This document summarizes research on the health effects of airborne particulate matter. It discusses epidemiological studies that have found associations between particulate exposure and increased mortality and morbidity. Specifically, exposures to PM10 and PM2.5 have been linked to increased hospital admissions and decreased lung function. The document also reviews the gaps in understanding these health impacts in India, noting that more research is needed that focuses specifically on PM10 and PM2.5, as most Indian data so far has examined total suspended particulates only. It calls for efforts to better understand the epidemiology, toxicology and exposure levels related to particulate air pollution in India.

1. Indian Journal of Air Pollution Control Vol. V No. II September 2005 pp 54-65
Airborne Particulate Matter And Human Health:Perspective And Case Study
Ashok Kumar*, DK Dhawan**, ML Garg***
*Reserach Fellow, Department of Biophysics, Panjab University, Chandigarh -160014. (akbph@rediffmail.com)
**Reader, Department of Biophysics, Panjab University, Chandigarh -160014. (dhawan@pu.ac.in)
***Reader, Department of Biophysics, Panjab University, Chandigarh -160014. (mohan@pu.ac.in)
Abstract
Health effects related to airborne particulate matter in urban and industrial areas have recently drawn great attention of
the environmental scientists. The main health effects statistically associated with exposures to ambient particulate
matter, PM10 (Particulate matter with aerodynamic diameter ≤10 µm) and PM2.5 (Particulate matter with aerodynamic
diameter ≤2.5 µm), include evidences of increased mortality (those with pre-existing cardiopulmonary conditions) and
morbidity (increased by increased hospital admissions, respiratory symptom rates and decrement in lung functions).
These particles also play a central role in environmental problems such as climate change and visibility impairment. In
addition, studies are also being made in U.S.A. and Europe to understand further their epidemiological, toxicological
and exposure aspects. However, concerted efforts to understand different environmental aspects of PM10 and PM2.5
have not been made in a country with a large population such as India. Major portion of the data available today in
India is for total suspended particulate matter (TSP) that is not enough for studying health effects. Further, there is a
wide gap in the technologies and evaluation methods adopted in USA and Europe compared to the ones used in India.
People in India are more vulnerable to adverse health effects compared to those in advanced countries due to poor
environmental controls and nutrition. This review makes an effort to highlight the gaps and emphasize the need to carry
out these studies.
Introduction
The problem of air pollution and health is of multidisciplinary nature. Some of the issues concerning this
field (Holgate et al, 1999) are atmospheric chemistry, new methods for pollutants monitoring, epidemiology
related to cancer, pulmonary and cardiovascular diseases and experiments with animals to examine the
effects of controlled exposure of a single or of a mixture of pollutants. Air pollutants include both the
gaseous and suspended particulate matter (SPM). Some of the air pollutants, namely the particulate matter
(PM); Ozone (O3) and other photochemical oxidants, nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon
monoxide (CO) and hydrocarbons (later rescinded), and their national ambient air quality standards
(NAAQS) were established for the first time in 1971 in US (Federal Register, 1971). Lead (Pb) was added to
this list as a 'criteria air pollutant' in 1976, and both Pb criteria and NAAQS were finalized and promulgated
in 1977. Since then, USEPA has undertaken a periodic review and revision of the criteria and of the
NAAQS. The most recent periodic review of criteria and NAAQS for air pollutants has been completed by
USEPA in 1997. This review (http//www.epa.gov/airs/criteria.html) includes important distinctions between
fine and coarse ambient air particles with regard to size, chemical composition, source and transport.
In the present review an attempt has been to cover different aspects of air pollution and in particular
airborne particulate matter (PM) and human health. The topics covered are brief comparison of PM with
other air pollutants, major epidemiological studies carried globally, instrumentation used for estimating PM,
techniques used to measure composition (in particular metals) of PM, metal exposure of the general
population. The status of work in India is covered in the end highlighting the need to address the problem of
PM and human health.
Epidemiology of Air Pollution
The study of the effects of air pollution on human populations began with a major episode of increased
mortality, in which the cause and effect relationship between the dramatic episode and its consequences
could not be doubted. The episode in the Meuse Valley, Donora, USA in 1930 and the London episode of
December 1952 provided unequivocal evidence of that kind. The development of epidemiological studies
can be dated from the London episode and it is natural to ask questions about the effects other than acute
mortality that air pollution may be causing.
US EPA initiated nation wide program of epidemiologic studies from early 1970 in an attempt to
document comprehensively the health effects of air pollution (US EPA, 1974). In the mid-1970s,

2. investigators at the Harvard School of Public Health initiated a landmark longitudinal investigation of the
health effects of the oxides of sulfur and particulate pollution (Ferris et al, 1979). This investigation involved
about 20,000 children and adults recruited from six US cities and provided a gradient of pollution. These
investigations hypothesized that air pollution would adversely affect lung growth during childhood and
accelerate lung function decline during adulthood. During 1980s, the same Harvard group implemented a
second nation wide study to investigate the health effects of acidic aerosols (Speizer, 1989). Such large-scale
studies were prompted by the need to address even the relatively lesser effects of air pollution than in the
past studies because ambient pollution levels had declined. Additionally these studies had become larger and
more complex in response to the rising requirement of the data for estimating risks with reasonable precision
and accuracy.
While the initial focus of epidemiological research was on outdoor pollution, potential public health
significance of pollutant exposure in indoor environments was also indicated by many other studies that
followed (Benson et al, 1972, Samet et al, 1978, Samet et al, 1988, US EPA, 1993). These studies showed
that indoor sources could contaminate indoor air and produce adverse health effects. Based on these and
other studies, the concept of total personal exposure has evolved and this concept remains fundamental in the
design of studies of outdoor air pollutants (NRC, 1991).
