f^^>Co^in9
Learning Science Using an
EPA Concentration Model
Georgianne McDonnell, U.S.E.P.A
http://www.epa.gov
Richard Wormell, U.S.E.P.A
http://www.epa.gov
The Center for Innovation in Engineering and Science Education
at Stevens Institute of Technology
http://www.stevens.edu/ciese
-------
Learning Science Using an
EPA Concentration Model
-------
Learning Science Using an
EPA Concentration Model
Georgianne McDonnell, U.S.E.P.A
http://www.epa.gov
Richard Wormell, U.S.E.P.A
http://www.epa.gov
The Center for Innovation in Engineering and Science Education
at Stevens Institute of Technology
http://www.stevens.edu/ciese
Environmental Protection Agency
United States
Center for Innovation In Engineering
and Science Education
Stevens Institute of Technology
Hoboken, New Jersey
-------
Georgianne McDonnell, U.S.E.P.A
http://w w w. epa, go v
Richard Wormell, U.S.E.P.A
http://www.epa. gov
The Center for Innovation in Engineering and Science Education
at Stevens Institute of Technology
http://www.stevens.edu/ciese
Design
Center for Innovation in Engineering and Science Education
at Stevens Institute of Technology
This publication was developed under Agreement No. 2W-0904-NANX awarded by the U.S.
Environmental Protection Agency. It has not been formally reviewed by EPA. The views
expressed in this document are solely those of Stevens Institute of Technology's Center for
Innovation in Engineering and Science Education, and EPA does not endorse any products or
commercial services mentioned in this publication.
Environmental Protection Agency
United States
Center for Innovation in Engineering
and Science Education
Stevens Institute of Technology
Hoboken, New Jersey
-------
Table of Contents
Chapter 1
SdcnCC Guide Introduction vii
Section 1: Air Pollution 1
Section 2: Models 5
Section 3: Overview of the Industrial Source
Complex Model (ISC) 9
Section 4: Pollution Sources 13
SectionS: Transport of Pollutants 17
Section 6: Plumes 19
Section 7: Meteorology 21
Section 8: Buildings 27
Section 9: Terrain, Urban versus Rural 29
Section 10: Receptors, Concentrations and Exposure.. 31
Section 11: Making Sense of ISC Output 37
Section 12: ISC and the Community . 39
Web Links 41
References 43
Chapter 2
Teacher's Guide The Donora Disaster 45
Weather Wisdom 47
Models, Models, Everywhere 49
Long Term Concentration Estimates Unit 51
Short Term Concentration Estimates Unit 53
Final Report 55
Chapter 3
Student Activities The Donora Disaster 57
Weather Wisdom 65
Models, Models, Everywhere 77
Long Term Concentration Estimates Unit 87
Short Term Concentration Estimates Unit 103
Final Report . 129
-------
Introduction
This Science Guide is designed to help students and teachers as they work with the
Downwind project. It will provide the background needed to understand the science
behind the EPA's Industrial Source Complex Long Term and Short Term Models.
This guide is designed for use in classrooms with no Internet access. If Internet access is
available, these lessons would be more effectively taught using the Downwind on-line
project located at: http://www.stevens.edu/ciese/curriculum/downwind/index.html
vii
-------
CHAPTER 1: SCIENCE GUIDE
SECTION 1
Air Pollution
Downwind Project Lesson: The Donora Disaster
Exactly what is air?
Air is a mixture of gases and without it we couldn't survive. The oxygen in the air
we breathe is essential for us to break down food to obtain energy. Table 1 below
shows the composition of unpolluted air:
Table 1: The composition of unpolluted air
Composition of air
Percentage of air
Nitrogen
annH
Oxygen
21
Argon
0.0093
Carbon dioxide
0.03
Methane
0.0002
Inert gases
<1%
Water vapor
variable
It probably wouldn't be easy to find unpolluted air like that shown in Table 1,
although in some remote parts of the earth, with the right conditions, we might
find something close to it.
What causes air pollution?
Whenever anything is added to the air that doesn't naturally belong there, we call
that substance a pollutant. Air pollutants can be produced by a variety of sources.
Some natural air pollutants come from dust, fires, and the soil. Human-produced
pollutants are generated by factories, power plants, pesticides, diesel and
gasoline vehicle exhaust, the burning of fossil fuels, wood, charcoal, and
petroleum refining. One example of a particularly bad form of air pollution is
smog. Combining the words "smoke" and "fog" forms the word smog. Smog has
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
1
-------
SECTION 1
CHAPTER 1: SCIENCE GUIDE
been responsible for serious incidents involving many deaths throughout history,
along with its harmful non-lethal health effects on millions of people around the
world. Examples of two very important episodes caused by smog were: 1) in 1948
in Donora, Pennsylvania, 20 people died and hundreds of others were made sick,
and 2) in the Great Smog of London that occurred in 1952, where it was estimated
that 4,000 people died as a result of a smog that was so thick it made the city of
London pitch black during the daytime hours. According to the National Society
for Clean Air in England, approximately 20,000 lives a year are still shortened as a
result of air pollution in England.
WEB LINKS
Learn more about the history of smog, by exploring the Donora Disaster
Internet Activity that is located at:
http://www.kl2science.org/ciirriculum/downwind/donora.html.
A good web site that discusses the history of smog is located on the PBS
web site: http://www.pbs.org/now/science/smog.html
How do we know if the air is polluted?
First of all, we need to know some information about pollutants. Air pollutants are
usually either gases or particles. We might be able to use our senses to realize that
air is polluted. Eyes burning, nose itching arid other signs and symptoms can all be
warning signs of air pollution. However, this isn't really accurate enough to tell us
anything useful about how much of a pollutant is in the air. More accurate tools
than our senses are needed to measure how much pollutant is in the air.
Scientists and engineers have developed instruments that can be used to measure
or monitor air pollution. One way to measure air pollution is to use badges or
tubes with special chemicals inside to adsorb the pollutants. The badge or tube is
left out in the air for a certain length of time, e.g., a week or a month, and the
chemical adsorbs any pollutant. You might notice that the term "adsorbed" is used
which has a very different meaning from "absorb." Adsorption is when a
substance accumulates on a surface. The tubes are then taken to the laboratory and
analyzed. A second way to measure pollution is by pumping a known volume of
2 CENTER FOR INNOVATION IN ENGINEERING AND SCIENCE EDUCATION AT STEVENS INSTITUTE OF TECHNOLOGY
-------
CHAPTER 1: SCIENCE GUIDE
SECTION 1
air through a filter or chemical. The filter or chemical can then be analyzed in the
laboratory. A third way to measure pollution is to set up an instrument that will
sample the air automatically, at regular intervals, for example, every hour for a
week.
WEB LINK
The EPA collects data on air pollution from all over the United States. You can
see real air pollution data for your hometown at the AIRNow web site :
http://www.epa.gov/airnow/. At this web site, data from across the country is
converted into something called an Air Quality Index.
\
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
3
-------
CHAPTER 1: SCIENCE GUIDE
SECTION 2
Models
Downwind Project Lesson - Models, Models Everywhere
In general, models can be used to describe, interpret or predict aspects of the world
around us. Models may be simple or complex, but they begin with a concept, a
mental construct used to interpret reality through data based on experiences. For
example, one might develop a conceptual model of a hurricane based on
observations about wind and water effects. Often, representations are developed to
express conceptual models. These might be pictorial or diagrammatic. A pictorial
representation of the heliocentric solar system represents a mental concept
concretely represented as in the example below:
Figure 1: Model of the Solar System
eptune
Asteroid Beit
Uranu:
Jupiter1
uto
40 AU
1 All* 150 million km
ORBITS OF THE INNER PLANETS
ORBITS
OF
Mercury, Venus, Earth, Mars
Image with permission of Peter van Keken
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
5
-------
SECTION 2
CHAPTER 1: SCIENCE GUIDE
Models have many advantages:
1. You can do things with a model that are not possible in real life. For
example, you can use a computer model to estimate the concentration of
a pollutant that might result from a chemical spill.
2. You can run such a model as many times as you want.
3. Models can easily be changed and then improved.
4. Models are great tools for solving problems.
Models may be concrete, such as the solar system above, or abstract using symbols
to represent the real world. Mathematics may be used to represent, manipulate
and extend a model to provide predictions about aspects of the physical world.
Computer models are mathematical constructs that allow complex models to be
developed. In this project we will be using a predictive computer model called the
"Industrial Source Complex Model."
In developing a predictive model, it is necessary to select the appropriate
mathematics and statistics to relate the variables into a mathematical format
known as an "algorithm." The development of this algorithm is an essential
element in computer modeling.
WEB LINK
Predictive models use mathematical algorithms. An algorithm is a series of
steps or a formula that can be used to solve a problem. You can find out more
about algorithms at; http://www.webopedia.eom/TERM/A/algorithm.html. If
you include an algorithm in your model to relate your variables to each other,
your model will be even more accurate.
\
6 CENTER FOR INNOVATION IN ENGINEERING AND SCIENCE EDUCATION AT STEVENS INSTITUTE OF TECHNOLOGY
-------
CHAPTER 1: SCIENCE GUIDE
SECTION 2
What if the model isn't correct or if it has mistakes? You can run the model as
many times as you like and then compare it to real world data. For example, you
might discover that there is another important variable that you left out of the
model. You could add the new variable, change the algorithm and run the model
again to test it. This is another reason that models are so useful, because you can
improve upon them. Algorithms are also used in the Industrial Source Complex
Model (ISC).
In general, predictive computer models, like the Industrial Source Complex Model
(ISC), are used to demonstrate events that:
• occur too slowly to observe directly
• occur too quickly or are difficult to observe
• are too costly to replicate in the laboratory
• are too dangerous to replicate in the laboratory
• involve a complex interaction of variables
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
7
-------
CHAPTER 1: SCIENCE GUIDE SECTION 3
Overview of the Industrial
Source Complex Model (ISC)
Downwind Project Lesson: Long Term Concentration Estimates
Downwind Project Lesson: Short Term Concentration Estimates
The Industrial Source Complex Model (ISC) is a computer model used to predict
concentrations of a pollutant at specified locations as it is transported through the
air. Industrial Source Complex means that this model was developed to work with
the emissions from sources such as factories or power plants. In the rest of this
guide you will learn more about the ISC model, and see how models like this can
make a positive difference in our lives.
The primary reason the ISC model was developed was to allow people to estimate
the concentration of a pollutant in ambient air to determine exposure to
pollutants. By ambient air we mean the air outside the source of the pollutant. We
are going to use the ISC model to estimate the concentration of a pollutant outside
a power plant and a new factory that will be built in our community.
The following flow chart describes the variable used by the model, the process and
the output generated. The chart may seem complex, but the various components
will be described in this Science Guide and you can refer back to see the
interrelationships.
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
9
-------
SECTION 3
CHAPTER 1: SCIENCE GUIDE
INPUT-
PROCESS
+ OUTPUT
Four Input Pathways
1. Control Pathway
2. Receptor Pathway
3. Source Pathway
4. Output Pathway
Algorithm - Plume Rise
Model Enhancements
Calculations:
1. Amount plume rises
above stack
2. Transport predicted
using meteorological
conditions
3. Downwind
concentrations
predicted
Concentrations of pollutants at
different distances and directions
from source.
Short Term
Long Term
Time Periods
Annual
1-24 hours
Average
Control Pathway
Receptor Pathway
Source Pathway
Output Pathway
Name of Pollutant
Polar or Cartesian
# of pollutant
Pollution by each
Type of Calculation
Coordinates
sources
source
(concentration)
# of Directions
Name of pollutant
Pollution by all
Dispersion - Rural or
# of Rings
sources
sources
Urban
# of Calculations/Ring
Source Coordinates
Source Contribution
Weather Station
Max. Pollution from
each source
Source Type
Max. Pollution from
all sources
t
Point Source
Area Source
Volume Source
Emission Height
Emission Height
Emission Height
Pollutant Exit Velocity
Width of Source
Initial Vertical Dimension
Emission Rate
Emission Rate
Initial Lateral Dimension
Exit Temperature
Emission Rate
Inner stack diameter
Building Downwash
Information
10 CENTER FOR INNOVATION IN ENGINEERING AND SCIENCE EDUCATION AT STEVENS INSTITUTE OF TECHNOLOGY
-------
CHAPTER 1: SCIENCE GUIDE
SECTION 3
A model should have at least three main parts: 1) input/ 2) processing, and 3)
output, and includes variables that are manipulated during the processing.
Let's summarize what we know about ISC. ISC is a model that can predict the
concentration of a pollutant downwind from a source or groups of pollutant
sources. For example, using a model we can predict the concentration of a
pollutant will be at a given distance and direction from a smokestack, and how the
pollutants are transported or dispersed through the atmosphere. In order to
understand the ISC model we need to understand the different factors that can
affect the transport and dispersion of a pollutant. First, we need to know the
physical characteristics of the stack or source that is emitting from the
pollutant. Next, we need to know the physical and chemical characteristics of our
pollutant. What kind of chemical is it? Is the pollutant reactive, i.e., will it break
down over time or react with other chemicals? If it is reactive, it cannot be used
with the ISC. We will need to know weather conditions and the features of the
terrain (e.g., mountains, valleys, nearness to the water), and human-made
obstacles such as buildings. You will learn about each of these factors in sections
of this guide and also in the related web activities.
An important limitation of ISC is that it can only work for distances up to 50 km. If
the new power plant was 75 km away, we could not use the ISC model. It is
important to note that there are two different types of ISC models. The short-term
model, (ISCST3), can calculate the concentration or deposition of a pollutant for
time periods of 1, 2, 3, 4, 6, 8, 12, and 24 hours. The long-term model, (ISCLT3),
uses statistical summaries of meteorological data to provide estimates of annual
average concentrations of a pollutant in the atmosphere. The ISCLT3 cannot be
used for short periods of time.
The ISC model uses a special algorithm called PRIME. Remember, we said that an
algorithm is just a way of solving a problem. PRIME stands for Plume Rise Model
Enhancements. PRIME goes through a series of steps to calculate how a plume of
smoke will rise through the air and be transported. You will find out more about
plumes in later sections of this guide. The ISC model has to make two important
calculations in order to calculate the downwind concentration of a pollutant at a
given time and location. First, the height that the plume rises above the stack (the
effective stack height) needs to be calculated. Second, the transport (dispersion) of
the pollutant from the source to the receptor (the area that we are interested in) is
predicted using information about the meteorological conditions.
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
11
-------
SECTION 3
CHAPTER 1: SCIENCE GUIDE
If we wish to use the ISC model, we would first have to get measurements or
estimates of measurements of the pollutant emissions from the power plant. These
would be some of our input variables. Once the model received the values of the
variables, they are processed using algorithms such as PRIME. The PRIME
algorithm uses something called a Gaussian equation to calculate the concentration
or deposition of the pollutant at a certain distance from the source. In case you
were wondering, the term "Gaussian" means that the model uses a Bell Curve.
Figure 2: Image of a Bell Curve (also referred to as a Normal or Gaussian Curve)
Many calculations and manipulation of the data take place when the ISC model
computer program runs. Some variables might be changed while others might stay
the same. New variables might even be created. In the next sections, we are going
to really dig into the ISC model by looking at the important factors that the ISC
model uses to make its estimates of pollutant concentration.
Learn more about the ISC model by exploring the Introduction to the
ISC Model web activity located at:
http://www.ciese.org/curriculum/downwind/airmodel/activities/igems_info/ige
ms_.introl.html
12 CENTER FOR INNOVATION IN ENGINEERING AND SCIENCE EDUCATION AT STEVENS INSTITUTE OF TECHNOLOGY
-2
-1
2
WEB LINK
-------
CHAPTER 1: SCIENCE GUIDE
SECTION 4
Pollution Sources
Pollutants are produced in many ways. For example, normally when fuels are
burned, carbon dioxide and water are produced. However, when there is not
enough oxygen present, carbon monoxide, a colorless, odorless gas is
produced. Many other chemicals might be in the smoke produced by burning of
fuels. Other common sources of air pollution are cars, buses, trucks, factories, and
power plants. These sources, while very significant contributors to air pollution are
not addressed in this module because the model was not designed to estimate their
contribution.
WEB LINK
Find oul more about sources of pollutants on the EPA Air Toxics website at:
hltp://wvi,W.epa.gov/ttn/atw/poHsour.html. The EPA is required to regulate 188
hazardous air pollutants, also called HAPS. You can see the original list of
HAPS at: http://www.epa.gov/ttn/atw/origl 89.html
Many of the variables input into the ISC model are related to the source of the
pollutant. The ISC model can work with three different types of sources. The first
type of source is called a point source. This is probably the most obvious one. An
example is a smokestack or isolated vent in a factory or power plant. The second
type of source is an area source. An example of an area source is the release of
ammonia from a wastewater treatment lagoon. The third type of source that the
ISC model can use is a volume source. An example of a volume source is the
release of volatile organic compounds (VOC) from the roof vents of an automobile
paint shop building.
All of the variables related to the source of the pollutant are called source
variables. Let's consider the source variables that the ISC model needs for a point
source like a smokestack. These will also be the variables that will be needed to
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
13
-------
SECTION 4
CHAPTER 1: SCIENCE GUIDE
input into the model. First, there is the location of the source. This is input to the
computer using an X and a Y coordinate, just like those used when plotting points
on a graph. With a point source, a grid of 50 meters by 50 meters is used to plot the
X and Y coordinates of the point source. It is necessary to enter the coordinates X =
0.0 and Y = 0.0 for the Power Plant smokestack since it is a point source. For the
number of source variables, enter 1. Here the source is identified, so if the
pollutant being investigated is carbon monoxide, for example, then enter CO for
the name of the source.
For source type, choose "Point Source." When a fuel is burned, smoke is produced
or emitted. In order to find out how high the emission will rise, it is necessary to
know something about the molecules being emitted. It is necessary to know the
"Pollutant Exit Temperature" to find out how high it will rise. The hotter the
emission, the higher it will rise as a result of increased buoyancy. Temperatures
need to be specified in degrees Kelvin. Celsius degrees can be converted to degrees
Kelvin by adding 273 to the number of degrees Celsius. See the example below.
WEB LINK
Water boils at 100 C. This is approximately 373 K. An online conversion
tool can be found at: http://www.onlineconversion.com/temperature.htm
It is also necessary to know the Pollutant Exit Velocity. This is the speed that the
molecules are ejected from the smokestack. The greater the velocity, and resulting
momentum, the higher the plume of emissions will rise. Another important
variable is the Emission rate, measured in grams per second. Finally, it is necessary
to look at the stack itself. The height of the emission (this could be the height of the
stack) in meters is required, along with the inner stack diameter. As noted earlier,
the amount that the plume rises above the stack is called the effective stack height
and this is influenced by the buoyancy and momentum of the molecules emitted
from the stack.
14 CENTER FOR INNOVATION IN ENGINEERING AND SCIENCE EDUCATION AT STEVENS INSTITUTE OF TECHNOLOGY
-------
CHAPTER 1: SCIENCE GUIDE SECTION 4
Table 2: Summary of Source Variables for a Point Source
Name of Source Variable
Class Source Input
Number of pollutant sources
1
Name of pollutant source
New Power Plant
Pollutant of interest
Carbon Monoxide
Source coordinates (location)
() 11
Source type
Point
Height ot' emission in meters
30 m
Pollutant exit temperature in degrees K
400 K
Pollutant exit velocity in meters per second
2.3 m/s
Inner stack diameter in meters
1.5 m
Emission rate in grams per second
2.6 g/s
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
15
-------
CHAPTER 1: SCIENCE GUIDE
SECTION 5
Transport of Pollutants
In the previous section we looked at the source of a pollutant Now we want to find
out how that pollutant is transported through the air. Without this information, the
ISC model couldn't give us accurate results and the model wouldn't be any better
than an educated guess.
Imagine the path traveled by a molecule of a pollutant. When ejected from a
smokestack, the molecule is very hot. How does the molecule travel from the top
of the smokestack from which it was emitted to a given area? First, the pollutant
molecule will rise. Once it has reached its highest point or the vertical component
of its movement, the wind will push it horizontally, that is the X component of its
movement. Now it will begin a journey through all the factors mentioned
previously. It will be part of a plume that contains many other pollutant
molecules. Depending on the stability of the air, it may move faster, slower, or up,
or down. It is difficult to predict its exact path.
In this model we use mathematics and statistics (the Gaussian Curve), to figure out
probabilities of where molecules will be at given times and distances from the
source. It may get caught up in a temperature inversion if it happens to be
transported into a foggy valley, or it might go over a building and get caught in
some downwash. The possibilities are numerous. That's one reason why the
mathematics of the ISC model, the PRIME algorithm and the Gaussian Curve
model are so complicated, in order to take all this complexity into account. Now,
let's look more closely at these different factors that influence the transport of
pollutants.
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
17
-------
CHAPTER 1: SCIENCE GUIDE
SECTION 6
Plumes
A plume represents a mixture of gases, and some molecules of pollutant, which are
emitted from the smokestack of a plant. The shape of a plume is elongated,
thickens in the middle and tapers at each end. It is important to realize that a
plume is not flat and two-dimensional like a piece of paper. Instead, it is three
dimensional. It has length, width and depth.
