United States EPA-600/9-82-003
Environmental Protection May 1982
Agency
Research and Development
Estimating
Microorganism :
Densities in
Aerosols from Spray
Irrigation of Wastewater
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Research and Development EPA-600/9-82-003
Estimating Microorganism
Densities in Aerosols from
Spray Irrigation of Wastewater
I'.S. Fr»hv:;rnen^! ruction Aconcy
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; ' ;-'- :_ ;..:4, 12th Floor
This report was developed under contract by Life Systems, Inc. and JACA Corp. in cooperation with the
Wastewater Research Program, Health Effects Research Laboratory for the Office of Research and
Development.
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CONTENTS
Introduction
Prior Studies 4
Progression of Prior Research 4
Monitoring Studies 4
The Model 8
Atmospheric Diffusion Model 8
Microbiological Dispersion Model 10
Estimating Specific Model Components 11
Site-Specific Model Inputs 11
Nonsite-Specific Model Inputs 15
Estimating Procedure 19
Model Prediction Examples 22
User Considerations 26
Perspective 27
Glossary 28
Bibliography 31
in
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ACKNOWLEDGMENTS
This project was sponsored by the Center for Environ-
mental Research Information (CERI), Cincinnati, OH,
and was directed by Herbert R. Pahren; Douglas
Williams was the Project Officer. The report was
written by John P. Glennon, Life Systems, Inc.,
Cleveland, Ohio.
The initial technical draft of this report was prepared
by David E. Camann and Donald E. Johnson, South-
west Research Institute, San Antonio, TX, with assist-
ance from Charles A. Sorber, University of Texas at
Austin, and John P. Glennon. Southwest Research
Institute performed the majority of the recent field
monitoring and model development efforts summa-
rized in this report. Technical reviewers were Charles
A. Sorber and Hiram Wolochow, Naval Biosciences
Laboratory, Oakland, CA, and Richard Thomas and
Herbert Pahren, USEPA. Photographs in the text
were provided by David E. Camann and Stephen A.
Schaub, U.S. Army Medical Bioengineering Re-
search and Development Laboratory, Frederick, MD.
Comments regarding this report should be ad-
dressed to:
Mr. Herbert R. Pahren
Office of Research and Development
U.S. Environmental Protection Agency
Cincinnati, OH 45268
Single copies of this report are available from:
Center for Environmental Research
Information
U.S. Environmental Protection Agency
Cincinnati, OH 45268
This report has been reviewed by the Health Effects
Research Laboratory, U.S. Environmental Protection
Agency, Cincinnati, OH, and approved for publica-
tion. Approval does not signify that the contents
necessarily reflect the views and policies of the U.S.
Environmental Protection Agency, nor does mention
of trade names or commercial products constitute
endorsement or recommendation for use.
IV
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INTRODUCTION
This document summarizes current knowledge about
estimating the density of microorganisms in the air
near wastewater management facilities, with em-
phasis on spray irrigation sites. One technique for
modeling microorganism density in air is provided.
Such information can be of use to individuals in-
volved in decision making on public health issues
associated with the siting, design, construction, and
operation of wastewater management facilities. Po-
tential users of this document include municipal offi-
cials, public health and medical professionals, waste-
water facility operators, and consulting engineers. Of
particular importance to these users is the aerosol
density estimating procedure presented here for
evaluating wastewater spray irrigation systems. This
procedure permits the user to develop estimates of
the density of microorganisms in air with a minimum
of on-site measurements.
The predictive model described in this document pro-
vides a mechanism for developing order of magni-
tude estimates of microorganism aerosol densities
from sources of unchlorinated or slightly chlorinated
wastewater. Depending on the precision required in
applications of the model, estimates can be made for
distances up to 1000 meters from the aerosol source.
This model may provide reasonable estimates of
human exposure for use during current and future
epidemiological studies at wastewater spray irriga-
tion sites. Use of model estimates should also be
valuable in making judgments as to the relative
human health effect associated with alternative
wastewater treatment facility designs and/or loca-
tions. Although data on the dose-response relation-
ships (to cause human infection) are not available,
estimates of microorganism densities in air can be
utilized to select alternatives that represent the least
human exposure, i.e., mode of land application, site
configuration, and location, etc.
Persons who are experienced in atmospheric disper-
sion modeling will readily see that a number of sim-
plifying assumptions have been made so that all
aerosol density estimates can be performed using a
standard scientific calculator. This was done to keep
the estimating procedure as simple as possible with-
out causing an unacceptable degree of inaccuracy.
Improved accuracy can be achieved by using more
sophisticated atmospheric dispersion modeling tech-
niques, but will generally necessitate supplemental
professional assistance to select the model appro-
priate for the situation and to perform the more com-
plex calculations. Regardless of the amount of mathe-
matical sophistication used, however, aerosol micro-
organism density estimates should be considered
best estimates or first approximations, not infallible
predictions. There are a number of microorganism-
unique and site-specific factors that are still poorly
understood and introduce uncertainty into all aerosol
density estimates.
Need for the predictive model described in this docu-
ment is based on concerns that human pathogens
contained in wastewater aerosols (sprays and mists)
may represent an infection risk to individuals down-
wind from wastewater management facilities. More
than a century has passed since John Snow asso-
ciated the disease cholera with the use of water from
the Broad Street Pump in London, England. In 1884
Robert Koch demonstrated the causal relationship be-
tween a specific microorganism and this disease.
Studies in the field of aerosol physics long ago estab-
lished that mechanical agitation of a liquid (in this
case, wastewater) generates sprays and mists.
Through evaporation these mists become smaller
droplets or particles containing the dissolved or sus-
pended material contained within the original drop-
lets. Those particles remain suspended in the atmo-
sphere for considerable periods of time. For example,
a particle (or droplet) of 20 Mm will fall at about 1.3
cm/sec, and will travel about 1.3 km if generated at a
height of 3 m into a 20 km/hr (5.6 m/sec) wind. Of
particular relevance to users of this document is the
survival time of aerosolized microorganisms. Labora-
tory and field studies have shown that the atmo-
sphere is a harsh environment for the survival of
microorganisms. Yet many microorganisms can sur-
vive (reproduce when placed back into a suitable
growth medium) and, if pathogenic, retain the ability
to initiate human infection following aerosolization.
Although relatively crude evaluations of wastewater
aerosols, which largely dismissed the potential hu-
man health effect, were made during the 1930s,
accumulated information now suggests that there
are limits to which humans should be exposed to
aerosols emanating from wastewater management
facilities. Figure 1 identifies a number of factors that
1
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Federal Water Pollution Control Act
and Amendments-Clean Water Act
Urban Sprawl/Encroachment
Near Wastewater Treatment
Facilities
Advancements in
Microbiology &
Aerobiology
Construction of Large/
Regional Wastewater
Treatment Facilities
Increased Application
of Wastewater
Irrigation
Increased Number and Source Strength of Waste-
water Aerosols
« Increased Size and Duration of Population
Exposure
Improved Definition of Infectious Disease Epide-
miologyEspecially for Viruses
» Improved Technology to Sample Viable Micro-
biological Aerosols
Figure 1. Basis for Recent Research Emphasis on Wastewater Aerosols
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Table 1. Factors that Have Prevented a Conclusive Definition of Human Health Hazard
Factor
Explanation
Many Common Diseases with Similar Symptoms
Common Disease Organisms
Variable Types and Densities of Microorganism
in Wastewater (Daily/Seasonal)
Induced Immunity
Population Size
Sensitivity of Monitoring Methods
Dose-Response Relationship
Human infection must be clinically confirmed to identify disease organism
Many cases of human disease are unreported
Organisms not unique to wastewater
Wastewater aerosols not the only transmission route for infection
Difficult to distinguish aerosol-induced infections from other sources
Pathogenic microorganisms in wastewater will be a function of enteric
disease in the population served by the wastewater treatment facility
Potential that persons routinely exposed to low aerosol levels will be at
reduced risk as a result of formation of specific pathogen antibodies (health
benefit, not hazard)
Extremely large populations may be required to distinguish between aerosol-
induced and other source-induced infections
Populations relatively small in vicinity of wastewater management facilities
Available aerosol sampling technology has insufficient sensitivity to monitor
low-level, potentially hazardous aerosol densities
Minimum microorganism aerosol densities that will initiate infection (espe-
cially by inhalation) are unknown for most pathogens
have led to renewed interest in evaluating waste-
water aerosols. These factors include larger popula-
tion densities and growing numbers of wastewater
aerosol sources, both of which increase the numbers
of individuals exposed. In addition, advances in the
ability to measure microbiological aerosols (aero-
biology), spray irrigation technology and hardware,
and the epidemiology of infectious diseases (espe-
cially viruses) have contributed to this recent re-
search emphasis.
