EPA/600/R-95/016
                                                         August 1995
Pathogen Risk Assessment Methodology for Municipal
   Sewage Sludge Landfilling and Surface Disposal
                   National Risk Management Research Laboratory
                      Office of Research and Development
                      U.S. Environmental Protection Agency
                           Cincinnati, OH 45268
                                                    Printed on Recycled Paper

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                                  DISCLAIMER
      This document has been reviewed in accordance with U.S. Environmental Protection
Agency policy and approved for publication. Mention of trade names or commercial products
does not constitute endorsement or recommendation for use.
                                       11

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                                      PREFACE

       Section 405 of the Clean Water Act requires the U.S. Environmental Protection Agency
(U.S. EPA) to develop and issue regulations  that identify:  (1) uses for  sludge including
disposal; (2) specific factors (including costs)  to  be taken  into  account  in determining  the
measures and practices applicable for each use or disposal; and (3) concentrations of pollutants.
that interfere" with each use or disposal.  To comply with this mandate,  the  U.S. EPA  has
embarked on a program to develop four major technical regulations: land application, including
distribution and marketing; landfilling; incineration; and surface disposal. The development of
these technical regulations requires a consideration of pathogens as well as chemical constituents
of sludge.  Public concern related to the reuse and disposal of municipal sludge often focuses
on the issue of pathogenic organisms.
       This report is one of a  series whose purpose is to assess  the potential risk to human
health  posed by parasites, bacteria and viruses in municipal sewage sludge and  to develop
preliminary risk .assessments for each of these classes of pathogens. This document describes
a methodology and computer model designed to assess human health risks from pathogens in
landfilled or surface  disposed sewage sludge.
                                           ui

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                           DOCUMENT DEVELOPMENT
Dr. Norman E. Kowal, Work Assignment Manager
Environmental Criteria and Assessment Office
U.S. Environmental Protection Agency
Cincinnati, OH 45268
Authors

Marialice Wilson, Project Manager
Dr. Charles T. Hadden
Mary C. Gibson
Jennifer Webb Chason
Dr. Patrick F. Ryan
Dr. M. Alauddin Khan
Julia H. Gartseff
Science Applications International Corporation
Oak Ridge, TN 37831

Reviewers

Dr. Robert F. Carsel
Dr. Rochelle Araujo
Dr. Rosemarie C. Russo
Dr. Robert Swank
Environmental Research Laboratory
U.S. Environmental Protection Agency
Athens, GA 30613

Dr. Milovan Beljin
Department of Civil and
  Environmental Engineering
University of Cincinnati
Cincinnati, OH 45221

Robert E. Mooney
Department of Microbiology
University of New Hampshire
Durham, NH  03824

Dr. John Woodward
University of Tennessee
Knoxville, TN 37996
Dr. Elizabeth D. Caldwell, Technical Review
ENSR Consulting and Engineering
Fort Collins, CO 80524

Dr. Barney Cornaby, Technical Review
Science Applications International Corporation
Oak Ridge, TN 37831
Anne Sergeant
Exposure Assessment Group
Office of Research and Development
U.S. Environmental Protection Agency
Washington, D.C. 20460

Walter Jakubowski
Dr. Gerard N. Stelma, Jr.
Dr. G. Shay Fout
Dr. Robert S. Safferman
Microbiology Research Division
Environmental Monitoring Systems Laboratory
U.S. Environmental Protection Agency
Cincinnati, OH  45268

Maureen E. Leavitt
Bioremediation Specialist
Science Applications International Corporation
Oak Ridge, TN 37830
                                        IV

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                          TABLE OF CONTENTS
1.  EXECUTIVE SUMMARY	. .  .	1-1

2.   INTRODUCTION AND DESCRIPTION OF GENERAL METHODOLOGIC
     APPROACH	.	 .2-1

     2.1.   PURPOSE AND SCOPE . . .	2-1
     2.2.   DEFINITION AND COMPONENTS OF RISK ASSESSMENT	2-2
     2.3.   RISK ASSESSMENT IN THE METHODOLOGY
           DEVELOPMENT PROCESS	2-3

           2.3.1.   Hazard Identification and Dose-Response Assessment  ...... 2-4
           2.3.2.   Exposure Assessment	2-10
           2.3.3.   Risk Characterization	 2-12

     2.4.   POTENTIAL USES OF THE MODEL IN DETERMINING
           RESEARCH NEEDS	. .  . .	2-12
     2.5.   POTENTIAL USES OF THE MODEL IN
           RISK MANAGEMENT	 . . 2-13
     2.6.   LIMITATIONS OF THE MODEL	.2-14

3.  DESCRIPTION OF DISPOSAL PRACTICES  ....................... 3-1

     3.1.   SURFACE DISPOSAL . . .	,	 3-1
     3.2.   LANDFILLING	 . .	 3-2

4.  IDENTIFICATION OF PATHOGENS .  . . .	... .	4-1

     4.1.   PATHOGENIC BACTERIA   . . . .	  . . .	4-1

           4.1.1.   Bacteria Persistence and Inactivation in Sludge  	4-6
           4.1.2.   Bacteria Persistence and Inactivation in Soil	 4-7
           4.1.3.   Bacteria Persistence and Inactivation in Groundwater	4-8

     4.2.   VIRUSES	 4-9

           4.2.1.   Virus Persistence and Inactivation in Sludge  ....	 . . 4-12
           4.2.2.   Virus Persistence and Inactivation in Soil and Water	 4-12
           4.2.3.   Virus Transport in Soil, .the Subsurface and Groundwater  .... 4-14

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                      TABLE OF CONTENTS (continued)

      4.3.   PROTOZOAN PARASITES .  .	4-16

            4.3.1.   Persistence in Sludge	4-18
            4.3.2.   Inactivation and Transport in Soil and Water	. .  4-19

      4.4.   HELMINTH PARASITES	 4-19

            4.4.1.   Persistence in Sludge	4-22
            4.4.2.   Inactivation and Transport in Soil and Water	4-23

      4.5.   FUNGI	4-23
      4.6.   PATHOGEN SUMMARY	4-24

5.  IDENTIFICATION OF EXPOSURE PATHWAYS	   5-1

      5.1.   GROUNDWATER INFILTRATION	5-1
      5.2.   SURFACE RUNOFF	 5-3
      5.3.   PARITCULATE SUSPENSION	5-3

6.  MODEL DESCRIPTION AND RESULTS	6-1

      6.1.   OVERVIEW OF THE METHOD	  6-1
      6.2.   ASSUMPTIONS	6-2
      6.3.   INPUT PARAMETER REQUIREMENTS	6-9

            6.3.1.   Pathway Data	6-10
            6.3.2.   Pathogen-Specific Data	 6-12
            6.3.3.   Processes and Transfers  	6-12

      6.4.   CALCULATIONS	 . .  .	6-12

            6.4.1.   Source Term	  6-12
            6.4.2.   Unsaturated Zone Transport	6-15
            6.4.3.   Saturated Zone Transport  	6-18
            6.4.4.   Offsite Well	  6-20
            6.4.5.   Risk of Infection	  6-21

      6.5.   RESULTS	6-23

            6.5.1.   Kinetics of Pathogen Transport	6-23
            6.5.2.   Comparison with Experimental Results  	6-25
            6.5.3.   Site-specific Parameter Testing	f	6-25
                                     VI

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                   TABLE OF CONTENTS (continued)

     6.6.  SOURCES OF UNCERTAINTY .	 6-30

7.  SENSITIVITY ANALYSIS .............		 7-1

     7.1.  SENSITIVITY TESTING FOR BACTERIA ..... ..... .	7-4

          7.1.1.   Parameter Values	.....,'"....'.. 7-4
          7.1.2.   Results for Bacteria	 7-4

     7.2.  SENSITIVITY TESTING FOR VIRUSES	 7-22

          7.2.1.   Parameter Values	. . . .	 7-22
          7.2.2.   Results for Viruses  ...... ...	 7-22

8.  SUMMARY AND CONCLUSIONS ............................. .8-1

9.  RESEARCH NEEDS	 . .9-1

10. REFERENCES	 .	  . .	 . .  . . 10-1

APPENDIX A. USER'S MANUAL	A-l
                                Vll

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                                 LIST OF TABLES

No.                                     Title

2-1   Pathogens of Concern in Sewage Sludges	2-5

2-2   Densities of Pathogens in Treated Sludge	2-7

2-3   Dose-Response Data	2-11

4-1   Pathogen Inactivation Rates in Soil and Water  	4-2

4-2   Pathogenic Bacteria of Major Concern in Sewage Sludges	  4-3

4-3   Human Viruses in Sludge and Wastewater	  4-10

4-4   Protozoa of Concern in Sewage Sludge   	4-17

4-5   Helminths of Concern in Sewage Sludge	4-20

6-1   Parameters for Pathogen Risk Assessment Methodology: Sludge
      Landfilling and Surface Disposal	6-3

6-2   Parameter Conversion Factors   	6-11

6-3   Values of Alpha and Beta for Selected Pathogens	6-22

6-4   Parameters for Site-Specific Model Evaluation	6-28

6-5   Results of Site-Specific Model Evaluation	6-29

7-1   Parameters Used to Test the SLDGFILL  Model for Bacteria  	7-5

7-2   Bacterial Concentrations at 240 Days in Model Test Runs   	7-6
                                        Vlll

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                              LIST OF FIGURES
No.

5-1


6-1

6-2

7-1

7-2

7-3

7-4

7^5

7-6

7-7

7-8

7-9

7-10

7-11

7-12

7-13


7-14


7-15
                               Title

Offsite Migration Pathways for Pathogens from Sewage Sludge Landfills
or Surface Disposal Sites	
Pathogen Concentration in Unsaturated Soil ...................

Comparison of Model Results with VIRTUS Model and Experimental Data

Dependence of Retardation Factor on SSPNDS and PORWTR  ........

Effect of SSPNDS on Pathogen Transport Rate in Saturated Soil   	

Parameters with Primary Impact on Model Output	

Parameters with Secondary Impact on Model Output	

Dependence of Pathogen Transport Kinetics on DSATZN	

Dependence of Drinking Water Bacterial Concentration on DSATZN

Dependence of Compartment Equilibration on DSATZN	

Dependence of Model Outcome on Sludge Pathogen Concentration  ....

Dependence of Model Outcome on SSPNDB  . .	

Dependence of Infection Risk on Infectivity Parameters  	

Effect of INACTW on Kinetics of Pathogen Transport  ............

Effect of INACTB on Kinetics of Bacterial Transport	
 Dependence of Virus Concentration in the Saturated Zone and the
 Groundwater Well on Depth to the Saturated Zone [P(l)]	
 Dependence of Maximum Predicted Virus Concentration on Initial
 Density in Sludge [P(13)]	
 Dependence of Virus Concentration and Time to Maximum Concentration
 on Inactivation Rate in Sludge [P(14>]	
 5-2

 6-24

 6-26

 7-2

 7-3

 7-9

 7-10

 7-12

 7-13

 7-14

 7-16

 7-17

 7-18

 7-20

 7-21'


, 7-24


.7-25


. 7-26
                                       IX

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                           LIST OF FIGURES (continued)

 7-16   Kinetics of Virus Concentration  in Groundwater as a Function of
       Inactivation Rate in Sludge [P(14)]	7-27

 7-17   Dependence of Maximum Virus  Concentration in Groundwater on
       Inactivation Rate in Groundwater [P(16)]	7-28

 7-18   Kinetics of Virus Concentration  in Groundwater as a Function of
       Inactivation Rate in Sludge [P(14)]	 7-29

 7-19   Dependence of Maximum Virus  Concentration in Groundwater on
       Soil-to-Water Resuspension Factor [P(18)]  	7-30

 7-20   Effect of Unsaturated-Zone Hydrodynamic Dispersion on
       Maximum Predicted Virus Concentrations in Groundwater	 7-32

 7-21   Effect of Unsaturated-Zone Hydrodynamic Dispersion on
       Time to Reach Steady-State Levels in Groundwater	7-33;

 7-22   Effect of Hydrodynamic Dispersion on Time of Transfer and
       Concentration of Pathogens in Groundwater	 7-35

 7-23   Effect of Groundwater Velocity on Maximum Predicted
       Virus Concentrations in Groundwater	   7.35

 7-24   Effect of Groundwater Velocity on Time to Reach
       Steady-State Levels in Groundwater	7.37

7-25   Effect of Distance to the Groundwater Well [P(23)] on Maximum
       Predicted Virus Concentrations in Groundwater	7-38

7-26   Effect of Distance to the Groundwater Well [P(23)] on Time to
       Reach Steady-State Levels in  Groundwater	 7-39

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                        ABBREVIATIONS AND SYMBOLS

CEC        Cation exchange capacity
CPU        Colony-forming units
D&M       Distribution and marketing
dia         Diameter
ffu         Focus-forming units
GWDR      Ground-Water Disinfection Rule
HAV        Hepatitis A virus
HID        Human infective dose
hr          Hour
ID          Infective dose
KD         Soil-water partition coefficient
MPN        Most probable number
MPNCU    Most probable number of cytopathogenic units
MULTIMED Multimedia Exposure Assessment Model for Evaluating the Land Disposal of
            Wastes
NR         Not reported
PFU        Plaque-forming Units
SRV        Small round viruses
TCID       Tissue culture infectious dose
TSS        Total suspended solids
USD A      U.S. Department of Agriculture
U.S. EPA   U.S. Environmental Protection  Agency
WHO       World Health Organization
wt          Weight
                                       XI

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                             1.  EXECUTIVE SUMMARY

       This document describes a methodology and associated computer model, SLDGFILL
(sludge-only landfill or surface disposal),  for assessing the risk to humans of pathogens from
disposal of treated municipal sewage sludge.  The disposal of municipal sludge, produced
annually in millions of dry metric tons, is a growing problem.   Pathogenic organisms  may
become concentrated in sludges during treatment processes, posing a potential human health risk
when receptors are exposed.
       The purpose of the SLDGFILL model is to determine the probability ofinfection of a
human receptor from pathogens in a sludge-only landfill (monofill) or in surface disposal sites.
The ultimate objective is to assist the U.S. Environmental Protection Agency (EPA) in its
technical criteria development and regulatory activities, but the immediate uses include (1) using
the model as a research and risk assessment tool to illustrate information gaps and research needs
and (2) applying the model in performing  actual pathogen risk assessments.
      , The exposure pathway addressed by the SLDGFILL model is infiltration from the sludge
disposal site to groundwater and subsequent ingestion by a human receptor of groundwater from
a drinking-water well.  The definition of the human receptor does not include workers exposed
in the production,  treatment, handling or transportation of sludge.  This model is geared toward
the protection of the general public, but using infection rather than illness as the measure of risk
results in a conservative approach designed to protect sensitive subpopulations.  It is assumed
that workers can be required to use special measures or equipment to minimize their exposure
to sludge-borne contaminants.
       In the SLDGFILL model, quantity of treated sludge and other parameters specific to the
disposal site are entered by the user.  Pathogen parameters required for  SLDGFILL include
(1) density  of pathogens  in treated municipal sewage sludge destined for landfilling or surface
disposal; (2) infectivity; (3) inactivation rates in sludge, soil and groundwater; and (4) dispersion
or transport in the  environment. Because many factors affect the density of pathogens in sludge,
a wide range of densities has been reported for each type of pathogen found in sludge. These
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densities in sludge (liquid, dewatered or dry wt) may be summarized as follows:
Bacteria      1.4 X10"2 - 107 organisms/100 mL
              5xlQ-2 - 8.5x10* MPN (most probable number)/g
              ~2 - 9X106 CPU (colony-forming units)/g
Viruses       0 - 260 particles/g
              1.3 - 410 PFU (plaque-forming units)/100 mL
              0.1- <2.3PFU/g              .
              0-19 MPNCU (MPN of cytopathogenic units)/100 mL
              0.3-26  TdD50 (tissue culture infectious dose for 50% response)/g dry wt
Helminths     < 10 - 11,000 ova/kg dry wt
Protozoa      0 - 38,700 cysts/g dry wt
              70 - 30,000 cysts/L
       The range of reported minimum infective doses  for pathogenic bacteria is  10  - 1011
organisms; for viruses,  the range is 9 X Ifr1 - 9 x 104 virus particles, 2 x 10'1 - 5.5 x 106 PFU, or
1 - 1 XlO7'6 TCID50; for protozoa, the range is 1 - 100 cysts; and for  helminths,  1 egg has been
known to cause infection.
       For the model, survival of pathogens in sludge,  soil and water is presented in terms of
inactivation rate constants (Iog10 day1).  The most important of the factors that affect pathogen
survival in sludge, soil and water are: temperature, survival increasing with lower temperatures;
moisture, survival increasing with conditions that encourage moisture  retention, such as clay soil
or high rainfall; and pH, survival enhanced at median values (pH 5-8). Because of these factors
affecting survival, inactivation rate constants based on experimental data may differ by several
orders of magnitude,  even for a  specific pathogen.  In general, survival rates for bacteria range
from  1.6xia10/day to  0.96/day and those for viruses  range from 2xl04/day to 0.996/day.
Helminths have been reported to persist for up to 15 years in soil,  and protozoan cysts have
survived from < 1  day to over a year in soil.  Thus, the ranking of pathogen persistence in the
environment, from longest to shortest, is helminth eggs, viruses, bacteria and protozoan cysts.
       The depth to the groundwater presents the greatest barrier to the  transport of pathogens
and,  hence, to exposure and risk.  Filtration and adsorption  are the  processes responsible for
limiting pathogen transport through the unsaturated zone.  The size of the organism,  therefore,
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determines which pathogen will be transported the greatest distance.  In general,  viruses, the
smallest of the pathogens considered, have the potential to travel farther in the environment.
Large particles like helminth eggs and protozoan cysts typically do not migrate into groundwater
because of the physical barrier provided by the soil, unless there are vertical cracks or fissures.
Due to their persistence,  potential for  transport and low infectious dose, viruses seem  to
represent the worst case when estimating human health risk from landfilling of sewage sludge.
       The SLDGFILL model for pathogen risk assessment was run  with many combinations
of input parameters to simulate the transport  of sewage sludge pathogens from a landfill and
from a surface disposal site to a nearby drinking-water well. The subsequent risk of infection
to humans who drink from the well was estimated for each  run.  The probability of infection is
calculated using a beta-Poisson model.  Conservative exposure assumptions include a drinking
water  consumption rate of 2 L/day and  parameters describing  highly  infective pathogens.
Projections  by the model predict that  the risk of infection  from  ingestion of bacteria  in
groundwater is not significant even at 50 m from the sludge source. In contrast, viruses in well
water downgradient from a surface disposal site present a potentially significant health hazard
to consumers.
       The  parameters to which the SLDGFILL model are most sensitive are resuspension
coefficients, which describe the adsorption of pathogens to sludge and soil particles.  Other
parameters to which the model is sensitive are infective dose,  pathogen density in sludge and
inactivation rate in water.  Data on infective doses are scarce, making further research necessary
for reliable  use of the model to predict health risks.  It is likely that  viruses present a greater
health  risk because they are  expected to have a lower minimum infective dose and are more
readily transported through soil.
       Future research should be oriented toward satisfying the following information needs to
allow more realistic modeling of human health risk from pathogens in  landfilled and surface-
disposed municipal sludge:
       •      field data on subsurface transport, in both the saturated and unsaturated zones, of
              bacteria and viruses;
       •      inactivation rates of pathogens under field conditions in sludge,  soil and water;
       •      solids-to-water suspension factors applicable to sludge-and soil-bound pathogens;

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leaching characteristics of sludge-bound pathogens;
interaction of factors affecting pathogen resuspension from sludge and soil; and
parameters needed to describe infective doses of selected indicator species and
strains of pathogens in sludge.
                             1-4

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                     2. INTRODUCTION AND DESCRIPTION
                   OF GENERAL METHODOLOGIC APPROACH
2.1.   PURPOSE AND SCOPE
       Pathogenic organisms present in municipal sewage sludge pose potential health risks that
must be addressed in the evaluation of sludge management (disposal/reuse) options.  As a part
of its regulatory function, the U.S.  EPA develops nationally applicable technical criteria for
sludge disposal and reuse based on the potential for adverse health impacts from the sludge.
These  criteria may regulate concentrations of pathogens in the sludges,  as well as regulating
other factors within the management practices, such as rates of disposal  and process controls.
Current sludge disposal and reuse practices include land application, landfilling, incineration and
surface disposal.  To derive regulatory criteria for pathogens in  sludge,  the  U.S.  EPA's
Environmental Criteria and  Assessment Office  is developing a series of methodologies for
assessing  health risks resulting from land application, landfilling (monofilling) and surface
disposal of sludge.  This document, which is one in that series, describes a methodology and
computer model for evaluating the potential risk to humans from pathogenic microorganisms
following landfilling or surface disposal of municipal sewage sludge.
       With increasing concern about the importance of uncontaminated groundwater, evidenced
by aquifer and well-head protection zones and the proposed Draft Groundwater Disinfection Rule
(U.S.  EPA,   1992), modeling  risk of contamination by pathogens from sludge  becomes
economically valuable.  Better predictive ability concerning pathogen risk allows disposal of
sludge by methods that protect human health without requiring levels of treatment beyond what
is needed.  For example, a knowledge of the  relative significance  of  pathogen densities in
sludge, pathogen viability during transport in the subsurface environment and what constitutes
a sufficient distance to groundwater wells (setback distance) can be used to design a sludge
landfill or surface disposal site whose operation  is not likely to adversely affect human health.
       The model, SLDGFILL, described in this document calculates the probability of human
infection from pathogens in drinking water from a well near a municipal  sewage sludge landfill
or surface disposal site. This methodology and model, based on the "Sandia Model" (U.S. EPA,
 1980), were  modified and  their development  has been  continued  by  Science Applications
                                          2-1

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 International Corporation, Oak Ridge, TN.  Previous volumes in this series address pathogen
 risk from land application of sludge (U.S. EPA, 1989c,d;  1990b; 1991a,b).
       This report is not concerned with chemical contaminants in  municipal sludge since the
 U.S. EPA is examining that issue separately (U.S. EPA, 1989b).  Also, risks associated with
 the treatment, transport, handling and accidental release of sludge are not addressed in this
 document. Codisposal of sludge with solid refuse is regulated under the Resource Conservation
 and  Recovery Act  (U.S.  EPA,  19895); no codisposal practices will  be considered in this
 methodology and model development.
       The SLDGFILL model is complex enough to represent the major factors determining
 transport and inactivation of pathogens migrating from a sludge landfill.  Yet the model is simple
 enough to avoid the impractical complexity that requires numerous and often unavailable input
 parameters.  The model runs on a personal computer, and data can be added and modified with
 no knowledge of programming languages. Although all the information required for an accurate
 risk  assessment is not yet available,  additional data can be easily incorporated  into the current
 model, thus improving the model's value and predictive ability.
       Use of the model to predict acceptable distances to groundwater wells  or outcrops (by
 running the model iteratively) and implementation of regulatory controls to achieve an acceptable
 risk  level are possible uses  of the model to protect human health.  When the groundwater
 disinfection  rule is implemented, local utilities may use a  pathogen  risk  model such as
 SLDGFILL to indicate adequate separation between a pathogen  source and a groundwater well,
 thereby eliminating or limiting the need for groundwater disinfection.
2.2. DEFINITION AND COMPONENTS OF RISK ASSESSMENT
       According to the National Academy of Science (NRC, 1983), risk assessment is "the
characterization of the potential adverse health effects of human exposures  to environmental
hazards."  Risk management, by contrast, is "the process of evaluating alternative regulatory
actions and selecting among them" by considering available technology, costs and other nonrisk
factors.
       The process of risk assessment was  subdivided into four working components by the
National Academy of Science (NRC,  1983).  (1)  Hazard identification is "the process of
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determining whether exposure to an agent can cause an increase in the incidence of a health
condition...." (2) "The process of characterizing the relation between the dose of an agent... and
the incidence of an adverse health effect in exposed populations and estimating the incidence of
the effect  as a  function  of human  exposure to the agent" is dose response  assessment.
(3) Exposure assessment is "the process of measuring or estimating the intensity, frequency, and
duration of human exposures to an agent...or of estimating hypothetical exposures that might
arise...."  (4) "The process  of estimating the incidence of a health effect...by combining the
exposure and dose-response  assessments" is  risk characterization.  The definitions of hazard
identification and dose-response assessment have been expanded by the U.S. EPA'to include the
nature and severity of the toxic effect as well as the incidence (U.S. EPA, 1989a).

2.3.  RISK ASSESSMENT IN THE METHODOLOGY DEVELOPMENT PROCESS
       The definition of the  management practice is the first step in the development of a risk
assessment methodology.  This methodology and model deal with the landfilling and surface
disposal of municipal sewage sludges, the products  of typical wastewater treatment processes.
Surface disposal  refers to disposal of municipal sewage sludge or biosolids on dedicated sites in
waste "piles."  A surface disposal site is an area of dedicated land on which the sewage sludge
remains for at least 1 year or longer (U.S. EPA, 1989e).  Surface disposal may also include
surface impoundments, or  sludge lagoons.  Landfilling has been defined as the burial of sludge
with a soil cover that exceeds the depth of the plow zone (Walsh, 1978).   The management
practices addressed include trench landfills, area fills, diked containment landfills, dedicated-site
surface disposal  and  sludge lagoons. These practices are described more fully in Chapter 3.
       The following information is required by the SLDGFILL model for risk assessment for
pathogens in municipal sewage sludges:
       •     the  sludge  reuse  or disposal option and the conditions of the  application
             (frequency,  quantity, etc.), i.e., specific sludge management practices;
       •     the  types of pathogens present in  the  sludge,  their  numbers  (level or
             concentrations), their  survival  capabilities  and  parameters describing their
             virulence; and
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       •      the fate of the pathogens in the environment, including the route of exposure to
              human receptors, and the magnitude and duration of the exposure.
All of these information requirements and the data available to satisfy them are addressed in this
report.
       2.3.1.  Hazard Identification and Dose-Response Assessment. Infection and disease,
the adverse effects on human health resulting from exposure to pathogens, have been identified
as hazards in the risk assessment process. For purposes of discussion, sewage-borne pathogens
are generally divided into four or five major groups: bacteria, viruses, protozoa, helminths and,
sometimes, fungi.  The World Health Organization (WHO, 1981), Kowal (1982,1985) and U.S.
EPA (1988a) document the presence of bacterial, viral and parasitic (protozoan and helminthic)
pathogens in municipal sludges. Fungi are generally not significant pathogens in sewage except
in relation to composting of sludge.  Most pathogenic microorganisms found in sewage cause
gastroenteric disease of some form, although secondary effects of the organisms  may also be
important (U.S. EPA, 1989c). The pathogens commonly found in  municipal sludges are listed
in Table 2-1 and described in Chapter 4.
       The pathogenic composition of sludges varies both in type and concentration, depending
on many factors including the degree of urbanization of a community, the rate of disease in it,
population sanitary habits, population density and season of the year (Fradkin et al., 1985). For
this reason, achieving a quantitative hazard  assessment for microbial pathogens in  municipal
sludge is difficult.  The  U.S. EPA  (1988a; 1990b;  1991a,b), Reimers et al. (1981; 1986),
Pederson (1981) and Yanko  (1988) present extensive surveys of reported levels of pathogenic
bacteria, viruses and parasites in treated municipal sludge. Table 2-2 presents a condensed
summary of those data.
       Because of the lack of available data to support quantitative assessments for all pathogens
identified in  sludges, representative organisms were selected by the U.S.  EPA  to act as
surrogates  in the risk assessment process. In addition to their  known presence in sludge and
their ability to  cause human disease, selection criteria for these surrogates included adequacy of
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                 Table 2-1. Pathogens of Concern in Sewage Sludges
            Type
Organism
Bacteria
                                Campylobacter jejuni
                                Escherichia coll (pathogenic strains)
                                Leptospira spp.
                                Salmonella spp.
                                Shigella spp.
                                Vibrio cholerae
                                Yersinia enterocolitica
                                Yersinia pseudotuberculosis
Viruses
                                Adenovirus
                                Astrovirus
                                Calicivirus
                                Coronavirus

                                Enteroviruses
                                       Coxsackievirus A
                                       Coxsackievirus B
                                       Echovirus
                                       New enteroviruses
                                       Poliovirus

                                Hepatitis A virus
                                Hepatitis E virus
                                Norwalk virus and other small round structured viruses
                                Parvovirus  and parvovirus-like agents
                                Reovirus
                                Rotavirus
                                          2-5

