Current Air Quality Trend In Malaysia

Dimitriou and Christidou (2007) mentions air pollution is one of the most pressing global environmental problems that threaten the wellbeing of living organisms, leading to a loss of biodiversity or disrupting the function of the environment as a system. Air pollution occurs as a consequence of natural processes as well as human activity (anthropogenic). Examples of natural causes of air pollution include volcanic eruptions, forest fires and windblown dust. Anthropogenic air pollution from sources like motor vehicles and industries continues to be a serious harm to human health and welfare is more likely, namely the more densely populated urban areas. The health effects of air pollution have been reported in research studies over the past 30 years. These effects include respiratory diseases such as asthma, cardiovascular diseases, changes in lung function, and death.

Colls (1997) reported particles in the atmosphere primary or secondary, solid or liquid. They come into the atmosphere, and leave it again by a wide variety of routes. Particulate matter is characterized by its physical and chemical properties Nader (1975). In addition, particle size and particle composition are characteristic that play a significant role in the assessment of health effect. In response to this information, regulatory agencies with a mandate to protect public health must now consider how to implement monitoring networks that will allow measuring the particulate matter concentration.

In recent years, a increasing of number of monitoring system for particulate matter (PM) are available and are wide ranging in type, cost, flexibility and accuracy. According to Kingham et al. (2006), accurate and reliable monitoring of PM aerosol in the respirable size fraction (<10 µm aerodynamic diameter PM10) is now legislative requirement of local authorities in many developed world countries. One of the essential prerequisites for monitoring requirements is the availability of a cost effective monitoring system that has been demonstrated to be reliable and accurate in its application to stationary source emissions.

In 2001, Chung et al pointed about traditional monitoring networks (Continuous Aerosol Mass Monitor, Integrating Nephelometer, Tapered Element Oscillating Microbalance) for airborne particulate matter. A small number of past studies have evaluated the tapered element oscillating microbalance (TEOM) and a series of manual gravimetric methods (Allen et al., 1997, Ayers, 2004, Cyrys et al., 2001, Hauck et al., 2004, Williams et al., 2000) but fewer still have compared other commercial monitors (Baldauf et al., 2001, Chung et al., 2001, Heal et al., 2000, Monn, 2001, Salter and Parsons, 1999).

CURRENT AIR QUALITY TREND IN MALAYSIA

There are 52 National Air Quality Monitoring Stations (AQMS) in Malaysia, function to monitor continuously 5 major pollutants, namely Particulate Matter (PM10), Ozone (O3), Sulphur Dioxide (SO2), Nitrogen Dioxide (NO2) and Carbon Monoxide (CO). For the northern region of Malaysia (Perlis, Kedah, Pulau Pinang and Perak), the overall air quality levelwas lies between good to moderate. However, there are curtain places (Tanjung Malim, Alor Star and Sungai Petani) recorded unhealthy level of the day especially in the mid of the day till late afternoon due to high concentration of ground level ozone (O3). In tanjung Malim, one unhealthy day was recorded due to high level of particulate matter (PM10)

Air Pollutant Index (API) system were used in reporting the air quality status in Malaysia. The API compute from the monitoring of Ground level Ozone (O3), Carbon Monoxide (CO), Nitrogen Dioxide (NO2), Sulphur Dioxide (SO2) and Particulate Matter of less than 10 microns in size (PM10). Air quality status can be categorized in five main level (good, moderate, unhealthy, very unhealthy and hazardous as in Table 1.1.

Table 1.1 Malaysia : Air Pollution Index (API)

(Malaysia Environmental Quality Report 2011, DoE)

API

Air Quality Status

DoE in Malaysia Environmental Quality Report 2011 highlights the annual average of PM10 was 43m3 , but was slightly increased compared to 2010 (39m3 ). However, for both year (2010 and 2011) value still below the Malaysian Ambient Air Quality Guidelines value (50m3 ). The trend of the annual average levels of PM10 concentration in the ambient air between 1999 and 2011 complied with the Malaysian Ambient Air Quality Guidelines as shown in Figure 1.1 and Figure 1.2 shows the trend based on land use categories (Urban, Sub Urban, Background and Rural).

MONITORING METHODS AND INSTRUMENTS

The underway monitoring of airborne particulate matter in the ambient atmosphere is mainly for determination of the mass of the particle. The methods used for monitoring of concentration of PM can differ and are very dependent upon the aim of monitoring, sites, monitoring problem and resource that available during monitoring period. Usually, monitoring is to determine the concentration of total suspended particulate (TSP) and suspended particulate matter (SPM) have become outdated with the awareness that PM effects varies depending on sizes of the particle. QUARG (1996) pointed that the latest method of monitoring (gravimetric and direct reading method) are designed to determine the concentration of particle in the different sizes (PM10 and PM2.5). Table 1.2 displays the examples of the instrument for PM10 monitoring and the detection methods.

