&EFA
United States Office of Water EPA-821 -B-01 -008
Environmental Protection (4303) January 2002
Agency Washington, DC 20460
Environmental Assessment of
Proposed Effluent Limitations
Guidelines and Standards for
the Meat and Poultry Products
Industry Point Source
-------
Table of Contents
Executive Summary ES-1
1.0 Introduction 1-1
1.1 Definition of MPP 1-1
1.2 Water Quality Issues Related to MPP 1-1
1.3 Potential Environmental Impacts of MPP 1-2
1.4 Organization of Report 1-3
2.0 Methodology 2-1
2.1 Introduction 2-1
2.2 Overview of Water Quality Assessment Approach 2-1
2.2.1 Characterize Effluent Discharges 2-3
2.2.2 Ensure MPP Survey Data is Model Read 2-4
2.3 Overview of NWPCAM .1.1 2-4
2.3.1 Types of Water Polluton Problems and Policies that Can Be Analyzed with
NWPCAM 2-5
2.4 Pollutant Parameters Modeled Using NWPCAM 1.1 2-6
2.4.1 Dissolved Oxygen (DO) 2-6
2.4.2 Biochemical Oxygen Demand (BOD) 2-6
2.4.3 Total Kjeldahl Nitrogen (TKN) 2-8
2.4.4 Total Suspended Solids (TSS) 2-9
2.4.5 Fecal Coliform Bacteria (FCB) 2-9
2.4.6 Nutrients (Total Nitrogen and Total Phosphorus) 2-10
2.5 Water Quality Modeling 2-11
2.6 Water Use Support Determinations 2-11
2.7 Facility Effluent Data Inputs for NWPCAM 2-14
2.8 Model Runs 2-14
2.9 Creating Municipal and Industrial Select Tables 2-16
2.10 Direct Industrial Dischargers 2-16
2.11 Indirect Industrial Dischargers 2-16
2.12 POTWs 2-17
3.0 Data Sources 3-1
3.1 Point Source Loads Used in NWPCAM to Estimate Baseline Water Quality Conditions . . 3-1
3.1.1 Municipal and Industrial Dischargers 3-2
3.1.1.1 Primary Data Sources 3-2
3.1.1.2 Typical Pollutant Concentrations 3-4
3.1.1.3 Inventory of Point Source Facilities 3-4
3.1.2 Urban Runoff and Combined Sewer Overflows 3-5
3.1.2.1 Primary Data Sources 3-5
-------
3.1.2.2 Typical Pollutant Concentrations 3-6
3.1.2.3 Primary Data Sources for Urban Runoff Estimates 3-7
3.2 Nonpoint Source Loads 3-7
3.3 Facility-Specific Loading Data 3-9
4.0 Results 4-1
4.1 WQEA Results Summary 4-1
4.1.1 Treatment Options Modeled 4-3
4.1.2 Facilities Modeled 4-4
4.1.3 Simplified Environmental Scale-up Factor 4-4
4.1.4 Limitations of the WQEA 4-5
4.2 Documented Environmental Effects 4-6
5.0 References 5-1
11
-------
Table of Contents (continued)
APPENDICES
A: Preamble Correction A-l
B: Equations used to update municipal facility loadings B-l
C: Modules C-l
111
-------
List of Tables
Page No.
Table ES-1 Regulatory Treatment Options ES-3
Table ES-2 Water Quality Criteria By Use ES-4
Table ES-3 Empirical Calculation of Criteria from the Baseline Scenario ES-6
Table ES-4 Benefit Scenarios Modeled (97 facilities) ES-7
Table ES-5 Water Quality Index (WQI) Baseline and Proposed Treatment Level Statistics . . . ES-8
Table 2-1 Regulatory Treatment Options 2-3
Table 2-2 Water Quality Criteria Threshold By Use 2-12
Table 2-3 Empirical Calculation of Criteria from the Baseline Scenario 2-13
Table 2-4 Benefit Scenarios Modeled 2-15
Table 2-5 Fraction of Pollutant Retained as a Function of Treatment Level 2-17
Table 2-6 Default Effluent Characteristics by Treatment Level 2-20
Table 3-1 Effluent Characteristics of rban Runoff and CSOs 3-6
Table 3-2 National Summary of Annual Load Estimates for Urban and Rural Runoff and
CSOs (as metric tons/day) 3-7
Table 4-1 Benefit Scenarios Modeled (97 facilities) 4-2
Table 4-2 Water Quality Index (WQI) Baseline and Proposed Treatment Level Statistics 4-3
Table 4-3 MPP Regulatory Treatment Options 4-4
Table 4-4 Documented Environmental Effects of MPP Wastes on Water Quality 4-8
Table IX.G-1 Modeled Environmental Benefits (97 facilities) A-l
IV
-------
Environmental Assessment
of Proposed Effluent Limitations Guidelines
and Standards for the
Meat and Poultry Products
Industry Point Source
January 2002
U.S. Environmental Protection Agency
Office of Science and Technology
Engineering and Analysis Division
1200 Pennsylvania Avenue, N.W.
Washington, D.C. 20460
Charles Tamulonis
Task Manager
-------
ACKNOWLEDGMENTS AND DISCLAIMER
The Engineering and Analysis Division, of the Office of Science and Technology, has reviewed
and approved this report for publication. The Office of Science and Technology directed,
managed, and reviewed the work of Tetra Tech in preparing this report. Neither the United
States Government nor any of its employees, contractors, subcontractors (Research Triangle
Institute.), or their employees make any warranty, expressed or implied, or assumes any legal
liability or responsibility for any third party's use of or the results of such use of any information,
apparatus, product, or process discussed in this report, or represents that its use by such party
would not infringe on privately owned rights.
-------
EXECUTIVE SUMMARY
Purpose of the Water Quality Environmental Assessment (WQEA)
The purpose of the Water Quality Environmental Assessment (WQEA) is to estimate the
change in water quality conditions resulting from implementing an effluent guideline and
pretreatment standards for a given industry. This assessment performed by the U.S.
Environmental Protection Agency (EPA) as part of its effort to develop effluent limitations
guidelines and pretreatment standards for Meat and Poultry Processing Industry (MPP) facilities.
Definition of MPP
EPA defines the meat and poultry products (MPP) industry as facilities that slaughter
livestock (e.g., cattle, calves, hogs, sheep, and lambs), and/or poultry or process meat, and/or
poultry into products for further processing or sale to consumers. The industry is often divided
into three categories: (1) meat slaughtering and processing; (2) poultry slaughtering and
processing; and (3) rendering.
Water Quality Issues Related to MPP
The meat poultry processing industry (excluding rendering) uses an estimated 150 billion
gallons of water per year and ranks in the top third of all three digit SIC manufacturing sectors
with regard to overall water consumption. Water is used to clean the product, clean and sanitize
the production equipment, and to transport the waste away from the production area Water can
also be used as a part of the process, such as in scalding birds to facilitate feather removal or
chilling the animal or meat to reduce its temperature. Although a portion of the water used by
this industry is reused and or recycled, most of the water becomes wastewater that is ultimately
discharged into the nation's waterways, either directly by the facility or indirectly though a
Publically Owned Treatment Works (POTW).
Potential Environmental Impacts of MPP
The untreated wastewater of MPP facilities contains high concentrations of biodegradable
ES- 1
-------
dissolved organics, biochemical oxygen demand (BOD), total suspended solids (TSS), oil and
grease, pathogens, and nutrients such as nitrogen (including ammonia) and phosphorus. EPA's
sampling data collected from MPP facilities also found treatable concentrations of some metals
(e.g., copper and zinc). Some of these metals are fed to the animals as feed additives, and
therefore are assumed to be the source for these pollutants in the wastewater.
The discharge of high levels of biodegradable organics into receiving streams results in
increased microbial activity, as the microorganisms biodegrade these materials. Increases in
microbial activity associated with excessive nutrient loadings requires greater amounts of oxygen
than natural aeration processes can provide resulting in the decrease of available dissolved
oxygen (DO) for more complex aquatic organisms. This potential of a pollutant to remove
oxygen from receiving waters is called the biochemical oxygen demand (BOD). High
concentrations of BOD can reduce the DO content of waterbodies to levels insufficient to support
fish and invertebrates.
Habitat degradation can result from increased suspended particulate matter. Suspended
particulate matter reduces light penetration, and thus primary productivity. Accumulation of
suspended particles may also alter benthic spawning grounds and feeding habitats.
Nutrients, including phosphorus and nitrogen, are the primary causes of surface water
eutrophication, which can reduce dissolved oxygen content of waterbodies to levels insufficient
to support fish and invertebrates. Eutrophication may also increase the incidence of harmful algal
blooms that release toxins as they die and can severely affect wildlife, as well as humans.
Additionally, meat and poultry processing raw wastewaters contain significant amounts of
organic nitrogen which rapidly breaks down into ammonia. If left untreated, this poses a direct
toxicant to aquatic communities.
Oil and grease are known to produce toxic effects on aquatic organisms (e.g., fish,
Crustacea, larvae and eggs, gastropods, bivalves, invertebrates, and flora). Pathogens are known
ES-2
-------
to impact a variety of water uses including recreation, drinking water sources, and aquatic life
and fisheries (Docket No. W-01-06, Record No. 10024 - Pathogen TMDL report).
Treatment Options Modeled
EPA modeled four treatment options (see Table ES-1) for this analysis. Three of the
treatment options are for facilities which discharge directly to a water body. These facilities will
be referred to as direct dischargers. EPA designates the treatment options for existing direct
dischargers as Best Available Technology (BAT). One of the treatment options is for facilities
which discharge indirectly to a water body through a Publicly Owned Treatment Work (POTW).
These facilities will be referred to as indirect discharges. EPA designates the treatment options
for existing indirect dischargers as Pretreatment Standards for Existing Sources (PSES).
Table ES-1: Regulatory Treatment Options
Regulatory Option1 Technical Component
BAT2
BAT3
BAT4
PSES1
Dissolved Air Flotation (DAF) (advanced
Lagoon, and Disinfection (Oil and Grease
removal) + Nitrification (NH3 removal)
oil/water separation),
, BOD5, TSS, Pathogen
BAT2 + Denitrification (Nitrate removal)
BAT3 + (Phosphorus removal)
DAF, Equalization (Oil and Grease, TSS,
removal) phosphorus removal
BAT = Best Available Treatment PSES = Pretreatment Standards for Existing Sources
Facilities modeled
EPA had sufficient data to model 97 out of the 977 meat, poultry, and rendering facilities
that are in scope of the regulatory options evaluated for this proposed rule. To prepare for the
WQEA and a separate economic analysis, EPA mailed out 350 detailed surveys to generate both
environmental and economic data. EPA received 230 detailed surveys in time for data analysis of
this proposed rule making. Of the 230 detailed surveys, EPA received sufficient data to model
ES-3
-------
the environmental impacts of 97 facilities (36 direct dischargers and 61 indirect dischargers).
EPA did not evaluate 79 facilities with zero discharges or 54 facilities for which EPA had
insufficient data to conduct the water quality analysis.
Modeling Tools
EPA used the following tools for the WQEA:
National Water Pollution Control Assessment Model (NWPCAM), version 1.1
A modified Vaughn water quality ladder
EPA used NWPCAM was used to model the in-stream dissolved oxygen (DO)
concentration, as influenced by pollutant reductions of BOD, total Kjeldahl nitrogen (TKN), total
suspended solids (TSS) and fcal coliform bacteria (FCB). A detailed description of the
NWPCAM is presented in Section 2.0 Methodology. EPA used a modified Vaughn water
quality ladder to associate water quality and designated uses (Vaughn, unpublished). NWPCAM
1.1 compares the concentrations of BOD, TSS, FCB, and percent DO saturation (DOPCT) to
benchmark values associated with swimming, fishing, and boating uses (see Table ES-2).
Table ES-2: Water Quality Criteria By Use
USE Supported
Water Quality
Index (WQI)
Criteria
BOD,
TSS
D0pct
FCB
Swimming
Fishing
Boating
99
94.4
79
1.5
3
4
10
50
100
83
64
45
200
1000
2000
Note:
BOD5
TSS
D0pct
FCB
= 5 day Biochemical Oxygen Demand (mg/L)
= Total Suspended Solids (JTU)
= percent of DO Saturation
= Fecal Coliform Bacteria(MPN/l 00ml)
ES-4
-------
Swimming is associated with the most stringent water quality criteria, and boating is associated
with the least stringent water quality criteria. For BOD, TSS, and FCB, the in-stream
concentration must be below the benchmark value to attain a given use. For DOPCT, the in-stream
value must be greater than the benchmark value to meet criteria for that use. If even one
parameter does not meet its benchmark value, the stream is not considered to support that use. If
the stream reach does not attain any of the three uses, it is designated as "not supporting."
This approach is somewhat problematic since water quality improvements are considered
to not occur unless movements result in migrating from one use category to another, e.g., fishing
to swimming. The implication of this is that the baseline condition for a given stream reach must
be just below the break point between categories so an improvement will result in the water
quality conditions moving beyond the breakpoint. Furthermore, this also implies that no within
use category movements have any value associated with them..
As an alternative to the stepwise ladder approach, EPA evaluated all water quality
changes. To accomplish this a continuous Water Quality Index (WQI) was constructed. The
WQI combines information from four water quality measures rather than using only the limiting
lowest quality criterion to define use category. For this benefit valuation, NWPCAM compiled a
WQI from turbidity, BOD, fecal coliforms, and dissolved oxygen indexes based on work by
McClelland (1974). Since the baseline distribution of use categories is well understood and
generally accepted, it is desirable for the distribution based on WQI to match the existing
distribution of use categories in the baseline. EPA derived WQI values to represent the
breakpoints on the water quality ladder based on empirical observation of the WQI distribution
among use categories in the baseline data. EPA calculated the mean and standard deviation of
WQIs for the reaches in each use category in the baseline population of reaches. If reaches are
normally distributed within each use category, 84 percent of observed WQI for each category
should be less than the mean WQI plus one standard deviation (SD). The Mean + SD value
serves as the criterion for the boundary with the next higher use category. Table ES-3 shows the
calculation and the resulting criteria.
ES-5
-------
Table ES-3: Empirical Calculation of Criteria from the Baseline Scenario
Mean Standard Deviation Criterion (Mean + SD)
Use Category (WQI) (WQI) (WQI)
No Use, 0
Boatable, 1
Fishable, 2
Swimmable, 3
54.1
84.9
92.5
98.5
24.8
9.5
6.5
2.3
79.0
94.4
99.0
Source: EPA analysis of Baseline Access database, 10/2/2001
Water Quality Environmental Assessment Results
EPA modeled the combined baseline loading of 49.9 million Ib/yr for sample set of 97
MPP facilities. The baseline loadings consist of the following pollutants: bio-chemical oxygen
demand (BOD), total suspended solids (TSS), nitrogen, phosphorus, and total Kjeldahl nitrogen
(TKN). The results for the various combinations of BAT and PSES scenarios modeled are
presented in Table ES-4.
EPA estimates the preferred treatment option (Scenario 7) for this proposed rule would
reduce pollutant discharges from 36 MPP facilities by 4.8 million Ib/yr. For this 10 percent
reduction, EPA estimates that this proposed rule would improve the WQI of 949 reach miles
(6,687 miles for the national set). The average WQI for these 949 reaches increases from 74.9 to
75.9 (see Table ES-5) which is still just below the boatable criteria breakpoint of WQI = 79. The
standard deviation suggest that 67 percent of the reaches impacted are located in the WQI range
of 60-92.