So, we have a three-dimensional plume containing molecules of pollutant being
shot out of a smokestack and transported through the air. How can you predict
where it will go? Remember the PRIME algorithm and the Gaussian Plume
Model? With good data and the ISC model, these algorithms and formulae can
make an approximate prediction of the concentration of the pollutant at a given
distance. Notice that we said "good data." By this, we mean the data have to not
only have been accurate but the data must conform to the limitations of the
model. Yes, that's right; the ISC model is not perfect. You will learn more about its
limitations later. For now, an example of a limitation is that it won't work for
distances greater than 50 km. If you tried to predict the concentration of a pollutant
60 km away from the source, it would not be accurate. So, our plume is being
transported through the air, and it has a distinctive shape. Does that shape remind
you of anything? Take a look at the bell-shaped or normal curve shown below.
2
1
-2
I*
You might have had teachers who graded on a "curve." Unfortunately, the Bell
Curve only holds true when you have a random sample and very large numbers.
However, in our case, we are going to use the Bell (Gaussian) curve for a different
and more useful purpose.
Imagine a single Gaussian Curve that you can rotate around the X-axis. Think
about rotating it all the way around, 360 degrees. What would the shape look like
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
19
-------
SECTION 4
CHAPTER 1: SCIENCE GUIDE
that is traced out by rotating the Gaussian Curve? A plume shape, at least
approximately. If we look at the Gaussian Curve again, notice that we can think of
it as being made of many points and each point has an X and a Y coordinate. Some
points are farther from the X-axis, others are closer, and the same holds true with
the Y-axis. With the Gaussian plume model there is even a third axis, the Z-axis.
By using the Gaussian Curve in our model we can approximate the positions of a
random selection of molecules in our plume. Once we have this, we can calculate
how the whole plume will behave as it is transported through the air and
encounters winds, buildings, and so on. Gaussian plumes are a fascinating subject,
and have many applications in other areas, besides air pollution. Studying them is
also a great way to learn more about mathematics.
20 CENTER FOR INNOVATION IN ENGINEERING AND SCIENCE EDUCATION AT STEVENS INSTITUTE OF TECHNOLOGY
-------
CHAPTER 1: SCIENCE GUIDE
SECTION 7
Meteorology
Downwind Project Lesson - Weather Wisdom
Meteorology is the scientific study of weather, which includes the atmosphere, and
the events that occur within it. Examples of meteorological events are wind,
tornadoes, rain, snow, clouds and many others. Accurate measurement is very
important in meteorological studies. Some of the important meteorological data
that are needed to use the ISC model are as follows:
Table 3: Weather data needed by the ISC Model
Weather Data
Instmment
Units
Temperature
Thermometer
K,0 C,0 F
Relative humidity Wet and dry bulb thermometers
% Water
Air pressure
Barometer
mm of Hg (mercury)
Wind speed
Anemometer
Wind direction
Wind vane
Points of compass, degrees
In the center column you can see the weather instruments and units that are
commonly used for the different types of weather data. Meteorological conditions
obviously affect the transport of pollutants and the movement of a plume. Earlier
we mentioned how fog, combined with excessive pollution and geographical
conditions, resulted in a temperature inversion in Donora, Pennsylvania in
1948. This resulted in a layer of poisonous smog being trapped in a valley with
lethal results. Before we can enter data into the ISC model we will need to consider
the meteorological factors that might affect the plume from the factory's
smokestack.
Many different meteorological factors are important in the transport of pollutants.
One important factor is caused by changes that occur from day to night (diurnal
differences). During the day, heat from the sun causes the mixing of air, while at
night, when cooling occurs, the air subsides (settles down) and becomes stratified
(arranged in layers). You can see how this happens in figures 3 and 4.
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
21
-------
SECTION 7
CHAPTER 1: SCIENCE GUIDE
Figure 3: Stable environment - layers of air do not mix - Nighttime
Layer of warm air
Layer of cold air
Figure 4: Unstable environment - Convection currents mix layers of air (summer)
Layer of cold air
Layer of warm (hot) air
Now that we know that air can form layers, another important concept that we
need to understand is the mixing height of the air. The lowest layer of the
atmosphere is the troposphere. The troposphere is made up of two parts: the
planetary boundary layer (PBL) and the free atmosphere. The planetary boundary
layer extends from the surface to between 100 meters and 3,000 meters, depending
on meteorological conditions. Scientists have developed a special mixing height
program that uses surface and upper air data to calculate the mixing height at any
given time.
There are special computer programs that prepare the meteorological data for
input into the ISC model and then use the mixing height. The PBL is higher
during the daytime than at night. The PBL also changes with the seasons. On
average, the PBL is lower in the winter and higher in the summer. To summarize,
the mixing height of the PBL is another important factor that the ISC model uses
in its calculations.
Synoptic differences are differences in meteorological conditions that occur over a
wide area. When a weather forecaster on the evening news discusses cold fronts or
warm fronts, he or she is describing a synoptic change in the weather. Another
example of synoptic change is frontal passages that are characterized by abrupt
changes in meteorological conditions such as wind or humidity.
Seasonal changes are also very important. During the summer, there is strong
vertical mixing of layers of air while in winter, cold and warm fronts play
important roles. In spring and fall, it is also possible to get very hot days like in the
summer, and very cold days like in the winter.
22 CENTER FOR INNOVATION IN ENGINEERING AND SCIENCE EDUCATION AT STEVENS INSTITUTE OF TECHNOLOGY
-------
CHAPTER 1: SCIENCE GUIDE
SECTION 7
In addition to widespread synoptic effects, there are local effects that affect the
transport of pollutants through the air. A sea breeze is produced during the day
when the land heats up faster than the nearby ocean water or large lake. As the air
over the land heats, it begins to rise. The cooler air over the water begins to flow in
over the land, creating a sea breeze. In the evening, the opposite can happen,
resulting in a land breeze. Once the sun sets, the land cools and loses heat more
rapidly than the water. The warmer air over the ocean begins to rise and the cooler
air over the land begins to flow over the ocean, creating a land breeze.
One decision that we will need to make is whether to use the short-term (ISCST3)
model, or the long-term (ISCLT3) model. The two models use different weather
data and cover different time periods so it is an important decision. The short-term
ISCST3 model uses data from the National Weather Service or from other weather
stations near a specific site. This data is collected and hourly averages are
calculated using a computer program called PCRAMMET. The long-term ISCLT3
model uses monthly, seasonal, or annual averages of meteorological data that are
processed by a computer program called STAR. We will need to use the long-term
model since the smokestack is probably not going to give off a huge amount of
pollutant over a short period of time, but instead it is more likely that there will be
a steadier emission over a long period of time.
Before the ISCLT3 model uses the meteorological data, they have to be processed
by a computer program called STAR. As you can see, scientists use lots of
acronyms, but once you find out what they mean, it's easier to remember them. As
you can imagine, over the course of one or two years, a huge amount of data could
be collected. One of the things the STAR and PCRAMMET programs do is
summarize the data so that the ISC model can use it. This is done by grouping the
different types of data into classes, such as different classes of wind speed. What
this means is that instead of giving the ISC model all the different wind speeds,
they are grouped into a small number of categories. In the table below you can see
the six different wind categories produced by STAR for use by the ISCLT3 model.
Table 4: STAR Wind Speed Categories
1 to 3 miles per hour
4 to 7 miles per hour
8 to 12 miles per hour
13 to 18 miles per hour
19 to 24 miles per hour
Greater than 24 miles per hour
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
23
-------
SECTION 7
CHAPTER 1: SCIENCE GUIDE
The STAR program goes through all the wind speed data and counts the number
of times the wind is in each category every hour.
Sixteen wind directions are used by STAR as shown in Table 5.
Table 5: STAR Wind Direction Categories
wsw
WNW
In addition to wind speed and wind direction, the STAR program classifies the
meteorological data into six stability categories. Stability refers to how much the
air is mixing at any given time. The stability of the atmosphere is determined by
solar insolation and wind speed. Solar insolation is the amount of solar radiation
received by earth on a horizontal surface over a certain amount of time. The sun
heats the earth, and then the same heat is given off by the earth to heat the
atmosphere above. For example, on a hot sunny day, there is greater solar
insolation and more hot air. The hot air will rise, and cool air will fall, and this will
create convection currents, lots of mixing and a highly unstable condition. At
night, when the sun is not heating the earth, and when there is no wind, there will
not be much mixing and the air will be very stable.
In Table 6 you can see the stability categories that STAR uses to classify the data.
24 CENTER FOR INNOVATION IN ENGINEERING AND SCIENCE EDUCATION AT STEVENS INSTITUTE OF TECHNOLOGY
-------
CHAPTER 1: SCIENCE GUIDE
SECTION 7
Table 6: Stability Classes for the ISCLT3 Model
Label |1 Stability Class
Possible Causes
A
Extremely unstable
Sunny days
B 11 Unstable
C
Slightly unstable
D J j Neutral
Cloudy days
E
Stable
Nights with no or low winds
V
Very stable
WEB LINKS
Read more about meteorology here: Weather and Climate Basics from the
National Center for Atmospheric Research at:
http://www.ncar.iicar.edu/eo/basics/index.html.
Find more information on National Weather Stations, STAR, and PCRAMMET
at: http://www.epa.gov/scram001/tt24.htm
Learn more about weather and the ISC model by exploring the Weather
Wisdom web activity at:
http://www.kl2science.org/curriculum/downwind/ww.html
\
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
25
-------
CHAPTER 1: SCIENCE CUIDE
SECTION 8
Buildings
Our plume is now approaching a building. A variety of things can happen. It could
run right into the wall and sink to the ground. Another possibility is that the
plume moves over the top of a building, and then eddying can occur. This is called
building downwash.
Eddying is the movement of air in a circle or in a direction different than the main
direction the air is moving. The area next to the building where the air is eddying
is called the cavity and higher concentrations of pollutant can accumulate
here. This is very important to remember because over time, high concentrations of
a pollutant can build up in the cavity. The area where the air is not disturbed by
the building downwash, downwind from the cavity, is called the fat wake
area. The term wake area refers to the cavity plus the far wake.
Engineers have developed something called Good Engineering Practice or GEP,
as a way of determining how high a smokestack should be in order to minimize
the possibility of harmful accumulation of pollutants due to building
downwash. GEP is calculated using the stack height and the height of the building
in the following formula:
GEP stack height = H + 1.5L
Where H = height of the building
L = lesser of the building heights or projected width
There is another thing that we will need to do. We must obtain the height of the
smokestack of the proposed power plant. All of this information is input to the ISC
model in the form of source variables that were discussed previously in Section
Five. The ISC model can use the information on building dimensions for area and
volume sources.
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
27
-------
CHAPTER 1: SCIENCE GUIDE
SECTION 9
Terrain: Urban vs. Rural
Another important factor that affects the transport of pollutants is the terrain. By
terrain, we mean a piece of ground and its characteristics. Characteristics of terrain
could include mountains, rivers, ridges, valleys, and so on. The ISC model needs to
know what the terrain is like in order to do its calculations. Terrain can be
classified as either flat or gently rolling, or complex, (these are places downwind
where the elevation is higher than the stack, i.e. a mountain). Terrain can be
divided into three main parts:
1. Simple terrain is the terrain between the base of the stack and the top of the
stack
2. Complex terrain is the terrain above the stack top
3. Intermediate terrain is the terrain between the stack top and the final plume
rise.
The ISCLT3 model also has a variable for rural or urban areas. Urban areas usually
have a higher density of people who might be affected by a pollutant. Urban areas
also have large buildings, and heat sources that could affect the movement of a
plume. The Pasquill-Gifford curves are used to calculate lateral and vertical plume
spread in the rural option while the Briggs urban dispersion coefficients are used
in the urban option. Don't worry about the specific names for the curves or
coefficients; all you really need to know about this is that scientists have come up
with different ways to calculate the movement of a plume in urban and rural
areas.
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
29
-------
CHAPTER 1: SCIENCE GUIDE
SECTION 10
Receptors, Concentrations and
Exposure
Downwind Project Lesson - Long Term Concentration Estimates
Downwind Project Lesson - Short Term Concentration Estimates
Let's back up and summarize what we know so far. Our pollutant molecules of
carbon monoxide started their journey by being released from a smokestack at a
power plant. The molecules were transported by the air and moved in a
plume. Along the way, the weather, buildings, and terrain, all influenced the path
of the molecules. Now they have finally reached the end of their journey, which
the ISC model calls a receptor.
A receptor is a point of interest such as the air near a house, the area around a
school, or anywhere we are interested in finding out the concentration of a
pollutant. When we are using the ISC model, we can enter information about
the receptor we want to use. Let's take a front porch as the example of our
receptor. One way to visualize the receptor is to think about a big mesh net or
grid. Depending on how accurate you want your results to be and the location
you are interested in, you can change many different receptor variables. Each
place where the lines cross on the grid, a point, can have x, y, and z
coordinates. When you are setting up your receptors in the ISC model you first
have to decide whether you want to use polar or Cartesian
coordinates. Cartesian coordinates are specified using two or three
perpendicular unit vectors. A good example of Cartesian coordinates is when
you plot points on a graph that has x and y axes. Each point has an x and y
coordinate such as (0, 0) or (10, 15). In our receptors we have an additional
dimension, height, that we specify using a third z coordinate. The ISC model
lets you specify the number of X-axis and Y-axis grids, their starting
coordinates, the height of the receptors, and the distance of each grid from the
source.
Polar coordinates, on the other hand, are used to specify an arrangement of
receptors in rings. Polar coordinates specify a point using distance from the origin,
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
31
-------
SECTION 10
CHAPTER 1: SCIENCE GUIDE
and an angle. The ISC model allows you to specify the number of rings, number of
radial directions in each ring (this is just like the spokes on a bicycle wheel), and
the distance from the source to the center of each ring.
Figure 5: Polar vs. Cartesian Comparison
Concentration and Exposure
?<
jii
it
VI
It
ii
A
a
1
r
c
liJ
jjr
dJ
u
u
t"
L*
4
y
__
i
*
¦0
ha
lc-
Hl
o
_
—
_
J
X]
il
1
SS
Si
J
£
Q
l!
iT>
Is
0
d
1!
aj
L
-
_
-
-
-J
—
_
—
-
—
f
1
w
]
—j
1
4
£L
1
i
j
ri
J
tr
u
..J
1 i
I
V
L.
1
p.
h—
r
4
I—-
1
-J
tm
1-
(L
-i.
J
r~
~
EH
J
, i
J
d
J
r
—
c
b
p
—1
""1
i
"i
_j
—i
h*
i
i
X
31
!_
¦J
0
A
3
4i
4i
nc
**!
an
y~
v
ft
i
i
Sr^
V
"Til
r
tr
n
i
J
1
[I
*—1
-J
Zj
H
p
U
I]
i
1
La
tj,
I
p
r
—J
Ij
1
! 1
£
£
55
S
IB
W9
w|
J
mm
» 1
n
1
e
—
jC
£
£
o
h"
La
—i
—j
b
tt)
FT"
n
T
6
w
m
It
MW
s
1™
I"
r
tfl
¦MKl
¦•¦¦III
ii
¦
mmmmmmmmmmmmmmMmmummmmmmum
i±
Point Referenced
by Radius and
Angk
of Directed Line
r-3.5,8 »6D°
(3-5,60°)
180°-
270°
0°
Polar Coordinates in a Plane
With permission from Peter H. Dana, The Geographer's Craft Project
32 CENTER FOR INNOVATION IN ENGINEERING AND SCIENCE EDUCATION AT STEVENS INSTITUTE OF TECHNOLOGY
-------
CHAPTER 1: SCIENCE GUIDE
SECTION 10
WEB LINKS
For more information on coordinate systems visit the Coordinate System Overview
at: http://www.colorado.edu/geography/gcraft/notes/coordsys/coordsys_f.html
Concentration and Exposure
After running the ISC model, we should have a good estimate of the ground-level
concentration of the pollutant. The ISC model calculates the concentration of a
chemical at the receptors that we choose using the model.
What do we mean by concentration?
In order to understand concentration more fully, we need to look at some of the
units that scientists use. A common unit for expressing concentration is ppm or
parts per million. Obviously one part per million is a very tiny amount. One way
to understand what we mean by ppm is by thinking about a simple activity where
we make a solution that contains 1 ppm of red food coloring. Imagine that we have
some red food coloring, water, an eyedropper, a stirring rod, and three beakers
labeled Beakers One, Two and Three. Let's make our 1 ppm solution!
Step 1: Add one drop of red food coloring to 99 drops of water in Beaker One and
stir. The concentration of the solution is now 1 part food coloring per
hundred. This can also be expressed as 1 per cent (1%) or .01 food coloring. You
should still be able to see the red color of this solution.
Step 2: Add one drop of the 1 part per 100 food coloring solution from Beaker One
to 99 new drops of water in Beaker Two and stir. You have diluted the solution
and your solution is now 1 part food coloring per ten thousand. This can also be
expressed as .01% or .0001 food coloring. You may be able to see a faint color but
probably it will not be visible.
Step 3: Add one drop of the 1 part per ten thousand food coloring solution from
Beaker Two to 99 new drops of water in Beaker Three and stir. You have diluted
the solution again and your solution is now 1 part food coloring per million
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
33
-------
SECTION 10
CHAPTER 1: SCIENCE GUIDE
(ppm). This can also be expressed as .0001% or .000001 food coloring. You will
definitely not be able to see any of the red color at this concentration.
We know that ppm is one important unit of concentration. If you do some research
on the concentration of pollutants you may come across other units. The ISC
models provide concentration values in micrograms per cubic meters (pg/m3). It is
very easy to convert parts per million to other units as follows:
In order to convert ppm of CO to micrograms per cubic meters (pg/m3) of air, a
series of calculations can be done using the Ideal Gas Law. If you interested in how
this is done, you can check a chemistry textbook for details. We are going to use a
simple conversion factor (that works for CO that is at 25°C and 760 mm Hg) that
has been provided for us.
To convert ppm CO to micrograms per cubic meters (pg/m3):
Multiply ppm of carbon monoxide times 1.15 = micrograms per cubic meter
(pg/m3) Note: 1.15 is our conversion factor for CO at standard temperature and
pressure. If we wanted to convert ppm for a different pollutant, say SO2, we
would need to use a different conversion factor.
WEB LINKS
To find conversion factors for other pollutants visit the following link:
http://www.epa.nsw.gov.au/air/amgmaap/amgmaap-ll.htm
Find out more about CO at the following EPA web sites:
• http://www.epa.gov/airtrends/carbon.htm I
• http://www.epa.gov/air/urbanair/co/index.html
Now we could look at the output of the model, and find the concentrations of CO
that ISC predicts will occur in a given location.
34 CENTER FOR INNOVATION IN ENGINEERING AND SCIENCE EDUCATION AT STEVENS INSTITUTE OF TECHNOLOGY
-------
CHAPTER 1: SCIENCE GUIDE
SECTION 10
Exposure
So far we have just discussed the concentration of CO in air. The next step in the
process is estimating the exposure (exposure assessment) that people will get as a
result of the estimated concentration. EPA defines exposure as the chemical
concentration at the boundary or the body (U.S. EPA, 1992). If you stop and think
about it, there are many factors that could affect the amount of exposure someone
might receive from a pollutant in the air. Exposure assessment involves the
following:
1. Identifying the ways that chemicals may reach individuals.
2. Estimating how much of a chemical an individual is likely to be
exposed.
3. Estimating the number of individuals who are likely to be exposed.
How do pollutants reach people?
Chemicals can be inhaled, absorbed through the skin, enter through drinking
water, or even by the ingestion (eating) of contaminated soil. In the case of CO, the
main route that the pollutant will reach individuals will be through inhalation.
The ISC model estimates how much of the chemical a person is likely to be
exposed to by considering a variety of factors. There are many factors that could
affect exposure but we will only focus on the ones that could affect the amount of
exposure due to inhalation. The factors listed below can be used to calculate the
average daily dose of a pollutant that a person will be exposed to:
1. Concentration of the contaminant in inhaled air (fig/m3)
2. Body weight (kg)
3. Inhalation rate (m3 / day)
4. Type of physical activity; resulting volume of air inhaled with each
breath
5. Exposure duration (days)
6. Averaging time (days) for non-carcinogenic effects or (lifetime, 70 years)
for carcinogenic or chronic effects
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
35
-------
CHAPTER 1: SCIENCE GUIDE
SECTION 11
Making Sense of ISC Output
• ,ys sj
s a
_..f. *-•
11
81 •
6.2
After running the ISCLT3 model with the data on the proposed power plant, we
will get a great deal of useful information. Probably the most important things will
be the following estimates of concentration of the pollutant:
• Annual average concentration of pollutant
• Daily maximum concentration of pollutant
• Annual maximum concentration of pollutant
A map showing the concentration of the pollutant in the area is shown below as an
example.
Hydrogen ion concentration as pH from measurements
made at the field laboratories, 2003
12
®-> s.i
8.3
8.3
St
6 6
(.*
S.I
1
J.I J
Ml
I
> { £ ! $
< t
M
JL JS—\
*.} r'
s. j* u ,i» *:* *2?
4.7
>.»'
67 • 4.® j*d 44 ~iiil '•"
A1" M
F » «' " 4.8 4 , ,
¦ 8.1, s.j 4.7 4M , • 4.4 V.* W
81
11
1,1
'f t.»
