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December 2000

PM Data Analysis Workbook: Background

1

Background


Emissions that Contribute
to PM Mass


Properties of PM


PM Formation in the
Atmosphere


Atmospheric Transport

of PM


Objectives of the PM
Monitoring Program


Critical Issues for Data
Interpretation


Summary


References

Note that conclusions should not be drawn

regarding attainment or non
-
attainment

status based on a single year of data.

U.S. EPA, 2000

1999 annual mean PM
2.5

concentrations

December 2000

PM Data Analysis Workbook: Background

2

Emissions that Contribute to PM Mass


Primary PM (directly emitted):


Suspended dust


Sea salt


Organic carbon


Elemental carbon


Metals from combustion


Small amounts of sulfate
and nitrate




Secondary PM (gases that form
PM in the atmosphere):


Sulfur dioxide (SO
2
): forms
sulfates


Nitrogen oxides (NO
x
):
forms nitrates


Ammonia (NH
3
): forms
ammonium compounds


Volatile organic compounds
(VOC): forms organic
carbon compounds



PM is composed of a mixture of primary and secondary compounds.

December 2000

PM Data Analysis Workbook: Background

3


NaCl



salt is found in PM near sea
coasts, open playas, and after

de
-
icing materials are applied.


Organic Carbon (OC)


consists
of hundreds of separate compounds
containing mainly carbon,
hydrogen and oxygen.


Elemental Carbon (EC)


composed of carbon without much
hydrocarbon or oxygen. EC is
black, often called soot.


Liquid Water



soluble nitrates,
sulfates, ammonium, sodium, other
inorganic ions, and some organic
material absorb water vapor from
the atmosphere.



Major PM
2.5

Components

Chow and Watson, 1997


Geological Material


suspended
dust consists mainly of oxides of
Al, Si, Ca, Ti, Fe, and other metal
oxides.


Sulfate



results from conversion
of SO
2

gas to sulfate
-
containing
particles.


Nitrate



results from a reversible
gas/particle equilibrium between
NH
3
, HNO
3
, and particulate
ammonium nitrate.


Ammonium



ammonium
bisulfate, sulfate, and nitrate are
most common.

Most PM mass in urban and nonurban areas is composed of a
combination of the following chemical components:

December 2000

PM Data Analysis Workbook: Background

4

Common PM
2.5

Emission Source Profiles
(1 of 2)

Emission source profiles from EPA SPECIATE for light duty vehicles (profile 31230) and oil
-
fired power plant (profile 11510).

Note differences in Ni and Br, for example. Data are shown using a log scale. (SPECIATE)

December 2000

PM Data Analysis Workbook: Background

5

Common PM
2.5

Emission Source Profiles
(2 of 2)

Emission source profiles from EPA SPECIATE for a municipal incinerator (profile 17106) and Earth’s crust (profile 43309).

Note differences in Zn, Cl, S, and Cu, for example. Data are shown using a log scale. (SPECIATE)

December 2000

PM Data Analysis Workbook: Background

6

AIRS Codes for PM
2.5

88102

Antimony PM2.5

88103

Arsenic PM2.5

88104

Aluminum PM2.5

88107

Barium PM2.5

88109

Bromine PM2.5

88110

Cadmium PM2.5

88111

Calcium PM2.5

88112

Chromium PM2.5

88113

Cobalt PM2.5


88114

Copper PM2.5


88115

Chlorine PM2.5

88117

Cerium PM2.5

88118

Cesium PM2.5

88121

Europium PM2.5

88124

Gallium PM2.5

88126

Iron PM2.5

88127

Hafnium PM2.5

88128

Lead PM2.5

88131

Indium PM2.5

88132

Manganese PM2.5

88133

Iridium PM2.5

88134

Molybdenum PM2.5

88136

Nickel PM2.5

88140

Magnesium PM2.5

88142

Mercury PM2.5

88143

Gold PM2.5

88146

Lanthanum PM2.5

88147

Niobium PM2.5

88152

Phosphorous PM2.5

88154

Selenium PM2.5

88160

Tin PM2.5

88161

Titanium PM2.5

88162

Samarium PM2.5

88163

Scandium PM2.5

88164

Vanadium PM2.5

88165

Silicon PM2.5

88166

Silver PM2.5

88167

Zinc PM2.5

88168

Strontium PM2.5

88169

Sulfur PM2.5

88170

Tantalum PM2.5

88172

Terbium PM2.5

88176

Rubidium PM2.5

88180

Potassium PM2.5


88183

Yttrium PM2.5

88184

Sodium PM2.5


88185

Zirconium PM2.5

88186

Wolfram PM2.5

88301

Ammonium Ion PM2.5

88302

Sodium Ion PM2.5

88303

Potassium Ion PM2.5

88305

Organic Carbon PM2.5

88306

Nitrate PM2.5

88307

Elemental Carbon PM2.5

88308

Carbonate Carbon PM2.5

88403

Sulfate PM2.5


December 2000

PM Data Analysis Workbook: Background

7

Properties of PM


Physical, Chemical and Optical
Properties


Size Range of Particulate Matter
(PM)