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Table 2-1. (continued)
Type
Protozoans
Helminths
Fungi
Organism
Balantidiwn coli
Cryptosporidiwi spp.
Dientamoeba fragilis
Entamoeba histolytica
Giardia lamblia
Isospora spp.
Toxoplasma gondii
Ancylostoma duodenale
Ascaris lumbricoides
Echinococcus spp.
Hymenolepis nana
Taenia sp.
Toxocara spp.
Trichuris sp.
Aspergillus fiunigatus
Candida albicans
Cryptococcus neoformans
Epidermophyton spp.
and Trichophyton spp.
Trichosporon spp.
Phialophora spp.
Source: U.S. EPA, 1988b; Gerba, 1983a; Thurn, 1988; Hurst, 1989.
         2-6

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Table 2-2.  Densities of Pathogens in Treated Sludge
Organism
Range of Reported Densities
Bacteria
Eschenchia coll
Salmonella
Shigella
Yersinia
0.014-107 number/100 mL
0.05-10,000 MPN/g
IxlQS-S.SxlO6 CFU/g
<0.6-lxl07 number/100 mL
> 0. 1-4.9 XlO3 MPN/g dry wt
< 0.1-85,000 MPN/g
> 2- < 24 CFU/g
>20 CFU/g
106-109 number/g wet wt
<0.1-2.5xl06 MPN/g
2X105 CFU/g
Viruses
Enteric viruses
Picornavirus
Enteroviruses
Echovirus type 7
Reoviruses
0-260 units/g
0.007-0.04 PFU/mg TSS
0-19 MPNCU/100 mL
<2.3 PFU/g
1.3-410 PFU/100 mL
0.3-260 TCID50/g dry wt
0.1 PFU/g
6-17 PFU/100 mL
Helminths
Ascaris
Nematodes
Toxocara
Trichuris
565-9600 ova/kg dry wt
100- 1 1 ,000 ova/kg dry wt
280-1730 ova/kg dry wt
< 10-7700 ova/kg dry wt
Protozoa
Cryptosporidium
1250-38,700 oocysts/g dry wt
140-4000 oocysts/L
                        2-7

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                               Table 2-2. (continued)
Organism
Giardia
Protozoa
Range of Reported Densities
70-30,000 cysts/L
0 cysts/kg dry wt (in D&M sludge)
CPU = colony forming units (number of viable bacteria capable of forming colonies on a
particular medium)
D&M = distribution and marketing
MPN = most probable number (not an actual enumeration but an index of bacteria that
more probably than any other number would give the laboratory result)
MPNCU = most probable number of cytopathogenic units (most probable number of
particles capable of causing cytopathic effects as measured by areas of clearing in a cell
culture)
PFU = plaque forming units (number of particles capable of causing cytopathic effects as
measured by areas of clearing on a cell culture sheet)
TCn>50  = median tissue culture infective dose (that quantity of a cytopathogenic agent
(virus) that will produce a cytopathic effect in 50% of the cultures inoculated)
TSS = total suspended solids
Sources: U.S. EPA, 1988b; Pedersen, 1981; Yanko, 1988; Rao et al., 1986b; Kowal,
1985; Jakubowsld, 1990; Sorber and Moore, 1987.
                                        2-8

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available data, known minimum infective dose, hardiness outside the human host, survivability
typical of other group members  and known routes of infection.   Representative pathogens
selected by the U.S. EPA were Salmonella spp. for enteric bacteria, enteroviruses for enteric
viruses,  Entamoeba  histofytica  and  Giardia lamblia  for  parasitic  protozoans,  Ascaris
lumbricoides and Ascaris Iwnbricoides var. swan  for helminths and Aspergillus fumigatus for
fungi.  The three pathogens dealt with in the current version of the model are Salmonella spp.,
representing bacteria; enteroviruses, representing the enteric viruses; and Ascaris lumbricoides,
representing both helminths and protozoa.  As more data become available on other pathogens,
pertinent parameters such as infectious dose and inactivation rate may be  modified to represent
other pathogens such as Giardia or rotaviruses.
       Dose-response assessment examines the relationship between the occurrence of infections
and disease and the exposure to pathogens.  The "dose" of pathogens is  the number of viable
organisms to which  a host is exposed, and  dose response is (1) no infection, (2) subclinical
infection (without apparent illness) or (3) infection with illness.  The incidence of disease in a
population is likely to increase with an increase in the concentration of pathogens to which the
population is exposed.
       Risk assessment involves understanding the dose-response relationship for each pathogen
identified in  sludge.  Dose response for a specific pathogen is dependent on the number of
organisms required to produce infection or disease in the  host.  Thus, because of variability
among hosts, there are no clearly defined exposure levels that always result in infection, even
for a given species or strain.  Many factors affect the host response, including the virulence or
pathogenicity of the organism, the length of exposure and host characteristics such as site of
exposure, degree of immunity, age and general health and prior treatment with antibiotics. The
virulence of a pathogen depends to some extent on the susceptibility of the host population and
also on the ability of the pathogen to overcome such host defenses as inflammatory and immune
responses.  Blaser and Newman (1982) observe that organisms that are host-adapted to humans
(humans are the only host) may have lower infective doses than nonadapted strains.
       The U.S. EPA (1992) recognizes  that while one infectious unit, such as a single virus
particle or Giardia cyst, can cause infection,  much larger doses,  even  orders of magnitude
                                          2-9

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larger, may be needed to cause disease.   Although a much higher number of organisms or
infectious particles may be required to produce illness instead of infection, using infection as a
detection endpoint would protect more susceptible subpopulations.  In other words, avoiding
infection is a conservative means for avoiding disease (Regli et al., 1991).
       Dose-response data that are available for some bacteria, viruses  and parasites are
summarized in Table 2-3.  The minimum infective dose, the lowest dose that will infect any
exposed individual, has been estimated for a few microbial pathogens.  Estimated frequency
of infection and disease related to probable exposure levels are drawn from epidemiological data,
or,  in some cases,  are  based  on the exposure  of volunteers to  known  doses.   Virus
concentrations can also be determined by measuring cytopathic effect by infecting tissue cultures
(U.S. EPA,  1990b; 1991a,b).
       2.3.2.   Exposure  Assessment.   The  exposure assessment  step  begins  with the
identification of pathways of potential exposure,  that is, migration routes of pathogens from or
within the disposal/reuse site to a target organism or receptor. In this pathogen risk assessment
model, humans drinking  groundwater are  the receptors of concern.  The potential exposure
pathways, described more fully in Chapter 5, include suspended particulates (aerosols), surface
water  runoff and groundwater.  Of the possible routes for pathogens  to reach the human
receptor, surface water runoff and paniculate suspension can be controlled by the use of good
management practices, which are defined in Chapter 3 (U.S. EPA, 1989b).  Therefore, only
groundwater remains a pathway of concern for pathogens in this model.
       Human exposure to sludge or contaminated groundwater can be highly variable. Ideally,
quantifying  exposures  of individuals would best assess human risk for any given pathway.
However, difficulties of estimating the distributions of each of the parameters involved in the
exposure calculations and modeling population distributions and behaviors in the vicinity of the
disposal site preclude quantifying the distribution profile for each exposure pathway in this
model. By varying the parameters describing exposure, the model user may gain an appreciation
for the range of risks that would potentially be encountered by exposed individuals.
       Default values,  describing reasonable, worst-case assumptions,  are provided for testing
the model.  The compounding of worst-case assumptions, however, can lead to improbable
                                         2-10

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Table 2-3.  Dose-Response Data*
Organism
Infective Dose
Range
Bacteria
Escherichia coli
Salmonella (various
strains)
Shigella
Vibrio cholerae
104
1Q2b
10-102
103
lOMO10
lOMO10
lOMO5"
10-109
K^-IO11
Viruses
Echovirus 12
Poliovirus
Rotavirus
HID50 919 PFU
HIDj 17 PFU predicted
1 TCID50
< 1 PFU
HID50 ~10ffuc
HID^ 1 ffu estimated
17-919 PFU
4xl07 TCID50 (infants)
0.2-5.5 X106 PFU (infants)
9xlO-1-9xl04ffuc
Parasites
Entamoeba coli
Cryptosporidiwn
Giardia lamblia
Helminths
1-10 cysts
10 cystsd
1 cyst (estimated)
1 egg
1-10 cysts
10-100 cysts"
NR
NR
•Source: Kowal, 1985.
b Seattle Metro, 1983.
"Wardetal., 1986.
d Casemore, 1991.
HID = Human infective dose.
TCID50 = Tissue culture infectious dose for 50% response.
PFU = Plaque forming units.
ffu = Focus-forming units. .
NR = Not reported.
             2-11

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            results.  Therefore, the key to effective use of this model is a careful and systematic examination
            of the effects of varying each of the input parameters,  using estimates of central  tendency and
            upper-limit values to gain an appreciation for the variability of the result.
                  2.3.3.  Risk characterization.  Risk characterization consists of combining the results
            of the exposure and dose-response assessments  to estimate the probability of a  health effect.
            Risk assessments ordinarily proceed from source to receptor.   That is,  the source, or sludge
            disposal/reuse practice, is first characterized, and contaminant movement away from the source
            is then modeled to estimate the degree of exposure to the human receptor. Human health effects
            are then predicted based on  the estimated exposure and dose-response relationships.  This
            computer model sums the exposures of a human receptor to pathogens daily and  computes the
            probability of the human receptor receiving an exposure exceeding an  infective dose.
            2.4. POTENTIAL USES OF THE MODEL IN DETERMINING RESEARCH NEEDS
                   One of the values of the pathogen risk assessment computer model described herein is
            its ability to identify areas in which additional research is needed. For example, a major hurdle
            in any risk assessment is estimating exposure by a variety of routes or pathways to a population
            that varies according to activity patterns.  The use of a conservatively defined human receptor
            is based, at least in part, on the difficulty in estimating exposure of a population to a changing
            level, or dose, of pathogens. Information on infectious dose for most pathogens is limited, and
            distribution of pathogens in soil or groundwater is often unknown. This model assumes random
            distribution of pathogens in environmental media, but data are not available to  verify this
            assumption. Further research on pathogen exposure pathways and infectious dose levels would
            facilitate the predictive accuracy of this model and its successors.
                   Another obvious data gap, illustrated by this methodology and model development, is the
            degree of  survival and transport of pathogens in the environment.  Information on the fate of
            pathogens in sludge,  subsurface soil  and groundwater is extremely limited.  The concentration
            and survival rates of pathogens  leaching through soil into groundwater are unavailable  for
            viruses, protozoa and helminths, while bacterial concentration data are few (U.S. EPA, 1988a).
            More data are needed concerning the transport of pathogens through sludge and through  the
            unsaturated and saturated zones.
                                                     2-12
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       Conducting a sensitivity analysis  of the model can reveal  areas in which additional
research is crucial, as well as areas of low priority.  Identifying (1) particular features of sludge
disposal practices,  (2) properties of the pathogens or (3) characteristics of the model that have
a large impact on risk projections can highlight areas in which more research would significantly
improve the predictive capability  of the model.  In contrast, identifying input parameters to
which the model  is not sensitive shows that research into more precise values for those
parameters has a low priority.
       Results of risk projections  may be unexpected,  counterintuitive or contrary to practical
experience or good scientific judgement.  Unrealistic model outcomes or unexpected sensitivity
or insensitivity to input parameters indicates the need  for field validation of those results  and
perhaps additional research on development and refinement of the model. If suitable field data
on pathogen survival and transport become available, the many different models for groundwater
transport, including SLDGFILL, can be compared to determine which model features are the
most important,  which ones provide sufficient accuracy and which ones need further refinement.

2.5.  POTENTIAL  USES OF THE MODEL IN RISK MANAGEMENT
       Risk assessment provides the starting point for risk management considerations and the
foundation for regulatory decision-making. While the risk assessment is not the sole determinant
for regulatory decisions, it provides important information to be evaluated along with societal
concerns  (costs, benefits, acceptability).
       The computer model described in this document can  be used to provide information for
making and  justifying regulatory decisions regarding  sludge landfill management practices.
Risks associated  with different  regulatory  strategies-establishing  acceptable  distances to
groundwater wells or outcrops, requiring certain thickness of the unsaturated zone or depth to
groundwater, specifying conditions of the sludge applications (frequency, duration), and limiting
initial pathogen  concentrations in sludge-could be compared using the SLDGFILL model.  The
model would help to identify conditions or actions with the greatest impact on reducing the
human health risk.   Risk management efforts could  then be  focused  on  these actions and
conditions to make decisions and establish regulations that  will have the greatest influence on
protecting human  health.
                                          2-13

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       In addition to potential use by risk managers making regulatory decisions, the computer
model may be useful for regulators and permit reviewers evaluating proposed sludge landfill
sites. Where hydrogeologic conditions of the proposed site are well known, the computer model
can be used to estimate the transport of pathogens to a groundwater well and the concentration
of pathogens in the drinking water source.
       The model  could also be  used to  evaluate  proposed regulations  and treatment
technologies.  Risk-based regulations proposed by U.S.  EPA (1992) for groundwater disinfection
can be evaluated to determine what technology might be used to achieve the proposed exposure
limits for groundwater potentially contaminated  by leachate from  the sludge landfill.  For
example, alternative disinfection methods may be more effective against different pathogens.
By comparing the risks from the different pathogens after their numbers have been reduced by
projected treatments, the treatments providing the greatest reduction in risk should be identified.
Utilities could also use the model to illustrate  sufficient separation between  a pathogen source
and a groundwater source or wellhead (and thus sufficient health protection), thereby avoiding
the need for unnecessary groundwater disinfection.
       Over time, as the model is refined by a better understanding of the fate of pathogens in
the environment, pathogen inactivation rates and  the minimum infective dose in humans, the
importance of the model as a management tool will continue to increase.

2.6.    LIMITATIONS OF THE MODEL
       In several cases, assumptions have been simplified to prevent the model from becoming
too cumbersome for practical  application.  If the user were required to  input all  possible
variables, the time required to collect the information and enter it before a model run would be
prohibitive.  As a result, the flexibility of the model has been restricted to some extent.
       The predictive value of the model depends on reliable input parameters and on the
accuracy with which initial pathogen concentrations are determined.   Municipal sludges are
highly variable mixtures of residuals and by-products of the wastewater treatment process, and
the distribution of microbial types in sludge  will depend in part on  the competition among
microbes. The model does not address competition among microorganisms.  Also, variations
                                         2-14

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in sewage may result in varying efficacy of treatment, so that the concentration of a particular
pathogen cannot be precisely predicted.
       Variability in weather or disposal practices is likely to result in differing rates of growth
or die-off in sludge,  soil, air and water.  Although the model does not allow for growth as
currently configured, the  die-off term (inactivation parameter) could be used to model growth;
however, growth of gastroenteric bacteria, such as some Salmonella strains, is unlikely to occur
in soil beneath a sludge landfill or surface disposal site.  Exponential die-off rates are assumed
to apply until the end of the practice, even though  under certain circumstances linear die-off
rates may be more appropriate; consequently, the modeled rates may not be completely realistic.
The model does not allow for changes in inactivation rate or variability in groundwater flow.
       The model, as currently configured, is limited to one-dimensional, advection/dispersion
transport with retardation and die-off, and it only accommodates one pathogen type per model
run.  As a result,  the infection algorithm is simplified.
                                           2-15

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                   3.  DESCRIPTION OF DISPOSAL PRACTICES

       Municipal sewage sludge, a mixture of organic and inorganic semisolids from human
activities, is  a by-product of the physical,  biological and chemical treatment of municipal
wastewater in sewage treatment plants.  The physical removal of settleable solids from raw
wastewater (i.e., primary treatment) produces sludges containing 3-7% solids; further removal
of additional solids may be accomplished by the biological and chemical methods of secondary
wastewater treatment.   The resultant primary and  secondary  sludges may be subjected to
treatment processes designed to reduce sludge volume, improve its workability and lower its
potential environmental and health risks.  Such treatments include stabilization processes (for
example, aerobic and  anaerobic  digestion,  composting and lime treatment), conditioning,
disinfecting, dewatering, thickening and drying  (Lu et al., 1982).
       The disposal of municipal sludges, produced annually in  millions of dry metric tons, is
a growing problem.  Pathogenic organisms become  concentrated  in sludges during treatment
processes, posing a human health risk that affects disposal options and practices (Lu et al.,
1982).  Decisions on the final disposal of sludge are  based on the  characteristics of the sludge
(e.g., solids content, stability, quantity, toxic compound and pathogen content), local conditions
(e.g., site hydrogeology, soil characteristics,  climate) and governmental regulations.  Because
ocean dumping of sludge is restricted, disposal usually means  some form of sludge application
to land, including application to agricultural and reclaimed land, distribution  and marketing
programs, surface disposal (e.g., lagooning) and landfilling (Corbitt, 1990).
       The scope of sludge disposal  practices  addressed by  the SLDGFILL model includes
sludge-only landfilling and surface disposal. The model does not address co-disposal of sludge
with refuse, nor does it include incinerated or composted sludges.

3.1.   SURFACE DISPOSAL
       As explained in the U.S. EPA's final rules for use or disposal of sewage sludge, surface
disposal is a term that is used to describe "what are essentially piles of sludge left on the land
surface. . ." (U.S. EPA, 1993).  A surface disposal site is an area of land on which the sewage
sludge has remained for at least 1 year or longer  and, typically, on which no daily or final cover
                                          3-1

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is established on the sewage  sludge (U.S.  EPA,  1989e).   Surface disposal is  also used to
characterize sludge lagoons. According to U.S. EPA (1990a), surface impoundments or lagoons
may be created  by  waste treatment plants for the  long-term storage or treatment of sludges.
Storage and treatment lagoons, such as those used for drying, may accumulate bottom layers of
sludge that remain in place for years before being removed.  A lagoon, an earth basin created
for untreated or digested sludge, may be any shape but is usually rectangular.  According to
Corbitt (1990),  drying lagoons are typically dikes with an interior slope of  1:3  vertical to
horizontal, a capacity of 35-38 kg/m3/yr, a depth of 0.15-1.2 m and  a depth to groundwater of
> 1.2 m.  Lagooning is not usually considered a method for permanent disposal because lagoons
have both odor and  insect vector disadvantages. When removal of sludges from impoundments
becomes impractical or satisfactory disposal  methods are not identified by the waste treatment
facility, these impoundments may become permanent disposal sites.   Although not  technically
disposal facilities, lagoons for long-term storage of sludge are included in this surface disposal
model because (1) sludge stored in lagoons may pose health or environmental risks similar to
permanent disposal  facilties, and (2) future plans for sludge removal  from storage lagoons may
change, resulting in permanent disposal (U.S. EPA, 1990a).

3.2.   LANDFILLING
       Landfilling,  the method most widely used for disposal of sludge (Corbitt, 1990), has been
defined as the burial of sludge with a soil cover that exceeds the depth of the plow zone. Sludge
may be deposited in sanitary landfills with other refuse  (co-disposal) or placed in sludge-only
(monofill)  trench landfills, area  fills  or  diked  containment landfills.    Although sludge
stabilization prior to landfilling is not required  in all states, some degree of stabilization  is
recommended for sludges before disposal by any landfilling method (Walsh, 1978).  Stabilization
processes are important in reducing pathogen levels  and controlling putrescence;  some also
dewater and reduce sludge mass.  To prevent the contamination of ground and surface waters,
landfill leachate and runoff are typically controlled by  providing adequate surface drainage,
natural attenuation,  the use of liners and by collection  and treatment.   Monitoring wells are
typically used to establish baseline groundwater quality,  for surveillance during operation and
to monitor after  closure (Corbitt, 1990).
                                          3-2

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       In trench filling, sludge is confined to excavated trenches, trench depth depending on side
wall stability, distance to groundwater and the limitations of the equipment  used.  Trench
landfills are recommended only for areas with sufficient depth to groundwater and bedrock and
with ground slopes of < 10-20%. .Soil is  not used for a bulking agent, and hauling vehicles
usually dump sludge directly into the trench (Walsh, 1978). Narrow trenches  <3 m (10 ft) are
used for  a single layer of sludge, typically covered by 0.6-1.2 m (2-4 ft) of soil.  Sludges with
solids content < 15% will not support cover without the addition of a soil bulking agent, which
is generally not cost effective (Walsh, 1978).  Thus, the recommended minimum solids content
for narrow  trenches is 15-28%,  depending on the width. Trenches wider than 3 m (10 ft)
require a sludge solids content > 20-28%  (Corbitt, 1990).  Sludge layers may alternate with
layers  of soil; soil cover is normally 0.9-1.5 m (3-5 ft) depending on the type equipment to be
used.  The installation of liners is impractical for narrow trenches, but liners are useful to
protect groundwater under wide trenches (Lu et al., 1982).
       The term  area fill applies to disposal on the  surface of the ground in layers or in a
mound.  Liners are useful with these methods to protect groundwater,  and surface drainage must
be controlled.  Area fill layer methods can handle sludges with solids content as low as 15%,
but mound methods  require sludge solids of at least 20%.  In these methods, soil is mixed with
sludge as a bulking agent to absorb  moisture, improve workability and stabilize and improve
bearing capacity for operation of equipment.  Typically,  sludge layers of —0.3-0.9 m (1-3 ft)
for layer fills and ~ 1.8 m (6 ft) for mound fills alternate with layers of sludge-soil mixture.
Recommended final soil cover thickness is 0.3  m (1 ft) for mound fills and 0.6-1.2 m (2-4 ft)
for area fills (Corbitt, 1990).  Area fill and diked containment type landfills may be used in
areas of shallow groundwater and bedrock and medium to steep terrain (Walsh, 1978).
       At diked containment landfills, earthen dikes have been constructed creating enclosures
above the  original  soil. surface, thereby  controlling surface  drainage.   Often used  under
conditions such as a high water table or shallow bedrock, this type of disposal is useful for
sludges of at least 20% solids.  Soil bulking is generally not used.  Sludge lifts, or layers, of
1.2-3  m (4-10 ft) may alternate with soil layers, with final soil cover of 0.9-1.5 m (3-5 ft)
(Corbitt, 1990).   The weight of the applied sludge and soil  at  the typical depths of these
                                           3-3

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containments (3-9 m or 10-30 ft) may force moisture from the sludge into the surrounding walls
and the soil below the containment, necessitating liners or other leachate controls (Walsh, 1978).
                                         3-4

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                      4.  IDENTIFICATION OF PATHOGENS

      Parameters  for microbial pathogens  required  for  the  SLDGFILL model include
(1) density of  pathogens in  treated municipal  sewage  sludge  destined for  landfilling;
(2) parameters describing minimum infective dose; (3)  inactivation rates in sludge, soil and
groundwater; and (4) dispersion or transport in the environment.  Summary data on pathogen
density in treated municipal sewage sludge and a compilation of minimum infective doses were
presented as Tables 2-2 and 2-3, respectively, in Section 2.3.1 as part of the discussion of
hazard identification and dose response. Inactivation rates are discussed in the following sections
within the description of each pathogen type.  Generally not available for pathogens in sludge,
die-off or inactivation rates for bacteria and viruses in soil and water are summarized in
Table 4-1.  Information  on dispersion  of pathogens  in  the environment  is limited  in  its
applicability to generating a rate of transport in environmental media. Although data supporting
the model parameter requirements are summarized,  a more complete  review  of current
knowledge on pathogens is presented in U.S. EPA (1990b;  1991a,b).

4.1.  PATHOGENIC BACTERIA
      Pathogenic bacteria are found in municipal wastewater and sewage sludge (WHO, 1981;
Kowal,  1982, 1985; U.S. EPA, 1988a,b; Pedersen, 1981; Feachem etal., 1983). Most of the
bacterial pathogens in sludge are enteric. Their natural habitat is the intestinal tract of animals
and  humans, and  they are  members of the  families  Enterobacteriaceae and Vibrionaceae.
Exposure commonly occurs by the fecal/oral route; disease outbreaks are often associated with
contaminated food or water.  Infection may result in either an asymptomatic carrier state or
disease, usually some form of gastroenteritis.  Some enteric bacteria may also invade the body
from the gut, causing generalized or localized infections.
      The U.S. EPA has classified pathogenic bacteria into two categories: those of major
concern and those of minor concern. Bacteria of major concern are those commonly found in
wastewater and sludges and resulting in disease to the general population.  Bacteria of minor
concern are opportunistic pathogens that cause disease only in debilitated or immunologically
compromised individuals.  Bacteria of major concern are listed in Table 4-2.  Some bacteria of
                                         4-1

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Table 4-1.  Pathogen Inactivation Rates in Soil and Water
Organism
Inactivation Rate Constant (Iog10 day"1)
Bacteria Soil
Escherichia coli
Salmonella
Shigella
0.015-6.39
0.0155-2.99
0.268-0.320 ...
Viruses Soil
Poliovirus type 1
Viruses
0.0017-0.7077
0.057-3.69
Bacteria Water
Campylobacter fetus
E. coli
Salmonella "
Shigella
Vibrio cholera
Yersinia entercolitica
0.156-0.890
0.0328-9.8
0.0255-3.01
0.0814-0.422
1.00
0.0228-0.0382
Viruses Water
Coxsackievirus
Echovirus
Enteric viruses and coliphage
Poliovirus
Rotavirus
0.0039-0.2455
0.0039-0.628
0.174-0.374
0.0075-2.383
0.36
Sources: Sorber and Moore, 1987; Moore et al., 1988; Bitton et al., 1983; Hurst,
1988; Hurst et al., 1978; Reddy et al., 1981; Hurst et al., 1989; Yates et al., 1985;
Kutz and Gerba, 1988; Cubbage et al., 1979; Keswick et al., 1982.
                         4-2

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Table 4-2. Pathogenic Bacteria of Major Concern in Sewage Sludges
Organism
Campylobacter jejuni
Escherichia coli (pathogenic
strains)
Leptospira spp.

Salmonella paratyphi A,B, C
S. typhi
Salmonella spp.