During the 1990s, there has been a rising use of time-series method to evaluate the consequences of air
pollution on daily mortality and morbidity measure, such as numbers of hospitalizations or emergency room
visits (American Thoracic Society, 1996). These studies have been facilitated by new statistical methods for
time series analysis as well as availability of suitable hardware and software. The data bases were typically
assembled from routinely collected information on mortality and morbidity, monitoring data collected for
regulatory purposes, and publicly available information on confounding factors such as weather, and an
extensive series of analyses were conducted (Schwartz and Morris, 1995, Pope III, 1995). These analyses
indicated adverse effects on human health as a result of air pollution levels in many cities (Englert, 2004).
Health Effects of Different Pollutants
Present status of the effects of the various air pollutants on human health in urban areas as reported in the
literature (Schwela, 2000; WHO) is as follows:
An association between Sulphur dioxide (SO2) exposure and daily mortality and morbidity has been
reported. Weak association between short-term nitrogen dioxide (NO2) exposure from cooking gas and
respiratory symptoms has been found in children, but it was inconsistent in exposed women. With long-term
exposure, children, but not adults, exhibit increased respiratory symptoms, decreased lung function, and
increased incidences of chronic cough, bronchitis, and conjunctivitis. Health effects of carbon monoxide
(CO) include hypoxia, neurological deficits and neuro-behavioral changes, and increase in daily mortality
and hospital admissions for cardiovascular diseases. Short-term acute effects of Ozone (O3) include
pulmonary function decrements, increased airway responsiveness and airway inflammation, aggravation of
pre-existing respiratory diseases like asthma, increases in daily hospital admissions and emergency
department visits for respiratory causes, and excess mortality. Exposure-response relations for the respective
associations between O3 and forced one-second expiratory volume (FEV1), inflammatory changes and/or
changes in hospital admissions have been found non-linear, whereas the relation between percent change in
symptom exacerbation among adults and asthmatics has been found linear. Single-pollutant associations
between O3 exposure and daily mortality and hospital admissions for respiratory diseases have been found
statistically significant even in multi-pollutant models. Associations between Suspended Particulate
Matter (SPM) concentrations and mortality and morbidity rates are significant. The acute health effects of
SPM, even at short-term low levels of exposure, include increased daily mortality and hospital admission
rates for exacerbation of respiratory disease, fluctuations in the prevalence of bronchodilator use and cough,
as well as long-term effects with respect to mortality and respiratory morbidity. Such effects depend on
particle size and concentration and can fluctuate with daily fluctuations in PM10 or PM2.5 levels. The relation
between PM10 or PM2.5 exposure and acute health effects has been found linear at concentrations below
100µg/m3
. Currently, no threshold has been reported below which no effects occur. Out of all the pollutants
the importance of SPM in general and PM10 and PM2.5 in particular can also be judged from the fact that
there are independent projects (USEPA, 1999-2004) being run in U.S.A and Europe to understand the
epidemiological, toxicological and exposure aspects of these. The biological effects of lead can be related to

3. blood lead levels, the best indicator of internal exposure (Sanborn et al. 2002). The potential effects of lead
in adults and children include encephalopathic signs and symptoms, central nervous system symptoms,
cognitive effects, increased blood pressure, and reduced measures of child intelligence.
Particulate matter size and composition
Particulate matter (PM) is a mixture of many different components with local and regional variation. PM can
be characterized by origin, e.g., anthropogenic or geogenic, primary or secondary particles, by source, e.g.,
combustion products and traffic, or by physicochemical properties such as solubility. PM is characterized by
particle size (aerodynamic diameter). A total suspended particle (TSP) is the most comprehensive term
including particles of any size suspended in air. However, particles larger than 30–70µm only remain
suspended for a very short period before deposition. PM10 and PM2.5 is PM with an aerodynamic diameter of
less than 10 and 2.5 µm, respectively. Ultra-fine particles (UF) are those with aerodynamic diameter of less
than 0.1 µm, also called PM0.1. The PM2.5 fraction is also called “fine particles”, and those particles between
10 and 2.5µm are currently named “coarse particles”. PM10 are also called “inhalable particles”.
The physical properties of air borne particles associated with the incidence of health hazard are the
size distribution and mass concentration of the dust. Medical researches strongly believe that aerosol
particles below 5 m are harmful to human health and below 3 m particles, in particular, tend to
accumulate in the lungs (Kotrappa, 1972). Recent inhalation studies with laboratory animals (Oberdarster et
al, 1995) suggest that even the inhalation of ultra fine particles are considered a health risk as they get
perfused through the alveoli of the lungs. Further, as the concentration of the ultra fine particles is negligible
in comparison to that of larger particles, it seems more appropriate to correlate their number concentration
with health effects rather than their mass concentration.
Only limited data are available on the chemical composition of the particulate matter (US EPA,
1999-2004). According to the present knowledge, Carbon, specifically "organic" carbon, Sulphate, Nitrate,
Fine crystal materials, Heavy metals, (Water content) are the major species of the PM10 and PM2.5. Crystal
material is partly of natural origin (fugitive dust) and partly of anthropogenic origin as a residue of coal
combustion or suspension due to traffic. Nitrates and most of the sulphates are of anthropogenic origin and
mainly present in the form of ammonium salts.
Instrumentation Development for Particulate Matter Collection and Characterization
Particulate matter is normally collected on a filter or impactor in devices that may also segregate particles by
size. Gent Stacked Filter Unit (SFU) (Hopke et al, 1997) has been developed through a collaborative program
of many universities/institutes. With SFU, it is possible to collect particulate matter in two size fractions (≤2
m and between 2m and 10 m). This sampler has also been adopted by the International Atomic Energy
Agency (IAEA) for its coordinated research programme around the world (Parr et al, 1996). The Particulate
matter collected on filters is then characterized by analytical techniques. Particle collection must take place
over an extended period, usually hours, before sufficient sample is acquired.
Environmental Particulate Air Monitor Model: EPAM 5000 from SKS Inc. USA is another
alternative for real time monitoring of either PM10 or PM2.5 at a time. It is based on the principle of
monitoring the intensity of light scattering by the aerosol particles. In addition, this sampler can be used to
collect aerosols on the filter paper over a specified period of time.