Table 1.2 Examples of instruments used in PM monitoring

Instrument

Principle of detection

Beta Attenuation Monitor (BAM)

The beta ray sources used in BAM are 14C. Directly measured the particle based on relationship between beta ray attenuation to particle mass.

Depends on the near exponential decrease in the total number of beta particle transmitted through a thin sample as the density increase (William et al., 1993)

The gravimetric method that only the mass of particle can be affect the detector not by the size of distribution, physical size, shape or either by chemical composition (Chow et al., 1996)

Tapered Element Oscillating Microbalance (TEOM)

Tapered hollowed channel will act as a gateway where the particles are collected on a filter.

For minimum thermal expansion that occurred at the tapered channel, the sample area is maintained at 50°C. Thermal expansion may affect the oscillation frequency and might be reduce the total amount of particle bound water.

DustTrak 8520

Hands carry instrument and highly portable direct reading monitor. Using light scattering laser to detect the particles.

Particles scattered the light which is from laser diode drawn through a constant stream. Liu et al., (2002) mentions the amount of light scatter find out the particles mass concentration.

PROBLEM STATEMENT

In Malaysia, PM10 monitoring was conducted by Alam Sekitar Malaysia Sdn. Bhd. (ASMA). Md Yusof et al (2010) lists two instruments used for monitoring are high volume sampler (HVS) and beta attenuation monitor (BAM). BAM is the standard instrument used by Department of Environment (DoE) to measure particulate matter in 51 monitoring station in Malaysia.

Air quality of these new areas cannot be monitored and observed due to the lack of monitoring stations of air quality. To develop these new monitoring stations, definitely it will be costly and need good maintenances. Additionally, air quality at the rural areas also cannot be monitored. Therefore, a new alternative instrument such as Direct Reading Monitors (DRM) will enable air pollutants to be monitored more comprehensively. Even though DoE has set up their monitoring station, the number of monitoring stations is limited. With the use of simple instruments and cost effective, the air quality in areas without monitoring stations can be monitored and assessed.

For this study, direct reading monitor (DRM) was used to monitor PM10 concentration at selected stations. However, PM10 concentration recorded using DRM and BAM was different. This is due to different detection method between both instruments (DRM used laser and BAM used beta ray) and response time for DRM was set to one minutes, while BAM records hourly PM10. In addition, the mobile factor that is owned by DRM is also affecting the reading. Therefore, an appropriate coefficient needed to make sure the reading obtained from the DRM is the same as the reading derived from the BAM.

OBJECTIVES

The objective of this project is:-

To estimate coefficient that relates DRM and BAM by using regression techniques.

To investigate the best coefficient based on performance indicator.

To determine the influence of meteorology on PM10 concentration.

SCOPE OF STUDY

In Malaysia, Beta Attenuation Monitor (BAM) is the standard instrument used by DoE to measure particulate matter in 52 monitoring stations. This instrument automatically measures and records hourly particulate mass concentration in ambient air. It uses beta ray attenuation to calculate collected particle mass concentration units of µg/m³. For this study, Direct Reading Monitor (DRM) was used to monitor PM10 concentration at Air Quality Monitoring Station (AQMS) conducted by Alam Sekitar Malaysia (ASMA). The station selected for this research is Prai and Seberang Jaya. Both stations are situated in the north part of Peninsular Malaysia.

They are many researches comparing the mass concentration results of the BAM and gravimetric methods. Salminen and Karlsson (2003) reported the agreement between PM10 concentration measured by BAM and gravimetric method. PM10 concentration recorded by the DRM was compared with data monitored using BAM provided by DoE.

Three method of linear regression was used to investigate the relationship between the DRM and BAM monitoring record which is method of ratio, method of quartile and method of quantile. Performance indicators were used to evaluate the goodness of fit for the ratio,quartile and quantile method to determine which method is the best.

THESIS OUTLINE

This thesis has a five important parts and brief outlines of this thesis follows. Chapter one gives an introduction about air quality monitoring in Malaysia, sources of air pollution in Malaysia. This thesis also stated the problem statement, objectives, scope of study and concludes with thesis outline.

Chapter 2 discussed about the literature review of the research area (particulate matter 10, measurement for PM10), and also review that determines to what extent the issues or research part has been investigated. From this chapter, a good view and knowledge about research area can be undertaken.

Chapter 3 describes the methodologies that have been used in this research. The area of study, setting and sitting of instrument, monitoring of PM10 using DRM and BAM, and method to analyzing the monitoring records also discussed in this chapter.

Chapter 4 presents the result from data analysis in the form of graphical techniques and table, for all three methods, performance indicator and meteorological effect with the discussion.

Chapter 5 gives a general discussion of this research. The comparison of three methods was discussed and to determine which method is the best using performance indicator. This chapter also discussed the best conclusions of this research and listed of recommendations for future research.

CHAPTER 2

LITERATURE REVIEW

2.1 INTRODUCTION

Sherman (2003) defined air pollution as the presence of undesirable levels of physical or chemical impurities. Many organization such as the World Health Organization (WHO, 1999) recognized particulate matter (PM), carbon monoxide (CO), nitrogen dioxide (NO2), ozone(O3), lead (Pb) and sulfur dioxide (SO2), as classical pollutants presenting a hazard to sensitive populations. Air pollution now becomes an increasing source of environmental degradation in the developing nations of East Asia (Alles, 2009).