Shigella sonnet, S. flexneri,
S. boydii, S. dysenteriae
Vibrio cholerae
Yersinia enterocolitica,
Y. pseudotuberculosis
Disease
Gastroenteritis
Gastroenteritis

Leptospirosis

Paratyphoid fever
Typhoid fever
Salmonellosis

Shigellosis (bacillary
dysentery)
Cholera
Yersiniosis

Nonhuman Reservoir
Cattle, dogs, cats, poultry
Cattle (E. coli tf 157-.H7)

Domestic and wild
mammals, rats
—

Domestic and wild
mammals, birds, turtles
— . •

—
Domestic and wild birds
and mammals
Source: Kowal, 1985; U.S. EPA, 1988b; Domingue, 1983.
                              4-3

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minor concern include: Bacillus cereus, Clostridiwnperfringens, Enterobacter spp., Francisella
tularensis, Klebsiella spp., Legionella pnewnophila, Listeria monocytogenes, Mycobacterium
tuberculosis, M.  avium  complex,  Pseudomonas  aeruginosa,  Staphylococcus  aureus  and
Steptococcus spp.
       Salmonella spp. and Shigella spp. are the most common bacterial pathogens in municipal
wastewater (Kowal, 1985). Although many Salmonella infections are symptomless, most of the
serotypes affecting humans produce acute but transient gastroenteritis (Feachem et al., 1983).
Direct human transmission of these serotypes is rare.  Although the Centers for Disease Control
reported only — 49,000 cases of salmonellosis during 1988, most cases go unreported, and there
has been a steady increase in incidence  over the past  35 years  (CDC, 1989).  Ingestion of
contaminated food or drink is the main cause of an estimated two million cases in the United
States per year (Domingue, 1983).  Animals, including poultry, farm animals, pets and rats and
mice, are an important reservoir of these organisms.   Gastroenteritis  from  salmonellosis is
serious only for infants or the elderly with underlying health problems.
       Other Salmonella serotypes, including S.  choleraesuis, S. typhi and S. paratyphi, invade
the tissues producing septicemia, typhoid fever (enteric fever) or paratyphoid fevers (Domingue,
1983). Food or water contaminated directly or indirectly from human excreta is the usual source
of infection of S. typhi; the primary source of infection of S. paratyphi is also humans, although
animals are a reservoir for the organisms.  In areas with high standards for sanitation and public
health, these diseases are not prevalent.   The mortality rate for paratyphoid is lower than  that
for typhoid; with the use of appropriate drugs, the mortality rate  for typhoid can be as low as
1-2%.
      Although the infective dose of Salmonella is reportedly relatively high, 105-108 organisms
(Kowal,  1985), such numbers may be easily achieved because some Salmonettae are capable of
significant regrowth in sludges or foodstuffs (Ward et al., 1984).  There is also some evidence
that infection with Salmonettae may occur at lower levels (Blaser and Newman,  1982; D'Aoust
and Pivnick, 1976). A wide range of densities of Salmonella in treated  sludge products has been
reported  (U.S. EPA, 1991a).
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       Members of the genus Shigella are a major cause of dysentery, producing diarrhea, fever,
vomiting and cramps (Feachem et al., 1983).  Although foodborne and waterborne outbreaks
have been reported, the usual mode of infection is the direct fecal/oral route under conditions
of poor hygiene and sanitation (Feachem et al., 1983).  The infection may be mild or severe,
depending on the health and age of the patient, the serotype of the organism and the infecting
dose.  Mortality for untreated cases of the severe form  may be as high as 25% but usually is
much lower.
       The infective dose for Shigella has been reported to be as few as  10-100 organisms
(Kowal,  1985).  Difficulties  in enumerating the organism  partially explain the fact that
organisms are seldom found in sewage even  when shigellosis is known to be present in the
community. Conventional treatments for sewage remove 90-99% of the organisms.  Although
data on the survival of Shigella in sludge treatment processes  are few, Feachem et al.  (1983)
conclude that the conditions of most processes will result in high rates of destruction.
       Feachem et al. (1983) suggest that Campylobacter is the  most common bacterial cause
of diarrhea in many countries, including the United States.  Stelzer and Jacob (1991) found that
raw sewage  and  river water  contained  1.05x10*  campylobacters/100 mL and typically
< 10 campylobacters/100 mL, respectively, but none was found in digested, conditioned sewage
sludge.  Incidence of campylobacteriosis is similar to  that of other enteric pathogens, with
contaminated poultry products,  unpasteurized  milk and  nonchlorinated drinking water serving
as the main vehicles.  Several large outbreaks of waterborne  campylobacteriosis involving
hundreds of people have been reported  (Stelzer and  Jacob, 1991).  Infection has resulted in
septicemia, meningitis, spontaneous abortion and septic  arthritis.
       The infective dose of Campylobacter has not been determined.  A recent U.S. EPA study
(Yanko, 1988)  found  no published  reports  of Campylobacter in sludge and  did  not find
Campylobacter in the final sludge products of 24 sludge treatment facilities examined. Although
the methodology for detecting the organism may have been inadequate, Yanko (1988) concludes
that the sensitivity of the organism to oxygen and its susceptibility to drying make it unlikely to
persist through composting and sludge drying  processes.
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       The  genus Vibrio includes several  species of enteric human  pathogens;  the most
significant,  Vibrio cholerae, results in the diarrhea! disease, cholera (Feachem et al.,  1983).
Water and foodborne transmission have been clearly demonstrated, but direct person-to-person
transmission may occur.  The role of animal reservoirs has not been determined.  Untreated
cases may result in death from dehydration and loss of electrolytes. Endemic to several areas
of Africa and Asia, cholera is difficult to control because asymptomatic and mild infections may
be widespread and have major significance to transmission. The ingestion of lOMO4 organisms
has been shown to cause mild or subclinical infection (Kowal, 1985). 'Normal gastric acidity
is an important defense against infection.  There are no reports of reduction  of V. cholerae
numbers during sludge treatment, but studies on the survival of the organism in feces  suggest
that a process  with  a  retention  time >5 days  and a warm environment decrease survival.
Feachem et al. (1983)  conclude that any sludge  digestion, composting or storage process will
eliminate the organism.
       Yersinia enterocolitica causes an acute enterocolitis and septicemia, which are normally
self-limiting (Feachem et al.,  1983).   Animals are  reservoirs, but  their  relationship  to
transmission is not clear. Transmission by food and water has been reported.  Kendall and
Gilbert (1980)  report that the organism multiplies readily in foods.  High levels of Yersinia
organisms have been reported in some treated wastewater sludges (Metro, 1983; Yanko, 1988),
and Langeland  (1983) suggests that Yersinia may grow in sewage  sludge.
       Members  of  the genus Leptospira are parasites of rodents.  They are transmitted  to
humans by contact with the urine of animals or water contaminated with animal urine. Infection
can result in severe illness that may  be fatal, but usually a milder form  of the  disease results.
Although not present in the feces of infected animals and humans, Leptospira in urine may result
in their presence  in sludges.  Feachem et al.  (1983) conclude that sludge treatments involving
anaerobic processes and heat will rapidly inactivate these organisms.
       4.1.1.  Bacteria Persistence and Inactivation in Sludge. Bacteria become concentrated
in sludges during primary (screening and settling) and secondary (biological)  sewage treatment
processes. Concentrations of pathogenic bacteria in these sludges are lowered by conventional
sludge treatment processes.  Ward et al.  (1984)  and U.S. EPA (1988b)  report  that mesophilic
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anaerobic digestion, aerobic digestion, composting, air drying and lime stabilization achieve
bacterial reductions of 0.5-> 4 orders of magnitude (an order of magnitude is equivalent to one
Iog10 reduction).   According to these reports, composting and lime stabilization processes
produce the best reductions of bacterial densities in sludge.  The success of a given treatment
process in lowering pathogen levels depends, in general, on its retention time and its ability to
produce a hostile environment (e.g., thermophilic  processes)  for pathogens (Feachem et al.,
1983).  In examining the final sludge products from 24 sludge treatment facilities, including
composting, air-drying and heat-treatment facilities,  Yanko (1988) reported  that densities  of
bacterial pathogens in sludges varied greatly between facilities and between samples of products
from the same facility.
       Inadequate or incomplete sludge treatment or recontamination may result in the regrowth
of some pathogenic bacteria under the proper  environmental conditions.   According to Ward
et al.  (1984) > bacteria associated with gastroenteritis are the only bacterial pathogens likely to
regrow, and the bacteria that cause salmonellosis are capable of significant regrowth in sludges.
Organic  content and  microbial  antagonism  are among the environmental factors  affecting
regrowth.  There are fewer competing microorganisms in compost and concomitantly greater
nutrient availability for the bacteria;  microbial competition or antagonism and less nutrient
availability are more probable in a sludge monofill. Hence, bacterial regrowth is less likely in
a sludge monofill than in composted sludge.
       4.1.2. Bacteria Persistence and Inactivation in Soil.  Rates of inactivation of bacteria
in soil vary with the strain, the condition of the organism, the method of sludge application, the
degree of predation and competition by other microorganisms,  atmospheric conditions and the
physical and chemical composition of the soil (Moore et al.,  1988).  Temperature and humidity
are the most significant environmental parameters affecting inactivation in soil.  In their review
Of survival and transport of pathogens, Sorber and Moore (1987) found that temperature was the
only physical or meteorological parameter related to microorganism survival in sludge-amended
soil, survival increasing as temperature decreased.  Yates  and Yates (1988)  suggest that soil
moisture is the dominant factor for survival of enteric bacteria in soil.  The presence of organic
matter in the  soil is conducive to pathogen survival not only because of the nutrient value but
also because  organic matter  increases  the water-holding capacity  of the soil, which  allows
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 enhanced survival of the bacteria.  Zibilske and Weaver (1978) observed an interaction between
 soil moisture and soil temperature in the survival of S. typhimuriwn in two soil types; dry soil
 conditions and higher temperatures were most detrimental to survival in both soil types.
       Hagedorn  (1984)  summarized information on  bacterial  transport through  the  soil:
 (1) when carried by percolating water in unsaturated soil, bacterial movement is limited to a few
 dozen cm, but much longer distances are possible under  saturated flow conditions; (2) retention
 of bacteria by soil is inversely proportional to soil particle size; (3) the major limiting factor to
 bacterial transport through soils is filtration by  soil  particles; (4) soils containing a greater
 percentage  of clay are more effective in adsorbing  bacteria;  and  (5) the importance of
 inactivation increases under conditions of unsaturated flow  or extended retention of bacteria.
 Other physical soil characteristics affecting bacterial transport include:  organic matter type and
 content, pH, cation exchange capacity (CEC) and pore size  distribution (Moore et al.,  1988).
 Other soil environmental and chemical factors affecting transport include: temperature, chemical
 makeup of ions in the soil solution and their concentrations, bacteria density and dimensions and
 nature of the organic matter in the waste effluent solution (concentration and size).  However,
 because rate of transport in soil is strain-specific and there is no consistent pattern in mobility
 (Alexander et al., 1991), the influence of these factors is difficult to quantify.  .
       4.1.3. Bacteria Persistence and Inactivation in Groundwater.  Enteric bacteria show
 very little growth in groundwater (Matthess and Pekdeger, 1985); their survival in groundwater
 depends primarily on the biological, physical and chemical conditions of the groundwater and
 on the processes that control the transport  of bacteria.  According to Matthess and Pekdeger
 (1985), enteric bacteria do not flourish in  groundwater in the presence  of active indigenous
 microorganisms.  Burton et al. (1987) report that survival rates  for several species were greater
 in sediments than  in the  overlying surface waters,  with particle size related  to  survival.
 Resuspension of the upper-layer sediments could create a potential health hazard. Gerba (1985)
 reports that shallow wells  are more frequently positive for  indicator organisms and average
 higher densities than deep wells.
       Adsorption and  filtration  limit the  movement of bacteria in  groundwater.  Rate of
movement is usually slow unless coarse soils or channels exist.  The biologically active layer
of sorptive small particles and microbial slimes at the sediment-water boundary is very effective
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in filtering out bacteria and preventing their migration to the aquifer (Matthess and Pekdeger,
1985).  Continuous adsorption-desorption reactions delay movement of bacteria relative to the
groundwater,  giving  inactivation  processes  more time to affect bacteria in the saturated
subsurface.  However, survival time in groundwater may be longer because conditions such as
increased moisture, lower temperature and the absence  of sunlight and other microorganisms
may be favorable.

4.2. VIRUSES
       Viruses are more resistant to inactivation than bacteria, and they  are smaller and thus
more mobile (U.S. EPA, 1992).  The presence and pathogenicity of viruses in sewage and
sludge are documented in U.S. EPA (1988a,b), Kowal (1985), Feachem et al. (1983) and WHO
(1981).  The major viruses found in wastewater are listed in Table 4-3. These viruses adsorb
to suspended particles and become concentrated in the sludges during wastewater treatment.
Although they will not grow in sludges as bacteria will,  viruses may persist for many weeks if
temperatures are cool (Feachem et al., 1983).  Animal  reservoirs have not been  shown to be
significant for the pathogenic viruses likely to be found in  sludge, but a few cases have been
reported that suggest  the transmission of hepatitis A from animals.
       Viruses are not normally present  in the feces  of persons who are not infected,  but
concentrations of > lOMO9 infectious particles may be in 1  g of feces from an infected person,
even if the individual does not exhibit disease (Feachem et al.,  1983).   Enteric viruses  are
transmitted primarily from person to person by the fecal/oral route.  Transmission occurs by
direct personal contact or contact with contaminated surfaces, by contact with recreational water,
by ingestion of contaminated food or water and possibly by the airborne route. Inhalation results
in infection following the mucociliary translocation and  ingestion of viral particles.
       The enteroviruses, including polioviruses, coxsackieviruses and echoviruses,  comprise
a large  group of pathogens causing a wide variety of diseases.   They normally infect the
digestive tract or the respiratory system, causing gastroenteritis or influenza-like disease. Spread
to other organs, such  as the liver or central nervous system, results in more severe,  but generally
short-lived, disease.  Poliomyelitis, caused by infection  of the,central nervous system by polio-
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Table 4-3. Human Viruses in Sludge and Wastewater
Virus
Adenovirus
Astrovirus
Calicivirus
Coronavirus-like Particles
Enteroviruses
Poliovirus
Coxsackievirus A
Coxsackievirus B
Echovirus
New Enteroviruses
Hepatitis A Virus
Hepatitis E
Norwalk virus and other small
round structured viruses
Papovavirus
Parvovirus and Parvovirus-like
Agents
Reovirus
Rotavirus
Disease or Symptoms
respiratory and eye infection
may be associated with gastroenteritis, diarrhea
gastroenteritis
respiratory tract infections, gastroenteritis

poliomyelitis, meningitis, fever
herpangina, respiratory disease, meningitis, fever
myocarditis, congenital heart anomalies, meningitis,
respiratory disease, pleurodynia, rash, fever
meningitis, respiratory disease, rash, diarrhea, fever
acute hemorrhagic conjunctivitis, meningitis,
encephalitis, respiratory disease, fever
infectious hepatitis
hepatitis
epidemic gastroenteritis with diarrhea, vomiting,
abdominal pain, headache, myalgia
may be associated with progressive multifocal
leukoencephalopathy
gastroenteritis, aplastic anemia, fever, rash, fetal death
or damage including hydrops fetalis
possibly fever, diarrhea and upper respiratory disease,
but relationship to clinical disease in hurnans is not
clear
acute gastroenteritis with severe diarrhea, vomiting
Sources: Kowal, 1985; Feachem et al., 1983; Kucera, 1983; Akin et al., 1978; U.S.
EPA, 1988a; Rao et al., 1986a; Levy and Read, 1990.
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virus, may result in permanent disability or recurring complications later in life.  Although most
people recover,  4-10% of the  paralytic  polio cases result in death from respiratory failure
(Feachemetal., 1983).
       Hepatitis A virus (HAV) occurs endemically in all parts of the world, and it represents
the greatest waterborne health threat from viruses because of the severity of hepatitis A illness
and because HAV is more resistant to disinfection than many other pathogens (Sobsey et al.,
1991). The severity of the disease increases with the age of the victim, but, in general, recovery
is complete.  Person-to-person  contact by the fecal/oral route is the  most common method,of
transmission, but food and waterborne transmission have been reported.
       A number of viruses have been found to be associated with diarrhea! disease, including
the caliciviruses, the  coronaviruses, Norwalk agent and other small round viruses; the most
significant of these are the rotaviruses, a major cause of childhood gastroenteritis. Transmission
is fecal/oral, usually person-to-person, but sometimes by water or food.
       Because of the many difficulties in estimation and measurement, reported infective doses
for enteroviruses vary widely (Table 2-3). Kowal (1985) reviewed the oral infective dose for
poliovirus and found ranges of 1-1 XlO7-6 TCID50 and 0.2-5.5 XlO6 PFU.  Schiff et al. (1984)
reported the human oral 50% infective dose (HID50) for echovirus  was 919 PFU in  volunteers
and predicted an HIDj (1% infective dose) of 17 PFU.  When rotavirus was administered orally
to volunteers, Ward et al. (1986) found an HID50 of -10 focus-forming units (ffu) and estimated
that -25% of susceptible adults would be infected by 1 ffu.  Regli et al. (1991) present data
 suggesting a minimum infective dose for rotavirus of ~ 3. These and other data suggest that the
 infective dose of enteroviruses  to humans is 10 or fewer infectious virus particles.  A review of
 the health significance of viruses in water suggested that the minimum infective dose of enteric
 viruses in healthy adults may  be larger than 1  PFU, but a single  PFU may be infective to
 susceptible individuals (IAWPRC, 1983).
        The U.S.  EPA (1992)  has developed a proposed Ground-Water Disinfection Rule in
 which they propose using  a "synthetic  virus" for risk calculations.  On the basis of model
 calculations,  a limit of 2xlO'7 viruses/L has been proposed as a target limit in  groundwater
 (Regli et al.,  1991).  The synthetic virus would combine properties of  several  viruses-
 enteroviruses representing worst-case waterborne occurrence, rotaviruses for dose-response and
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 HAV for estimating disinfection efficiency.  This combination of properties would create a
 reasonable worst-case situation. Because this proposed rule is currently a draft and will not be
 promulgated until 1995, SLDGFILL uses a representative enterovirus.  However, the model
 could be configured to use the synthetic virus, which would  result in a more conservative risk
 assessment.
       4.2.1. Virus Persistence and Inactivation in Sludge.  A range of 2-215 enteric virus
 units/g of raw sludge has been reported in the United States (Gerba, 1983a); Pedersen (1981)
 reports average geometric mean values for enteric viruses of 390 PFU/g dry wt in primary
 sludge, 320 PFU/g dry wt in secondary sludge and 360 TCIDSO in mixed sludge.  Viruses are
 less easily removed by treatment processes than bacteria; viruses may be protected in sludge by
 adsorption and association with solids.  The U.S. EPA (199Ib) records mean  densities of
 enteroviruses in digested sludges of 3.3-138 PFU/100 mL of sludge and 0.3-53 TCID50/g dry wt
 of sludge. Mean densities of 0-260 enteric virus units/g sludge and 0.007-0.04 PFU/mg of total
 suspended solids  are  reported  for  enteric  viruses.   Determining the fate of hepatitis A,
 rotaviruses and other viral agents of gastroenteritis in sewage and sludge treatment processes has
 been hampered by inadequate isolation techniques for the  viruses (Feachem et al., 1983).
 According to Feachem et al.  (1983), "any sludge treatment process that involves temperatures
 of 50 °C or above should yield a virus-free product if the process is well controlled and carried
 out for sufficiently long periods to ensure that all parts of the mass are heated."  Rao et al.
 (1986a) suggest that higher temperatures may be necessary because HAV was  infective at 80°C
 in the presence of high concentrations of some salts.  Ionic detergents have been shown to
 protect poliovirus from heat  in raw sludge (Ward et al., 1976).  Although aqueous ammonia
 speeds inactivation of enteroviruses at moderate temperatures, adsorption of the virus particles
 to sludge solids may protect them from heat inactivation and from inactivation by ammonia
 (Ward and Ashley,  1978).
       4.2.2.  Virus Persistence and Inactivation in Soil and Water.  The most important
 factor influencing persistence and inactivation of viruses in both soil and water is temperature,
 with  lower temperatures  enhancing survival  and infectivity  (Yates  and Yates,   1988).
Temperature and desiccation  may  act synergistically to influence the fate of viruses  in  soil
 (Gerba and Bitton, 1984).  Yeager and O'Brien (1979a,b) suggest that the mechanisms for viral
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inactivation in moist soils differ from those in dry soils and that inactivation occurs during the
drying process.
       Microbial activity may play a role  in  the inactivation of viruses in soil and water;
investigations have yielded inconsistent results. Hurst (1988) suggests that microbial antagonism
in soil  results  from  the metabolic products of bacteria or bacterial interference with viral
adsorption onto soil particles. Yates et al. (1990) examined filtered and unfiltered groundwater
and concluded that bacteria may produce a substance that inactivates viruses.  Viruses survive
well at the pH levels of natural waters (pH 5-9) (Bitton et al., 1987), and Bitton (1978) asserts
that enteric viruses will not be affected by the pH values of the natural environment.  According
to Salo and Cliver (1976), virus persistence relative to pH in the aqueous environment varies
with the type of virus.   Gerba and Bitton  (1984)  suggest that pH may have indirect effects on
inactivation by affecting adsorption.   Although conflicting reports in the literature indicate that
the relationship is not clear-cut,  adsorption may be minimal at alkaline pH values.  Pancorbo
et al. (1987) report that inactivation of human rotavirus type 1 was significantly correlated with
water pH, with inactivation increasing as pH increases.
       The association  of viruses with organic  and  inorganic particles in water  appears  to
enhance survival, possibly by protecting viruses from light, heat and biologic degradation. Yates
and Yates (1988) conclude that the survival of viruses in soil may be  enhanced or reduced by
adsorption to soils  or other materials, depending on the sorbent, and that organic, matter
competes with virus particles for sites on soil particles.  Gerba (1984) reports that organic
material acts as an eluting agent,  desorbing viruses from the soil.  Gerba (1985) and Hurst et al.
(1980) found that viral survival increased  with greater adsorption by soil.
       Yates and Yates (1988) conclude that many soil properties influence viral persistence in
soil by affecting the degree of adsorption to soil particles. Hurst et al.  (1980) suggest that viral
adsorption increases with high  aluminum levels and  with  lower levels of resin-extractable
phosphorus. Clay minerals may increase viral adsorption to soil, and clay can be protective to
the viral genome (Gerba and Bitton, 1984).  According to Sobsey (1983), increasing the soil
CEC increases virus adsorption.  Minerals have been  shown to be better adsorbents than soils
in some studies (Sobsey and Shields, 1987). According to Bitton (1980), virus persistence in
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 natural water is affected by the formation of aggregates, possibly by protecting the aggregated
 virus particles from environmental factors.
       Inactivation of enteroviruses in the environment can be influenced by  salt species and
 their concentrations.  Yates and Yates (1988) report that the type and concentration of salts in
 the soil  affect virus adsorption to soil and that the presence of some cations in  the media is
 protective against heat for some viruses.
       In their study of grouridwater in the United States,  Yates et al. (1985) found that water
 characteristics such as hardness, turbidity, total dissolved solids, nitrate, ammonia, sulfate and
 iron  were  not significantly  correlated  with the  inactivation  of three viruses at  in  situ
 temperatures.  However, Jansons et al. (1989) found  that the viral inactivation rate increased
 with an increase in the dissolved oxygen  in groundwater.
       Adsorption to particles and susceptibility to inactivation in soil and water vary with  the
 type of virus and  the particular strain.  HAV has been shown to persist longer than polio and
 echovirus at 25 °C in groundwater, wastewater and soil suspensions.
       In summary,  virus inactivation varies by species  and as  a result of environmental,
 physical and chemical factors.  Table 4-1  gives an indication of the ranges of inactivation rates
 for several viruses in soil and in water.  This range of values  has been used in SLDGFILL to
 model virus risk from a sludge monofill to a nearby human receptor.
       4.2.3.  Virus Transport in Soil, the Subsurface and Groundwater. The potential for
 virus removal is greater in the unsaturated  zone than in the saturated zone because of adsorption,
 filtration and other retardation processes, which increase the likelihood of inactivation (Yates and
 Ouyang, 1992). Viruses applied to soil in sludge will be less mobile than those in sewage water
because they will be adsorbed to sludge solids (Lance and Gerba, 1982).  The application rate
of sludges will affect the number of viruses passing through the soil to the groundwater (Rao et
al., 1986a).
       Adsorption is the primary mode of removal of free virions in soil, desorption allowing
further transport through the soil (Yates and Yates, 1988). Initially, most viruses applied to soil
are retained in the  upper soil layers (Rao et al., 1986a).  Lance et al. (1976) suggest that viruses
near the surface desorb and migrate vertically through the soil with periodic rainfall; Lance and
Gerba (1984)  found that poliovirus moved farther in columns of loamy sand  under saturated
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conditions than under unsaturated flow conditions.  Lance and Gerba (1980) suggest that virus
adsorption is not affected by increases in water flow rate up  to a breakthrough rate point that
corresponds to the rate at which water  begins  to  move only through the large soil  pores,
allowing little contact between viruses and soil particles.  Column and field studies suggest that
water flow velocity is possibly the most important soil characteristic affecting virus movement
in soil (Lance and Gerba,  1982).
       Coarse-textured  soils that do  not  adsorb  well promote migration of viruses.  In field
studies, Lance arid Gerba (1982) found that movement of viruses to groundwater was a problem
primarily in coarse sandy or gravelly soils.  Soils with high CEC and large surface area, such
as clay, are active in virus adsorption (Yates and Yates,  1988),  and some minerals have been
shown to increase virus adsorption and retention in soil (Sobsey and Shields,  1987).  However,
soluble organic matter reduces virus adsorption, thereby enhancing virus persistence and mobility
in soils (Gerba and Bitton, 1984).
       Sobsey and Shields (1987) report a number of studies indicating greater viral adsorption
in neutral and  acidic materials.  Gerba et al.  (1981) found  that for poorly adsorbed viruses
                                      .            '                                   vx
(including coxsackie B4 viruses, echo 1 viruses and phage MS-2) viral adsorption to soil was
greatly affected by pH, as well as by CEC and organic matter, but for highly adsorbed viruses
(including  polio 1,  echo 7,  coxsackie  B3  and  phages T4 and  T2),  pH  and  other  soil
characteristics were not correlated with soil adsorption. Although high pH values will promote
virus desorption and migration in the soil, these pH values are expected only under experimental
conditions (Rao et al., 1986a).
       Increasing the concentration  of ionic salts increases virus adsorption to soil particles,
retarding virus transport (Sobsey, 1983).  During rainfall, the ionic strength of the soil water
decreases,  and desorption and redistribution of viruses  creates  the potential for groundwater
contamination (Gerba, 1983b).  Gerba and Bitton (1984) report that rempbilization varies with
the nature of the soil and with virus type and strain.  Adsorptive capacity is  both type- and
strain-dependent (Gerba et al., 1980). The electronegativity of a virus type is determined by the
physicochemical composition of the capsid surface,  and desorption and migration in the soil are
affected by this charge  on the particle (Rao et al., 1986a).
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       Because viruses are small in diameter, porous aquifers are not effective in filtering out
virus particles; the large flow paths permit rapid passage of suspended viruses (Matthess and
Pekdeger,  1985).  Passage through loamy aquifers with high cation concentrations effectively
removes viruses that adsorb well, retarding transport and providing time for inactivation  to
occur.  Also, the microbial slime and sorptive small particles at the water/sediment boundary
impede transport.  Heavy rainfall may result in decreased cation concentration and further virus
transport.
       Viruses, because of their small size, mobility, resistance to inactivation and low infective
dose, are the most likely of the pathogens to result in a potential health risk as a result of sludge
landfilling.  Although virus transport in the subsurface has been studied and modeled, there is
little quantitative laboratory or field data to determine the relative impacts of climatic, biologic,
chemical or physical factors on subsurface transport, particularly in the unsaturated zone.

