Monitoring and Source Apportionment for Particulate Matter Pollution in Six Asian Cities

Chapter 3

Introduction

Atmospheric particulate matter (PM) can cause multiple effects on human health and
the environment. Major emission sources in Asian urban areas, highlighted in Chapter
1 of this book, release not only a huge amount of primary PM but also precursor gases
which subsequently form secondary PM in the atmosphere. High levels of TSP and
PM10 in populated urban areas have been reported (Molina and Molina, 2004; HEI,
2004; Gupta et al., 2006; Tsai and Chen, 2006). Fragmented available PM2.5 data also
show very high levels of this toxic air pollutant which often exceeds the WHO
guidelines by a factor of 2 or more (Kim Oanh et al., 2006; Hopke et al., 2008).

The extent of the health and atmospheric effects of particles depends on their size and
compositions. The smaller the particles the deeper they can enter the lungs; hence are
more damaging. PM10 have long been connected to the adverse health effects
including increased mortality, whereas fine particles (PM2.5) pose even higher risks
(Dockery et al., 1994; Donaldson et al., 1998; Scwartz et al., 2000; Pope III et al.,
2009). These fine particles also have large surface areas for adsorption of toxic
organic compounds such as carcinogenic polycyclic aromatic hydrocarbons (PAH).
Furthermore, due to their ability to absorb and scatter solar radiation, the atmospheric
particles, especially fine ones, effectively reduce visibility (Watson, 2002; Kim et al.,
2001) and affect the Earth’s radiation energy balance (IPCC, 2007; Bond et al. 2004).
Black carbon particles, for example, strongly absorb the solar radiation, hence can
also warm the Earth (Ramanathan and Carmichael, 2008).

There have been growing research interests on characterization of levels and
compositions of size-segregated PM. These data help to understand the nature of the
particulate pollution in relation to local sources, long-range transport and atmospheric
transformation processes, which are essentially required in formulation of effective air
quality management strategies. In particular, the data can be analyzed by the receptor
modeling tool to identify the contributing sources and to quantify their contributions
to PM pollution, as detailed in Chapter 2 of this book.

There are still insufficiency of systematic, regionally compatible and long term PM
data records in the Asian developing countries. Until recently, only the total
suspended PM (TSP) was the most monitored and is still a regulated pollutant (refer
to detail in Chapter 1). Scarcity of information on levels of ambient fine particles and
their physical and chemical properties in large urban areas of Asia prevents from
gaining insights into the nature of PM pollution. To partly fill up the gap, the Asian
Regional Air Pollution Research Network or AIRPET (http://www.serd.ait.ac.th/airpet), had designed and implemented a monitoring program to collect such data. One of the main research objectives of AIRPET was to provide a comprehensive assessment of the PM pollution in the region. The focus was on PM2.5 and PM10 or PM10-2.5 levels and composition in six cities/metropolitan regions in Asia, namely, the Bangkok Metropolitan Region (BMR, Thailand), Bandung (Indonesia), Beijing (China), Chennai (India), Metro Manila (Philippines) and Hanoi Metropolitan Region (Vietnam). The network was mainly funded by the Swedish International Development Cooperation Agency (Sida) through the Asian Regional Research Program in Environmental Technology (ARRPET) and was
coordinated by the Asian Institute of Technology (AIT). This chapter summarizes the
findings on levels, composition and source contributions of the PM in the six AIRPET
cities during the 2002-2008 period. The focus is on the design of the regional PM
monitoring program with necessary QA/QC to generate data of adequate quality.