ES-6
-------
Table ES - 4: Benefits Scenarios Modeled (97 facilities)1
Scenar io'
Regulatory
Options 3
Pollutant4
Load
(million
Ibs/yr)
Pollutant Step Improvement:
Reduction Overall use
(percent) (reach miles)
Contiuous 6
Improvement:
Water Quality Index
(reach miles)
Sample7 National8 Sample National
Baseline
1
2
3
4
5
6
7
8
BAT2
BATS
BAT4
BAT2 + PSES1
BATS + PSES1
BAT4 + PSES1
BAT 3 (meat,
poultry), BAT2
(Rendering)
BAT 3 (meat,
poultry), BAT2
(Rendering) +
PSES1
49.9
47.5
45.0
44.8
36.2
33.7
33.5
45.1
33.7
5
10
10
27
32
33
10
32
17
21
21
24
28
28
21
28
116
143
143
200
227
227
143
227
926
949
952
1216
1240
1244
949
1240
6,325
6,482
6,502
9,799
9,968
10,000
6,687
9,813
This table corrects several errors reported in preamble Table IX. G-l. For more information, please see Appendix A.
EPA is proposing Scenario 7 for the MPP effluent guideline rule making
BAT = Best Available Treatment (for Direct Discharges)
PSES= Pretreatment Standards for Existing Sources (for Indirect Dischargers)
Pound totals include BOD, TSS, Nitrogen, Phosphorus and TKN. Some overlap between categories may be occurring
Improvement credited when threshold conditions are met
Improvement credited for any measurable change in water quality.
Sample set represents 97 facilities (36 direct and 61 indirect).
National set represents 977 facilities (246 direct and 731 indirect).
In addition to estimating the continuous change in water quality, EPA also analyzed the
use category or step change approach. The reductions in loadings from the Scenario 7 with this
approach would result in the improved overall use of 21 reach miles (for the sample set), which
scales up to 143 reach miles (for the national set).
ES-7
-------
Table ES-5: Water Quality Index (WQI) Baseline and Proposed Treatment Level Statistics
Scenario Average Standard Mean + SD 2 Minimum Maximum3
. WQI'1 Deviation' ' .
' '
Baseline
BAT3 (meat, poultry),
BAT2 (Rendering)
74.9
75.9
16
16.3
59 - 91
60 - 92
6
6
99
99
1 Beatable criteria is 79. Reaches with WQIs less than 79, are designated as supporting no use.
2 Represent the interval by which 67% of reaches are represented
Fishable criteria is 94.4.
3 Swimmable criteria is 99.
The large differences in miles of stream reaches affected attributable to these two
approaches is intuitively consistent: the continuous approach will count all stream reaches where
decreases in pollutants occur, whereas the use category approach will only estimate those
instances where a change in water quality results in migrating from one use category to another.
Limitations of the WQEA
EPA believes that its analysis likely underestimates the potential benefits of the
regulatory options evaluated for this proposal. Specifically, the current version of the NWPCAM
model used for this environmental assessment (See Chapter 2) only models DO, BOD, Fecal
Coliform, TKN, andTSS. Accordingly, the analysis presented in today's proposal addresses only
a subset of MPP effluent contaminants. EPA intends to modify the model in support of the final
rule to include the following: (1) modeling of nutrients for an eutrophication analysis of ponds
and lakes; and (2) modeling of other pollutants for rivers and streams.
EPA did not evaluate the human health benefits associated with reduction of toxic
pollutant discharges, because MPP effluents do not contain significant levels of toxic
contaminants. Nonetheless, it is possible that MPP pollutants, especially nitrates, could have an
impact on certain human receptors, if contaminants reach drinking water supplies.
ES-8
-------
EPA also did not evaluate the effects of MPP discharges on POTWs. MPP facilities
discharge mostly conventional pollutants (BOD, TSS, oil and grease, and fecal coliform
bacteria), which POTWs are designed to treat.
ES-9
-------
ES- 10
-------
1.0 INTRODUCTION
The purpose of the Water Quality Environmental Assessment (WQEA) is to estimate the
change in water quality conditions resulting from implementing an effluent guideline and
pretreatment standards for a given industry.
This WQEA presents the results of the water quality assessment performed by the U.S.
Environmental Protection Agency (EPA) as part of its effort to develop effluent limitations
guidelines and pretreatment standards for Meat and Poultry Processing Industry (MPP) facilities.
1.1 DEFINITION OF MPP
EPA defines the meat and poultry products (MPP) industry as facilities that slaughter
livestock (e.g., cattle, calves, hogs, sheep, and lambs), and/or poultry or process meat, and/or
poultry into products for further processing or sale to consumers. The industry is often divided
into three categories: (1) meat slaughtering and processing; (2) poultry slaughtering and
processing; and (3) rendering.
1.2 WATER QUALITY ISSUES RELATED TO MPP
The meat poultry processing industry (excluding rendering) uses an estimated 150 billion
gallons of water per year and ranks in the top third of all three digit SIC manufacturing sectors
with regard to overall water consumption. Water is used to clean the product, clean and sanitize
the production equipment, and to transport the waste away from the production area Water can
also be used as a part of the process, such as in scalding birds to facilitate feather removal or
chilling the animal or meat to reduce its temperature. Although a portion of the water used by
this industry is reused and or recycled, most of the water becomes wastewater that is ultimately
discharged into the nation's waterways, either directly by the facility or indirectly though a
1 - 1
-------
Publically Owned Treatment Works (POTW).
1.3 POTENTIAL ENVIRONME NTAL IMPACT S OF MPP
The untreated wastewater of MPP facilities contains high concentrations of biodegrable
dissolved organics, biochemical oxygen demand (BOD), total suspended solids (TSS), oil and
grease, pathogens, and nutrients nitrogen (including ammonia) and phosphorus. EPA's sampling
data collected from MPP facilities also found treatable concentrations of some metals (e.g.,
copper and zinc). Some of these metals are fed to the animals as feed additives, and therefore are
assumed to be the source for these pollutants in the wastewater.
The discharge of high levels of biodegradable organics into receiving streams results in
increased microbial activity, as the microorganisms biodegrade these materials. This increase in
microbial activity requires greater amounts of oxygen than natural aeration processes can
provide. This deficit results in the decrease of available dissolved oxygen (DO) for more
complex aquatic organisms. This potential of a pollutant to remove oxygen from receiving waters
is called the biochemical oxygen demand (BOD). High concentrations of BOD can reduce the
DO content of waterbodies to levels insufficient to support fish and invertebrates.
Habitat degradation can result from increased suspended particulate matter. Suspended
particulate matter reduces light penetration, and thus primary productivity. Accumulation of
suspended particles may also alter benthic spawning grounds and feeding habitats.
Nutrients, including phosphorus and nitrogen, are the primary causes of surface water
eutrophication, which can reduce dissolved oxygen content of waterbodies to levels insufficient
to support fish and invertebrates. Eutrophication may also increase the incidence of harmful algal
blooms that release toxins as they die and can severely affect wildlife, as well as humans.
Additionally, meat and poultry processing raw wastewaters contain significant amounts of
1 -2
-------
organic nitrogen which rapidly breaks down into ammonia. If left untreated, this poses a direct
toxicant to aquatic communities.
Oil and grease are known to produce toxic effects on aquatic organisms (i.e., fish,
Crustacea, larvae and eggs, gastropods, bivalves, invertebrates, and flora). Pathogens are known
to impact a variety of water uses including recreation, drinking water sources, and aquatic life
and fisheries (Docket No. W-01-06, Record No. 10024 - Pathogen TMDL report).
1.4 ORGANIZATION OF REPORT
EPA has organized this WQEA report into five sections. Section 2 outlines the
methodology EPA used to evaluate water quality effects from direct and indirect discharging
facilities. Section 3 describes the data sources used for evaluating water quality effects, such as
facility-specific data, water use category criteria, and documented environmental impact data.
Section 4 presents a summary of the results of this analysis. Section 5 provides a complete list of
references cited. Appendices B and C provide additional detail on the specific information
addressed in the main report.
1-3
-------
1 -4
-------
2.0 METHODOLOGY
2.1 INTRODUCTION
EPA evaluated potential water quality effects of discharges of conventional pollutants
from meat and poultry processing (MPP) facilities on receiving streams in a national analysis of
direct and indirect discharges1. Specifically, EPA used the National Water Pollution Control
Assessment Model (NWPCAM version 1.1) to model the change in reach specific instream
concentrations of total suspended solids (TSS), fecal coliform bacteria (FCB), ultimate
carbonaceous biochemical oxygen demand (CBODu), and dissolved oxygen (DO) concentration.
Total Kjeldahl nitrogen (TKN) was also modeled to account for oxygen depletion through
nitrogenous biochemical oxygen demand (NBOD).
The modeled changes in these concentrations were then used to identify changes in use
categories ranging from the least desirable of no use, to boatable, to fishable, to the most
desirable of swimmable.
In the following sections, EPA presents the water quality assessment approach, the
NWPCAM model, the pollutants evaluated, and water use support determinations.
2.2 OVERVIEW OF WATER QUALITY ASSESSMENT APPROACH
The main purpose of the Water Quality Environmental Assessment (WQEA) is to
estimate changes in water quality conditions resulting from adoption of new limitations and
'Direct discharge facilities are those which discharge effluent directly into water bodies,
usually following on-site wastewater treatment. Indirect discharge facilities are those which
discharge effluent into a publicly owned treatment works (POTWs), which provides subsequent
effluent treatment prior to discharge.
2-1
-------
standards as established by the proposed rule. Developing these estimates involves a multi-step
process that begins with the analysis presented in the MPP Technical Development Document
(TDD) and ends with the MPP Economic Analysis. The first four steps, which are covered in the
TDD, are:
1. Identify the universe of MPP discharging facilities
2. Differentiate MPP direct dischargers from MPP indirect dischargers
3. Characterize the technology in place for each of the MPP facilities being
evaluated
4. Characterize effluent discharges from each of the MPP facilities being evaluated
with baseline and various regulatory options being proposed.
The next three steps, which are the focus of this WQEA, are:
5. Identify and characterize the receiving water body for each direct discharger, and
identify the associated POTW for each indirect discharger.
6. Estimate water quality conditions under current discharge conditions and under
regulatory alternatives.
7. Quantify changes in water use categories (i.e., fishable, boatable, swimmable)
The final step, covered in the Economic Analysis, is:
8. Monetize changes in environmental benefits associated with changes in water use
categories.
Even though the characterization of the MPP effluent discharges (step 4) is covered in the
MPP TDD, a quick summary of the process is presented below. The rest of Section 2 presents
EPA's methodology used to complete steps 5 through 7.
2-2
-------
2.2.1 Characterize Effluent Discharges
EPA estimated baseline and treatment option loadings on a facility-specific level. The
baseline loadings were based primarily on data provided in the 2001 MPP Detailed Survey.
Where data for specific pollutants could not be obtained from the survey or facility compliance
reports, EPA used surrogate data, so that each facility could be modeled for the full suite of
pollutants of concern addressed by NWPCAM.
EPA estimated the treatment option loadings for each facility, based upon expected
pollutant removals from implementation of the proposed effluent guideline. The evaluated
treatment options are presented in Table 2-1.
Table 2-1: Regulatory Treatment Options
Regulatory Option1 Technical Component
BAT2
BAT3
BAT4
PSES1
Dissolved Air Flotation (DAF) (advanced
Lagoon, and Disinfection (Oil and Grease
removal) + Nitrification (NH3 removal)
oil/water separation),
, BOD5, TSS, Pathogen
BAT2 + Denitrification (Nitrate removal)
BAT3 + (Phosphorus removal)
DAF, Equalization (Oil and Grease, TSS,
removal) phoras removal
BAT = Best Available Treatment (covers existing Direct Dischargers)
PSES = Pretreatment Standards for Existing Sources (covers existing Indirect Dischargers)
EPA only applied those BAT/PSES controls that would achieve pollutant concentration
levels at least equal to the facility's current treatment in place. Under this approach, a facility that
was characterized as having equivalent B AT2 technology in place would only obtain reduced
pollutant concentrations levels under more stringent technology options (i.e., BAT3 or BAT4
controls).
2-3
-------
2.2.2 Ensure MPP Survey Data is Model Ready
EPA performed several additional steps to ensure that the facility information provided
through the MPP Survey, as well as the loadings data generated by the other analyses, could be
successfully entered into the NWPCAM model. For example, data on facility specific location
information provided in the survey had to be matched with NWPCAM location data for receiving
water bodies. In cases where Survey respondents did not identify discharge location (direct
dischargers) or associated POTW ( indirect dischargers), EPA staff made follow-up calls to the
facility operators to ensure that estimated discharges were allocated to the correct water body or
POTW, respectively. The Agency made additional modifications to the facility loadings data set
to ensure proper data formatting for use in the NWPCAM model. Once EPA entered the facility
loadings into the NWPCAM model, EPA combined facility impacts with existing stream reach
conditions to estimate water quality under both baseline and regulatory options.
2.3 OVERVIEW OF NWPCAM 1.1
NWPCAM is a national-level water quality modeling system and policy analysis tool. It
incorporates a national-scale water quality model into a system designed for conducting policy
simulations and benefits assessments. The core of NWPCAM is its water quality modeling
system. The system is built on a surface water routing framework that covers virtually the entire
inland region of the continental United States. This framework catalogs where surface waters are
located and how they are interconnected, and it characterizes the dimensions and flow of water
through this network. It is through this routing framework that the hydrological, hydrodynamic,
and surface water transport components of the system are integrated into NWPCAM.
A second major component of the modeling system is the pollutant loadings data. This
component defines the location and magnitude of discharges to the nationwide surface water
network for a selected number of conventional and nutrient pollutants. These loadings are
defined for both point and nonpoint sources of water pollution.
The kinetics component of the modeling system then incorporates information from the previous
2-4
-------
components and simulates how the selected pollutants are dispersed and transformed throughout
the surface water network. The primary output of these integrated modeling components are
water quality estimates, primarily measured as in-stream pollutant concentrations, across this
network.
2.3.1 Types of water pollution problems and policies that can be analyzed with
NWPCAM
NWPCAM was originally developed and designed to conduct retrospective analyses of
Clean Water Act policies, but has been adapted for conducting prospective analyses of new or
proposed regulations. As the model has been expanded and refined, it has become suitable for
analyzing an increasingly diverse set of water pollution problems and policies.
Because of its large scale, the development of NWPCAM's water quality mode ling and
policy evaluation system has been incremental. The scope of the model has been gradually
expanded to include more pollutants, more pollutant sources (point and nonpoint), more water
bodies, and more water quality measures. For instance, the first version of this model (the
CWAEM) incorporated only two "conventional" pollutants (CBODu and TSS), and it included
urban and rural nonpoint sources, municipal point sources, and "major" industrial point sources.
A subsequent version (NWPCAM Version 1.0) added modeling capability for two additional
conventional pollutants (FCB and DO) and added Combined Sewer Overflows (CSOs) and
approximately 20,000 "minor" industrial dischargers. The entire model has been reimplemented
from its original location on the EPA IBM mainframe running under SAS to a PC-based platform
under Microsoft Access.