The analytical techniques such as Particle induced X-ray emission (PIXE) and Energy Dispersive X-
ray Fluorescence (EDXRF) are dominant tools in the particulate matter research (Grieken et al,1993). These
techniques are successfully competing with the other well-established analytical techniques such as Atomic
Absorption Spectroscopy (AAS) and inductively coupled Atomic Emission Spectroscopy (IC-AES). PIXE
and EDXRF techniques are able to support the short and long-term sampling studies and provide accurate
elemental concentration data. Normally observed elements in particulate matter analyzed by these techniques
are Si, P, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Se, Br, Rb, Sr, Zr and Pb. It may be mentioned that the
instrumentation for the estimation of the aerosol components such as carbonaceous material, nitrates,
sulphates and water is still not available and is being developed by collaborative efforts of many scientists of
different countries in Europe (USEPA, 1999-2004).

4. Metal Exposure to General Populations
Metal are more frequently associated with air pollution particles of anthropogenic origin and have values of
MMAD less than 2.5 µm (Schroeder et al, 1987). Such particles originate from incomplete combustion of
carbon (containing these materials) at power plants, smelters, incinerators, cement kilns, home furnaces,
fireplaces, and motor vehicles. The incineration of municipal waste is becoming an important atmospheric
source of metals like zinc, iron, mercury, lead, tin, arsenic, cadmium, cobalt, copper, manganese, nickel and
antimony. Open-hearth furnaces at steel mills are a notable source of iron, zinc, chromium, copper,
manganese, nickel, and lead.
Metal exposure occurs from many exposure routes (inhalation, ingestion, skin transfer, Transplacental,
parenteral), and health effects in humans have been reported for almost all the heavy metals. Recently the
environmental exposure of general population to the toxic metals has been carried out at many places in the
world. The mean blood lead (PbB) levels in the population of Taiwan, Republic of China was estimated to be
8.99 g/dl (Liou et al, 1994). In Uruguayan children the mean PbB was 9.6 g/dl (Schutz et al, 1997),
among the general population of Korea, levels were 6.36 g/dl for males and 5.09 g/dl for females (Yang et
al, 1999). A small fraction of the population in French community was found to exceed the maximum limit
of 35 g/dl (Huel et al, 1986). Iron deficiency was found to be significantly associated with low-level lead
poisoning in Children aged 9 to 48 months (Wright et al, 1999). In a pilot study carried by Singh et al (1994)
the PbB levels were found to be between 28 to 52 g/dl in the automobile/Battery workers, which are quite
high as compared to other places. Although, the overall lead levels may not seem to be alarming but these
are higher by 10 to 10,000 fold than the PbB of pre-industrial humans (0.016g/dl) (Flegal and Smith, 1995).
Several review articles have emphasized the exposure of general population to toxic metals such as Ni, As,
Cr, and Cd (Faroon et al, 1994, Bencko, 1983).
Urban Air Quality in India
Tata Energy Research Institute (TERI), Delhi, had reviewed the past and on-going work on urban air quality
in India in 2001 (TERI, 2001, Saksena et al, 2002,). According to this report, air quality monitoring
programme in India was started in 1967 by the National Environmental Engineering Research Institute
(NEERI) at three stations each, in the major Indian cities. During 1984-85, Central Pollution Control Board
(CPCB) established National Air quality Programme (NAMP) with seven monitoring stations. The pollutants
monitored are Suphur dioxide (SO2), Nitrogen dioxide (NO2), Suspended Particulate Matter (SPM). In
addition to these criteria pollutants, NEERI monitors pollutants like ammonia (NH3), Hydrogen Sulphide
(H2S), Respirable Suspended Particulate Matter (RSPM) and Polyaromatic Hydrocarbons (PAH). In Delhi,
pollutants such as Carbon monoxide (CO), Ozone (O3), Benzene (C6H6) and trace elements are monitored at
a few locations by CPCB.
Key findings from the NAMP (National Air Quality Monitoring Programme) are the following:
 Major air quality concern in India is Suspended Particulate Matter (SPM). Maximum SPM values
have been observed at Kanpur, Calcutta and Delhi. Low values of SPM have been observed in south
Indian cities Chennai, Bangalore and Hyderabad. This may be due to topography and weather
conditions. In coastal areas, the particulate levels may be low due to high humidity. Vishwanadham
et al (1995) has reported that dilution capacity is quite high in Southern parts of India and whereas it
is low in Northern parts.
 The level of Respirable Suspended Particulate Matter (RSPM) from 1998 to 1999 at ITO, Delhi
fluctuated between 56µgm-3
to 820µgm-3
.
 The SO2 levels are well within the prescribed limits at many locations. High Sulphur dioxide (SO2)
levels are recorded in Howrah, Calcutta and Pondicherry where the standard has been violated many
times during the past. Annual average NO2 has been well within the limit with the exception of
violation in some residential areas of Howrah, Vishakhapatnam and Kota. Carbon monoxide level at
ITO, Delhi violates the standard for most of the monitored period. Ozone (one hour average) value
measured at ITO, Delhi since 1998 ranges between 26-104 µgm-3
, which is well within the USEPA
standard of 235µgm-3
. Level of ammonia (NH3) exceeded the standard annual average of 100µgm-3
at
Delhi and Calcutta in 1996. H2S values are low at all NEERI monitored locations.

5. Besides the NAMP, research groups at the Universities, Indian Institutes of Technology (IITs) and
National Research Laboratories have tried to address the problem of air pollution at their local levels. About
15-20 studies have been reported on the problem of pollution by heavy elements (including Cu, Cr, Fe, Ni,
Pb, Zn, Ni, V, As, Be, Cd, Ti, Mn, Al). In our earlier study (Bandhu et al, 1998, 2000), we measured sixteen
elements in aerosol samples from industrial, commercial, and relatively clean zone of Chandigarh with
EDXRF and PIXE. Possible sources included soil dust while anthropogenic sources suggested refuse
burning, automobile exhaust and industrial activities (Iron foundry and Lead recycling). In Lucknow city,
Singh et al (1997) evaluated lead in soil and vegetation along the highways. Bajwa, Bhatia and Ghosh
measured lead (Pb), Cadmium (Cd) and Zinc using AAS in Variance and Kanpur (Bajwa et al, 1999).