S.J
S3
8.3
&,#
4.1
• 4.3
~
8.8
(.3
M
87
S»
4> 41 , •' 44 44 .44
- fW 4fi
• •
¦" ,
* ¦ • 4
If
1.2
441
SO
17
s.i
*! '
.41 8 1
4.B
11
Sites not pictured:
AK01 5.2
AK03 5.2
HI99 4.7
PR20 4.8
VI01 4.9
National Atmospheric Deposition Program/National Trends Network
http://nadp, sws.uiuc.edu
% " '! £">> ¦%
1 • 41 4.7
• 4.5 • *4 • /
. ht- — /¦— ¦ - y 4 C
tVa V»
VI 4.1
\ t "i*
) V: 'u 4-7
* 4.7
4'V
" V1
• at;
-4, V
\*1
Field pH
m
£ 5.3
m
6.2-5.3
5.1 - 5.2
5.0 - 5.1
4.9 - 5.0
4.8-4.9
4.7-4.8
4.6-4.7
mm
4.5-4.6
4.4-4.5
4.3-4.4
m
<4.3
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
37
-------
SECTION 10
CHAPTER 1: SCIENCE GUIDE
The map shows the calculated concentrations at the receptor locations, and also
lines called isopleths. An isopleth is a continuous line where the concentration of a
pollutant is constant. It is possible to examine the map and follow the isopleths to
determine the concentration of a pollutant in different areas of a community.
Limitations of the model
The ISC model is the product of many scientists working over the years. In fact,
when you think about it, it is absolutely amazing that it is possible to predict
concentrations of a pollutant at such far distances with the huge number of
variables involved. However, the ISC model isn't perfect.
There are certain assumptions that have to be met in order to use the ISC model:
There have to be steady-state conditions. This means that there should be a
constant emission rate, and constant wind speed and direction. The mass of the
pollutant is also conserved (it does not change as it is transported by the air). This
also means that the pollutant does not settle on the ground, there is no chemical
transformation of the pollutant as it moves through the air, and the pollutant does
not radioactively decay. There are also certain boundary conditions. The earth is
assumed to perfectly reflect any plumes and there is also no upper boundary.
38 CENTER FOR INNOVATION IN ENGINEERING AND SCIENCE EDUCATION AT STEVENS INSTITUTE OF TECHNOLOGY
-------
CHAPTER 1: SCIENCE GUIDE
SECTION 12
ISC and the Community
Now that we have data, what can we do next? Our analysis can ensure that we are
better informed about air quality, and this will help the community to make more
informed decisions. But we must be careful not to leap to conclusions. These
models provide information on the concentration of pollutants at given
points. People often make a broad leap from this information to infer health
effects. It is improper to do this. Concentrations represent an important first step
towards eventually assessing possible health effects but there are several necessary
steps that must still be considered including the establishment of short term and
long term exposure limits through scientific analysis and the development of
appropriate risk parameters for a
given population.
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
39
-------
Web Links
Smithsonian Magazine - A Darkness in Donora
http://www.smithsonianmag.si.edu/smithsonian/issues99/nov99/phenom_nov99.html
National Center for Atmospheric Research
http://www.ncar.ucar.edu/eo/basics/index.html
Unisys Weather
http://weather.unisys.com/
The Farmer's Almanac
http://www.farmersalmanac.com/weather/weather.html
National Weather Service Tropical Predication Center
http://www.nhc.noaa.gov/aboutmodels.shtml
Track a Storm
http://www.tropical-storms.com/
Cli-Mate
http://users.nac.net/splat/climate/index.htm
Shodor Educational Foundation
http://www.shodor.org/
IGEMS web site
http://www.ciese.org/curriculum/downwind/template/simulation/signin.html
EnviroMapper
http://www.epa.gov/enviro/wme/index.html
EPA Air Toxins Web Site
http://www.epa.gov/ttn/atw/pollsour.html
Temperature Conversion Tool
http://www.chemie.fu-berlin.de/chemistry/general/uni ts_en.html#temp
41
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
-------
CHAPTER 1: SCIENCE GUIDE
Coordinates Systems Overview
http://www.colorado.edu/geography/gcraft/notes/coordsys/coordsys_f.htm]
Coordinate Systems Overview 2
http://hyperphysics.phy-astr.gsu.edu/hbase/coord.html
Evaluating Exposures to Toxic Air Pollutants: A Citizen's Guide
http://www.epa.gov/ttn/atw/3_90_023.html
Asthma and Outdoor Air Quality Consortium
http://www.aqmd.gov/prdas/asthmaconsortmm.html
EPA Glossary of Key Terms
http://www.epa.gov/ttn/atw/nata/glossl.html
Asthma and Outdoor Air Quality Consortium
http://www.aqmd.gov/prdas/asthmaconsortium.html
Using Data in GIS
http://www.gis.com/data/usingdata/map_projections.html
Exposure Factors Handbook
http://www.epa.gov/ncea/pdfs/efh/front.pdf
EPA Glossary of Key Terms
http://www.epa.gov/ttn/atw/nata/glossl.html
h ttp://www. pbs. org/no w/science/smog. h tml
http://www.co.clark.nv.us/Air_Quality/FAQ/faq_monitoring.html#monitoring3
Measuring relative humidity
http://www.uswcl.ars.ag.gov/exper/relhum.htm
-------
References
Kleinman, M. (2000). The health effects of air pollution on children. Retrieved from
the web at http://www.aqmd.gov/forstudents/Kleinman_article.pdf
Samet, J., DeMarinia, and Mailing, H. (2004). Science. Vol. 304, Issue 5673, 971-972,
14 May 2004. "Do Airborne Particles Induce Heritable Mutations?"
43
-------
CHAPTER 2: TEACHER'S GUIDE
Teacher's Guide:
<1
The Donora Disaster
Note to Teacher: This guide is designed for use in classrooms with no Internet
access. If Internet access is available, these lessons would be more effectively taught
using the Dowmoind on-line project located at:
http://www.stevens.edu/ciese/curriculum/downwind/index.html
Lesson Goal: To provide students with an introduction to the topic of air quality.
The students will see how critically important air quality is, and will explore the
different factors involved in the Donora Disaster. After the students have explored
some air quality and weather data from Donora, they will use historical data to
draw conclusions regarding how to prevent this type of environmental disaster.
This lesson is based on an actual historical incident that occurred in Donora,
Pennsylvania in 1948. As a result, the nation began to take action to improve air
quality. Actual data is available in a Public Health Service preliminary report. (See
Appendix A.)
Scientific background for the teacher
See: Science Guide; Air Pollution; Pollution Sources; Transport of Pollutants; and
Meteorology,
Objectives:
Students will be able to:
• collect and analyze historical, weather and air quality data
• list the important factors involved in the Donora disaster
• analyze historical data from the Donora Disaster and synthesize ideas for
ways that the disaster might have been prevented
Materials
• The Donora Disaster Student Worksheet
• maps of Donora, Pennsylvania
• Smithsonian Magazine article: "A Darkness in Donora," November 1999
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
45
-------
CHAPTER 2: TEACHER'S GUIDE
• Public Health Bulletin No. 306 entitled "Air Pollution in Donora, PA.
Epidemiology of the Unusual Smog Episode of October 1948." A copy of
this can be obtained through your local public library or nearby university
libraries. (See Appendix A.)
• When Smoke Ran Like Water. Dr. Devra Davis, Basic Books, 2002.
• Maps, Student Worksheet and a copy of "A Darkness in Donora" are
available in the "Donora Disaster" chapter.
Assessment
Have the students share their group reports:
Prepare a report for the team addressing the original questions:
• Where is Donora, PA located?
• What happened there and why is it significant to the project?
• What factors do you think might have caused the disaster?
Implementation Tips
This lesson would be a good introduction to the topic of air quality, and air
pollution.
A good approach to this lesson is to not give away too much information on the
disaster at the beginning of the lesson. Set the stage by reading some interesting
excerpts from Dr. Devra Davis' book, "When Smoke Ran Like Water" to hook the
students and get them interested. Ask the students to be the investigators, and
encourage them to come up with ideas on how events like this could be prevented
in the future.
46 CENTER FOR INNOVATION IN ENGINEERING AND SCIENCE EDUCATION AT STEVENS INSTITUTE OF TECHNOLOGY
-------
VSAA
CHAPTER 2: TEACHER'S GUIDE
Teacher's Guide:
Weather Wisdom Activity
Note to Teacher: This guide is designed for use in classrooms with no Internet
access. If Internet access is available, these lessons would be more effectively taught
using the Doxvnwind on-line project located at:
http://www.stevens.edu/ciese/curriculum/downwind/index.html
Lesson Goal: To provide the students with an introduction to the topics of climate
and weather and their effects on the dispersion of pollutants.
Scientific background for the teacher
See Science Guide - Meteorology; Transport of Pollutants
Objectives
Students will be able to:
• collect and analyze historical and real time weather data from Donora, PA
• list the important meteorological factors that affect the dispersion of
chemicals in air
• explain what causes a temperature inversion and how it affects the
dispersion of chemicals
Materials
• Weather Wisdom student worksheets
• 1949 Public Health Bulletin Diagrams
• Optional: digital weather instruments, anemometer, wind vane, weather
station
Assessment
1. Hold a discussion with the students on whether the Donora Disaster could
occur again today. Have students base their arguments on historical and
real-time weather data.
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
47
-------
CHAPTER 2: TEACHER'S GUIDE
2. Have teams of students prepare a report to answer: 1) How did weather
affect the Donora disaster? 2) How does weather affect the transport of
pollutants?
Implementation Tips
To help determine the level of your students' meteorological knowledge, discuss
how weather might affect the movement of pollutants. Encourage students to take
advantage of the many excellent sources of real-time and historical weather data
on the web. Have students collect some weather data of their own using simple
instruments such as an anemometer, wind vane, and thermometer.
Useful Internet Resource: Air Quality Meteorology Course (From the Shodor
Foundation) http://www.shodor.org/iTietweb/
48 CENTER FOR INNOVATION IN ENGINEERING AND SCIENCE EDUCATION AT STEVENS INSTITUTE OF TECHNOLOGY
-------
CHAPTER 2: TEACHER'S GUIDE
^jntf Teacher's Guide: Models,
Models, Everywhere Activity
— : —¦— ———— —— :—: : :———— —
Note to Teacher: This guide is designed for use in classrooms with no Internet
access. If Internet access is available, these lessons would be more effectively taught
using the Downwind on-line project located at:
http://www.stevens.edu/ciese/curriculum/downwind/index.html
Lesson Goal: To provide the students with an introduction to the concept of
models. The students will see examples of a variety of types of models and this
will prepare them to begin to learn more about the ISC models
Scientific background for the teacher
Science Guide - Models; Overview of the Industrial Source Complex Model;
Plumes
Objectives
Students will be able to:
• define what is meant by a model
• explain why models are important, especially in science
Materials
• Models, Models Everywhere student worksheets
• Optional: Examples of models, such as: physical models, diagrams,
computer simulations
Assessment
Discuss team reports.
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
49
-------
CHAPTER 2: TEACHER'S GUIDE
Team Report
Prepare a team report answering the original questions:
• How might models be used to prevent tragedies like the Donora
disaster?
• How might models be used to assist in site selection for a new factory?
Implementation Tips
This is a very abstract topic. It is important to connect the concept of "models" to
familiar topics for students. Point out that many scientific terms have other
meanings in everyday life. It may be useful to show students a variety of different
models, including physical models.
If you have access to computer modeling software, for example Stella, or
simulations, this could be very helpful in assisting students in understanding how
models work.
Useful Websites with Information on Models
National Computational Science in Education
http://www.ncsec.org/sc2001 tm. cfm
Case Study: Modeling Smokestack Plumes (Word doc)
http://www.ncsec.org/cd/gotwals/smokestack.doc
Case Study: Modeling Smokestack Plumes (Excel spreadsheet)
http://www.ncsec.org/cd/gotwals/plumeblank.xls
Overview of Air Quality Modeling Lesson (From the Shodor Foundation)
http://www.ncsec.org/cd/aqm/aqmover.pdf
Air Quality Modeling for Teachers (From the Shodor Foundation)
http://www.ncsec.org/cd/aqm/index.htm
An interdisciplinary air quality educational exercise (From the Shodor Foundation)
http://www.shodor.org/ekma/
50 CENTER FOR INNOVATION IN ENGIN EERING AND SCIENCE EDUCATION AT STEVENS INSTITUTE OF TECHNOLOGY
-------
CHAPTER 2: TEACHER'S GUIDE
Teacher's Guide: Long Term
Concentration Estimates Unit
Note to Teacher: This guide is designed for use in classrooms with no Internet
access. If Internet access is available, these lessons would be more effectively taught
using the Downwind on-line project located at:
http://www.stevens.edu/ciese/curriculum/downwind/index,html
Lesson Goal: To provide the students with an introduction to the ISCLT3 model.
The students will use an example data set in the context of an interesting scenario.
Scientific background for the teacher
See the Science Guide - Overview of the Industrial Source Complex Model, Plumes,
Receptors, Concentration and Exposure
Objectives
Students will be able to:
• define what is meant by a "model"
• explain how data is entered and run by the SCLT3 model
• interpret the output files and carry out a simple analysis of the data
• draw conclusions from the data and make reasonable recommendations
based on the data
Materials
• Long Term Concentration Estimates student worksheets
• selected data
• Donora map
• rulers
• protractors
Assessment
• Analysis of data
• Group conclusions for school location
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
51
-------
Teacher's Guide:
Short Term Concentration
Estimates Unit
Note to Teacher: This guide is designed for use in classrooms with no Internet
access. If Internet access is available, these lessons would be more effectively taught
using the Doronwind on-line project located at:
http://www.stevens.edu/ciese/curriculum/downwind/index.html
Lesson Goal: To provide the students with an introduction to the ISCST3 model.
The students will use an example data set in the context of an interesting scenario.
The lesson illustrates how to input the data and run the model. The students will
analyze the data, and make conclusions and recommendations.
Scientific background for the teacher
See Science Guide: Overview of the Industrial Source Complex Model; Plumes;
Receptors; Concentration; and Exposure
Objectives
Students will be able to:
• define what is meant by a model
• explain how data is entered and run by the ISCST3 model
• interpret the output files and carry out a simple analysis of the data
• draw conclusions and make reasonable recommendations based on the data
Materials
• Short Term Concentration Estimates student worksheets
• selected data
• Donora map
• rulers
• protractors
Assessment
• Team report including an analysis of the data
• Group conclusions
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
53
-------
CHAPTER 2: TEACHER'S GUIDE
Teacher's Guide:
Final Report
Note to Teacher: This guide is designed for use in classrooms with no Internet
access. If Internet access is available, these lessons would be more effectively taught
using the Downwind on-line project located at:
http://www.stevens.edu/ciese/curricuIum/downwind/index.htm1
It is recommended, that in order to bring closure to the project and to best assess
student progress, each team prepare a final report. The time allotment and
presentation mode is at the teacher's discretion. The student instructions suggest
that the team demonstrate their ingenuity for the report.
Suggestions for a final student report include:
• Students design a web site to show what they have learned
• Write a technical report
• Develop a persuasive oral presentation
• Create a written presentation: poster, brochure
• Plan and implement a mock town meeting. (Teams of students
represent special interest groups. Each team will research and present
points of view regarding the construction of the new plants and school.)
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
55
-------
DONORA DISASTER
A look at an ecological disaster - On a late October night, in. 1948, in the small town
of Donora, Pennsylvania, disaster struck. Unusual and persistent weather
conditions trapped a layer of poisonous smog over the entire town. After four
days, 20 people died and hundreds of others were sickened by the fumes.
CHAPTER 3: STUDENT ACTIVITIES
Student Activity:
The Donora Disaster
Donora, Pennsylvania
(with permission from
http://whensmokeranlikewater.com)
IftBMBB
Your Assignment: What Happened in Donora.?
Your team is looking for answers to these specific questions....
• Where is Donora, Pennsylvania located?
• What happened there, why is it significant to the project?
• What factors do you think might have caused the disaster?
The Action Plan: Procedures to follow
Obtain a copy of The Donora Disaster Student Worksheet, maps of Donora, and a
copy of "A Darkness in Donora" from your teacher.
Step 1: Locating Donora
Use the maps of Donora to answer the following questions:
DOWNWIND: LEARNING SCIENCE USING AN EPA <'((NCENTRAHON MODEL
57
-------
CHAPTER 3: STUDENT ACTIVITIES
DONORA DISASTER
1. What is the name of the river close to Donora?
2. How would you classify the terrain around Donora? Is it desert,
mountainous?
3. What is the highest elevation to the east and west of the town?
Step 2: Historic Information about Donora
1. Read A Darkness in Donora from Smithsonian Magazine. List three factors
that contributed to the Donora Disaster
2. Use the historic image of Donora to answer the questions below:
a. Where are the factories located relative to the river and the
mountains?
b. Where is the residential area of Donora located relative to the river
and the mountains?
c. If the wind were to blow from the east, how would that impact the
residential area of Donora?
d. If the wind were to blow from the west, how would that impact the
residential area of Donora?
e. Why do you think the factories are located on the river?
Team Report
Prepare a report for the team addressing the original questions:
Where is Donora, Pennsylvania located?
What happened there, why is it significant to the project?
What factors do you think might have caused the disaster?
58 CENTER FOR INNOVATION IN ENGINEERING AND SCIENCE EDUCATION AT STEVENS INSTITUTE OF TECHNOLOGY
-------
DONORA DISASTER
CHAPTER 3: STUDENT ACTIVITIES
€>00^
Student Worksheet:
The Donora Disaster
Name:
The Action Plan - Procedures to follow
Step 1: Locating Donora
Review the links and answer the following questions.
1. What is the name of the river close to Donora?
2. How would you classify the terrain around Donora? Is it desert,
mountainous, etc?
3. What is the highest elevation to the east and west of the town?
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
59
-------
CHAPTER 3: STUDENT ACTIVITIES DONORA DISASTER
Step 2: Historic Information about Donora
1. List three factors that contributed to the Donora Disaster
a.
b.
c.
2. Use the historic map of Donora to answer the following:
a. Where are the factories located relative to the river and the
mountains?
b. Where are the residential area of Donora located relative to the river
and the mountains?
c. If the wind were to blow from the east, how would that impact the
residential area of Donora?
60 CENTER FOR INNOVATION IN ENGINEERING AND SCIENCE EDUCATION AT STEVENS INSTITUTE OF TECHNOLOGY
-------
DONORA DISASTER
CHAPTER 3: STUDENT ACTIVITIES
d. If the wind were to blow from the west, how would that impact the
residential area of Donora?
e. Why do you think the factories are located on the river?
Report
Prepare a report for the team. Make sure to address the original questions:
1. Where is Donora, PA located?
2. What happened there, why is it significant to the project?
3. What factors do you think might have caused the disaster?
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
61
-------
CHAPTER 3: STUDENT ACTIVITIES
£^>b0«»<"ina
DONORA DISASTER
Donora Maps:
The Donora Disaster
Name:
Donora, Pennsylvania
Crestview
~ Donora
unltvy
62 CENTER FOR INNOVATION IN ENGINEERING AND SCIENCE EDUCATION AT STEVENS INSTITUTE OF TECHNOLOGY
-------
DONORA DISASTER
CHAPTER 3: STUDENT ACTIVITIES
Michigan
¦ Detroit
New York
Ohio
Q Columbus
Lake
Eiie
Cleveland
~
¦ Akron
- Canton
• |
Erie "¦
Pennsylvania
• Pittsburgh
^Donora
Harrisburg Q
West
timore
Virginia S A",M,,0'|S O
Maryland
0
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
63
-------
WEATHER WISDOM
CHAPTER 3: STUDENT ACTIVITIES
Luu
Student Activity:
Weather Wisdom
Weather Wisdom
In this lesson, you will assess the impact of weather on the Donora disaster,
investigate weather effects in general and then assess the impact of weather on the
transport of pollutants.
Your Assignment - How does weather impact the transport of pollutants?
• How did weather affect the Donora disaster?
• How does weather affect the transport of pollutants?
The Action Plan - Procedures to follow
Obtain a copy of the 1949 Public Health Bulletin Diagrams and the Weather
Wisdom Student Worksheet from your teacher.
Step 1: Gather some basic weather information
A) Weather vs. Climate -
Weather is the mix of events that happen each day in our atmosphere including
temperature, rainfall and humidity. Weather is not the same everywhere. Perhaps
it is hot, dry and sunny today where you live, but in other parts of the world it is
cloudy, raining or even snowing. Everyday, weather events are recorded and
predicted by meteorologists worldwide.
Climate in your place on the globe controls the weather where you live. Climate is
the average weather pattern in a place over many years. So, the climate of
Antarctica is quite different than the climate of a tropical island. Hot summer days
are quite typical of climates in many regions of the world, even without the affects
of global warming.
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL 65
Your team is looking for answers to these specific questions...
-------
B) Weather Effects
One very important meteorological factor in the Donora Disaster was the
formation of temperature inversions. Use the diagrams from the 1949 Public
Health Service Bulletin to answer the following questions on the Student
Worksheet:
DIAGRAM 1
C TEsr.HQST'.TlON
va ur«tl_
t.FWfnot tlritcirsreaiW tm «irfv-
~ JTiuiry caIm day-v. A'- t&vui *•( mcAL7?ru'rrt toss.
Diagram 1 represents the average thermal structure across the Monongahela valley on a non-smoky, calm day.
la) What happens to the temperature as the altitude gets higher on a normal day?
lb) Is this what you would expect to happen? Explain why or why not.
DIAGRAM 2
ZZfO
ME."M
1-A LETVtL
EUkWCTW
*'J FfZT
O riu h* r.ui i:u
GO.• Awifi Vi»V vtslk fyvgrfiw) HucwMi draffu.%*.