4.3.   PROTOZOAN PARASITES
       WHO  (1981), Kowal (1982, 1985) and U.S.  EPA (1988a) document the presence  of
protozoan parasites in sludge at different  stages of treatment.  Table 4-4 lists the protozoa,
commonly found in sewage sludge, that are significant human pathogens. Because animals are
often reservoirs of protozoan parasites, sludges containing animal wastes may have high levels
of protozoa.  Protozoa are present in sewage and sludge as cysts and oocysts, dormant structures
resistant to adverse environmental conditions (U.S. EPA,  1990b).   Epidemiological evidence
suggests little risk to human health from parasites in municipal sludge, but their persistence in
the environment and their low infective doses mean  that protozoa in sludge cannot be dismissed
from  health risk considerations  (Kowal, 1985).  However, the large size of protozoan cysts,
relative to viruses  and bacteria,  makes transfer of the cysts to groundwater after landfilling  or
surface disposal of sludge unlikely (Kowal, 1985).
       The protozoan pathogens cause a variety of symptoms, including enteritis, diarrhea and
dysentery, by colonizing the gastrointestinal tract of  humans and other mammals.  Kowal (1985)
identifies the protozoan parasites of greatest human health significance in sludge as Balantidium
coli (balantidiasis), Entconoeba histolytica (amebiasis) and Giardia lamblia (giardiasis). All are
                                          4-16

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Table 4-4. Protozoa of Concern in Sewage Sludge
Pathogen
Balantidium coli
Cryptosporidium
parvum
Dientamoeba fragilis
Entamoeba
histolytica
Giardia lamblia
Isospora belli,
I. kominis
Toxoplasma gondii
Effect/Disease
Balantidiasis
Cryptosporidipsis
Amebiasis
Amebiasis (amebic
dysentery)
Giardiasis

Toxoplasmosis
Nonhuman
Reservoir
pigs, other mammals
cattle, sheep and
other domestic and
wild animals

mammals
dog
dog
cat
Human
Infective
Stage
cyst
oocyst
3»
unknown
cyst
cyst
oocyst
oocyst
oocyst
Source: Kowal, 1985; U.S. EPA, 1988b; Sorber and Moore, 1987.
                     4-17

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 transmitted by water contaminated with cysts, and Entamoeba and Giardia are also transmitted
 by contaminated food.  Amebiasis, giardiasis and balantidiasis are often asymptomatic infections
 (Kowal, 1985); the diseases may be debilitating, but they are rarely fatal in developed countries.
 However,  severe  cases of amebiasis may produce liver, lung or brain  abscesses and death.
 Ciyptosporidium parvum, a coccidian protozoan, has recently been recognized as a widespread
 pathogen of humans  and animals with a potential for waterborne transmission equal to or greater
 than  Giardia (Rose, 1988; Current, 1987); it has been the cause  of  several outbreaks of
 waterborne disease.   Cryptosporidiosis  ordinarily  produces  mild to severe diarrhea, but in
 immunologically compromised individuals, it may result in a life-threatening cholera-like illness
 and may not be confined to the gastrointestinal  tract.
       The infectious dose of protozoans has been determined to be small,  as few as one cyst
 of Giardia or 10-100 oocysts of Cryptosporidiwn (Casemore, 1991).
       4.3.1. Persistence in Sludge.  Trophozoites, the active stage  of flagellate protozoans,
 and sporozoites* the active stage for coccidian protozoans, can become  precysts following a
 period of reproduction.  These precysts can secrete a tough membrane to protect the parasite
 (Kowal, 1985).  It is these thick-walled,  environmentally resistant, dormant structures that are
 excreted in the feces and are found in sewage and sludge.  These forms are  capable of causing
 human infection and are, therefore, the source of concern, if any, in landfilled sewage sludge
 (U.S. EPA, 1990b).
       There is little information on the survivability of  Giardia and  Cryptosporidium during
 sludge treatment processes. According to Reimers et al. (1981) and Leftwich et al. (1981), 99%
 of primary municipal sludges and 89% of final municipal sludges from southern states contained
 large  numbers of viable parasite cysts and ova.  Direct counts (centrifugation) of Giardia. cysts
 in 11  municipal secondary sludges ranged from 70-30,000 cysts/L (Sykora et al.,  1991).  The
 highest average concentration (1723 cysts/L) was in dewatered but not digested sludges. Yanko
 (1988) examined the  final sludge products from 24 treatment facilities, including composts, air-
dried  and heat-treated sludges,  and found no protozoan cysts.  Kayed and Rose (1987) reported
concentrations of Cryptosporidiwn ranging from 1250-38,700 oocysts/g dry wt in anaerobically
digested sludges.  Filtration at  water treatment plants removes Cryptosporidium oocysts, which
                                         4-18

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are resistant to routinely used disinfectants (Payer and Ungar, 1986; Current, 1987; Rose, 1988).
Table 2-2 illustrates the wide range of densities of protozoan cysts and oocysts in treated sludge,
from as few as 70 cysts/L to as many as 38,700 oocysts/g dry wt; some researchers found none
at all in multiple sludge samples.
       JL3Jj^X*"""4'--~~'^	* ""      	' 	~""'	"-~~- •  '  •  "'	'"'•	  "'"	'-" -ir-C	~.,-
the survival of protozoan  cysts in soil.  The U.S. EPA (1990b) documents  the sensitivity of the
cysts of Entamoeba histolytica to drying, with longer survival in moist soils.  Yanko (1988)
reports protozoan cysts survive a maximum of 10 days on soil; Frenkel et al. (1975) found  that
cysts of Toxoplasma species survived up to 410 days in soil.
       The persistence of  Cryptosporidium  oocysts and  Giardia  cysts in  water  is well
documented (Madore et al., 1987; Hayes et al., 1989). Jakubowski (1990) reports that Giardia
cysts survive best in water at temperatures of 4-8 °C and that temperatures below 20 °C allow
the cysts to survive for long periods.  Survival time of Entamoeba histolytica in water is also
temperature dependent, survival decreasing with a rise in temperature. Cryptosporidium oocysts
were not infective after exposure to temperatures below freezing or above 65 °C (Tzipori, 1983).
Kayed and Rose (1987)  report  survival of protozoan cysts in water in the, laboratory  for
> 140 days.
       Unless there are vertical cracks or fissures, protozoan cysts are large enough (~ 5-25 /tm
dia) that they do not migrate vertically through soil into the groundwater  (U.S. EPA,  1988b).
For example,  Seattle Metro (1983) found that cysts of Entamoeba histolytica were unable to pass
through 61  cm (24 in.) of sand. So, despite their relatively long  survival time in soil and water,
protozoan cysts are unlikely to be a health risk in groundwater.
4.4.   HELMINTH PARASITES
       WHO (1981),  Kowal  (1982,  1985) and  U.S. EPA (1988a) survey helminth parasites
present in sewage sludges and discuss the associated diseases. The pathogenic helminths, some
of which are only incidental parasites of humans, include both the nematodes (or pinworms,
roundworms and whipworms) and the cestodes (or tapeworms).  Most have animal reservoirs.
Table 4-5 shows the significant human pathogenic helminths that are most commonly found in
                                         4-19

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       The dwarf tapeworm, Hymenolepis nana, requires no intermediate host and inhabits the
human intestinal tract.   Light infections  may be asymptomatic,  but anorexia and digestive
disturbances may occur.  Humans may serve as the intermediate host for the pork tapeworm,
Taenia saginata, by ingestion of feces contaminated with eggs.  Cysticercosis results as the
larvae migrate into tissues  and encyst.  Localization of the migrating larvae in the ear, eye,
central nervous system or heart may be quite serious.  When humans are the intermediate host
for the dog tapeworms, Echinococcus granulosus and E. multilocularis, hydatid cysts formed
by larvae in body organs can cause serious problems as the cysts grow or rupture.
      • A single helminth egg may produce human infection; however, because infection is dose-
responsive, many infections are asymptomatic (Kowal, 1985).
       4.4.1. Persistence in Sludge. Helminths typically reproduce in the gut and generally
require more than one host to complete their life cycle.  The adult worm typically lives in the
gut of the definitive, or final, host and sheds fertilized ova, either free or in proglottids, in the
feces.  Helminth ova are the resistant stage found in sludge (U.S. EPA, 1990b).
       Schwartzbrod et al. (1989) report that ordinary wastewater treatments, such as activated
sludge, lagoon treatment and  sand filtration,  concentrate parasite eggs in sludge and lower the
density in wastewater effluent.  Temperatures >55°C during aerobic and anaerobic digestion
are lethal to parasite eggs (Leftwich et al., 1981); drying beds are effective for inactivating eggs
when moisture is  <5%.  Black et al. (1982)  report that survival and viability of helminth eggs
during mesothermic digestion varies with the type of digestion, anaerobic or aerobic, and the
species of helminth.  Fewer viable Ascaris and Toxocara eggs were found in anaerobic sludges
than in aerobic sludges, possibly because of the  higher temperatures in anaerobic digestion
(Reimers et al., 1986). Mbela et al. (1990) conclude that high temperature is a significant factor
in Ascaris  inactivation during aerobic and anaerobic digestion, and that liming and caustic
stabilization increase  inactivation.  High  temperatures have also been reported  to be  more
effective for  inactivating parasite eggs  during lagooning  (O'Donnell et al., 1984) and  for
decreasing survival of Taenia eggs during other sewage treatment processes (Storey,  1987). At
temperatures  <51°C, heating alone for 1 hour was not effective in destroying viable ova, but
heating to 55°C for 15 minutes was lethal (Pike et al., 1988).
                                         4-22

-------
       Although Yanko (1988) reported that helminth ova were detected regularly in the sludge
products from  the  24 sludge treatment facilities  studied, no  indications  of viability were
observed. One or more of Ascaris spp., Toxocara spp., Trichuris trichiura or Trichuris vulpis
were detected in 89% of the municipal sludge samples from plants in  four northern states;
densities of eggs were 565, 265, 270 and 370 eggs/kg dry wt, respectively (Reimers et al.,
1986).
       4.4.2. Inactivation and Transport  in SoU and  Water.   The eggs and larvae of
helminths are sensitive to desiccation and sunlight, but under  cool, moist conditions they may
survive and remain infective for years (Kowal, 1985).  Ascaris eggs may survive in soil up to
15 years (U.S.  EPA,  1988b).  Although some field studies indicate that subsurface conditions
are more conducive to survival of helminth eggs than conditions at the soil surface, other studies
have failed to find a correlation between viability and solar radiation, relative humidity or soil
temperatures.   Leftwich  et al. (1988a) reported that repeated freeze-thaw conditions reduced
viability of Ascaris eggs, with greater soil-moisture promoting viability despite temperature.
       Sorber and Moore (1987) conclude that the size of helminth ova prevents their vertical
migration through soil. Based on their measurement of the rate of transport of T. saginata and
A. lumbricoides ova in soil columns, Storey and Phillips (1985) calculated that the ova would
move 100 cm in 65 years assuming an average annual rainfall of 152 cm (60 in.).
       No data were found on survival or transport of helminths in water.

4.5.   FUNGI
       Pathogenic fungi can be divided into the yeasts (Candida spp., Cryptococcus neoformans
and Trichosporon  spp.)  and filamentous  molds  (Aspergillus  spp., Epidermophyton spp.,
Phialophora spp. and Trichophyton spp.). Because these fungi  are ubiquitous in nature, even
pasteurized  sludges may become recontaminated (WHO,  1981).  Therefore, it is  difficult to
evaluate their  public health significance.   Aspergillus fiunigatus is prevalent in municipal
compost, but composted  sludge is not buried in  landfills (U.S. EPA, 1988a) because of its
capacity for beneficial reuse.
                                          4-23

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4.6.   PATHOGEN SUMMARY
       The parameters required for the SLDGFILL model—density of pathogens in  sludge,
minimum infective dose,  inactivation rates and data on transport in the environment—have been
described. Summary data on pathogen density in treated sludge and on minimum infective doses
were presented in Tables 2-2 and 2-3, and inactivation rates are summarized in Table 4-1.  The
ranking of pathogen persistence in the environment, from longest to shortest, is helminth eggs,
viruses, bacteria and protozoan cysts (U.S. EPA, 1988a). The most important of the factors that
affect pathogen survival in sludge, soil and water are temperature, survival increasing with lower
temperatures; moisture, survival increasing with conditions that encourage moisture retention,
such as clay soil or high  rainfall; and pH, survival enhanced at median values (pH 5-8).  The
groundwater pathway is the most significant route of human exposure following surface disposal
or landfilling  (see Chapter 5).  Depth to groundwater presents the greatest barrier  to the
transport of pathogens and hence to exposure and potential risk.  Filtration  and adsorption,
which  delay transport and allow more time for inactivation,  are the processes responsible for
limiting pathogen movement through the unsaturated zone.  The size and surface charge of the
organism,  therefore,  determine which  pathogen  will  be transported  the greatest  distance.
Viruses,  the smallest of  the pathogens considered, have the potential to travel farther in the
environment.   Large particles  like helminth eggs and protozoan cysts do not  migrate  into
groundwater because of the physical barrier provided by the soil, unless there are vertical cracks
or fissures. Therefore, viruses seem to present the greatest potential for producing human health
effects from landfilling or surface disposal of sewage sludge.
                                         4-24

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                 5. IDENTIFICATION OF EXPOSURE PATHWAYS

       Considering  current sludge surface disposal  facility or landfill design and operating
practices,  the potential pathways for offsite migration of pathogens can be summarized (U.S.
EPA, 1989b,e) as illustrated in Figure 5-1:
       •     groundwater infiltration—infiltration of water  and drainage of leachate from
             sludge, transporting pathogens to the underlying aquifer;
       •     surface runoff—suspension of pathogens in surface runoff from the sludge working
             face and transport to nearby surface waters (this pathway is not relevant to trench
             monofills, because the sludge is placed below the surface in an enclosed trench);
             and
       •     particulate suspension—suspension in  air  of particles and pathogens  from the
             working face with subsequent transport downwind.

5.1.   GROUNDWATER INFILTRATION
       Infiltration of water from and through the sludge into groundwater and subsequent uptake
of pathogens in drinking  water  is considered the most  significant of the potential exposure
pathways  (U.S. EPA, 1989b,e).  Sludge lagoons, surface disposal sites or landfills receiving
recharge  will allow  formation  of leachate  and  downward  migration  of that  leachate to
groundwater.  Groundwater may be used as drinking water or to irrigate crops, water livestock,
provide drinking water for wildlife or serve as recharge for surface water habitats for edible
aquatic organisms.   Because the greatest threat and most likely occurrence of health effects
would result from drinking groundwater contaminated by this leachate, risk evaluations will be
based on drinking water concerns. Each of the other pathways is considered as a supplementary,
or  less serious, groundwater pathway.   Therefore, the most  conservative assumption for
evaluating risk from pathogens in sludge is direct ingestion of groundwater from a drinking-
water well near the landfill site.
                                          5-1

-------
5-2.

-------
5.2.   SURFACE RUNOFF
       •Pathogen migration in surface runoff may result from suspension of pathogens in surface
water following contact between sludge and runoff. Therefore, pathogens must be present at the
surface of the sludge or soil for pathogen migration by this route.   Because good management
practices require the use of clean soil for cover, the working face is the only significant source
for pathogen-contaminated runoff.   As explained in the  description  of  disposal practices,
•operating procedures require drainage ditches or dikes to control runon and runoff from the
working face. All trench fills and sludge lagoons will contain runoff by design,  since the
working face is below grade relative to  the surrounding  areas. Area fills must include design
provisions to prevent runon from upgradient and  to contain drainage downgradient.  Assuming
good operating practices, runoff becomes a part  of the groundwater pathway or is eliminated.
Precipitation that runs off the working  face will collect below the face in a drainage control ditch
where it will percolate into the soil, be used for  dust control or be routed to treatment.  In the
first two instances, the runoff becomes part of the groundwater pathway. In the third instance,
the pathway is terminated. Therefore, the surface runoff pathway is not considered in this
 model.
        Because good sludge management practices will prevent the surface runoff pathway from
 being a significant route for exposure from pathogens in sludge, regulations to control risk from
 this pathway are best focused on requiring these practices: diversion dikes/berms or ditches to
 redirect runon from adjacent areas away from the disposal area, and berms or ditches at the foot
 of the disposal area to collect runoff from that area and from the working face.  These berms
 and ditches should be designed to contain the estimated runoff from a 24-hr, 100-yr storm event
 (U.S. EPA, 1989b,  1990a).

 5.3.   PARTICIPATE SUSPENSION
        Like the surface runoff pathway, the paniculate suspension pathway requires pathogen-
 bearing sludge to be at the surface where it can  be disturbed by  wind or human activity.  The
 wo'rking face is the only location where this occurs to any appreciable extent. With application
 of daily cover, the working face will only be exposed for a period of 8-12 hours in a 24-hour
 period. Furthermore, particulate suspension will occur only above a given wind scour threshold
                                           5-3

-------
velocity or with mechanical disturbance. Most sludges would not be susceptible to particulate
suspension because of their high moisture content and their tendency to mat as they dry, making
them unlikely to be dispersed by wind.  Since particulate suspension would occur only under a
limited set of conditions, it is preferable to regulate operating procedures such as requiring
placement of daily cover over landfilled sludges.  Cover would typically consist of clean soils
or a mixture of sludge and soil at least 15 cm (6 in.) deep (U.S. EPA, 1989b).
       In summary, good management practices should control any health risks from pathogen
transport in runoff and resuspended particulates in the atmosphere. However, similar regulatory
controls would not eliminate potential pathogen exposure through the groundwater pathway.
Therefore,  only exposure to pathogens'via the  groundwater pathway is included in the
SLDGFELL model.
                                         5-4

-------
                    6.  MODEL DESCRIPTION AND RESULTS

6.1.   OVERVIEW OF THE METHOD
      The SLDGFILL model was adapted from the pathogen risk assessment model for land
application of sewage sludge (U.S. EPA, 1989c,d).   SLDGFILL addresses the disposal of
dewatered sludges (^15% solids) in sludge-only landfills (monofills) that use trench, area fill
or diked containment methods (U.S. EPA, 1988a) and long-term storage or disposal of sludge.
in surface containment  lagoons (U.S. 1990a).  SLDGFILL  is considerably simpler than the
parent model because it deals only with the groundwater pathway and only with disposal sites
from which pathogens may be leached into groundwater (Chapter 5, "Identification of Exposure
Pathways"). The other exposure routes are less significant or better regulated through good
sludge management practices (U.S. EPA, 1988a; i989b). The receptor is an individual ingesting
water directly from a drinking-water well near the site.  Appendix A (User's Manual) describes
how to run the model.
      In SLDGFILL, the saturated zone groundwater transport and infection algorithms from
the parent model have been modified.  A groundwater  transport subroutine for unsaturated soil
was added. Based on the van Genuchten model (van Genuchten and Alves, 1982), it combines
features of the saturated zone transport subroutine from the parent model with U.S. EPA's
unsaturated zone transport methodology for chemicals  in sludge (U.S. EPA, 1989b).
      This sludge pathogen risk assessment model is a compartment-vector  model with four
compartments: bulk sludge, unsaturated soil, saturated soil and groundwater (drinking-water)
well. The model begins with a trench filled with dewatered sludge or a lagoon filled with liquid
sludge as the worst case for the source term in each application. The number of organisms in
each compartment is  calculated for a column with square cross section, 1 m (all units are metric)
on each side and the entire depth of the compartment.  The number of organisms may increase
or decrease by transfer  from one compartment to another or may decrease by inactivation or
death. Growth equations are not included because viruses and  human parasites do not reproduce
without a suitable host and the growth of pathogenic enteric bacteria is not favored by conditions
in a sludge monofill or surface disposal site. Under certain conditions (e.g., addition of compost
                                        6-1

-------
or other nutrient mixtures), bacteria may increase by regrowth;  however, such substrates are
not considered in this application, which is specific for monofills or sludge lagoons.
       Transfers are assumed to be unidirectional, from sludge through soil to the well from
which the exposed individual drinks. The numbers of pathogens to be transferred are calculated
on a daily basis. Inactivation or die-off is included in each transfer step, as well as retardation
and dispersion, which are calculated by the groundwater transport subroutines.

6.2.   ASSUMPTIONS
       With the exception of Cryptosporidiwn and Giardia, it is assumed that helminth ova and
protozoan cysts are too large to move through the soil.  Table  6-1 lists conservative values for
resuspension  coefficients (SSPNDB and SSPNDS) to  address  these  pathogenic parasites.
Bacteria and viruses are considered  to move freely, with limitations described by parameters of
the groundwater transport subroutine.
       The model is intended to be used for distances from a few meters to several hundred
meters and for times from several days to a few years,  and a  description of short-term events
is not necessary. In particular, a daily step is adequate for groundwater, because the model does
not need to consider rapid events  such as surface runoff (assumed to be prevented by  site
management).
       Two key features of microbial fate-and-transfer models  are inactivation and transport in
groundwater.  It is assumed in this model that inactivation or death of pathogens in sludge,  soil
and groundwater follows exponential kinetics with a constant inactivation rate.   Therefore,
inactivation is described by equations of the form
                                      N = N0*e*
where
       N      = number of surviving pathogens,
       NO     = initial number of pathogens,
       k      = exponential inactivation coefficient,
       t      = time.
                                          6-2

-------
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 Microbial inactivation rates are known to be sensitive to temperature, and algorithms accounting
 for annual fluctuations in temperature were incorporated in the models designed to evaluate soil
 amendment with sludge (U.S. EPA 1989c,d;  1990b; 1991a,b). However, Yates and Ouyang
 (1992) showed that daily temperature fluctuations in soil were minimal below 20 cm, so effects
 on virus inactivation rates were not significant. Therefore, because it is assumed that a thick
 pile of sludge will insulate the soil compartments  from rapid surface temperature fluctuations,
 temperature-dependent inactivation rates were not included in this model.
       The  exponential die-off or inactivation rate coefficient may change as the number of
 surviving organisms decreases, or inactivation may become linear with time. In the absence of
 sufficient data describing inactivation of bacteria and viruses in soil, exponential inactivation at
 a constant rate is assumed in this model.
       Composted or incinerated sludges are not considered in this model. Although liners may
 be used in lagoons, wide-trench or area fill methods, this model assumes no liners for a more
 conservative modeling approach.  It is assumed that the  soil compartments are homogeneous.
 Unsaturated soil and the aquifer have different properties,  but the model's calculations are based
 on homogeneity throughout each compartment.  In actuality, pathogen transport is accelerated
 through cracks  and solution channels and impeded by layers of less  permeable material.
 Groundwater velocity, hydrodynamic  dispersion  coefficient and  retardation  coefficient  are
 calculated from parameter values input by the user and represent the average properties of the
 soil through which the pathogens must pass.
       The  groundwater transport algorithm  used in  this model is based on advection and
 dispersion (U.S. EPA, 19.89c,d; van Genuchten  and Alves, 1982).  Advection is bulk flow
 through the soil, and dispersion describes the diversion of particles from direct flow lines by the
presence of a network of pores and channels.  Groundwater transport models for pathogens may
also include consideration of filtration/clogging in soil pores or adsorption/desorption reactions
between pathogens  and soil particles.  Few  field data are available to  validate the  various
models, so it is difficult to determine which are best.  A comparison of the SLDGFILL model's
predictions for transport in  the unsaturated  zone with  experimental data obtained  in  the
laboratory is presented in Section 6.5.2. Because water typically percolates more slowly through
sludge than through soil, the soil layer beneath the  sludge trench should remain  unsaturated. If
                                         6-8

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not, as in the case of a sludge lagoon, the depth of the unsaturated zone must be modeled as
zero.
       The calculated concentration of pathogens reaching the aquifer is used as the starting
concentration of pathogens migrating to the well. This is highly conservative because vertical
mixing with uncontaminated water is not included.  However, regulations for the protection of
groundwater require that water released to Class I aquifers (in current use or of sufficient quality
for use as a drinking water source) must meet the requirements for drinking water before it is
diluted, and it seems reasonable to base evaluations of pathogen transport on similar restrictions.
In addition, it was shown by U.S. EPA (1989e) that mixing was not significant over distances
 < 150 m when a three-dimensional solution was used to model pathogen transport.
       The probability of infection is calculated in this model by a beta-Poisson relationship, in
which it is assumed that the dose-response curve is adequately represented by the empirically
derived equation
                               P* = 1 - (l.+ .n//8)  - a
where P* is the probability of infection and a and /? are empirically derived parameters (see
Section 6.4.5).  The effect of each day's exposure is independent of the outcome for any other
day.   This  assumption ignores additive effects  of  exposure or the induction of immunity by
subinfective exposures.  However,  it is conservative, because low-level exposure typically
reduces susceptibility to infection. U.S. EPA (1992) has suggested that groundwater protection
should be based on that assumption and  has  proposed to use the beta-Poisson  model for
groundwater protection.
       On the basis of model calculations, a limit of 2x 107 viruses/L has been proposed as a
 target limit in groundwater (Regli et al.,  1991).  Results in Section 7.2 are interpreted in light
 of this proposed limit.

 6.3    INPUT PARAMETER REQUIREMENTS
       Parameters are identified by name and by parameter number [parameter 1, DSATZN,
 is denoted P(l)]. Parameters describe physical characteristics of the site, nature and amount of
 sludge or properties of the pathogens.  Default values and descriptions of the  parameters are
 shown in Table 6-1. The ranges of these values are  taken from literature discussed in Chapter 4
                                          6-9

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and from U.S. EPA (1988b, 19905, 1991a,b).  In some cases, intermediate values have been
added to provide additional detail.
       Before computations begin, the parameters are converted^ to common units of days,
meters and kilograms, as shown in Table 6-2.
       6.3.1.  Pathway Data. These parameters describe bulk sludge in a full trench or lagoon.
A full trench or lagoon as a starting point simplifies calculations and provides a maximum source
term of sludge pathogen number in the disposal site.  The loading parameters are:
       DEPTH      =  P(9)       Depth of sludge (m)
       SOLIDS      =  P(10)      Fractional solids of sludge
       BLKDEN    =P(11)      Bulk density of sludge (g/cm3)
       PATHDN    =  P(13)      Density of pathogens in sludge (number/kg dry wt)
       Site-specific parameters:   Site-specific parameters describe physical properties of the
site's underlying soil and the relevant weather conditions.  They are:
       DSATZN    =  P(l)       Depth to saturated zone under sludge (m)
       AQUIFR     =  P(2)       Thickness of aquifer (m)
       PORWTR    =  P(3)       Fractional water content of aquifer
       ANRAIN     =  P(4)       Annual rainfall (cm)
       EVAP        =  P(5)       Fraction  of rainfall lost by evaporation and surface runoff
       WCSAT      =  P(6)       Saturated water content of subsurface soil (fraction)
       USATCND   =  P(7)       Saturated conductivity rate of vadose-zone soil (m/s)
       GSATCND   =  P(8)      Saturated conductivity rate of aquifer soil (m/s)
       SMRSLP     =  P(12)     Slope of the soil moisture retention curve (unitless).
       Groundwater transport parameters:  Groundwater transport parameters are used by the
transport subroutine and describe the soil and groundwater through which the pathogens pass to
the  well. They are:
       DSTAR      =P(19)     Diffusivity (cmVsec)
       GRADI      = P(22)     Hydraulic gradient (unitless)
       XWELL      = P(23)     Distance from the sludge area  source to the  groundwater
                                well (m)
                                        6-10

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                       Table 6-2.  Parameter Conversion Factors"
Parameter
Name
DSATZN
AQUIFR
PORWTR
ANRAIN
EVAP
WGSAT
USATCND
GSATCND
DEPTH
SOLIDS
BLKDEN
SMRSLP
PATHDN
INACTB
INACTS
INACTW
SSPNDB
SSPNDS
DSTAR
INFALF
INFBET
GRADI
XWELL
Final
Number
Pd)
P(2)
P(3)
P(4)/(365*100)
P(5)
P(6)
P(7)*86400
P(8)*86400
P(9)
P(10)
P(ll)*1000
P(12)
P(13)
P(14)
P(15)
P(16)
P(17)/1000
P(l 8)71000
P(19)
P(20)
P(21)
P(22)
P(23)
Final
Units
m
m
fraction
m/day
fraction
fraction
m/day
m/day
m
fraction
kg/m3
number
number/kg
Iog10/day
Iog10/day
Iog10/day
kg/m3
kg/m3
cm2/sec
unitless
unitless
unitless
m
Conversion Factors



(365 days/yr)*(100 cm/m)


86400 sec/day
86400 sec/day


(106 cm3/m3)/(1000 g/kg)





(1000 g/kg)/(106 cmVm3)
(1000 g/kg)/(106 cnvYm3)
a




*P(x) is the value entered by the model user.  Mathematical conversion is performed within the model,
as indicated in the second column, to produce the Final Value in the Final Units shown.
                                           6-11

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                   6.3.2.  Pathogen-Specific Data.  Organism-specific properties characterize survival of
            pathogens, their interaction with sludge and soil particles and their infective dose.  They are:
                   INACTB     = P(14)      Inactivation rate in bulk sludge (logjo/day)
                   INACTS     = P(15)      Inactivation rate in soil (loglc/day)
                   INACTW     = P(16)      Inactivation rate in water (logn/day)
                   SSPNDB     = P(17)      Sludge-to-water resuspension factor
                                             [(number/g sludge)/(number/cm3 water) =cm3/g]
                   SSPNDS     = P(18)      Soil-to-water resuspension factor
                                             [(number/g sludge)/(number/cm3 water) =cm3/g]
                   INFALF     = P(20)      beta-Poisson alpha (required to calculate risk of infection)
                   INFBET     = P(21)      beta-Poisson beta (required to calculate risk of infection)
                   6.3.3.  Processes  and Transfers.  Transfers and  inactivation  are calculated at daily
            intervals in a do-loop structure.  The concentration of organisms in water suspension in each
            compartment is calculated using the assumed solids/water distribution coefficients.  Subsurface
            transport subroutines are called daily from the unsaturated soil and saturated soil compartments,
            and the number of pathogens in each compartment is calculated from the transfers in and out and
            the inactivation rate appropriate for each compartment.   It is assumed that  inactivation  of
            pathogens occurs at a constant exponential rate in each compartment. The only human exposure
            considered in the model is consumption of drinking water from an  offsite well.

            6.4.   CALCULATIONS
                   6.4.1.  Source Term.  Bulk Sludge in Trench or Lagoon~A full trench or lagoon as a
            starting point simplifies calculations while providing a maximum source term of sludge pathogen
            number in  the disposal unit. Sludge-specific loading parameters describe only the sludge. It is
            known that the survival of sludge  pathogens  is enhanced by moisture, organic matter and
            moderate pH values (Kowal,  1985; U.S. EPA,  1988a).  In this study it was assumed that the
            moisture and nutrient content of sludge protect  pathogens from inactivation; this assumption is
            probably overly conservative, but it provides a reasonable  worst-case assessment of potential
            risks from pathogen transport.  Depth of monofill application should allow the protective effects
            of bulk sludge to remain constant; the variable INACTB [P(13)] assumes  the default exponential
                                                    6-12
.