Researchers have not detected any significant in-
crease in the incidence of human disease attribut-
able to microbiological aerosols from wastewater
treatment or spray irrigation facilities, as they are de-
signed and operated in the United States. These
studies, however, are considered inconclusive by
many who believe the potential for a significant hu-
man health effect still exists. Table 1 provides a
listing of some of the factors that have hampered a
conclusive evaluation. Particularly lacking are con-
clusive definitions of the dose-response relation-
ships for the many pathogenic microorganisms found
in wastewater. Technology to estimate the density of
pathogenic microorganisms in aerosols (estimate
human exposure) is prerequisite to defining the dose
required to initiate human infections. Research studies
have now progressed to the stage where reasonable
estimates of microorganism densities in air can be made
and compared to observed human infection rates. This
represents a major step toward a better under-
standing of this hypothesized human health effect.
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PRIOR STUDIES
Progression of Prior Research
A principal focus of prior microbiological aerosol re-
search studies has been to define the dose portion of
the dose-response relationship required to initiate
human infections. The general progression of studies
in this area is shown in Figure 2. A tremendous vol-
ume of literature has been published on the concen-
tration and fate/survival of pathogens in waste-
water. In addition, researchers have evaluated the
survival of pathogens in specific wastewater treat-
ment processes. This combined body of knowledge
provides the principal basisforthe disinfection that is
commonly required before wastewater can be dis-
charged to surface waters. Research studies of
wastewater aerosols initially evaluated the aerosol
formation/generation processes. Specific studies
were undertaken to examine the degree to which
spray irrigation machinery generates aerosols that
will travel downwind from wastewater sources. These
efforts were followed by evaluations of the atmo-
spheric diffusion and dilution processes that are
common to all airborne pollutants (particles and
gases) and laboratory evaluations of the survival
characteristics of specific microorganisms suspended
in the atmosphere. The results of these studies were
used to develop initial hypotheses of the densities of
viable, infectious microorganism aerosols in the
vicinity of wastewater treatment facilities, including
spray irrigation sites.
More recent field monitoring studies of microbio-
logical wastewater aerosols have been undertaken to
validate and refine these initial aerosol density hy-
potheses. These, in turn, have led to the development
of a predictive model that permits estimations of
microorganism densities in air within several hun-
dred meters of the source without extensive field
monitoring. These two recent research areas deserve
specific emphasis, and their results provide the basis
for this document.
Monitoring Studies
Most of the information for the model described in
this document was obtained during an extensive
aerosol monitoring program performed at a waste-
water spray irrigation site in Pleasanton, CA. Munici-
pal wastewater at that site undergoes biological
treatment, is lightly chlorinated (primarily for odor
control) and is sprayed year-round onto grasslands.
Additional aerosol monitoring data were collected
from field studies at two other spray irrigation sites:
Fort Huachuca, AZ and Deer Creek Lake, OH. Chlori-
nated, secondarily treated municipal wastewater is
used at Fort Huachuca to irrigate a golf course.
Wastewater from the recreational area at Deer Creek
Lake is treated in aerated ponds, chlorinated, and
then sprayed onto a 6-acre test site. Other sources of
data for this document were monitoring studies of
microbiological aerosols in the vicinity of two acti-
vated sludge wastewater treatment plants: the Egan
Plant, Schaumburg, ILandthe Durham Plant,Tigard,
OR.
These aerosol monitoring efforts emphasized ob-
taining data for the prevalent indicator microorga-
nisms, such as total aerobic and facultative bacteria
(as determined by Standard Plate Count) and total
and fecal conforms. At the Pleasanton spray irriga-
tion site and the two wastewater treatment plants,
microbiological aerosol sampling and analyses were
also conducted for specific fecal and pathogenic
microorganisms. Some representative aerosol den-
sity data from those prior studies are provided in
Table 2. These data are presented for purposes of
illustration only and do not necessarily reflect aerosol
densities that can be expected at other locations of
interest to the user of this document. In addition, this
table does not reflect the tremendous variability (one
to two orders of magnitude) in the individual values
that make up the calculated geometric means. There-
fore, caution in the use of these values is strongly
emphasized. Individuals interested in details are
urged to refer to the original reports for these studies,
which are listed in the Bibliography.
Microbiological aerosol monitoring efforts represent
a significant investment of resources in terms of
time, people, and money. For example, the field
studies conducted at Pleasanton required an expend-
iture of over one half million dollars. In spite of
expenditures of this magnitude, the results still
suffer from significant limitations. Some of these
limitations are due to the high variability in the
general environment (changing wind conditions, var-
iability in the quality of wastewater, etc.). Such varia-
bility necessitates much replicate sampling in order
to obtain statistically reliable aerosol density values.
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** t
*4Ll
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Table 2. Microorganism Densities in Air at Several Wastewater Treatment Facilities
Geometric Mean Microorganisms/Cubic Meter"
Spray Irrigation
Microorganism
"Standard Plate Count"
Total Cohform
Fecal Coliform
Coliphaged
Fecal Streptococci
Pseudomonas
Mycobacteria
Enterovirus"
3-day assay8
5-day assay*
Distance
Downwind
Upwind
10-30 m
31-80 m
81-200 m
Upwind
10-30 m
31-80 m
81-200 m
Upwind
10-30 m
31-80 m
81-200 m
Upwind
10-30 m
31 -80m
81 -200m
Upwind
10-30 m
31 -80m
81-200 m
Upwind
10-30 m
31-80 m
81-200 m
Upwind
10-30 m
31-80 m
81 -200m
30-50 m
30-50 m
Pleasanton
970
5400
1390
880
0.2
11.5
50
1.5
0.04
2.1
1.0
0.5
0.02
0.7
0.8
0.4
0.5
3.0
1 3
0.9
6
170
100
55
0.4
ND
36
1.6
0.004
0.029
Fort Huachuca
41
800
570
130
1.3
6.1
0.7
0.4
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
Deer Creek
Lake
89
500
440
140
0.7
2.2
4.8
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
Aeration Basin
Egan Plant
4400
29000
9000
7100
1.3
12.4
6.9
3.2
0.2
0.7
0.5
0.3
002
0.08
0.04
<0.04
<2
<2
15
<2
<4
50
<4
4
ND
ND
ND
ND
<0.02
<0.02
Durham Plant
ND*>
ND
ND
ND
<0.02C
14.1
8.2
1.9
ND
ND
ND
ND
<0.04
2.3
1.1
06
0.06
5.0
2.7
1 5
<4
70
23
4
<002
28
15
5
<0.002
<0.002
^Colony-forming units (cfu) per m3 for bacteria, plaque-forming units (pfu) per m3 for viruses
ND = No data availablesampling and analysts not performed for thts microorganism
< = None detected in any samples, yielding the stated cumulative detection limit
Virus
>
Virus
Presumed polio virus
Presumed polio plus other viruses
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Other limitations are associated with the cost, conve-
nience, and available technology for microorganism
aerosol sampling. Many field aerosol samplers can-
not be used for the collection of viable microorga-
nisms. Those field samplers that do collect aerosols
in an aqueous medium often lack the required sensi-
tivity (high air flow rate/long sampling time) to pro-
vide statistically significant results. This is particu-
larly a problem when one attempts to sample for
specific pathogens (especially viruses) that occur at
relatively low densities in the wastewater. The result
of these difficulties is an overall limitation that pre-
vents field monitoring from providing reliable esti-
mates of microorganism densities in air at distances
more than 100 to 200 meters from the source. This
limitation has led to the conclusion that mathe-
matical modeling is the most practical means of esti-
mating microorganism densities in air at more dis-
tant downwind locations, where the significant ex-
posed populations are likely to be.