NWPCAM 1.1 models four conventional pollutants: DO, CBOD, TSS, and FCB. TKN is
also included to support the modeling of DO and BOD. These pollutants have been the primary
focus of federal water pollution control policies under the Clean Water Act and have the
following advantages for modeling purposes:
2-5
-------
They can be characterized by first-order kinetics.
Data is widely available to estimate point and nonpoint source loadings of these
constituents.
Existing surface water quality indices are based, at least in part, on these
parameters.
For this analysis, NWPCAM 1.1 was further modified to also model total nitrogen and
total phosphorous. However, only the four conventional pollutants were employed in use support
determinations.
2.4 POLLUTANT PARAMETERS MODELED USING NWPCAM 1.1
2.4.1 Dissolved Oxygen (DO)
Levels of DO in surface water are commonly used as an indicator of aquatic health. High
levels of oxygen are characteristic of good water quality that can support a high-quality fishery
and diverse aquatic biota. Conversely, low or depleted oxygen concentrations indicate poor water
quality and an inability to support a diverse population of aquatic biota. DO is added to water
through photosynthesis and aeration from turbulent mixing, and is removed through respiration
and sediment oxygen demand.
In NWPCAM 1.1, oxygen production from photosynthesis (P) and consumption from
respiration (R) were assumed to balance (i.e., P = R or P - R = 0). Increases in DO concentration
due to atmospheric reaeration were accounted for by water temperature, velocity, and depth of
the river channel. The additional atmospheric oxygen that can be contributed to a free-flowing
stream falling over a dam or waterfall was not represented.
2.4.2 Biochemical Oxygen Demand (BOD)
Biodegradable organic materials, such as plant, fish, or animal matter, consume DO
2-6
-------
during decomposition. The level of organics in wastewater and natural water bodies has
historically been assessed using BOD, which measures the pollutants' potential to remove oxygen
from the receiving waters. BOD is a primary determinant of DO concentrations in surface water.
Both the carbonaceous and nitrogenous components of the ultimate BOD (CBODU and
NBODU, respectively) are needed to model DO. The decomposition of organic carbon was
represented by the decay of CBODU as an oxygen equivalent measure of the amount of organic
carbon. The labile/refractory and dissolved/particulate fractions of total organic carbon were not
differentiated. Eutrophication was not considered in this model, so the contributions of algal
respiration, algal mortality, and zooplankton grazing to organic carbon concentrations were also
not represented.
Loadings of CBODU occur from both point (e.g., municipal and industrial dischargers)
and nonpoint sources (e.g., urban runoff). Since effluent loading data for these sources are
typically characterized as the 5-day BOD or CBOD (BODS and CBOD5, respectively),
conversion factors were used to obtain CBODU for input to the model. BODS data obtained from
literature was assumed to represent CBOD5 because of uncertainty related to the interpretation of
BODS measurements (Hall and Foxen, 1984). The magnitude of the conversion factors for
municipal dischargers depend on treatment level as the relative proportion of easily degraded
materials in the effluent declines as the efficiency of waste treatment improves (Leo et al., 1984;
Thomann and Mueller, 1987).
The sequential nitrogen-cycle processes of hydrolysis of organic nitrogen to ammonia,
oxidation of ammonia to nitrite, and oxidation of nitrite to nitrate (nitrification) were simplified
by combining these steps into a single NBOD representation. Because organic nitrogen in
wastewater can be hydrolyzed to ammonia and thus contribute to the eventual oxygen demand in
a receiving water, the total NBOD is determined as the oxygen equivalent of the sum of organic
nitrogen and ammonia (see Equation 1). Total Kjeldahl nitrogen (TKN) represents the sum of
2-7
-------
organic nitrogen and ammonia.
N
where:
O2/N = stoichiometric equivalent of 4.57 g oxygen per 1 g nitrogen consumed in the
stepwise nitrification process of ammonia to nitrate, and
TKN = total Kjeldahl nitrogen.
Although the use of a lumped NBOD approach to account for the oxygen consumption
component of the nitrogen cycle has known shortcomings in representing the lag time needed to
initiate nitrification (Chapra, 1997), the approach adopted is consistent with other components of
the simplified model framework.
2.4.3 Total Kjeldahl Nitrogen (TKN)
Total Kjeldahl nitrogen (TKN) is the sum of organic nitrogen and ammonia. It is the key
pollutant in modeling DO. Sources of TKN include municipal and industrial discharges,
combined sewer overflows, and urban and rural runoff. It is routinely measured in water and
wastewater monitoring programs. Under aerobic conditions, nitrification occurs as described in
Section 2.1.2 and results in DO consumption. Under anaerobic conditions, the reverse process
(denitrification) occurs. During denitrification, nitrate is reduced to nitrite, nilrate is converted to
free nitrogen, and the free nitrogen is either assimilated by nitrogen-fixing, blue-green algae, or
released to the atmosphere as a gas.
In the absence of a national database to characterize benthic regeneration rates for
ammonia, a stoichiometric weight ratio for oxygen to nitrogen of 15.1:1 (Redfield, Ketchum, and
Richards, 1963) was used to define the equivalent amount of ammonia nitrogen released by
decomposition of organic carbon in the sediment bed. The benthic release of ammonia to the
2-8
-------
water column was estimated from the reach-dependent parameter values assigned for sediment
oxygen demand (Di Toro, 1986; Di Toro et al., 1990).
2.4.4 Total Suspended Solids (TSS)
Total suspended solids (TSS) are used as a surrogate indicator of water transparency to
characterize recreational service flows provided by a water body. Low TSS concentrations are
associated with a high degree of water clarity. High concentrations of TSS are generally
associated with murky or turbid waters and are therefore important contributors to perceptions of
poor water quality. The assessment of economic benefits is, in part, dependent on changes in
water transparency (as assessed by TSS) and corresponding improvements that result from
implementing controls to reduce TSS loadings.
InNWPCAM 1.1, no distinction is made between the relative fractions of cohesive (clays
and silts) and noncohesive (sands) particle sizes that contribute to deposition processes from the
water column or the sediment bed concentration of solids that contributes to the resuspension of
solids back into the water column. A simple net settling velocity was used to parameterize the
interactions of particle size distributions with deposition and resuspension.
2.4.5 Fecal Coliform Bacteria (FCB)
In accordance with the practices of the EPA and other public health officials, the
NWPCAM 1.1 model uses FCB as a surrogate indicator for waterborne pathogens that are known
to cause a variety of human illnesses. Low densities of FCB are characteristic of good water
quality and low risk of waterborne diseases. High concentrations of FCB indicate poor water
quality and a high risk of waterborne diseases. Using typical water quality standards for primary
contact recreation (swimming) and secondary contact recreation (boating), the concentration of
FCB is directly related to service flows and economic benefits. The assessment of economic
benefits, in part, depends on changes in FCB concentrations and improvements in service flows
that may result from implementing controls to reduce FCB loadings.
2-9
-------
FCB are introduced into natural waters by municipal and industrial wastewater
discharges, combined sewer overflows, and urban and rural runoff. Animal feedlots in rural areas
also contribute high loading rates of bacteria. High loading rates are most commonly associated
with untreated or poorly treated human sewage or animal waste. Bacteria are lost from the water
column by mortality, adsorption to particles, and settling. The mortality of coliform bacteria can
be functionally related to salt content, water temperature, and incident solar radiation (Mancini,
1978). In shallow waters, bacteria can be reintroduced back into the water column by
resuspension of particles under high flow conditions. In NWPCAM 1.1, the components of the
mortality and net settling loss rate for FCB were parameterized by a lumped
temperature-dependent net loss rate.
2.4.6 Nutrients (Total Nitrogen and Total Phosphorous)
Total nitrogen (TN) and total phosphorous (TP) are present in wastewater, surface runoff,
rainwater, ground water, and surface waters. They exist inorganic and inorganic forms and in
both dissolved and particulate fractions.
Elevated nutrient concentrations can affect a number of different water quality processes
and endpoints. Perhaps the most direct impact of nutrient loading is the toxicity of ammonia and
nitrate to aquatic and human populations. Ammonia, particularly the un-ionized form (NH3), is
highly toxic to aquatic organisms. Nitrates are considered a potential health concern for humans,
particularly for infants.
Excessive enrichment with phosphorous and/or nitrogen is also associated with the
process of cultural eutrophication, the anthropogenically induced acceleration of natural aging in
aquatic systems. Symptoms include shifts in ecological processes (e.g., carbon, nitrogen,
phosphorus, and oxygen cycling rates and dynamics) and plant and animal species. In the
extreme state of "hypereutrophy," a system may suffer extensive DO depletion, wide diurnal
shifts in oxygen corresponding with photosynthesis and respiration cycles, extreme bloom
events, noxious and undesirable algal species, fish kills, foul odors, and turbidity.
2- 10
-------
Total nitrogen and total phosphorous were modeled using first order kinetics. Decay
coefficients were obtained from the SPAtially Referenced Regressions On Watershed
(SPARROW) study (Smith, Schwarz, and Alexander, 1997).
As mentioned above, nutrient concentrations were not considered in use support
determinations. However, the development of regional nutrient criteria makes this apossibility
for the future.
2.5 WATER QUALITY MODELING
NWPCAM 1.1 has the capability to model water quality in a stream reach after inclusion
of all source loadings. A change of loadings from one source is realistically considered in
comparison with the total loadings to a stream reach. NWPCAM 1.1 contains information on
approximately 8,000 municipal facilities and 23,000 industrial facilities. It can be run on any
scale, ranging from a basin to the entire United States.
Municipal and industrial select tables contain all loading information. Each discharger is
associated with identification information (name and NPDES number), receiving water (as
identified by CU, segment number, and distance along the stream reach), loading data (flow rate
and concentrations), and a sequence number to identify the order in which stream reaches are
modeled. The municipal and industrial select tables are generated each time the study area is
selected. After the model is run, each stream reach is associated with steady-state flow rate and
concentration information.
2.6 WATER USE SUPPORT DETERMINATIONS
In order to quantify the economic benefits associated with improved water quality, a
2- 11
-------
modified Vaughn water quality ladder is used to associate water quality and designated uses
(Vaughn, unpublished). NWPCAM 1.1 compares the concentrations of BODS, TSS, FCB, and
percent DO saturation (DOPCT) to benchmark values associated with swimming, fishing, and
boating uses (see Table 2-2). Swimming is associated with the most stringent water quality
criteria, and boating is associated with the least stringent water quality criteria. For BODS, TSS,
and FCB, the in-stream concentration must be below the benchmark value to attain a given use.
For DOPCT, the in-stream value must be greater than the benchmark value to meet the criterion for
that use. If even one parameter does not meet its benchmark value, the stream is not considered
to support that use. If the stream reach does not attain any of the three uses, it is designated as
"not supporting."
Table 2-2: Water Quality Criteria Threshold By Use
USE Supported Water Quality BOD5
TSS
DO
pet
FCB
. '-.. Index (WQI) ' .. . .
. . Criteria . . .. . ; .'' : '
. . . ,
Swimming
Fishing
Boating
99
94.4
79
1.5
3
4
10
50
100
83
64
45
200
1000
2000
Note: BOD5 = 5 day Biochemical Oxygen Demand (mg/L)
TSS = Total Suspended Solids (mg/L)
DOpot = percent of DO Saturation
FCB = Fecal Coliform Bacteria(MPN/l 00ml)
This approach is somewhat problematic since water quality improvements are considered
to not occur unless movements result in migrating from one use category to another, e.g., fishing
to swimming. The implication of this is that the baseline condition for a given stream reach must
be just below the break point between categories so an improvement will result in the water
quality conditions moving beyond the breakpoint. Furthermore, this also implies that no within
use category movements have any value associated with them..
2- 12
-------
As an alternative to the stepwise ladder approach, EPA evaluated all water quality
changes. To accomplish this a continuous Water Quality Index (WQI) was constructed. The
WQI combines information from four water quality measures rather than using only the limiting
lowest quality criterion to define use category. For this benefit valuation, NWPCAM compiled a
WQI from turbidity, BOD, fecal coliforms, and dissolved oxygen indexes based on work by
McClelland (1974). Since the baseline distribution of use categories is well understood and
generally accepted, it is desirable for the distribution based on WQI to match the existing
distribution of use categories in the baseline. EPA derived WQI values to represent the
breakpoints on the water quality ladder based on empirical observation of the WQI distribution
among use categories in the baseline data. EPA calculated the mean and standard deviation of
WQIs for the reaches in each use category in the baseline population of reaches. If reaches are
normally distributed within each use category, 84 percent of observed WQI for each category
should be less than the mean WQI plus one standard deviation (SD). The Mean + SD value
serves as the criterion for the boundary with the next higher use category. Table 2-3 shows the
calculation and the resulting criteria.
Table 2-3: Empirical Calculation of Criteria from the Baseline Scenario
Mean Standard Deviation Criterion (Mean + SD)
Use Category (WQI) (WQI) (WQI)
No Use, 0
Boatable, 1
Fishable, 2
Swimmable, 3
54.1
84.9
92.5
98.5
24.8
9.5
6.5
2.3
79.0
94.4
99.0
Source: EPA analysis of Baseline Access database, 10/2/2001
2- 13
-------
2.7 FACILITY EFFLUENT DATA INPUTS FOR NWPCAM
Effluent data extracted from the MPP Detailed Surveys were entered into NWPCAM
model for the 97 meat-processing facilities evaluated for the benefit analysis. As described
below, some adjustments were required, because not all facilities collected data for all parameters
evaluated in the environmental assessment.
Each facility s effluent was characterized by flow rate and the six water quality
parameters discussed in section 2.0 (BODS, TSS, FCB, TN, TKN, and TP). The current effluent
quality at each facility was defined at the "baseline average concentration" (BAC). Direct
discharge facilities were also associated with a maximum of three alternative effluent qualities
that would result upon implementation of a Best Available Technology (BAT) control. Indirect
discharge facilities were associated with one alternative effluent quality that would result upon
implementation of the Pretreatment Standard for Existing Sources (PSES).
The facility effluent data were modified prior to use in NWPCAM. The type of discharger
(i.e., direct or indirect) was changed for four industrial facilities based on the NWPCAM model.
Of the 97 total facilities, 36 were direct dischargers and 61 were indirect dischargers. When
facilities lacked data for one or more control options, the effluent quality was assumed to be
identical to the baseline average concentration. The original data contained some instances of
TKN concentrations that were larger than corresponding TN concentrations. In these instances,
TN was set equal to TKN. The modified data was reformatted and inserted into NWPCAM as
two tables (TTMunSelect and TTIndSelect).
2.8 MODEL RUNS
EPA performed nine model runs to estimate baseline conditions and water quality
changes for various combinations of regulatory controls. They correspond to the following
2- 14
-------
scenarios shown in Table 2-4.
BAT options were applied to direct dischargers and PSES options were applied to
indirect dischargers. It should be emphasized that differences between baseline loadings and
technology treatment options were calculated prior to input into NWPCAM. As described in
detail in the MPP Technical Development Document, facility loadings under alternative
technology options were derived based on technology performance of model facilities for each
MPP industry subcategory. The NWPCAM model used these estimates to model water quality
changes in affected receiving water bodies on a facility-by-facility basis.