¦in 4KiUty fer ruhfUi-jit- Mfiito, ttocc? tftJ.'* m
J {nut of tivcrfatw*
Compare Diagram 1 with Diagram 2, also taken from the 1949 Public Health
Service Bulletin.
66 CENTER FOR INNOVATION IN ENGINEERING AND SCIENCE EDUCATION AT STEVENS INSTITUTE OF TECHNOLOGY
-------
WEATHER WISDOM CHAPTER 3: STUDENT ACTIVITIES
lc) What happens to the temperature as the altitude increases?
Id) How might the inverted temperature layers impact the area?
le) Do you think that air will be able to rise up (radiate) as under normal
conditions? Explain.
DIAGRAM 3
® DErntiTiNn ahrow QJrwraH
Q ABWKM5 AWOM lKJt-T
WBCTWS Fur WIN THE »'ND
FtatrsE 09.—v.igM
-------
lh) What type of conditions might help to move pollutants out of the valley?
li) Which direction should the wind blow to clear out the maximum amount of
pollutants from the area?
Step 2 Return to Donora
The town of Donora on different days. Notice the dramatic difference.
2a) Which picture of Donora was taken on a day with normal temperature
conditions? Explain.
2b) Which picture of Donora was taken on a day when a temperature inversion
was occurring? Explain.
According to Devra Davis (2002, p.9), "October 26,1948, brought a massive, still
blanket of cold air over the entire Monongahela Valley. All the gases from
Donora's mills, its furnaces and stoves, were unable to rise above the hilltops and
began to fill the homes and streets of the town with a blinding fog of coal, coke,
and metal fumes."
Source: Davis, Devra. (2002). The Heavy Air of Donora, Pa. The Chronicle of
Higher Education. 10/25/2002
68 CENTER FOR INNOVATION IN ENGINEERING AND SCIENCE EDUCATION AT STEVENS INSTITUTE OF TECHNOLOGY
-------
WEATHER WISDOM
CHAPTER 3: STUDENT ACTIVITIES
Weather played a very important role in the Donora Disaster. In the
Meteorological Investigation of the 1949 Public Health Bulletin report 306, W.H.
Hoeker, Jr. stated that the following general factors were important:
A) Sources of pollution. A variety of pollutants were released from several
smokestacks less than 1000 feet high.
2c) Why do you think this was a problem? Recall the height of the surrounding
mountains before answering the question.
B) Topography - Terrain that trapped air at a low level, e.g. the valley.
C) Humidity - Enough water vapor was present so fog formed.
2d) Think about what occurs during the condensation process. Why would the
presence of water vapor compound the problem?
D) Meteorological features - A temperature inversion led to high pressure and
trapped the pollutants.
2e) Where did the pollutants end up going during the disaster?
E) Season - October in Donora is the time of the year when the conditions are most
common to form an anticyclone, fog, and temperature inversion
Team Report
Prepare a report for the team answering the original questions:
• How did weather affect the Donora disaster?
• How does weather affect the transport of pollutant
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
69
-------
WEATHER WISDOM
CHAPTER 3: STUDENT ACTIVITIES
UdA
Student Worksheet:
Weather Wisdom
The Action Plan
Step 1 Basic Weather Information
DIAGRAM 1
la) What happens to the temperature as the altitude increases on a normal day?
lb) Is this what you would expect to happen? Explain why or why not.
DIAGRAM 2
lc) What happens to the temperature as the altitude increases?
Id) How might the inverted temperature layers impact the area?
DOWNWIND! LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL 71
-------
WEATHER WISDOM
CHAPTER 3: STUDENT ACTIVITIES
le) Do you think that air will be able to rise up (radiate) as under normal
conditions? Explain.
DIAGRAM 3
If) In this diagram, how is the air moving, radiating up? Down? Side-ways?
lg) How might this type of air movement impact pollutants moving out of the
area?
lh) What type of conditions might help to move pollutants out of the valley?
72 CENTER FOR INNOVATION IN ENGINEERING AND SCIENCE EDUCATION AT STEVENS INSTITUTE OF TECHNOLOGY
-------
WEATHER WISDOM
CHAPTER 3: STUDENT ACTIVITIES
li) Which direction should the wind blow to clear out the maximum amount of
pollutants from the area?
Step 2: Return to Donora
2a) Which picture of Donora was taken on a day with normal temperature
conditions? Explain.
2b) Which picture of Donora was taken on a day when a temperature inversion
was occurring? Explain.
2c) Why do you think this was a problem? Recall the height of the surrounding
mountains before answering the question.
2d) Think about what occurs during the condensation process. Why would the
presence of water vapor compound the problem?
2e) Where did the pollutants end up going during the disaster?
Team Report
Prepare a team report addressing the original questions:
• How did weather affect the Donora disaster?
• How does weather affect the transport of pollutants?
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
73
-------
WEATHER WISDOM
CHAPTER 3: STUDENT ACTIVITIES
Public Health Service Bulletin 1949
J-R/O
KON
VA LT.tL
t.FVKSCl
IN >r?"
C TSiiMO S7*>TI9N
•Iitunti; 73. Ai&w ikr.yfi.ul «(ruttirc nsftt* vility «•<»»-
»fja)!ry calm *Uxy* Al- tttcAiTruti to}** ?ois.
/
»'•
>
Diagram 1
J7T.fl
ME.'.N
&£* LETVSL
ar.* uti-v.
el£"v*fw.
f* ir
(K».« Awipt ih ry still* tyumikj*) ihirw.ii tiractus-.
in «MKy/i;r rukuii-.'h uocd item m
Jl'mu of «irenanlV7*i
Diagram 2
•'tco
mCMK
• ISTOCinxn aha&w
0 A4WWKN5 At*Or* lNtt'f
iffBTWS FUI W.Tlfl THE *'ND
1 i-suse 09.—Ax*r*»/* r.ifAt <7if jiw .lv^;r i*vy We (vw*-
llM;
-------
CHAPTER 3: STUDENT ACTIVITIES
MODELS, MODELS, EVERYWHERE
Student Activity:
Models, Models, Everywhere
Models, Models, Everywhere
It is obvious that, with hindsight, the Donora disaster could have been anticipated
and avoided. With the advent of computer usage, it is even easier to predict
performance and future possibilities through computer modeling. For the next
part of your project, you are to investigate the concept of modeling, explore some
representative samples, and then explore the environmental models which might
be useful for your primary task - determining the concentration of pollutants that
might be emitted at particular locations by new plants.
For more information about models, see "Understanding Models in Earth and
Space Science," NSTA press, 2003.
Your Assignment - How might models be used for environmental predictions.
Your team is looking for answers to these specific questions...
How might models have been used to prevent tragedies like the Donora disaster?
How might models be used to assist in site selection for a new factory?
The Action Plan - Procedures to follow
Step 1 - Gather some basic information on modeling.
Models can be used to describe, interpret or predict aspects of the world around
us. Models actually have a lot of advantages:
5.You can do things with a model that are not possible in real life. For
example, you could use a computer model to estimate the concentration
of a pollutant that might result from a chemical spill.
6. You can run such a model as^many times as you want.
7.Models can easily be changed and then improved.
8.They are great tools for solving problems.
Models may be concrete, such as a diagrammatic representation of the solar
system, or abstract using symbols to represent the real world. Mathematics may
be used to represent, manipulate and extend a model to provide predications
about aspects of the physical world. Computer models are mathematical
constructs that allow complex models to be developed.
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL 77
-------
CHAPTER 3: STUDENT ACTIVITIES
MODELS, MODELS, EVERYWHERE
Computers models use mathematical formulas to input data to be used to make
predications or simulate behavior. Weather forecasting and hurricane path
predictions rely heavy on a variety of computer models.
In general, predictive computer models are used to demonstrate events that:
• occur too slowly to observe directly.
• occur too quickly or are difficult to observe.
• are too costly to replicate in the laboratory
• are too dangerous to replicate in the laboratory
• involve a complex interaction of variables.
Step 2 - Investigate Environmental Models
The Gaussian Plume Model
A plume is the region of space containing the gases and particulates released from
a smokestack as fuel is burnt. The Gaussian Plume Model is the most commonly
used model to make the calculations needed to predict the movement of a
pollutant in complex situations. In order to do this, several assumptions need to be
made. It is assumed that certain things will stay the same, i.e., remain in a "steady
state." For example, meteorological factors such as temperature and wind speed
and direction are assumed to remain fairly constant over the time period when the
prediction is being made.
Some limitations of the model
As a result, the Gaussian plume model will only work well over short distances of
up to 50 km from the source of the pollutant to the receptor. The receptor could be
a measuring instrument, but it might well be a neighborhood in the path of the
pollutant flow. The model will also not work well in areas where the terrain is very
complex or in a coastal area where sea and land-breezes can cause dramatic
changes in meteorological conditions.
Fuel is burned and a plume of emissions is produced. This may look like smoke
and could contain one or more pollutants.
Because the plume is hot, it will rise, since hot air is less dense. The plume will rise
to a certain point and this is called the "effective stack height." The effective stack
height depends on three main factors:
1.the exit velocity of the gas from the stack
2.the temperature of the plume
3. the temperature of the surrounding air
78 CENTER FOR INNOVATION IN ENGINEERING AND SCIENCE EDUCATION AT STEVENS INSTITUTE OF TECHNOLOGY
-------
CHAPTER 3: STUDENT ACTIVITIES
MODELS, MODELS, EVERYWHERE
After the plume reaches the effective stack height, the plume starts to disperse in
three different directions.
1) The plume can move downwind. The amount that the plume moves is directly
proportional to the wind speed and in the direction of the prevailing wind.
2) The plume can move in a cross-wind direction. This is determined by the
Gaussian Plume equations.
3) The plume can move in a vertical direction, either up or down. This is also
determined by the Gaussian Plume equations.
Gaussian Plume Model Simulations
Here is a screen shot of a Gaussian Plume Simulation:
[ !lCii>u«iUiTPIumaC«lcu|jtar Microsoft Internri lyplorcr
r: fSm
Pte rat VHm FmrtM TK* h*>
O"*4 ' J Isl liS > ' s~"h
® * QIGL
13 «o i«*» * Wr Q »
**wp|
Gaussian Plume Java Applet
5 Um ester
ropVtaw
Wind
Err:; ">«»
UUck
Stetli Hamate*
/
v>
/
/
10
)
11
AWidt^HfiC CtiliJiliM
J iji
vcoruourpjotrwifj*
pKlIt
3 "If
rumttlll ploirwu*
plotwnw
1
• Mm*
¦S start t» • • 2
rPij.« M -
-------
CHAPTER 3: STUDENT ACTIVITIES
MODELS, MODELS, EVERYWHERE
This applet provides a number of slider bars to that allow you to change
parameters:
1.wind speed
2. stack height
3.stack diameter
Remission rate
5.gas temperature
6. gas velocity
7.atmospheric temperature
8. atmospheric conditions
9.3D coordinates and graphics resolution
To change the values, you simply slide the slider bar. Alternatively, you can type
in a value and hit the Enter/Return key.
Output is provided in several formats: x-y graph, top and side view visualizations,
and text-based output. In the side-view format, the black bar on the left of the
graphics window shows the stack, changing in height as the stack height slider bar
is modified. In the top-view format, the stack is seen as a black dot, half-way up
the y-axis.
The x-y-z contour plot range sliders help to zoom in and out of the plume. The z-
contour plot only modifies the side-view, while the y-contour slider only modifies
the top view. The x-contour modifies both top and side views. The computer
model responds to these changes and shows the modified gaseous plume.
Gaussian Plume Model Interface
The following screen shots show the results of changing specific variables in the
plume model interface.
80 CENTER FOR INNOVATION IN ENGINEERING AND SCIENCE EDUCATION AT STEVENS INSTITUTE OF TECHNOLOGY
-------
CHAPTER 3: STUDENT ACTIVITIES MODELS, MODELS, EVERYWHERE
Figure 1
Top View
Wind Speed 10 m/s
Emission Rate 10 g/s
H Cumtian Plume Calculator Microsoft Interpol F*|iU>it
Mb Edt VtaM PavculM Tad* hMp
O*"" ¦ O Si 3 ft /'»«»-ft"-*- b u
Addmn Jjft Mlp://www.»iiua».««/o:;*i I /UK* jn*rf « A^*
let
wjQtio irks v r**»v.Q •
"^IsaerthWsfe |-|£3- yH' O* | ©•MM*ngw Boc*m»to Qtt/Yehooi • fcjMai » 8tatu(fl
ji i
Ainioenheilc OonrtlBor
RwaiuHcn
xtonlow piolrano»
4JJ":
Yr.flntoufpMrwiOfl
Icofitour piotranjjt
1^-
~ 11.0
«J A«*X p*j*>wt Aertad
Jr. '.-I
Figure 2 below represents an increase in the wind speed.
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
81
-------
CHAPTER 3: STUDENT ACTIVITIES
MODELS, MODELS, EVERYWHERE
Figure 2
Top View
Wind Speed 40 m/s
Emission Rate 10 g/s
•'jJ c;.»tJ»sian Plume CaleuUtor Microsoft Internet fxplarar
E
©« • j a a & y 0 65- 4. b l j ©
-i&j Nttji: / ,'OJWW. shorlof 1 -Y*hoot • QMsJ - • ti trtMtoKtMKk - ft Sport* - # Shopping » Frnnc*
*
j NctfMt AntWrv* gj »
"y> fflhoo! ¦» ^ *
Gaussian Plume Java Applet
if Usui owr
Using dais Applet
Tin* applet provide* a number of slider bar* to change parameters
1 wind speed
2. track height
J. stack dinmeter
4. emission rate
5 gas temperature
6. gas velocity
7. atonosphew temperature
8 atmoepheiic eotdtfioni
9. 3D coordinates and graphic* resolution
To change the value». nmply ibde the slider bar Alternatively, you can type in a value and hit the Etster/Rrtum key
Output is provided in several format* x-y graph, top and side view visualizations, and Mnc-based output. In the tide-
view format, the black bat on the l*ft of the graphic* window show* the a tack, changing in height m the stack height
slider bar is modified. In the top-view format, the stack, is seen as a black dot, half-way up the y-aw.
Ilha x-y-e contour plot range sliders help to room in wd out of the plume. The x-eontour plot only modifies the tide-
r, while the y-contour slider orJy modifies the top view The x-contour modifies both top and tide views
J Top view
V
\
9fl
94
B.4
OB
»•
10
ywijjSpijea
•J. i
dtttkwaw
'i -I t .
8W«kD»rrieter
SjK;
gmisftion r?ai*
,u J
Oii'j Tinniwaiurc
'"ii j
UMVSto!
. ,
Ttwimralure
,<| j
AtmOSPMlH C(J1t2lBor
I NXIjtl.il
Resolution
M
saL
V contour plot Imt
yL,
•ZWptoutp(ptr|i{j9
fir
M.O HO-JC
Hi ah** ttamfm «*t*d
If the red area represents maximum concentration near the pollutant release point,
how does an increase in air speed affect that concentration?
Figure 3 below represents an increase in the emission rate.
82 CENTER FOR INNOVATION IN ENGINEERING AND SCIENCE EDUCATION AT STEVENS INSTITUTE OF TECHNOLOGY
-------
CHAPTER 3: STUDENT ACTIVITIES
MODELS, MODELS, EVERYWHERE
Figure 3
Top View
Wind Speed 10 m/s
Emission Rate 30 g/s
3 Caimlan Plume falrulalor Microsoft Internet (jcplorar
p'ire'ijsn1
Kite Edt Vtow PavctftM
r
^93^
n.«v
0.0
>0
AppW nl.jrr»vi^
Ti'ini'uriihw
> I4C
MHO
^ contour pio* r«ito«>
'"Tri'
V mr
' 'J Start * •• J 1 *S • ¦ J !«•••; / Jr. • •• J ' R ' f •
If the red area represents maximum concentration near the pollutant release point,
how does an increase in emission rate affect that concentration?
Team Report
Prepare a team report answering the original questions:
1.How might models have been used to prevent tragedies like the Donora
disaster?
2.How might models be used to assist in site selection for a new factory?
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
83
-------
CHAPTER 3: STUDENT ACTIVITIES
MODELS, MODELS, EVERYWHERE
Student Worksheet:
Models, Models, Everywhere
Name
The Action Plan - Procedures to follow
Step 2: Investigate Environmental Models
Gaussian Plume Model Simulation
1) How does an increase in air speed affect the concentration of the pollutant near
the release point?
2) How does an increase in emission rate affect the concentration of the pollutant
near the release point?
Team Report
Prepare a team report addressing the questions:
l.How might models have been used to prevent tragedies like the Donora
2.How might models be used to assist in site selection for a new factory?
disaster?
84 CENTER FOR INNOVATION IN ENGINEERING AND SCIENCE EDUCATION AT STEVENS INSTITUTE OF TECHNOLOGY
-------
CHAPTER 3: STUDENT ACTIVITIES
MODELS, MODELS, EVERYWHERE
WEB LINKS
The on-line version of this lesson can be found at:
http://ciese.org/curriculum/downwirid/models.html
Weather Forecast Models:
National Weather Service Tropical Predication Center
http://www.nhc.noaa.gov/aboutmodels.shtml
Track a Storm
http://www.tropical-storms.com/
Cli-Mate
http://users.nac.net/splat/climate/index.htm
Gaussian Plume Java Applet developed by the Shodor Foundation
http://www.shodor.org/os4H/courses/_master/tools/models/gplume/gplume.ht
ml
Downloadable Excel spreadsheet simulation of the Gaussian Plume Model
http://san.hufs.ac.kr/~gwlee/plume.xls
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
85
-------
LONG TERM CONCENTRATION ESTIMATES
CHAPTER 3: STUDENT ACTIVITIES
Uaa
Student Activity:
Long Term Concentration
Estimates
Long Term Concentration Estimates
Using EPA's Internet Geographic Long Term Exposure Model
A new coal-fired power plant is being built in Donora, Pa. Concern has been
expressed about possible pollutants from the factory. Your team wishes to
determine the concentrations of pollutants in various locations resulting from the
construction of the new power plant.
Your Assignment: Assess the possible pollutant concentration from this power
plant.
Your team is looking for answers to these specific questions...
1. What pollutants might be released by the plant?
2. What might be the concentrations of pollutants near the present school, the
hospital and the chief residential area?
3. Which proposed new school sites would have the lowest concentration of
pollutants?
The Action Plan - Procedures to follow
Step 1 - Gather information regarding potential pollutants that may be released
from the proposed coal-fired power plant.
For this study you will concentrate on just one common pollutant released by coal
powered plants - mercury.
Step 2 - Gather specifics on the proposed power plant.
The owners of the plant agreed to provide you with some data. Later you will
input this data to the ISCLT3 model. After you run the model you will be able to
analyze the data and determine the potential pollutant concentration from the
power plant.
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL 87
-------
CHAPTER 3: STUDENT ACTIVITIES
LONG TERM CONCENTRATION ESTIMATES
WEB LINK
Frequently asked questions about Mercury
http://www.epa.gov/mercury/informationl.htm
Factory Data
The power plant will have one smokestack. The height of the smokestack is 30
meters. The exit temperature of the gases from the smokestack is 400°K and the
pollutants will exit with a velocity of 2.3 m/s. The diameter of the stack is 1.5
meters and the emission rate is 2.6 g/s.
Step 3 - Use the information you have gathered in the ISCLT model.
This analysis uses the EPA IGEMS/ISCLT3 model to analyze some sample data.
Notice the "LT" in ISCLT3 stands for "long term." The Long Term model uses
averaged STAR meteorological data.
The main difference between the Short Term and Long Term models is the type
of meteorology data that is used as input.
Remember, the goal of this model is to predict the dispersal of a pollutant through
the air over a long period of time. In order to do this, you will have to give the
model some input.
INPUT to the IGEMS/ISCLT Model
There are FOUR INPUT pages:
The CONTROL pathway
-------
LONG TERM CONCENTRATION ESTIMATES
CHAPTER 3: STUDENT ACTIVITIES
The following simulates how the model would be run:
Entering Control Data
l.Sign in on the IGEMS web site.
1^ i(n Ncl*r«|io
tu t
i +> i _m> lo i*«4 Do«nilo«4 OEMS Library *nrl lnrt«0«Uon Iiutiuflinrx
Welcome lo IGEMS Login
lamaNewUser. sion mo udI
lam already registered.
IGEMS User ID
Password
SH»n|
I forgot my 10 ancVor password. I oood help I
Before you access me system, please see this important Note
I .Jj 'W.iVf • V < • ¦ tfj A.tv* r'r. f« ^ .Art-" ¦ .|TU4»
¦ 1 •»{•(•
2.Moving the mouse over the Environmental Modeling link at the top left of
the page would allow you to click on ISCLT3.
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
89
-------
CHAPTER 3: STUDENT ACTIVITIES
LONG TERM CONCENTRATION ESTIMATES
So Cwrjmunr-at:
: 4 £ 3 a * a 41
£ Bact r;*wv.; R«fc«j Horn* $aarch Nal*c«» Pwi $ aamtn Shop
' s^'Paakiwrk* A Mm** "
$ Inrtmt Met «<)* £$ V/rtM.U ttitnim Q| R«*o Pw*4« ®J Y Mow Paqmi .CJ OoMnio«j SI C
G EM S InK'nvt OebgrewhlcofewOTMi.- mMwII) iWien
Fll> Hrtuwmgm
SlfljlMss
AT1230
sesott.