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THE MODEL
The need for a predictive model was recognized prior
to the extensive aerosol monitoring effort conducted
at Pleasanton. Therefore, that program was specifi-
cally designed to develop, refine, and verify such a
model. The remaining portion of this document de-
scribes, in some detail, the results of that effort. In-
cluded are stepwise instructions whereby the user,
through the collection of a limited amount of site-
specific information, can make rough estimates of
aerosol densities to distances up to 1000 meters
downwind from wastewater spray irrigation sites
without having to conduct aerosol monitoring studies.
This stepwise procedure is, however, applicable only
to wastewater spray irrigation sites. Potentially, the
model could be refined to provide a user-oriented
estimating procedure for other aerosol sources, such
as wastewater treatment aeration basins, trickling
filter units, and air conditioning system evaporation
condensers. At the present time, however, estimates
of microorganism densities in air in the vicinity of
these types of facilities would require some field
aerosol monitoring.
Atmospheric Diffusion Model
The basic building block of the mathematical model
for estimating microorganism densities in air is an
atmospheric diffusion model. A number of such
models, developed and validated over the past quar-
ter century, are currently in wide use for estimating
the downwind density of air pollutants (both inert
gases and small particle aerosols). The general form
of this atmospheric diffusion model is shown in
Figure 3. The model assumes that pollutants will dif-
fuse in a random manner resulting in a Gaussian
(normal) distribution of pollutants at any specific
downwind location. This diffusion pattern is shown
in Figure 4. Pollutants released from the point source
will achieve a median plume height (H) and diffuse in
both the horizontal (y) and vertical (z) directions
during travel along the downwind plume centerline
(x). This figure correctly represents the diffusion pat-
tern when diffusion in the downwind direction (x) can
be ignored, i.e., when pollutant release is continuous,
or when the duration of release is equal to or greater
than the travel time to the location of interest. In this
figure a receptor location is represented by the coor-
dinate location x,-y,z which is on a straight line down-
wind distance (d) from the point source. It should be
noted that downwind distance (d) is different from the
downwind distance along the plume centerline (x).
Since most aerosol density estimates are made on or
near the centerline and at nominal elevations, the
values for d and x are often quite close and can be
used interchangeably.
Where:
And.
d = downwind distance, m
Cd= total air pollutant density at d, mass/m3
Pd= air pollutant density attributable to source being
modeled, mass/m3
B = background air pollutant density, mass/m3
Dd - atmospheric diffusion factor at d, sec/m3
Q = pollutant source strength/emission rate, mass/sec
Figure 3. Atmospheric Diffusion Model
The atmospheric diffusion factor (Dd) in the model
accounts for this downwind dispersion of pollutants.
The detailed expression for this factor, applicable to
pollutants emanating from a point source, is shown
in Figure 5. This equation, taken from Turner's Work-
book (see Bibliography) is only one of several alterna-
tive methods for describing this process mathemati-
cally. Users who desire greater accuracy in the
aerosol density estimates may substitute more so-
phisticated expressions of Da for this equation. Users
who are not mathematically inclined should not be
intimidated by this equation. Its solution is straight-
forward and can be performed using a basic scientific
calculator.
The equation in Figure 3, as expanded by the detailed
expression in Figure 5, fully describes the atmo-
spheric dispersion model that is used as the basic
building block for the microbiological dispersion
model. In more sophisticated modeling efforts, adjust-
ments to the atmospheric diffusion model are gen-
erally necessary to account for factors that interfere
with the random diffusion behavior of pollutants.
This includes: plume rise resulting from local mete-
orological conditions, gravitational settling resulting
8
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Figure 4.
x = downwind direction along plume centerlme
y = crosswind direction
z = vertical direction
(x,-y,z) = receptor location
H = mean plume height
h = source height
d = downwind distance from source to receptor
Gaussian Distribution of Aerosol Plume in Crosswind and Vertical Direction Downwind from a
Point Source
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e~
+ e -
Where: y = distance in crosswind direction, m
z = distance in vertical direction, m
u - mean wind speed, m/sec
ay - standard deviation of plume concentration distri-
bution in the crosswind direction, m
az = standard deviation of plume concentration distri-
bution in the vertical direction, m
H = height of plume centerline, m
Figure 5. Atmospheric Dispersion Factor
from particle size and density, pollutant decay (chem-
ical or biological degradation) with time, reflection or
"bouncing" of particles following their gravitational
settling, deposition of pollutants at horizontal mixing
boundaries (the ground, other surfaces, or at a tem-
perature inversion boundary), and wash-out of pollu-
tants by rainfall. For simplification, most of these
factors are ignored in this use of the model.
For estimating pollutant density relatively close to the
source, the atmospheric diffusion model should also
be adjusted to account for the geometry of the pollu-
tant source(s). This is because the close-in downwind
diffusion pattern will vary significantly for pollutants
that emanate from a single point, a line, or an area. At
relatively distant locations all source types will re-
semble, and can be dealt with mathematically as,
point sources. One general procedure for mathe-
matically dealing with line and area sources is to
apply the model to each point source within the line
or area source. Integration of the pollutant density
predictions from each point source provides the over-
all downwind density estimate. This and alternative
procedures for more accurately dealing with multiple
pollutant sources elevate the mathematics beyond
the level that would be attempted by many potential
users of this document. Therefore, another simpli-
fying assumption is to treat mathematically all spray
irrigation systems as point sources. The error intro-
duced by this assumption decreases with distance
downwind because the geometry of all sources will
increasingly resemble that of a point source.
Microbiological Dispersion Model
The principal developmental efforts on the micro-
biological dispersion model have been to identify
necessary adjustments to the atmospheric diffusion
model. In other words, what unique factors associ-
ated with microbiological aerosols would make the
use of the general atmospheric diffusion model in-
appropriate? It was clearly understood that micro-
organisms do not survive as well in the atmosphere
as they do in wastewater. Therefore, a major adjust-
ment was to incorporate factors to describe micro-
organism survival upon aerosolization and with
aerosol age (time that the microorganism is sus-
pended in the atmosphere).
A general expression for the microbiological disper-
sion model is provided in Figure 6. The only differences
between this equation and the general atmospheric
dispersion model (Figure 3) are: (1) the use of a
source strength factor (Qa) that is adjusted to account
for loss of microorganism viability during the initial
moments of aerosolization; and (2) the addition of the
microorganism die-off factor (Md) to account for
reduced survival over time.
Where:
Qa = aerosol source strength adjusted for loss of micro-
organism viability during spray process, micro-
organisms/sec
Md = microorganism die-off factor, fraction of micro-
organisms that remain viable at distance d from
the source
Figure 6. General Form of Microbiological Disper-
sion Model
In its general form the microbiological dispersion
model requires on-site monitoring to provide values
for the source strength (Qa) and the microorganism
die-off (Md) components. As discussed earlier, on-
site microbiological aerosol monitoring is costly.
Therefore, the next developmental efforts identified
the mathematical components of these factors and
estimated input values for these components for
application at other wastewater spray irrigation sys-
tem locations. The mathematical expressions for Qa
and Md are shown in Figures 7 and 8.
The microbiological dispersion model presented in
Figure 6 consists of four principal components: the
10
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Qa = W F E I
Where:
W = microorganism density in the wastewater, micro-
orgamsms/l
F = flow rate of the spray irrigation wastewater, I/sec
£ = aerosolization efficiency: fraction of sprayed
wastewater that becomes an aerosol, 00
Figure 7. Microorganism Aerosol Source Strength
for Wastewater Spray Irrigation Systems
atmospheric dispersion factor (Dd), the microorga-
nism aerosol source strength (Qa), the microorga-
nism die-off factor (Md), and the microorganism
aerosol background density (B).
Where:
X = viability decay rate of the microorganism, sec*1
downwind distance (d), m
d wind speed (u), m/sec
Figure 8. Microorganism Aerosol Die-Off Factor
Use of the complete microbiological dispersion model
will provide an estimate of the total density (Cd) of
viable microorganisms in the atmosphere at a down-
wind distance (d) from the spray irrigation system.
Subtraction of background (B) from the calculation
will provide an estimate of the downwind aerosol
density (Pd) at distance (d) that is actually due to the
spray irrigation system.
Before the model can be used, the user must select
the site to be evaluated and the microorganism(s) for
which aerosol density estimates will be made. These
decisions will be influenced by the specific circum-
stances and needs of the user. The selection of spe-
cific microorganisms for consideration represents
the most difficult, and potentially arbitrary, decision.