The air pollution in Malaysia has not reached a critical level as in other metropolitan areas in Asia, like Jakarta or Manila. (Malaysian German Technical Cooperation, 2000). However; even outside extreme haze periods, pollution levels increased despite tight regulations and this is added by the increase in the number of vehicle, distance travelled and growth in industrial production.

Air quality in Malaysia is a major concern as the nation forged ahead to become an industrialized nation by the year 2020. The Malaysian Air Pollution Index (API) is obtained from the measurement of PM10 and several toxic gases such as SO2, CO, NO2, and O3. The air quality status in Malaysia is determined accordingly to API which indicates the level of pollution in the atmosphere. The API system of Malaysia closely follows the Pollutant Standard Index (PSI) system of the United States of America.

According to Department of Environment, based on the Air Pollutant Index (API), the overall air quality for Malaysia in 2010 was between good to moderate levels most of the time. The overall number of good air quality days increased in 2010 (63 percent of the time) compared to that in 2009 (56 percent of the time) while remaining 36 percent at moderate level and one percent at unhealthy level. However, peatland fires resulting in transboundary air pollution that occurred in the Southern Asean region in the month of October resulted in a short spell of haze episode in the southern part of Peninsular Malaysia (DoE, 2009 & DoE, 2010)

DoE also reported that the overall air quality of the northern region of the West Coast of Peninsular Malaysia (Perlis, Kedah, Pulau Pinang and Perak), was between good to moderate most of the time. However, Tanjung Malim and Tasek recorded four unhealthy days and one unhealthy day, respectively. The pollutants of concerned were ground level Ozone (O3) and PM10.

2.2 AIR QUALITY MONITORING IN MALAYSIA

In order to ascertain the quality of the environment in Malaysia, the Department of Environment (DoE) regularly monitor the air quality. The air quality monitoring, which involves measurements of total suspended particulates, atmospheric lead and dust fallout, are conducted at 52 monitoring stations (Figure 2.1 and 2.2) categorised as industrial, urban and sub urban areas (DoE, 2010). In addition to the 52 stations in the National Continuous Air Quality Monitoring Network, manual air quality monitoring stations using High Volume Samplers were also established at 14 different sites for measuring total suspended particulates, particulate matter (PM10) and heavy metals such as lead.

A continuous automatic monitor which gives instantaneous measurements of gaseous pollutants such as CO, SO2, oxides of nitrogen and ozone, as well as suspended particulate matter and total hydrocarbon used as the monitoring equipments by the DoE to assess air quality (Abdullah, 1995).

The air quality status is reported in terms of Air Pollutant Index (API). The air pollutants used in computing the API are ground level ozone (O3), carbon monoxide (CO), nitrogen dioxide (NO2), sulphur dioxide (SO2) and particulate matter of less than 10 microns in size (PM10). The API is categorized as good, moderate, unhealthy, very unhealthy and hazardous.

2.3 SOURCERS OF PM10

The US EPA defines particulate matter (PM) as a mixture of solid particles and liquid droplets found in the air. PM can be in sizes or colors large or dark enough to be observed or it can be so small that an electron microscope is required to distinguish it. According to Fierro (2000), coarse particles (PM10) have an aerodynamic diameter between 2.5µm and 10µm. They are formed by mechanical disruption (e.g. crushing, grinding, abrasion of surfaces), evaporation of sprays, and suspension of dust. PM10 particles are small enough to be inhaled and accumulate in the respiratory system (Colls, 1997).

Particulate matter can come from many sources. Generally, any activity which involves burning of materials or any dust generating activities are sources of PM. Some sources are natural, such as volcanoes and water mist (Bates, 1995). PM is introduced to the air through both natural and human causes (Harrisonu & Yin, 2000). PM from specific sources typically follow short term and long term (seasonal) trends (Yatin et al. 2000). For example, space heating generates more combustion related PM emissions during the cold seasons while, at the same time, snow cover can inhibit PM emissions from the soil.

Quality of Urban Air Review Group (1996), published the report in which they describe that primary particles are those directly emitted to the atmosphere from sources such as road traffic, coal burning, industry, windblown soil and dust and sea spray. On the other hand, secondary particles are particles formed within the atmosphere by chemical reaction or condensation of gases, and the major contributors are sulphate and nitrate salts formed from the oxidation of sulphur dioxide and nitrogen oxides respectively.

The primary sources of PM in Malaysia, are motor vehicles diesel trucks, industrial emissions, agricultural, slash and yard waste burning, and even exhaust from lawn mowers and boats (Department of Environment, Malaysia, 2010). PM concentrations tend to be especially high in area with greater population density, nearby industries or agriculture, or where local topography or weather conditions contribute to air stagnation.