Table 2-4: Benefits Scenarios Modeled
Model Regulatory Options 1
Run
1
2
3
4
5
6
7
8
9
Scenario
Scenario
Scenario
Scenario
Scenario
Scenario
Scenario
Scenario
Scenario
0:
1:
2:
3:
4:
5:
6:
7:
8:
Baseline
BAT2
BAT3
BAT4
BAT2 + PSES1
BAT3 + PSES1
BAT4+PSES1
BAT3 (meat, poultry), BAT2 (Rendering)
BAT3 (meat, poultry), BAT2 (Rendering) + PSES1
BAT: Best Available Treatment (for Direct Discharges)
BAT2: Dissolved Air Flotation (DAF) (advanced oil/water separation), Lagoon, and Disinfection (Oil and Grease,
BOD5, TSS, Pathogen removal) + Nitrification (NFL, removal)
BATS: BAT2 + Denitrification (Nitrate removal)
BAT4: BATS + Phosphorus removal
PSES Pretreatment Standards for Existing Sources (for Indirect Dischargers)
PSES1: Dissolved Air Flotation (DAF) , Equalization (Oil and Grease, TSS removal)
2-15
-------
2.9 CREATING MUNICIPAL AND INDUSTRIAL SELECT TABLES
To perform the nine model runs, one municipal select and nine industrial select tables
were needed. The original NWPCAM model was run over the entire United States to generate
one municipal and one industrial select table containing information on the facilities originally
contained in NWPCAM. Nine copies were made of the industrial select table to correspond with
baseline and Model Runs 2-9. Records for 151 facilities (36 direct industrial dischargers, 61
indirect industrial dischargers, and 59 municipalities) were inserted or updated using the facility
specific data generated from the MPP Survey and other compliance reports. The specific
approach to update the loadings data was dependent on the facility type (i.e., direct industrial
discharger, indirect industrial discharger, municipal discharger). However, in each case a module
was used to automatically update the appropriate table. Appendix A contains the code used in the
modules.
2.10 DIRECT INDUSTRIAL DISCHARGERS
Data for the 36 direct discharge facilities were inserted in the industrial select tables
without any modification.
2.11 INDIRECT INDUSTRIAL DISCHARGERS
The original version of NWPCAM did not include records for indirect dischargers,
because their loadings were captured through the corresponding municipality. For this analysis,
flow rates from the meat-processing facilities and municipalities were separated. This approach
permitted adjustment of the loadings from the meat processing facilities without affecting the
municipalities. New records were inserted into the industrial select tables for each indirect
discharger. Pollutant concentration data were then multiplied by a factor to account for the
2- 16
-------
treatment received prior to discharge (see Table 2-5). The fractions estimate the proportion of
pollutant retained based on level of municipal treatment. The module linked the indirect
discharger to its municipality through the NPDES number. The treatment level of the
municipality was used to determine the appropriate multiplication factors for updating the
industrial select tables.
Table 2-5: Fraction of Pollutant Retained as a Function of Treatment Level
Treatment Type Level Fraction Retained
' ' '. BODS .'..TSS;. . FCB TKN . TN TP
Primary
Advanced Primary
Secondary
Advanced Treatment I
Advanced Treatment II
Default
2
3
4
5
6
9
0.70
0.50
0.08
0.03
0.02
0.08
0.50
0.30
0.08
0.03
0.02
0.08
0.65
0.65
0.005
0.005
0.0000032
0.005
0.78
0.78
0.55
0.43
0.12
0.55
0.78
0.78
0.61
0.61
0.48
0.61
0.87
0.87
0.42
0.06
0.06
0.42
Notes: BOD5 = Five-day biochemical oxygen demand
TSS = Total suspended solids
FCB = Fecal coliform bacteria
TKN = Total Kjeldahl nitrogen
TN = Total nitrogen
TP = Total phosphorous
2.12 POTWs
Mass and flow balances were developed to calculate new effluent information for the
municipal facilities (see Equations 2 and 3). Appendix B contains full details on how the
equations were developed.
2-17
-------
xi
meat
mun,new
_
Ks
1 \c c _0 c f
\_f^mun,old mun,old 'foment meat J r
meatJ retained
(2)
(3)
where
Qmun,new
Qmun,old
Qmeat
= updated municipal flow rate (MOD)
= original municipal flow rate (MOD)
= flow rate from the meat-processing facility (MOD)
Cmun,new = updated municipal concentration (mg/L)
Cmun,old = original municipal concentration (mg/L)
Cmeat = concentration in the meat-processing facility's effluent (mg/L)
fretained = fraction of pollutant retained after treatment.
Two municipalities received flow from multiple meat-processing facilities. For this
situation, equations were developed to calculate total flow and average concentrations to use for
Qmeat and Cmeat in Equations 2 and 3 (see Equations 4 and 5).
,1 "*" &meat, 1
(4)
C
meat
meat, 1* meat A
X~,
meat, TX~, meat ,2
Qmeat A + Q:
(5)
meat ,1
where
Qmeat
Qmeat,!
= total flow rate from all meat-processing facilities (MOD)
= flow rate from meat-processing facility 1 (MOD)
2- 18
-------
Qmeat,2 = flow rate from meat-processing facility 2 (MOD)
Cmeat = average concentration in effluent from all meat-processing facilities
(mg/L)
Cmeat,! = concentration in effluent from meat-processing facility 1 (mg/L)
Cmeat,2 = concentration in effluent from meat-processing facility 2 (mg/L).
There were nine meat-processing facilities that had a flow equal to or larger than their
corresponding municipalities. For these treatment plants, the flow rate was divided in half and
the original concentration values were retained.
Analysis using these equations revealed that there were 15 wastewater treatment plants
that had negative concentrations for one or more parameters. This occurred when the meat
facilities comprised a large fraction of the total municipal flow and/or when the meat facility
effluent concentration was much larger than the municipal concentration. Negative
concentrations were replaced by default concentration values based on treatment level (see Table
2-6).
2- 19
-------
Table 2-6: Default Effluent Characteristics by Treatment Level
Treatment Type Level Effluent Characteristics
= . BODS . TSS FCB '. TKN ' TN ''TP
Primary
Advanced Primary
Secondary
Advanced Treatment I
Advanced Treatment II
Default
2
3
4
5
6
9
143.5
102.5
16.4
6.2
4.1
16.4
107.5
64.5
17.2
6.5
4.3
17.2
2.06E+06
2.06E+06
1.58E+03
1.58E+03
l.OOE+01
1.58E+03
23.4
23.4
16.5
12.9
3.6
16.5
23.4
23.4
18.3
18.4
14.4
18.3
5.2
5.2
2.5
0.4
0.4
2.5
Notes: BOD5 = Five-day biochemical oxygen demand (mg/L)
TSS = Total suspended solids (mg/L)
FCB = Fecal coliform bacteria (MPN/100 mL)
TKN = Total Kjeldahl nitrogen (mg/L)
TN = Total nitrogen (mg/L)
TP = Total phosphorous (mg/L)
2-20
-------
3.0 DATA SOURCES
EPA uses readily available Agency and other databases, models, and reports to evaluate
water quality effects. For the Meat and Poultry Processing (MPP) Environmental Assessment,
EPA used two basic sets of data. The first data set was used to develop baseline conditions
(current use levels) for stream reaches affected by MPP discharges. The second set of data were
used to develop estimates of individual facility pollutant loadings. These data sets were then
entered into the National Water Pollution Control Assessment Model (NWPCAM) to quantify
impacts of the MPP dischargers under current and regulatory treatment levels. The following
sections describe the specific types of data used to run the NWPCAM model and the primary
sources for those data.
3.1 POINT SOURCE LOADS USED IN NWPCAM TO ESTIMATE BASELINE
WATER QUALITY CONDITIONS
Point sources represented in NWPCAM 1.1 include municipal and industrial wastewater
treatment plants and combined sewer overflows. Pollutant discharges from municipal and
industrial outfall pipes are represented in the model by estimates of annual mean loading rates
input at a discrete location along the length of a stream or river. Pollutant discharges from urban
runoff and combined sewer overflows, accounted for by an urban network of multiple discrete
outfall pipes discharging to one or more waterways, are aggregated and distributed uniformly to
RF1 reaches within the urban land use portions of a watershed. Pollutant loads for point sources
are estimated for each of the following state variables selected for NWPCAM 1.1:
5-day biochemical oxygen demand (BODS)
Total Kjeldahl nitrogen (TKN)
Dissolved oxygen (DO)
Total suspended solids (TSS)
3-1
-------
Fecal coliform bacteria (FCB).
3.1.1 Municipal and Industrial Dischargers
3.1.1.1 Primary Data Sources.
The primary data sources used to estimate the magnitude and location of municipal and
industrial point source loads are the following EPA national databases:
Permit Compliance System (PCS)
Clean Water Needs Survey (CWNS)
Industrial Facilities Database (IFD).
The PCS database, used by EPA to track compliance by a discharger with NPDES permit
limits, provides monthly or quarterly summaries of monitored effluent flow and concentration
data submitted to EPA as Discharge Monitoring Reports (DMRs) by "major" municipal and
industrial facilities. Standard Industrial Classification (SIC) codes are used to identify the type of
discharger (e.g., municipal, pulp and paper, allied chemicals). Data are generally not available in
PCS for numerous small facilities classified by EPA as "minor" based on criteria that include
effluent flow (<1 MOD), population served (<10,000), or a qualitative judgment of minimal
"water quality impact."
The CWNS provides an inventory of the existing and projected status of both major and
minor municipal wastewater treatment plants. The database contains records of population
served, effluent flow rates, influent and effluent concentrations, and loads of conventional
pollutants. The CWNS also includes a coded description to identify the category of each
treatment plant by the level of existing and projected wastewater treatment. The levels of
treatment performed by plants represented in the CWNS include the following treatment
technologies that are summarized briefly below:
Raw (no treatment): Wastewater is collected and discharged to surface waters
3-2
-------
without any removal of pollutants.
Primary: Screens and physical settling of wastewater results in separation and
removal of heavy solids. Pollutants associated with large particles are removed.
Advanced Primary: Enhanced settling and physical removal of pollutants are
achieved with low to high doses of chemical coagulants such as metal salts or
organic polyelectrolytes.
Secondary: Removal of heavy solids by physical settling is followed by biological
processes designed to enhance bacterial growth to decompose organic materials.
Biological treatment processes used are designed to enhance the growth of
suspended or attached bacteria in (a) activated sludge and waste stabilization
ponds and (b) trickling filters.
Advanced Secondary: Physical settling and conventional biological treatment are
enhanced with either chemical coagulation or additional biological processes to
increase the removal efficiency of solids, BOD, and nutrients.
Tertiary or Advanced Treatment: Physical settling and conventional biological
treatment are enhanced for very high removal efficiency with high dosage
chemical coagulation, biological processes for nitrification and denitrification,
filtration, and adsorption with granular activated carbon or reverse osmosis.
No Discharge (to surface waters).
Technical details about these levels of municipal treatment can be obtained from standard
environmental engineering texts (e.g., Metcalf and Eddy, 1991).
The IFD provides comprehensive records on effluent discharges from the nation's major
and minor industrial facilities. A significant shortcoming of the IFD, however, is that EPA no
longer maintains this database. Therefore, these data are no longer completely up to date. The
RF1 database was used to link the locations of point source inputs with specific river-mile points
on an RF1 reach for input to the model.
3-3
-------
3.1.1.2 Typical Pollutant Concentrations.
For many major municipal facilities, reliable estimates of effluent flow, BODS, and TSS
concentrations were available from PCS and CWNS. Considerably fewer data were available to
characterize municipal effluent concentration levels of TKN and FCB. For estimates of DO
loads, effluent data were typically not reported by wastewater treatment facilities. Literature data
were used to assign effluent DO levels assuming 50 percent saturation (at 25 degrees C).
Thousands of industrial facilities are included in EPA inventories of the nation's
industrial wastewater dischargers. In both PCS and IFD, municipal and industrial facilities are
identified by their NPDES identification number and a Standard Industry Category (SIC) code.
For example, municipal sewage treatment facilities are assigned the SIC code of 4952. In general,
the availability of data to characterize effluent flow and pollutant loading rates for industrial
dischargers was more limited than for municipal facilities. Most of the largest industrial "major"
sources are, however, included.
For municipal and industrial point sources (major and minor) in which actual discharge
data were available from either PCS, IFD, or CWNS, those data were used to assign a loading
rate for input to the model. For municipal point sources for which effluent data were not
available, default effluent flow, loads, and concentrations, compiled from PCS, CWNS, and
other sources (e.g., Metcalf and Eddy, 1991; EPA, 1995; NRC, 1993), were used to estimate
typical pollutant loading rates for input to the model. For industrial point sources for which
effluent flow and pollutant loading data were not available, typical pollutant loads (TPLs) and
typical pollutant concentrations (TPCs), compiled as look-up tables for groups of four-digit level
SIC codes were obtained from the National Oceanic and Atmospheric Administration (NOAA,
1994) to develop NWPCAM 1.1.
3.1.1.3 Inventory of Point Source Facilities.
There were 8,878 reach-indexed municipal facilities and 23,118 reach-indexed industrial
facilities (direct discharge) included in NWPCAM version 1.1.
3-4
-------
3.1.2 Urban Runoff and Combined Sewer Overflows
3.1.2.1 Primary Data Sources.
The public works infrastructure in every town and city includes an urban stormwater
drainage system designed to collect and convey runoff from rainstorms and snow melt.
Stormwater runoff can contribute significant intermittent loading of pollutants with adverse
impacts on water quality and aquatic resources. EPA's National Urban Runoff Project (NURP)
concluded that wet weather events contribute significant loadings of pathogens, heavy metals,
toxic chemicals, and sediments (EPA, 1983). Over the past several years, EPA has worked
closely with state and local governments to design and implement effective programs to reduce
pollutant loading from urban runoff. Under the 1987 Amendments to the CWA, EPA published
regulations for general permits for stormwater discharges from urban areas (Phase 1, > 100,000
population; Phase 2, <100,000 population) and industrial sites. Reduction of pollutant loads to
surface waters is typically accomplished using best management practices (BMPs) designed to
remove debris accumulation on paved surfaces and to attenuate the rate of urban stormwater flow
(Novotny and Olem, 1994).
As a vestige of public works practices in vogue from the nineteenth century (ca.
1850-1900), many older cities, primarily in the Northeast, Midwest, and Upper Midwest, have
urban drainage systems that were designed, for cost-saving reasons, to convey both stormwater
runoff and raw sewage. These combined sewer overflow (CSO) systems were intentionally
designed to overflow and discharge the mixture of raw sewage and stormwater into the nearest
urban waterway, when runoff from heavy rainstorms exceeded the hydraulic capacity of the
combined sewer pipe network. Although pollutant loading from CSOs occurring only during
heavy rainstorms is intermittent, high loading rates of pathogens often result in closure of
recreational beaches and shellfish beds to protect public health (Brosnan and Heckler, 1996).
Discharges from CSOs also can result in high loading rates of organic materials and
accumulations of noxious sludge beds near CSO outfalls with locally depressed levels of
dissolved oxygen. EPA 1997) estimates that about 880 older cities, including Washington, DC,
for example, still have combined sewer systems that periodically discharge a mixture of raw
3-5
-------
sewage and stormwater runoff into urban waterways. Several cities have also initiated costly
construction projects to eliminate combined sewer systems by separating urban stormwater
drainage from raw sewage collection systems. In Minneapolis-St. Paul, MN, for example, an
aggressive $320 million (1996 dollars) construction program implemented over a 10-year period
from 1985-1995 eliminated the old combined sewer system and greatly improved compliance
with water quality standards for FCB levels in the Upper Mississippi River (MCES, 1996).