Mass Distribution of PM vs. Size:
PM
10
, PM
2.5


Fine and Coarse Particles


Fine Particles: PM
2.5


Coarse Particle Fraction:

PM
10
-
PM
2.5
; Relationship of PM
2.5

and PM
10


Chemical Composition of PM vs.
Size


Internal and External Mixtures


Optical Properties of PM

Husar, 1999

December 2000

PM Data Analysis Workbook: Background

8

Physical, Chemical and Optical Properties


PM is characterized by its physical, chemical, and optical properties.


Physical properties include particle size and shape. Particle size refers to
particle diameter or “equivalent” diameter for odd
-
shaped particles.
Particles may be liquid droplets, regular or irregular shaped crystals, or
aggregates of odd shape.


Particle chemical composition may vary including dilute water solutions
of acids or salts, organic liquids, earth's crust materials (dust), soot
(unburned carbon), and toxic metals.


Optical properties determine the visual appearance of dust, smoke, and
haze and include light extinction, scattering, and absorption. The optical
properties are determined by the physical and chemical properties of the
ambient PM.


Each PM source type produces particles with a specific physical,
chemical, and optical signature. Hence, PM may be viewed as several
pollutants since each PM type has its own properties and sources and
may require different controls.


December 2000

PM Data Analysis Workbook: Background

9

Size Range of Particulate Matter


The size of PM particles ranges from about tens of nanometers (nm) (which corresponds to molecular
aggregates) to tens of microns (70

m


the size of human hair).


The smallest particles are generally more numerous, and the number distribution of particles
generally peaks below 0.1

m. The size range below 0.1

m is also referred to as the ultrafine range.


The largest particles (0.1
-
10

m) are small in number but contain most of the PM volume (mass).
The volume (mass) distribution can have two or three peaks (modes). The bi
-
modal mass
distribution has two peaks.


The peak of the PM surface area distribution is always between the number and the volume peaks.

Husar, 1999

December 2000

PM Data Analysis Workbook: Background

10

Mass Distribution of PM vs. Size: PM
10
, PM
2.5


The mass distribution tends to be bi
-
modal with the saddle in the 1
-
3

m size range.


PM
10

refers to the fraction of the PM mass 10

m or less in diameter.


PM
2.5
,

or fine mass, refers to the fraction of the PM mass 2.5

m or less in size.


The difference between PM
10

and PM
2.5

constitutes the coarse fraction.


The fine and coarse particles have different sources, properties, and effects. Many of the known
environmental impacts (health, visibility, acid deposition) are attributed to PM
2.5
.


There is a natural division of atmospheric particulates into fine and coarse fraction based on particle size.

Fine

Coarse

Husar, 1999

December 2000

PM Data Analysis Workbook: Background

11

Fine and Coarse Particles
(1 of 2)

Adapted from Seinfeld and Pandis, 1998

Fine
Coarse
Formation pathway
Chemical reaction, nucleation,
condensation, coagulation,
cloud/fog processing
Mechanical disruption, suspension
of dust
Composition
SO
4
=
, NO
3
-
, NH
4
+
, H
+
, EC,
organics, water, metals (
Pb,
Cd, V,
Ni, Cu,
Zn,
Mn, Fe…)
Resuspended road dust; coal and oil
flyash;
crustal elements (
Si, Al,
Ti,
Fe) oxides; CaCO
3
,
NaCl; pollen,
mold, spores; plant and animal
debris
Sources
Combustion (coal, oil,
gasoline, diesel, wood);
gas-to-particle conversion of
NO
x
, SO
3
, and
VOCs;
smelters, mills, etc.
Resuspension of industrial soil and
dust; suspension of soil (farming,
mining, unpaved roads), biological
sources, construction/demolition,
ocean spray
Atmospheric lifetime
Days to weeks
Minutes to days
Travel distance
100s to 1000s km
Generally < 10s km
December 2000

PM Data Analysis Workbook: Background

12

Fine and Coarse Particles
(2 of 2)


The principal types of secondary particles are ammonium sulfate
and ammonium nitrate formed in the atmosphere from gaseous
emissions of SO
2

and NO
x

reacting with NH
3.


There is a direct relationship between the particle size and the
atmospheric residence time of particles:

Lyons and Scott, 1990

December 2000

PM Data Analysis Workbook: Background

13

Fine Particles: PM
2.5


Fine particles (


2.5

m) result primarily from combustion of fossil
fuels in industrial boilers, automobiles, and residential heating systems.