2.3.1 Traffic

Vehicular particle emissions are the result of a great many processes, an example combustion products from fuel and oil, wear products from brake linings, tyres, bearings, car body and road material, and the resuspension of road and soil dust (Laschober et al. 2004). Traffic is an effective source of both fine and coarse mode primary particles, condensable organic gases, and a major source of nitrogen oxides that then form secondary nitrate aerosols. Particles of condensed carbonaceous material are emitted mainly by diesel vehicles and poorly maintained petrol vehicles (Vardoulakis et al. 2003). Diesel exhaust particles have been shown to display a multimodal size distribution (Kerminen et al. 1997) and are mainly carbonaceous agglomerates below 100 nm in diameter, whereas particles emitted by gasoline vehicles are also mainly carbonaceous agglomerates but considerably smaller, ranging from 10 to 80 nm (Morawska and Zhang 2002). Particulate matter originating from traffic can be present at elevated concentrations especially during high traffic density and poor dispersion conditions, e.g. in street canyons, which can lead to high human exposures to traffic-related pollutants (Vardoulakis et al. 2003). Identification of traffic related particulate matter in source apportionment studies has become difficult due to phasing out of Pb as an additive to gasoline. Elements that have often been associated with vehicular emissions include Cu, Zn, Pb, Br, Fe, Ca and Ba (Huang et al. 1994, Cadle et al. 1997, Kemp 2002, Morawska and Zhang 2002, Sternbeck et al., 2002). Emissions of many metallic elements from vehicular sources are mainly due to non exhaust emissions, examples from the wearing of tyres, brakes and other parts of vehicles (Sternbeck et al. 2002, Adachi and Tainosho 2004, Laschober et al. 2004, Lough et al. 2005). In addition to road traffic, emissions from the main and auxiliary engines of ships can be a significant source of particulate matter and associated elements such as V and Ni (Lyyränen et al. 1999) at certain locations (Ohlström et al. 2000, Colvile et al. 2001, Isakson et al. 2001).

2.3.2 Stationary sources

The most significant stationary combustion sources include energy production facilities such as municipal power plants, waste incineration, and residential combustion. Several industrial processes, such as iron and steel production, also involve combustion of fossil fuels or biomass for generating power and heat needed for the process. Most of these sources are considered point sources, although smaller and more widespread sources such as residential combustion could also be considered as an area source. Physical and chemical characteristics of the particles emitted from these source categories depends on the combustion process itself, and the type of fuel burnt (solid, liquid, or gas). Combustion processes and properties of particulate matter emitted from these sources have been comprehensively reviewed by Morawska and Zhang (2002). The major industrial processes include factories processing metals and chemicals, materials handling, construction and mining. Particulate matter from these sources are partly released as fugitive emissions, which are not collected and released in a controlled manner, but emitted from a variety of points and areas connected to a process (Seinfeld and Pandis 1998). Chemical and physical properties of fugitive emissions depend on the processes by which they are emitted. Since the bulk of most trace metals are nowadays emitted from industrial processes, their concentrations are spatially heterogeneous and subsequently, their measurement is quite sensitive in terms of location; however, the reported concentrations of trace metals in major cities demonstrate rather similar levels of trace metals (Harrison and Yin 2000).

PM10 CHARACTERISTIC.

PM is characterized by its physical, chemical and optical properties. The quality of air that we breathe in every second determine by the amount of particulate matter in it. These particulate matters measure by their particles size. Those with the particles size less than 10 micron (PM10) is used to monitor the air quality which in turn is related to the health problems of the workers or public at large (Alias et al., 2007). The most important characteristic of particulate matter (PM) is the particle size. This property has the greatest impact on the behavior of particulate matter in control equipment, the atmosphere, and the respiratory tract. Particles of importance in air pollution control span a broad size range from extremely small (0.01 micrometer) to more than 1,000 micrometers (US EPA, 2010). As a frame of reference, a human hair has a diameter of approximately 50 micrometers.

The suspended particles vary in size, composition and origin. It is convenient to classify particles by their aerodynamic properties because, (a) these properties govern the transport and removal of particles from the air, (b) they also govern their deposition within the respiratory system and (c) they are associated with the chemical composition and sources of particles (WHO, 2003).

2.4.1 Physical Characteristic

The physical attributes of airborne particulates include mass concentration and size distribution. the size is from a few nanometers (nm) to ten of micrometers (µm) in diameter. Size is the single most important determinant of the properties of particles and it has implications on formation, physical and chemical properties, transformation, transport, and removal of particles from the atmosphere. Ambient levels of mass concentration are measured in micrograms per cubic meter (μg/m3), size attributes are usually measured in aerodynamic diameter. Particulate matter (PM) exceeding 2.5 microns (μm) in aerodynamic diameter is generally defined as coarse particles, while particles smaller than 2.5 microns (PM2.5) are called fine particles (World Bank Group, 1998). Particles of any substances that are less than 10 or 2.5 micrometres diameter. Particles in this size range make up a large proportion of dust that can be drawn deep into the lungs. Larger particles tend to be trapped in the nose, mouth or throat. The concentration and other characteristics of suspended particulate matter are determined by the presence and activity of sources. Once formed, particles change their size and composition by condensation or evaporation, by coagulating with other particles or by chemical reactions (Seinfeld and Pandis 1998). Pohjola et al., (2000), found that meteorological factors such as wind speed and direction, temperature, amount of precipitation, and the height of the atmospheric boundary layer, are most important in governing the concentration variations of particulate matter. The highest PM concentrations are often reported during stable meteorological conditions such as inversion with low wind speeds (Pohjola et al. 2004). Also the physical and chemical processes affecting the particles are regulated to a great extent by meteorological factors.