ISCLT3
ISC5T3
TRIAIR
kA
m I
90 CENTER FOR INNOVATION IN ENGINEERING AND SCIENCE EDUCATION AT STEVENS INSTITUTE OF TECHNOLOGY
-------
LONG TERM CONCENTRATION ESTIMATES CHAPTER 3: STUDENT ACTIVITIES
3.Now we are ready to go! A click on "Load Default" would allow you to begin.
~j a i§j w yy m us ai n n
'!• rnwrnnrnont Mo doling NuUcdp®
ll«M Mp Hew TP
I'wl I Pxa*J!| W°lI
cc
i oirtmlPiithWiiy
Diajciuifo'i dfTnifl Run
fiuMiUfi
Pollutant N*m(>
• Cuh:nlak>-: -
® ConrenValtort
j r "''
Dltpmicm Option
f Rural OfspArtlon
(• Urban otfS^fslori
Poiiifl^nrt
t'-t: !" |
" (oc )»' '
[5? Re3Ut«toiv Dftfauli Mode
r • , ¦
*f ><"'1¦¦ ' "i
,n':t
PU*M clklt httt 10 «kd Dowuldkd OEMS Ltbifty kttd butiUtlitxt IrullUttidA*.
........—.......
* 4J
* *a «vA
; start
Sipro 4**30 ?w».' ¦
J V' / 'i' • Jr,1
•?. 'n •• • «>
W/x mhwmi
C<-y. ivJJwj
4.For "Description of this run" you would enter a unique name, e.g.,
myschoolnamel. You also need to enter a "Subtitle". You could enter
today's date but remember not to include any spaces. Example: 4/16/04
5.You would next enter the "name of the pollutant". You cannot have any
spaces in the name of the pollutant. You can put an underscore like this,
chemicall_chemical2 or you could capitalize the first letter of each part, e.g.,
ChemicallChemical2. In this case we are using mercury.
6.For "calculate" you would choose concentration.
7.Enter the "Dispersion Option" - urban
8.Enter the "Regulatory Default Mode" - X
9.The other variables on this page are already selected.
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
91
-------
CHAPTER 3: STUDENT ACTIVITIES LONG TERM CONCENTRATION ESTIMATES
PAGE 2 - THE RECEPTOR PATHWAY
l.You would click on the Page 2 button.
If. I nwuoiiment Modeling Nct»c«|W
lu a m sj m W w m ?i m
Of** lOBfl
I < . . j W I
ttapjttn W4p» Hew To
~a
Ree«|tk* f.tttiAjy
<4 Pdlw Cafi4UiilHi-
Qtid Wfcfrwatlon
Numtjef cifT'ifecllono
Niimb«fofPinfl<5) |
NWjiblir oft'.nti (jUwipi iiei Ring [
HijiijhtlM'or'Mloii
| r *,H .« :*'.
Ring IMtfaftog...
,< if ,rj< fViijfe "¦ j
PUbm rtwfc USU *4 Download OEMS Lihisiy and lr>*taUnlktn taftnurtiatii
J start.
JU"» --'wiy.' fi ' J: ji.-frt-M . - s • f
2.For "Pathway" you would click the white radio button next to polar
3.For "Number of Directions" you would enter 36
4.For "Number of Rings" enter 7
5.For "Number of Calculations/Ring" enter 1
6.For "Weather Station" you enter Washington, DC; 1982-1986 (Note: it must be
typed in exactly as shown)
7. Now go on to Page 3.
92 CENTER FOR INNOVATION IN ENGINEERING AND SCIENCE EDUCATION AT STEVENS INSTITUTE OF TECHNOLOGY
-------
LONG TERM CONCENTRATION ESTIMATES
CHAPTER 3: STUDENT ACTIVITIES
Page 3 - The SOURCE PATHWAY
You would click on the Page 3 button.
I KvlJOnmenl Moitiling Ncl»r«|M!
~I lej si HI M M II *1 3J
Op* i)N Lorn *»• y<* nw-t#
| Pjgo? | jPfotftTf fii'j* 4 f
us
'I '
¦»!»*£• r>.XltW.(V
Ntimtlifpf Poll(||:inl
^JrLZ"h:
i— —
M »rn» of Pollutant 6 ourt • jPouuUrtMourtaX
jqui« v ;,joa ""
WcnTvn# « PiiMrtftwrcH r fwifiotiic# C Voi^n# ftouM
f.flnwtimrit.aUUmg |
Ermsion Height •• v;-
Inr.ff .:acKL''i»nwt»r (mj Jo I
Pift>nwiinln(tifiTaB»?n [
Pl» m» cfcck tail lo i «4d Download OEMS Uhrwy md lmt*fl*uon liwtwrtion*.
»i Start * TJt ¦ ¦ i'»». : 11$F *•" •' ' ... ,r r ' If I . * -.11
The source information all refers to the source of the chemical pollutant. There are
three main types of sources that the ISC Model can be used to predict:
• point sources \
• area sources
• volume sources
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
93
-------
CHAPTER 3: STUDENT ACTIVITIES LONG TERM CONCENTRATION ESTIMATES
Page 3 - The SOURCE PATHWAY - Entering Data for Source 1
Now you would start preparing to enter the data on the sources of the pollutant
from the proposed power plant.
1.For "Number of Pollutant Sources" leave "1"
2.Enter the "Name of Pollutant Source" - put "smokestack" in place of
"PollutantSourceX"
3.Leave the "Source Coordinates" km as X = 0.0 and Y = 0.0
4.Make sure that "Point Source" is selected.
5.Enter the following data for your source 1, the smokestack:
a. "Emission Height (m)" = 30.0
b. "Pollutant Exit Temperature (K)" = 400
c. "Pollutant Exit Velocity (m/s)" = 2.3
d. "Inner Stack Diameter (m)" = 1.5
e."Emission Rate (g/s)" = 2.6
Congratulations! This finishes the entry of input for the Source, the smokestack.
94 CENTER FOR INNOVATION IN ENGINEERING AND SCIENCE EDUCATION AT STEVENS INSTITUTE OF TECHNOLOGY
-------
LONG TERM CONCENTRATION ESTIMATES
CHAPTER 3: STUDENT ACTIVITIES
Page 4 - The OUTPUT PATHWAY
You would now click on the Page 4 button.
¦f 1 nvl/onmcnt Mudcllnf) Nel»i..i|w
•- *
~j e isi u in
M 183 SI 1
3 m
Mw vr»Mtef |Fo
Output ril« lab«l |ou!pi/tfnoL»to«lx
PUu« rifk but wo ftid Dovnloid OEMS Library *nd lnniU«tjon UiiuucUoni
•» . ' n 0- - M. H-t-' 3 ) iji »W4; **¦ | Enrtgv-i'wiv. r. if; Acs" .- ¦ • kj t; r. w
Only three things need to change on this page.
Make sure that there is an "X" next to "Pollution by All Sources" and that the
"Number of Maximum Values to Summarize" = 10
\
1.You now need to enter an "Output File Label." Choose a unique name so that
you don't write over someone else's file. For example, you might use
"MySchoolNameLTout" Put your name in place of "Output File Label X"
2.Next save your file, by clicking on the "Save" button. A small window will
pop up and you will need to enter an "Input File Name" Make sure to use a
unique name. We'll use "MySchoolNameLTinput." Remember, feel free to
use your own name. You do not have to use the same file and source names
as in this example.
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
95
-------
CHAPTER 3: STUDENT ACTIVITIES
LONG TERM CONCENTRATION ESTIMATES
3.You would click the "OK" button. You will see a message stating that the
"system is saving data"
Congratulations! All your data is entered and saved. Now, the most exciting part,
you are going to run the model!
Running the Model
Ok, you have entered the data from the power plant, and saved it. Now let's try
and run the model.
Li]
You would click on the "Run" button. Run
You would see a message that states "Model is running, please wait" You would
then see "Model Running Completed"
When you click on the "View" button v,evy you would find 53 pages of data. For
our analysis, we will view select data.
Step 4 - Analyze the Data
Look at the selected data below. It represents the average concentration of mercury
in micrograms/cubic meter at different distances and in different directions for
each of the four seasons.
Locate the direction of the highest concentrations at 2 kilometer and 8 kilometer
distance from the source. Identify those concentrations to the nearest micrograms/
m3 for each of the four seasons.
Step 5 - Drawing Conclusions
The following community map shows the locations of the proposed power plant,
the present school, the hospital, the residential area and proposed new school
locations.
96 CENTER FOR INNOVATION IN ENGINEERING AND SCIENCE EDUCATION AT STEVENS INSTITUTE OF TECHNOLOGY
-------
LONG TERM CONCENTRATION ESTIMATES
CHAPTER 3: STUDENT ACTIVITIES
It would be useful to print out copies of the map below.
13 v
litftj-rijita
EPAzEnviroMapper
Location on Map
Site Identification
Red Dot near river and
Scott
Proposed
ChemPure plant
Orange Dot near river
and Washington
Proposed Power
Plant
Green Dot near Bank and
Park Manor
Hospital
Blue Dot near Gilmore
Present School Site
DOWNWIND: LEARNING SCIENCH USING AN EPA CONCENTRATION MODEL
97
-------
CHAPTER 3: STUDENT ACTIVITIES
LONG TERM CONCENTRATION ESTIMATES
Proposed sites for new school include:
1.Area between Lookout and Park Manor
near Hospital
2. Area south of State Route 837 just west of
Park
3. Area just north of the intersection of Rabe
and Cemetery
Main Residential Area is located between 1st
and 10 th Streets
Using the concentration values in the table above determine the predicted
concentration levels at the present school, the hospital, the residential area and
proposed new school locations in each of the four seasons. Since you only have the
four cardinal directions - north, east, south and west - your values will be rough
estimates. Remember 1 mile = 1.61 kilometers
Team Report
What advice would you give to the community about the selection of a site for the
new school?
98 CENT® FOR INNOVATION IN ENGINEERING AND SCIENCE EDUCATION AT STEVENS INSTITUTE OF TECHNOLOGY
-------
LONG TERM CONCENTRATION ESTIMATES
CHAPTER 3: STUDENT ACTIVITIES
3p'- -a
A
w rfln# Student Worksheet:
Long Term Concentration
Estimates
Name
The Action Plan - Procedures to follow
Step 1 - Gathering Information
Possible pollutants from coal powered plaints -
Step 2 - Specifics on the Plant
Type of Source
Height (m)
Exit Temperature (°K)
Exit Velocity (m/s)
Diameter (m)
Emission Rate (g/s)
Step 4 - Analyzing the Data
Distance'! Winter
LSP™$
1 Summer j
Fall 1
]]
j]
Dir.!
Cone.
1 Dir,l
Cone.
Dir.!
| - - ! ..
Concl
Dir.
Cone. |
2 km. i
1 li ll
8 km.
i. '
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
99
-------
CHAPTER 3: STUDENT ACTIVITIES
LONG TERM CONCENTRATION ESTIMATES
Step 5 - Drawing Conclusions
Site
Concentration (micrograms/cu.m.);
Winter
Spring
Summer Fall
Present
School
; 1 - - :
— --
- -
Hospital
r _ r
I
Residential
Area
Proposed
School Site
1
Proposed
School Site j
2
T ¦
i
Proposed
School Site ¦
3
s
Team Report
Prepare a report addressing the original question -
1.Which site would you recommend for the new school?
100 CENTER FOR INNOVATION IN ENGINEERING AND SCIENCE EDUCATION AT STEVENS INSTITUTE OF TECHNOLOGY
-------
LONG TERM CONCENTRATION ESTIMATES
CHAPTER 3: STUDENT ACTIVITIES
Student Resource:
Mercury FAQ
Frequently Asked Questions about Mercury
Q How does mercury occur in the environment?
^ Mercury is a naturally occurring element that can be found throughout the environment.
Human activities such as burning coal and using mercury to manufacture certain products,
have increased the amount of mercury that is currently cycling in the atmosphere, in soils,
and in lakes, streams and the oceans. Mercury in these locations increases risks to people
and wildlife.
"What are the biggest sources of mercury air emissions?
ft According to EPA's 1999 National Emissions Inventory, coal-fired electric power plants are
the largest source of human-caused mercury air emissions in the U.S. Power plants account
for about 40% of total U.S. manmade mercury emissions. Other large sources are industrial
boilers (about 10% of U.S. mercury emissions), burning hazardous waste (about 5%), and
chlorine production (also about 5%). Burning municipal waste and medical waste was once a
large source of emissions but today, in response to EPA and State regulations and reductions
in mercury use, these sources are much less important.
Hhow do people and wildlife become exposed to mercury?
^Mercury that is emitted to the air falls to the ground either very close to the source or many
miles away. When mercury is deposited into the water, or runs off the ground into the water,
microorganisms convert it to methylmercury, a highly toxic form of mercury.
Small organisms take this up as they feed. As animals higher up the food chain eat those
small organisms, they also take in methylmercury. The process, known as bioaccumulation,
continues with levels of mercury increasing as it moves up the food chain. Fish that are
higher in the food chain, such as sharks and swordfish, have much higher mercury
concentration than fish that are lower on the food chain. Humans become exposed when they
eat fish that are contaminated with mercury.
5 How does mercury affect health?
^Methylmercury is highly toxic. The developing fetus is the most sensitive to the effects of
mercury, and so women of childbearing age are the population of greatest concern. Children
of women exposed to relatively high levels of methylmercury during pregnancy have
exhibited a variety of abnormalities, including delayed onset of walking and talking, reduced
neurological test scores, and delays and deficits in learning ability. Eight percent of the
women of childbearing age have levels of mercury in their blood that exceeds the level EPA
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
101
-------
CHAPTER 3: STUDENT ACTIVITIES LONG TERM CONCENTRATION ESTIMATES
considers safe. In addition, there is growing evidence that methylmercury exposure can have
adverse cardiovascular effects for adults, resulting in elevated blood pressure and incidence
of heart attack.
«D o some fish contain more mercury than others?
®Yes. Predator fish - big fish that eat smaller fish - tend to have higher methylmercury
concentrations than other fish. The Food and Drug Administration has issued advice to
pregnant women regarding consumption of certain types of fish. States issue fish advisories
that inform consumers of the extent to which they need to limit their consumption of locally
caught fish. Certain species of commercially available saltwater fish, such as shark and
swordfish, kingfish and tilefish also can contain high levels of mercury. National and regional
information is available from our Fish Advisory page.
®How will EPA reduce mercury emissions from power plants?
&EPA is currently developing a standard to limit emissions from coal-fired power plants. A
standard will be proposed for public comment on or before December 15, 2003. The
Administration's proposed Clear Skies legislation would cap emissions of mercury at 26 tons
in 2010 and 15 tons in 2018, down from a current total of 48 tons.
Qwhat else is EPA doing to reduce mercury emissions?
^EPA has taken a number of recent actions to reduce mercury pollution, including issuing
stringent regulations for industries that significantly contribute to mercury pollution. These
actions, once fully implemented, will reduce nationwide mercury emissions significantly.
They include:
• Municipal waste combustors (MWCs) emitted about 42 tons of mercury emissions into
the air in 1990. EPA issued final regulations for MWCs on October 31,1995. These
regulations require that mercury emissions from these facilities be reduced by about
90 percent, from 1990 emission levels.
• Medical waste incinerators (MWIs) emitted about 50 tons of mercury emissions into
the air in 1990. EPA issued emission standards for MWIs on August 15,1997, which
requires mercury emissions from MWIs be reduced by over 90 percent from 1990
emission levels.
In addition, EPA has other regulations that have been proposed that will reduce emissions of
mercury including standards for: chlor-alkalai plants and industrial boilers. In addition, other
factors that have influenced mercury emissions include:
• Federal bans on mercury additives in paint and pesticides;
• Industry efforts to reduce mercury in batteries;
• Increasing state regulation of mercury emissions and mercury in products;
• State-mandated recycling programs; and Voluntary actions by industry.
Reprinted with permission: http://www.epa.gov
102 CENTER FOR INNOVATION IN ENGINEERING AND SCIENCE EDUCATION AT STEVENS INSTITUTE OF TECHNOLOGY
-------
SHORT TERM CONCENTRATION ESTIMATES
CHAPTER 3: STUDENT ACTIVITIES
Student Activity:
Short Term Concentration
Estimates
Short Term Concentration Estimates
Using EPA's Internet Geographic Exposure Short Term Model
ChemPure Inc. has proposed a site for a new factory in Donora, Pa. The plant has
the potential to revitalize industry in your town. There is a concern that an accident
may release pollutants into your community. Because of the ecological disaster that
occurred in Donora in 1948, ChemPure is particularly sensitive to minimize the
environmental effect of their company on the surrounding community.
Your team will gather information regarding potential pollutants released in the
manufacturing process, examine the proposed site and assess the potential pollutant
concentrations at various locations using the Environmental Protection Agency's
Internet Geographic Exposure Modeling System Short-Term Computer Model. You
will also recommend the best choice for the location of the proposed new school.
Your Team's Assignment: Assess the possible pollutant concentrations of this
plant at various locations in the community.
Your team is looking for answers to these specific questions...
1. What pollutants could potentially be released as a gas?
2. What might be the concentrations of pollutants near the present school, the
hospital and the chief residential area?
3. Which proposed new school sites would have the lowest concentration of
pollutants?
4. Present evidence to back your conclusion.
The Action Plan: Procedures to follow
Step 1 - Using the attached ChemPure Brochure, gather information regarding
potential pollutants that may be released as a gas in the manufacturing process.
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL 103
-------
CHAPTER 3: STUDENT ACTIVITIES
SHORT TERM CONCENTRATION ESTIMATES
Jl Pdlfutdnlk M Lin Mlcrotolr inlmnct t *|ilnrer
Pit Edk VWw fasmt*s Foe* H*t> 3#
©»** • Q S iM r
-------
SHORT TERM CONCENTRATION ESTIMATES
CHAPTER 3: STUDENT ACTIVITIES
•C2 CortgrttfiOM
0'nrlcl*
edt FwxtM Took mp
©»• O id id P>~* 9>Wi 4$ 0- iSii • ,j ct
"Vf ' ^'"jjf^afchWab'I'^EB' l)tt- £• | C"W»mng« ^~Beotawtb yjh«f» You Uvq » tMndcyi-to Mv Envtnmmflft > Mapping RatUM
'3l Window lo My fnvironmenl Mk-ra»olt Inlnrnel fsplnrer
»«* wSitewywSw»»w5
At) f« intar««ntlr>g th* m*p window will »pf>»«r
n put «t ih» Information .•** bttlow.
c^ffimunity pa
(Tovn,«ut«)
Cvonty(»; W»»hin®*on PA,
WostmoxrUod PA
C.>rmr«liictrul DlrtrtctfO 20(PA), ia(PA)
Ui4>»n »•> Mon«*f*n Pa
w MtmhudfO I. uvw Mrthorkfl »MU.
P«MiylY*nip, *»«
vfrtyfl'luv. .
w •t»rbodv(>) Mefio{»h»l» W««i,
Monono»h«l» Hiv«r
Ar.« / Width *i
Window
At>PtC*. pWUlMsOft «~*!*»•» AW.
Ho. ofJ'j
i« porting to SPA
r. MU«rr,oflr«phi bfiuwUn.
ft era ZIP Co(3«»
f* o C«unii«*
V Air monitors
BHHMtoimiftr
p * Surface w«?«r
n • Ground w*n*r j
n * ooim*
ad>A»Ji*»rm««M*»-*
P * SoHflC# WdtW
P* • <3found w*tar
H * Othnrt
K-)Tw|Hyi»|>hU fMhw
~ Sf>«*c»»l flo«jd
U#J*rd Aia* V:
Iffl
~ L.g.nd
Identify i*Jr AWnlarn
WME Help j
Add •&•<*»«**) V
¦
- a <*) Life " Wtan Ar*i#tix $£J »
&»t>p<*i* - fJShoppHo - ^fnrt*rK« • "VrYflhoai » <$l •
Ho |PA W»t«r monitoring «n» « found lr
M'A.Unm# I to*Y.«itt5«art*£tdX* l EOA l Centoct.Ux
ImA updrtod ariWM'WMtoy. October 06,20M
URL http //134 -87 -00.108Mma*ir/AhKk>w up
$ Cawfc -^.871096, «u«ms
$ tntwnti
,j start X
i#>. j CJ u-it"
V V 11 .11 AM I
Unfortunately, at this scale you cannot see the single air monitor and there are no
water monitors noted.
Step 3 - Gather specifics regarding the proposed industrial site.
Using the technical data above, what types of sources of potential pollution are
present? Look for point, area, and volume sources. Gather data on smokestacks,
their height and width, pollutant exit velocity in m/s, pollutant exit temperature in
degrees K, pollutant emission rate in g/s.
Step 4 - Use the information you have gathered to access the model.
Before we go on, you should understand this model. In this case, the ISCST3 model
can be used to predict the movement of chemicals through the air. The model is a
complex computer program that runs on a computer at EPA headquarters.
There are some big advantages to using computer models. We can try changing the
values of different variables and running the model to see what would happen in
DOWNWIND: LEARNING SCIENCE USING AN EI'A CONCENTRATION MODEL 105
-------
CHAPTER 3: STUDENT ACTIVITIES
SHORT TERM CONCENTRATION ESTIMATES
different scenarios. This can be a big advantage in predicting and preventing
hazardous air pollution. You are now going to use the EPA ISCST3 model to
analyze the data on ChernPure.