A significant fraction of the PM
2.5

mass over the United States is
produced in the atmosphere through gas
-
particle conversion of
precursor gases such as sulfur oxides, nitrogen oxides, organics, and
ammonia. The resulting secondary PM products are sulfates, nitrates,
organics, and ammonium.


Some PM
2.5

is emitted as primary emissions from industrial activities
and motor vehicles, including soot (unburned carbon), trace metals,
and oily residues.


Fine particles are mostly droplets, except for soot which is in the form
of chain aggregates.


Over the industrialized regions of the United States, anthropogenic
emissions from fossil fuel combustion contribute most of the PM
2.5
.
Biomass burning, windblown dust, and sea salt also contribute.


Fine particles can remain suspended for long periods (days to weeks)
and contribute to ambient PM levels hundreds of km away from where
they are formed.

December 2000

PM Data Analysis Workbook: Background

14

Spatial Variability of PM
2.5

Site correlation of 1999 24
-
hr
average PM
2.5

concentrations
against distance between sites. Plot
prepared using SAS. Data obtained
from AIRS on July 12, 2000. Only
sites within 100 km were
considered; sites had to have at
least 10 data pairs matching; no
adjustments for different time
zones were made. U.S. EPA, 2000


This analysis characterizes the spatial variability of 24
-
hr average PM
2.5

by calculating
the linear correlation coefficients for each possible pair of sites and plotting these as a
function of distance.


The correlation remains very high in most of the data out to 100 km. This relationship
supports the notion that PM
2.5

is a macro
-
scale or regional pollutant.

December 2000

PM Data Analysis Workbook: Background

15

Coarse Particles: PM
10
-
PM
2.5


Coarse particles (2.5 to 10

m) are generated by mechanical processes
that break down crustal material into dust that can be suspended by the
wind, agricultural practices, and vehicular traffic on unpaved roads.


Coarse particles are primary in that they are emitted as windblown dust
and sea spray in coastal areas. Anthropogenic coarse particle sources
include flyash from coal combustion and road dust from automobiles.


The chemical composition of the coarse particle fraction is similar to
that of the earth's crust or the sea, but sometimes coarse particles also
carry trace metals and nitrates.


Coarse particles are removed from the atmosphere by gravitational
settling, impaction to surfaces, and scavenging by precipitation. Their
atmospheric residence time is generally less than a day, and their typical
transport distance is below a few hundred km. Some dust storms tend to
lift the dust to several km altitude, which increases the transport distance
to many thousand km.

Albritton and Greenbaum, 1998

December 2000

PM Data Analysis Workbook: Background

16

Relationship of PM
2.5

and PM
10
(1 of 2)


Different areas may have different relationships between PM
2.5

and PM
10
. In this
example, the coarse fraction comprises a larger portion of PM
10

in the southwestern
United States

than in the northeasteern
United States
.

U.S. EPA, 2000

December 2000

PM Data Analysis Workbook: Background

17

Relationship of PM
2.5

and PM
10
(2 of 2)


PM
2.5

and PM
10

may have a different relationship during different seasons.


In these examples from 1988, PM
2.5

seasonal patterns are similar to those for PM
10

in the northeast
while seasonal patterns of PM
2.5

and PM
10

differ in southern California.


PM
2.5

comprises a larger fraction of PM
10

in the northeastern United States than in southern
California. (Note that the concentrations shown in the monthly plots are averages; thus, the sum of
fine and coarse concentrations may not equal PM
10
concentrations.)

Husar, 1999

December 2000

PM Data Analysis Workbook: Background

18

Chemical Composition of PM vs. Size


The chemical species that make up
the PM occur at different sizes.


For example in Los Angeles,
ammonium and sulfate occur in the
fine mode,

2.5

m in
aerodynamic diameter.
Carbonaceous soot, organic
compounds, and trace metals tend
to be in the fine particle mode.


The sea salt components, sodium
and chloride, occur in the coarse
fraction, > 2.5

m. Windblown
and fugitive dust are also found
mainly in the coarse mode.


Nitrates may occur in fine and
coarse modes.

Husar, 1999

December 2000

PM Data Analysis Workbook: Background

19

Internal and External Mixtures of Particles


During their multi
-
day atmospheric residence time, particles from different
sources and with different compositions are mixed together by a range of
atmospheric processes. The resulting particles can be either external or internal
mixtures.


In an external mixture, the particle composition will be non
-
uniform because the
components from different sources remain separate (e.g., a soot particle inside a
sulfate droplet, as illustrated by the electron micrograph below).


In an internal mixture, the particle composition is uniform because the individual
components are completely mixed.


The main process that produces internal mixtures is processing by water such as
in fog and/or cloud scavenging and subsequent evaporation.


Electron micrograph of a PM
2.5

droplet residue.
Evidently, the droplet contained a solid particle,
possibly soot.

Husar, 1999

December 2000

PM Data Analysis Workbook: Background

20

Optical Properties of PM


Particles effectively scatter and
absorb solar radiation.