2.4.2 Chemical Characteristic

The chemical composition of the particulate matter is also important. The chemical composition of PM is highly variable due to pollution sources, chemical reactions in the atmosphere, long-range transport effects and meteorological conditions. Absorption and heterogeneous nucleation of vapor phase pollutants onto existing particles can create toxic particulate matter (US EPA, 2010). The chemical properties vary depending on sources of particles. It is important to note that particulates are not one particular chemical substance but a classification of particles by size rather then chemical properties.The acid component of particulate matter, and most of its mutagenic activity, are generally contained in fine particles, although some coarse acid droplets are also present in fog. Particles interact with various substances in the air to form organic or inorganic chemical compounds. The most common combinations of fine particles are those with sulphates (World Bank Group, 1998). The relative abundance of the major chemical components, termed as ‘bulk chemical composition and also about trace element and strong acid contents was reviewed in the studies of Harrison and Jones (1995) and Harrison and Yin (2000). In addition to the bulk composition, Harrison and Yin (2000) also discussed trace element and strong acid contents. In the United States, sulphate ions account for about 40% of fine particulates and may also be present in concentrations exceeding 10 μg/m3 (US EPA, 1982).

2.5 PARTICULATE MATTER HEALTH EFFECT

There are a very limited number of studies that relate air pollution to its health impact in Malaysia. The lack of data gathering for environmental epidemiological analysis makes it difficult to estimate the health impact of air pollution (Afroz et al., 2003). Whilst epidemiological studies have consistently demonstrated adverse effects of particulate matter exposure on human health, the mechanism of effect is currently unclear (Harrisonu & Yin, 2000).

The US Environmental Protection Agency’s 1996 Air Quality Criteria for Particulate Matter reviewed the physiologic, toxicology, and epidemiologic studies related to the inhalation, deposition and health effects of PM exposures (US EPA, 1997). Some research has identified several plausible biological mechanisms for both the initial pulmonary injury and the consequent systemic effects (Neas, 1999). The respiratory system is the major route of entry for airborne particulates. The deposition of particulates in different parts of the human respiratory system depends on particle size, shape, density, and individual breathing patterns (mouth or nose breathing) (World Bank Group, 1998).

In adults, PM exposure was associated with increased incidence of respiratory symptoms, transient decrements in pulmonary function levels, and the onset of chronic pulmonary disease in adults (Neas, 1999). Seaton (1995), has identified several plausible biological mechanisms for both the initial pulmonary injury and the consequent systemic effects following PM exposure and the initial pulmonary injury may be related to one or more properties of PM and its constituents including physical, chemical and biological characteristics. Several hypotheses have been proposed to explain the path physiology of PM induced health effects. The most obvious mechanism involves the reduction in pulmonary function in response to the pulmonary inflammation. In the hypoxia hypothesis, the susceptible population consists of individuals with severe respiratory disease whose pulmonary reserve capacity is already near the minimum compatible with life. Exposure to PM further lowers their pulmonary function levels and results in emergency hospitalization and death (Neas, 1999)

Children are especially susceptible to particulate matter pollution for several reasons, their respiratory systems are still developing, they breathe more air (and air pollution) per pound of body weight than adults and they’re more likely to be active outdoors. Older adults are also more likely to be affected by particulate matter pollution, possibly because they are more likely to have chronic heart or lung diseases than younger people. In addition, people who have heart or lung disease, such as congestive heart failure, angina, chronic obstructive pulmonary disease, emphysema or asthma, are likely to experience health effects earlier and at lower particulate matter pollution levels than healthy people (American Lung Association, 1996).

The capacity of particulate matter to produce adverse health effects in humans depends on its deposition in the respiratory tract. Particle size, shape, and density affect deposition rates. The most important characteristics influencing the deposition of particles in the respiratory system are size and aerodynamic properties. In Malaysian Ambient Air Quality Guidelines (MAAQG), the level of PM10 concentrations are, 150 micrograms per cubic meter (µg/m3) for 24 hour and 50 micrograms per cubic meter (µg/m3) for the annual (Department of Environment, Malaysia, 2010).