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die-off rate of 0 Iog10/day, but can be changed when data on die-off rates in bulk sludge become
available.
      The initial number of sludge pathogens/m2 of sludge is calculated from the concentration
of pathogens (number/kg solids), the fraction of sludge solids, the bulk density (kg/m3) and the
depth of sludge (m):
              N(1)=PATHDN*SOLIDS*BLKDEN*DEPTH  (number/m2).
      SLUDGE is the mass of sludge solids.  The mass of sludge particles is calculated from
the fraction of sludge solids, the bulk density and the depth of sludge:
                   SLUDGE=SOLIDS*BLKDEN*DEPTH   (kg/m2).
      WATER is the depth of water (m) in the sludge.  The  water  content is expressed as
meters of water/m2 of sludge, using the bulk density, solids content and depth of the sludge and
the density of water (1000 kg/m3):
                 WATER=(1-SOLIDS)*BLKDEN*DEPTH/1000  (m).
      Not all of the soil water is  free to migrate.   Some of it  is associated  with particles or
colloids or trapped by capillarity in soil pores.  In this discussion, the water that is free to move
through the soil will be termed free water. Particulate-associated pathogens can be leached into
free water. Although the actual distribution between water and particles is likely to depend on
chemical composition  of the sludge or soil and of the water solution, it is assumed that the
distribution is constant through the compartment and that suspended and particulate-bound
pathogens are in  equilibrium (i.e., the ratio of pathogens adsorbed  to solids to pathogens
suspended in free water in the same volume of soil remains constant).  The ratio of particulate-
bound to suspended organisms is given by the parameter SSPNDB for bulk sludge.
       SSPNDB [P(16)] is the sludge/water resuspension coefficient for a particular sludge and
pathogen.   The concentration of pathogens suspended in free water in the sludge column  is
calculated by using the distribution of pathogens between water and solids  (SSPNDB for sludge,
SSPNDS for soil).  The equation is derived as follows:
              Total Number N(l)   =  Nwater+NsoBd
                    Nn,,,,,         =  ConcWJIte*Amt. of water [in m because N(l) is calculated
                                       per m2 of cross section]
                                 =  C(1)*WATER
'water
                                        6-13

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                   N^jd         =  ConCjoUd^mt. of sludge
                                =  Conc^^SLUDGE.
For any distribution coefficient SSPNDX,
                   SSPNDX      = (Pathogens/kg solidj / (Pathogens/m3 water)
Therefore,
                   ConCjoiid      = Concw,ter*SSPNDx
                   Conc.,^     = C(1)*SSPNDB
and
                   Ndudge        = C(1)*SSPNDB*SLUDGE.
Combining equations,
                   N(l)         = (C(1)*WATER)+(C(1)*SSPNDB*SLUDGE)
                                = (C(1)*WATER)+(C(1)*SLUDGE*SSPNDB)
                                = C(1)*(WATER+SLUDGE*SSPNDB)
and
                   C(l)         = N(1)/(WATER+SLUDGE*SSPNDB) (pathogens/m3).
      Transfer from compartment 1 to compartment 2 (TR12) is assumed to occur by leaching
of water percolating through the sludge layer. The amount of rain (m/yr) passing through and
leaching pathogens from the sludge is calculated by using the annual amount of rainfall and the
fraction that evaporates or runs off:
                      WFLUX=ANRAIN*(1-EVAP)  (m/day).
      It is assumed that the sludge remains saturated because percolation is slow and the soil
cap placed on top of each day's application retards evaporation.  Based on this assumption,
leaching is characterized by a constant rate rather than pulses associated with rainfall. Assuming
a constant leaching rate may overestimate the length  of time for which  concentrations of
pathogens are elevated and may underestimate what would be peak concentrations of pathogens
in individual pulses (U.S. EPA, 1989d).
      The concentration [C(l)] of pathogens in pore water in compartment 1 (sludge) is used
to calculate the transfer TR12:
                               = N(1)/(WATER + SLUDGE*SSPNDB)
                                      6-14

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                   TR12        = C(1)*WFLUX
where N(l) is the number of pathogens in compartment 1 (pathogens/m2). To determine the
number of pathogens transferred to compartment 2, the concentration [C(l)3 is multiplied by the
volume of water/day percolating through a 1-m2 column of sludge at the average recharge rate.
The number of pathogens remaining in compartment 1 is the current number times the die-off
rate minus the flux to the unsaturated zone:
                         N(l)  = N(1)*(10**(-INACTB))-TR12.
       6.4.2.  Unsaturated Zone Transport.  Unsaturated transport, modeled according to
methods described for chemicals in  sludge (U.S. EPA,  1989b), uses the solution of a one-
dimensional advective-dispersive transport model (van Genuchten and Alves, 1982). This is the
same method used to model unsaturated zone transport in MULTIMED (Multimedia Exposure  .
Assessment  Model for Evaluating the Land Disposal of Wastes) developed by the U.S. EPA
(Salhotra et al., 1990).   This is also  the same model used for transport in the saturated zone.
Each daily loading of pathogens is treated as an independent pulse through the unsaturated zone.
The resulting concentration at the saturated zone boundary is calculated for every day in the
model run,  and all values  for the same  day of the model run are added together.  Thus, the
concentration reaching the saturated zone [C(2)] is the sum of all of the portions of each day's
input that arrives  at the saturated zone on that day.
       6.4.2.1. Initial Populations and Transfers~The initial concentration of pathogens in
unsaturated soil may be specified as POPL(2) during the parameter input phase of the model run.
The initial  number  of pathogens/m2 in this compartment is calculated  from the initial
concentration (number/kg), the bulk density of soil (kg/m3) and the depth of unsaturated soil (m):
                   N(2)=POPL(2)*USDEN*DSATZN (number/m2).
Unless compartment populations are entered at the beginning of the model run, it is assumed that
the initial pathogen number in the soil compartment is zero.
       The number of organisms entering the compartment daily from sludge is given by TR12,
the product of pathogen concentration in the sludge water phase and the flux of water through
the sludge.  This  number is decreased by TR23, the product of water flux and concentration of
pathogens in water in the unsaturated zone:
                               TR23 = C(2)*WFLUX.
                                         6-15

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 The latter is  calculated by  SUBROUTINE UNSATZN, which  uses the concentration of
 pathogens in the sludge water phase as the concentration entering unsaturated soil.  Die-off in
 this compartment is assumed to be exponential, described by INACTS [P(17)] (logs/day) for
 soil-bound organisms and INACTW [P(15)] (logs/day) for suspended organisms.
       The bulk density of soil in  the unsaturated (USDEN)  zone is used to calculate the
 distribution of pathogens between solids and water. This calculation assumes a particle density
 of 2650 kg/m3 (U.S. EPA, 1989b):
                         USDEN=(1-WCSAT)*2650   (kg/m3).
       Particulate-associated  pathogens are leached  into free  water.  Although  the  actual
 distribution between water and particles is  likely to  depend on chemical composition  of the
 sludge or soil and of the water  solution, it is assumed that the distribution is constant through
 the compartment and that suspended and particulate-bound pathogens are in equilibrium. The
 ratio of particulate-bound to suspended organisms is given by the parameter SSPNDS for soil.
       6.4.2.2. Derivation of Particle/Water Distribution Equations—The concentration of
 pathogens suspended in free water in the soil column  is calculated by using the distribution of
 pathogens between water and  solids (SSPNDS for soil). The equation is derived as follows:
                          Total Number N(l) = Nwater+N
11 solid-
For the unsaturated zone, the amount of water is the product of the depth to the saturated zone
(DSATZN) and the water content of soil in the unsaturated zone  (FUNSAT, defined below).
The amount of soil is the depth of unsaturated soil (DSATZN) times its bulk density (USDEN):
                   Nw.ter        = C(2)*DSATZN*FUNSAT
                   Nun^^a      = ConcimMt.soil*USDEN*DSATZN.
For any distribution coefficient SSPNDX,
                   SSPNDX      = (Pathogens/kg solidx)/(Pathogens/m3 water)
                                = Concha/Cone,^,..
Therefore,
                                = Concwater*SSPNDx
                                = C(2)*SSPNDS
and
                                = C(2)*SSPNDS*USDEN*DSATZN.
                                       6-16

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Combining equations,
             N(2)   = (C(2)*DSATZN*FUNSAT)+(C(2)*SSPNDS*USDEN*DSATZN)
                   = (C(2)*DSATZN)*FUNSAT+(C(2)*DSATZN)*(USDEN*SSPNDS)
                   = (C(2)*DSATZN)*(FUNSAT+USDEN*SSPNDS)
                   = C(2)*(DSATZN*(USDEN*SSPNDS+FUNSAT))
and
             C(2)   = N(2)/(DSATZN*(USDEN*SSPNDS+FUNSAT))  (number/m3).
      6.4.2.3.  Pore Water Velocity—Moisture content in the unsaturated zone is used to
calculate the pore water velocity in the unsaturated zone (U.S. EPA, 1989b). The fractional
water content, FUNS AT, is the product of the saturated water content of the soil and a nonlinear
function of the ratio of the flux through unsaturated soil to the flux through saturated soil. The
latter term is approximated by using the slope of the soil retention curve, which is related to soil
type (U.S. EPA, 1989b).  For typical values of water content the slope may range from 7 to 11,
but this parameter appears  in an  exponent with other terms.  The corresponding range of
exponents is 0.04 - 0.059:
           FUNS AT=(WCS AT*(WFLUX/USATCND)**(1/(2*SMRSLP+3))).
      Pore water velocity is used by the subsurface transport subroutine to calculate transport
in the unsaturated zone. Pore water velocity in the unsaturated zone is calculated from the site-
specific annual recharge rate and the moisture capacity and the matric potential (a measure of
the pressure required to remove water from the soil) of the unsaturated soil (U.S. EPA 1989b).
It is  calculated by dividing the flux through the unsaturated zone (WFLUX) by the fractional
moisture content (FUNSAT):
                       VUNSAT=WFLUX/FUNSAT  (m/day).
      6.4.2.4.  Retardation and Dispersion Coefficients—The retardation coefficient for
unsaturated  soil (RUS) is  calculated from the soil-water suspension coefficient (SSPNDS), the
soil bulk  density (USDEN)  and the moisture content in  the unsaturated zone (FUNSAT).
SSPNDS is input as P(18). USDEN is calculated as described in Section 6.4.2.1, and FUNSAT
is calculated as described  in Section 6.4.2.3. These parameters are  then used to calculate the
retardation coefficient:
       .             RUS  = 1.0 + ((SSPNDS*USDEN)/FUNSAT).
                                       6-17

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In this context, SSPNDS is analogous to KD, the soil-water partition coefficient for solutes being
transported in groundwater.  RUS is passed to the groundwater transport subroutine for
unsaturated soil.
      The hydrodynamic dispersion coefficient for unsaturated soil (DUNSAT) is calculated
from  the flux of water through the unsaturated  zone, which  is equal to the annual rainfall
[ANRAENf, P(4)] minus the fraction that evaporates [EVAP, P(5)]:
                           WFLUX =  ANRAIN*(1-EVAP)
This  value is used in an equation that has been empirically  derived to approximate the
hydrodynamic dispersion of solutes in groundwater:
                 DUNSAT=(0.6 + 2.93*(WFLUX*100)**1.11)710,000
DUNSAT is also passed to the groundwater transport  subroutine  for unsaturated soil.
      6.4.2.5. Daily Number of Pathogens—The number of  pathogens in compartment 2
[N(2)] is calculated as:
     N(2) = N(2)+TR12-TR23-(N(2)-CX(2)*DSATZN*FUNSAT)*(1-10**(-INACTS))
where INACTS [P(14)] is the pathogen inactivation rate on the soil particles (logs/day) and
CX(2) is the average concentration of suspended pathogens in the unsaturated zone.
      6.4.3.  Saturated Zone Transport.  Transport is modeled by the solution  of a one-
dimensional advective-dispersive transport model (van Genuchten and Alves,  1982) as in the
unsaturated zone.   The concentration  of pathogens from the unsaturated zone, C(2), is used
along with the transport parameters and inactivation rate, INACTS [P(14)], to determine the
concentration in the groundwater at the well, C(3).
      6.4.3.1 Initial Populations and Transfers—The initial concentration of pathogens in
saturated soil may be specified as POPL3 during the parameter input phase of the model run.
The initial number  and concentration of pathogens/m2 are analogous  to the number in the
unsaturated zone:
                   N(3) =  POPL(3)*GWDEN*AQUIFR  (number/m2).
Die-off rate is exponential, described by the inactivation rate INACTW [P(15)] (logs/day). The
concentration is calculated from the number of pathogens present in the 1-m2 column whose
volume is (1 m2)*AQUIFR*PORWTR m3; each day the number  is incremented by TR23 and
adjusted for die-off.  Concentration is calculated using the suspension factor and calculated water
                                        6-18

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volume. The resulting concentration is then passed to SUBROUTINE GRDWTR to calculate
transfer to the offsite well.
      The bulk density of soil in  the saturated (GWDEN) zone is used to  calculate the
distribution of pathogens between solids and water. This calculation assumes a particle density
of 2650 kg/m3 (Brady, 1984):
                      GWDEN = (1-PORWTR)*2650  (kg/m3).
      Paniculate-associated pathogens are leached into free water. Studies have shown that the
fraction of microorganisms suspended in water is dependent on properties of the soil as well as
on the type of microorganism (Burge and Enkiri, 1978; Drewey and Eliassen,  1968; Gerba
etal., 1975; Marshall, 1971; Reddy et al., 1981),  Although the actual distribution between
water and particles is likely to depend on chemical composition of the sludge or soil and of the
water solution, we assume that the distribution is constant through the compartment and that
suspended and particulate-bound pathogens are in equilibrium or  steady-state.  The ratio of
particulate-bound to suspended organisms is given by the parameter SSPNDS for soil.
       6.4.3.2 Particle/Water Distribution—The concentration of pathogens suspended in free
water in the soil column is calculated by using the distribution of pathogens between water and
solids (SSPNDS for soil).  For the saturated zone,
                    = C(3)*AQUIFR*PORWTR
                    = Conc»t.soU*AQUIFR*GWDEN
                    = (C(3)*AQUIFR*PORWTR)+(C(3)*SSPNDS*AQUIFR*GWDEN)
                    = C(3)*AQUIFR*(PORWTR+GWDEN*SSPNDS)
       * water
      N(3)
and
      C(3)
                   = N(3)/(AQUIFR*(GWDEN*SSPNDS+PORWTR)) (number/m3).
       6.4.3.3 Pore Water Velocity~The velocity of pore water in the saturated zone (VGW)
depends on the hydraulic gradient [GRADI, P(22)], the saturated conductivity rate [GSATCND,
P(8)] and the fractional water content of the aquifer [PORWTR, P(3)]:
                       VGW = (GSATCND*GRADI)/PORWTR
VGW is calculated after data input and  passed to the groundwater transport subroutine for
saturated soil.
                                       6-19

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       6.4.3.4 Retardation  and  Dispersion  Coefficients—The retardation coefficient  for
saturated soil (ROW) is calculated from the soil-water suspension coefficient (SSPNDS), the soil
bulk density (GWDEN) and the fractional moisture content in the aquifer (PORWTR). SSPNDS
is input as P(18).  Like USDEN, GWDEN is calculated by assuming a soil particle density of
2650 kg/cubic meter, reduced by the fraction of saturated soil that is water [PORWTR, P(3)]:
                            GWDEN=(1-PORWTR)*2650
The moisture content  for the aquifer is not reduced from  PORWTR because the aquifer is
assumed to be saturated with water.  These parameters are then used to calculate the retardation
coefficient:
                    ROW = 1.0 + ((SSPNDS*GWDEN)/PORWTR)
RGW is passed to the groundwater transport subroutine for unsaturated soil.
       The hydrodynamic dispersion coefficient for saturated soil (DGW) is calculated by a
standard empirically fitted equation for groundwater transport:
                       DGW=(VGW*0.1*XWELL) + DSTAR,
where VGW is calculated as  described in Section 6.4.3.3, XWELL (distance from the sludge
source to the groundwater well) is input as P(23) and DSTAR (the dispersivity of pathogens in
water) is input as P(19).  For solutes, dispersivity decreases  with increasing molecular weight;
because pathogens are very large relative to solute molecules, DSTAR is assumed to be very
small (IxlQ-6).  Along with  VGW and RGW, DGW is passed to the groundwater transport
subroutine for the saturated zone.
       6.4.4. Offsite Well. If the concentration of pathogens in the groundwater is greater than
zero,  SUBROUTINE  GRDWTR  is called.   The number of pathogens/m2 in the well
compartment is equal to  the concentration in groundwater multiplied by  the thickness of  the
aquifer.  The concentration  of pathogens in  the well is assumed to be the same as their
concentration in groundwater at distance XWELL from  the source:
       N(4)        = C(3)*AQUIFR  (number/m2)
       C(4)     ,   = C(3)   (number/m3).
The output from SUBROUTINE GRDWTR is passed to SUBROUTINE RISK, which calculates
the  probability of ingesting more than an infective dose  of pathogen in 2 L of well water.
                                       6-20

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      6.4.5 Risk of Infection. For infection to occur, a susceptible host must be exposed, by
a suitable exposure route, to a sufficient number of pathogens that are virulent enough to cause
infection. This model assumes that individuals ingesting contaminated drinking water from a
groundwater well are susceptible to the pathogens in the water. The quantity of water ingested
daily is not assumed to vary among exposed individuals.  The number of pathogens ingested is
calculated from the modeled concentration in the well water. This number is used in the dose-
response model to calculate the probability of infection,
       A number of models have been proposed to describe the dose responses of infectivity of
pathogens.  Most are based on mathematical theories of infection,  with parameters that are
empirically fitted to clinical data.  This SLDGFILL model uses the beta-Poisson model (Haas,
1983), which assumes that both individual susceptibility to pathogens and the infectivity of the
pathogens themselves vary within the populations being modeled. The probability of infection
is the probability of receiving  more than  an  infective dose,  or 1 minus the  sum of the
probabilities of receiving all multiples less than the infective dose.  In the beta-Poisson model,
the effectiveness of the pathogen-host interaction is described by a  distribution rather than  a
single value (Haas, 1983).  The resulting equation is:
                                P* = 1 - (1 + (N//3)r
which appears in the SLDGFILL code as
       XPROB       =!-(! + (SUMX/INFBET))**(-INFALF),
where
       XPROB       = the daily probability of infection,
       SUMX        = the calculated number of pathogens ingested daily,
       INFBET      = empirically derived value of j8 for the pathogen in question
       INFALF      = empirically derived value of a for the pathogen in question.
 Currently available  values of 0 and a are  presented in  Table 6-3.   Values for additional
 pathogens are being developed and are expected to be available within several months (Haas,
 personal communication, 1994), which will extend the flexibility of the SLDGFILL model. For
 the model determinations presented in this document, values of a and /3 for Salmonella  were
 used. Other bacterial pathogens (e.g., Shigellae) are generally much more infective, but they
                                          6-21

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Table 6-3.  Values of Alpha and Beta for Selected Pathogens
Pathogen
Salmonella spp.
Shigella dysenteriae
Shigellaflexneri 2A##
Entamoeba coll
Echovirus 12
Echovirus 12
Poliovirus 1
Poliovirus 1
Poliovirus 1
Poliovirus 3
Poliovirus 3
Rotavirus
Alpha
0.33
0.5
0.2
0.17
1.3
0.374
15
0.119
0.11
0.5
0.409
0.26
Beta
139.9
100
2000
1.32
75
186.7
1000
200
1524
1.14
0.788
0.42
Reference
Rose (1993)
Haas (1983)
Haas (1983)
Haas (1983)
Haas (1983)
Regli et al. (1991)
Haas (1983)
Haas (1983)
Regli et al. (1991)
Haas (1983)
Regli et al. (1991)
Regli et al. (1991)
                         6-22

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are found in sludge less frequently and at lower concentrations than Salmonellae.  Whenever
possible, pathogen-specific values should be used to estimate risk for other pathogens of interest.

6.5.   RESULTS
       The results of several model simulations are presented in the following sections.  The
default values for bacteria and viruses shown in Table 6-1 were used as input in the initial model
runs (Section 6.5.1).  Section 6.5,2 compares  the predictions of the SLDGFILL model with
results  obtained  in  a laboratory soil column study  and with  the  predictions of  another
unsaturated-zone transport model for pathogens. Section 6.5.3 presents the results of modeling
transport of bacteria and viruses when the parameter values were chosen to characterize six
geographically and climatologically different sites described in the pathogen risk assessments for
land application  of sludge (U.S. EPA, 1990b;  1991a,b).   The results  show  that pathogen
concentrations are attenuated with each step from the source so that no pathogens reach saturated
soil 3.5  m below  the  sludge within 2  years;  that under  default conditions, pathogen
concentrations in soil water reach an early maximum  followed by a slight  steady decrease; that
viruses are transported at significantly higher concentrations than bacteria and parasites;  and that
site-specific differences in rainfall and soil parameters have relatively little effect on pathogen
transport.                            -,               _
        6.5.1. Kinetics of Pathogen Transport. Figure 6-1 shows the kinetics of transport of
bacteria, viruses and parasites in soil  water from sludge into unsaturated soil.  Under default
conditions,  pathogens  do not reach unsaturated soil in 2 years.
        Pathogens are rapidly transported into the unsaturated soil, but under  default conditions
 they do not reach the saturated soil in 2 years.  Because transport  rates are proportional to
 SSPNDS [P(18>] (see Chapter 7), it is possible to extrapolate the time required to traverse the
 unsaturated and saturated zones. To calculate the time required for viruses to reach  the aquifer,
 the default values of PATHDN [P(13>] and SSPNDS [P(18)] (1 x 105 and 100, respectively) were
                                                       .     -                      v      -
 used.   SSPNDB [P(17)] was set at 0.  Viruses  were assumed to have reached the aquifer when
 their concentration became 2xlO'7/L, the proposed limit for groundwater (U.S. EPA, 1992).
 The extrapolated time required to reach  an aquifer 3.5 m below the sludge layer was -420
 years. To  calculate the time required to reach the well after entry into the aquifer, DSATZN
                                           6-23

-------
                                                                   500
                                                                -  400
                                                                -  300

100
200
Bacteria, monofill
Bacteria, lagoon
300      400      500
     Time (days)
  +  Viruses, monofill
  O  Viruses, lagoon
600
700
800
                                    Parasites, monofill
                                    Parasites, lagoon
Figure 6-1.  Pathogen Concentration in Unsaturated Soil
                         6-24

-------
[P(l)] was set to 0, and XWELL [P(23)] was varied (see Section 7.2.2.5). The extrapolated
time required for viruses to be transported 50 m in groundwater was ~ 128 years.  Because
SSPNDS is higher for bacteria than for viruses, the bacteria would be expected to appear in
the aquifer and the well much later (>4000 years for bacteria and > 1280 years for viruses).
These times are much greater than the survival times in soil of any known pathogens.
       Figure 6-1 shows that the concentrations of viruses in the unsaturated zone was -200
times (from a monofill) or ~ 100 times (from a disposal lagoon) the maximum concentration of
bacteria  and  parasites.  These differences are the  result of  differences in  particle/water
resuspension  coefficients and inactivation rates in the sludge-and unsaturated  zones.  At all
times,  the calculated concentration of all pathogens in water from the groundwater well was
lxlO'10/L. Conditions required to show transport to the well are described in Chapter 7.
       6.5.2. Comparison with Experimental Results.  A report comparing the outcome of
the VIRTUS model for unsaturated-zone transport to experimental data was published by Yates
and Ouyang (1992).  The predictions of the SLDGFILL model were compared with one of the
data sets used to check the VIRTUS model.  A large sludge layer was specified in these test runs
so the input of viruses to the unsaturated zone would be constant as it was in  the laboratory
study (Powelson et al., 1990).  The thickness of the unsaturated zone was varied to match the
depths at which virus  concentrations were measured in the study.  As nearly as possible,
groundwater  transport parameters  and soil properties were  as specified by the  authors of the
study.  Figure 6-2 shows that SLDGFILL predicts more rapid transport into the upper part of
the column than the VIRTUS model and laboratory results indicated, whereas the SLDGFILL
model predicted  much less transport beyond 40 cm than the  VIRTUS model and the laboratory
results showed.  However, the distance over which transport was measured in  the laboratory
study was very small compared to  the distances for which the SLDGFILL model was designed,
and the transport time was only 4 days.  Field data over larger distances and longer times are
needed to allow  a better choice among transport models.
       6.5.3.   Site-specific Parameter Testing.    In  previous  modeling  studies of  soil
amendment with sewage sludge (U.S. EPA, 1990b; 1991a,b), six hypothetical sites have been
described.  Properties of the soil and climate at these sites were used to choose values for model
                                         6-25

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    0
20
40          60
    DISTANCE (cm)
                                                  80
100
                   B Expt. Avg.
                   D VIRTUS Model
SIMULATED MIGRATION 4 DAYS
                          Expt. Range
                          SLDGFILL Model
  Figure 6-2.  Comparison of Model Results with VIRTUS Model and Experimental Data
                                    6-26

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parameters,  and the outcome  was then determined.   Variability  in  the results gave some
indication of the importance of climate and soil type on applicability of the soil amendment
technology.   Selected  values  for the same sites were used to test the sensitivity  of the
SLDGFILL  model to site-specific parameters.  The parameters chosen were ANRAIN [P(4)],
EVAP [P(5)L WCSAT [P(6)] and USATCND [P(7)]. Parameter values are listed in Table 6-4.
Default values were used for groundwater transport parameters for the sites.
       Annual rainfall amounts were calculated from average rainfall data given in soil surveys
(USDA 1980;  1981a,b,c; 1985; 1989).  In several cases, values were also included above and
below which rainfall could be expected during 20% of the years.  These values were taken to
represent the 80% upper and lower confidence intervals in a normal distribution.  From them,
the assumed standard  deviation was calculated, and  the 95% upper and  lower confidence
intervals were calculated. When these values were not available, the same ratio of upper value
to the mean was used. EVAP, the fraction of rainfall that evaporates or  runs  off, was the
default value of 0.5 except in the case of Chaves Co., NM, which was described as being very
dry (assigned a value of 0.7), and Highlands Co., FL (assigned a value of 0.6). WCSAT was
calculated from soil bulk density, as described in Section 6.4.2.1. Soil bulk density was usually
given in the soil surveys. If not, a value of 0.45 for WCSAT was used.  USATCND was listed
in tables of physical properties of the soils in the soil surveys.  Artificial parameter values were
used  to allow a comparison of results:  SSPNDB was set at 200, SSPNDS =  100, DSATZN =
0.1 and XWELL =  10.  Model runs were done for 800 days.
       Model runs for bacteria and viruses are compared in Table 6-5.  The results show that
site-specific parameters had little effect on the concentration in the unsaturated zone.   The
predicted virus concentrations in the unsaturated soil after 800 days ranged from 300/L to 980/L.
However, the predicted maximum concentration of viruses in the saturated soil ranged from
 1.3xlO'7/L to 3.0xlO"2/L.  These  results show that site-specific  parameters, most likely
variation in saturated  conductivity rate in the unsaturated soil,  had a significant  effect on
transport into  the aquifer. Even with these unrealistically low parameter values, pathogens did
not reach the groundwater well in any model run.
        Effects on soil-water suspension factors and inactivation rates are expected to be more
important in determining site-specific impacts. However, values for these parameters were not
                                         6-27

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Table 6-4.  Parameters for Site-Specific Model Evaluation
Site
No.
1
2
3
4
5
6
Location
Anderson Co., TN
Chaves Co., NM
Clinton Co., IA
Highlands Co., FL
Kern Co., CA
Yakima Co., WA
ANRAIN
P(4)
(cm)
187
42.7
130
200
37.9
29.5
EVAP
P(5)
(fraction)
0.5
0.7
0.5
0.6
0.5
0.5
WCSAT
P(6)
(fraction)
0.45
0.46
0.46
0.42
0.46
0.46
USATCND
P(7)
(m/s)
4.24 xlO-6
4.24 xlO'7
4.24 XlO-6
2.5 XlO'2
2. 82 XlO'5
2. 82 XlO-6
                       6-28

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Table 6-5. Results of Site-Specific Model Evaluation
Site
No.
1
2
3
4
5
6
Location
Anderson Co., TN
Chaves Co., NM
Clinton Co., IA
Highlands Co., FL
Kern Co., CA
Yakima Co., WA
Organism
Bacteria
Virus
Bacteria
Virus
Bacteria
Virus
Bacteria
Virus
Bacteria
Virus
Bacteria
Virus
Concentration (Pathogens/L)
at 800 days
Saturated zone
1.8X10-3
3.0 xlO-2
6.6 xia8
1.1 xlO-6
1.6X104
2.8 xlO-3
4.6 xia7
7.7 XlO"6
7.5 XlO-9
1.3 xlO-7
2.0 XlO-8
3.4 XlO-7
Unsaturated zone
6.2X101
9.8 xlO2
3.8 xlO1
6.2X102
5.3 xlO1
8.5 xlO2
4.8X101
7.5 xlO2
3.7 xlO1
3.0X102
3.7X101
6.1 xlO2
                       6-29

-------
 known.  For realistic modeling and for use of the model in a regulatory framework,  more
 information must be gathered on inactivation rates of viruses and soil-water  suspension of
 bacteria and (especially) viruses under natural conditions in soil.