The scattering efficiency per PM
mass is highest at about 0.5

m.
This is why, for example,

10

g of fine particles

(0.2 < D < 1

m) scatter over ten
times more than 10

g of coarse
particles (D > 2.5

m).

Husar, 1999

December 2000

PM Data Analysis Workbook: Background

21



Sulfate Formation in the Atmosphere



Sulfate Formation in Clouds



Seasonal SO
2
-
to
-
Sulfate Transformation Rate



Residence Time of Sulfur and Organics



Nitrate Formation in the Atmosphere



Links to Ozone Formation, Health, and Visibility

PM Formation in the Atmosphere

December 2000

PM Data Analysis Workbook: Background

22

Sulfate Formation in the Atmosphere


Sulfates constitute about half of the PM
2.5

in the eastern United States. Virtually all
the ambient sulfate (99%) is secondary,
formed within the atmosphere from SO
2
.


About half of the SO
2

oxidation to sulfate
occurs in the gas phase through
photochemical oxidation in the daytime.
NO
x

and hydrocarbon emissions tend to
enhance the photochemical oxidation
rate.


The condensation of H
2
SO
4

molecules
results in the accumulation and growth of
particles in the 0.1
-
1.0

m size range


hence the name “accumulation
-
mode”
particles.

Husar, 1999

December 2000

PM Data Analysis Workbook: Background

23

Sulfate Formation in Clouds


At least half of the SO
2

oxidation takes
place in cloud droplets as air molecules
pass through convective clouds at least
once every summer day.


Within clouds, the soluble pollutant gases,
such as SO
2
, get scavenged by the water
droplets and rapidly oxidize to sulfate.


Only a small fraction of the cloud droplets
rain out; most droplets evaporate at night
and leave a sulfate residue or “convective
debris”. Most elevated layers above the
mixing layer are pancake
-
like cloud
residues.


Such cloud “processing” is responsible for
internally mixing PM particles from many
different sources. It is also believed that
such “wet” processes are significant in the
formation of the organic fraction of PM
2.5
.

Husar, 1999

Heterogeneous Oxidation

December 2000

PM Data Analysis Workbook: Background

24

Seasonal SO
2
-
to
-
Sulfate Transformation Rate



SO
2
-
to
-
sulfate transformation
rates peak in the summer due

to enhanced summertime
photochemical oxidation and
SO
2

oxidation in clouds.

Husar, 1999

Transformation rates derived from the

CAPITA Monte Carlo Model, Schichtel

and Husar, 1997.

December 2000

PM Data Analysis Workbook: Background

25

Residence Time of Sulfur and Organics


SO
2

is depleted mostly by dry deposition (2 to 3% per hour) and also by
conversion to sulfate (up to 1% per hour). This gives SO
2

an atmospheric
residence time of only 1 to 1.5 days.


It takes about a day to form the sulfate PM. Once formed, sulfate is removed
mostly by wet deposition at a rate of 1 to 2 % per hour yielding a residence time
of to 5 days.


Overall, sulfur as SO
2

and sulfate is removed at a rate of 2 to 3% per hour, which
corresponds to a residence time of 2 to 4 days.


These processes have at least a factor of two seasonal and geographic variation.


It is believed that the organics in PM
2.5

have a similar conversion rate, removal
rate, and atmospheric residence time.

Husar, 1999

December 2000

PM Data Analysis Workbook: Background

26

Nitrate Formation and Removal in the Atmosphere


NO
2

can be converted to nitric acid (HNO
3
) by reaction with hydroxyl
radicals (OH) during the day.


The reaction of OH with NO
2

is about 10 times faster than the OH
reaction with SO
2
.


The peak daytime conversion rate of NO
2

to HNO
3

in the gas phase
is about 10 to 50% per hour.


During the nighttime, NO
2

is converted into HNO
3

by a series of
reactions involving ozone and the nitrate radical.


HNO
3

reacts with ammonia to form particulate ammonium nitrate
(NH
4
NO
3
).


About one
-
third of anthropogenic NO
x

emissions in the United States are
estimated to be removed by wet deposition.


Thus, PM nitrate can be formed at night and during the day; daytime
photochemistry also forms ozone.

December 2000

PM Data Analysis Workbook: Background

27

PM and Ozone
(1 of 2)

NESCAUM, 1992

The formation of a substantial fraction of secondary PM
2.5

depends on
photochemical gas phase reactions which also produce ozone.

Concentrations of OH radicals, ozone, and hydrogen peroxide (H
2
O
2
), formed by gas
phase reactions involving VOCs and NO
x
, depend on the concentrations of the
reactants and on meteorological conditions including temperature, solar radiation,
wind speed, mixing volume, and synoptic weather conditions.

December 2000

PM Data Analysis Workbook: Background

28

PM and Ozone
(2 of 2)


An illustration of some of the
environmental factors that
influence the production of
ozone and secondary PM
formation.