Some tiny pieces of particulate matter, PM10, are small enough to pass from our lungs to our bloodstream. PM can alter the body’s defense systems against foreign materials, damage lung tissues, aggravate existing respiratory and cardiovascular disease, and can lead to cancer. In some cases, PM exposure can even lead to premature death. Adverse health effects have been associated with exposures to PM over both short periods (such as a day) and longer periods (a year or more). The people who are most at risk are people with asthma, influenza, lung, heart, or cardiovascular disease, the elderly, and children. The human immune system developed in a time and environment where dust was made of large particles. Humans have developed a means of protecting themselves against these large particles. Particles larger than 10 microns generally get caught in the nose and throat, never making it as far as the lungs. Unfortunately, more recent human activity has created many particles that are much smaller, which can make it past our natural defenses, and can enter our systems (Fierro, 2000).

The size of particles is directly linked to their potential for causing health problems. Most concerned about particles that are 10 micrometers in diameter or smaller because those are the particles that generally pass through the throat and nose and enter the lungs. Once inhaled, these particles can affect the heart and lungs and cause serious health effects. EPA groups particle pollution into two categories:

“Inhalable coarse particles,” such as those found near roadways and dusty industries, are larger than 2.5 micrometers and smaller than 10 micrometers in diameter.

“Fine particles,” such as those found in smoke and haze, are 2.5 micrometers in diameter and smaller. These particles can be directly emitted from sources such as forest fires, or they can form when gases emitted from power plants, industries and automobiles react in the air. (U.S Environmental Protection Agency).

2.6 MEASUREMENT FOR PARTICULATE MATTER (PM10)

2.6.1 Reference Method

The US Environmental Protection Agency (EPA) has designated a handful of instruments as Federal Reference or Federal Equivalency Methods (FRM and FEM, respectively) for the monitoring of particulate matter. In Europe as well as in the US, manual gravimetric methods have been defined as reference methods (CEN, 1998; US Government, 1991). These FRM also know as a filter based instruments. These filter based instruments (including the BGI PQ200 and the RAAS2.5 single and multi day sampler) report a cumulative average over a 24-hour period. While filter-based instruments have proven to be robust and accurate for the study of the detailed nature of airborne particles during intensive experiments, they have several drawbacks when used in a routine monitoring network for regulatory purposes.

Mass concentrations for the FRM sampler were obtained from gravimetric analysis of the filters and the sample volume which is logged by the sampler throughout the sampling period. In another major study, Koistinen et al. (1999) and Yanosky and MacIntosh (2001) reported the air density during the weighing session, nominal density of calibration masses, and density of each filter type were used to correct the balance readings for the buoyant effect of air.

Chung et al., (2001) highlight, the chief disadvantage associated with filter based samplers for PM is the fact that the instrument does not provide information in real time. Often weeks or even months pass between the time when samples are collected and when PM data become available. This time lag makes it impossible for regulatory agencies to react quickly to changing air quality. These data also are critical when investigating health effects of PM, as acute exposures to elevated levels of PM have been linked to multiple adverse health outcomes (Barrett et al., 2006).

McNamara et al.,(2011) conclude that it is impractical and expensive to allocate a FRM or FEM sampler to measure indoor residential PM levels.

2.6.2 Equivalent Method

Automatic online monitors for particulate matter with an aerodynamic diameter up to 10 µm (PM10) (TEOM, beta attenuation) are widely used in air pollution monitoring networks. However, the data cannot always be considered equivalent to the manual gravimetric reference method, which is required in Europe as well as in US for compliance measurements (Gehrig et al., 2005).

McNamara et al., (2011) traces the use of FRM or FEM samplers to monitor residential indoor or outdoor air for health based research studies is impractical, as such instruments that are large, loud, and expensive. However, to measure PM variability in the ambient environment, Federal Equivalent Method (FEM) samplers such as the MetOne BAM 1020 can provide hourly PM monitoring, thereby allowing for a more comprehensive exposure assessment. FEM also know as real time monitor.

Due to the time consuming analytical procedure, several days are needed from the sampling until the result is available when using the FRM. Therefore, no online information about PM concentrations can be obtained from measurements with the standard reference methods. These disadvantages could be avoided with automatic online monitors, which are already in operation in many monitoring networks. The measurement principles of these monitors are in general based either on tapered element oscillating microbalances (TEOM) or beta attenuation monitor (BAM).

In addition, monitors provide a far better time resolution, thus, giving information also about the variability of the PM concentrations during the day. However, the data, which are obtained with these automatic monitors, cannot be considered equivalent to the reference methods because of the significantly different measurement methodologies compared to gravimetric (Gehrig et al., 2005). There are many reports about the differences and measurement methodologies, by Ayers et al. (1999), Charron et al. (2004) and Muir (2000).

However, at very low background concentrations, Chang et al. (2001) and Salminen and Karlsson (2003) observed a quite good comparability of beta-attenuation monitors with gravimetry during dry conditions, but higher monitor readings during periods with high humidity. Chung et al., (2001) compared the response of several real times continuous PM monitoring instruments to measurements made using standard filter based sampling techniques.