3.1.2.2 Typical Pollutant Concentrations
Based on data archived in EPA's NURP database (EPA, 1983) and data compiled by
Novotny and Olem (1994), a range of characteristic effluent concentrations is presented in Table
3-1 for urban runoff and for CSOs. The data in Table 3-1 illustrate the relative magnitude of the
range of characteristic effluent levels for urban runoff and CSOs. The urban runoff loading rates
used in NWPCAM 1.1 are based on data obtained from Lovejoy (1989) and Lovejoy and
Dunkelberg (1990).
Table 3-1. Effluent Characteristics of Urban Runoff and CSOs
Parameter
Urban Runoff
CSO (Event Mean)
BODS (mg/L)
CBODU:CBOD5
TSS (mg/L)
TKN (mg/L)
NH3-N (mg-N/L)
NO2-N + NO3-N (mg-N/L)
Total N (mg-N/L)
Total P (mg-P/L)
Total lead (mg/L)
Total coliforms (MPN/100 mL)
10-13
3.0
141-224
1.68-2.12
ND
0.76-0.96
3-10
0.37-0.47
161-204
103-108
60-200(115)
1.4
100-1100(370)
ND (6.5)
ND(1.9)
ND(l.O)
3-24 (7.5)
1-11
ND (370)
105-107 (ND)
Note: ND = no data'
MPN = most probable number.
3-6
-------
3.1.2.3 Primary Data Sources for Urban Runoff Estimates
Annual urban runoff pollutant loading data have been compiled on a county-level basis
by Lovejoy (1989) and Lovejoy and Dunkelberg (1990). Urban runoff loads were first
transformed from county-level loads to catalog unit loads using the areal proportion of a county
in a given catalog unit. Urban and rural runoff loads were then allocated to RF1 stream reaches
based on the length of the reach and whether or not a populated place (1990 Census) was
allocated with the reach. Estimates of effluent loads derived from CSO inputs are based on an
analysis performed to support EPA's 1992 Clean Water Needs Survey (Tetra Tech, 1993) with
the inventory of CSO facilities reduced from 1300 to 880 by EPA (1997). Effluent loads from
CSOs are based on a pulse load driven by storm runoff volume and the pollutant load associated
with a 5-year, 6-hour duration design storm event. Using the design storm parameter values,
runoff volume was estimated from the CSO system drainage system, population served, and
degree of imperviousness. Table 3-2 presents a nationally aggregated summary of the loading
estimates used in NWPCAM 1.1 to represent pollutant loads contributed by urban runoff and
CSOs.
Table 3-2. National Summary of Annual Load Estimates for Urban and Rural Runoff
and CSOs (as metric tons/day)
Parameter Urban Runoff Rural Runoff CSOs
BOD5
TSS
1,701
3,081
19,974
778,638
2,823
10,361
3.2 NONPOINT SOURCE LOADS
Nonpoint source loads, characterized as intermittent diffuse inputs distributed over an
entire drainage basin, are related to hydrologic conditions, topography, physiography, and land
3-7
-------
uses of a watershed. InNWPCAM 1.1, the county land-use data used by Lovejoy(1989) and
Lovejoy and Dunkelberg (1990) to estimate pollutant loads over a drainage basin were classified
very simply as either urban or rural. In NWPCAM 1.1, urban and rural runoff are the only
nonpoint sources of pollutant loads included in the model framework. The very broad category of
rural land uses accounts for essentially all other land uses not classified as urban (e.g., forest,
agricultural pasture, and crops). The data obtained from Lovejoy's work (1989) do not allow a
breakdown of rural nonpoint source loads into more detailed classifications of either forest or the
several subclassifications of agricultural land uses (e.g., grassland, pasture, feedlots, cropland).
To assign the catalog unit-based rural nonpoint source loads as an input load for each RF1
reach, the loads were attenuated using drainage area-dependent sediment delivery ratios (SDR)
assigned to each catalog unit (Vanoni, 1975). Since the data used to quantify rural nonpoint
source loads are so highly aggregated, evaluations of policy scenarios for BMP controls of
nonpoint sources are not possible in NWPCAM 1.1. Nonpoint source loads from rural land uses
are included in the model framework to account for the contribution and impact of nonpoint
source loads on water quality. The NPS data provided by Lovejoy and Dunkelberg is based on
work done by Giannessi at Resources For the Future. The urban loadings are estimated using a
simplified procedure that takes estimates of the number of urban residents per county and
multiplies that number by coefficients to get total loadings of urban pollutants to the water. The
"Lovejoy rural loadings is a much more involved process that includes three modules. The first
module estimates sheet and rill erosion, first estimating the total tons of erosion, then applying
soil texture and stream density factors, which provides a net amount deposited to surface waters
by county. Then, the elemental composition of the surface soil and non-sheet and rill sources are
added in to get a total pounds of pollutants (BODS, TSS, TKN, TP, Cu, Pb, Fe, Zn) reaching the
surface waters. The second module accounts for livestock runoff by estimating the total manure
generated by county, then applying USDA estimates of manure "losses" by state from
volatilization, runoff, and seepage. The total quantity "lost" to surface waters is then partitioned
into physical/chemical characteristics by assuming 12 percent of the total manure is total solids
(TS), BODS is 23 percent of TS, COD is 95 percent of TS, TKN is 4.9 percent of TS, and TP is
3-8
-------
1.6 percent of TS. This calculation produces total annual estimates of these pollutants reaching
surface waters by county. The third module is a nutrient runoff module using the Cornell Nutrient
Simulation Model; outputs from this module are not used in NWPCAM 1.1.
3.3 FACILITY-SPECIFIC LOADING DATA
EPA used various sources for collecting data on MPP facilities. The Agency obtained
data through EPA site visits and sampling, and facility responses to 2001 Meat Products Industry
Survey (herein referred to as the "Detailed Survey"). Information from the Detailed Survey
provided many of the facility-specific parameters required for this analysis, such as annual
discharge volume, current pollutant loadings, and discharge location information (i.e., name of
receiving water body). EPA's data collection procedure is described in detail in Chapter 3 of the
technical development document.
For the MPP facilities which responded to the Detailed Survey, EPA identified discharge
location based primarily on NPDES information provided in the Survey. For indirect dischargers,
EPA also used NPDES information provided by the respondent. Where such information was not
available, EPA contacted the facility or performed additional analysis using either the EPA's
Permit Compliance System (PCS) or the Industrial Facilities Discharge (IFD) database to identify
the appropriate POTW.
EPA also extracted facility-specific pollutant loading information from the Detailed
Surveys. Facilities respondents provided final discharge information for a suite of pollutants. As
noted above and described in Chapter 2 of this document, the NWPCAM model assessed four
conventional pollutants: DO, BOD, TSS, and FCB. In addition, loadings for TKN were also
included to support the modeling of DO and BOD.
3-9
-------
3- 10
-------
4.0 RESULTS
This section presents EPA's estimate of the water quality effects of Meat and Poultry
Processing (MPP) discharges under baseline conditions and following the adoption of the
proposed limits and standards. In addition, analytical results are presented for regulatory options
that were evaluated by EPA, but not included in today's proposal.
EPA used the National Water Pollution Control Assessment Model (NWPCAM) to
estimated the potential benefits of controlling discharges of bio-chemical oxygen demand
(BODS), total suspended solids (TSS), total Kjeldahl nitrogen (TKN) and fecal coliform bacteria
(FCB) from MPP facilities. A total of 97 MPP facilities were modeled for this analysis, including
36 direct and 61 indirect dischargers. EPA estimates that 246 direct and 731 indirect discharges
are within scope of the regulatory options evaluated for this proposed rule.
The first subsection (4.1) presents a summary of the overall results, modeled treatment
options, modeled facilities, environmental scale-up factor and limitations of the Water Quality
Environmental Assessment (WQEA). The second subsection, 4.2., presents documented impacts.
4.1 WQEA RESULTS SUMMARY
EPA modeled a sample set of 97 MPP facilities with a combined baseline loading of 49.9
million Ib/yr (see Table 4-1). The baseline loadings consist of the following pollutants: BOD,
TSS, nitrogen, phosphorus and TKN.
EPA estimates the preferred treatment option (Scenario 7) for this proposed rule would
reduce pollutant discharges from 36 MPP facilities by 4.8 million Ib/yr. For this 10 percent
reduction, EPA estimates that this proposed rule would improve the WQI of 949 reach miles
(6,687 miles for the national set). The average WQI for these 949 reaches increases from 74.9 to
4- 1
-------
75.9 (see Table 4-1) which is still just below the beatable criteria breakpoint of WQI = 79. The
standard deviation suggest that 67 percent of the reaches impacted are located in the WQI range
of 60-92.
Table 4-1: Benefits Scenarios Modeled (97 facilities)1
Scenar io'
Regulatory
Options 3
Pollutant4
Load
(million
Ibs/yr)
Pollutant Step Improvement:
Reduction Overall use
(percent)
(reach miles)
Contiuous 6
Improvement:
Water Quality Index
(reach miles)
Sample7 National8 Sample National
Baseline
1
2
3
4
5
6
7
8
BAT2
BATS
BAT4
BAT2 + PSES1
BATS + PSES1
BAT4 + PSES1
BAT 3 (meat,
poultry), BAT2
(Rendering)
BAT 3 (meat,
poultry), BAT2
(Rendering) +
PSES1
49.9
47.5
45.0
44.8
36.2
33.7
33.5
45.1
33.7
5
10
10
27
32
33
10
32
17
21
21
24
28
28
21
28
116
143
143
200
227
227
143
227
926
949
952
1216
1240
1244
949
1240
6,325
6,482
6,502
9,799
9,968
10,000
6,687
9,813
This table corrects several errors reported in preamble Table IX. G-l. For more information, please see Appendix A.
EPA is proposing Scenario 7 for the MPP effluent guideline rule making
BAT = Best Available Treatment (for Direct Discharges)
PSES= Pretreatment Standards for Existing Sources (for Indirect Dischargers)
Pound totals include BOD, TSS, Nitrogen, Phosphorus and TKN. Some overlap between categories may be occurring
Improvement credited when threshold conditions are met
Improvement credited for any measurable change in water quality.
Sample set represents 97 facilities (36 direct and 61 indirect).
National set represents 977 facilities (246 direct and 731 indirect).
In addition to estimating the continuous change in water quality, EPA also analyzed the
4-2
-------
use category or step change approach. The reductions in loadings from the Scenario 7 with this
approach would result in the improved overall use of 21 reach miles (for the sample set), which
scales up to 143 reach miles (for the national set).
The large differences in miles of stream reaches affected attributable to these two
approaches is intuitively consistent: the continuous approach will count all stream reaches where
decreases in pollutants occur, whereas the use category approach will only estimate those
instances where a change in water quality results in migrating from one use category to another.
The continual approach is considered to be the preferred method of estimating water quality
impacts. The Economic Assessment presents the monetized benefits for this proposed rule,
which are based on the continuous approach.
Table 4-2: Water Quality Index (WQI) Baseline and Proposed Treatment Level Statistics
Scenario . Average Standard Mean + SD MJn. Max.3
WQI1 Deviation Range2
''
Baseline
BAT3 (meat, poultry),
BAT2 (Rendering)
74.9
75.9
16
16.3
59 - 91
60 - 92
6
6
99
99
1 Beatable criteria is 79. Reaches with WQIs less than 79, are designated as supporting no use.
Represent the interval by which 67% of reaches are represented
Fishable criteria is 94.4.
3 Swimmable criteria is 99.
4.1.1 Treatment Options Modeled
EPA modeled four treatment options for analysis (see Table 4-3). Three of the treatment
options are for facilities which discharge directly to a water body (i.e., direct dischargers). EPA
designates the treatment options for direct dischargers as best available technology (BAT). One
of the treatment options is for facilities which discharge indirectly to a water body (i.e., indirect
dischargers), through a publicly owned treatment work (POTW). EPA designates the treatment
4-3
-------
options for existing indirect dischargers as pretreatment standards for existing sources (PSES).
The combination of BAT and PSES scenarios modeled is presented in Table 4-1.
Table 4-3: MPP Regulatory Treatment Options
Regulatory Option1 Technical Component
BAT2
BAT3
BAT4
PSES1
Dissolved Air Flotation (DAF) (advanced oil/water separation),
Lagoon, and Disinfection (Oil and Grease, BOD5, TSS, Pathogen
removal) + Nitrification (NH3 removal)
BAT2 + Denitrification (Nitrate removal)
BAT3 + (Phosphorus removal)
DAF, Equalization (Oil and Grease, TSS, removal)
BAT = Best Available Treatment (covers existing Direct Dischargers)
PSES = Pretreatment Standards for Existing Sources (covers existing Indirect Dischargers)
4.1.2 Facilities Modeled
EPA had sufficient data to model 97 out of the 977 meat, poultry, and rendering facilities
which are in scope of the regulatory options evaluated in this proposed rule. To prepare for the
Water Quality Environmental Assessment (WQEA) and a separate economic analysis, EPA
mailed out 350 detailed surveys to generate both environmental and economic data. EPA
received 241 detailed surveys in time for data analysis of this proposed rule making. Of the 241
detailed surveys, EPA received sufficient data to model the environmental impacts of 97
facilities (36 direct dischargers and 61 indirect dischargers). EPA did not evaluate 79 facilities
with zero discharges or 65 facilities for which EPA had insufficient data to conduct the water
quality analysis.
4.1.3 Simplified Environmental Scale-up Factor
EPA developed environmental scale-up factors for both the direct and indirect facilities.
4-4
-------
The environmental scale-up factors are ratios between the number of facilities in scope and
modeled. These scale-up factors allow EPA to approximate what the environmental impact of the
proposed rule might be on the national level. These weighting factor were only used for
estimating water quality impacts. EPA presents the separate methodology used for scaling of the
monetized benefits in the Economic Analysis.
EPA estimates that 246 direct discharger facilities are in scope of the evaluated BAT
options. Since EPA modeled 36 direct dischargers, the ratio of in scope directs (246) to modeled
directs (36), is 6.83, or
246 (in scope direct dischargers)
Scaling Factor direct dischargers =
36 (modeled direct dischargers)
6.83
EPA estimates that 731 indirect discharger facilities are in scope of the evaluated PSES1
option. Since EPA modeled 61 indirect dischargers, the ratio of in scope indirects (731) to
modeled indirects (61) is 11.98, or
731 (in scope indirect dischargers)
Scaling Factor indirect dischargers =
61 (modeled indirect dischargers)
11.98
4.1.4 Limitations of the WQEA
EPA believes that its analysis likely underestimates the potential benefits of the
regulatory options evaluated for this proposal. Specifically, the current version of the NWPCAM
4-5
-------
model used for this environmental assessment only models DO, BOD, fecal coliform bacteria,
TKN and TSS. (See Chapter 2.) Accordingly, the analysis presented in today's proposal addresses
only a subset of MPP effluent contaminants. EPA intends to modify the model in support of the
final rule to include the following: (1) modeling of nutrients for an eutrophication analysis of
ponds and lakes; and 2) modeling of other pollutants for rivers and streams.
EPA did not evaluate the human health benefits associated with reduction of toxic
pollutant discharges, because MPP effluents do not contain significant levels of toxic
contaminants. Nonetheless, it is possible that MPP pollutants, especially nitrates could have an
impact on certain human receptors, if contaminants reach drinking water supplies.