The user's choices here will be constrained by the
availability of microorganism-unique model inputs
for which estimates have been developed. In in-
stances where the user is making aerosol density
estimates to identify the relative human exposure at
several candidate spray irrigation sites, it may be
advisable to select either total coliform or fecal
streptococci organisms. Since these microorganisms
generally occur in relatively high concentrations in
wastewater, but are present only in low densities in
the background air, more reliable estimates for W
and B can be obtained for input to the model. Other
indicator organisms or groups, such as coliphage,
may be more appropriate for selection, depending on
their concentration in the wastewater under study.
Estimating Specific Model Components
After choices concerning site and microorganisms
have been made, the user must collect data for cal-
culating each of the model's major components. The
following sections describe ways of obtaining these
model inputs. Most are site-specific, meaning that
they must be obtained (measured, calculated, or esti-
mated) for each site evaluated. Other inputs are
nonsite-specific. These depend upon irrigation
sprinkler characteristics and microorganism survival
properties and can be applied to any wastewater
spray irrigation site using impact-type rotating
sprinklers. Only those model components that are
relatively complex or have been derived from prior
aerosol monitoring efforts are discussed in the fol-
lowing sections. The development of all other model
inputs is explained later in this document under Esti-
mating Procedure.
Site-Specific Model Inputs
Site-specific model inputs are greatly influenced by
the design and operating conditions of the spray irri-
gation system and the prevailing meteorological
characteristics of the site.
Meteorological Data. The only meteorological data
mandatory for performing model estimates are values
for wind direction, wind speed, and atmospheric sta-
bility classification. Information concerning wind
direction is used to identify those areas that are
generally downwind of the spray irrigation site and,
therefore, of interest. Thus, wind direction influences
the selection of locations where aerosol density esti-
mates are made. Wind speed (u) is necessary to
11
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calculate the atmospheric dispersion factor (Dd) and
to calculate aerosol age (ad), an input to the micro-
organism die-off factor (Md) calculation.
Atmospheric stability is a measure of the amount of
turbulence or mixing in the air. It influences the rate
of diffusion as the aerosol travels downwindfrom the
source and affects the atmospheric dispersion factor
calculation. The six atmospheric stability classes (A
through F) established by Pasquill (see Bibliography)
are used here. Stability class A represents the most
unstable, turbulent atmospheric condition while sta-
bility class F represents the most stable atmospheric
condition.
All meteorological data can be obtained from local
sources (historical on-site measurements or local
weather station records) or selected by the user as
assumptions under which the aerosol density esti-
mate will be made. Historical meteorological data are
the recommended source to ensure that aerosol
density estimates are made under conditions some-
what representative of the site. Atmospheric stability
information may be difficult to obtain from local
sources in terms of the six stability classes. There-
fore, Table 3 provides a means for selecting the most
appropriate stability class. During many applications
of the microbiological dispersion model, parallel cal-
culations are made under class B and E conditions to
obtain aerosol density estimates under relatively
turbulent and stable conditions.
Dispersion Coefficients (ay and az). The dispersion
coefficients in the crosswind (ay) and vertical (az) di-
rections are the actual values used in the atmo-
spheric dispersion factor equation to account for
atmospheric stability (diffusion/dilution of aerosol
downwind from the source). The amount of aerosol
diffusion/dilution increases both with the distance
from the source and with increased atmospheric tur-
bulence or mixing. Figures 9 and 10 should be used to
obtain values for ay and az for each centerline dis-
tance (x) and atmospheric stability class combination
under which aerosol density estimates are being
made.
Microorganism Density in Wastewater (W). To
obtain model input values for the microorganism
density in wastewater (W), samples of the sprayed
wastewater must be collected and analyzed. Sepa-
rate analyses are required for each microorganism of
interest to the user. As a result of high daily and
seasonal variability, it is also recommended that an
appropriate sampling and analysis program be con-
ducted to provide a mean value for W. When results
from a single wastewater sample are used, the
aerosol density estimate will likely be less than
reliable.
Flow Rate (F). The spray irrigation system total flow
rate (F) is generally measured at the spray irrigation
pump and is expressed in liters of wastewater
sprayed per second.
Table 3. Atmospheric Stability Categories
Surface Wind
Speed (at 10 m)
m/sec
<2
2-3
3-5
5-6
>6
Strong
A
A-B
B
C
C
Day
Incoming Solar Radiation
Moderate
A-B
B
B-C
C-D
D
Slight
B
C
C
D
D
Night
Thinly Overcast
or
>4/8 Low Cloud
E
D
D
D
<3/8
Cloud
F
E
D
D
The atmospheric stability categories A to F are from most unstable to most stable. The neutral class, D, should be assumed for overcast
conditions during day or night.
aFrom Turner, 1970
12
-------
1000
100
1000
10,000
Downwind Centerline Distance (x), meters
Figure 9. Horizontal Dispersion Coefficient as a Function of Downwind Distance from the Source
13
-------
1000
100
10
+H
j#
E
n-rt
m
TR t#-
tit
-3:
100
1000
10,000
Downwind Centerline Distance M, meters
Figure 10. Vertical Dispersion Coefficient as a Function of Downwind Distance from the Source
14
-------
Table 4. Background Microorganism Aerosol Densities
Microorganisms Per Cubic Meter"
Spray Irrigation Sites
Wastewater Treatment Plants
Microorganism
"Standard Plate Count"
Total Conforms
Fecal Coliforms
Coliphage
Fecal Streptococci
Mycobacteria
Pseudomonas
Clostridium perfringens
Enteroviruses
Pleasanton
970
0.2
0.04
0.02
0.5
0.4
6
0.1
c
Ft. Huachuca
41
1.3
NO
ND
ND
ND
NO
ND
Deer Creek Lake
89
0.7
ND
ND
ND
ND
ND
ND
Egan
4400
1.3
0.2
0.02
<2
ND
<4
ND
Durham
NDb
<0.02
ND
<0.04
0.06
<0.02
<4
ND
Colony forming units (cfu)/m3 for bacteria, plaque forming units (pfu)/m3 for virus
ND = No data available
= No data available, value presumed very low = 0 0 for model calculations
Microorganism Background (B). The background
density (B) of microorganisms in air representsone of
the more tenuous model input values to be estimated
without performing on-site aerosol sampling. Recent
field sampling has shown that for certain micro-
organisms (especially those not unique to waste-
water) B will vary both with location and over time.
One procedure for estimating the background micro-
organism density involves simultaneous sampling
upwind and downwind of the aerosol source under
known meteorological conditions. The overall back-
ground (B) is then computed as the mean of all up-
wind values obtained during the study period. An-
other procedure is to sample the air at several loca-
tions when the aerosol source has not been operated
recently.
Mean background density values from prior field
monitoring studies are presented in Table 4. Unfortu-
nately, no highly reliable guide is available for se-
lecting a value of B from this table when making
microbiological dispersion model estimates. Ideally,
a limited field monitoring study should be under-
taken. An expedient, and less costly, procedure is to
utilize the mean background values from "similar"
sites (rural agricultural, urban residential, etc.) where
considerable field sampling has already been per-
formed. Alternatively, the user may wish to ignore
the background component altogether and make
predictive estimates only of those aerosols from the
spray source (Pd) rather than of the total aerosol
density (Cd = Pd + B). This would be the preferred pro-
cedure when the user is making relative aerosol
density estimates for several candidate spray sites or
when estimates are being made for wastewater-
unique pathogens (B = 0).
Nonsite-Specific Model Inputs
This section describes those model components that
are not unique to the spray irrigation site and for
which estimated values have been developed to
avoid the considerable time and expense associated
with on-site aerosol monitoring. These include the
model inputs for aerosolization efficiency (E), micro-
organism impact (I), and microorganism viability
decay rate (A). Estimated values for these model in-
puts have been developed during prior on-site aero-
sol monitoring efforts, primarily at Pleasanton, CA.
Aerosolization Efficiency (E). Aerosolization effi-
ciency (E) is the fraction of wastewater that is sprayed
into the air and leaves the immediate vicinity of the
spray irrigation system as aerosols. Values of E have
been measured by injecting a fluorescent dye into the
wastewater irrigation system and performing rela-
tively inexpensive aerosol sampling and analyses at
predetermined downwind locations.