Distribution and concentration of these elements in soil/plants was measured along roads with high and low
traffic density, tire abrasion was cited as a source of cadmium and Zinc. Regression studies revealed that
dispersion of Pb, Cd and Zn in these habitats is dependent on the intensity of vehicular traffic. Concentration
of metals, both in plants and soil, decreased with the depth of soil. Another study in Bombay determined the
lead level in the atmosphere and children’s blood to estimate the importance of vehicular emission as source
of lead (Tripathi et al, 2001). They profiled the exposure due to inhalation, ingestion and temporal variations
and found that level has decreased for the study period from 1984-1998. Ambient concentrations of lead
were lower than the prescribed standards. Daily intake for children through ingestion and in halation was
found to be the important route. Gokhale and Patil (2004) conducted another study at traffic intersections
using Anderson sampler to monitor aerosols and AAS for estimating Pb. In their study, they found PM10 to
be 528±62 and Pb to be up to 4.5± 0.26 µg/m3
which are above permissible limits. Studies by Ghaghate and
Hasan (1999) reported lead to be at the highest concentration in Kolkata followed by Delhi and Kanpur. In
Coimbatore, in an industrial zone, Pb was found with concentrations up to 2.147 µg/m3
(Mohanraj et al,
2004). In Bhilai, Chhattisgarh, lead levels in SPM were found between 0.888-1.414µg/m3
, and blood Pb
levels in traffic and non-traffic personals was found up to 56.7 and 31.2 µg/dl (Sharma and Pervezs, 2003).
Pb level in SPM is again beyond permissible limits and blood Pb levels is also in chronically toxic range.
Negi et al (1987) have reported urban aerosol composition for both major and trace elements, determined
using EDXRF technique, in four major cities of India, namely, Bombay, Banglore, Nagpur and Jaipur.
Analysis of Data Collected at Chandigarh
The authors have also collected samples of aerosol at Chandigarh and carried out their analysis. The data for
Chandigarh is from Hallomajra (HM), a suburban area 8 km SE of the city center, located in the vicinity of
industrial zone on the Chandigarh-Delhi highway. About 100 samples between April 1995 to April 1996
were collected on 47 mm diameter, 0.8 m pore size, cellulose nitrate filter papers (Microdevices Pvt. Ltd.,
Ambala, India). Filter paper was mounted in an aerosol filter holder (Millipore, Cat no xx50 04700) having
an inlet dispersion chamber to produce optimum particle distribution on the surface of the filter. The air
through the filter paper was sucked at a flow rate of 12 l/min with the help of diaphragmatic vacuum pump
(Millipore, Cat. no. xx55 22050) and critical orifice ( Millipore, Cat. no.xx50 000 00). The flow rate was
monitored periodically for each sample with a rotameter and no case of reduction of flow rate due to filter
clogging were experienced during the sampling. The collection surface was directed downward to prevent
particle collection by sedimentation and the filter holder was protected with a rain cover. The error in
sampling is estimated to be 10%.
The elemental analysis of aerosol samples was carried out using EDXRF set-up involving a low
power (100 watt) tungsten anode X-ray tube (Kevex, 50 kV, 2.0 mA, water cooled) as source of excitation.
The X-ray tube was operated at 35kV and 1.7 mA. The X-rays from the tube were made to fall on a Mo
secondary exciter and the characteristic K X-rays of Mo (17.8 keV, the weighted average energy of the Mo-
K and -K lines) were in turn used to excite the characteristic X-rays of elements present in the aerosol
samples. The X-ray tube, secondary exciter, sample and the detector were arranged in the triaxial geometry
to minimize the background due to scattered radiation. A 30 mm2
x 6 mm Ortec Si (Li) detector (FWHM=
180 eV at 5.96 keV) coupled with PC-286 based multi-channel analyzer (MCA) was used to collect the
fluorescent X-ray spectra from the samples. Each spectrum was collected for time periods ranging from 3-5
h. Each spectrum was analyzed for photo peak areas using a computer code AXIL (Van Gricken and
Markowicz 1992). The elemental concentrations in various samples were determined using the equation:

6. Mj = Nij/ IoG ij ij ij
where Nij is the number of counts/s for the ith X-ray photo peak of the jth element, Io is the intensity of the
photons emitted by the source, G is the geometry factor, ij is the X-ray fluorescence cross section of the ith X-
rays of the jth element in cm2
/g at the incident photon energy, ij is the detector efficiency for the ith X-ray of the
jth element and ij is the self absorption correction factor for the absorption of the incident X-rays. Evaluation of
different parameters is explained by Garg et. al. (1998). The error in the concentration estimation by EDXRF is
8-10%.
The overall error in concentrations is estimated to be 13-15%. This is attributed to the errors incurred
during sampling (10%) and EDXRF analysis (8-10%). The summary statistics of elemental concentrations is
given in Table 1. These include arithmetic sample means (excluding the extreme outlier samples), arithmetic
unbiased sample standard deviation (), and the minimum and maximum values for elemental concentration
data. The mean concentration levels for summer are in general lower than the winter season. The plausible
reason could be the fact that in this region, weather conditions in winter season are generally stable. These
conditions result in thermal inversions concentrating the pollutants. Similar observations have been reported
by IAEA for the apportionment of air pollution for a city in New South Wales, Australia (Parr et al, 1996).