EPA also did not evaluate the effects of MPP discharges on POTWs. MPP facilities discharge
mostly conventional pollutants (BODS, TSS, oil and grease, and fecal coliform bacteria), which
POTWs are designed to treat.
4.2 DOCUMENTED ENVIRONMENTAL IMPACTS AND PERMIT VIOLATIONS
In addition to modeling environmental effects of MPP facilities using the NWPCAM
model, EPA performed a literature search to document cases where meat and poultry processing
facilities have been identified as sources of water quality impairment. The results of this
literature search are published in the Administrative Record as part of the public docket.
While the literature search was not comprehensive and was limited mostly to newspaper
articles and government press releases covering the last five years, EPA found 20 cases in which
plant operators were cited for for a variety of permit violations. One meat processing facility was
cited for more than 5,000 permit violations, which led to degradation of water quality in the
affected river. In fact, this facility received the highest fine ever issued under the Clean Water
Act. Other documented impacts cited in the articles included ten stream reaches with nutrient
loadings, two sites with contaminated well water, one site with contaminated ground water, and
4-6
-------
one lake threatened by nutrient loadings. In all cases, the identified source of contamination or
perceived threat is an MPP facility. In cases in which permit levels were violated or alleged to be
violated, NH3-N, PO4 , fecal coliform bacteria, and TSS were the most common contaminants of
concern.
Eighteen of the articles document legal action in criminal cases taken against meat and
poultry processing facility owners or operators . Documented legal action includes: (1)
conspiracy of five facilities to violate the CWA; (2) one case of illegal dumping of waste; and (3)
five cases of falsifying records, diluting waste samples, and/or destroying records. These legal
actions resulted in possible cases of incarceration and fines ranging from $0.25 million to $12.6
million. Table 4-4 summarizes the environmental impacts identified and type of legal action
pursued.
4-7
-------
Table 4-4. Documented Environmental Effects of MPP Wastes on Water Quality
Case #1
Case #2
Case #3
Case #4
Case #5
Case #6
Case #7
Case #8
Identified Impacts
High concentrations of fecal coliform, an indicator of the presence of animal intestinalwaste found in receiving waters.
Also excessive discharges of phosphorus, ammonia, cyanide, oil, and grease. Plant was fined $12.6 million , the
largest Clean Water Act fine ever (1 997).
Operators of five poultry processing facilities were indicted for actions leading to more than 5,000 permit violations
during a 20-year period from 1975-1995.. Indictment (01/2000) alleged oneof the plants pined pollutants in the form
of ammonia nitorgen, fecal colifcrm, oil and grease, suspended solids, and other rotting materials directly into
receiving waters.
Poultry processing plant agreed to pay $500,000 (1998) for permit violations. Parameters on the discharge of
phosphorus were also established for the first time for this facility.
Meat processing facility operators agreed to pay fine of $250,000 for permit violations. Permit violations included
falsification of discharge monitoring reports, exceedances of effluent limitations, and inadequate record-keeping
practices (1998)
Turkey processor agreed to make improvements is wastewater treatment system and pay $300,000 fine for permit
violations. Violations included exceeding limitations fro phosphorus and ammonia (1997). High levels of these
pollutants were found downstream from plant. Biologists also found a dearth of aquatic insects.
Rendering facility officials agreed to pay $600,000 in fines for polluting river with dead animal parts and Jalsifying
sewer discharge records (2000).
Chicken processing plant was fined $10,800 for permit violations. Wastewater exceeded limits on fecal colifcrm and
also exceeded volume limits. During 1998, a fish kill caused by oxygen depleted water was tied to facility's treatment
plant.
Two poultry plants were fined more than $46,000 for 206 water quality violations that took place during 1998 and
1 999. Waste with high bacteria levels was running off sprayed fields.
4-8
-------
Table 4-4. Documented Environmental Effe
Case #9
Case #10
Case #11
Case#12
Case#13
Case#14
Case#15
Case#16
Case#17
Case #18
Case #19
cts of MPP Wastes on Water Quality (continued)
Identified Impacts
A poultry plant was fined $6 million for allowing excessive runoff from its farms and processingplants.
Pork Processing plant cited 20 times since 1994 for permit violations. Tests of receiving water body indicated high
levels of several pollutants including ammonia and fecal bacteria.
High levels of phosphorous were detected downstream from poultry processing plant. In addition, state alleged that
high levels of ammonia and high temperatures resulted from plant's discharges.
State Conservation Commission study indicated that waste from poultry processing plans threatened viability of lake
due to discharges of phosphorous and nitrogen.
Water Quality data collected by EPA indicated marked increase in phosphorous in many areas downstream from
chicken plants.
State Department of Natural Resources obtained a court order to compel poultry processor to adhere to State Water
Quality Laws. The plant willreduce its discharge by about 50 percentunder the court order.
State e nviron mental o fficial filed su it again st pou Itry pro cessor for will fully co ntamin ating gr oundw ater in the vici nity
of fields where the plant had sprayed with wastewater. Wastewater was laden with nitrates (1998)
Owner of meat slaughter house indicted for allegedly dumping blood and other animal waste products into nearby
water bodies (2000)
State issued an order containing a $25,000 fine for violating permit limits for ammonia, solids, and other pollutants.
Operator of rendering plant sentenced for one month in prison for illegally discharging pollutants int river (1998).
Ammonia and other pollutants were discharged and monitoring reports falsfied.
Meat further processing firm was fined $28,000 for railing to file proper forms for discharge of oil, grease, TSS, and
BOD (1998). Consent agreement also required company to install pollution equipment.
4-9
-------
4-10
-------
5.0 REFERENCES
Brosnan, T.M., andP.C. Heckler. 1996. "The Benefits ofCSO Control: New York City
Implements Nine Minimum Controls in the Harbor." Water Environment &
Techechnology 8(8): 75-79.
Carson, Richard T. and Robert Cameron Mitchell. 1993. The Value of Qean Water: The Public's
Willingness to Pay for Boatable, Fishable, and Swimmable Quality Water. Water Resources
Research, 29(7 July):2445-2454.
Di Toro, D.M. 1986. "A Diagenetic Oxygen Equivalents Model of Sediment Oxygen Demand."
In Hatcher, K. J. (ed.). Sediment Oxygen Demand, Processes, Modeling and
Measurement. Institute of Natural Resources, University of Georgia, Athens, GA. pp.
171-208.
Leo, W.M, R.V. Thomann, and T.W. Gallagher. 1984. Before and After Case Studies:
Comparisons of Water Quality Following Municipal Treatment Plant Improvements.
EPA 430/9-007. Washington, DC: U.S. Environmental Protection Agency, Office of
Water, Program Operations.
Lovejoy, S.B. 1989. Changes in cropland loadings to surface waters: Interim report No. 1 for
the development of the SCS National Water Quality Model. Purdue University, West
Lafayette, Indiana.
Lovejoy, S.B., and B. Dunkelberg. 1990. Water quality and agricultural policies in the 1990s:
Interim report No. 3 for development of the SCS National Water Quality Model. Purdue
University, West Lafayette, Indiana.
McClelland, Nina I. 1974. Water Quality Index Application in the Kansas River Basin. Prepared for U.
S. EPA-RegionVII.
National Oceanic and Atmospheric Administration (NOAA). 1994. Gulf of Maine Point Source
Inventory, A Summary by Watershed for 1991. National Coastal Pollutant Discharge
Inventory. Pollution Sources Characterization Branch, Strategic Environmental
Assessments Division, National Oceanic Atmospheric Administration, Silver Spring,
MD, December.
Novotny, V. and H. Olem. 1994. Water Quality Prevention, Identification and Management of
Diffuse Pollution. New York: Van Nostrand Reinhold.
NRC. 1993. Managing Wastewater in Coastal Urban Areas. Committee on Wastewater
Management for Coastal Urban Areas, Water Science and Technology Board,
5-1
-------
Commission on Engineering and Technical Systems, National Research Council,
National Academy Press, Washington, DC.
Redfield, A.C., B.H. Ketchum, and F.A. Richards. 1963. "The Influence of Organisms on the
Composition of Seawater." In The Sea, Vol.2, M.N. Hill (ed.). pp. 26-77. New York:
Wiley-Interscience.
U.S. EPA, 1983. Technical Guidance Manual for Performing Wasteload Allocations. Book
Two: Streams and Rivers. Chapter 2: Nutrient/Eutrophication Impacts. Office of Water
Regulations and Standards, Monitoring and Data Support Division.
U.S. EPA (Environmental Protection Agency). 1995. Technical Guidance Manual for
Developing Total Maximum Daily Loads, Book II: Streams and Rivers, Part 1:
Biochemical Oxygen Demand/Dissolved Oxygen and Nutrients/Eutrophication. EPA 823-
B-97-002. Office of Water, Washington, DC. September.
U.S. EPA. 2001. Environmental and Economic Benefit Analysis of Proposed Revisions to the National
Pollutant Discharge Elimination System Regulation and the Effluent Guidelines for Concentrated
Animal Feeding Operations, Chapter 4, Modeling of Improvements in Surface Water Quality and
Benefits of Achieving Recreational Use levels. Washington: EPA/Office of Water, EPA-821-R-
01-002. January, 2001.
Vaughan, William J. 1986. The RFF Water Quality Ladder, Appendix B in Robert Cameron Mitchell
and Richard T. Carson, The Use of Contingent Valuation Data for Benefit/Cost Analysis in
Water Pollution Control, Final Report. Washington:Resources for the Future.
5-2
-------
APPENDIX A: PREAMBLE CORRECTION
Two corrections have been made since the signing of the MPP preamble. Corrections are
noted as follows: Black line strikeouts (shown as: black line strikouts) represent original text that
has been removed. Redline strikeouts (shown as: redHriedjext) represent newly added text.
The first correction is a typo found in the "Sample" column of Table K.G-1 (page 155).
The value of 21, should actually be 28.
Table IX.G-1: Modeled Environmental Benefits (97 facilities)
n * *IT j Pollutant
o n i * r\ * Pollutant Load , ,.
Scenario Regulatory Options , .. , , Reduction
* J F (million Ibs/yr) , A.
v J ' (percent)
Overall use
improvement2
(reach miles)
Sample National
Baseline
1
2
3
4
5
6
7
8
BAT2
BATS
BAT4
BAT2 + PSES1
BAT3+PSES1
BAT4 + PSES1
BATS (meat, poultry),
BAT2 (Rendering)
BATS (meat, poultry),
BAT2 (Rendering) +
PSES1
49.9
47.5
45.0
44.8
36.2
33.7
33.5
45.1
33.7
5%
10%
10%
27%
32%
33%
10%
32%
17
21
21
24
28
2±28
21
28
29 U6.
36 143
36 143.
4* 200
4§ 227
36 227
36 143.
4§ 227
Note 1: Baseline = 49.9 Million Ibs/yr. Pound totals include BOD, TSS, Nitrogen, Phosphorus and TKN
from 97 facilities. Some overlap between categories may be occurring
Note 2: Sample set represents 97 facilities {3^djrecXand-61Jiidirect). National set represents 246 direct
an^7^Hndirect_discharger.facilities. Of the 246 facilities represented, 79 facilities arc zero
dischar
ciiicl tiicrcrorc do not coiTtriDixtc to tiicsc modeled "Welter ciu.3-iit
improvements.
A- 1
-------
The second correction has to do with the scale-up of the overall use improvement to the
national level. EPA originally used a scale-up factor of 1.72 which incorrectly assumed that the
246 facilities covered by this rule, consisted of both direct, indirect and land applying (or zero
discharger) facilities. The calculation was done as follows:
Scaling Factor = 246 (Facilities in scope) - 79 (zero dischargers)
97 (Modeled Facilites)
1.72
The 246 facilities are actually the direct dischargers in scope of this rule. Therefore a
scale-up factor for the direct dischargers based on a simple ratio of the total number of directs
(246) to the number of directs modeled (36) is 6.83, or
246 (in scope directdischargers)
Scaling Factor directdischargers -
36 (modeled directdischargers)
6.83
An example calculation of scaling BAT3 overall use improvement to the national level is
as follows:
Use Improvement BAT3 natlonal = BAT3 sample x Scaling Factor directdischargers
21 mi. x 6.83
143 mi
EPA estimates that 731 indirect facilities are in-scope of the PSES1 option. Therefore,
A-2
-------
the scale-up factor for indirect dischargers based on a simple ratio of the total number of
indirects (731) to the number indirects modeled (61) is 11.98, or
Scaling Factor mdirect dischar_
731 (in SCOpe indirect dischargers)
gers
61 (modeled mdirectdischargers)
11.98
An example calculation of scaling PSES1 overall use improvement to the national level is
as follows:
PSES1 Use Improvement sample
(BAT3+PSESl)sample-BAT3sample
28 mi - 21 mi
7 mi
PSES1 Use Improvement national
PSES1 sample x Scaling Factor mdirect dischargers
7 mi x 11.98
84 mi
An example calculation of the scale-up of BAT3 + PSES1 overall use improvement to the
national level is as follows:
(BAT3 + PSESl)natIonal
BAT3 national + PSES1 national
143 mi + 84 mi
227 mi
A-3
-------
As a result of this correction to the scaling methodology, EPA updated preamble Table
IX.G-1 (see table above). EPA also corrects the following two sentences found in the preamble:
(page 150): " EPA estimates the national improvement in overall use to be 29 Ilj6 to 49 227
reach miles.
(page 154): "The recommended treatment option would result in the over-all use improvement
of 21 river miles at the sample set, and approximately 36^i43,miles at the national
level."
A-4
-------
Appendix B: Equations used to update municipal facility loadings
Variable Definition
Qtmmnew= updated municipal flow rate (MGD)
Qtmrnoid= original municipal flow rate (MGD)
Qmeat = flow rate from the meat-processing facility (MGD)
Q0 = flow rate to municipality from other (non-meat) sources (MGD)
Cmimnew= updated municipal concentration (mg/L)
Cmimold= original municipal concentration (mg/L)
Cmeat= concentration in the meat -processing facility's effluent (mg/L)
C0= concentration in the flow from other (non-meat) sources (mg/L)
f = fraction of pollutant retained after treatment
Flow Balance
Therefore
Vmun,new ~ Vmun,old ~ Vmeat
Mass Balance
Mass in - Mass out - Mass depleted = 0 (Steady-state)
(Q me at C me at + Q o^o ) ~~ Qmun .old^num ,old ~ 0 ~ f ) (Qmeat ^rne at
(Q me at C me at + Q.o^oft "~ Qmun, old Cmun, old =^
,"i P _ Mmun,old^'mun,old _
xo^o 7 "~ x meat ^ meat
ymun,old^-'mun,old _
^ x meat^meat
Q
,-. Lxmun.old^'mun.old
MO
-------
B-2
-------
Appendix C: Modules
Module 1: Update direct industrial dischargers
SubUpdateTTIndQ
'Create 9/14/01 by Megan Tulloch
'Last modified 9/20/01 by Megan Tulloch
'Modified 12/4/01 by A. Miles
'Tables
Dim dbs As Database
Dim ttindselect As Recordset
Set dbs = CurrentDbQ
Set ttindselect = dbs.OpenRecordset("TTDirect")
'Variables
Dim v_bod As Variant
Dim v_tss As Variant
Dim v_tn As Variant
Dim v_tp As Variant
Dim v_fec As Variant
Dim v_tkn As Variant
Dim v_npdes As Variant
Dim v_flow As Variant
'SQL query statement variables
Dim UpdqryStr As String
Dim SelqryStr As String
'Open TT Industrial Data
SelqryStr = "select * from TTDirect where (option = 'BAT4' Or option = 'PSESI');"
Set ttindselect = dbs.OpenRecordset(SelqryStr)
DoCmd.SetWarnings False
ttindselect.MoveFirst
Do Until ttindselectEOF
'Set variables to TT industrial data values
v_bod = ttindselectlBOD
v_tss = ttindselect! TSS
v_tn = ttindselect !TN
v_tp = ttindselect !TP
v_fec = ttindselectlFEC
v_tkn = ttindselect! TKN
v_npdes = ttindselectlNPDES
vjflow = ttindselectlFlow If TT flow rates are in gpd, need to add conversion factor!