The atmospheric diffusion model is then used to pro-
vide predictions of how much dye should be present
at these downwind locations if 100 percent of the
sprayed wastewater were aerosolized. The ratio
between the predicted and measured dye concentra-
tions defines the "efficiency" of the irrigation machinery
15
-------
Table 5. Estimates of Aerosolization Efficiency
Spray Irrigation
Site
Pleasanton, CA
Fort Huachuca, AZ
Deer Creek Lake, OH
No. of Sampling
Runs Made
17
3
4
Percentile Distribution of E Values8
(Median)
10% 25% 50% 75%
0.0009 0.0019 0.0033 0.0064
b 0.0029
0.0047
90%
0.018
All values are for impact-type spray irrigation equipment
= Insufficient number of samples to provide percentile distribution
in generating aerosols. The median estimate of E
from the studies conducted at Pleasanton, Fort
Huachuca, and Deer Creek Lake is approximately
0.003 (i.e., 0.3 percent of the sprayed wastewater left
the immediate vicinity of the spray irrigation system
as aerosol droplets). Table 5 provides a probability
distribution of values for E that were determined
during these prior studies and can be used to select
inputs for future model applications. Using the
Pleasanton study data, the regression equation in
Figure 11 was developed to indicate that values of E
are primarily inf Iuenced by wind speed (shear forces),
air temperature, and solar radiation (evaporation
rate). This equation can be used as an alternative
means for developing values of E when using the
model. It is important to note, however, that these
values of E have been developed only for rotating
impact type sprinklers. A revised family of estimates
for E is required where the spray irrigation system
utilizes a different type of spray irrigation machinery
(i.e. large rain guns, rotating wands, etc.).
Log,0 E = 0.031t + 0.000096ur - 3.10
Where:
t = air temperature, °C
u - wind speed, m/sec
r - solar radiation, watts/m2
Figure 11. Aerosolization Efficiency Prediction
Equation
Microorganism Viability Decay Rate (X). The micro-
organism viability decay rate (X) defines unique sur-
vival properties for each microorganism in the aerosol
state. Values for this model component have been
measured by comparison of aerosol densities at
several sequential downwind distances from the
aerosol source. By subtracting the amount of aerosol
that would be lost from the measured aerosol den-
sities as a result of atmospheric diffusion, settling,
etc. (as predicted from the atmospheric diffusion
model), the remaining reduction in aerosols can be
attributed to loss of microorganism viability. Micro-
organism viability decay rates have also been mea-
sured for various microorganisms under controlled
laboratory conditions. These laboratory studies have
generally provided much slower viability decay values
than studies conducted in the ambient environment.
This is presumably due to the effects of ambient tem-
perature, relative humidity, solar radiation, reactive
trace compounds (air pollutants) in outdoor air, and,
possibly, wastewater as the pre-aerosolization
medium. Therefore, the user is advised to select
values for X that have been derived from the prior
field studies and presented in Table 6. Although this
table presents a percentile distribution for the X ob-
served values, it is recommended that only values
close tothe median (40-60 percent) be selected. Field
study measurements of these low numerical decay
rates have been highly variable, thus making their
accuracy at the upper and lower percentiles highly
uncertain. Also, since this model component is a
time-dependent factor, any errors will be magnified
for aerosol density estimates made further from the
source. Therefore, X has a strong impact on the accu-
racy of the model predictions at distant locations from
the aerosol source. The magnitude of this impact has
yet to be fully defined.
No aerosolization efficiency values are included in
Table 6 for enteroviruses. Because these organisms
16
-------
Table 6. Estimates of Viability Decay Rate*
Microorganism
Total Coliform
Fecal Coliform
Cohphage
Clostridium perfringens
Standard Plate Countd
Mycobacteria
Pseudomonas
Fecal Streptococci
Enterovirus
No. of Aerosol
Sampling Runs
44
13
43
11
33
8
13
31
0
Percentile Distribution of X (sec-') Values
10%
-0.23
-0.19
-0.11
-0.10
-0.12
-0.15
-0.08
-0.06
25%
-0.094
-0.070
-0.051
-0.039
-0.020
-0.009e
-0.008"
-0.006°
40%
-0.050
NE°
-0.029
NE
-0.006
50%
-0.032
-0.023
-0.011
-0.0046
-0.0048
60% 75%
-0.020 -0.004
NE
NE
90%
_b
All estimates based on data obtained at Pleasanton, CA
= Slow decay rate, presumed = 0 0 for model calculations
*!NE = No estimate. Insufficient samples to make estimate at this percentile
Total aerobic and facultative bacteria
Questionable value, may be indistinguishable from zero
occur in extremely low densities, extensive aerosol
sampling has been required to obtain quantitative
data at very close downwind locations, i.e., 50 mfrom
the aerosol source. Therefore, to provide an estimate
of X, no aerosol sampling has been attempted at loca-
tions further downwind. Laboratory studies have
shown that the decay rate for enteroviruses is very
slow. For model calculations it is presumed to be zero.
Microorganism Impact (I). The microorganism
impact factor (I) is essentially a catch-all for all un-
defined processes that influence the viable micro-
organism source strength (Qa) component of the
model. Originally, this factor was intended to repre-
sent the initial shock (rapid water evaporation, turbu-
lent forces, etc.) associated with the aerosolization
process. Laboratory studies have shown that micro-
organisms consistently undergo a rapid, second-
order die-off during the initial seconds of aerosoliza-
tion. This is followed by a slower, first-order die-off
that is represented in the model by the viability decay
rate (X). This initial shock is believed to reflect the
death of that percentage of the microorganism popu-
lation that is extremely fragile or unprotected and,
therefore, more susceptible to the forces associated
with the aerosolization process. The factor I, there-
fore, should represent some fractional reduction of
viable microorganisms below that predicted from the
other components of Qa, i.e. density of microorga-
nism in the wastewater (W), wastewater flow rate (F),
and aerosolization efficiency (E).
During the field studies at Pleasanton, microorga-
nism impact values greater than one were routinely
observed. While such values seem to imply that some
processes associated with aerosol generation or
sampling might be responsible for an increase in the
number of viable microorganisms, reproduction of
microorganisms during the aerosolization process is
not a reasonable explanation. Several plausible ex-
planations have been postulated. Microorganisms
that are contained in wastewater aggregates may be
broken apart during aerosol generation or sampling.
Since the microbiological assay procedure provides a
count of viable particles (not the number of orga-
nisms per particle), an increased count could be ob-
tained in the aerosol sample in spite of a significant
die-off of organisms upon aerosolization. Alterna-
tively, the density of microorganisms in the waste-
water (W) may, as a result of "masking" effects
during the assay procedure, be an underestimate of
the actual number of organisms. Such "masking"
could be due to toxic or growth inhibiting factors,
such as toxic chemicals in the wastewater or micro-
biological competition for assay nutrient sources,
that are not present in the less concentrated aerosol
samples. There has been no progress to date on
defining separate values for the suspected individual
components of I.
Table 7 provides the percentile distribution of micro-
organism impact values (I) obtained for each of the
microorganisms evaluated during the Pleasanton
17
-------
Table 7. Estimates of Microorganism Impact8
Microorganism
Fecal Coliforms
Total Coliforms
Standard Plate Count
Coliphage
Mycobacteria
Clostridium perfringens
Fecal Streptococci
Pseudomonas
Enteroviruses
No of Aerosol
Sampling Runs
13
44
33
43
8
11
31
13
2
Percentile Distribution
10%
NEb
0.034
0.076
0.036
NE
NE
0.57
NE
NE
25%
0.14
0.13
023
0.20
1.6
0.50
1.5
3.6
NE
40%
NE
0.27
0.40
0.38
NE
NE
2.0
NE
NE
50%
0.27
0.34
044
0.71
1.9
2.5
3.6
29
80°
of I Values
60%
NE
0.48
050
1.1
NE
NE
5.7
NE
NE
75%
1.2
1.2
0.74
1.9
4.4
14
13
150
NE
90%
NE
2.3
2.5
3.8
NE
NE
67
NE
NE
HAH estimates based on data obtained at Pleasanton, CA
NE = Insufficient number of samples to provide values at all percentiles
cApproximate value
study. Preliminary analyses have suggested that
reduced survival (low values of I) may be associated
with low relative humidity, high wind speed, and a
large temperature difference between the waste-
water and air. Enhanced survival (higher I values)
would be expected in situations of high relative
humidity, low wind speed, and a minimal tempera-
ture difference between the wastewater and air.
