

Kaur, S. et al. (2007). Fine particulate matter and carbon monoxide exposure concentrations

in urban street transport microenvironments. Atmospheric Environment , 41 (23),

4781-4810.

Maroni, M. (1998). Health Effects on Indoor Air Pollutants and their Mitigation and Control.

Radiation Protection Dosimetry , 78 (1), 27-32.

Marr, L.C. et al. (2004). Vehicle traffic as a source of particulate polycyclic aromatic

hydrocarbon exposure in the Mexico City metropolitan area. Environmental Science

Technology , 38 (9), 2584-2592.

McCreddin, A. et al. (2013). Personal Exposure to Air Pollution in Office Workers in Ireland:

Measurement, Analysis and Implication. Toxics , 1, 60-76.

Michael J. Kleeman, et-al. (2000). Size and Composition Distribution of Fine Particulate

Matter Emitted from Motor Vehicles. Environmental Science & Technology , 24 (7),

1132-1142.

Ministry of Environmental Protection (MEP), National Development Reform Commission

(NDRC) & ministry of Finance, China. (2013). "Twelfth five-year plan" on air pollution

prevention and control in key regions (English translation). China: Clean Air Alliance

of China.

Ministry of Health Malaysia. (2013, July). Retrieved from Health Fact 2013:

http://www.moh.gov.my/images/gallery/publications/HEALTH%20FACTS

%202013.pdf

Moller, K.L. et al. (2014). Occupational exposure to ultrafine particles among airport

employees - combining personal monitoring and global positioning system. PLOS

ONE , 9 (9).

Muhamad A. et-al. (2000). Air quality in Malaysia: Impacts, management issues and future

challenges. Respirology , 5 (2), 183-196.

N.B.A. Wahid et-al. (2014). Source identification of particulate matter in a semi-urban area of

Malaysia using multivariate techniques. Bulletin Environmental Contamination

Toxicology , 92, 317-322.

Naeher, L.P. et al. (2000). Particulate Matter and Carbon Monoxide in Highland Guatemala:

Indoor and Outdoor Levels from Traditional and Improved Wood Stoves and Gas

Stoves. Indoor Air , 10, 200-205.

Norela S. et-al. (2005). Concentration and Composition Of PM10 in Outdoor and Indoor Air

in. Sains Malaysiana , 34 (2), 43-47.

Nur Zafirah M.S. & Marzuki I. (2011). Indoor and Outdoor Relationships of Respirable

Suspended Particulate Matter at Primary Schools in Kuala Terengganu, Malaysia.

Indoor and Built Environment .

Paul, A. & Tiwari, A.C. (2014). Performance Analysis of Air Curtain: A Review of CFD

Approach. Corona Journal of Science and Technology , 3 (1), 1-7.

S.C. Lee & M. Chang. (2000). Indoor and outdoor air quality investigation at schools in Hong

Kong. Chemosphere , 41 (1-2), 109-113.

San Joaquin Valley Air Pollution Control District. (n.d.). Retrieved from Particulate Matter

(PM) Sources:

http://www.valleyair.org/Air_Quality_Plans/AQ_plans_PM_sources.htm

Sheesley, R.J. et al. (2008). Assessment of diesel particulate matter exposure in the

workplace: freight terminal. Journal Environmental Monitoring , 10, 305-314.

Thorpe, A. & Harrison, R.M. (2008). Sources and properties of non-exhaust particulate matter

from road traffic: a review. Science of the Total Environment , 400 (1-3), 270-282.

U.S. Environmental Protection Agency. (n.d.). Retrieved from Air Quality Management Online

Portal: http://www.epa.gov/airquality/aqmportal/management/monitoring.htm

U.S. Environmental Protection Agency. (n.d.). Retrieved from Quality Assurance Handbook

for Air Pollution Measurement System Volume II Ambient Air Quality Monitoring

Program: http://www.epa.gov/ttnamti1/files/ambient/pm25/qa/QA-Handbook-Vol-

II.pdf

Wahlina, P. et al. (2001). Experiment studies of ultrafine particles in streets and the

relationship to traffic. Atmospheric Environment , 35 (Supp. 1), S63-S69.

Weijers, E.P. et al. (2004). Variability of particulate matter concentrations along road and

motorways determined by a moving measurement unit. Atmospheric Environment ,

38 (19), 2993-3002.

WHO Regional Office of Europe. (2000). Retrieved from The Right to Healthy Indoor Air:

http://www.euro.who.int/__data/assets/pdf_file/0019/117316/E69828.pdf

World Health Organization. (n.d.). Retrieved from Ambient (outdoor) air quality and health:

http://www.who.int/mediacentre/factsheets/fs313/en/

Xianglu Han, Luke P. Naeher. (2006). A review of traffic-related air pollution exposure

assessment studies in the developing world. Environment International , 32 (1), 106-

120.

Yu-Hsiang, C. et al. (2012). Temporal variations in airborne particulate matter levels at an

indoor bus terminal and exposure implications for terminal workers. Aerosol and Air

Quality Research , 12, 30-38.

Zhang, J. & Smith, K.R. (2003). Indoor air pollution: a global health concern. British Medical

Bulletin , 68, 209-225.

Zhu, Y. et al. (2002). Study of ultrafine particles near a major highway with heavy-duty diesel

traffic.

mohdruhaizie.commohdruhaizie.com/.../mohdruhaizie_fyp_fullreport.docx · web viewfinal year...

Documents