'Update NWPCAM industrial select table withTT values by corresponding NPDES
UpdqryStr = "UPDATE indselect SET "& _
"flow = " & vjflow & ", bod = " & v_bod & ", tss= " & v_tss & ", tn= " & v_tn & ", tp= " & v_tp & ", fec=
" & v_fec & " , tkn= " & v_tkn & " " & _
"WHERE npdes = '" & v_npdes & "';"
DoCmd.RunSQL (UpdqryStr)
tt indselect.MoveNext
Loop
ttindselect.Close
DoCmd.SetWarnings True
End Sub
Module 2: Insert Indirect Industrial Facilities
C-l
-------
Sub InsertTTMuntoIndQ
'Create 9/14/01 by Megan Tulloch
'Last modified 9/20/01 by Megan Tulloch
'Modified 1/8/02 by A Miles
'Tables
Dim dbs As Database
Dim ttmunselect As Recordset
Dim modmunselect As Recordset
Set dbs = CurrentDbQ
'Variables
Dim i As Long
Dim v_npdes As Variant
Dim v_type As Variant
Dim v_bod As Variant
Dim v_tss As Variant
Dim v_tn As Variant
Dim v_tp As Variant
Dim v_fec As Variant
Dim v_tkn As Variant
Dim v_ttflow
Dim v primary BOD As Variant
Dim v_primary_TSS As Variant
Dim v_primary_TN A s Variant
Dim v_primary_TP A s Variant
Dim v_primary_FEC As Variant
Dim v_primary_TKN As Variant
Dim v_advprimary_BOD As Variant
Dim v_advprimary_TSS As Variant
Dim v_advprimary_TN As Variant
Dim v_advprimary_TP As Variant
Dim v_advprimary_FEC A s Variant
Dim v_advprimary_TKN As Variant
Dim v_secondary_BOD As Variant
Dim v_secondary_TSS As Variant
Dim v_secondary_TN As Variant
Dim v_secondary_TP As Variant
Dim v_secondary_FEC As Variant
Dim v_secondary_TKN As Variant
Dim v_advwtl_BOD As Variant
Dim v_advwtl_TS S As Variant
Dim v_advwtl_TN As Variant
Dim v_advwtl_TP As Variant
Dim v_advwtl_FEC As Variant
Dim v_advwtl_TKN As Variant
Dim v_advwt2_BOD As Variant
Dim v_advwt2_TS S As Variant
Dim v_advwt2_TN As Variant
Dim v_advwt2_TP As Variant
Dim v_advwt2_FEC As Variant
Dim v advwt2 TKN As Variant
C-2
-------
Dim v_default_BOD As Variant
Dim v_default_TSS As Variant
Dim v_default_TN As V ariant
Dim v_default_TP As Variant
Dim v_default_FEC As Variant
Dim v_default_TKN As Variant
Dim v_seqno As Variant
Dim v_mi As Variant
Dim v_do As Variant
Dim v_cbodtoubod As Variant
Dim v_psfbod As Variant
Dim v_psftss As Variant
Dim v_cu As Variant
Dim v_seg As Variant
Dim v_name As Variant
'SQL Query Statement Variables
Dim TTSelqryStr As String
Dim SelqryStr As String
Dim UpdqryStr As String
Dim InsqryStr As String
v primary BOD = 0.7
v_primary_TSS = 0.5
v_primary_TN = 0.78
v_primary_TP = 0.87
v_primary_FEC = 0.65
v_primary_TKN = 0.78
v_advp rimary_B OD =0.5
v_advprimary_TSS = 0.3
v_advprimary_TN = 0.78
v_advprimary_TP = 0.87
v_advprimary_FEC = 0.65
v_advprimary_TKN = 0.78
v_secondary_BOD = 0.08
v_secondary_TSS = 0.08
v_secondary_TN = 0.61
v_secondary_TP = 0.42
v_secondary_FEC = 0.0005
v_secondary_TKN = 0.55
v_advwtl_BOD = 0.03
v_advwtl_TSS = 0.03
v_advwtl_TN = 0.61
v_advwtl_TP = 0.06
v_advwtl_FEC = 0.0005
v_advwtl_TKN = 0.43
v_advwt2_BOD = 0.02
v_advwt2_TSS = 0.02
v_advwt2_TN = 0.48
v_advwt2_TP = 0.06
v_advwt2_FEC = 0.0000032
v_advwt2_TKN = 0.12
v_default_BOD = 0.08
v default TSS = 0.08
C-3
-------
v_default_TN = 0.61
v_default_TP = 0.42
v_default_FEC = 0.0005
v_default_TKN = 0.55
'Open TT Municipal Data
TTSelqryStr = " select * from TTIndirect where option = 'BAG';1'
Set ttmunselect = dbs.OpenRecordset(TTSelqryStr)
DoCmd.SetWarnings False
i = 0
ttmunselect.MoveF irst
Do Until ttmunselect.EOF
i = i+ 1
'Select Row in NWPCAM Model Data corresponding TT data by NPDES
SelqryStr = "select * from munselect where npdes = '" & ttmunselect!NPDES & '";"
Set modmunselect = dbs.OpenRecordset(SelqryStr)
'Set variable from TT data to be moved into NWPCAM Industrial Table
v_npdes = ttmunselectlNPDES
v_type= "INDIRECT"
'Set Flow variables to be used in calculating loads
v_ttflow = ttmunselectlFlow 'If TT flows are in gpd, need to add conversion factor.
If modmunselectlLEVEL = 2 Then
'Calculate loads for both TT and NWPCAM municipal data
v_bod = ttmunselectlBOD * v primary BOD
v_tss = ttmunselect!TSS * v_primary_TSS
v_tn = ttmunselectlTN * v_primary_TN
v_tp = ttmunselect !TP * v_primary_TP
v_fec = ttmunselect!FEC * v_primary_FEC
v_tkn = ttmunselect!TKN * v_primary_TKN
Elself modmunselect!LEVEL = 3 Then
'Calculate loads for both TT and NWPCAM municipal data
v_bod= ttmunselect!BOD * v_advprimary_BOD
v_tss = ttmunselect!TSS * v_advprimary_TSS
v_tn = ttmunselect!TN * v_advprimary_TN
v_tp = ttmunselect!TP * v_advprimary_TP
v_fec = ttmunselect!FEC * v_advprimary_FEC
v_tkn = ttmunselect!TKN * v_advprimary_TKN
Elself modmunselect! LEVEL = 4 Then
'Calculate loads for both TT and NWPCAM municipal data
v_bod= ttmunselect!BOD * v_secondary_BOD
v_tss = ttmunselect!TSS * v_secondary_TSS
v_tn = ttmunselect!TN * v_secondary_TN
v_tp = ttmunselect!TP * v_secondary_TP
v_fec = ttmunselect!FEC * v_secondary_FEC
v_tkn = ttmunselect! TKN * v_secondary_TKN
Elself modmunselect! LEVEL = 5 Then
'Calculate loads for both TT and NWPCAM municipal data
v_bod= ttmunselect!BOD * v_advwtl_BOD
v_tss = ttmunselect!TSS * v_advwtl_TSS
v_tn = ttmunselect!TN * v_advwtl_TN
v_tp = ttmunselect !TP * v_advwtl_TP
v_fec = ttmunselect!FEC * v_advwtl_FEC
v tkn = ttmunselect!TKN * v advwtl TKN
C-4
-------
Elself modmunselect!LEVEL = 6 Then
'Calculate loads for both TT and NWPCAM municipal data
v_bod= ttmunselectlBOD * v_advwt2_BOD
v_tss = ttmunselectlTSS * v_advwt2_TSS
v_tn = ttmunselectlTN * v_advwt2_TN
v_tp = ttmunselectlTP * v_advwt2_TP
v_fec = ttmunselectlFEC * v_advwt2_FEC
v_tkn = ttmunselectlTKN * v_advwt2_TKN
Elself modmunselect! LEVEL = 9 Then
'Calculate concentrations for both TT and NWPCAM municipal data
v_bod = ttmunselectlBOD * v default BOD
v_tss = ttmunselectlTSS * v_default_TSS
v_tn = ttmunselectlTN * v_default_TN
v_tp = ttmunselectlTP * v_default_TP
v_fec = ttmunselectlFEC * v_default_FEC
v_tkn = ttmunselectlTKN * v_default_TKN
End If
'Insert into the NWPCAM industrial select table new values
InsqryStr = "INSERT INTO indselect" & _
"(flow,bod,tss,tn,tp,fec,tkn,npdes,type)" & _
"VALUES (" & v_ttffow & "," & v_bod & ", " & v_tss & ", " & v_tn & "," & v_tp & ", " & v_fec & ", " &
v_tkn &",'"& v_npdes & "', '" & _
v_type & '");"
DoCmd.RunSQL (InsqryStr)
'Set variables to be moved from NWPCAM Municipal Select table driectly into Industrial Select Table
v_seqno = modmunselect! seqno
v_mi = modmunselect! MI
v_do = modmunselect! DO
v_cbodtoubod = modmunselectlCBODTOUBOD
v_psfbod= modmunselectlPSFBOD
v_psftss = modmunselectlPSFTSS
v_cu = modmunselect ICU
v_seg= modmunselectlSEG
v_name = modmunselect! NAME
'Update the new row with the constant data to copied from the NWPCAM municipal select table
UpdqryStr= "UPDATE indselect SET "& _
"name = '" & v_name & '", seqno = " & v_seqno & ", mi= " & v_mi & ", do= " & v_do & ", cbodtoubod=
" & v_cbodtoubod & ", psfbod= " & v_psfbod & ", psftss= " & v_psftss & ", cu= " & v_cu & ", seg= " &
v_seg & " " & _
"WHERE npdes = '" & v_npdes & "';"
DoCmd.RunSQL (UpdqryStr)
ttmunselect.MoveNext
Loop
ttmunselect.Close
MsgBox i & " were updated"
DoCmd.SetWarnings False
End Sub
C-5
-------
C-6
-------
Module 3: Update municipal facilities
Sub UpdateMunQ
'Create 11/12/01 by Megan Tulloch
'Last modified 11/13/01 by Megan Tulloch
'Tables
Dim dbs As Database
Dim ttmunselect As Recordset
Dim modmunselect As Recordset
Set dbs = CurrentDbQ
'Variables
Dim i As Long
Dim v_npdes As Variant
Dim v_ttflow As Variant
Dim v_modflow As Variant
Dim v_bod_new As Variant
Dim v_tss_new As Variant
Dim v_tn_new As Variant
Dim v_tp_new As Variant
Dim v_fec_new As Variant
Dim v_flow_new As Variant
Dim v_tkn_new As Variant
Dim v primary BOD As Variant
Dim v_primary_TSS As Variant
Dim v_primary_TN A s Variant
Dim v_primary_TP A s Variant
Dim v_primary_FEC As Variant
Dim v_primary_TKN As Variant
Dim v_advprimary_BO D As Variant
Dim v_advprimary_TSS As Variant
Dim v_advprimary_TN As Variant
Dim v_advprimary_TP As Variant
Dim v_advprimary_FEC As Variant
Dim v_advprimary_TKN As Variant
Dim v_secondary_BOD As Variant
Dim v_secondary_TSS As Variant
Dim v_secondary_TN As Variant
Dim v_secondary_TP As Variant
Dim v_secondary_FEC As Variant
Dim v_secondary_TKN As Variant
Dim v_advwtl_BOD As Variant
Dim v_advwtl_TSS As Variant
Dim v_advwtl_TN As Variant
Dim v_advwtl_TP As Variant
Dim v_advwtl_FEC As Variant
Dim v_advwtl_TKN As Variant
Dim v_advwt2_BOD As Variant
Dim v_advwt2_TS S As Variant
Dim v_advwt2_TN As Variant
Dim v_advwt2_TP As Variant
Dim v_advwt2_FEC As Variant
Dim v advwt2 TKN As Variant
C-7
-------
Dim v_default_BOD As Variant
Dim v_default_TSS As Variant
Dim v_default_TN As V ariant
Dim v_default_TP As Variant
Dim v_default_FEC As Variant
Dim v_default_TKN As Variant
'SQL Query Statement Variables
Dim TTSelqryStr As String
Dim SelqryStr As String
Dim UpdqryStr As String
v_primary_BOD = 0.7
v_primary_TSS = 0.5
v_primary_TN = 0.78
v_primary_TP = 0.87
v_primary_FEC = 0.65
v_primary_TKN = 0.78
v_advp rimary_B OD =0.5
v_advprimary_TSS = 0.3
v_advprimary_TN = 0.78
v_advprimary_TP = 0.87
v_advprimary_FEC = 0.65
v_advprimary_TKN = 0.78
v_secondary_BOD = 0.08
v_secondary_TSS = 0.08
v_secondary_TN = 0.61
v_secondary_TP = 0.42
v_secondary_FEC = 0.0005
v_secondary_TKN = 0.55
v_advwtl_BOD = 0.03
v_advwtl_TSS = 0.03
v_advwtl_TN = 0.61
v_advwtl_TP = 0.06
v_advwtl_FEC = 0.0005
v_advwtl_TKN = 0.43
v_advwt2_BOD = 0.02
v_advwt2_TSS = 0.02
v_advwt2_TN = 0.48
v_advwt2_TP = 0.06
v_advwt2_FEC = 0.0000032
v_advwt2_TKN = 0.12
v default BOD = 0.08
v_default_TSS = 0.08
v_default_TN = 0.61
v_default_TP = 0.42
v_default_FEC = 0.0005
v_default_TKN = 0.55
'Open TT Municipal Data
TTS elqryStr = " select * from T TIndire ct where op tion = 'BAG'
Set ttmunselect = dbs.OpenRecordset(TTSelqryStr)
DoCmd.SetWarnings False
i = 0
ttmunselect.MoveF irst
C-8
-------
Do Until ttmunselectEOF
i = i + 1
'Select Row in NWPCAM Model Data corresponding TT data by NPDES
SelqryStr = "select * from munselect where npdes = '" & ttmunselectlNPDES & '";''
Set modmunselect = dbs.OpenRecordset(SelqryStr)
'Set variable from TT data to be moved into NWPCAM Industrial Table
v_npdes = ttmunselectlNPDES
'Set Flow variables to be used in calculating loads
v_modflow = modmunselect! Flow
v_ttflow = ttmunselectlFlow 'If TT flows are in gpd, need to add in conversion factor!