Notice the "ST" in ISCST3. ST stands for "short term." This computer model uses
hourly meteorological data to predict how chemicals are dispersed. The main
difference between the Short Term and Long Term models is the type of
meteorology data that is used as input. Hopefully the results will help both the
business and community to determine the concentration levels of emissions of
chemicals that might be produced by the ChemPure factory.
You are now ready to use the model. Remember, the goal of this model is to predict
the dispersal of a pollutant through the air over a short period of time. In order to do
this, you will have to give the model some input,
INPUT to the ISCST Model
There are FOUR INPUT pathways:
The CONTROL pathway
The RECEPTOR pathway
<©
The SOURCE pathway
Hi
The OUTPUT pathway
Since you cannot access the on-line model, all significant access screens have been
duplicated and the instructions simulate the entry of data from the ChemPure
Company into each of the four ISCST pathways. When finished, the model is run
and data obtained. Once you have finished that, you can start to analyze the data
and provide ChemPure with an assessment of the situation.
106 CENTER FOR INNOVATION IN ENGINEERING AND SCIENCE EDUCATION AT STEVENS INSTITUTE OF TECHNOLOGY
-------
SHORT TERM CONCENTRATION ESTIMATES
CHAPTER 3: STUDENT ACTIVITIES
Entering Control Data
1. You would go to the IGEMS web site and sign in.
15f IGIMSMpmiiBrl,ns>n NatM;«|JC > |
Pto Mt Go Communicate* Holp
HI B«:k RtfaxJ Hem* S«wich N«xr*{*
¦ :t A ® 8
nu so*
SI
1 j j t M«Ue jhlip: "tin** 11
1j ® W«bM«rf gjj Dalwviar gj| Kacfc. $ 1
T *~\ r7i\f n
. vJT Jtl/ JV10 Intern©? Geogrbphfcaf
Welcome to IGEMS Login
l am a New User. sign me t>pi
I am already registered.
IGEMS User 10
Password'
I forgot my D and/or password, l neod help'
Before you access the system, please see this important Note
Pl««at click htflt to rand DowtJoid OEMS Libiwy uuiliuitllttiui luinirlkas
ft R6j» 1 jtbeiiminti 0or*
ijstsrt Sfc •- •. .. :• j ,-r •••!•«' •' '
2. Then you would move your mouse over the Environmental Modeling link at
the top left of the page and click on ISCST3.
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL 107
-------
CHAPTER 3: STUDENT ACTIVITIES
SHORT TERM CONCENTRATION ESTIMATES
1" (ifMS Menu NcHr«i|ie
ft" 'fT- #1
i% tdK 'At-t <*> C9smrX#or Help
1 € M A * A at 35
!g BwA niolMd Hem# 6 HKti HHscotA Prrf SoeuJy Shop
S3
¦ ¦ » 1 jJF J *
I & U*>** M«u«gr $ W«hM,* §| CArvl* j$| $ Prof* $ Y*r»»P*«M fijf Downlo*! $1
vMlMtzntn * J Hp w?wi n»»w
-at Aa «ii» i
¦|t| ¦:>, . J I.-.' 'If!?,.; I.V., . jf. • *,**» R,kv« ftv
3. Now you would be ready to go!
108 CENTER FOR INNOVATION IN ENGINEERING AND SCIENCE EDUCATION AT STEVENS INSTITUTE OF TECHNOLOGY
-------
SHORT TERM CONCENTRATION ESTIMATES CHAPTER 3: STUDENT ACTIVITIES
$'• fnvfrqnment Modeling Nplacftpa
swim
qj I B cy 11 88
m ai ?i n
•tor" Opt* Sa* gun MB»T»
l>n»u.y
>WI I P*Qn? I PJH'3 I Paa»< I
lii....... -—
i ui iii <>< patthwny
ijt senrili ow ofT»J a F>«i s
, Subt'lio
¦ PftlNiMnl Narr.ts
rCUteutai*
! * Cohcni1ii!lci|i
Oio0««3l6ri Opliort - "....i.;..
r Rural Disp«i9ion
i» uifcati DiepDhmn
r f'QliutJnre
;:;; r . ...., :• r ¦¦ |
. F ' ¦' m
If P'3flul3t#'i)efauiiMetin
P R«dfilW alK' -.1 r
"
It It, »¦¦¦¦!
Pltmt click LtlS to r#«d DowrJo4d OEMS Ubrwy *nd InaUtUtion Instruction*-
*Tj start
J r'i I, ¦ IS \ --i-O 5 «: . / JfM.- lUrt.vl
'¦ --4L Vl iAffil cn
4. For "Description of this run" you would enter a unique name, e.g.,
MySchoolNameST.
5. Visit the ChemPure site to get the data you need.
6. Enter the "name of the pollutant." You cannot have any spaces in the name of
the pollutant. You can put an underscore like this, chemicall_chemical2 or
you could capitalize the first letter of each part, e.g., ChemicallChemical2. In
our case we will use EthyleneDichloride
7. For "Calculate" choose concentration.
8. Enter the "Dispersion Option" - urban or rural - choose urban
9. Enter the "Regulatory Default Mode" - X
10. Don't worry about the other variables on this page for now, they are already
selected.
11. When you have finished entering the data for page 1 you would go on to
page 2.
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL 109
-------
CHAPTER 3: STUDENT ACTIVITIES SHORT TERM CONCENTRATION ESTIMATES
The Receptor Pathway
1. You would click on the Page 2 button.
Jnwpjmwnl Murtrlin^ Nf|Kap*
iHHHHHyyyi
~j Id lil 1
,i hi m i«a at n i
Op*n !»*• tMU mm vw tinftttn HMp How T»
' I > I fwi |
ar
fU'r.«i|rtoi p.xiiwjy
(* 'PftKir Cam din uUt J',r Courdi.kut«(i
><3lW IrtfowiatMrt • *— ¦ it * : It
Kumutr of Direction^)
NiDYibsfofRlnfl^i
NuitlDdl Of >>li Hli1l6il(s) |l"?i H
¦Qiwiiy RW3 rj'UiiimMKi.
^ : "
r rt.ii ¦ •• '-'.w -vjifti,
*,-,kwM.i# /v.. |
v*/»sfc»r Station \ G*lacl..,
PUu* click tuuc lo i ltd Doiruload (JEMS Libruy vd InttalhUori InrtiiKliom
' ilLjflt VK» lift* SB •>£¦ J
Sf^ft » '• - Jfr-.Hti . ' ¦ j. Ji- ••.:••• • i q-:'--. y'lLi#.,,! ¦ ?' ft; i-.K}
2. This is the data that would be entered into the model.
3. For "Pathway" click the white radio button next to polar
4. For number of directions" enter 36
5. For "Number of Rings" enter 7
6. For "Number of Calculations/ring" enter 1
7. For "Weather Station" you should enter
"PITTSBURGH/WSCOM_2_AIRPORT" , which is the closest weather station
to Donora, Pa.
8. Now you would go on to Page 3.
110 CENTER FOR INNOVATION IN ENGINEERING AND SCIENCE EDUCATION AT STEVENS INSTITUTE OF TECHNOLOGY
-------
SHORT TERM CONCENTRATION ESTIMATES CHAPTER 3: STUDENT ACTIVITIES
~] IS) 11] HJ 111 Ifil
New Open Loud Dehult Run Vkw HMp
S9
miitc* p.uriA»v
Mumbtr ofpalMird Oouue(i)
N;imo OfPuiiuHmt sduk'ii PoiiulinJOourtoK
V u i)
Convtiinm Utvumg
(Kill)
Source Type Polm Source f Are% flours f Volw^S-ourc#
ertili Ui«>n HoltfMfin) 110.0
FoJiiium Exit
vmotiMijjr*)
Emit 3ttn P;.m (o'i) jl 0
Pollute EMI
Tnir.|WftiHjfil (K)
lnn«r BtiickDtojtjffri (m)
-------
CHAPTER 3: STUDENT ACTIVITIES
SHORT TERM CONCENTRATION ESTIMATES
Entering Data for Source 1
Now you would start preparing to enter the data on the sources of the pollutant.
The instructions indicate what data is to be entered in each specific area.
If you look at the Technical Specifications page for ChemPure above, you can see
that there are three main sources of emissions:
1) A smokestack
2) Factory 2 has an area source
3) Factory 3 has a volume source
For "Number of Pollutant Sources" You would click on the black arrow until a "3"
appears.
Number of Pollutant Source(s) |3
Let's start with the smokestack:
1. Enter the name "smokestack" in place of "PollutantSourceX"
2. Leave the "Source Coordinates" km as X = 0.0 and Y = 0.0
3. Make sure that "Point Source" is selected
4. Enter the following data for your source 1, the smokestack:
a. "Emission Height (m)" = 10.0
b. "Pollutant Exit Temperature (K)" = 400
c. "Pollutant Exit Velocity (m/s)" = 2.3
d. "Inner Stack Diameter (m)" = 1.5
e. "Emission Rate (g/s)" = 2.6
5. Buildings can have a big effect on the dispersal of a pollutant. You will now
need to enter data on the building for Source 1, the smokestack.
6. Next you would click on the "Downwash Information" button in the lower
left.
112 CENTER FOR INNOVATION IN ENGINEERING AND SCIENCE EDUCATION AT STEVENS INSTITUTE OF TECHNOLOGY
-------
SHORT TERM CONCENTRATION ESTIMATES
CHAPTER 3: STUDENT ACTIVITIES
,J Downwtuh Information
Duikffng Height Building Wldrth
t
0
1
1)
n
1'
0 I®.
4
0
0
6
0
0
A
0
0
F
0
0
»
0
0
9
u
0
.0
0
6
11
0
0
12
0
0
13
0
0
1«
0
0
18
0
0
i! :::::::
ttiv;
li! id lej m Hi IMI u
N9W Of»n Savt LoMi D* fault rtun VW HHp
r«j»i I ph.: I Pw.i| I
1.U"
tout*
f iufrib«i 61 PolluM So«r*»(»j
^[signed by: Science Applications Inlonatlo
m
Nmm*(ifPtfflirtvdKiumco WrnokftUack
Soijrtt Ctwrtantwt
'In)
Oourte Typo is Point 3quk# 'f Aifiai'ourt®
¦•;t)iif..)flhrnYi i.jtunu |
VfjiunifrSoufc#
,j i
PMMUM 6s!
yi icKlhf (rnfii)
BniHHon R*tt< (git,) y.riO
Pwlltiftltl &-II '
TflHpflMlM (K)
ihMf$ti$Dlsmtltir(m) |l5
NUniiw i)| P
-------
CHAPTER 3: STUDENT ACTIVITIES
SHORT TERM CONCENTRATION ESTIMATES
»
\ and then you would see a "2" in the white box. Now you could enter the data
for the second source, the AREA SOURCE.
rnvfronmonl Mailing Netscape
ni i&i imi &i lu isi u sn
New Opmn Savt LomI ftatevH Nun Vbw Htip How To
j v , | " ; ; Convert from Lai/Uirifl
Soui<« "JVP0 r Polr>t Source j« -Mta Sourco ] C voiujti® Squfto
of 5 (
PUu« click hut Co r»*4 Do«mlo*d OEMS Ubfuy «nd Imt tilaticnljwuuriicn*.
.•m.-mf.,.- i.'
„• ¦ WJL VI |flj sA 1
% suit
J r>.* ¦.!• M-l
u 1 J-/If*
'i '¦ . 1 prfrA ~'M
!l
12. Enter the name "FactoryBuilding2" in place of "PollutantSourceX"
13. Leave the "Source Coordinates" km as X = 0.0 and Y = 0.0
14. Make sure that "Area Source" is selected.
15. Enter the following data for your source 2, the Factory Building 2:
a. "Emission Height (m)" = 30
b. "Pollutant Exit Temperature (K)" = 10
c. "Pollutant Exit Velocity (m/s)" = 5.2
You do not need to enter building information for Source 2, FactoryBuilding2.
The data has been entered for Source 2, FactoryBuilding2. Now you would repeat
the process for the VOLUME SOURCE.
114 CENTER FOR INNOVATION IN ENGINEERING AND SCIENCE EDUCATION AT STEVENS INSTITUTE OF TECHNOLOGY
-------
SHORT TERM CONCENTRATION ESTIMATES CHAPTER 3: STUDENT ACTIVITIES
•r t nvlronmcnt Mnriclfng NrUr<»pe
M id y mi uj isi u ri
Nw Optn Sav* Lo*d Default Run Vhw H«fp How To
f 1
PW2 | | Pay** |
EL .
M
PaHrw.iy
Np$«|r of FolM»«SocrtW*>
nm<> (ifPcimiMni Soutct |
, | , | uM.,n, |
ooiKteryp* r Poir?9ou«» ** 'Aim Bourtt J5Tytiium»8ourc»]
EniHtlort HalgMint) I
Inltidi Vtrtit W
r>irrtunp.t(m {in)
toW lateral
r—
Emn:«innp»i»('ij/i.- |
Murtiburof Pwtkuliitui
PI«M« «liek tan >«kd Dd*wJ(i*d OEMS libtwy *M ln«Ulltlion Imlnvlii>n<
»v atari
J I', J CM->' -
i":ry -¦
Entering Data for Source 3
1. Now you would enter the data on the VOLUME SOURCE of the pollutant.
2. Under the "Number of Pollutant Sources" you would see the following:
\ » I
3. You would click ONCE on the right pointing arrow, ——\ and then you
would see a "3" in the white box. Now you could enter the data for the third
source, the VOLUME SOURCE.
4. Enter the name "FactoryBuilding3" in place of "PollutantSourceX"
5. Leave the "Source Coordinates" km as X = 0.0 and Y = 0.0
6. Make sure that "Volume Source" is selected.
7. Enter the following data for your source 3, the Factory Building 3:
a. "Emission Height (m)" = 15
b. "Initial Lateral Dimension (m)" = 4.65
c. "Initial Vertical Dimension (m)" = 13.95
d. "Emission Rate (g/s)" = 2.6
The data has been entered Source 3, FactoryBuiIding3. Now you would be ready to
go to the final page, Page 4, the OUTPUT page.
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL 115
-------
CHAPTER 3: STUDENT ACTIVITIES SHORT TERM CONCENTRATION ESTIMATES
The Output Pathway
After you had clicked on the Page 4 button you would see the following:
if I nwiioiirnuril Moiltflinu Nchcapv-
nj i^j imi mi LiJ iwi i]
Niw Open Savt Lo+ti Dthull Run Vimw H*tp Hew To
Pjh«< | p..jH | nn i 1 i>-i» ¦ I
ECZZZZZZ ZZL-. - Li]
ompu Kith».iy
Output Tawa
W Paiiuflon bi Eatn eouit#
W fotMfen fcV Ait BfwUt
P Sa'jiniCvjfiUituBufi
r *U»iniuni FelUillon fiijm Ebt h 8um« o
r M*crr,um Pollution Ham All 8otjn»«
Tirm P»rlOO
pf I par i r 3 r 4 rs r« fu I* 2« l~ Monthly » erm*ro period
Note: pio*4« ch«ckup to fow
NunAfc*f of M«','«.! tjf*ffi 3wiW«8rK» HID M
OVip'HF«»l-3Kti . OutpmFi(»UI>*lX
PWw< click but to <*«i Downlo»dOEMS Libtuy ind IruitlUti
Uffirr;
CD sA i
; shirt
9h
-------
SHORT TERM CONCENTRATION ESTIMATES
CHAPTER 3: STUDENT ACTIVITIES
6. All your data would now be entered and saved. Now you would run the
model!
Running the Model
Ok, you have entered the data from the ChemPure web site, and saved it. Now let's
try and run the model.
in
1. You would click on the "Run" button. Kun
2. You would see a message that states "Model is running, please wait" You
would then see "Model Running Completed."
3. Now you should be able to find your output file.
t?'
4. You could click on the "View" button. vlew
5. You would view a 33 page printout of data.
6. Use the information obtained from the model to make an appropriate
decision.
Analyzing the Data
As an illustration, we will concentrate on just one portion of the data produced,
which shows the first highest one hour average concentrations at different distances
and directions for the pollutant (chlorine) in micrograms per cubic meter.
*"THE 1ST HIGHEST 1-HR AVERAGE CONCENTRATION VALUES FOR SOURCE GROUP: POINT "*
INCLUDING SOURCE(S): AREA .VOLUME .
*" NETWORK ID: POL1 ; NETWORK TYPE: GRIDPOLR *"
" CONC OF OTHER IN MICROGRAMS/M"3
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
117
-------
CHAPTER 3: STUDENT ACTIVITIES
SHORT TERM CONCENTRATION ESTIMATES
DIRECTION | DISTANCE (METERS)
(DEGREES) j 100.00 200.00 300.00
10.0 |1433114.88000 (90071824) 362247.53100 (90071824) 166595.89100 (90071824)
20.0 |1293119.75000 (90010724) 340993.12500 (90050824) 163327.00000 (90050824)
30.0 |1333177.38000 (90110304) 350923.46900 (90071907) 166282.10900 (90071907)
40.0 |1444148.00000 (90110623) 375762.03100 (90110623) 176589.40600 (90110623)
50.0 |1474431.38000 (90042424) 382350.28100 (90042424) 179524.46900 (90042424)
60.0 |1469878.00000 (90022020) 380731.03100 (90022020) 178997.28100 (90110103)
70.0 11456108.88000 (90032707) 374087.00000 (90032707) 174103.26600 (90032707)
80.0 |1434120.25000 (90053103) 374747.12500 (90053103) 176691.82800 (90030205)
90.0 |1397648.13000 (90080804) 364743.93800 (90091804) 175025.73400 (90091804)
100.011382977.00000 (90050701) 371179.00000 (90080805) 174449.00000 (90080805)
110.0 |1280761.13000 (90050222) 364364.90600 (90081904) 175006.56300 (90081904)
120.0 |1095083.13000 (90042502)272934.53100 (90062720) 129610.43000 (90062720)
130.0 |1235236.63000 (90081603) 359872.56300 (90081603) 171674.70300 (90081603)
140.0 | 952368.06300 (90052320) 255926.46900 (90071904) 132207.09400 (90071904)
150.0 |1241883.88000 (90032703) 332938.15600 (90032703) 153928.60900 (90032703)
160.0 |1055417.00000 (90080901)261143.70300 (90082502) 125691.10900 (90082502)
170.0 (1002262.75000 (90072706) 260510.87500 (90080901) 133304.48400 (90080901)
180.0 | 876258.87500 (90052402) 264989.62500 (90072706) 134749.45300 (90072706)
190.0 (1151626.63000 (90091203)339903.18800 (90091123) 166256.23400 (90091123)
200.0 |1147050.63000 (90080206) 335111.50000 (90061601) 165062.60900 (90061601)
210.0 | 938001.12500 (90072707) 258196.34400 (90072707) 127492.86700 (90072121)
220.0 |1065098.63000 (90083024) 316188.62500 (90083024) 155400.68800 (90083024)
230.0 |1136093.75000 (90102003) 336154.93800 (90102003) 165128.67200 (90102003)
240.0 |1127150.75000 (90081024) 327289.25000 (90081024) 159280.78100 (90081024)
250.0 |1147050.38000 (90092802) 335111.53100 (90032805) 165061.50000 (90032805)
260.0 |1160137.63000 (90071503) 336583.78100 (90071503) 162907.03100 (90071503)
270.0 |1175205.50000 (90042405) 341621.78100 (90043005) 167061.39100 (90043005)
280.0 |1185311.00000 (90070803) 333514.34400 (90052506) 165281.56300 (90052506)
290.0 |1214404.63000 (90062821) 348202.34400 (90062005) 168956.09400 (90041902)
300.011560835.00000 (90031422) 502769.56300 (90031422) 249631.87500 (90031422)
310.0 11269865.38000 (90071807) 355843.06300 (90010803) 171119.65600 (90081621)
320.0 11285212.88000 (90010804) 359871.81300 (90051124) 172373.14100 (90031324)
330.0 |1329183.38000 (90010302) 359459.50000 (90062623) 173673.50000 (90062623)
340.0 11358261.13000 (90111509) 367790.18800 (90072921) 175008.39100 (90091807)
350.0 11382977.88000 (90022023) 371177.71900 (90071723) 174448.45300 (90071723)
360.0 |1414672.63000 (90080322) 373906.43800 (90060821) 177291.35900 (90060821)
DIRECTION | DISTANCE (METERS)
(DEGREES) | 500.00 1000.00
10.0 65903.67190(90030108) 21158.13280(90030108)
118 CENTER FOR INNOVATION IN ENGINEERING AND SCIENCE EDUCATION AT STEVENS INSTITUTE OF TECHNOLOGY
-------
SHORT TERM CONCENTRATION ESTIMATES
CHAPTER 3: STUDENT ACTIVITIES
20.0 66655.92970 (90050824) 21273.66210(90050824)
30.0 | 67357.91410 (90071907) 21404.62890 (90071907)
40.0 | 71221.83590(90110623) 22688.09570(90110623)
50.0 | 72360.29690(90042424) 23080.31640(90042424)
60.0 | 72273.34380(90110103) 23072.78520(90110103)
70.0 | 69416.24220(90032707) 21835.62700(90032707)
80.0 71880.48440(90030205) 23033.42190(90030205)
90.0 | 71624.92970 (90091804) 22993.93360 (90091804)
100.0| 71236.52340(90091302) 22947.59180(90091302)
110.0| 71288.13280(90081904) 24582.22660(90021014)
120.0| 52874.33980(90082604) 21696.83200(90021015)
130.0 | 69344.64060 (90081603) 21886.93950 (90081603)
140.0| 56852.67580(90071904) 18618.70120(90071904)
150.0 60177.84380(90032703) 18143.61910(90032703)
160.0| 51249.37500(90082502) 16292.91990(90082502)
170.0 57096.89450(90080901) 18707.56050(90080901)
180.0| 57493.18750(90072706) 18777.93160(90072706)
190.0 69113.97660(90051501) 22623.59380(90051501)
200.0 | 69033.88280(90061601) 22603.35940(90061601)
210.0| 53062.50780(90072121) 22175.00390(90102217)
220.0 64851.94530(90083024) 21083.12300(90083024)
230.0 | 68986.14840(90102003) 22581.26170(90102003)
240.0 | 65903.00780 (90081024) 21294.43550 (90081024)
250.0 | 69033.34380 (90032805) 22603.21480 (90032805)
260.0 | 67159.67970 (90032802) 22055.34960 (90032802)
270.0 | 69304.41410(90043005) 22641.22270 (90051505)
280.0 | 69326.57810(90052506) 22661.48050(90052506)
290.0 | 69853.10940 (90041902) 22690.67770 (90072807)
300.0 1104460.69500 (90031422) 34088.57030 (90031422)
310.0 | 70451.86720 (90081621) 22766.98050 (90101607)
320.0 | 70747.26560(90031324) 22810.44730(90080324)
330.0 | 71032.62500 (90062623) 22855.79880 (90110405)
340.0 1 71288.67190 (90091807) 22901.45700 (90110703)
350.0 ) 71236.35940(90110122) 22947.53910(90110122)
360.0 ) 71701.98440(90060821) 22993.90820(90060604)
DIRECTION | DISTANCE (METERS)
(DEGREES) | 1500.00 2000.00
10.0 | 11301.06930
20.0 | 11353.56840
30.0 | 11410.84960
40.0 | 12198.25000
50.0 | 12455.29790
60.0 | 12452.82520
70.0 t 11669.05660
(90030108)
7444.