Table 1: Summary statistics for aerosol concentration (ng/m3
) data from HM, Chandigarh City
Element Summer (1995-1996) Winter (1995-1996)
Mean  Min Max Mean  Min Max
S 4485 6203 143 39422 5053 5223 9.4 20066
Cl 2895 2063 54 9197 3209 3296 9.6 10190
K 4169 3901 204 16013 5386 5832 694 19896
Ca 7024 6748 933 32037 9129 11036 853 35400
Ti 547 602 2.2 2709 684 834 29 2735
Cr 39.6 55.7 0.8 267 58.8 93 0.8 302
Mn 280 290 12 1326 381 487 17 1759
Fe 6748 7344 491 34470 9294 11826 866 37110
Ni 10.8 12.9 0.4 52 18 21 0.7 71
Cu 23.5 28.9 0.1 152 44.6 58.6 0.2 186
Zn 914 1151 10 5508 1250 1885 41 7937
Br 22.4 24.4 0.3 138 34 41 0.7 183
Rb 48 86 0.9 541 52 73 0.9 253
Sr 52 65 0.3 285 79 108 0.2 401
Pb 1219 2001 5 10109 1235 1753 5.2 6923
Analysis of Data Collected at Mandi Gobindgarh and Morinda
Fifty samples were collected from both the study areas between August 1999 and May 2000. Moderate to
heavy rains were received during this period in the region. The sampling time for all these samples was 12 or
36 hrs. The flow-rate of air was chosen as 3 or 8 l /min. Aerosol sampling kit contained Millipore
diaphragmatic vacuum pump (Catalog No. 5522050) and sequential filter unit (SFU) with coarse pored
Nuclepore Filters for collection of fractionated samples of particulate matter under ambient conditions. With
this sampler, outdoor aerosols could be separated in two fractions that roughly can be described as
anthropogenic (PM2.5) and soil derived particles (PM10). The Nuclepore Filters are produced by irradiating
sheets of polycarbonate (or polyester) with charged particles. The created tracks are etched to pores with
rather well defined diameters. Particles are collected on the filters mainly through diffusion, interception and
impaction. In the interest of size for our purpose (1-10 µm), impaction and especially interception are
important indices.
The SFU consisted of 8µm pore size Nuclepore Filter (110632 Polycarbonate membrane, 25 mm
diameter) followed by a 0.4 µm pore size filter (110607 Polycarbonate membrane, 25 mm diameter) both
held in a double 25 mm filter-holder (Nuclepore Corp., Pleasanton, CA, USA). The air through the filter

7. membranes was sucked at a required flow rate with the help of a diaphragmatic vacuum pump (Millipore
Catalog No.-5522050). The flow rate was monitored periodically for each sample with a rotameter. The flow
rate was kept constant by a critical orifice and precaution was taken regarding the reduction of flow rate due
to filter clogging during the sampling period. The collection surface was directed downward to prevent
particle collection by sedimentation and the filter holder was protected with a rain-cover. All the aerosol-
sampling sites were located on the flat rooftop of the building (20-40 feet high) to have an effective
collection of the aerosols below 10 µm size.
To study the composition of fractionated aerosols, about twenty samples were analyzed using Proton
Induced X-ray Emission (PIXE) technique at the Institute of Physics (IOP), Bhubaneshwar, Orissa. Details
of experimental set up involving multipurpose scattering chamber have been described earlier (Hajivaliei et
al, 1999). The elemental concentrations were determined with the help of GUPIX computer code (Maxwell
et al, 1995). This code utilizes the fundamental parameter method (FPM) for quantitative analysis. It requires
parameters like angle between the beam direction and Si (Li) detector, thickness of the chamber window and
target, major matrix of the target, energy of the incident particle and charge collected.
The concentrations in ng/m2
obtained were converted into ng/m3
using the relation:
Elemental concentrations in ng/m3
in air = ( C×A) / V
Where C denotes concentration in ng/cm2
using GUPIX,
A denotes area (4.91 cm2
) covered by aerosol sample on filter and
V denotes volume of air sucked (for some samples it is 2.16 m3
and for others is 5.76 m3
) by
sampler.
The error in concentrations can be up to 30 %. This includes the error of air volume sucked and
charge collection and other physical parameters used by GUPIX for quantitative estimation. The arithmetic
mean and standard deviation of the concentration levels of different elements obtained in samples from
Mandi-Gobindgarh and Morinda are given in Table 2 and 3 respectively. The minimum and maximum
concentration values and also the minimum detection limits (MDL) for each element by PIXE set up at IOP
Bhubaneshwar for aerosol samples are given. The concentration levels are found to be, in general, higher in
Mandi Gobindgarh as compared to Morinda. The large deviation from the mean concentration is indicative
of highly varying day-to-day industrial activity and weather conditions.
In Table 4 the concentrations of trace elements available from Indian cities are compared with some
of the prominent cities of Europe and North America. The aerosol concentrations from Chandigarh are the
average of summer and winter data from Table 1., for Mandi Gobindgarh and Morinda are the total
concentration in the PM2.5 and PMcf given in Tables 2 and 3 respectively. The data for Jaipur and Bombay are
taken from the reference of Negi et al (1987). Data for Campana are from Smichowski et al. (2005) and that
of Houston is from Bandhu et al (2000). It is clear from this Table that the concentration levels for
Chandigarh, considered to be clean, are higher by a factor of 2-50 in comparison to that for Campana,
Argentina, Europe and Houston, North America. This may be attributed to the higher aerosol loadings in the
tropics as compared to other latitudes and also due to poor pollution control measures. The concentration
values at Chandigarh are found to be higher than those measured at Bombay by a factor of 2-5, and are found
to be comparable with those measured at Jaipur (these measurements were made in 1980-1981) (Negi et al,
1987). At Jaipur the major source of pollution was soil dust.
The concentration levels in Mandi Gobindgarh are generally higher as compared to Morinda and
other cities of India. Higher pollution levels in Mandi-Gobindgarh, in the present study could be because of
the intense industrial activity. The higher concentrations of toxic elements like Cr, Ni, Ar, Pb should be taken
into consideration. Similarly, the level of Pb in Chandigarh is a cause of concern. As per WHO air quality
guidelines, the potential pollutants which are of concern for public health are Ni, and Pb with the maximum
permissible limit of 0.5 - 1.0 gm-3
(WHO, 1987). Higher concentrations of Pb may lead to the health effects
which include developmental Sanborn et al, 2002). Elements such as S, Cl, Cr, Ni, As, Br are also known to
be toxic (Arowolo, 2004, Aposhian, 1989), however, presently no permissible limits in air have been defined
for these elements.