 6.6.   SOURCES OF UNCERTAINTY
       The site-specific values of many of the parameters used in the model may not be known
 with certainty. Soil properties [WCSAT, P(6), USATCND, P(7) and GSATCND, P(8)] may
 be available from site characterizations, but the inherent variability of soil structure means that
 a single soil sample may not be representative of the entire unsaturated zone.  Depth to the
 saturated zone [DSATZN, P(l)]  may vary seasonally and with the amount of water in the
 trenches.   If the model is to be used to assess a potential .site for its suitability  as a sludge
 landfill, it will be necessary to gather site-specific information to reduce these uncertainties. If
 it is known that soil types vary between the soil surface and the aquifer or between the landfill
 site and the well in question, the model can be run with data describing each soil type and the
 most protective results can be used to establish concentration limits or set-back distances.
       Properties of sludge [SOLIDS, P(10) and BLKDEN, P(l 1)] may vary from batch to batch
 and may not be determined for every batch of sludge submitted for  disposal.  Comparative
 model runs (Chapter 7) have shown  that these factors do not have  a major impact on model
 outcome, so it is not essential to know them precisely. PATHDN is specific to  each batch of
 sludge and varies with different processes as well as different mixtures  of  raw sewage.
 PATHDN  cannot be  predicted  accurately   from process  knowledge;  therefore,  direct
 determination of pathogen concentrations is necessary for use'of the model.  Similarly, the
 resuspension coefficient SSPNDB [P(17)] should vary with both the nature of the pathogen and
 the composition of the sludge-water mixture. There is not yet sufficient information about the
 relationships  of the  many  interacting  factors to  allow reliable  predictions  of pathogen
 resuspension from sludge.  More research should be done to find reliable ways to determine the
 leaching characteristics of sludge-bound pathogens.
       Inactivation rates [P(14), P(15) and P(16)] under field conditions are not known  with
 much accuracy, nor are solids-to-water suspension factors [P(17), P(18)]. Infective doses  vary
greatly among pathogens, among populations of pathogens with different histories  and among
                                         6-30

-------
populations exposed to a given pathogen. Inactivation rates and infective doses are extremely
important to model outcome and need to be predicted accurately.
       Groundwater  transport parameters may be  not  be known accurately.   Retardation
coefficients for pathogens are calculated from input parameters but are not known under field
conditions, nor are hydrodynamic dispersion coefficients.  These factors are of much greater
importance than inactivation rates and infective doses. The groundwater transport subroutine
used in this model is simple and may not be highly accurate.  However, the imprecision of the
input data may be less than the uncertainties caused by variability of soil properties.
       The groundwater transport algorithm has not been validated. Many attempts have been
made to model transport of pathogens in groundwater, but all are limited by lack of suitable field
validation data.  Most assume homogeneous conditions in the soil  and constant flow rates and
inactivation.  Therefore, since the assumed conditions are not realistic, none of the models is
likely to predict pathogen movement accurately.
       A large contribution to the inherent uncertainty of the model is the number of pathogens
and pattern of exposure required to  produce an infection.  Estimates of the minimum infective
dose for bacteria and viruses vary considerably depending on several factors:  route and vehicles
of exposure (inhaled, ingested, in liquid, food or capsules); timing of the exposure (whether
acute or chronic); resistance mechanisms of the host,  including immune responses or barriers
to infection such as stomach acidity and enzymes, circulating leucocytes, etc.; general health and
age of the host; incidental treatment with antibiotics, which may reduce competition by normal
bacterial flora and thus allow pathogens to colonize more readily; and virulence of the strain or
preparation of pathogens used in-the  study. Especially with viruses,  enumeration techniques may
not be efficient, so the number of viruses in an administered dose may not be known accurately.
The beta-Poisson model allows for  variability  of susceptibility in  the test populations, so it is
probably adequate to describe risks  to sensitive individuals.
       In the SLDGFILL model, each day's exposure is considered to provide a risk of infection
independent of any other day's exposure. That is, the exposure is cumulative through that day,
but there is no accumulation beyond that day.  The host is assumed to become neither sensitized
 nor immune to the  pathogen, and  the host population is assumed to be homogeneous in its
 response to exposure.  The endpoint of the assessment is infection,  whether or not clinical
                                          6-31

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 disease is observed.  These principles are also followed in the U.S. EPA Draft Ground-water
 Disinfection Rule  (U.S. EPA, 1992).  Infection is assumed in this model to follow the beta-
 Poisson model presented in the draft rule (Regli et al., 1991; U.S. EPA,  1992).
       Because there is little information that can be used to  derive accurate estimates of
 infective dose (U.S. EPA, 1992), estimation of the risk of infection from a large number of
 sludge pathogens cannot be modeled  with a known level of confidence.  With more detailed
 information on infective doses, the model could more effectively be used to evaluate the relative
 benefits of treatment technologies that have differential effects on different pathogens.
       In summary, uncertainties result from both the  model structure and  the input data.
 Structural uncertainty remains because the equations that represent the model  structure may not
 include all of the important processes  or may not represent them accurately.   Uncertainties that
 result from the model structure are difficult to quantify until the model results are compared with
 actual field measurements.  Structural  uncertainty can be minimized by applying the model only
 to the situations for which it was designed. For example,  SLDGFILL should be used to predict
 average concentrations of pathogens in groundwater over a year. It is not designed to represent
 short-term changes during storm events.
       Parameter uncertainty results from parameters that cannot be easily measured in the field
and parameters that vary spatially and temporally.  The  effects of parameter uncertainty are
quantified in the sensitivity analysis in Chapter 7.  The parameter uncertainty  that will have the
greatest effect on the results at a site  depends on the potential parameter ranges for that site.
A site-specific  sensitivity analysis may be used  to evaluate the benefit of making additional
measurements to narrow parameter ranges. Defining those parameter values to which the model
is most sensitive will have the greatest effect on minimizing uncertainty of the results.
                                         6-32

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                           7.  SENSITIVITY ANALYSIS

      The results presented in  Section 6.5 showed that  several site-specific parameters
governing the amount and rate of leaching by rainwater had significant effects on the rates of
simulated pathogen transport. To determine whether other parameters were of more importance,
the model was tested by systematically varying each parameter over a realistic range of values.
Preliminary model runs had shown that the rate of pathogen transport depends strongly on
SSPNDS [P(18)]. SSPNDS is used to calculate the  concentration of pathogens  in soil water
when the concentration in bulk soil is known, the retardation coefficients for unsaturated-zone
(RUS) and saturated-zone (RGW) transport and the hydrodynamic dispersion coefficients (DGW
and DUNS AT).  It seemed that the effect on retardation was a likely cause for the dependence
of transport on SSPNDS. Figure 7-1 shows the dependence of RGW on both SSPNDS and
PORWTR [P(3)]} two parameters used in the calculation of RGW. RGW is directly proportional
to the value of SSPNDS and inversely proportional to PORWTR. Since RGW is the ratio of the
rate of transport of pathogens in water to the rate of movement of the water, it is clear that high
values of SSPNDS should make pathogens migrate very slowly in groundwater.
      The rate of migration of pathogens in soil water in the unsaturated zone also depends on
retardation, which is calculated  from  SSPNDS and parameters describing unsaturated soil
moisture.  Figure 7-2 shows the effect of  SSPNDS  on the rate of migration through the
unsaturated zone.  The value plotted as breakthrough  time is  the time  required  for  the
concentration of viruses in the aquifer to reach 2xlO~?/L, the proposed limit in drinking water
(U.S. EPA,  1992), when DSATZN=5 cm and SSPNDS is varied. This figure confirms the
marked sensitivity of the model to SSPNDS.
      Because the times required to achieve maximum or steady-state concentrations  under
default conditions were much longer than the model can be run, the remainder of the sensitivity
analysis was done using a version of the model in which SSPNDS is not used to calculate RGW
and RUS.  In this version of the model, SSPNDS =0 in the calculation of retardation and
dispersion coefficients,  but  not in the calculation of particle/water resuspension.  Unless
otherwise noted,  all parameters were held at default values.  The parameter values were based
on the information found in Chapter 4. Parameters for both bacteria and viruses were tested.
                                        7-1

-------
•>  e
p-  co

O  3
      0
        0            500





      ,PORWTR = 0.3  _^_ PORWTR = 0.4
1000

   SSPNDS
     1500





PORWTR = 0.5
 2000          2500





. PORWTR = 0.6
        ilgure 7-1. Dependence of Retardation Factor on SSPNDS and PORWTR
                                     7-2

-------
  700
  600 -
     0                 50                100
                                 SSPNDS [P(18)J
DSATZN=0, SSPNDB=0, Other parameters at default values
150
200
                        Figure 7-2. Effect of SSPNDS on

                     Pathogen Transport Rate in Saturated Soil

                                      7-3

-------
Results  for bacteria  are  presented in Section  7.1, and  results  for viruses are shown  in
Section 7.2.  The range of outcomes was examined to determine .how sensitive the model is to
each parameter.
      Pathogen concentrations in each compartment reached steady-state levels representing the
maximum observed concentrations for each combination of parameter values. In some cases,
the time at which steady state  was  achieved was determined.   This  value was calculated
arbitrarily as the day on which the concentration of pathogens in water in a given compartment
was not more than 2% higher than the concentration 20 days earlier.

7.1.  SENSITIVITY TESTING FOR BACTERIA
      7.1.1. Parameter Values. The parameter values used for bacterial pathogens are listed
in Table 7-1.
      7.1.2. Results for Bacteria.
      7.1.2.1. Dependence on Parameters—Individual parameters were varied over the ranges
of values shown in Table 7-1 to determine the sensitivity of the model to each parameter for
bacteria. Table 7-2 shows the calculated concentrations of bacteria in the ground water well,
saturated soil and unsaturated soil at 240 days. The maximum differences observed are plotted
against parameter numbers in Figures 7-3 and 7-4.  Figure 7-3 shows that two parameters,
PATHDN [P(13>] and  SSPNDB [(P18)], have  the  most  effect on bacterial concentrations.
PATHDN is the concentration of pathogens in sludge, and  SSPNDB is the resuspension factor
describing the ratio of the sludge pathogens associated with sludge particles  to those in water
suspension. Figure 7-4 shows the parameters that have a secondary effect on the outcome. Of
these, DSATZN [P(l)] is the most important to concentration in unsaturated soil but not in the
groundwater well.  Inactivation coefficients in sludge and  groundwater  are important, as are
some of the  groundwater transport  parameters.  The  effects of groups of parameters on
concentration are discussed in more detail below.
      7.1.2.2. Site-specific Parameters—Site-specific parameters describe the landfill site,
including properties of the soil between the sludge trench  and  the groundwater aquifer.  The
parameters in this group are DSATZN [P(1)L AQUIFR [P(2)], PORWTR [P(3)], ANRAIN
P»(4)], EVAP [P(5)], WCSAT [P(6)], USATCND [P(7)], GSATCND  [P(8)j and SMRSLP
                                        7-4

-------
                         Table 7-1. Parameters Used to Test
                          the SLDGFILL Model for Bacteria
Parameter
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18


23
Name
DSATZN
AQUIFR"
PORWTR0
ANRAIN
EVAP
WCSAT
USATCND
GSATCND
DEPTH
SOLIDS
BLKDEN
SMRSLP
PATHDN
INACTB
INACTS
INACTW
SSPNDB
SSPNDS
VOW*
DGW"
XWELL
Base
2.0
10
0.3
150
0.5
0.4
io-7
lO'7
3.5
0.17
1.3
9
5X10"
0
0.016
0.0228
2000
1000
3.6
60
50
Run number
1
0.0001
5
0.4
50
0.1
0.2
io-8

1
0.1
1.1
7
IxlO2
0.0
0.005
0.005
2000
1000
0.36
20
20
2
2
5
0.8
100
0.2
0.4
io-7

2
0.2
1.2
8
SxlO3
0.001
0.01
0.02
200
100
1.08
40
50
3
4
10
0.2
150
0.5
0.6
10*

3.5
0.25
1.3
9
5X104
0.01
0.02
0.1
20
20
3.6
60
100
4
7
10
0.4
200
0.7
- .
-

5
0.3
1.5
10
5X105
0.1
0.1
0.5
10
10
10.8
80
150
5
10
10
0.8
500
-
-
-

10
-
-
11
5X106
1
1
1
-
-
36
100
200
6
20
20
0.2
-
•
-
-

-
-'
-
' -
-
-
-
-
-
-
-
-
-
• These parameters were varied together, as shown by the joined cells.
b Subsurface transport parameter, usually calculated from SSPNDS and other parameters.
                                         7-5

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Table 7-2.  Bacterial Concentrations
  at 240 Days in Model Test Runs
Parameter
Base
DSATZN
P(l)




AQUIFR +
PORWTR
P(2) and
P(3)


ANRAIN
P(4)



EVAP
P(5)


WCSAT
P(6)

USATCND,
GSATCND
P(7) and P(8)
Run
0
1
2
3
4
5
6
1
2
3
4
5
6
1
2
3
4
* 5
1
2
3
4
1
2
3
1
2
3
Well
3.14
6.7
3.14
1.47
0.465
0.145
0.00208
3.14
3.14
3.14
3.14
3.14
3.14
3.06
3.1
3.14
3.17
3.38
3.22
3.2
3.14
3.09
3.25
3.14
3.1
3.13
3.14
3.15
Pathogens/L
Sat.
6.53
14
6.53
3.06
0.976
0.309
0.00552
6.53
6.53
6.53
6.53
6.53
6.53
6.38
6.46
6.53
6.61
7.03
6.71
6.67
6.53
6.44
6.77
6.53
6.46
6.51
6.53
6.56
Unsat.
.17.5
24.9
17.5
12.9
8.93
6.73
3.89
17.5
17.5
17.5
17.5
17.5
17.5
17.3
17.4
17.5
17.6
18.1
17.7
17.7
17.5
17.4
17.8
17.5
17.4
17.5
17.5
17.5
              7-6

-------
Table 7-2. (continued)
Parameter
DEPTH
P(9)



SOLIDS
P(10)


BLKDEN
P(1I)


SMRSLP
P(12)



PATHDN
P(13)



INACTB
P(14)



INACTS
P(15)



Run
1
2
3
4
5
1
2
3
4
1
2
3
4
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
Well
3.14
3.14
3.14
3.14
3.14
3.13
3.14
3.14
3.14
3.14
3.14
3.14
3.14
3.14
3.14
3.14
3.14
3.14
0.00627
0.314
3.14
31.4
31.4
3.14
2.16
0.086
0.000371
0
3.14
3.14
3.14
3.14
3.14
Pathogens/L
Sat.
6.53
6.53
6.53
6.54
6.54
6.52
6.54
6.54
6.54
. 6.53
6.53
6.53
6.53
6.54
6.54
6.53
6.53
6.53
0.0131
0.653
6.53
65.3
65.3
6.53
4.14
0.087
0.000299
o
6.53
6.53
6.53
6.53
6.53
Unsat.
17.5
17.5
17.5
17.5
17.5
17.5
17.5
17.5
17.5
17.5
17.5
17.5
17.5
17.5
17.5
17.5
17.5
17.5
0.035
1.75
17.5
17.5
17.50
17.5 .
10.3
0.0949
0.00012
0
17.5
17.5
17.5
17.5
17.5
          7-7

-------
Table 7-2. (continued)
Parameter
INACTW
P(16)



SSPNDB
P(17)


SSPNDS
P(18)


DUNSAT




VGW




DGW




XWELL
P(23)



Run
1
2
3
4
5
1
2
3
4
1
2
3
4
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
Well
12.9
3.87
0.0167
1.8E-12
3.6E-23
3.14
30.6
248
411
3.14
3.14
3.14
3.14
1.88
2.67
3.14
3.46
3.7
0.000011
0.16
3.14
7.52
10.2
3.13
3.13
3.14
3.14
3.15
6.9
3.14
0.84
0.219
. 0.0235
Pathogens/L
Sat.
15.1
7.32
0.948
0.0629
0.0133
6.53
63.8171
516
850
6.53
6.53
6.53
6.53
3.92
5.56
6.53
7.2
7.7
1.53
2.89
6.53
9.45
10.9
6.53
6.53
6.53
6.54
6.54
9.09
6.53
4.22
3.05
2.4
Unsat.
21
17.9
12.4
6.89
5.16
17.5 '

1380
2260
17.5
17.5
17.5
17.5
14.2
16.4
17.5
18.3
18.8
17.5
17.5
17.5
17.5
17.5
17.5
17.5
17.5
17.5
17.5
17.5
17.5
17.5
17.5
17.5
        7-8

-------
2500
2000
 u

I
.s
 u
 I
£
5
 *
1500
1000
 500
   0
                                                               SSPNDB
                                               PATHDN
                                                 I
         1  2/3.  4   5  6   7
                                  8   9   10  11  12  13  14  15  16  17  18  23

                                    Parameter Number
           Well
                                  Saturated Zone
Unsaturated Zone
         Figure 7-3. Parameters with Primary Impact on Model Output


                                   7-9

-------
Max. Difference in Cone. (Bacten'a/L)
HI K-» NJ N;
D Lrt O Ul O W
DSATZN

p
^


^
^
?
> #
>/!
INACTW
^ -'•
'y
4
f
y
\ INACTB
7
^
#
^
#
7
'/
\' 1
/ grCT ___, J |c

^
^
^
^
t
#


^
<
K
<
<
<
<
<
^
^
^
#i
^
#
^

XWELL
E3n
X^
X 15
^
x#
x '
x ^
X .
x^
12/34   5
8   9  10  11  12  13  14  15  16  17  18  23
  Parameter Number
    Well
  Saturated Zone
I Unsaturated Zone
  Figure 7-4. Parameters with Secondary Impact on Model Output

                             7-10

-------
[P(12)].  Of these parameters, only DSATZN [P(l)] had a  significant impact on bacterial
pathogen concentrations and time to steady state.  Figure 7-5 shows that both the maximum
concentration  of bacteria in  the  groundwater well and  the time  required  to reach  that
concentration depend strongly on DSATZN. When all of the  soil beneath the sludge layer is
saturated (DSATZN=0) and retardation factors equal 1, the pathogen concentration at the well
rises rapidly and remains high. With thicker layers of unsaturated soil, the well water pathogen
concentrations rise later and reach lower steady-state levels.  Figure 7-6 shows that even a
shallow layer of unsaturated soil beneath the sludge trench greatly reduces the concentration of
bacterial pathogens reaching the well. The time at which the pathogen concentration reaches
steady state is shown in Figure 7-7. It is clear from this figure that unsaturated soil significantly
retards the transport  of pathogens even when the retardation  factors are artificially low.
Although the model does not allow for a transient rise of the water table to the sludge layer, the
foregoing results show  that that eventuality could increase the concentration of pathogens in
groundwater and should be prevented by design parameters for a  sludge monofill.
       The size and volumetric moisture content of the aquifer do not have any effect on the
concentration of pathogens in water in either the saturated soil or in the well.  These parameters
would be important if the pathogens were mixed throughout the vertical extent of the aquifer.
Over short distances, however, vertical mixing of pathogens with the water in the saturated soil
compartment is negligible (U.S. EPA, 1989e). In addition, groundwater protection regulations
require that releases to Class I groundwater, which is defined as groundwater in use as a source
of drinking water, meet requirements for quality without prior dilution.  Therefore, it is  most
appropriate for the size of the aquifer not to be taken into consideration by the model.
       The amount of rainfall to which the sludge is subjected has a minor effect on bacterial
 concentration in the well (Figure 7-4). Apparently, permeability of the sludge layer is so low
 that excessive rainfall does not greatly increase the rate of leaching from the sludge.   The
 saturated water content of subsurface  soil [WCSAT, P(6)] also has a minor effect on pathogen
 concentration in the well.
        7.1.2.3.  Bulk  Sludge Parameters—These parameters describe bulk sludge in a full
 trench (or mounded area).  They are DEPTH [P(9)J, SOLIDS [P(10)], BLKDEN [P(ll)] and
 PATHDN [P(13)]. The most important of the sludge-specific parameters is the concentration
                                          7-11

-------
  8
                                                          DDaaaaaoDDD
                 50
100           150
 Time (days)
            H  Om   _4_2m    A  4m
Other Parameters at Default Values, 240 days
           7m
10m
200


20m
                       250
          Rgure 7-5. Dependence of Pathogen Transport Kinetics on DSATZN

                                    7-12

-------
0
  0
                     5                 10                15
                    DISTANCE TO SATURATED ZONE (m)
Other Parameters at Default Values
                  Figure 7-6. Dependence of Drinking Water

                     Bacterial Concentration on DSATZN
                                   7-13

-------
 0
WELL
5           10           15
 DISTANCE TO SATURATED ZONE (m)
      20
         . SATURATED SOIL
UNSATURATED SOIL
    Figure 7-7. Dependence of Compartment Equilibration on DSATZN

                            7-14

-------
of pathogens in the sludge [PATHDN, P(13)].  Figure 7-3 shows the relative importance of
bacterial concentration when compared to  other parameters.   The  steady-state bacterial
concentration  of pathogens in each  compartment  is  directly proportional to  PATHDN
(Figure 7-8).   As with the thickness of the aquifer, the thickness of the sludge layer [DEPTH,
P(9)] has no significant effect on the steady-state concentration of bacterial pathogens. However,
the length of time over which pathogens can be released without the sludge being depleted of
pathogens does depend on depth.  These results suggest that the concentration of pathogens in
the sludge determines the magnitude of the transport to groundwater, while the amount of sludge
determines the duration of the release.
       7.1.2.4.  Organism-specific Parameters-Organism-specific properties are INACTB
[P(14)], INACTS [P(15)], INACTW [P(16)L SSPNDB [P(17>] and SSPNDS [P(18)]. Figure 7-3
shows that SSPNDB  [P(17)] was one  of the two most significant parameters for  bacterial
concentration.  Figure 7-9 shows  that bacterial concentrations  are not directly proportional to
SSPNDB, but tend to level off as  SSPNDB decreases. Like PATHDN [P(13)], this parameter
plays a key role in determining the concentration of pathogens in leachate entering unsaturated
 soil from the  sludge.  Reliable data on  suspension of sludge pathogens in water  are crucial to
 realistic model predictions but are not available.
        The most significant parameters for risk of infection are the infective dose parameters
 alpha and beta [INFALF, P(20) and INFBET, P(21)], although these parameters have no effect
 on concentration of organisms in any compartment. Figure 7-10 shows the effects of different
 combinations  of alpha and beta on the daily probability of infection.  These default values are
 intended to be reasonable rather than  overly conservative.  As  shown in Table 2-2 and as
 reported by Kowal (1985), Casemore (1991) and Ward et  al.  (1986), the  estimated  ranges of
 minimum infective doses for infection by  enteroviruses are from  1 to  > 107, and for bacteria
 from 10 to 1010.
        U.S. EPA (1992) has proposed that the maximum allowable daily risk of infection with
 enteric microorganisms from ingestion of groundwater should be 2.7 x Itf7 (corresponding to an
 annual risk of 1X1O4). Assuming the exposed individual drinks 2 L of groundwater daily, the
 allowable concentration of pathogens in the groundwater is determined by the infective dose.
 Data for rotavirus infection (Regli  et al.,  1991) imply that the maximum allowable virus
                                          7-15

-------
  200
   0
                                      300         400
                                 Thousands
                    SLUDGE CONCENTRATION (Bacteria/kg)

               . UNSATURATED ZONE
                    500
600
SATURATED ZONE
            -+.WELL
DEFAULT VALUES, 240 DAYS
      Figure 7-8. Dependence of Model Outcome on Sludge Pathogen Concentration
                                    7-16

-------
   10000
   1000

-------
1E+00    1E+01     1E+02     1E+03     1E+04     1E+05     1E+06    1E+07
                          DOSE (number ingested)

_B_alpha=0.17,beta=1.32  _^_ alpha =15, beta=1000  _A_alpha=0.33,beta=140
      Kgure 7-10. Dependence of Infection Risk on Infectivity Parameters

                                7-18

-------
concentration is 2X 10'7/L, a concentration difficult to attain and to verify.  Results of model
runs in which SSPNDS is used to calculate retardation imply that even  with no retardation
(RGW=1) a concentration of 2 X10"7 is unlikely to occur at a well, although that concentration
might be achieved in groundwater in direct contact with the sludge layer.
       Persistence of pathogens in the environment is typically limited because conditions in soil
and water are not optimum for pathogens.  Inactivation rates are described by parameters P(14),
P(15) and P(16). Of these, the inactivation rate in water [INACTW, P(16)] has the most effect
on pathogen concentration,  and  the inactivation rate  in bulk sludge PNACTB, P(14)] is also
significant (Figure 7-3).  Because inactivation is a composite function of inactivation rate and
elapsed time,  pathogen concentrations in groundwater depend  on the inactivation rate,  the
distance to the well and the velocity of groundwater  travel.  As a conservative measure, it is
assumed  that bulk  sludge is protective to pathogens found there.  The protective properties of
bulk sludge in the monofill are not expected to change markedly over time.  Therefore,  the
default inactivation rate in sludge is an  exponential rate of 0 logs/day.  Other values  for
INACTB [P(14)] should be used when/if data on die-off rates in bulk sludge become available.
       Varying INACTW [P(16)] changed the concentration of pathogens in each compartment,
but in each case a steady-state level was  reached (Figure 7-11).  This was also  true when a
negative value for INACTS  [P(15)] was used to simulate growth of the bacteria  in soil at an
exponential rate of 0.05 logs/day.  Because of the dynamic movement of organisms through the
compartments, there is an equilibrium between growth or inactivation and transport: the steady-
state level (and time at which steady-state is achieved) depends on that balance, but the general
shape of the kinetic curve remains the same.
       In contrast,  with a non-zero INACTB |P(14)], the concentration of bacteria  in each
compartment reached a maximum and then decreased as the pathogens in  bulk sludge  died off
(Figure 7-12).  This implies that if conditions in bulk  sludge result in inactivation of pathogens,
the pathogen concentration  in groundwater should  be much less than if there is no die-off in
sludge. Conversely, if bacterial growth in the sludge layer is modeled by specifying a negative
value for INACTB, the concentration of bacteria in the groundwater increases throughout the
model run.  This emphasizes the importance of maintaining conditions in the sludge that do not
allow regrowth of pathogenic bacteria.
                                         7-19

-------
   15
•J
03
'C

% 10
«
CQ
   0 k
     0
50            100           150
               TIME (days)

_,_ INACTW=0.005 LOG/DAY

_o_ INACTW=1 LOG/DAY, RESULTS X 1E23
200
250
            Figure 7-11. Effect of INACTW on Kinetics of Pathogen Transport

                                      7-20

-------
   3.5
.2  2.5
o
cd
2  1.5
I
8'
   0.5
    0
      0
50
100            150
 TIME (days)
     INACTB=0 LOG/DAY
                   200           250


IN ACTB=1 LOG/DAY, RESULTS X 20
            Figure 7-12. Effect of BVACTB on Kinetics of Bacterial Transport

                                       7-21

-------
       7.1.2.5.  Groundwater  Transport Parameters—Groundwater transport parameters
 describe the soil and groundwater through which the pathogens pass to the well.  They are
 GRADI [P(22)] and XWELL [P(24)].  These parameters were tested in the model in which
 SSPNDS is used to calculate other groundwater parameters.  Those results are discussed in the
 introduction to Chapter 7.
       Parameters DUNSAT,  VGW and DGW were tested in the modified model.  DUNSAT
 has a small effect on bacterial concentrations in all three compartments, and VG\V has a small
 effect on concentrations in only two, saturated soil and the well (Figure 7-4).