2.6.3 Alternative Method

The TSI, Inc. Model 8520 DustTrak Aerosol Monitor (DustTrak) is a small and portable direct reading aerosol monitor that is intended for indoor or outdoor use (Yanosky et al., 2001).

Due to their portability and ease of use, light scattering instruments are more appropriate for use in indoor air sampling studies, but the manufacturer recommended these instruments that a correction factor be applied when assessing source specific conditions (McNamara et al., 2011).

A Comparison of real time instruments used to monitor airborne particulate matter done by Chung et al., (2001) claims that based on instrument performance, the BAM, the integrating nephelometer, and the continuous aerosol mass monitor (CAMM) appear to be suitable candidates for deployment in a real time continuous PM monitoring network in central California for the range of winter conditions and aerosol composition encountered during the study.

The integrating nephelometers used to measured particle concentrations by intersecting an aerosol sample with light at several wavelengths in the visible range. It should be noted that the greatest problem associated with the use of nephelometers in routine PM monitoring networks is the variability of light scattering by particles with different sizes and compositions. The uncertainty associated with nephelometer measurements increases when a wide distribution of particle sizes is sampled, and the proportionality constant used to convert nephelometer scattering data to airborne particle mass concentrations may need to be adjusted when aerosol size distributions and composition differ significantly from the size and composition of the calibration aerosol (Rabinoff et al., 1973, Anderson et al., 1996, Reed et al., 1981).

2.6.4 Previous Study in Comparison of Measurement for PM10

Accurate and reliable monitoring of particulate matter (PM) aerosol in the respirable size fraction (10 mm aerodynamic diameter, PM10) is now a legislative requirement of local authorities in many developed world countries (Kingham et al., 2005). A number of monitoring systems for PM are available and are wide ranging in type, cost, flexibility and accuracy. A continuing research and development problem for the manufacturers of such instruments and their users is the need to accurately record the true mass of the aerosol in ambient air over a given time period. The mass, size spectra and chemistry of urban PM aerosol are not fixed over time. Their physical and chemical properties are sensitive to environmental variables (Seinfeld, 2004).

The Department of Environment sampling work using BAM 1020 is the method currently using for air monitoring in Malaysia. There is no studies have been conducted before to compare between BAM and E-sampler. The BAM method is widely used for continuous monitoring of SPM in Japan (Mizuno and Kaneyasu, 1994, Watanabe et al., 2000) and worldwide (Chueinta and Hopke, 2001, Arends et al., 2000, Salminen and Karlsson, 2003, Chang and Tsai, 2003, Hauck et al., 2004). The mass concentration of atmospheric aerosols is measured directly, using the relationship of beta ray attenuation to particle mass.

In the gravimetric method, atmospheric particles are collected on a filter. The low volume air sampler method is the standard method, though a high volume air sampler may also be used. With the gravimetric method, a collection period of 24 hour to several weeks is necessary, due to the sensitivity of the microbalance used to weigh the filters. Therefore, the gravimetric method is not suitable for the observation of short term concentration changes. On the other hand, the BAM can observe the variation of concentration every hour. However, there is a drawback in using BAM the atmospheric aerosol cannot be collected for analysis of its chemical composition. To investigate the aerosol characteristics and sources, a long-term air sample must be collected. There is much research comparing the mass concentration results of the BAM and gravimetric methods. Several papers show that results differ between the methods (Arends et al., 2000, Watanabe et al., 2000, Salminen and Karlsson, 2003).

Several studies have been conducted to determine if the DustTrak, TSI, (Shoreview, MN), a real-time aerosol monitoring instrument may be used to estimate DPM concentrations contained in airborne particulates as compared to the accepted pump-filter methods for PM1, PM2.5, PM10 and Respirable DPM concentrations. This study is to determine if the TSI DustTrak is adequate for use as an additional monitoring instrument providing real-time concentrations that can be used to ensure exposure controls are adequate in an underground mining work environment.

A small number of past studies have evaluated the tapered element oscillating microbalance (TEOM) and a series of manual gravimetric methods (Allen et al., 1997, Ayers, 2004, Cyrys et al., 2001, Hauck et al., 2004, Williams et al., 2000) but fewer still have compared other commercial monitors (Baldauf et al., 2001, Chung et al., 2001, Heal et al., 2000, Monn, 2001, Salter and Parsons, 1999). There have been little advantages in some of the portable instruments that have emerged in recent years including the MiniVol, DustTrak and others. These and similar instruments have potentially cost effective, small in size and operational advantages over the FRM and equivalent methods.

(Cheng et al., 2008) compared PM10 and PM2.5 mass concentrations inside trains and on underground station platforms in Taipei using a TSI Dust Trak monitor (TSI Model 8520). (Tasik et al.,2012) reported, the TSI Dust Trak monitor was calibrated with the Met One E-BAM sampler within the underground station. Experimental results suggested that the TSI Dust Trak overestimated PM10 and PM2.5 levels by about 2.0 and 2.2 times, respectively, compared with the Met One E-BAM sampler.