Judgments of which percentile column to use during
applications of the model can be based on prevailing
atmospheric conditions.
18
-------
ESTIMATING PROCEDURE
Utilization of the microbiological dispersion model for
estimating the density of microbiological aerosols
involves five basic steps. The first calls for decisions
regarding the site to be evaluated and the specific
microorganisrn(s) of concern. The next three steps
involve collection or selection of model input values
to permit calculation of the atmospheric dispersion,
aerosol source strength, and microorganism die-off
factors. Finally, all inputs are combined and the
aerosol density estimate is made for the selected
downwind location. A detailed discussion of thisfive-
step procedure follows.
1. Make initial prediction decisions.
a. Select the site to be evaluated.
b. Select the microorganism(s) for which an
aerosol density estimate is desired.
2. Calculate the atmospheric dispersion factor.
a. Prepare a scale drawing of the spray irri-
gation system and the surrounding area of
interest. If the spray irrigation system is a
line or area source, a central location
should be marked to represent the aerosol
"point source."
b. Select the prevailing wind direction and
wind speed (u) for the meteorological con-
ditions under which the aerosol density
estimate is to be made. Draw a directional
line through the aerosol "point source" on
the scale drawing to represent the aerosol
plume centerline direction.
c. Select and plot on the scale drawing the
downwind location where the aerosol
density estimate will be made. Measure or
estimate the three-dimensional coordi-
nates for the downwind location relative
to ground level at the point source. This
measurement includes: the plume center-
line downwind distance (x), the crosswind
deviation from the plume centerline (y),
and the elevation above ground level at
which the estimate is to be made (z). The
downwind centerline distance (x) should
not be confused conceptually with the
downwind distance to the location (d). The
value for d is the distance aerosol will
travel in a straight line from the elevated
point source to the location where the
estimate is to be made. In most model
applications the values for x and d are
nearly equivalent, especially when a loca-
tion on the plume centerline is selected. In
such cases y is zero. To represent the
breathing zone for persons standing down-
wind, 1.5 m is commonly used for z.
d. Estimate the median aerosol plume height
(H) for the point source. For rotating impact
sprinklers, the elevation of the sprinkler
head (h in Figure 4) is commonly used for
this value. Precise values for H and z are
not necessary because the atmospheric
dispersion model is not sensitive to mod-
erate deviations in these values.
e. Using Table 3 and/or local meteorological
data, select the atmospheric stability class,
A through F, that represents the meteoro-
logical conditions under which the esti-
mate is to be made. Alternatively, the
neutral class, D, can be assumed. Parallel
calculations using class B and E are com-
monly performed to provide comparative
aerosol density estimates under "stable"
and "unstable" atmospheric conditions.
f. By consulting Figures 9 and 10, determine
the crosswind and vertical dispersion co-
efficients (ayand az respectively) by using
the value for x and atmospheric stability
established in steps 2c and 2e above.
g. Calculate the atmospheric dispersion fac-
tor using the equation:
1
2 fy/ayf
+ e-'/,f(Z+H)/aJ2
3. Calculate aerosol source strength.
a. Initiate a wastewater sampling program to
develop mean wastewater density values
(W) for the selected microorganisms.
Microorganisms that can be easily moni-
tored in wastewater and for which reliable
estimates of I and A have been derived are
not, however, the pathogenic microorga-
nisms of epidemiological concern. There-
fore, aerosol density estimates will gener-
ally be made for nonpathogenic organisms
and assumptions made regarding the
association between these density esti-
mates and those for the pathogens of
actual concern.
19
-------
b. Measure or calculate the total flow rate (F)
of wastewater in the spray irrigation sys-
tem. This is the total flow rate to all
sprinklers contributing to the aerosol source
and is usually measured at the irrigation
system pump.
c. Select an aerosolization efficiency (E) value
appropriate to the type of spray system
being evaluated. This will involve selec-
tion of a value for E from Table 5 or calcu-
lation of a value using the equation in
Figure 11.
d. Select an appropriate value for the micro-
organism impact factor (I) for each micro-
organism for which an aerosol density
estimate is to be made. These values
should be selected from the percentile
table presented in Table 7. Median per-
centile values (50 percent) should be
selected to represent average meteoro-
logical conditions. Lower percentile values
(25 percent) should be selected for aerosol
density estimates made under conditions,
such as high solar radiation, high ambient
temperature, or low to medium relative
humidity, that adversely affect microorga-
nism survival. An example of this condi-
tion would be a very hot, dry summer day.
Selection of values of I from the higher
percentile range (75 percent) should be
made under those environmental condi-
tions deemed favorable for the survival of
microorganisms, such as little or no solar
radiation, low ambient temperature, or
high relative humidity. An example of this
condition would be a cool, humid night.
e. Calculate aerosol source strength using
the equation:
is also on or near the plume centerline
(i.e., y = 0), the value for x can be used for
d.
b. Using downwind distance (d) and wind
speed (u) in the following equation, calcu-
late the aerosol age (ad) of the downwind
location where the aerosol density esti-
mate is to be made:
a 4 = d/u.
c. Select val ues for the viability decay rate (X)
for each microorganism for which an
aerosol density estimate is to be made.
Values for this model component should
be selected from the percentile table pro-
vided in Table 6. Median values should be
selected for relatively moderate meteoro-
logical conditions. Low percentile values
(40 percent) should be selected for envi-
ronmental conditions that are adverse to
microorganism survival, and higher per-
centile values (60 percent) should be
chosen for environmental conditions
favorable for microorganism survival.
d. Calculate the microorganism die-off factor
(Md) applicable to the downwind location
from the viability decay rate (X) and aerosol
age (ad) with the equation:
5. Calculate downwind microorganism aerosol
density estimates
a. Using the following equation, calculate
the microorganism aerosol density (Pd) at
the downwind location that is attributable
to the spray irrigation source:
Qa = WFEI.
4. Calculate the microorganism die-off factor.
a. Make a line on the scale drawing that con-
nects the aerosol "point source" to the
downwind location where the estimate is
to be made. Calculate or estimate the
downwind distance (d). When z and H are
similar, d can be measured on the two-
dimensional drawing. When the location
b. Estimate, when desired, the background
microorganism aerosol density (B) for the
microorganism. Table 4 provides values
for B from prior studies. The user should
note, however, that selection of a value
from this table for a microorganism that is
not generally unique to wastewater may
result in an unreliable density estimate.
20
-------
c. If background aerosol density is being con- from the spray irrigation system with the
sidered, calculate the total microorganism equation:
aerosol density at the location downwind Cd
21
-------
MODEL PREDICTION EXAMPLES
To demonstrate this procedure and to provide insight
into the accuracy and precision of the model, several
estimates of microbiological aerosol densities have
been calculated for specific cases at both the Pleasanton
and Deer Creek Lake spray irrigation sites. Table 8
provides a detailed summary of the predictions made
for total coliforms and fecal streptococci in the vicin-
ity of the Pleasanton spray irrigation site. The closest
exposure population is in a subdivision located ap-
proximately 770 m from the center ("point source")
of the aerosol source. The case considered in this
example was for a typical summer night, correspond-
ing, perhaps, to a maximum, worst case exposure
situation. Following the five step procedure, the total
aerosol density values (Cd) for total coliform and fecal
streptococci were 0.3 and 29.5 cfu/m3, respectively.