 7.2.   SENSITIVITY  TESTING FOR VIRUSES
       Because infection parameters are different for viruses, and because viruses are likely to
 provide a highly significant health risk in groundwater, a separate set of model runs  was done
 to assess the sensitivity  of predicted effects for viruses.
       7.2.1.  Parameter  Values.  The parameter values used for viral pathogens  are those
 listed in Table 7-1.  In many cases, these parameters are the same as for bacteria, except for the
 virus-specific default values such as  density in sludge,  infectivity parameters, resuspension
 factors and inactivation  rates.  These values are representative of a wide variety  of viruses, and
 specific values for viruses of interest should be used to model their behavior. However, these
 values should be conservative enough to be  at least as protective as is realistic  for viral
 pathogens.
       7.2.2. Results  for Viruses.   In every case, the concentration of viruses in soil pore
 water and groundwater  was greater than that of bacteria.  This result occurred  because of the
 relatively low inactivation rates of viruses in soil and groundwater and because of lower values
 of resuspension coefficients for viruses than for bacteria.  This underscores the  significance of
 viruses as a potential health threat for surface disposal of sludge.
       7.2.2.1.  Kinetics-Kinetics of viral transport into the unsaturated zone, the saturated
 zone and then to the groundwater well are not qualitatively different from those for bacterial
pathogens.  Quantitative differences are discussed in the sections below dealing with parameter-
 specific sensitivities.
                                         7-22

-------
       7.2.2.2. Site-specific Parameters—The only site-specific parameter showing a significant
impact on concentration of viruses in the groundwater was DSATZN.[?(!)],  depth  to  the
saturated zone (Figure 7-13).  As with bacteria, the groundwater concentration decreased with
increasing depth of  unsaturated  soil.   Figure 7-13  shows  that the  maximum  observed
concentration was approximately logarithmically related to the depth of the unsaturated zone,
reflecting the exponential inactivation of viruses with traverse time in the unsaturated zone. In
these model runs the time at which a steady-state concentration was reached was also calculated.
The results showed that increasing the depth of the unsaturated zone increases the time to reach
steady-state concentrations in the saturated zone.
       7.2.2.3.  Bulk Sludge Parameters~As with bacteria, the maximum concentration of
viruses in groundwater was proportional to their density in the sludge (Figure 7-14).  The time
required  to reach steady-state levels was not affected by density.  No other sludge-specific
parameters had a significant effect on either the concentration of viruses in groundwater or the
time at which steady-state concentrations  were achieved.
       7.2.2.4.  Organism-specific Parameters—The inactivation  rate of viruses in  sludge
[P(14)] had a significant effect on both the maximum predicted concentrations in groundwater
and the time to achieve those levels (Figure 7-15).  As in the case of bacteria (Figure 7-12), as
viruses were inactivated in  the source sludge, fewer viruses entered  the unsaturated zone, and
levels in groundwater decreased  (Figure 7-16).
       The  effect of inactivation in groundwater was  more  profound than  the  effect of
inactivation in sludge.  Figure 7-17 shows that increasing inactivation  rates in groundwater
greatly  decreased the exposure concentration  at the  groundwater well.    An  exposure
concentration of 1 xlO'7 occurred when the inactivation rate in groundwater was —0.2 logs/day
and the retardation factor was  1.0,  within a reasonable range of inactivation rates.  Changes in
inactivation rate in groundwater  did not change the kinetics of transport to the well except to
alter the concentration (Figure 7-18).
       The maximum predicted virus concentrations in groundwater in the saturated zone and
the well were inversely related to resuspension from soil particles.  Figure 7-19 shows that as
the resuspension  factor  SSPNDS [P(18)3 increased, the maximum predicted concentrations
decreased.  Along with  the results shown earlier (Figure 7-1),  this shows the importance of
                                         7-23

-------
     0
5            10           15
  DISTANCE TO SATURATED ZONE (m)
20
              _a_WELL
WELL AT 50 m FROM SLUDGE SOURCE
                      SATURATED ZONE
                 Figure 7-13. Dependence of Virus Concentration
                in the Saturated Zone and the Groundwater Well on
                       Depth to the Saturated Zone [P(D]
                                   7-24

-------
   1000
>   100
     10
    0.1
     1E+03
1E+04            1E+05
   PATHOGEN DENSITY (Virus/kg)
1E+06
1E+07
                _»_WELL
 WELL AT 50 m FROM SLUDGE SOURCE
                     SATURATED ZONE
            Figure 7-14. Dependence of Maximum Predicted Virus Concentration

                          on initial Density in Sludge [P(13)]
                                      7-25

-------
 30
                                                                      200
  0.0001
0.001
      0.01          0.1
INACTIVATION RATE (log/day)
              _._ WELL, CONG.
              _e_ WELL, DAYS
WELL AT 50 m FROM SLUDGE SOURCE
                          SATURATED, CONC.
                          . SATURATED, DAYS
             Figure 7-15. Dependence of Virus Concentration and Time
           to Maximum Concentration on Inactivation Rate in Sludge [P(14>]
                                    7-26

-------
   0
    .0
200            300
 TIME (days)
   _»_ 0 LOG/HR     _+_ 0.001 LOG/HR
WELL AT 50 m FROM SLUDGE SOURCE
           0.01 LOG/HR
400
0.1 LOG/HR
500
              Figure 7-16.  Kinetics of Virus Concentration in Ground water

                  as a Function of Inactivation Rate in Sludge [P(14)]

                                       7-27

-------
   1E+02

   1E-01
£ 1E-04

O 1E-07
   IE- 10
|C_«

8  1E-
13
8
   1E-16
   IE-19
   1E-22
   1E-25
       0.001
                  0.01              0.1               1
                   INACTIVATION RATE (log/day)
                _._WELL
 WELL AT 50 m FROM SLUDGE SOURCE
                                    SATURATED ZONE
10
             Figure 7-17. Dependence of Maximum Virus Concentration in

               Groundwater on Inactivation Rate in Groundwater [P(16)J
                                     7-28

-------
                   50
100
 TIME (days)
150
200
250
             _«_ 0.005 LOG/HR  _+_ 0.02 LOG/HR
WELL AT 50 m FROM SLUDGE SOURCE
                    0.1 LOG/HR
              Figure 7-18. Kinetics of Virus Concentration in Groundwater

                   as a Function of Inactivation Rate in Sludge [P(14)]

                                        7-29

-------
   10000
O   1000
I
8
s
100
      10
                        10               100

                            RESUSPENSION FACTOR
                _»_WELL


 WELL AT 50 m FROM SLUDGE SOURCE
                                                    1000




                                      SATURATED ZONE
10000
               Figure 7-19. Dependence of Maximum Virus Concentration


               in Groundwater on Soil-to-Water Resuspension Factor [P(18>]



                                      7-30

-------
knowing the tightness of binding of the viruses in question to the soil particles. Published values
for pathogen resuspension factors are highly variable, ranging from ~5 to -2000 (Matson et
al.,  1978;  Burge  and Enkiri,  1978).   This variability limits the  accuracy  of  predicted
groundwater transport.
       Virus particles typically bind well to clay and poorly to highly organic soils (Kowal,
1985), implying that soils with a high clay content might provide a greater barrier to  virus
migration through the unsaturated zone than sandy or organic soils, although clay exhibits poor
percolation properties.  Especially in regions of low rainfall where the amount of water required
to percolate out of the landfill is low, a layer of high-clay soil beneath the landfill may provide
enhanced protection from contamination of groundwater.
       7.2.2.5.  Groundwater Transport  Parameters-Some groundwater parameters were
tested using the model in which SSPNDS is used to calculate retardation and dispersion. These
parameters DSTAR [P(19)] and GRADI [P(22)] appear only in that model.  DSTAR is used to
calculate DGW, the hydrodynamic dispersion coefficient for pathogens in groundwater.  It is a
small number added  to a term that is  ~ 1, so its value is  expected  to have little effect on
groundwater transport.  The effect of GRADI [P(22)] on rate of transport in the aquifer was
tested by setting DSATZN=0 and XWELL=5 m.  The time required for the virus concentration
to reach 2 x 10'7/L was inversely proportional to GRADI: 50 days when P(22) = 1, 99 days when
P(22)=0.5 and 246 days  when P(22)=0,2. These values extrapolate to a transport time of
 ~ 130 years for XWELL=50 m and GRADI=O.OL
        Other groundwater parameters were tested by the model in which SSPNDS is  not used
to calculate retardation and dispersion.  The effects of groundwater transport parameters on
transport of viruses to the groundwater  well were observable but relatively minor  in impact.
The effects of  ROW and RUS are reflected in the calculated breakthrough times to the
 groundwater and to the well (Figures 7-1 and 7-2).  Hydrodynamic dispersion in the unsaturated
 zone also had minor effects on the kinetics of transport and maximum predicted concentrations
 in groundwater.  The maximum predicted concentration increased non-linearly with increasing
 hydrodynamic dispersion coefficient (Figure 7-20), while the time required to reach steady-state
 levels  decreased (Figure  7-21).  This effect occurs because with increasing  hydrodynamic
 dispersion, some organisms arrive at the saturated zone, and therefore at the well, more quickly.
                                          7-31

-------
   36



   34

   30
§  28
O


8  26



1  24



   22



   20
     10      20      30     40     50     60     70     80     90

                   HYDRODYNAMIC DISPERSION COEFFICIENT
                _»_WELL

 WELL AT 50 ra FROM SLUDGE SOURCE
SATURATED ZONE
                         100
110
           Figure 7-20.  Effect of Unsaturated-Zone Hydrodynamic Dispersion

             on Maximum Predicted Virus Concentrations in Groundwater


                                    7-32

-------
Having less time for inactivation, they achieve a higher maximum concentration.  Figure 7-22
demonstrates  that the time at which pathogens first arrive at the saturated zone boundary is
shorter and the maximum concentration is greater when DUNSAT=100 than when its value
is20.
      Groundwater velocity (VGW) was an important variable at low values,  but had little
effect at high  values. Figure 7-23 shows that the predicted virus concentrations in groundwater
increased sharply as groundwater velocity increased from 0.36 to 3.6 cm/hr,  and then leveled
off.  The time to reach steady-state levels decreased accordingly (Figure 7-24).  These results
reflect increased inactivation with increased travel time of the pathogens to the well.
      The final groundwater parameter tested was distance  to the groundwater well [P(23)].
As for bacteria, this parameter had a minor influence on maximum predicted concentrations in
groundwater (Figure 7-25).  However, the effect on time required to reach steady-state levels
was significant (Figure 7-26). The effect of distance on concentration at the well would increase
with increasing inactivation rates in groundwater, and especially with the effect of SSPNDS on
retardation factors.
      It is important to remember that most of the sensitivity analysis described above ignores
the contribution of SSPNDS to retardation during subsurface transport.  The  sensitivity of the
model to variations in parameters other than SSPNDS are to a large degree overwhelmed by the
model's response to variations in  SSPNDS.  As long as it is assumed that  pathogens  are
transported in unsaturated soil and in the aquifer by advection and  dispersion rather than in
cracks and solution channels, so that retardation is a significant factor, and that the binding of
pathogens to  soil particles is described by values  of  SSPNDS observed in laboratory  studies,
SSPNDS remains the most important parameter on which to focus additional investigation.
                                         7-33

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>
   260
   250
   240
   230
   220
   210
ffi  200
W  190
O  180
H
^ 17°
& 160
W
§  150
   140
   130
      10     20     30     40     50     60     70     80     90
                    HYDRODYNAMIC DISPERSION COEFFICIENT
                                                                     100     110
                _«_WELL
 WELL AT 50 m FROM SLUDGE SOURCE
                                           SATURATED ZONE
            Figure 7-21.  Effect of Unsaturated-Zone Hydrodynamic Dispersion
                 on Time to Reach Steady-State Levels in Groundwater
                                     7-34

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0
            50
100
 150        200
TIME (days)
                                                        250
                                            300
350
                           .P(21)=100
                    P(21)=20
               Figure 7-22. Effect of Hydrodynamic Dispersion on

         Time of Transfer and Concentration of Pathogens in Groundwater

                                     7-35

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   40
2
O
   25
§  20
i  10
    0
      0
10
20
30
40
                              VELOCITY (cm/hr)

                 ,  WELL              _«_ SATURATED ZONE

 WELL AT 50 m FROM SLUDGE SOURCE
                    Figure 7-23. Effect of Groundwater Velocity

             on Maximum Predicted Virus Concentrations in Groundwater
                                    7-36

-------
w
en
 I
   600
   500
   400
00
PJ
*  300
5-
T3
   200
   100
       0
10
20
30
40
                               VELOCITY (cm/hr.)


                  , WELL              _+_ SATURATED ZONE

 WELL AT 50 m FROM SLUDGE SOURCE
                       Figure 7-24. Effect of Groundwater Velocity

                   on Time to Reach Steady-State Levels in Groundwater
                                        7-37

-------
   40
¥35
p
   30
   25
   20
   15
   10
     0
50
                    WELL
     100           150
DISTANCE TO WELL (m)
200
250
                        SATURATED ZONE
             Figure 7-25. Effect of Distance to the Groundwater Well [P(23)]

              on Maximum Predicted Virus Concentrations in Groundwater
                                      7-38

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   400
   350
   300
   250
   200
w
S  150
a
fe
ffi
   100
      0
50            100           150

        DISTANCE TO WELL (m)
200
250
                _«_WELL

 WELL AT 50 m FROM SLUDGE SOURCE
                       SATURATED ZONE
               Figure 7-26. Effect of Distance to the Groundwater Well [P(23>]


                   on Time to Reach Steady-State Levels in Groundwater


                                       7-39

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                         8.  SUMMARY AND CONCLUSIONS

       The  SLDGFILL model for  pathogen  risk assessment  has been  run  with many
combinations of input parameters to simulate the transport of sludge pathogens from a disposal
site to a nearby drinking-water well and the subsequent risk of infection to humans who drink
from the well. Conservative exposure assumptions included a drinking water consumption rate
of 2 L/day.  Projections by  the model show that the risk of infection by  bacterial or viral
pathogens is not significant at 50 m from the sludge source, even if the sludge trench or lagoon
is essentially in contact with grounclwater.  In contrast, using average values from available data
on virus transport and inactivation rates, it must be concluded that viruses present a potentially
significant health hazard to consumers of well water downgradient from a sludge disposal site.
       Sources of uncertainty in the model results have been discussed in Chapters 6 and 7.
Uncertainties result from  both the  model structure and the values of the input  parameters.
Structural uncertainty remains because the  equations that represent the model  structure may not
include all of the important processes or may  not represent them accurately.  In particular, the
assumption that pathogens are transported  by  advectioh and dispersion has not been validated.
Uncertainties that result from  the model structure are difficult to quantify until the model results
are compared with actual field measurements.  Structural  uncertainty can  be minimized by
applying the model only to the situations for which it was designed. For example,  SLDGFILL
should be used to predict average concentrations of pathogens in groundwater over a year.  It
is not designed to represent short-term changes during storm events.
       Parameter uncertainty results from parameters that cannot be easily measured in the field
and parameters that vary spatially and temporally. The effects of parameter uncertainty have
been quantified in the sensitivity analysis in Chapter 7. The parameter uncertainty that will have
the greatest effect on the results at a  site depends on the potential parameter ranges for that site.
A site-specific sensitivity analysis may be used to evaluate the benefit of making additional
measurements to narrow parameter ranges. The resuspension coefficient SSPNDS had the most
dramatic effect on  pathogen transport. The effects of other parameters were tested by using a
model in which SSPNDS was  not used to calculate the retardation and hydrodynamic dispersion
coefficients. Based on the ranges used for that sensitivity analysis, the pathogen density in the
                                          8-1

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sludge (PATHDN) and the sludge/water resuspension coefficient (SSPNDB) affected pathogen
concentration  in  the  groundwater by several  orders  of magnitude  more  than  any other
parameters.  Other parameters that had a large effect on pathogen concentration were the depth
to the saturated zone (DSATZN), the pathogen inactivation rates in water and soil  (INACTB,
and INACTW), and the distance of  the sampling  point from  the disposal  site (XWELL).
Defining these parameter values will have the most effect on minimizing  uncertainty of the
results. An important question to be answered by field data is the extent to which pathogens are
transported through cracks and solution channels rather than by advection and dispersion.
       The model can be used to highlight aspects of sludge treatment and disposal and aspects
of pathogen survival and transport under field conditions that need further study.  With further
validation, it could also be  used to show the sludge pathogen concentration limits and  well
setback distances that may be necessary to ensure adequate groundwater quality to protect human
health.  U.S. EPA (1992) has proposed a maximum annual probability of infection by enteric
pathogens of IxlO4 as  a  limit to regulate the  quality of groundwater used  for human
consumption.  A  corresponding limit on rotavirus concentration of 2 x 10"7/L has been derived
by Regli et al. (1991). By iterative operation, the SLDGFILL model could be used to determine
similar sludge concentration  limits for any pathogen whose minimum infective dose is known.
From that information, the well setback distances required to attain those limits could also be
derived.
       The dose response is characteristic of each pathogen, and alpha and  beta parameters to
describe it should be determined as each pathogen is identified and described.  However,  data
on infective doses are scarce, making  further research necessary for reliable use of the model
to predict health risks.  It is likely that viruses will present a greater health risk because they are
expected to have  a lower minimum infective dose.
       Parasites are not expected to migrate from  the bottom of the sludge trench or lagoon
because their ova and cysts are too large to be transported through unsaturated soil.  Transport
of parasite ova and cysts through cracks and solution  channels is possible,  but it cannot be
described by models based on advection and dispersion, because they typically assume that the
soil is homogeneous.
                                          8-2

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       Other than SSPNDS, after viruses reach the aquifer the most important parameter for
virus concentration in the groundwater well is the inactivation rate in water [INACTW, P(16)].
At the extrapolated time required to reach the well (—128 years for XWELL = 50 m), all
viruses would be inactivated. Changing the distance to the well changes the time over which
inactivation operates to reduce the concentration of infective virus particles.  Inactivation rates
under field conditions are  not well understood, so predictions cannot be made accurately by
modeling. However, it appears that if the setback distance to the well is chosen with an eye to
both groundwater velocity and inactivation rate,  it should be possible to maintain the virus
concentration in drinking water below the target value of 2x 10"7/L.
       The modeled concentration of pathogens in the unsaturated zone responds proportionately
to PATHDN, the concentration in the sludge.  To some degree, exposure can be controlled by
limiting the concentration in sludge accepted for landfilling or surface disposal.  However, the
concentration of viruses in well water calculated by using default parameters is at least ten orders
of magnitude below the concentration  (2xlO~7/L) proposed by Regli et al. (1991).  Therefore,
the concentration of pathogens in the sludge should not be a  concern for human health.   An
important implication  of the test results  is that the total number  of sludge pathogens in the
landfill trench or surface lagoon is less important to the pathogen concentration in the soil than
is the concentration of pathogens  in the sludge. Therefore, there would be no risk-based limit
to the depth  of sludge in the disposal units.  The strong dependence on SSPNDB suggests that
if resuspension of sludge pathogens into the water phase is high, a mixed landfill containing a
material with a lower SSPNDB  (such as clay) would  reduce transport offsite.  Because the
default condition that pathogens will not be inactivated while they are  in the sludge layer is
unlikely, any treatment that delays the leaching of pathogens to groundwater will decrease both
the magnitude and the duration of risk to groundwater consumers.
       Several parameters  were of secondary importance to model outcome.  They were the
depth of unsaturated soil, or depth to the saturated zone, [DSATZN, P(l)], pathogen inactivation
rates in bulk sludge [INACTB, P(13)], hydraulic gradient [GRADI, P(22)] and distance from
the sludge trench or lagoon to the groundwater well [XWELL, P(23)].  Of these, DSATZN
[P(l)] and XWELL [P(23)] should be known accurately at any site, and GRADI [P(22)] can be
measured.   The uncertainty  about values of the dominant  parameters PATHDN [P(13)],
                                         8-3

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SSPNDB  D?(17)] and especially SSPNDS [P(18)] is high enough that it becomes much less
important to know the parameters P(13), P(21) and P(22) accurately.
       The   soil-to-water   resuspension  factor  SSPNDS   [P(18)]  includes  effects   of
adsorption/desorption to soil in the unsaturated and saturated zones, so no additional factors for
retardation should be necessary.  No factor is included for filtration by soil structure.  Filtration
is assumed to be the dominant effect for protozoa. It  should be more significant for bacteria
than for viruses.  Therefore, because viruses appear the  most likely to constitute any health risk,
the inclusion of filtration may not be important to the model. Retardation allows more time for
inactivation  to reduce the number of infective viral particles,  so it may be very important to
determine resuspension coefficients accurately under field conditions.
                                           8-4

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                               9.  RESEARCH NEEDS

       Although significant research has provided an ever-increasing understanding of the risk
from pathogens in sludge, there are still major information needs to be satisfied. For example,
a major hurdle in any risk assessment is estimating exposure by a variety of routes or pathways
to a population that varies according to activity patterns. The use of a conservatively defined
human receptor is based, at least in part, on the difficulty in estimating exposure of a population
to a changing level, or dose, of pathogens.  Information on infective dose for most pathogens
is limited. Infective doses vary greatly among pathogens, among populations of pathogens with
different histories and among populations exposed to a given pathogen.  Infective doses  are
extremely important to model outcome and need to be predicted accurately. The limited set of
beta-Poisson parameters will  probably be expanded in  the near future.  However, the large
number of potentially pathogenic strains that may be found in sludge makes it impractical to
characterize dose responses for all of them.  Instead, a  few indicator strains should be chosen
that are widely prevalent, resistant to inactivation and highly infective and that have a significant
impact to health.  Dose responses of these indicators should be determined. In addition, rapid
and reliable quantitative assays for the  indicator strains in sludge should be developed and
uniformly applied among sewage treatment operators.  Protecting against these "worst-case"
indicators would at the same time protect against less hardy or less infectious pathogens.
       There is no accurate quantification of distribution of pathogens in soil or groundwater.
This model assumes random distribution  of pathogens in environmental media, but data are not
available to verify  this assumption.   Further research on pathogen exposure pathways and
infectious dose levels would facilitate the predictive accuracy of this model and its successors.
       Another obvious data gap, illustrated by this methodology and model development, is the
degree of survival and transport of pathogens in the environment. Inactivation rates under field
conditions are not known with much accuracy.  Information on the fate of pathogens in landfijled
or  surface-disposed  sludge,  subsurface  soil  and  groundwater is  extremely limited.   The
concentration and  survival rates of pathogens leaching through  soil into groundwater  are
unavailable for viruses, protozoa and helminths, and bacterial concentration data are few.  More
data are needed concerning the transport of pathogens through sludge, particularly as transport
                                          9-1

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rate is related to percentage solids in the sludge and to climatic factors.  There is not yet
sufficient information about the relationships of the many interacting factors to allow reliable
predictions of pathogen resuspension from sludge and soil, or solids-to-water suspension factors.
Groundwater  transport  parameters  such as  retardation coefficients  for  pathogens  and
hydrodynamic dispersion coefficients are not known  under field conditions.   More research
should be done to find reliable ways to determine the  leaching characteristics of sludge-bound
pathogens.  Likewise, data are needed on pathogen transport through the unsaturated zone,
including quantification of subsurface transport rates of pathogens as a function of soil type and
percentage of organic matter, soil chemistry, climatic  factors, etc.
       This model should be laboratory- and field-verified before using it for purposes other than
research and development.  Input of actual field data, should it become available, would reveal
other research needs and would indicate any needed additional development and refinement of
the model.  When field data on pathogen survival and transport become available, the many
different models for subsurface transport can be compared to determine which model features
are the most important, which ones provide sufficient accuracy and which ones need further
refinement.
       In summary,  future research  should be oriented toward satisfying  the  following
information needs to allow for more realistic modeling of human  health risk from pathogens
from  landfilled and surface-disposed municipal sludge:
       •      field data on subsurface transport, in both the saturated and  unsaturated zones, of
              bacteria and viruses;
       •      inactivation rates of pathogens under field conditions in sludge, soil and water;
       •      solids-to-water suspension factors applicable to sludge- and soil-bound pathogens;
       •      leaching characteristics of sludge-bound pathogens;
       •      interaction of factors affecting pathogen resuspension from sludge and  soil; and
       •      parameters needed to describe infective doses of selected  indicator species and
              strains of pathogens in sludge.
                                           9-2

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                                 10.  REFERENCES

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 Matthess, G. and A. Pekdeger.  1985. Survival and transport of pathogenic bacteria and viruses
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John Wiley and Sons, NY.  p. 472-482.

 Mbela, K.K., D.B.  McDonell, D.B. Leftwich, R.S. Reimers, M.D. Little and T.G. Akers.
 1990.  Evaluation of temperature effects on inactivation of Ascaris eggs in both aerobic and
 anaerobic digestion processes. (Submitted to J. Water Poll. Contr. Fed.)
                                        10-5

-------
Metro (Municipality of Metropolitan Seattle).  1983. Metro Sludge Quality Monitoring Report
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Moore, J.A., J. Smyth, S. Baker and J.R. Miner. 1988. Evaluating Coliform Concentrations
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NRG (National Research Council).  1983.  Risk Assessment in the Federal  Government:
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O'Donnell, C.J., K.B. Meyer, J.V. Jones, T. Benton, E.S. Kaneshiro, J.S. Nichols and F.W.
Schaefer ffl.  1984.  Survival of parasite eggs upon  storage in sludge.   Appl.  Environ.
Microbiol. 48(3): 618-625.

Pancorbo, O.C., E.G. Evanshen, W.F. Campbell, S. Lambert, S.K. Curtis and T.W.  Woolley.
1987. Infectivity and antigenicity reduction rates of human rotavirus strain Wa in fresh waters.
Appl. Environ. Microbiol. 53(8): 1803-1811.

Pedersen, D.C.  1981.   Density Levels of Pathogenic  Organisms in Municipal Wastewater
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Inc., Boston, MA.  Municipal Environmental Research Laboratory, Office of Research  and
Development, U.S. Environmental Protection Agency, Cincinnati, OH.  EPA-600/2-81-170.

Pike, E.B.,  E.G.  Carrington  and S.A.  Harman.    1988.   Destruction  of Salmonellas,
enteroviruses and  ova of parasites in wastewater sludge  by pasteurisation and anaerobic
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Powelson, D.K., J.R. Simpson and C.P. Gerba.  1990.  Virus transport and survival in saturated
and unsaturated flow through  soil columns. J. Environ.  Qual. 19:  396-401.

Rao, V.C., T.G. Metcalf and J.L. Melnick.  1986a.  Human viruses in sediments, sludges, and
soils. Bull. WHO 64(1): 1-14.

Rao, V.C., T.G. Metcalf and J.L. Melnick.  1986b.  Removal of pathogens during waste water
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Reddy,  K.R., R.  Khaleel and M.R. Overcash.  1981.  Behavior and transport of  microbial
pathogens and indicator organisms in soils treated with organic wastes.  J. Environ. Qual.  10:
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Regli, A., J.B. Rose, C.N. Haas and C.P. Gerba.  1991. Modeling the risk from Giardia and
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                                         10-6

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Reimers, R.S., M.D. Little, AJ. Englande, D.B. Leftwich, D.D. Bowman and R.F. Wilkinson.
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Reimers, R.S., M.D.  Little,  A.J. Englande, Jr., D.B. McDonell, D.D.  Bowman and J.M.
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Salo, R.J. and D.O. Cliver.  1976.  Effect of acid, pH, salts, and temperature on the infectivity
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                                        10-7

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                                        10-8

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                                        10-9

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                                                          °f
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 Technical Bulleto No. 1661
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                                                      •
                                                      ""*»*"
                                                                             n
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                                   10-10

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                                         10-11

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                                  APPENDIX A
    USER'S MANUAL FOR THE PATHOGEN RISK ASSESSMENT MODEL FOR
    MUNICIPAL SEWAGE SLUDGE LANDFILLING AND SURFACE DISPOSAL
                                   (SLDGFILL)
INTRODUCTION.  The purpose of this appendix is to provide directions for the use of the
SLDGFILL model, which has been described in the body of this document.  Before you begin,
you should have a floppy disk containing SLDGFILL.EXE.  To run the model, simply follow
the steps outlined below.
A.I.  MODEL  OVERVIEW.  This model evaluates  the potential risk to humans from
pathogenic microorganisms following surface disposal or landfilling of municipal sewage sludge.
Surface disposal includes land application of dewatered sludge to dedicated non-agricultural land
or long-term storage or disposal  of  liquid  sludge  in  surface impoundments  of lagoons.
Landfilling  is  the disposal  of dewatered  sludges (>15% solids) in sludge-only landfills
(monofills) that use trench, area fill, or diked containment methods.  The methodology and
computer model deal only with the  groundwater pathway. The other exposure routes are less
significant or better regulated through good sludge management practices.  The receptor is a
person ingesting water directly from a drinking water well near the site.
    This pathogen risk assessment model, SLDGFILL, is a compartment-vector model with four
compartments:  bulk sludge, unsaturated soil, saturated soil, and groundwater well. The model
begins with a trench filled with dewatered sludge as the worst case for the source term.  The
number of organisms in each compartment is calculated for a column with square cross-section,
1 m on each side and  the entire depth of the column.  The number of organisms may increase
or decrease by transfer from one compartment to another or they may decrease by inactivation.
Transfers are assumed to be unidirectional, from sludge  to the well from which the exposed
individual drinks.
    The program begins with a short initial sequence that calls a subroutine to enter operating
parameters. Default values of these parameters are contained in BLOCK DATA statements, but
any parameter can be  changed from the keyboard at menu prompts or from an input data file.

                                       A-l

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This subroutine is read only once during each model run.  Parameters are then converted to
consistent units, and the initial compartment loadings are calculated.  The subsurface transport
subroutines for unsaturated soil and saturated soil are then initialized.  Following the model run,
the model will display a summary table showing daily calculations made of the probability of
infection and  of pathogen concentrations in  each  subsurface compartment.  The output file,
which the user specified during the initial phase of parameter selection, can be read with a text
editor or word processor.

A.2.   SOFTWARE  AND HARDWARE REQUIREMENTS.   This  program requires a
personal computer installed with MS-DOS.  It does not require a math coprocessor, but it will
run significantly faster if one is present. The CONFIG.SYS file must be written to allow at least
20 open files, i.e. CONFIG.SYS must contain the line FILES =20. The CONFIG.SYS file must
also contain the line DEVICE=ANSI.SYS, DEVICE=VANSI.SYS, or an equivalent statement
for an ANSI device driver.