8. Table 2: Arithmetic mean concentrations (ng/m3
) and standard deviation (σ) of various elements
detected in aerosol samples from Mandi-Gobindgarh. MDL stands for minimum
detection limit of the PIXE set up at Bhubaneshwar for the aerosol samples in (ng/m3
).
To calculate the arithmetic mean the concentrations of the elements in the samples where
these were below detection limits were taken to be zero.
Elements MDL PM2.5 Pmef
Mean σ Min Max Mean σ Min Max
Silicon (Si) 80090 11288 28856 0 94125 0 0 0 0
Sulphur (S) 769 6315 6031 0 19136 901 1620 0 5009
Chlorine (Cl) 229 1897 2125 0 18598 5096 4228 0 13910
Potassium (K) 86 2833 3243 878 22339 3769 3911 499 15506
Calcium (Ca) 78 713 571 0 3609 6054 5276 1031 19428
Titanium (Ti) 54 74 83 0 329 612 522 98 1945
Chromium (Cr) 45 92 87 0 258 199 238 0 828
Manganese (Mn) 44 140 168 5 3012 351 313 66 1221
Iron (Fe) 15 4189 4325 488 14021 20931 22587 3534 82239
Nickel (Ni) 54 24 35 0 908 105 167 0 522
Zinc (Zn) 37 14707 16109 1307 51808 11607 13740 88 44637
Arsenic (As) 167 96 175 0 601 384 782 0 2381
Bromine (Br) 153 2960 2062 44 7311 227 681 0 2417
Lead (Pb) 301 3783 4811 0 14550 1283 1952 0 7304
Table 3: Arithmetic mean concentrations (ng/m3
) and standard deviation (σ) of various elements
detected in aerosol samples from Morinda. MDL stands for minimum detection limit of the
PIXE set up at Bhubaneshwar for the aerosol samples in (ng/m3
). To calculate the
arithmetic mean the concentrations of the elements in the samples where these were below
detection limits were taken to be zero.
Elements MDL PM2.5 Pmef
Mean σ Min Max Mean σ Min Max
Silicon (Si) 80090 0 0 0 0 0 0 0 0
Sulphur (S) 769 3602 533 3264 4217 298 516 0 894
Chlorine (Cl) 229 1132 644 667 1868 3002 1991 1332 5207
Potassium (K) 86 4720 3670 1596 8762 3711 3160 1152 7243
Calcium (Ca) 78 643 734 40 1461 7816 5377 2841 13522
Titanium (Ti) 54 61 90 0 165 746 500 349 1307
Chromium (Cr) 45 187 60 120 236 195 96 99 292
Manganese (Mn) 44 127 120 47 265 254 199 60 458
Iron (Fe) 15 1611 1330 726 3141 10348 7926 3773 19149
Nickel (Ni) 54 41 60 0 111 7 13 0 23
Zinc (Zn) 37 5957 7560 592 14605 849 385 411 1139
Arsenic (As) 167 13 23 0 40 0 0 0 0
Bromine (Br) 153 4745 203 4542 4948 42 37 0 70
Lead (Pb) 301 0 0 0 0 247 428 0 742

9. Table 4: Comparative summary statistics for the aerosol samples analyzed from various cities
world over. The concentrations (ng/m3
) are mean with standard deviation for all other
places except for the Campana, Argentina, where standard deviations were not available.
Element Campana Houston Chandigarh Bombay Jaipur Morinda Mandi-Gobindgarh
ng/m3
(Geometric/Arithmetic Mean  S.D)
Na - - - - - - -
Mg - - - - - - -
Al - 1495424 - 10802850 76102460 - -
Si - 40001002 - 39902360 144003320 - 11288±28856
S - - 47025855 16201800 4401880 3900 ±1049 7216±7651
Cl - 34922 30152608 12703060 10602330 4134 ± 2635 6993±6353
K - 30022 4633 4768 4002180 17103020 8431 ± 6830 6602±7012
Ca - 3250160 78278699 24002130 50002290 8459 ± 6111 6767±5847
Ti 12 4814 599703 1602070 3903010 807 ± 590 686±605
Cr 3 - 4773 - - 382 ± 156 291±325
Mn 21 363.60 318381 462330 1002320 381 ± 319 491±481
Fe 552 90041 77209394 17802050 44502420 11959±9256 25120±26912
Ni 2 81.41 1417 82700 - 48 ± 73 129±202
Cu - 302.82 3244 482740 572030 - -
Zn 37 17036 10421484 1702770 1702460 6806±7945 26314±29849
Br - 1095 2732 152340 1213 4787 ±240 3187±2743
Sr - - 6282 131910 302190 - -
Pb 71 61025.07 12251910 1203410 801810 247 ± 428 5066±6763
Epidemiological studies addressing the problem of health from air pollution covering large group of
population as from USA and Europe are not available from India. The health effect due to occupational
exposure has been addressed to some extent (Sharma et al, 1998, NWLE, 2001) by institutes such as
National Institute of Occupational Health (NIOH), Ahemdabad, All India Institute of Medical Science
(AIIMS), New Delhi, National Institute of Nutrition (NUN) Hyderabad, and Industrial Toxicology Research
Centre (ITRC), Lucknow.
The information about metal exposure to general population in developing countries is inadequate,
and the environmental level of toxic metals in such parts of the world is expected to rise. Sociologically, the
population in these countries may be particularly at risk as a result of a) high population density and poor
hygienic conditions in the crowded cities, and b) the preponderance of the most susceptible population
groups related to nutritional and health status (interaction with pre-existing endemic diseases). People
working or living near industries and facilities that manufacture and use As, Be, Cd, Cr, Hg, Mn, Ni, Pb, Tl
and V etc must be exposed to much higher than background levels of these hazardous metals. Multiple
pathways of exposure may exist for populations near hazardous waste site.