Meteorological (e.g., mixing
heights, transport) and

chemical conditions (e.g.,
emissions composition and
intensity) affect the
concentration of secondary

PM and ozone precursors.

RRWG Policy Team, 1999

Biogenic
VOC
Emissions,
Composition, and
Intensity
Anthropogenic
VOC
Emissions,
Composition, and
Intensity
Carry-over VOC
Composition
NO
x
,
CO, O
3
Chemical
Conditions
NO
x

Emissions
Meteorological
Conditions
Transport and
Mixing
Temperature
Radiation
Environmental
Conditions
Maximum Mixing
Radical
Initiation,
Propagation
(VOC),
Termination
Cycle
Toxics
and
Nitrates
Secondary PM
Formation
O
3

Production
NO
x
Emissions,
Oxidation,
Photolysis
,Loss
Cycle
Concentration of
NO, NO
2
, and
each VOC
December 2000

PM Data Analysis Workbook: Background

29

PM, Health, and Visibility


Human health research indicates that PM mass correlates
with sickness and death. The components of PM that cause
these health effects are not known.


Fine particles and/or coarse particles may contribute to
these health effects.


Visibility, the distance one can distinguish a target, is
influenced by lighting, contrast of the target to the
background, and most importantly, the size, color, and
concentration of the particles between the observer and the
target.

Thus, we need to better understand the chemical and physical

characteristics and the formation of PM in order to identify the links

between, and reduce the influence of, PM on health and visibility.

December 2000

PM Data Analysis Workbook: Background

30

Summary of Factors Influencing PM
Concentrations: Meteorology


Meteorological parameters important to PM concentration variations include
temperature, relative humidity, mixing heights, wind speed, and wind
direction. In this example, higher PM
2.5

concentrations occur under lower
wind speed conditions.


Seasonal changes in meteorology effect diurnal, seasonal, and chemical
patterns of PM.

Episodic relationship between PM
2.5

and afternoon wind

speed at urban California sites (1988
-
1998). The curve
is a spline function fitting through the 99th percentile of
the data. Chu and Cox, 1998.

December 2000

PM Data Analysis Workbook: Background

31

Summary of Factors Influencing PM
Concentrations: Emissions


Time patterns of emissions


Diurnal patterns (e.g., traffic, biogenics)


Weekday/weekend patterns


Source type and location of emissions


Point versus area versus mobile source emissions


Height of emissions


Primary PM emissions vs. secondary PM


Chemical composition (e.g., Ni and V from oil, Se from
coal, Na from sea salt or winter road salt)

Temporal, spatial, and chemical emissions characteristics influence
PM concentrations and provide clues to source contributions.

December 2000

PM Data Analysis Workbook: Background

32

Atmospheric Transport of PM


Transport Mechanisms


Influence of Transport on Source Regions


Plume Transport


Long
-
range Transport


Atmospheric Residence Time and Spatial Scales


Residence Time Dependence on Height


Range of Transport


December 2000

PM Data Analysis Workbook: Background

33

The three major airmass source regions that
influence North America are the northern Pacific,
the Arctic, and the tropical Atlantic. During the
summer, the eastern United States is influenced

by the tropical airmass from the Gulf of Mexico.

The three transport processes that shape
regional dispersion are wind shear, veer, and
eddy motion. Homogeneous hazy airmasses
are created through shear and veer at night
followed by vigorous vertical mixing during
the day.

Transport Mechanisms

Pollutants are transported by the atmospheric flow field which
consists of the mean flow and the fluctuating turbulent flow.

Husar, 1999

Regional
-
Scale Pollutant Mixing Mechanisms

Axial Mixing Lateral Mixing Random Mixing


Shear Veer Eddy Diffusion

December 2000

PM Data Analysis Workbook: Background

34

Low wind speeds over a source region
allows pollutants to accumulate. High
wind speeds ventilate a source region
preventing local emissions from
accumulating.

Horizontal Dilution

Vertical Dilution

In urban areas, during the night and early
morning, the emissions are trapped by
poor ventilation. In the afternoon, vertical
mixing and horizontal transport tend to
dilute the concentrations.

Influence of Transport on Source Regions

Husar, 1999

December 2000

PM Data Analysis Workbook: Background

35

Plume Transport


Much of the man
-
made PM
2.5

in
the eastern United States is
from SO
2

emitted by power
plants.


Plume transport varies diurnally
from a ribbon
-
like layer near
the surface at night to a well
-
mixed plume during the
daytime.


Even during the daytime
mixing, individual power plant
plumes remain coherent and
have been tracked for 300+ km
from the source.


Most of the plume mixing is
due to nighttime lateral
dispersion followed by daytime
vertical mixing.