2.6.5 Beta Attenuation Method (BAM)

The BAM1020 (Figure 2.3) measure and records hourly particulate mass concentrations in ambient air. It uses beta ray attenuation to calculate collected particle mass concentration in unit of μg/m³. Automated samplers (analyzers) use a continuous filter tape, first measuring the attenuation by the unexposed tape, and then measuring the attenuation after the tape has passed through the ambient air flow. The attenuation measurement converts to a measure of the mass on the filter, so that the filters do not require later laboratory analysis for the mass variable. For some devices, the beta particle source is 14C (NARSTO, 1998)

The beta attenuation is repeated, and the difference in attenuation between the blank filter and the deposit is a measure of the accumulated concentration. Blank corrected attenuation readings can be converted to mass concentrations for averaging times as short as 30 minutes. The automatic BAM consists of a size-selective inlet, a filter tape, a beta radiation source, and a beta radiation detector. Particles smaller than the cut diameter of the size-selective inlet are collected at a single point on a length of filter tape. The difference in the transmission of beta radiation through the filter tape before and after a particulate sample has been collected is measured and used to determine the mass of collected particulate matter. The mass absorption coefficient for beta radiation is determined through the measurement of a series of known standards that bracket the mass range of interest (Jaklevic et al., 1981). Continuous operation is achieved by an automatic mechanism that advances the filter tape between sampling events. Since the baseline attenuation signal is measured before each sampling event, significant drift in the baseline signal does not occur. In the current study, each of the beta attenuation instruments was operated with hourly time resolution. In another study, Chung et al., (2001) found typical operation protocols for the BAM specify heating of the inlet line to a temperature of ~30 °C to reduce relative humidity to below 60%. This methodology minimizes particle-bound water, but it may also bias the particulate measurements when large amounts of volatile particulate matter are present. Figure 2.4 shows the schematic diagram for BAM1020.

2.6.6 Direct Reading Monitor (DRM)

Direct reading instruments were developed as early warning devices for use in industrial settings, where a leak or an accident could release a high concentration of a known chemical into the ambient atmosphere. Today, some direct reading instruments can detect contaminants in concentrations down to one part contaminant per million parts of air (ppm), although quantitative data are difficult to obtain when multiple contaminants are present. Unlike air sampling devices, which are used to collect samples for subsequent analysis in a laboratory, direct reading instruments provide information at the time of sampling, enabling rapid decision making.

In this research, the DRM is a dual technology instrument that combines the unequalled real-time measurement of light scatter with the accuracy standard of filter methods. The simple filter loading process testifies to the seamless blending of both technologies. Ambient temperature and pressure are measured and actual flow is calculated and controlled by the DRM microprocessor independent of filter loading change. The DRM is rugged, portable and easy to use. The all aluminum enclosure is not only rugged but provides electronic stability by filtering potential RF interference. Simply turning the monitor on will start a sample using the most recent parameters. The unit will continue to operate until user intervention or battery failure. Auto-Zero and Auto-Span ensure that the data collected will be of the highest quality. Both Zero and Span can be operated manually or individually programmed at varying time bases (15 minutes to 24 hours). The DRM can also be configured for start/stop times, recording periods, averaging time and other parameters.

A particle counter is an instrument that detects and counts particles. By its very nature a particle counter is a single particle counter, meaning it detects and counts particles one at a time. The nature of particle counting is based upon either light scattering or light obscuration. A high energy light source is used to illuminate the particle as it passes through the detection chamber. Figure 2.5 shows clean air condition for DRM. The particle passes through the light source (a laser) and if light scattering is used, then the redirected light is detected by a photo detector. Or if light blocking (obscuration) is used the loss of light is detected. The amplitude of the light scattered or light blocked is measured and the particle is counted and tabulated into standardized counting bins. Figure 2.6 shows the particulate scatter the light when particulate sample air intersects the laser beam.

Quantile Regression

Quantile regression (Koenker and Bassett 1978) is a method for estimating functional relations between variables for all portions of a probability distribution. Cade and Noon, (2003) described quantile regression is a way to estimate the conditional quantiles of a response variable distribution in the linear model that provides a more complete view of possible causal relationships between variables in ecological processes. Koenker and Bassett (1978) highlight quantile regression, which models conditional quantiles as functions of predictors and it also a natural extension of the linear regression model. Cade and Noon, (2003) founds that many ecological applications have used quantile regression as a method of estimating rates of change for functions along or near the upper boundary of the conditional distribution of responses.

Hao and Naiman, (2007) generally discusses the other quantiles can be used to describe noncentral positions of a distribution. The quantile notion generalizes specific terms like quartile, quintile, decile, and percentile. Gehrig et al, 2005, Hauck et al 2004 obtained correction factor and relationship using linear regression due to research in a new method to link PM10 concentrations from automatic monitors to the manual gravimetric reference method according to EN12341 and on the equivalence of gravimetric PM data with TEOM and beta attenuation measurements. Kingham et al (2005) previous study in comparability of monitors was investigated by linear regression using the reduced major axis (RMA) method.