Conclusion
Despite continuous efforts made by many research groups the data on air pollution and health in India is not
adequate and more needs to be done in this regard. The integration of different agencies involved in such
works need to be strengthened. The techniques like PIXE though available at few places can address the
problem of analysis of large number of samples coming from different places. The indigenous efforts of
developing aerosol sampling techniques are needed. The epidemiological studies relating to aerosol

10. concentrations with cardiopulmonary diseases, which are non-existent at present in India, need to be
undertaken without delay.
References
1. American Thoracic Society 1996: Committee for Environmental and Occupational Health
Assembly: R Bescom, PA Bromberg, DA Costa et al. Health effects of outdoor air pollution.
Part 2. Am J Respir Crit Med 153: 477-498.
2. Aposhian, H.V., 1989: Biochemical toxicology of arsenic. In: Reviews in Biochemical
Toxicology. E Hodgson, JR Bend, RM Phipot (Eds.) pp.265-299. New York: Elsevier.
3. Arowolo, T.A., 2004: Heavy metals and health. West Indian Medical Journal, 53(2), 63-5.
4. Bajwa, Bhatia, I., and Ghosh, D.K., 1999: Heavy metal dispersion along road side habitats of
India. J Envir and poll 6:33-42.
5. Bandhu, H.K., Puri, S., Garg, M.L., Shahi, J.S., Mehta, D., Dhawan, D.K., Singh, N., Mangal,
P.C., and Trehan P.N., 1998: Monitoring of urban air pollution using EDXRF technique.
Radiation Physics and Chemistry 51(4-5): 625-626.
6. Bandhu, H.K., Puri, S., Garg, M.L., Singh, B., Shahi, J.S., Mehta, Swietlick, D.E., Dhawan
D.K., Mangal, P.C., Singh N., 2000: Elemental composition and sources of air pollution in city
of Chandigarh, India using EDXRF and PIXE technique. Nuclear Instruments and Methods in
Physics Research B 160:126-138.
7. Bencko, V., 1983: Nickel: a review of its occupational and environmental toxicology, J. Hyg
Epidemiol Microbiol Immunol 27, 237-247.
8. Benson, F.B., Henderson, J.J., and Caldwell, D.E., 1972: Indoor-outdoor air pollution
relationship: a literature review. Pub. No. AP-112.Research Triangle Park, NC: US EPA.
9. Ferris Jr, B.G., Speizer, F.E., Splenger, J.D., 1979: Effects of sulfur dioxide and
respirable particles on human health: methodological and demography of population in
Englert, N., 2004: Fine particles and human health—a review of epidemiological studies.
Toxicology Letters, 149, 235–242.
10. Faroon, O.M., Williams, M., Connor, R.O., 1994: A review of the carcinogenicity of chemical
most frequently found at national priorities list sites, Toxicol Ind Health 10, 203-230.
11. Federal Register 1971: National primary and secondary ambient air quality standards. Fed. Reg
36: 8186-8201.
12. study. Am Rev Respir Dis 120:767-779.
13. Flegal, A.R., Smith, D.R., 1995: Measurements of environmental lead contamination and human
exposure, Rev Environ Contam Toxicol 143, 1-45.
14. Gaghate, D.G., and Hasan, M.Z., 1999. Ambient lead level in urban Areas. Bulletin of Environ
Contamination and Toxicology 62(4): 403-408.
15. Garg R.R., Puri S., Singh S., Mehta D., Shahi J.S., Garg M.L., Singh Nirmal, Mangal P.C.,
Trehan P.N., 1998: Measurements of L X-ray Fluorescence cross sections and yields for
elements in the atomic range 41 Z 52 at 5.96 keV, Nuclear Instruments and Methods in
Physics Research B 72:147-152.
16. Gokhale S.B. and Patil 2004: Size distribution of aerosols (PM10) and lead (Pb) near traffic
intersections in Mumbai (India). Environ Monit Assess. 2004 Jul; 95(1-3):311-24.
17. Hajivaliei M, Garg ML, Handa DK, Govil KL, Kakavand T, Vijayan V, Singh KP and Govil IM.
1999: PIXE Analyis of ancient Indian coins, Nuclear Instruments and Methods in Physics
Research B, 150, 645-650.
18. Holgate, S.T., Samet, J.M., Koren, H.S. and Maynard, R.L., 1999: Air Pollution and Health.
Academic Press USA.
19. Hopke, P.K., Xie, Y., Raunemaa, T., Biegalski, S., Landsberger, S., Maenhaut, W., Artaxo, P., Cohen,
D., 1997: Characterisation of the Gent Stacked Filter Unit PM10 Sampler, Aerosol Science and
Technology, 27, 726-735.
20. Huel, G., Boudene, C., Jouan, M., Lazar, P., 1986: Assessment of exposure to lead of the general
population in the French community through biological monitoring, Int. Arch Occup Environ
Health 58, 131-139.

11. 21. Kotrappa, P., 1972: Shape factor for aerosols of coal, VO2, TiO2 in respirable size range,
assessment of air borne particles. Proceedings of the 3rd Rochester International Conference on
Environmental Toxicity, Rochester, New York.
22. Liou, S.H., Wu, T.N., Chiang, H.C., Yang, G.Y., Wu, Y.Q., Lai, J.S. Ho, S.T. Guo, Y.L., Ko,
Y.C., and Chang, P.Y. 1994: Blood lead levels in the general population of Taiwan, Republic of
China, Int. Arch Occup Environ Health 66, 255-260.
23. Maxwell JA, Teesdale WJ, Campbell. The Guelph PIXE software package II Nuclear
Instruments and Methods in Physics Research B, 95, 407, 1995.
24. Mohanraj R., Azeez P.A., Priscilla T., 2004: Heavy metals in airborne particulate matter of
urban Coimbatore. Arch Environ Contam Toxicol. 47(2):162-7.
25. National Workshop on Lead Exposure: Prevention and Control of Poisoning 2001. (Sponsored
by WHO-MoEF, India) at Industrial Toxicology Research Centre, Lucknow.