Husar, 1999

December 2000

PM Data Analysis Workbook: Background

36

Long
-
range Transport


In many remote areas of the United States, high
concentrations of PM
2.5

have been observed. Such events
have been attributed to long
-
range transport.


Long
-
range transport events occur when there is an airmass
stagnation over a source region, such as the Ohio River
Valley, and the PM
2.5

accumulates. Following the
accumulation, the hazy airmass is transported to the receptor
areas.


Satellite and surface observations of fine particles in hazy
airmasses provide a clear manifestation of long
-
range
pollutant transport over eastern North America.

Husar, 1999

December 2000

PM Data Analysis Workbook: Background

37

Atmospheric Residence Time and Spatial Scales


PM
2.5

sulfates reside 3 to 5 days in
the atmosphere.


Ultrafine 0.1

m particles coagulate
while coarse particles above 10

m
settle out more rapidly.


PM in the 0.1
-
1.0

m size range has
the longest residence time because it
neither settles nor coagulates.



Atmospheric residence time and transport
distance are related by the average wind
speed, about 5 m/s.


Residence time of several days yields

“long
-

range transport” and more uniform
spatial pattern.


On average, PM
2.5

particles are transported
1000 or more km from the source of their
precursor gases.

Husar, 1999

December 2000

PM Data Analysis Workbook: Background

38

Residence Time Dependence on Height


The PM
2.5

residence time increased with height.


Within the atmospheric boundary layer (the lowest 1 to 2 km), the residence time is

three to five days.


If aerosols are lifted to 1 to 10 km in the troposphere, they are transported for weeks
and many thousands of miles before removal.


The lifting of boundary layer air into the free troposphere occurs by deep convective
clouds and by converging airmasses near weather fronts.

Husar, 1999

December 2000

PM Data Analysis Workbook: Background

39

Range of Transport


The residence time
determines the range of
transport. For example,
given a residence time of

four days (~100 hrs) and a

mean transport speed of

10 mph, the transport
distance is about 1000 miles.


The range of transport
determines the “region of
influence” of specific
sources.

Husar, 1999

December 2000

PM Data Analysis Workbook: Background

40

Objectives of the PM Monitoring Program


The primary objective of the PM monitoring
program is to provide ambient data that support the
nation’s air quality program objectives. At a
minimum, this includes the following actions:


Determine whether health and welfare standards
(NAAQS) are met.


Assess annual and seasonal spatial characterization of PM.


Track progress of the nation and specific areas in meeting
Clean Air Act requirements (provided, for example,
through national trends analyses).


Develop emission control strategies.


Homolya et al., 1998

December 2000

PM Data Analysis Workbook: Background

41

Site Category
Projected Number
Major Purpose
Core Sites
850 Reference
50 Continuous
Min. required for attainment designations.
Continuous needed for air quality index (AQI).
Spatial Averaging/
Special Purpose
200 Reference
other
States requested additional monitors for spatial
averages or other specific monitoring needs.
Continuous
50 Continuous
AQI reporting and further delineation of
source/exposure patterns.
IMPROVE
100 additional
IMPROVE monitors
Supports regional haze rules in class I areas
and PM transport assessment. Speciation.
Routine chemical
speciation
50 required
Up to 250 additional
Trends, source apportionment, model
evaluation, strategy effectiveness, risk
assessment, better understanding of
atmospheric processes.
Super site study
areas
4 to 7 areas with
research grade
equipment
Intensive work on source receptor relationships
in areas representative of PM issues
; health
risk, monitor advances.
Overview of National PM
2.5

Network

Homolya et al., 1998

December 2000

PM Data Analysis Workbook: Background

42

PM
2.5

Implementation Update


The bulk of all compliance and continuous monitoring
sites are to be established by December 31, 1999.


The first chemical speciation sites will begin operation by
November 1999, and installations will continue through
December 31, 2000.


The IMPROVE sites were to have been deployed by
December 31, 1999; however, this schedule has been
delayed.


Operation of the Super
-
sites began with Atlanta in August
1999; the site in Fresno will be next, followed by the
remaining areas (to be announced once grants are
awarded).


Byrd, 1999

December 2000

PM Data Analysis Workbook: Background

43

PM
2.5

Sampling Schedule


Compliance sites [those with federal reference method
samples (FRMS)] will operate largely on an everyday or
one
-
in
-
three
-
day schedule. Some sites will operate on a
one
-
in
-
six
-
day schedule.


Continuous sites will operate every day.


Fifty
-
four speciation sites will operate on a one
-
in
-
three
-
day schedule.


The remaining sites will operate on a one
-
in
-
six
-
day or
episodic schedule, depending on data needs.


The IMPROVE sampling schedule will ultimately match a
one
-
in
-
three
-
day schedule.