Potential users should note that the predicted aerosol
density for total coliforms entering the residential
area from the spray field source (Pd) is only one half
the background value (B). Therefore, the total esti-
Table 8. Example Calculation Using the Microbiological Dispersion Model: Pleasanton, CA Residential Area
"Worst Case" (Summer Night)
Procedure Step
Value
1. Initial Decisions
a. Site
b. Microorganisms of Interest
2. Atmospheric Dispersion Factor
a. Scale Drawing
b Wind Data
Direction
Speed, u
c. Downwind Location
Centerline Distance, x
Crosswind Deviation, y
Height, z
d. Aerosol Plume Height, H
(equal to sprinkler height)
e Atmospheric Stability Class
f. Dispersion Coefficients
Crosswind, ay
Vertical, az
g. Atmospheric Dispersion Factor, Dd
3 Aerosol Source Strength
a Microorganism Density in Wastewater, W
b. Total Wastewater Flow Rate to Irrigation System, F
c Wastewater Aerosohzation Efficiency, E
d. Microorganism Impact Factor, I
e. Aerosol Source Strength, Qa
4. Microorganism Die-off Factor
a Downwind Distance to Location, d (Y = 0, d = x)
b. Aerosol Age, ad
c Viability Decay Rate, A
d. Microorganism Die-off Factor, Md
5 Downwind Microorganism Aerosol Density Estimates
a. Microorganism Aerosol Density resulting from
Spray Irrigation Source, Pd
b. Background Aerosol Density, B
c Total Microorganism Aerosol Density, Cd
Pleasanton, CA
Total Coliform and Fecal Streptococci
See Figure 12
East
2 m/sec
770 m
0 m
1.5 m
0.6 m
E (stable)
40
18
2.2 x 1Q-4 sec/m3
Total Coliform
1 Ox 107 cfu/l
70 I/sec
3.3 x 10-3a
0.48
1.1 x 1Q6 cfu/sec
770 m
385 sec
-0.02 sec-1*
4.53 x 10-"
0.1 cfu/m3
0 2 cfu/m3
0.3 cfu/m3
Fecal Streptococci
1.0x 10s cfu/l
70 I/sec
3.3 x 10-3a
57
1.3 x 106 cfu/sec
770m
385 sec
0.0 see-'0
1
29.0 cfu/m3
0.5 cfu/m3
29.5 cfu/m3
,50th percentile value selected
6Oth percentile value selected
cSlow decay rate, presumed = 0 0 for model calculations
22
-------
240 m
Spray Line
Adjacent Receptor
Locations
-100 m
T
"Point Source"
H = 0.6 m
770 m
Receptor Location
x = 770 m
y = Om
z = 1.5 m
"Point Source" Plume Centerlme
Wind Direction
Figure 12. Diagram of Pleasanton, CA Prediction Example
23
-------
Table 9. Major Model Inputs for Sample Predictions for Total Coliforms
Pleasanton
Deer Creek Lake
Site Condition
Atmospheric Diffusion Factor (Dd)
Wind Speed (u), m/sec
Centerline Distance (x), m
Atmospheric Stability Class
Dispersion Coefficients
Crosswind(av)
Vertical (az)
Aerosol Source Strength (Qa)
Total Cohform Density
in Wastewater (W), cfu/l
M
Wastewater Flow Rate (F), I/sec
Aerosolization Efficiency (E)
Microorganism Impact Factor (1)
roorganism Die-off Factor(Md)
Downwind Distance (d), m
Aerosol Age (a d), sec
Viability Decay Rate (X)
Summer Night
2
770
E (Stable)
40
18
1 Ox 10'
70
33 x 10-3
0.48
770
385
-0.02
Summer Midday
4
770
B (unstable)
125
83
1.0x 1Q7
70
1.6 x 10-2
0.27
770
193
-0.05
Summer Night
2
700
E (stable)
36
16.5
1.8 x 105
30
47 x 10-3
048
700
350
-0.02
Summer Midday
4
700
B (unstable)
112
72
1 .8 x 1 05
30
9.0 x 10-3
0.27
700
175
-0.05
mated density (Cd) for this microorganism reflects the
significant influence of that background value.
Of greatest importance in this parallel sample calcu-
lation is a demonstration of the impact that micro-
organism survival factors have on downwind aerosol
densities. Fecal streptococci are relatively hardy
microorganisms in the aerosol state. Although their
density in wastewater is two orders of magnitude
below the coliforms, their aerosol density 770 m
downwind is predicted to be nearly two orders of
magnitude greater than the coliforms. The enhanced
survival properties (higher I value and lower A value)
account for a four-log difference in the relative
wastewater density measurements and downwind
aerosol density estimates. Thus, pathogens that exist
in relatively low densities in wastewater and have
hardy survival properties can be expected to occur in
relatively high densities at locations distant from the
aerosol source.
A second aerosol density estimate was made at this
same location for a typical summer midday case, per-
haps corresponding to a minimum, best case expo-
sure situation. In addition, model predictions were
made for residents of a campsite located 700 m
downwind from the Deer Creek Lake spray irrigation
facility. These sample calculations were performed
only for total coliforms. The major model inputs for all
of these example calculations are summarized in
Table 9. All model inputs absent from this table are
the same as for the detailed example (Table 8). The
summary of these calculations, presented in Table
10, shows that the midday predictions were approxi-
mately two orders of magnitude below the nighttime
situations. Reduced microorganism survival (from
higher temperature, presence of solar radiation, or
lower relative humidity) and greater atmospheric
diffusion/dilution (from unstable, highly mixed air)
more than compensated for the shorter aerosol age
(from greater wind speed), and higher aerosolization
efficiency (from higher temperature, solar radiation,
and wind speed) present at midday.
Although these estimates are for sites where aerosol
field monitoring has been conducted previously, they
are all for downwind distances beyond the sensitivity
limits of practical aerosol monitoring programs (100-
200 m), and thus represent another important appli-
cation of the microbiological dispersion model. Even
when the user undertakes a major wastewater
aerosol sampling program, model estimates are still
required to predict human exposures at downwind
locations beyond the range of reliable sampling.
A final example aerosol density estimate is presented
to demonstrate the significant impact of the cross-
wind diffusion coefficient (ay) in the model. The
24
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Table 10. Summary of Example Predictions for Total Coliforms
Pleasanton
Model Component
Atmospheric Diffusion Factor (Dd), sec/m3
Aerosol Source Strength (Qa), cfu/sec
Microorganism Die-off Factor(Md)
Microorganism Density at Distance (d3)
attributable to Source (Pd), cfu/m3
Summer Night
2.
1.
4.
0
2 >
1 >
5 >
1
< 10-"
t 106
c 10-"
Summer
7
3
6
.7 x
.Ox
.4 x
4.4 x
Midday
10-6
106
10-5
10-3
Deer Creek Lake
Summer Night
2
1.
9.
2
.7x
2 x
.1 x
,9x
10-"
10"
10-"
10'3
Summer
9.9 x
1.3x
1.6 x
2.1 x
Midday
10-«
10"
10-"
10-6
detailed example calculation summarized in Table 8
is for a location 770 m downwind on the aerosol
plume centerline, i.e. y = 0 and under stable (class E)
atmospheric conditions. Table 11 compares the re-
sults of this and two similar calculations where the
receptor location is 50 and 100 m away (crosswind)
from the plume centerline. Using these values for y
has a major impact on the calculated atmospheric
diffusion factor. Because the aerosol travel distance
(d) also increases slightly, the microorganism die-off
factor is slightly altered. Thus, major reductions in
the downwind aerosol density are predicted at not too
distant locations adjacent to the plume centerline.
This predicted reduction at adjacent downwind loca-
tions should be less pronounced under more
unstable atmospheric conditions (i.e., class B), when
greater mixing and diffusion of the aerosol plume will
take place.
Table 11. Impact of Crosswind Location
Crosswind Distance, y
Model Component
Atmospheric Dispersion (Dd), sec/m3
Aerosol Source Strength (Qa), cfu/sec
Microorganism Die-off Factor(Md)
Total Col if or m Aerosol Density at x = 770 m
attributable to the source (Pd), cfu/m3
0 m
22 x 10-"
1.1 x 1Q6
45 x 10-"
10.0 x 1Q-2
50 m
1 Ox 10-"
1.1 x 1Q«
44 x 10-"
48 x 10-2
100m
9.7 x 10-6
1.1 x 1Q6
43 x 10-"
0.46 x 10-2
25
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USER CONSIDERATIONS
Users of this model are cautioned that treating all
spray irrigation systems mathematically as point
sources generates a significant error in the absolute
and relative magnitude of both centerline and adja-
cent downwind aerosol density estimates. For spray
irrigation systems that are line or area sources, the
centerline aerosol density estimate will be higher
when the point source model, rather than a more
sophisticated model, is used to account for source
geometry. The adjacent location aerosol density esti-
mates will be low when the point source model is
used because, in reality, aerosol is being generated
along a line upwind from the receptor location.