26. Negi, B.S., Sadasivan, S., 1987: Aerosol Composition and Sources in Urban Areas in India, U.C.
Mishra, Atoms. Environ. 21, 1259-1266.
27. NRC 1991. National Research Council (NRC) and committee on advances in Assessing Human
Exposure to airborne pollutants. Human Exposure Assessment for air borne pollutants:
Advances and opportunities. Washington, DC: National Academy Press
28. Oberdarster, G., Ferin J., and Lehnert, B.E., 1995: Correlation between particle size, in-vivo particle
persistence and lung injury. Environmental Health Perceptive; 102: 173-177.
29. Parr, R.M., Stone, S.F., and Zeisler, R., 1996: Environmental Protection: Nuclear analytical techniques
in air pollution monitoring and research, IAEA Bulletin 2, 16-21.
30. Pope III, C.A., Dockery, D.W., Sachwartz, J., 1995: Review of epidemiological evidence of
health effects of particulate air pollution. Inhal Toxicol 7:1-18.
31. Saksena, S., Joshi, V., and Patil, R.S., 2002: Determining Spatial Patterns in Delhi’s Ambient
Air Quality Data Using Cluster Analysis, East-West Center Working Papers 1-28
32. Samet, J.M., Marbury, M.C., Spengler, J.D., 1988: Health effects and sources of air pollution.
Part 2. Am Rev Respir Dis 137:221-242.
33. Samet, J.M., Marbury, M.C., and Spengler, J.D., 1978: Health effect and sources of indoor
pollution. Am Rev Respir Dis 136:1486-1508.
34. Sanborn M.D., Abelsohn, M. Campbell and Weir, E., 2002: Identifying and managing adverse
environmental health effects: 3 Lead exposure. Canadian Medical Association Journal, 166(10),
1287-1292.
35. Schroeder, W.H., Dobson, M., Kane D.M., and Johnson, N.D., 1987: Toxic trace elements
associated with airborne particulate matter: a review. J Air Pollut Control Assoc 37: 1267-1285.
36. Schutz, A., Barreegard L., Sallsten, G., Wilske, J., Manay, N., Pereira, L., Cousillas, Z.A., 1997:
Bloodlead in Uruguayan children and possible sources of exposure, Environ Res. 74, 17-23.
37. Schwartz, J., Morris, R., 1995: Air pollution and hospital admissions for cardiovascular disease in
Detroit, Michigan. American Journal of Epidemiology July1; 142(1): 23-5.
38. Schwela, D., 2000: Air Pollution and health in urban areas, Rev. Environ. Health 15, 13-42.
39. Sharma R., Pervez S., 2004: A case study of spatial variation and enrichment of selected
elements in ambient particulate matter around a large coal-fired power station in central India.
Environ Geochem Health. Dec;26(4):373-81.
40. Sharma, S., Sethi, G.R., Rohtagi, A., Chaudhary, A., Shanker, R., Bapna, J.S., Joshi, V., Sapir,
D.G., 1998: Indoor air quality and acute lower respiratory infection in Indian urban slums.
Environ Health perspectives 106:291-297.
41. Singh, B., Dhawan, D., Nehru, B., Garg, M.L., Mangal, P.C., Chand B., and Trehan, P.N., 1994:
Impact of lead pollution on the status of other trace metals in blood and alterations in Hepatic
functions, Biological Trace Element Research 40, 21-29.
42. Singh, N., Pandey, V., Misra, J., Yunus, M., and Ahmad, K.J., 1997: Atmospheric Lead
pollution from vehicular emission –measurements in plants, soil and milk samples. Envir
Monitoring and Assessment 459(1): 9-19.

12. 43. Smichowski P, Marrero J, Darý´o Go´mez., 2005: Inductively coupled plasma optical emission
spectrometric determination of trace element in PM10 airborne particulate matter collected in an
industrial area of Argentina. Micro-chemical Journal 80, 9– 17.
44. Speizer, F.E., 1989: Studies of acid aerosols in six cities and in a new multi-city investigation:
design issue. Environ Health Perspect 79: 61-67.
45. TERI Report for World Bank, 2001: Review of past and on-going work on Urban air quality in
India.
46. Tripathi, R.M., Raghunath, R., Kumar, V., Sastry, V.N., and Sadasivan, S., 2001: Atmospheric
and children blood lead as indicators of vehicular traffic and other emission sources in Mumbai,
India. The Science of the Total Environment 267:101-108.
47. U.S. Environmental Protection Agency (EPA), Airborne Particulate Matter (PM) Research
Centers, Project officer, Deran Pashayan, 1999-2004, Website,
http://es.epa.gov./ncerqa/centres/airpm/
48. US EPA 1974: Health Consequences of Sulphur Oxide: A Report from CHESS, 1970-1971.
EPA-650/1-74-004. Research Triangle Park, NC: US EPA.
49. US EPA 1993: Indoor-Outdoor Air Pollution Relationships, volume II: An annotated
Bibliography. Pub. No. AP-112b. Research Triangle Park, NC: US EPA.
50. Vishwanadham, D.V., Mishra, S. and Satyanarayana A.V., 1995: Climatological atmospheric
dilution indices over India. Indian Journal of Environment Protection 15(10): 734-738.
51. Van Gricken R.E. and Markowicz, A.A. eds., 1992: in: Handbook of X- ray Spectrometry
(Marcel Dekker, New York)
52. World Health Organization 1987: Air Quality Guidelines for Europe. European Series No. 23,
Geneva: Regional Publications.
53. Wright, R.O., Shannon, M.W., Wright, R.J., Hu, H., 1999: Association between iron deficiency
and low-level lead poisoning in an urban primary care clinic, Am J Public Health 89, 1049-
1053.
54. Yang, J.S., Kang, S.K., Park, I.J., Rhee, K.Y., Moon, Y.H., Sohn, D.H., 1996: Lead
concentrations in blood among the general population of Korea, Int. Arch Occup Environ Health
68, 199-202.
ECRD.IN