(90050824)
7447.
(90071907)
7451.
(90110623)
8018.
(90042424)
8229.
(90110103)
8227.
(90032707)
7569.
38281 (90030108)
43896 (90050824)
91406 (90071907)
73047 (90110623)
05273 (90042424)
94824 (90110103)
46338 (90032707)
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
119
-------
CHAPTER 3: STUDENT ACTIVITIES
SHORT TERM CONCENTRATION ESTIMATES
12440.02250 (90030205) 8221.76074 (90030205)
12430.45800 (90091804) 8217.36719 (90091804)
15606.09570 (90021017) 12313.06930 (90021017)
17560.47270 (90021014) 13968.09670 (90021014)
15383.75390 (90021015) 11867.38960 (90021015)
11701.17770 (90081603) 7684.07568 (90081603)
10013.47850 (90071904) 6563.32227 (90071904)
9365.11914 (90032703) 5870.60449 (90032703)
8743.73828 (90082502) 5725.89795 (90082502)
9992.97168 (90080901) 6587.26514 (90080901)
9983.54785(90072706) 6613.72021 (90072706)
12300.75490(90051501) 8155.63281 (90051501)
12293.22070 (90061601) 8152.14648 (90061601)
15834.78030 (90102217) 12569.03520 (90102217)
11315.55470 (90083024) 7392.32959 (90083024)
14868.01370 (90102216) 11768.16410 (90102216)
11462.56350 (90081024) 7587.60449 (90102216)
12293.10160 (90032805) 8151.99609 (90032805)
11955.06840 (90032802) 7912.10107 (90032802)
12309.97170 (90051505) 8160.11719 (90051505)
12470.49800 (90102214) 9872.03223 (90102214)
13267.89160 (90102214) 10106.94240(90102214)
18520.82230 (90031422) 12266.83500 (90031422)
12361.59770 (90101607) 8185.18359 (90101607)
12376.40920 (90080324) 8192.12500 (90080324)
12391.82320 (90110405) 8199.15430 (90110405)
12406.02540 (90110703) 8205.75000 (90110703)
12418.86910 (90110122) 8211.78418 (90110122)
12430.44530 (90060604) 8217.35449 (90060604)
Locate the direction of the highest concentrations at 1 kilometer and 2 kilometer
distance from the source. Identify those concentrations to the nearest hundred
micrograms/m3 (fig/m3).
Interpreting the Data
The following community map shows the locations of the proposed power plant, the
present school, the hospital, the residential area and proposed new school locations.
It would be useful to print out copies of the following map.
120 CENTER FOR INNOVATION IN ENGINEERING AND SCIENCE EDUCATION AT STEVENS INSTITUTE OF TECHNOLOGY
-------
SHORT TERM CONCENTRATION ESTIMATES CHAPTER 3: STUDENT ACTIVITIES
¦ate aon.tfl-Ql
-Wakeut
A EPk EnviroMapper 7
Location on Map
Site Identification
Red Dot near river and
Scott
Proposed ChemPure
plant
Orange Dot near river and
Washington
Proposed Power
Plant
Green Dot near Bank and
Park Manor
Hospital
Blue Dot near Gilmore
Present School Site
DOWNWIND: LEARNING SCIENCE USING AN EI'A CONCENTRATION MODEL
121
-------
CHAPTER 3: STUDENT ACTIVITIES
SHORT TERM CONCENTRATION ESTIMATES
Proposed sites for new school include:
4. Area between Lookout and Park Manor
near Hospital
5. Area south of State Route 837 just west of
Park
6. Area just north of the intersection of Rabe
and Cemetery
Main Residential Area is located between 1st and
10th Streets
Using the concentration values in the table above determine the predicted
concentration levels at the present school, the hospital,, the residential area and
proposed new school locations. Remember 1 mile = 1.61 kilometers
Team Report
Based on this example:
1. What advice would you give to the community about the selection of a site
for the new school? In making these recommendations consider the results of
the Long Term study.
122 CENTER FOR INNOVATION IN ENGINEERING AND SCIENCE EDUCATION AT STEVENS INSTITUTE OF TECHNOLOGY
-------
SHORT TERM CONCENTRATION ESTIMATES
CHAPTER 3: STUDENT ACTIVITIES
Student Worksheet:
Short Term Concentration
Estimates
Name
The Action Plan - Procedures to follow
Step 1 - Gathering Information
What is the pollutant being studied?
Step 2 - Gather information regarding conditions in Donora today.
How many monitors are available in Donora today?
Air -
Water -
Step 3 - Gather specifics regarding the proposed industrial site.
Smokestack Information
Emission height
Exit temperature
Exit velocity
Stack diameter
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
123
-------
CHAPTER 3: STUDENT ACTIVITIES SHORT TERM CONCENTRATION ESTIMATES
Factory Building 1
Building Height (m)
Building Width (m)
Factory Building 2
Emission height
Width of source
Emission rate
Factory Building 3
Emission height
Initial lateral dimension
Initial vertical dimension
Emission rate
Step 4 - Use the information obtained from the model to make an appropriate
decision.
Distance j
Direction
Concentration
One kilometer
124 CENTER FOR INNOVATION IN ENGINEERING AND SCIENCE EDUCATION AT STEVENS INSTITUTE OF TECHNOLOGY
-------
SHORT TERM CONCENTRATION ESTIMATES
CHAPTER 3: STUDENT ACTIVITIES
jTwo kilometers
Site
Concentration
(mi crogr ams/cu. m.)
Present School
•
Hospital
-
Residential Area
" — —
Proposed School
Site 1
Proposed School
Site 2
Proposed School
Site 3
Team Report
Based on this example, prepare a report:
1. What advice would you give to the community about the selection of a site
for the new school?
2. Present evidence to back your decision.
WEB LINKS
The on-line version of this lesson can be found at:
http://ciese.org/curriculum/downwind/,shortterfft.html
The EPA's "Window On My Environment" site can be found at:
http ://www.epa. gov/en v i ro/wme/index. h trnl
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
125
-------
CHAPTER 3: STUDENT ACTIVITIES
SHORT TERM CONCENTRATION ESTIMATES
Chemicals for the 21st Century!
ChemPure is dedicated to supplying the need for industrial standard chemicals as
well as searching for new alternatives.
Technical Information
126 CENTER FOR INNOVATION IN ENGINEERING AND SCIENCE EDUCATION AT STEVENS INSTITUTE OF TECHNOLOGY
-------
SHORT TERM CONCENTRATION ESTIMATES
CHAPTER 3: STUDENT ACTIVITIES
ChemPure Products
Carbon Tetrachloride, CCI»
Carbon tetrachloride is a clear, colorless, liquid that is used in the manufacture of
refrigerants, and in catalyst regeneration, and incinerator testing.
Chlorine, Ch
Chlorine is a greenish-yellow gas with a pungent odor. Chlorine may be fatal if
inhaled; it can cause severe burns and is corrosive to eyes, skin, and mucous
membranes. Chlorine is used for the purification of 98% of public water supplies. It
is also used to manufacture products such as refrigerants, silicones, PVC,
polyurethane ingredients, plastics, cleaning chemicals and chlorinated organic
chemicals.
Chloroform, CHCb
Chloroform is a dense, nonflammable, colorless, clear liquid that is used in the
production of pharmaceuticals and dyes and as a raw material for the production of
refrigerants.
Ethylene Bichloride, C?HiCh
Ethylene dichloride, otherwise known as EDC, is a colorless, flammable clear liquid
that is used as a raw material in the production of vinyl chloride. It is also used as a
general industrial solvent and as a fumigant insecticide.
Methyl Chloroform, CH.CCb
Methyl Chloroform is a dense, nonflammable, clear, colorless liquid that is used as a
feedstock to produce fluorocarbons and fluoropolymers. Other uses include general
purpose cold cleaning, vapor degreasing, adhesives, paint and coating formulations.
lethylene Chloride, CH2CI2
Methylene Chloride is a dense, nonflammable, colorless, clear liquid that used in
paint remover formulations, solvent vapor depressant in aerosol applications,
general cleaning solvent and as a foam blowing agent.
Specific Release Data:
• Source of chemical release
DOWNWIND: LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL 127
-------
CHAPTER 3: STUDENT ACTIVITIES
SHORT TERM CONCENTRATION ESTIMATES
o One smoke stack
o emission height = 30 m
o exit temperature = 400 Kelvin
o exit velocity = 2.3 m/s
o stack diameter 1.5 m
o emission rate = 2.6 g/s
• Factory Building 1 information
o Building height =25 m
o Building widths = 35 43 36 37 35 18 32 92 29 66 25 50 20 56 15 00 20 56
25 50 29 66 32 92 35 18 36 37 36 45
• Factory Building 2 information
o emission height = 30 m
o width of source = 10m
o emission rate = 5,2 g/s-m*m
• Factory Building 3 information
o emission height 15m (bldg ht = 30m)
o initial lateral dimension - 4.65m (20/4.3)
o initial vertical dimension - 13.95m (30/2.15)
o emission rate - 2.6 g/s
Meteorological Information
• Prevailing wind direction - Southwest
128 CENTER FOR INNOVATION IN ENGINEERING AND SCIENCE EDUCATION AT STEVENS INSTITUTE OF TECHNOLOGY
-------
CHAPTER 3: STUDENT ACTIVITIES
FINAL REPORT
Student Activity Sheet:
Final Report
Final Report
Now that you have satisfactorily completed the Downwind Project, your team needs
to prepare a final report to demonstrate your understanding of the project to your
entire class. Your teacher will provide details involving your options for
presentation approaches. You now have the opportunity to show your creativity in
demonstrating the knowledge you have gained.
Suggestions for your final student report:
• Design a web site to show what you have learned
• Write a technical report
• Develop a persuasive oral presentation
• Create a written presentation: poster, brochure
• Plan and implement a mock town meeting. (Each team will represent a
special interest group who will research and present points of view
regarding the construction of the new plants and school.)
DOWNWIND; LEARNING SCIENCE USING AN EPA CONCENTRATION MODEL
129
-------
PUBLIC HEALTH BULLETIN ISO. 306
Air Pollution
in Donora, Pa.
Epidemiology of the
Unusual Smog Episode
of October 1948
PRELIMINARY REPORT
H. II. SCliRENK
HARRY HETMAKN
GEOtfGE D. CLAYTON
W. M. GAFAFER
U. S. Public tftnllh. Scrvite
HARRY WEXLER
U. S. Weather fiunxai
•' ro j
FEDERAL .SKCtittlTY AGFNCY
Poblio Health Service
Bureau of Suiie Services
Division of Industrial Hygiene
Washington, D. C.
1949
-------
FRONTISPIECE
Artist's conception by Charles C. Shinn of the valley where the
Monongahela River runs past Donora and Webster.
Foreword iii
Origin of iv
List of Contributors v
Acknowledgements vi
/. Introduction
The Donora Area
Industries
Plan of Investigation
Biological
Engineering
Meteorological
1
2
3
3
3
3
II. Biological Studies
Introduction
Acute Episode 6
Collection of data 6
Community survey 6
The sample 6
The household visit 6
Interviews by physicians 9
Interviews of ill persons 9
Blood samples 9
The acute illness
The community experience
Donora area as a whole
Population characteristics
Incidence of smog affection
Incidence rates by sex and race 12
Incidence rates by sex and age 13
Incidence rates by occupation and age
The Acute Illness - Continued
The community experience - Continued
Donora area as a whole - Continued
Duration of symptoms 17
Symptoms present at time of survey 21
Duration of disability 21
Smog affection among persons with bronchial
Asthma, heart disease, or chronic bronchitis 21
Residence districts 23
Population characteristics 23
Webster 25
Incidence rates by residence district 25
Onset of affection 27
Frequency of symptom complexes 27
Frequency of individual symptoms 29
Summary of findings 29
Hospitalized persons 31
Case descriptions 31
Fatalities 40
Methods of study 40
General findings 40
Duration of fatal illness 41
Autopsy findings 44
Discussion of autopsy findings 45
Summary 46
Case descriptions 46
Related Studies 54
Pulmonary emphysema studies 54
Influenza studies 55
Allergy and smog illness 55
Blood spectrophotometry 55
Study of domestic animals 56
Methods 56
Results 58
Effects on dogs 58
Effects on other animals 58
Discussion 59
Conclusions 59
Conditions of housing 59
The sample 59
Method of evaluation 60
General findings 60
Housing, and affection from smog 60
Community sanitation 60
Long-Term Effects 61
Oral structures 61
Methods 61
Examination of male adults 61
SCIENCE GUIDE
Appendix A: Public Health Bulletin No. 306
-------
Oral structures - Continued
Methods - Continued
Examination of school children 61
Chemical studies 63
Fluoride effects 63
Teeth of school children 63
Fluoride content of urine 64
Fluoride content of bones 65
Acid aerosol effects 65
Conclusions 65
References 66
Morbidity and mortality 66
Morbidity: a study of sickness absenteeism 66
Collection of data 67
Analysis of results 67
Mortality 69
Source of data 69
Unusual weather periods prior to 1948 71
Deaths in Donora Borough, 1945-48 71
Death ratios 73
Deaths during the 1948 smog period 74
Discussion 75
Summary and conclusions 77
III. Atmospheric Studies
INTRODUCTION 79
INESTIGATION OF
ATMOSPHERIC CONTAMINANTS 81
Collection and determination 81
Collection of contaminants 81
Zinc plant 81
Steel plant 81
Collection methods and apparatus 81
Nonindustrial sources of contaminants 82
Sampling in general atmosphere 82
Collection methods and apparatus 82
Determination of contaminants 84
Sulfur 84
Oxides of nitrogen 84
Chloride 85
Fluoride 85
Arsenic 85
Antimony 85
Lead 85
Cadmium 85
Zinc 85
Iron 85
Manganese 86
Acid gases 86
Total particulate matter 86
Insoluble solids 86
References 86
Evaluation of plant effluents 86
Description of zinc plant operation 86
Roasters 86
Sinter plant 88
Evaluation of plant effluents - Continued
Description of zinc plant operation - Continued
Evaluation of plant effluents - Continued
Description of zinc plant operation - Continued
By product processes 89
Acid plant 89
Cadmium plant 90
Flux liquor plant 90
Description of steel plant operation 90
Blast furnace 90
Open hearth 92
Blooming and billet mills 92
Rod mills 92
Wire mills 92
Plant operation during survey 93
Zinc plant 93
Steel plant 93
Results of zinc plant survey 94
Roasters 94
Sinter plant 94
Zinc spelters 97
No. 1 waste heat boiler 99
Waelz plant 99
Zinc dross plant 99
Acid plant 99
Cadmium plant 101
Summary 103
Recommendations 103
Results of steel plant survey 103
Blast furnace and sinter plant 103
Open hearth department 106
Blooming mill 107
Wire mill 107
Nail galvanizing 107
Summary 107
Recommendations 108
Fuels used in zinc and steel plants 108
Atmospheric pollution from domestic sources, steamboats,
trains, and automobiles 109
Domestic sources 109
Furnaces 109
Fuels 109
Estimation of air pollution 110
Comment 110
Steamboats 110
Type of motive power 110
River traffic 110
Estimation of air pollution Ill
Comment Ill
Trains 111
Comment 112
Automobiles including trucks 112
Summary 112
References 112
General atmospheric pollution 113
Selection of air sampling stations (more info, bar chart).... 113
SCIENCE GUIDE
Appendix A: Public Health Bulletin No. 306
-------
Zinc spelters 88
Pottery department 89
Waelz plant 89
Station No. 1
Station No. 2
Selection of air sampling stations (more info, bar chart
Station No. 1
Station No. 2
Station No. 3
Station No. 4
Station No. 5
Station No. 6
Station No. 7
General atmospheric pollution - Continued
Selection of air sampling stations - Continued
Station No. 8 115
Station No. 9 115
Station No. 10 115
Station No. 11 115
Station No. 12 115
Discussion of results 115
Contaminants by station 116
Contaminants in relation to date periods 120
Contaminants in relation to time periods 120
Halogens, oxides of nitrogen, and miscellaneous
Constituents 121
Halogens 121
Oxides of nitrogen 121
Miscellaneous samples 121
Results obtained by Thomas Recorder 122
Particulate matter from home filters 122
Contaminants in communities adjacent to Donora 122
METEOROLOGICAL INVESTIGATION 126
Meteorological terminology 127
Distribution and instrumentation of weather stations 128
Micrometeorology of the Monongahela River Valley,
vicinity of Donora 128
General wind mechanism of valley ^ 129
Micrometeorology for special periods 130
Smoky mornings 130
Nonsmoky, calm mornings 134
Windy periods 136
The Donora smog episode of late October 1948 139
Conclusions 147
Acknowledgements 147
References 147
METEOROLOGICAL CONDITIONS AND
ATMOSPHERIC CONTAMINANTS 149
Contaminants in relation to wind direction 149
Contaminants in relation to wind speed
Contaminants in relation to temperature and
humidity
Contaminants in relation to atmospheric stability
Two stable periods compared
Onset of illness
Recommendation
49
54
54
55
55
59
IV. Discussion of Cause of Episode
SUBSTANCES STUDIED 161
Single substances 161
Fluoride 161
Chloride 161
Oxides of nitrogen 161
Hydrogen sulfide 161
Cadmium sulfide 161
Sulfur dioxide 161
Summary 162
Combination of substances 162
Summary 162
V. Summary and Recommendations
SUMMARY OF BIOLOGICAL STUDIES
163
SUMMARY OF ATMOSPHERIC STUDIES 164
RECOMMENDATIONS 165
Appendix I - Manual for use of form, history
of smog illness 167
Appendix II. - Manual for use of form,
clinical data on affected persons 169
Appendix III. - Why is October the optimum
month for smog at Donora? 171
SCIENCE GUIDE
Appendix A: Public Health Bulletin No. 306
-------
FRONTISPIECE
mN»i
1 *¦
Artist's conception by Charles C. Shinn of the valley where the Monongahela River
runs past Donora and Webster
SCIENCE GUIDE
Appendix A: Public Health Bulletin No. 306
-------
Selection of air sampling stations
Tahljs 53.—Distribution of atmospheric constituent* found at 12 air sampling stations in the Donor a area from February J
through A pril 87\ J94&, by station
Concentration range
Total
number
of
lamplei
Station number
4 : A
Total
0.00-0.00...
.20._.
0.30-0.39...
0.40-0.49-,.
0.50 or over.
Total.
0.00-0.09...
0.10-0.19.. .
0.20-0.29...
0.30-0.39...
0.40-0.49...
0.60 or over.
146
78
2 J
9
4
3
Total.
0.0-0.4
0.6-0.9
1.0-1.4
1.8-1.®
2.0-2.4
2.S or over..
Total.
0.0(K0.09...
0.10-0.19...
0.20-0.29...
0.30-0.39...
0.40-0.19...
0.60 or ov«*.
Sulfur dioxide (parts per million)
260 10 [20 81 33 | 23 26 21 20 19 ' 15
16
Totnl sulfur (parts per million)
267
21
22
\ 17
11
10
M
7
5
24
1
2
IS
1
2
ft
0
I
12
1
3
25
19
18
Total particulate matter (milligrams per cubio meter)
205
15
10
24
25
20
20
17
'
12
13
13
13
93 1 10
9
8
4
9
7
9
8
8
8
9
M
3
7
10
ft
6
11
4
2
3
8
4
21
1
1
1
e
4
2
3
I
1
1
0
9
0
0
2
3
1
0
0
1
1
0
0
7
0
1
1
a
0
0
1
0
0
1
0
8
1
1
2
8
0
0
0
0
0
0
0
Zlne (mJlltgranui per cubio meter)
12
0+
1
0
0
M
n
205
U
l
10;
24
26
20
20
17
12
13
13
13
175
15
17 !