Therefore, estimates of aerosol densities at locations
adjacent to the centerline should be restriced to loca-
tions beyond the lateral dimensions of the actual
spray system. No attempt has been made to provide a
quantitative estimate of the magnitude of this source
of error because it is variable and increases dramati-
cally for locations closer to the aerosol source, when
source geometry becomes increasingly important.
Users are also cautioned that another potential
source of significant error in application of the model
occurs in the microorganism viability decay rate (X).
The values for this model input in Table 6 have been
derived from aerosol sampling studies performed
within 100-200 m from the aerosol source. Owing to
the time (distance) dependence and exponential
nature of microorganism die-off component, any
inaccuracies in the A values will be magnified as
distance from the source increases. Thus, users are
advised to restrict downwind aerosol density esti-
mates to within approximately 1000 m from the spray
irrigation system.
26
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PERSPECTIVE
In studies to date, no significant increase of human
infection or disease resulting from microbial aerosols
generated by wastewater treatment or spray irriga-
tion facilities has been observed in populations living
nearby. There are several reasons for such results:
Densities of specific pathogens in the waste-
water were low, and were reduced rapidly with
time and distance from the source.
A person would ordinarily inhale very feworga-
nisms unless exposed for many hours.
The exposure levels were below the minimum
infective dose.
Microorganisms in wastewater were primarily
enteric organisms, whereas the route of expo-
sure was respiratory.
Phagocytic cells tended to respond to the foreign
substances inhaled before antibody cells were
formed.
Exposed persons were probably in good health
and better able to combat infection than sickly
persons would be.
Infectious agents other than those checked
may have caused an undetected infection.
While our knowledge of wastewater aerosols has
increased significantly during the past few years, it
should always be kept in mind that despite the lack
of a relationship between aerosols and disease, sew-
age contains potentially pathogenic agents and expo-
sure should be kept to a minimum. Aerosol genera-
tion should be minimized, and nearby populations
should not be indiscriminately exposed.
27
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GLOSSARY
Aerobiology
Aerosol
Atmospheric Stability
Classification
cfu
Coliform
Coliform, fecal
Coliphage
Decay rate
Density
The portion of aerosol science that investigates aerosols containing micro-
organisms.
Any material, solid or liquid, of a size that remains suspended in air for an appre-
ciable length of time before settling. Typical size range is 0.01 to 20 /urn
(Vm = 3.94 x 1Q-5 inches).
A method of reducing a number of complex atmospheric motion phenomena
into classes useful in designing and using the "Model."
Colony-forming units. An expression derived from the method of quantitating
bacteria, yeasts, and molds by their growth on a nutrient agar medium (see
Standard Plate Count). Each colony that is seen and counted originates from a
single cell, or a collection of cells, deposited at one place on the medium.
A type of bacterium closely resembling other species found in the intestinal tract
of animals, including man. From "colon," hence "coli-."
Coliform bacteria that have a demonstrably high probability of having come from
human fecal material. (See also Streptococcus, fecal.)
A virus that invades and kills coliform bacteria. There are numerouscoliphages,
distinguishable from each other by special tests.
Most airborne microorganisms "disappear" (in terms of viability) from the air
faster than would be indicated by their fall-out through gravitational settling.
This disappearance is a result of some lethal event endured by the microbe as a
consequence of being airborne. Expressed as percent decrease over time
(minutes or seconds).
The number or weight of a substance (of particulate or molecular dimensions)
present in a unit volume (or weight) of diluting material, e.g..
Diffusion
Disinfection
Dose
Dose-response
Epidemiology
Number of bacterial cells
m3 of air
or
number of virus particles
ml of wastewater
The random motion of molecules and small particles resulting from unequal
"push and shove" of molecular motion, the strength of which is a function of
temperature. The diffusion process tends to cause local densities of a gas or
small particle aerosol to decrease over time.
Any physical or chemical method that reduces the number of living microorga-
nisms present in a given location.
The total number of infectious disease units (bacteria, mold cells, virus particles)
or weight of toxic chemicals that an individual absorbs, ingests, or inhales.
The relationship between dose and the effect a dose has on the individual
receiving it.
The branch of science that seeks to establish relationships between cause and
effect by examining pertinent records of large numbers of affected individuals.
28
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Enterovirus
Immunity
Impact factor
Microorganism
Model
Monitoring
Mycobacteria
pfu
Plate, petri
Pollutant
Pseudomonas
Sampler, air
Sampler, water
Standard Plate Count
A descriptive name for a large number of viruses that can cause diseases with
intestinal symptoms. These viruses are shed in the feces.
Natural or induced resistance of an individual toa known pathogenic microorga-
nism. Immunity is usually not absolute. A large enough dose of the pathogen
may overcome immunity.
The loss of microorganisms taking place during the process of aerosol genera-
tion, thought by some to be a reflection of the large shear forces generated in
efficient sprayer operation.
A member of the class of living entities that is small in size, in which the repro-
ductive and living unit is composed of one cellular element. Included in this class
are bacteria, yeasts, molds, and viruses.
A formal description of the outcome of a series of events, all of which may be ex-
pressed in some mathematically valid form. To be of use, a model must be
demonstrably valid; it must predict, within known limits, a previously estab-
lished or known outcome.
The process of assessing the quality of wastewater or air. Those components
that are to be quantitatively determined must be specified.
From the genus name Mycobacterium, the most famous of which is Myco-
bacterium tuberculosis. Most mycobacteria are harmless saprophytes, some of
which are part of the fecal flora.
Plaque-forming unit is the "cfu" concept applied to a virus that is able to form
defined plaques (or regions of cell destruction) when it grows in a cell (either
plant, animal, or microbial) and, on rupture of the infected cell, spreads progres-
sively to other cells until the area of cellular damage is large enough to be seen.
A shallow vessel, flat-bottomed glass or plastic, ca. 100 mm in diameter, into
which a sterile nutrient growth (e.g.. Standard Plate Count agar) medium is
poured.
Any substance that constitutes a threat to human, animal, or plant health or
welfare. A pollutant may be a solid, liquid, or gas.
The genus name of a large number of species. Some of the pseudomonads are
serious disease agents. Most are harmless, including those present in animal
feces.
A device that removes, by quantitative means, those materials to be monitored
and subsequently assessed quantitatively. The results obtained by sampling
microorganisms in air must be interpreted with caution, since the very acts of
sampling, of transporting the sample, and of assessing the kinds and numbers of
microorganisms are fraught with varying degrees of uncertainty.
A device to remove a representative portion of the water stream to be monitored.
An assessment of the number of microbes (bacteria, yeasts, or molds) that can
grow on a sterile, jelly-like nutrient surface from single cells to an aggregate of
29
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Streptococcus
Streptococcus, fecal
Source strength
Sterilization
Treatment, primary
Treatment, secondary
Virus
Wastewater
Wastewater
Management Facility
cells sufficient in number to be visible to the minimally assisted eye. The
nutrient medium made from a recipe widely adopted by sanitation specialists is
termed Standard Plate Count agar.
A genus of bacteria commonly found in the mouth and intestines of man and
other animals. Some of the members of this genus are pathogens.
A species of Streptococcus that is a normal inhabitant of human (and other
animal) fecal microbial flora.
The effective number of particles that can be rendered airborne and be subject to
wind transport and diffusion. Source strength depends on the quantitative and
qualitative nature of the wastewater being sprayed, by the mechanical nature of
of the spray head, hydraulic pressure, and other environmental factors.
A disinfection process that kills all living microorganisms.
Treatment of wastewater to remove or reduce gross paniculate material and a
portion of the dissolved organic material.
Treatment of effluent from a primary treatment facility that reduces, through
chemical-biological action, the organic constituents of that effluent to a level
acceptable for discharge into a receiving body of water.
A form of life that grows and reproduces only in a living cell of a bacterium, a
higher plant, or animal. Such growth and reproduction frequently kills the host
cell. Numerous types of viruses exist.
Water that has been used for domestic, sanitary, or industrial purposes but no
longer can be used for those purposes.
An assembly of equipment and structures arranged to permit raising the quality
of wastewater by removing (or reducing concentrations of) undesirable dis-
solved or suspended material. Includes a variety of wastewater land application
systems (spray irrigation being a popular design) often erroneously referred to
as wastewater disposal.
30
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*USGPO: 1982 559-092/3395
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