A.3.   HOW TO RUN THE MODEL. The SLDGFILL model is provided to the  user on a
floppy disk.  Although the model  can be run using  the floppy disk only, it is recommended that
the SLDGFILL file be copied to  a hard disk, if available, before the model run.  Output files
also should be saved to the hard disk, if possible.  (Important: Any existing data files that will
be retrieved for the current model run  should be copied to the same disk drive as SLDGFILL
before starting the model).
    To start the SLDGFILL model, the user will retreive the file from the hard disk or load the
program diskette into  one of the PC floppy drives.  Then the user will enter the drive name and
the model name,  for example:
                                    C:SLDGFILL
This will load the model into the computer and the following screen will appear:
                                        A-2

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                    PATHOGEN RISK ASSESSMENT MODEL FOR
             MUNICIPAL SLUDGE LANDFILLING OR SURFACE DISPOSAL
                                  VERSION 2
                                 U.S. EPA, 1994
               DO YOU WANT TO ENTER PARAMETER VALUES FROM
                        THE KEYBOARD OR FROM A FILE?
                               (ENTER "K" OR "F1)
A.4.  PRELIMINARY DECISIONS ABOUT THE MODEL RUN. The model will ask the
user a series of preliminary questions about the model run.   Each of the user's keyed-in
responses appears on the screen on the left margin beneath the question.  Then each response
is entered by pressing the "enter" key.  Once a response has  been entered the screen will
"scroll" to the next question.  (Warning: It is not possible to scroll backwards to a previous
question once a response has been entered. However,  the output file can be saved for future
editing - see Section A.6.)
    A.4.1.   Selecting a File for Parameter Values.  The model asks the user if parameter
values will be entered from the keyboard or an existing file.  If the user enters  "F" for FILE,
the  following message will appear:
                       ENTER THE NAME OF THE INPUT FILE.
                            (8 CHARACTER MAXIMUM)
                              (.IN SUFFIX IS ASSUMED)
If the user enters "K" for KEYBOARD entry of parameter values, the model will ask for a name
for the output file. In this example the user entered the name "TEST" for the output file.
                                       A-3

-------
                       ENTER A NAME FOR THE OUTPUT FILE.
                        (YOU MAY USE UP TO 8 CHARACTERS)
                 (THE SUFFIX .OUT WILL BE APPENDED TO THE NAME)
              TEST
Once the existing file is accessed or a new file is created, the model will report the name of the
file to be used for parameter selection:
                                  OUTPUT FILES
                   PARAMETER AND RESULTS SUMMARY: TEST.OUT
The user is then asked to select either landfilling or surface disposal as the model option.
                          SELECT MODEL OPTION:
                          1 = LANDFILLING
                          2 = SURFACE DISPOSAL
At this point, the user may review and edit the parameter values.
                  DO YOU WANT TO VIEW OR MODIFY PARAMETERS?
If the user enters "N" , indicating that no parameter review is needed, the model run will be

initiated, as shown in Section A.6. In most cases, the user will answer "Y" so that parameters

can be viewed and modified if necessary.  The following screen will appear:
                                       A-4

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              300
                    *** SLUDGE MONOFILL PATHOGEN MODEL***
                        ENTER VALUES FOR THE FOLLOWING
                           (PRESS RETURN AFTER EACH):
                    1. END TIME OF PRACTICE IN DAYS
                    2. FREQUENCY FOR PRINTING RESULTS IN DAYS
    A.4.2.   End Time of Practice and Frequency of Printing. The "end time of practice"
refers to the total number of days for which the model will  simulate transport following
introduction of the sludge to the landfill or surface disposal site.  The SLDGFILL model can
simulate pathogen transport to other subsurface compartments for periods as short as one day
and as long as 2000 days, or about 5.5 years/
    Frequency of printing results refers to the reporting intervals for the model output. Usually,
the user will request the results to be reported in daily intervals  (response =1).
    A.4.3.   Selection of Pathogen Type.  The user now is asked to specify one category of
pathogen for  the model run.  The answer to this question determines the default values for
pathogen-specific parameters that will appear later in the program.  In this example, the user
selected number 3, enterovirus,  a viral pathogen.
        PROVIDE PATHOGEN TYPE
        YOUR CHOICES ARE:
              1 SALMONELLA    (BACTERIA)
              2 ASCARIS         (PARASITE)
              3 ENTEROVIRUS    (VIRUS)
    A.4.4.   Pathogen Loadings from Other Sources.  The initial pathogen .loadings to the
unsaturated zone and saturated zone are presumed to be zero (0).  This scenario could be
modified if there are sources of pathogen contamination other than the sludge disposal site.  The
                                        A-5

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 initial pathogen loadings of the unsaturated and saturated soils are referred to as POPL(2) and
 POPL(3).  Loading data are expressed as PATHOGENS/KG DRY WT and are limited to the
 same category of pathogen as previously selected for the model run (in Section A.4.3).
        INITIAL PATHOGEN LOADINGS
      2: UNSATURATED ZONE       .00000
      3: SATURATED ZONE         .00000
(POPL(2)- PATHOGENS/KG DRY WT)
(POPL(3)- PATHOGENS/KG DRY WT)
     TO CHANGE INITIAL PATHOGEN LOADINGS ENTER THE
     COMPARTMENT NUMBER.
     (ENTER 0 TO ACCEPT THE CURRENT VALUES.)
       0
In this example, only sources of viral pathogens were considered.  (Important: POPL(2) and
POPL(3) are not parameters that are saved to the output file; any modifications of these values
must be re-entered for each model run).  See Section 6.4.2 for a discussion of POPL(2) and
Section 6.4.3 for POPL(3).

A.5.   SELECTING VALUES FOR KEY PARAMETERS. The next series of screens allows
the user to view and modify the 23 key parameters of the SLDGFILL model.  These parameters
are organized under the following headings:  physical, pathogen-specific,  and groundwater
transport.
    A.5.1.   Physical  Parameters.   The first set of parameters presented are  physical
parameters. The physical properties of the sluge and of the site's underlying soil layers are
addressed under this heading. Default values appear on the screen for each parameter.  (Note:
If an existing file had been retrieved, the file values would appear instead of the default values.)
    The model allows the user to  edit any or all parameter values.  Parameter definitions and
ranges of probable values are presented at the end of Appendix A in Table  A-l. The values
within a heading can be edited and re-edited in any order.  However, once the user accepts a
set of values by keying in "0", the model  will proceed to the next set of parameters.
                                        A-6

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PHYSICAL PARAMETERS
PARAMETER NAME
1: DSATZN
2: AQUIFR
3: PORWTR
4: ANRAIN
5: EVAP
6: WCSAT
7: USATCND
8: GSATCND
9: DEPTH
10: SOLIDS
11: BLKDEN
12: SMRSLP

VALUE
3.5000
10.000
0.32000
150.00
0.50000
0.43700
6.40000E-07
5.80000E-05
3.50000
0.17000
1.38000
8.52000

UNITS CHANGED
(M)
(M)
(FRACTION)
(CM)
(FRACTION)
(FRACTION)
(M/S)
(M/S)
(M)
(FRACTION)
(G/CM3)

TO CHANGE PHYSICAL PARAMETERS ENTER THE
PARAMETER NUMBER. (ENTER 0 TO
4
ACCEPT ALL

VALUES.)

If the user wishes to change the value of a physical parameter, the number of that parameter
must first be entered.  For example, in this model run, the user has entered "4" for the annual
rainfall parameter ANRAIN P(4).  The model then  asks for the new value for ANRAIN.
                                       A-7

-------
ENTER NEW VALUE FOR PARAMETER
100
PHYSICAL PARAMETERS
PARAMETER NAME
1: DSATZN
2: AQUIFR
3: PORWTR
4: ANRAIN
5: EVAP
6: WCSAT
7: USATCND
8: GSATCND
9: DEPTH
10: SOLIDS
11: BLKDEN
12: SMRSLP
TO CHANGE PHYSICAL PARAMETERS
ANRAIN IN


VALUE
3.5000
10.000
0.32000
100.00
0.50000
0.43700
6.40000E-07
5.80000E-05
3.50000
0.17000
1.38000
8.52000
ENTER THE
(CM)


UNITS CHANGED
(M)
(M)
(FRACTION)
(CM) *
(FRACTION)
(FRACTION)
(M/S)
(M/S)
(M)
(FRACTION)
(G/CM3)


PARAMETER NUMBER. (ENTER 0 TO ACCEPT ALL VALUES.)
0


Table A-l  shows that the default value for ANRAIN is 150 cm and that the rationale for
selecting a value is site-specific.  In  this example, the  user selects and  then enters "100",
indicating an average rainfall of 100 cm/yr for the sludge disposal site.  The model substitutes
"100.00" under VALUE for ANRAIN.   An  asterisk (*) appears in the far right column
indicating that a change has been made to that parameter.  The same procedure would be used
to edit values for an existing file.
    A.5.2.   Pathogen-specific Parameters.   The next set  of parameters presented are
pathogen-specific.  If possible, the user should enter a site-specific value for PATHDN, the
pathogen density in the sludge, because the model results are sensitive to this parameter.  A
range of values specific to each type of pathogen is presented in Table A-l.
                                         A-8

-------
THE PATHOGEN ENTEROVIRUS WAS SELECTED.
PATHOGEN-SPECIFIC PARAMETERS
PARAMETER NAME VALUE
13: PATHDN l.OOOOOE+05
14: INACTB 0.00000
IS: INACTS 1.70000E-03
16: INACTW 7.50000E-03
17: SSPNDB 20.0000
18: SSPNDS 100.000
19: DSTAR l.OOOOOE-06
20: INFALF 15.0000
21: INFBET 1000.00


UNITS CHANGED
(NO./KG)
(LOG10/DAY)
(LOG10/DAY)
(LOG10/DAY)
(CM3/G)
(CM3/G)
(CM2/SEC)

--..-'
TO CHANGE PATHOGEN-SPECIFIC PARAMETERS ENTER THE
PARAMETER NUMBER. (ENTER 0 TO ACCEPT ALL
0
VALUES.)

    A.5.3.   Groundwater Transport Parameters.  The final set of parameters are those
related to movement of groundwater between the landfill and the well.
       TRANSPORT MODEL PARAMETERS

     PARAMETER NAME               VALUE
     22:
     23:
GRADI
XWELL
l.OOOOOE-02
50.000
UNITS


(M)
                                                    CHANGED
     TO CHANGE TRANSPORT MODEL PARAMETERS ENTER THE
     PARAMETER NUMBER. (ENTER 0 TO ACCEPT ALL VALUES.)

    23

     ENTER NEW VALUE FOR PARAMETER XWELL  IN (M)

     30
                                    A-9

-------
The actual distance to the well from the sludge area source (XWELL) should be entered if
available. In this example, XWELL was known to be 30 m and therefore parameter number

"23" was selected and a new value of "30" was entered.
        TRANSPORT MODEL PARAMETERS

     PARAMETER NAME               VALUE
     22:
     23:
GRADI
XWELL
l.OOOOOE-02
30.000
                                         UNITS
(M)
                              CHANGED
     TO CHANGE TRANSPORT MODEL PARAMETERS ENTER THE
     PARAMETER NUMBER. (ENTER 0 TO ACCEPT ALL VALUES.)

      0
A.6. SAVING THE MODIFIED PARAMETER VALUES AND INITIATING THE RUN.
Once the parameter review is completed, the  model  allows the user to create a unique

descriptive header for the run.
     DESCRIPTIVE HEADER FOR RUN FOLLOWS:
     1:
     2:
     3:
     4:
     5:
     TO REPLACE A LINE ENTER THE LINE NUMBER.
     (ENTER 0 TO ACCEPT ALL LINES.)
In this example,  the first line of the header was selected and the text was entered: "MOST
PROBABLE VALUES."  Other pertinent information was then entered for lines 2-4. (Note:
lines do not "wrap" around; each header entry is limited to one line).
                                     A-10

-------
     DESCRIPTIVE HEADER FOR RUN FOLLOWS:
     1:  MOST PROBABLE VALUES
     2:  ENTEROVIRUS
     3:  ABC LANDFILL, ANYTOWN USA
     4:  30 METERS FROM LANDFILL TO WELL
     5:
     TO REPLACE A LINE ENTER THE LINE NUMBER.
     (ENTER 0 TO ACCEPT ALL LINES.)
The user can save the modified parameter values for future reference by entering "Y" for YES
and by naming the parameter file.  All files should be saved to a hard disk if possible, or to the
same floppy diskette as SLDGFILL if there is capacity on the diskette.
     DO YOU WANT TO SAVE THE REVISED PARAMETERS?
              (ENTER "Y" OR "N")
The user is asked to name the file of modified parameters.  In this example, the parameter file
was named "ABC-RUN1."                      :
       ENTER A NAME FOR THE PARAMETER FILE.
        (8 CHARACTER MINIMUM)
       (.IN SUFFIX IS ASSUMED)
   ABC-RUN1
 ********MODEL INTTIALIZED-RUN STARTED********
Once the parameters are saved and the file is named, the model run will be initiated.  (Hint:
If the user wishes to stop the model run, type "CTRL C".  Results will not be displayed, and
the run must be re-initiated.) The model will display a summary table showing daily
calculations made of the probability of infection and of pathogen concentrations in each
subsurface compartment.
                                      A-ll

-------
        INFECTION
    DAY **PROB**
       1 O.OOE+00
       2 O.OOE+00
       3 O.OOE+00
       4 O.OOE+00
       5 O.OOE+00
       6 O.OOE+00
       7 O.OOE+00
       8 O.OOE+00
     10 O.OOE+00
     11 O.OOE+00
     12 O.OOE+00
     13 O.OOE+00
***CONCENTRATION IN COMPARTMENT***
*********(PATHOGENS/LITER)*********
**WELL** *SAT ZN* DNSAT ZN *SLUDGE*
O.OOE+00 O.OOE+00
O.OOE+00 O.OOE+00
O.OOE+00 O.OOE+00
O.OOE+00 O.OOE+00
O.OOE+00 O.OOE+00
O.OOE+00 O.OOE+00
O.OOE+00 O.OOE+00
O.OOE+00 O.OOE+00
O.OOE+00 O.OOE+00
O.OOE+00 O.OOE+00
O.OOE+00 O.OOE+00
.02E+02 4.02E+03
.02E+02 4.02E+03
.02E+02 4.02E+03
.02E+02 4.02E+03
.02E+02 4.02E+03
.02E+02 4.02E+03
.02E+02 4.02E+03
.02E+02 4.02E+03
.02E+02 4.02E+03
.02E+02 4.02E+03
.02E+02 4.02E+03
O.OOE+00 O.OOE+00 4.02E+02  4.02E+03
A.7.  RECOVERING THE DATA.  After the run has been completed, you will see the
reminder,
     . . . RUN COMPLETE
             OUTPUT FILES
     PARAMETER AND RESULTS SUMMARY: TEST.OUT
To view the results, the user can use a word processor, text editor, or the TYPE command
using the filename provided by the user at the second prompt after invoking the model:
"TYPE FILENAME.OUT".  The file will then scroll up the monitor screen.  The scrolling
can be stopped by typing "CTRL S".  It will continue if the user strikes any key.
   To print the results, use the print functions of a word processor or text editor, or type
"CTRL P" to activate the printer echo mode of the computer; then  "TYPE
FILENAME.OUT". The file should then be printed. This file contains the descriptive
header supplied by the user, a summary of the parameters accepted, and the probability of
infection for each day. The output file also gives the concentration of pathogens in each of
the four compartments in pathogens/liter. (WARNING: Avoid specifying a font that uses
                                   A-12

-------
proportional spacing for the output files.  Proportional spacing may result in unaligned
columns.)

A.8.   SAMPLE INPUT AND OUTPUT.  The test.out file contains input parameters,
default values and those modified by the user, for the model run.  Results are also included
in this file.  The following pages are a portion of the test, out file that resulted from  the
preceding examples.
                                         A-13

-------
  ******:


 FILE test.OUT
                                                   r*****************
                                                          r**************
  MOST PROBABLE VALUES
  ENTEROVIRUS
  ABC LANDFILL, ANYTOWN USA
  30 METERS FROM LANDFILL TO WELL
    PRACTICE STOP TIME=     300 DAYS
    PRINT SAMPLING RATE (IPRNT) =    1 DAYS
    PATHOGEN =  3 ENTEROVIRU
    INITIAL POPULATIONS FOR COMPARTMENTS (PATHOGENS/KG DRY WGT)
   1:   SLUDGE               =  5.0000E+04
   2:   UNSATURATED ZONE     =  0.0000
   3:   SATURATED ZONE       =  0.0000

 THE FOLLOWING INPUT PARAMETERS WERE ACCEPTED:
  1
  2
  3
  4
  5
  6
  7
  8
  9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
VARIABLE

  DSATZN
  AQUIFR
  PORWTR
  ANRAIN
  EVAP
  WCSAT
  USATCND
  GSATCND
  DEPTH
  SOLIDS
  BLKDEN
  SMRSLP
  PATHDN
  INACTB
  INACTS
  INACTW
  SSPNDB
  SSPNDS
  DSTAR
  INFALF
  INFBET
  GRADI
  XWELL
   VALUE

 3.500
 10.00
0.3200
 100.0
0.5000
0.4370
6.4000E-07
5.8000E-05
 3.500
0.1700
 1.380
 8.520
l.OOOOE+05
0.0000
1.7000E-03
7.5000E-03
 20.00
 100.0
l.OOOOE-06
 15.00
 1000.
l.OOOOE-02
 30.00
                            CHANGED
                            BY USER
   UNITS
(M)
(M)
(FRACTION)
(CM)
(FRACTION)
(FRACTION)
(M/S)
(M/S)
(M)
(FRACTION)
(G/CM3)

(NO./KG)
(LOGIO/DAY)
(LOGIO/DAY)
(LOGIO/DAY)
(CM3/G)
(CM3/G)
(CM2/SEC)
                                     (M)
                   *********CONCENTRATION IN COMPARTMENT**********
        INFECTION  ***************(PATHOGENS/LITER)***************
  DAY    **PROB**    **WELL**    *SAT ZN*    UNSAT ZN*   *SLUDGE*

                                   A-14

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2
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50 .
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54
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.QOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
0 .OOE+00
0; OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
0". OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
4. 02E+02
4.02E+02
4.02E+02
4.02E+02
4.02E+02
4.02E+02
4.02E+02
.4.02E+02
4.02E+02
4.02E+02
4.02E+02
4.02E+02
4.02E+02
4.02E+02
4.02E+02
4.01E+02
4.01E+02
4.01E+02
4.01E+02
4.01E+02
4.01E+02
4. 01E+02
4.01E+02
4.01E+02
4.01E+02
4.01E+02
4.01E+02
4.01E+02
4.01E+02
4.01E+02 -
4.01E+02
4.01E+02
4 . 01E+02
4.01E+02
4.01E+02
4.01E+02
4.01E+02
4.01E+02
4. 01E+02
4.01E+02
4.01E+02
4.01E+02
4.01E+02
4.01E+02
4. 01E+02
4.01E+02
4.01E+.02
4.01E+02
4.01E+02
4.01E+02
4.01E+02
4.01E+02
4.00E+02
4.00E+02
4.02E+03
4 . 02E+03
4.02E+03
4.02E+03
4.02E+03
4.02E+03
4.02E+03
4. 02E+03
4.02E+03
4.02E+03
4.02E+03
4.02E+03.
4.02E+03
4.02E+03
4.02E+03
4.01E+03
4.01E+03
4.01E+03
• 4.01E+03
4.01E+03
4.01E+03
4.01E+03
4.01E+03
4.01E+03
4 . 01E+03
4.01E+03
4.01E+03
4.01E+03
4.01E+03
4.01E+03
4 . 01E+03
4.01E+03
4. 01E+03
4.01E+03
4.01E+03
4.01E+03
4.01E+03
4.01E+03
4.01E+03
4.01E+03
4.01E+03
4.01E+03
4.01E+03
4.01E+03
4.01E+03
4.01E+03
4 . 01E+03
4.01E+03
4.01E+03
4.01E+03
4.01E+03
4.01E+03
4.00E+03
4.00E+03
A-.15

-------
55
56
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108
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+OQ
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00 .
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
0 .OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
4.00E+02
4.00E+02
4.00E+02
4.00E+02
4.00E+02
4.00E+02
4-. OOE+02
4.00E+02
4. OOE+02
4.00E+02
4.00E+02
4.00E+02
4. OOE+02
4.00E+02
4. OOE+02
4. OOE+02
4. OOE+02
4. OOE+02
4. OOE+02
4. OOE+02'
4. OOE+02
4. OOE+02
4. OOE+02
4. OOE+02
4. OOE+02
4. OOE+02
4. OOE+02
4. OOE+02
4. OOE+02
4. OOE+02
4. OOE+02
4. OOE+02
4. OOE+02
4. OOE+02
4. OOE+02
4. OOE+02
3.99E+02
3.99E+02
3.99E+02
3.99E+02
3.99E+02
3.99E+02
3.99E+02
3.99E+02
3.99E+02
3.99E+02
3.99E+02
3.99E+02
3.99E+02
3.99E+02
3.99E+02
3.99E+02
3.99E+02
3.99E+02
4.00E+03
4.00E+03
4.00E+03
4.00E+03
4.00E+03
4.00E+03
4.00E+03
4.00E+03
4.00E+03
4.00E+03
4.00E+03
4.00E+03
4.00E+03
4.00E+03
4.00E+03
4.00E+03
4.00E+03
4.00E+03
4.00E+03
4.00E+03
4.00E+03
4.00E+03
4.00E+03
4.00E+03
4.00E+03
4.00E+03
4.00E+03
4.00E+03
4.00E+03
4.00E+03
4.00E+03
4.00E+03
4.00E+03
4.00E+03
4.00E+03
4.00E+03
3.99E+03
3.99E+03
3.99E+03
3.99E+03
3.99E+03
3.99E+03
3.99E+03
3.99E+03
3 .99E+03
3.99E+03
3.99E+03
3.99E+03
3 .99E+03
3.99E+03
3.99E+03
3.99E+03
3.99E+03
3.99E+03
A-16

-------
109
110
111
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142
143
144
145
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147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
.OOE+00
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.OOE+00
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.OOE+00
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.OOE+00
.OOE+00
.OOE+00
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.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
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.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
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.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
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.OOE+00
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.OOE+00
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0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
• o
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
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.OOE+00
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.OOE+00
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.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
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.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00 •
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
0
0
0
0
. 0
0
' 0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
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.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
.OOE+00
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
.3
' 3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
:3
. 99E+02 •
.99E+02
.99E+02
.99E+02
.99E+02
.99E+02
.99E+02
.99E+02
.99E+02
.99E+02
.99E+02
.99E+02
.99E+02
.99E+02
.99E+02
.99E+02
. 99E+02
.99E+02
.99E+02
.98E+02
.98E+02
.98E+02
.98E+02
.98E+02
.98E+02
.98E+02
.98E+02
.98E+02
.98E+02
. 98E+02
.98E+02
.98E+02
.98E+02
.98E+02
.98E+02
.98E+02
.98E+02
.98E+02
.98E+02
.98E+02
.98E+02
.98E+02
.98E+02
.98E+02
. 98E+02
.98E+02
.98E+02
.98E+02
, 98E+02
.98E+02
.98E+02
.98E+02
.98E+02
.98E+02
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
-.3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
.99E+03
. 99E+03
.99E+03
.99E+03
.99E+03
. 99E+03
.99E+03
.99E+03
. 99E+03
. 99E+03
. 99E+03
.99E+03
.99E+03
. 99E+03
. 99E+03
. 99E+03
.99E+03
. 99E+03
.99E+03
.98E+03
. 98E+03
.98E+03
. 98E+03
. 98E+03
. 98E+03
. 98E+03
. 98E+03
. 98E+03
. 98E+03
. 98E+03
. 98E+03
. 98E+03
. 98E+03
. 98E+03
. 98E+03
. 98E+03
.98E+03
. 98E+03
. 98E+03
. 98E+03
.98E+03
. 98E+03
. 98E+03
. 98E+03
. 98E+03
. 98E+03
. 98E+03
. 98E+03
. 98E+03
. 98E+03
. 98E+03
.98E+03
. 98E+03
. 98E+03
A-17

-------
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
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O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
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O.OOE+00
O.OOE+00
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O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
' O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O:OOE+OO
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
1 O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
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O.OOE+00
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O.OOE+00
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O.OOE+00
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O.OOE+00
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O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
3.98E+02
3. 98E+02
3.97E+02
3.97E+02
3. 97E+02
3.97E+02
3.97E+02
3.97E+02
3.97E+02
3.97E+02
3.97E+02
3.97E+02
3.97E+02
3.97E+02
3.97E+02
3.97E+02
3.97E+02'
3.97E+02
3.97E+02
3.97E+02
3.97E+02
3.97E+02
3.97E+02
3.97E+02
3.97E+02
3.97E+02
3.97E+02
3.97E+02
3.97E+02
3.97E+02
3.97E+02
3.97E+02
3.97E+02
3.97E+02
3.97E+02
3.97E+02
3.97E+02
3.97E+02
3.97E+02
3.97E+02
3.96E+02
3.96E+02
3.96E+02
3.96E+02
3.96E+02
3.96E+02
3.96E+02-'
3.96E+02
3.96E+02 .
3.96E+02
3.96E+02
3.96E+02
3.96E+02
3.96E+02
3.98E+03
3.98E+03
3.97E+03
3.97E+03
3.97E+03
3.97E+03
3.97E+03
3.97E+03
3.97E+03
3.97E+03
3.97E+03
3.97E+03
3.97E+03
3.97E+03
3.97E+03
3.97E+03
3.97E+03
3.97E+03
3.97E+03
3.97E+03
3.97E+03
3.97E+03
3.97E+03
3.97E+03
' 3.97E+03
3.97E+03
3.97E+03
3.97E+03
3.97E+03
3.97E+03
3.97E+03
3.97E+03
3.97E+03
3 .97E+03
3.97E+03
3.97E+03
3.97E+03
3.97E+03
3.97E+03
3 .97E+03
3.96E+03
3:96E+03
3.96E+03
3.96E+03
3.96E+03
3.96E+03
3.96E+03
3.96E+03
3.96E+03
3.96E+03
3.96E+03
3.96E+03
3.96E+03
3.96E+03
A-18

-------
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234 .
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264 ,
265
266
267
268
269
270
O.OOE+00 *
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OQE+00
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O.OOE+00
O.OOE+00
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O.OOE+00
O.OOE+00
- O.OOE+00
O.OOE+00
O.OOE+00
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O.OOE+00
O.OOE+00
O.OOE+00
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O.OOE+00
O.OOE+00
O.OOE+00 ,
O.OOE+00
O.OOE+00
O.OOE+00
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O.OOE+00
O.OOE+00
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O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
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O.OOE+00
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O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
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O.OOE+00
O.OOE+00
O.OOE+00
0.. OOE+00
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O.OOE+00
O.OOE+00
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O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
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O.OOE+00
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O.OOE+00
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0, OOE+00
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O.OOE+00
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O.OOE+00
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O.OOE+00
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0.. OOE+00
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3.96E+02
3.96E+02
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. 3.96E+02,
3.96E+02
3.96E+02
3.96E+02
3.96E+02
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3.96E+02
3.96E+02
3.96E+02
3.96E+02
3.96E+02
3.96E+02
3.96E+02
3.96E+02
3.96E+02
3.96E+02
3.S6E+02
3.96E+02
3.96E+02
3.96E+02
3.96E+02
3 . 95E+02
3.95E+02
3 .95E+02
3.95E+02
3.95E+02
3.95E+02
3.95E+02
3.95E+02
3. 95E+02
3.95E+02
3.95E+02
3.95E+02
3 . 95E+02
3.95E+02
3.95E+02
3.95E+02
3.95E+02
3.95E+02
3.95E+02
3.95E+02
3.95E+02
3.95E+02
3 .95E+Q2
3.95E+02
3.95E+02
3.95E+02
3.95E+02
3.95E+02
3.95E+02
3.95E+02
3.96E+03
3.96E+03
3.96E+03
3.96E+03
3.96E+03
3.96E+03
3.96E+03
3.96E+03
3.96E+03
.3.96E+03
3.96E+03
3.96E+Q3
3.96E+03
3.96E+03
3.96E+03
3.96E+03
3.96E+03
3.96E+03
3.96E+03
3.96E+03
3.96E+03
3.96E+03
3.96E+03
3.96E+03
3.95E+03
3.95E+03
3.95E+03
3.95E+03
3.95E+03
3.95E+03
3.95E+03
3.95E+03
3 . 95E+03
3.95E+03
3.95E+03
3.95E+03
3.95E+03
3.95E+03
3.95E+03
3 .95E+03
3 .95E+03
3.95E+03
3 .95E+03
3.95E+03
3.95E+03
3.95E+03
3.95E+03
3.95E+03
3.95E+03
3.95E+03
3.95E+03
3.95E+03
3.95E+03
3.95E+03
A-19

-------
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
O.OOE+00
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O.OOE+00
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O.OOE+00
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3.94E+02
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3.94E+02
3.94E+02
3.94E+02
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3.94E+02
3.94E+02
3.94E+02
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3
3
3.95E+03
3.95E+03
3.95E+03
3.95E+03
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3.95E+03
3.95E+03
3.94E+03
3.94E+03
3.94E+03
3.94E+03
3.94E+03
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3.94E+03
3.94E+03
3.94E+03
3.94E+03
3.94E+03
3.94E+03
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3.94E+03
3.94E+03
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3.94E+03
3.94E+03
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3.94E+03
3
3
                                  A-20

-------


1

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                                             A-22

-------

-------
!
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                                              A-24

-------
1

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                                                               A-25
U.S. GOVERNMENT PRINTING OFFICE:  1995-653-487

-------

-------