Byrd, 1999

December 2000

PM Data Analysis Workbook: Background

44

PM2.5 Monitoring Objectives
Network
Element
NAAQS
Comparison
Public
Information
(AQI)
SIP
Development
Assess
SIPS,
Trends
Health/
Exposure
Assess
Visibility
Methods
Testing
FRM Mass




Continuous
Mass



Speciation
(NAMS)



Speciation
(State)




IMPROVE



Supersites



Site Types

The larger check marks reflect the primary use of the data.

Homolya et al., 1998

December 2000

PM Data Analysis Workbook: Background

45

Analytes
Analytical technique
Filter Medium
Elements Al through
Pb
Energy
dispersive X-ray
fluorescence (XRF)
PTFE
Major ions: sulfate, nitrate,
ammonium, sodium,
potassium
Ion chromatography (IC)
Nylon filter with
nitric acid
denuder
Total, elemental, organic, and
carbonate carbon
Thermal optical analysis
(TOA)
Pre-fired quartz
fiber filter
Data Collected

Homolya et al., 1998

December 2000

PM Data Analysis Workbook: Background

46

Sampling Artifacts and Interferences
(1 of 2)



Homolya et al., 1998

Monitoring Issue
Possible Effects
Possible Solution
Inlet surface deposition
Nitric acid loss
Suspended particle attraction
Coat inlet surface with
PFA.
Use non-plastic surface.
Organic carbon
volatilization
Collection of gas phase organics
(+ bias); loss of particle phase
organics (- bias)
Use denuder to remove gas phase
organics and back-up sorbent to
assess semi-volatiles.
Nitrate particle
volatilization
Loss of nitrate during/after
sampling
Proper ventilation and cooling of
sampler; store filters in sealed
containers and refrigerate.
Sample moisture
Bias in mass measurements
Control relative humidity
equilibration ranges.
Electrostatic charge
Bias in mass measurements
Use radioactive antistatic strip.
Passive deposition
(windblown dust)
Bias (+ ) mass measurements
Reduce filter residence time in
sampler.
Handling
contamination
Invalid samples
Use proper standard operating
procedures.
Filter media artifacts
Nitrate loss, SO
2
conversion
Denuder use and maintenance.
December 2000

PM Data Analysis Workbook: Background

47

Sampling Artifacts and Interferences

(2 of 2)


Organic gas adsorption

(positive bias) comprised up to 50% of the
organic carbon measured on quartz
-
fiber filters in southern California
(Turpin et al., 1994). These studies also indicated that adsorption was
much more important than organic particle volatilization (negative bias).



Sampling losses on the order of 30% of the annual federal standard for
PM
2.5

may be expected due to
volatilization of ammonium nitrate

in
those areas of the country where nitrate is a significant contributor to the
fine particle mass and where ambient temperatures tend to be warm
(Hering and Cass, 1999).


December 2000

PM Data Analysis Workbook: Background

48

Critical Issues for Data Interpretation
(1 of 2)

Issues to be considered when planning and performing data interpretation:


Data availability (mass, ions, metals, organic carbon, speciated organic
carbon, etc.)


Data quality (standard operating procedures, audits, accuracy and
precision, data validation)


Sampling artifacts and interferences (organic carbon volatilization,
nitrate volatilization, moisture)


Data representativeness for planned analysis (nearby sources vs.
regional background)


Sampling duration (24
-
hr data cannot be used to investigate diurnal
changes in photochemistry, emissions and meteorology)


Sampling frequency (1
-
in
-
6 day data cannot be used to investigate
many episodes of high PM)


Availability of complementary data (PM precursor, meteorological,
and visibility data)

Use the decision matrix to proceed from policy
-
relevant objectives,

to data analysis activities, to applicable data and tools.

December 2000

PM Data Analysis Workbook: Background

49

Critical Issues for Data Interpretation
(2 of 2)

Issues to be considered when graphing data:

-
Use visually prominent graphical elements to show the data

-
Do not clutter the interior of the scale
-
line rectangle

-
Preserve visual clarity under reduction and reproduction

-
Put major conclusions into graphical form. Make captions
comprehensive and informative

-
Strive for clarity

-
Understand that a large amount of quantitative information can be
packed into a small region

-
Make graphing data an iterative, experimental process

-
Choose the scales so that the data rectangle fills up as much of the
scale
-
line rectangle as possible

-
Choose consistent scales when data on different panels are
compared

-
Avoid the use of pie charts, stacked bar charts, and three
-
dimensions as it is difficult to decode (i.e., obtain quantitative
information), compare, and interpret these graphs

Cleveland, 1994

December 2000

PM Data Analysis Workbook: Background

50

Summary


This section contains background information on

PM emissions, properties, formation, and transport, and the
objectives of the EPA PM monitoring program.


Critical issues for data interpretation, presentation, and
analysis are also provided to aid data analysts.

December 2000

PM Data Analysis Workbook: Background

51

References

(1 of 2)

Albritton D.L. and Greenbaum D.S. (1998) Atmospheric observations: Helping build the scientific basis for decisions related
to airborne particulate matter.