1#
12
13
19
17
12
12
13
13
13
0
0 i
3
6
8
1
0
0
I
O
0
r.
0
1
1
1
2
0
0
0
0
0
0
6
0
o
i
2
0
0
0
0
0
0
0
8
0
1
}
1
D
0
0
0
0
o
0
4
0
0
0
4
°
0
0
0
0
0
°i
116
SCIENCE GUIDE
Appendix A: Public Health Bulletin No. 306
-------
Selection of air sampling stations
f^uLE 53.—Distribution of atmcspkeria constitxie-nts found at IS air sampling Motion* hi the Donora area from¦ F*bruar\-
throwjh April27,19.'$) ly station—Continued
Concentration range
Total ;
Dumber •
of
samples j ;
Station number
s \ a
4 ¦ 5 | fl
i !
7
&
9
10
ii i
• i
Lead (milligrams per cubio meter)
Total..
oooo-oooo..
0.01&-O.OW —
0.020-0.02y._
0.030 or over.
205 :
15
19 :
24
25
20
20
1S6 | 15 17 | 19
14 I 0 ! 1 i 4
2 I 0 i 0 ; 0
S ' 0 1 I 1
IS 19
1 1
1 0
0 Q
17
12
13
13
13
0
0 !
0 i
Cadmium (milligrams per cubic meter)
Total
! 205
It |
ID
24
t
25 j
SO
20
17
»
13
13
13 j i.
0,0000-0.0009
is i
12
16
7 !
10
13
14
12
12
11
13
O.OOtO-O.OttlS
0 1
2
1
3 ;
3
3
2
0
0
1
0 |
0.0020-0.0029
0 !
2
2
0 !
3
3
1
u
1
0
0
O.Q030-0.0039
J 8
0 i
2
2
2 :
1
1
0
Q
0
0
0 :
0.0040-0.0049...
0 i
U
0
1 j
0
0
0
0
0
0
0 ¦
0.0050 or over -
20
o ;
1
3
12
3
0
0
0
0
1
0 :
gram per cubic meter. The three highest lead samples were
0.0303,0.03X1, and 0.0337, and the four highest zinc samples
were 0.52, 0.56, 0.84, wid 0.07 milligram per cubic meter.
Cadmium concentrations were very low. The three highest
Talues were 0.0163, 0.0164, and 0.01T8 milligram per cubic
meter of air.
The station to station distribution of concentrations of
the various constituents showed variations in pattern which
may be roughly correlated with sources of contaminants.
Sulfur dioxide showed the most even distribution of the con*
laininar.ts among the 12 stations. This even distribution may
be explained hv the large number ami wide distribution of
sources of sulfur dioxide.
Total sulfur showed a greater concentration near the zinc
plant than did sulfur dioxide. No satisfactory explanation
of this observation is available from the data obtained.
Total particulate matter showed even distribution except
for Stations N'o. 3 and 4. The even distribution may be
"plained by the large number and wide distribution of
sources. The high values at Stations No. 3 and 4 may have
teen influenced by nearness to the line plant
Zinc and lead had a very limited distribution for values
above the lowest frequency range. The highest values were
found near the zinc plant on either side of the river and at
relatively low elevations. Ho values for lead or zinc abov4
the lowest frequency range were found at stations 1, 7, S, 10,
11, and 12. Cadmium wis somewhat more widely distributed
by station and showed a special concentration of higher
values just across the river from the zinc, plant. The high
value for cadmium at. Station No. 10 was yielded by a sample
^Hected during a temperature inversion. Figure 61 shows
the average cor.cuctratiou of zinc, lead, and cadmium for each
stntion arranged in descending order. Stations No. 4,1),
and 2, which are closest to the zinc plant, have the greater
amounts of zinc, lend, and cadmium. Stations No. 10, 7. 1.
12,8, and 11, which are located at the greatest distance from
the zinc plant, show the smallest amount of contamination.
Table M shows the stations ranked in decreasing order in
accordance with average ratios for the si* contaminants. In
establishing the ratios the highest average concentration was
taien as a base and the ratio of the average concentration for
a particular contaminant for each station was calculated on
the basis of 100 assigned to the highest concentration.
Station No. 4 shows a value of 100 since the highest average
concentration was found for all six constituents at this station.
Stations 8, 5, 10, 2, and 12 follow in order. Station No. 11
showed the lowest ratio.
Tablk a,-—Sampling stations ranked on the basis of 1'JO
chosen to represent the highest average concentration of
eatsh constituent
Statlou
No.
Rank:
Average
ratio for
6 con-
tami-
nants
Sulfur
dioxide
Total
lul/ur
Total
partic-
ulate
matter
Zino
Lead
Codtci-
ticn
4
100.0
100. 0
100.0
100. 0
100.0
100. 0
100. 1)
3
64. 1
80. 0
79. 2
75. 5
50. 4
G8. 2
25. 1
5
64.0
77.5
sa 4
45. 3
37.0
55. 7
30. G
10
44.2
300.0
58. 3
42. 0
6. i
36. 4
22. U
2
43. 4
£0.0
70. 8
50. 0
23. 4
42. 1
23. 3
13
42. 2
93.0
83.4
46. 5
2. 8
23. 8
o. J.
6__
3ft. 8
71.8
41.7
45. 0
13.3
44 4
17. 0
7
36.0
77.5
45. 8
44. 5
0.2
3fi. 2
0. -S
0
34. 4
77.5
54. 2
88. &
0.2
23. 8
3.4
1
33.3
89. 0
54. 2
37. 8
3. 4
17. 0
i.:
8
24. 1
67.0
21>. 2
31 2
1. 6
)
-------
Bar Chart
illicit
t-trr
0.220
0.210--
0.200 - -
0.190-•
0.160
0.070
0
4 3 5 2 6 9 10 7 I 12 6 II
STATION NUMBER
0.180 -¦
0.170- ¦
0.150 ¦'
0.060
0.050
0.040
0.030
OjDZO
0.010
Fiohxk 61.—Average concentration* oj cadmium, Uad, and tine by utation, arranged in descending order oj totals.
in
B
Z
O
§
-------
Contaminants by station
Figobjc 61.—Average concentration* oj cadmium, lead, and tine by Italian, arranged in descending order of totaU.
%
2
O
§
ac
UJ
O
z
o
o
0-220
0.210
0.200
0.130
0.180
0.170
0.160
0.15 0
0.140
0.130
0.120
0.110
0.100
0090
ojoeo
0.070
0.060
0.060
0.040
0.030
0.020
0.010
0
I I CADMIUM
> I LEAD
¦¦ ZINC
5 a 6 9 10 7
STATION NUMBER
118
SCIENCE GUIDE
Appendix A: Public Health Bulletin No. 306
-------
Conclusions
As already mentioned, the Donora occurrence of 1948 was
not a unique one. A sequence of meteorological,ciicuraatancea
during; the period October 4-14,1923, had also brought about
serious smog conditions in the vicinity of Donora. The
synoptic situation was quite similar to that of October 1948.
Following passage of a cold front, a large polar anticyclone
moved into the area surrounding southwestern Pennsylvania,
stagnated for many days, and was finally displaced by a
frontal system from the west. There is a report of yet another
serious smog period at Donora during the period October
7-18,1038. Again a stagnating polar anticyclone dominated
Che weather maps. In this case, however, there were two
such anticyclones—one persisting from the 9th through the
12th and the other from the 14th through the 18th. Frontal
passages occurred on the 6th, 8th, 13th, and 19th. On the
7th a rapidly moving polar anticyclone, passing over the
northeastern portion of the United States, caused one pre-
liminary day of the weak winds and low-level stability which
seams to be requisite to intense pollution concentrations near
the ground.
CONCLUSIONS
This report has presented the results of a micrometeoro-
logical investigation of the Monongahela Biver Valley in the
vicinity of Donora, Pa., and a description of the meteorologi-
cal conditions during the Donora smog episode of October
1948. From these findings the following conclusions may be
drawn:
A. Micrometeorology of the valley for the period Febru-
ary 14, to April 28,1949:
1. Smoky periods were caused by the occurrence of strong
atmospheric stability and stagnation of the air in the valley
as well w some thousands of feet above the valley.
2. Anticyclones of polar origin often-accompanied these
conditions, of strong stability and calm or light winds through
& great depth of the atmosphere.
3. Stagnation alone did sot cause an accumulation of
¦moke in the valley as was demonstrated by nonsnoky peri-
ods with light to calm winds. These periods occurred when
fresh, unstable polar air, behind a vigorously moving cold
front, lay over tike area.
4. Stability alone did not cause an accumulation of smoke.
Daring windy periods with stable atmospheric conditions
above the hilltop level, smoke was carried out of the valley.
5. Midvalley height stations on the east side of the valley
all indicated flow parallel to the valley orientation at times
of very stable conditions when the drainage current was deep
enough to reach them, and down slope flow at other times
when the main valley drainage current waa more shallow and
only the valley-side drainage flow affected the stations.
6. During periods of very stable conditions the main valley
drainage current in the lower portion of the valley came from
down river.
7. Due to the turbulence of gravity currents operating all
light on very stable nights, smoke, as determined by morning
visual observations, apparently was evenly distributed
throughout the valley longitudinally, laterally, and verti-
cally.
8. During moderate to strong winds, turning effects within
the valley were imposed upon the hill top wind direction;
wind speeds in the valley along the valley sides were de-
creased in proportion to the depth in the valley and were
lower on the lee side than the windward side. The decrease
of speed with depth along the valley sides was greater for
cross valley flow than for flow parallel to the valley.
B. Meteorology of the smog episode of October 25-31,
1948:
L The Donora smog episode of October 25-81, 1948, was
an extreme case of the "smoky morning" type described in
this paper.
2. Willett (It), in examining weather records for the past
80 years, has shown that occurrences of meteorological con-
ditions similar to those at Donora in late October 1948, may
be expected on the average once in every 10 or 15 years with
no guarantee that they would not occur in consecutive years
or months or twice in the same month. Other notable stag-
nant meteorological periods occurred in October 5-13,1923,
and October 7-18,1938.
3. Dense fog in the valley persisted past midday for four
conseoutive days, which maintained a high albedo during
the period, and prevented heating of the valley floor.
4. Wind speeds remained less than 7 miles per hour from
the surface to 6,000 feet for a period of three consecutive
days, showing that the atmosphere lacked the ability to
remove contaminants rapidly.
5. Four-day presence of maximum temperatures at
Donora below those at the Pittsburgh airport shows the
persistence of extreme valley stability for four consecutive
days.
6. An extensive high pressure area covered the eastern
United States and persisted over the Appalachian region.
C. General requirements for recurrence of smog conditions:
1. Pollution—Sources must be near and active.
2. Topography—Terrain favorable for the low-level trap-
ping of air indicates potentially dangerous areas.
3. Humidity—Moisture in the lowest layers should be such
that fogs can form and persist and so reflect the sunlight
which might otherwise destroy the inversion.
4. Meteorological Model (16)—A polar anticyclone rein-
forced by upper air anticyclogenesis appears to be the mete-
orological model most likely to produce the stagnant condi-
tions required for the great pollution concentrations.
6. Season—October appears to be the month with the
highest probability of occurrences of intense atmospheric
stability and stagnation in the area of Donora. (See
Appendix HI.)
ACKNOWLEDGMENTS
The writer dwiru to expreaa hla appreciation to all thoae who give
aulitann la tha preparation of this report. Special credit toes to
Dr. Bare? Waaler and Dr. Robert D. Fletcher for their valuable
technical advice; to Ur. I. IB. Caekey, Jr., who performed the major
portion of the editorial work; and to Mr. Hired D. Whit* who expedited
the adntslattaUve problems necessarily accompanying the prepara-
tion of such a report. A]] are with the United States Weather
Bureau.
Xo Ur. Raymond a Wanta, Halted 8tates Weather Bureau
meteondoflatr pea credit for preliminary technical advice In locating
the mlcnuneteoroloflcal nations. To Uemra. John Mayer, Weather
Bureau Impaction section, and Maurice Orris, lmtrumerrt technician,
toe* credit for the erection, operation, and maintenance of the eleven
Weather Bureau station
147
SCIENCE GUIDE
Appendix A: Public Health Bulletin No. 306
-------
V. Summary and Recommendations
Summary of Biological Studies
1. During the smog of October 1048 a total of 5,910 per-
sons, or 42.7 percent of all persons in the Donora area, were
affected to some degree by the smog.
2. The affection was essentially an irritation of the respira-
tory tract and other exposed mucous membranes, and varied
in degree from mild to severe. Cough was the predominant
single symptom during the illness.
3. Classified as to degree of affection, 2,148 persons, or lfi.5
percent of the total population in the area, were mildly
affected; 2,322 persons or 16.8 percent were moderately af-
fected, and 1,440 persons or 10.4 percent were severely af-
fected by the smog.
4. Neither incidence nor severity of affection appeared to
be influenced by sex, race, occupational status, length of resi-
dence in the area, or degree of physical activity at time of
onset of affection.
5. Both incidence and severity revealed a direct relation-
ship with increasing age. Over 60 percent of persons 6S
years of age and over reported some affection from the smog,
and almost one-half of these were in the severely affected
group.
6. The population of Webster reported a higher inci-
dence of affection of each degree than in the area as a whole.
Age-specific rates for Webster revealed an age pattern similar
to the corresponding area pattern, but at a higher level.
7. Although onset of affection began in some cases as early
as S-day (the first day of severe smog), the larger number of
persons became ill on day No. 2 (the second day after S-day).
About 40 percent of affected persons reported onset of affec-
tion between 6 p. m. and midnight of day No. 2.
8. Twenty persons died in the Donora area during or
shortly after the smog of October 1948; 17 died on day No. 3.
9. Based on data available for 18 of the persons who died,
the death rate was significantly higher in the nonwhite than
in the white population, and was significantly higher for
Webster than for the area as a whole.
10. The ages of the persons who died ranged from 62 to
84 years with a mean of 65 years.
11. Principal past employment,, duration of residence In
the community, and mx played no significant part in the
occurrence of the fatal illnesses.
12. Only in the degree of severity and in the outcome were
the fatal cases different clinically from the severely ill per-
sons who did not die.
13. Preexisting disease of the cardiorespiratory system ap-
peared as a single significant factor among the fatally ill,
although in four cases, no history of any chronic disease prior
to the smog was obtained.
14. In spite of the apparent association, between cardio-
respiratory disease and smog affection, no significant differ-
ence appeared in the occurrence of pulmonary emphysema in
a group of persons who had heen ill during the smog, and in a
nonaffected group.
15. Epidemic influenza did not play a part in the illnesses
which occurred during the smog.
16. Some relationship appeared between severity ol affec-
tion and certain characteristics of housing quality.
17. In addition to the persons who became ill during the
smog, domestic animala also became ill, and some died.
These illnesses resembled those observed in the human in
that there was evidence of irritation of exposed mucous mem-
branes of the respiratory tract.
18. Studies for dental caries, dental fluorosis, urinary ex-
cretion ol fluoride, and fluoride content of bone, revealed no
evidence that there was excessive inhalation or ingestion of
fluoride in the community.
19. With the exception of such episodes as that of the Oc-
tober 1948 smog, long-term studies of mortality records and
plant morbidity records indicate that the health of the people
of Donora appeared essentially no different from that of
nearby towns.
20. Although bronchial asthma and heart disease appeared
to be somewhat more prevalent among persons in the Donora
area than in the United States as a whole, studies of mortality
data, when compared with those of nearby communities, indi-
cated that death due to disease of the heart and respiratory
system waa not increased in Donora.
21. Mortality records showed that crises have occurred in
Donora creating, occasionally, higher death rates due to
cardiovascular disease. These crises are probably related
to atmospheric conditions.
22. Among the autopsies performed there were three of
persons who died during the smog and these showed acute
change in the lungs characterized by capillary dilatation,
haemorrhage, oedema, purulent bronchitis and bronchiolitis.
23. Chronic cardiovascular disease, the origin of which
antedated the smog incident, was a prominent feature in the
autopsies.
163
SCIENCE GUIDE
Appendix A: Public Health Bulletin No. 306
-------
Summary of Atmospheric Studies
1. The zinc .spelters are major contributors to the atmos-
pheric pollution load with special referents to particulate
matter and carbon monoxide.
2. The amount of contaminants discharged from the zino
spelters during the "test period" wag approximately twice
that which occurred during the "curtailed production"
period.
8. The line plant waste heat boiler stacks are major con-
tributors of atmospheric pollution with special reference to
particulate matter and sulfur dioxide.
4. The zinc plant sintering operation is a major contribu-
tor to the atmospheric pollution load with particular refer-
ence to sulfur dioxide.
5. The acid plant is the main source of discharge of oxides
of nitrogen into the atmosphere.
6. The contribution of the zinc ore roosters, Waelz plant,
zinc dross and cadmium plants to the general atmospheric
pollution load of the voile; is not considered significant
7. The blast furnace department, including the sinter
plant, is a major contributor to the general atmospheric pol-
lution load with special reference to particulate matter and
carbon monoxide.
8. The open hearth furnace stacks are significant con-
tributors of particulate matter to the atmospheric pollution
load.
9. The blooming mill and wire mill, including nail gal-
vanizing, are not considered important contributors to the
general atmospheric pollution of the valley.
10. The blooming mill and steel mill boiler Btaclra are major
sources of sulfur dioxide.
11. Domestic heating systems and local steam locomotives
are significant contributors to the general atmospheric pollu-
tion of the valley with speoial reference to carbon monoxide,
sulfur dioxide, and particulate matter.
13. The distribution of concentrations in the general at-
mosphere of sulfur dioxide, total particulate matter, zinc,
lead, and cadmium showed variations which may be roughly
correlated with sources of contaminants.
13. Sulfur dioxide showed the moat even distribution, in-
dicating the wide distribution of sources of sulfur dioxide.
14. Total particulate matter showed sven distribution with
the exception of the areas closest to the line plant, which wen
higher than the others.
15. Concentrations of zinc, lead, and cadmium were hi k
est in the vicinity of the zinc plant "
10. Air-sampling Station No. 4 (representing an, am ^
Webster directly across the river from the zinc speltersl
showed higher concentrations for all contaminants than thl
other stations.
17. Concentrations of various contaminants when consid-
ered by time of the day indicated that the greater air sta-
bility at night and fluctuation in plant operations influenced
concentrations found.
18. Low concentrations of chloride, fluoride, and oxides of
nitrogen were found in the general atmosphere.
19. Samples of particulate matter obtained from home
filters in Conor* and a home filter in Monessen showed no
significant difference in the composition of the samples with
the exception of sulfur. A. higher concentration of sulfur
was found in the particulate matter collected during the
smog period than in samples obtained from filters in opera-
tion after the smog.
20. A combination of a high degree of atmospheric sta-
bility and stagnation was found to be necessary and sufficient
to cause an accumulation of airborne pollutants in the valley
at Donora.
21. Local micro-turbulences within the valley at night
appeared to distribute the particulate matter evenly th rough-
out the valley as determined by morning visual observations.
22. Wind speeds during windy periods within the valley
were lower than those at hill top with the decrease being
greater for cross-valley flow than for parallel-to-valley flow.
B8. Similarity of average concentrations at all stations for
various wind directions for sulfur dioxide, total sulfur, and
total particulate matter showed multiple sources of these
contaminants while definite high concentrations of zinc and
cadmium ware found only downwind from the zinc plant
(except for variable, low speed wind periods), indicating a
single source for thoee elements,
24. In general a greater percentage of higher concentra-
tions was found is the wind speed range of 0-3 inph and the
next highest in the 10-22 mph range; lowest values being
found in the 4r-8 mph range.
95. lbs concentration of contaminants showed no signifi-
cant relationship to relative humidity or temperature.
SB. A definite relationship was found to exist between the
concentration of contaminants and atmospheric stability.
SCIENCE GUIDE
Appendix A: Public Health Bulletin No. 306
-------
Recommendations
1. Reduce the gaseous contaminants
especially sulfur dioxide and
particulate matter discharged from
the sinter plan Cottrell stacks.
2. Reduce the particulate matter and
carbon monoxide from the zinc
spelters.
3. Reduce the particulate matter and
sulfur dioxide discharged from the
waste heat boiler stacks.
4. Reduce the discharge of oxides of
nitrogen and acid mists from the
Gay-Lussac stacks.
5. Reduce the amount of particulate
matter and carbon monoxide from
the waste blast furnace gas.
6. Reduce the amount of carbon
monoxide discharged from the stove
and sinter stacks.
7. Reduce the amount of particulate
matter discharged from the sinter
plant and open hearth stacks.
8. Reduce the amount of particulate
matter discharged from the waste
heat and blast furnace boilers and the
sulfur dioxide from the waste heat,
stell and wire plant boilers.
9. Reduce the amount of particulate
matter discharged from domestic
heating systems, steam locomotives
and steamboats.
10. Establish a program of weather
forecasts to alert the community of
impending adverse conditions so that
adequate measures can be taken to
protect the populace.
SCIENCE GUIDE
Appendix A: Public Health Bulletin No. 306
------- |