Byrd L. (1999) Personal communication.

Chow J.C. (1995) Measurement methods to determine compliance with ambient air quality standards for suspended particles.
J. Air & Waste Manage
.,
45
, 320
-
382.

Chow J.C. and Watson J.G. (1997) Guideline on speciated particulate monitoring. Report prepared by Desert Research
Institute and available at <http://www.epa.gov/ttn/amtic/files/ambient/pm25/spec/drispec.pdf>.

Chu S. and W. Cox (1998) Relationship of PM fine to ozone and meteorology. Paper 98
-
RA90A.03 presented at the
Air &
Waste Management Association's 91
st

Annual Meeting & Exhibition, San Diego, CA, June 14
-
18.

Cleveland W. S. (1994)
The Elements of Graphing Data
. Published by Hobart Press, Summit, New Jersey.

Hering S. and Cass G. (1999) The magnitude of bias in the measurement of PM
2.5

arising from volatilization of particulate
nitrate from Teflon filters.
J. Air & Waste Manage. Assoc
.,
49
, 725
-
733.

Hidy G.M., Hales J.M., Roth P.M., and Scheffe R. (2000) Fine particles and oxidant pollution: developing an agenda for
cooperative research.
J. Air & Waste Manage. Assoc
.,
50
, 613
-
632.

Homolya J.B., Rice J., and Scheffe R.D. (1998) PM
2.5

speciation
-

objectives, requirements, and approach. Presentation.
September.

Husar, R. (1999) Draft PM
2.5

topic summaries available at
<http://capita.wustl.edu/PMFine/Workbook/PMTopics_PPT/PMProperties/sld001.htm>
<http://capita.wustl.edu/PMFine/Workbook/PMTopics_PPT/Pm25Formation/sld001.htm>
<http://capita.wustl.edu/PMFine/Workbook/PMTopics_PPT/PMTransport/sld001.htm>
<http://capita.wustl.edu/PMFine/Workbook/PMTopics_PPT/PMOrigin/sld001.htm>
<http://capita.wustl.edu/PMFine/Workbook/PMTopics_PPT/PM10PM25Relationship/sld001.htm>
<http://capita.wustl.edu/PMFine/Workbook/PMTopics_PPT/PMAnalysis/sld001.htm>
<http://capita.wustl.edu/PMFine/Workbook/PMTopics_PPT/Pm25TransportROI/sld001.htm>
<http://capita.wustl.edu/PMFine/Workbook/PMTopics_PPT/DiurnalPattern/sld001.htm>
<http://capita.wustl.edu/PMFine/Workbook/PMTopics_PPT/WeeklyPattern/sld001.htm>
<http://capita.wustl.edu/PMFine/Workbook/PMTopics_PPT/PMGlobalContPattern/sld001.htm>
<http://capita.wustl.edu/PMFine/Workbook/PMTopics_PPT/NaturalEvents/sld001.htm>


December 2000

PM Data Analysis Workbook: Background

52

References
(2 of 2)

NESCAUM (1992) 1992 Regional Ozone Concentrations in the Northeastern United States. Paper available at
<http://capita.wustl.edu/neardat/reports/TechnicalReports/NEozone92/avoztitl.html>.

Reactivity Research Work Group Policy Team (1999) VOC Reactivity Policy White Paper. Prepared for the Reactivity
Research Work Group, October.

Schichtel B. and Husar R. (1997) Derivation of SO
2



SO
4
2
-

Transformation and Deposition Rate Coefficients Over The
Eastern US using a Semi
-
Empirical Approach. Paper available at
<http://capita.wustl.edu/capita/capitareports/mcarlokinetics/mcrateco4_AWMAPres.html>.

Seinfeld J.H. and Pandis S.N. (1998)
Atmospheric chemistry and physics: from air pollution to climate change
. John Wiley
and Sons, Inc., New York, New York.

Turpin B.J., Huntzicker J.J., and Hering S.V. (1994) Investigation of organic aerosol sampling artifacts in the Los Angeles
basin.
Atmos. Environ
.,
28
, 3061
-
3071.

U.S. Environmental Protection Agency (1998) Fact sheet on PM data handling available at
<http://ttnwww.rtpnc.epa.gov/naaqsfin/fs122398.htm>.

U.S. Environmental Protection Agency (1999a) Particulate matter (PM
2.5
) speciation guidance document. Available at
<http://www.epa.gov/ttn/amtic/files/ambient/pm25/spec/specpln3.pdf>.

U.S. Environmental Protection Agency (1999b) General Information regarding PM
2.5

data analysis posted on the EPA
Internet web site <http://www.epa.gov/oar/oaqps/pm25/general.html>.

U.S. Environmental Protection Agency (2000) Internal memorandum of analyses of 1999 PM data for the PM NAAWS
review. September.