'Calulate new flow value to be inserted in industrial select table
'changed from ttmunselectlFlow to v_ttflow
v_flow_new = modmunselectlFlow -v_ttflow
'If new flow <0 then set all concentration variables to original values
If v_flow_new <= 0 Then
v_flow_new = modmunselectlFlow / 2
v_bod_new = modmunselect! BOD
v_tss_new = modmunselectlTSS
v_tn_new = modmunselect! TN
v_tp_new = modmunselect!TP
v_fec_new = modmunselect!FEC
v_tkn_new = modmunselect !TKN
Elself modmunselect!LEVEL = 2 Then
'Calculate loads for both TT and NWPCAM municipal data
v_bod_new = ((modmunselect!BOD * v_modflow) - (ttmunselect!BOD * v primary BOD * v_ttflow)) /
v_flow_new
v_tss_new = ((modmunselect!TSS * v_modflow) - (ttmunselect!TSS * v_primary_TSS * v_ttflow)) /
v_flow_new
v_tn_new = ((modmunselect!TN * v_modflow) - (ttmunselect!TN * v_primary_TN * v_ttflow)) /
v_flow_new
v_tp_new = ((modmunselect!TP * v_modflow) - (ttmunselect!TP * v_primary_TP * v_ttflow)) /
v_flow_new
v_fec_new = ((modmunselect!FEC * v_modflow) - (ttmunselect!FEC * v_primary_FEC * v_ttflow)) /
v_flow_new
v_tkn_new = ((modmunselect!TKN * v_modflow) - (ttmunselect!TKN * v_primary_TKN * v_ttflow)) /
v_flow_new
Elself modmunselect! LEVEL = 3 Then
'Calculate loads for both TT and NWPCAM municipal data
v_bod_new= ((modmunselect!BOD * v_modflow)- (ttmunselect!BOD * v_advprimary_BOD *
v_ttflow))/ v_flow_new
v_tss_new = ((modmunselect!TSS * v_modflow) - (ttmunselect!TSS * v_advprimary_TSS * v_ttflow)) /
v_flow_new
v_tn_new = ((modmunselect!TN * v_modflow) - (ttmunselect!TN * v_advprimary_TN * v_ttflow)) /
v_flow_new
v_tp_new = ((modmunselect!TP * v_modflow) - (ttmunselect!TP * v_advprimary_TP * v_ttflow)) /
v_flow_new
v_fec_new = ((modmunselect!FEC * v_modflow) - (ttmunselect!FEC * v_advprimary_FEC * v_ttflow)) /
v_flow_new
v_tkn_new = ((modmunselect!TKN * v_modflow) - (ttmunselect!TKN * v_advprimary_TKN * v_ttflow))
/ v_flow_new
Elself modmunselect! LEVEL = 4 Then
'Calculate loads for both TT and NWPCAM municipal data
C-9
-------
v_bod_new = ((modmunselectlBOD * v_modflow) - (ttmunselectlBOD * v_secondary_BOD * v_ttflow))
/ v_flow_new
v_tss_new = ((modmunselectlTSS * v_modflow) - (ttmunselectlTSS * v_secondary_TSS * v_ttflow)) /
v_flow_new
v_tn_new = ((modmunselectlTN * v_modflow) - (ttmunselectlTN * v_secondary_TN * v_ttflow)) /
v_flow_new
v_tp_new = ((modmunselectlTP * v_modflow) - (ttmunselectlTP * v_secondary_TP * v_ttflow)) /
v_flow_new
v_fec_new = ((modmunselectlFEC * v_modflow) - (ttmunselectlFEC * v_secondary_FEC * v_ttflow)) /
v_flow_new
v_tkn_new = ((modmunselectlTKN * v_modflow) - (ttmunselectlTKN * v_secondary_TKN * v_ttflow)) /
v_flow_new
Elself modmunselect!LEVEL = 5 Then
'Calculate loads for both TT and NWPCAM municipal data
v_bod_new = ((modmunselectlBOD * v_modflow) - (ttmunselectlBOD * v_advwtl_BOD * v_ttflow)) /
v_flow_new
v_tss_new = ((modmunselectlTSS * v_modflow) - (ttmunselectlTSS * v_advwtl_TSS * v_ttflow)) /
v_flow_new
v_tn_new = ((modmunselectlTN * v_modflow) - (ttmunselectlTN * v_advwtl_TN * v_ttflow)) /
v_flow_new
v_tp_new = ((modmunselectlTP * v_modflow) - (ttmunselectlTP * v_advwtl_TP * v_ttflow)) /
v_flow_new
v_fec_new = ((modmunselectlFEC * v_modflow) - (ttmunselectlFEC * v_advwtl_FEC * v_ttflow)) /
v_flow_new
v_tkn_new = ((modmunselectlTKN * v_modflow) - (ttmunselectlTKN * v_advwtl_TKN * v_ttflow)) /
v_flow_new
Elself modmunselect! LEVEL = 6 Then
'Calculate loads for both TT and NWPCAM municipal data
v_bod_new = ((modmunselectlBOD * v_modflow) - (ttmunselectlBOD * v_advwt2_BOD * v_ttflow)) /
v_flow_new
v_tss_new = ((modmunselectlTSS * v_modflow) - (ttmunselectlTSS * v_advwt2_TSS * v_ttflow)) /
v_flow_new
v_tn_new = ((modmunselectlTN * v_modflow) - (ttmunselectlTN * v_advwt2_TN * v_ttflow)) /
v_flow_new
v_tp_new = ((modmunselectlTP * v_modflow) - (ttmunselectlTP * v_advwt2_TP * v_ttflow)) /
v_flow_new
v_fec_new = ((modmunselectlFEC * v_modflow) - (ttmunselectlFEC * v_advwt2_FEC * v_ttflow)) /
v_flow_new
v_tkn_new = ((modmunselectlTKN * v_modflow) - (ttmunselectlTKN * v_advwt2_TKN * v_ttflow)) /
v_flow_new
Elself modmunselect! LEVEL = 9 Then
'Calculate loads for both TT and NWPCAM municipal data
v_bod_new = ((modmunselectlBOD * v_modflow) - (ttmunselectlBOD * v_default_BOD * v_ttflow)) /
v_flow_new
v_tss_new = ((modmunselectlTSS * v_modflow) - (ttmunselectlTSS * v_default_TSS * v_ttflow)) /
v_flow_new
v_tn_new = ((modmunselectlTN * v_modflow) - (ttmunselectlTN * v_default_TN * v_ttflow)) /
v_flow_new
v_tp_new = ((modmunselectlTP * v_modflow) - (ttmunselectlTP * v_default_TP * v_ttflow)) /
v_flow_new
v_fec_new = ((modmunselectlFEC * v_modflow) - (ttmunselectlFEC * v_default_FEC * v_ttflow)) /
v flow new
C- 10
-------
v_tkn_new = ((modmunselect!TKN * v_modflow) - (ttmunselectlTKN * v_default_TKN * v_ttflow)) /
v_flow_new
End If
'QA new concentrations to see if any are < 0. If they are, set to default values based on treatment level.
Ifv_bod_new <= 0 Then
If modmunselect! LEVEL = 2 Then
v_bod_new = 143.5
Elself modmunselect!LEVEL = 3 Then
v_bod_new = 102.5
Elself modmunselect!LEVEL = 4 Then
v_bod_new = 16 .4
Elself modmunselect! LEVEL = 5 Then
v_bod_new = 6.2
Elself modmunselect!LEVEL = 6 Then
v_bod_new = 4.1
Elself modmunselect! LEVEL = 9 Then
v_bod_new = 16 .4
End If
End If
If v_tss_new <= 0 Then
If modmunselect! LEVEL = 2 Then
v_tss_new = 107.5
Elself modmunselect!LEVEL = 3 Then
v_tss_new = 64.5
Elself modmunselect!LEVEL = 4 Then
v_tss_new = 17.2
Elself modmunselect! LEVEL = 5 Then
v_tss_new = 6.5
Elself modmunselect! LEVEL = 6 Then
v_tss_new =4.3
Elself modmunselect!LEVEL = 9 Then
v_tss_new = 17.2
End If
End If
If v_tn_new <= 0 Then
If modmunselect! LEVEL = 2 Then
v_tn_new =23.4
Elself modmunselect! LEVEL = 3 Then
v_tn_new =23.4
Elself modmunselect! LEVEL = 4 Then
v_tn_new = 18.3
Elself modmunselect! LEVEL = 5 Then
v_tn_new = 18.4
Elself modmunselect! LEVEL = 6 Then
v_tn_new = 14.4
Elself modmunselect! LEVEL = 9 Then
v_tn_new = 18.3
End If
End If
If v_tp_new <= 0 Then
If modmunselect! LEVEL = 2 Then
v_tp_new =5.2
C-ll
-------
Elself modmunselect!LEVEL = 3 Then
v_tp_new = 5.2
Elself modmunselect! LEVEL = 4 Then
v_tp_new = 2.5
Elself modmunselect!LEVEL = 5 Then
v_tp_new =0.4
Elself modmunselect!LEVEL = 6 Then
v_tp_new =0.4
Elself modmunselect! LEVEL = 9 Then
v_tp_new =2.5
End If
End If
If v_fec_new <= 0 Then
If modmunselect! LEVEL = 2 Then
v_fec_new = 2060000
Elself modmunselect! LEVEL = 3 Then
v_fec_new = 2060000
Elself modmunselect! LEVEL = 4 Then
v_fec_new = 1580
Elself modmunselect! LEVEL = 5 Then
v_fec_new = 1580
Elself modmunselect! LEVEL = 6 Then
v_fec_new = 10
Elself modmunselect! LEVEL = 9 Then
v_fec_new = 1580
End If
End If
If v_tkn_new <= 0 Then
If modmunselect! LEVEL = 2 Then
v_tkn_new =23.4
Elself modmunselect!LEVEL = 3 Then
v_tkn_new =23.4
Elself modmunselect! LEVEL = 4 Then
v_tkn_new = 16.5
Elself modmunselect! LEVEL = 5 Then
v_tkn_new = 12.9
Elself modmunselect! LEVEL = 6 Then
v_tkn_new =3.6
Elself modmunselect! LEVEL = 9 Then
v_tkn_new = 16.5
End If
End If
'Update the new row with the constant data to copied from the NWPCAM municipal select table
UpdqryStr= "UPDATE munselectSET " & _
"flow = " & v_flow_new & ", BOD = '" & v_bod_new & '", TSS = " & v_tss_new & ", tn = " & v_tn_new
& ", TP= " & v_tp_new & ", FEC= " & v_fec_new & ", TKN= " & v_tkn_new & " " & _
"WHERE npdes = '" & v_npdes & "';"
DoCmd.RunSQL (UpdqryStr)
ttmunselect.MoveNext
Loop
ttmunselect.Close
C- 12
-------
MsgBox i & " were updated"
DoCmd.SetWarnings False
End Sub
Module 4: Update indirect facilities
SubUpdateTTMunQ
'Created 12/5/01 by Amy Miles
'Last modified 1/9/02 by Amy Miles
'Tables
Dim dbs As Database
Dim ttmunselect As Recordset
Dim modmunselect As Recordset
Set dbs = CurrentDbQ
'Variables
Dim i As Long
Dim v_npdes As Variant
Dim v_type As Variant
Dim v_bod As Variant
Dim v_tss As Variant
Dim v_tn As Variant
Dim v_tp As Variant
Dim v_fec As Variant
Dim v_tkn As Variant
Dim v_ttflow
Dim v primary BOD As Variant
Dim v_primary_TSS As Variant
Dim v_primary_TN A s Variant
Dim v_primary_TP A s Variant
Dim v_primary_FEC As Variant
Dim v_primary_TKN As Variant
Dim v_advprimary_BO D As Variant
Dim v_advprimary_TSS As Variant
Dim v_advprimary_TN As Variant
Dim v_advprimary_TP As Variant
Dim v_advprimary_FEC As Variant
Dim v_advprimary_TKN As Variant
Dim v_secondary_BOD As Variant
Dim v_secondary_TSS As Variant
Dim v_secondary_TN As Variant
Dim v_secondary_TP As Variant
Dim v_secondary_FEC As Variant
Dim v_secondary_TKN As Variant
Dim v_advwtl_BOD As Variant
Dim v_advwtl_TSS As Variant
Dim v_advwtl_TN As Variant
Dim v_advwtl_TP As Variant
Dim v_advwtl_FEC As Variant
Dim v_advwtl_TKN As Variant
Dim v advwt2 BOD As Variant
C-13
-------
Dim v_advwt2_TS S As Variant
Dim v_advwt2_TN As Variant
Dim v_advwt2_TP As Variant
Dim v_advwt2_FEC As Variant
Dim v_advwt2_TKN As Variant
Dim v_default_BOD As Variant
Dim v_default_TSS As Variant
Dim v_default_TN As V ariant
Dim v_default_TP As Variant
Dim v_default_FEC As Variant
Dim v_default_TKN As Variant
Dim v_seqno As Variant
Dim v_mi As Variant
Dim v_do As Variant
Dim v_cbodtoubod As Variant
Dim v_psfbod As Variant
Dim v_psftss As Variant
Dim v_cu As Variant
Dim v_seg As Variant
Dim v_name As Variant
v_primary_BOD = 0.7
v_primary_TSS = 0.5
v_primary_TN = 0.78
v_primary_TP = 0.87
v_primary_FEC = 0.65
v_primary_TKN = 0.78
v_advp rimary_B OD =0.5
v_advprimary_TSS = 0.3
v_advprimary_TN = 0.78
v_advprimary_TP = 0.87
v_advprimary_FEC = 0.65
v_advprimary_TKN = 0.78
v_secondary_BOD = 0.08
v_secondary_TSS = 0.08
v_secondary_TN = 0.61
v_secondary_TP = 0.42
v_secondary_FEC = 0.0005
v_secondary_TKN = 0.55
v_advwtl_BOD = 0.03
v_advwtl_TSS = 0.03
v_advwtl_TN = 0.61
v_advwtl_TP = 0.06
v_advwtl_FEC = 0.0005
v_advwtl_TKN = 0.43
v_advwt2_BOD = 0.02
v_advwt2_TSS = 0.02
v_advwt2_TN = 0.48
v_advwt2_TP = 0.06
v_advwt2_FEC = 0.0000032
v_advwt2_TKN = 0.12
v_default_BOD = 0.08
v default TSS = 0.08
C-14
-------
v_default_TN = 0.61
v_default_TP = 0.42
v_default_FEC = 0.0005
v_default_TKN = 0.55
'SQL query statement variables
Dim TTSelqryStr As String
Dim UpdqryStr As String
Dim SelqryStr As String
'Open TT Municipal Data
TTSelqryStr = " select * from TTIndirect where (option = 'BAT4' Or option = 'PSES 1');
Set ttmunselect = dbs.OpenRecordset(TTSelqryStr)
DoCmd.SetWarnings False
i = 0
ttmunselect.MoveF irst
Do Until ttmunselect.EOF
i = i+ 1
'Select Row in NWPCAM Model Data corresponding to TT data by NPDES number
SelqryStr = "select * from munselect where npdes = '" & ttmunselect!NPDES & '";"
Set modmunselect = dbs.OpenRecordset(SelqryStr)
'Set variable from TT data to be moved into NWPCAM Industrial Table
v_npdes = ttmunselectlNPDES
v_type= "INDIRECT"
'Set Flow variables to be used in calculating loads
v_ttflow = ttmunselect! Flow 'if TT flows are in gpd, need to add conversion factor
If modmunselect ILEVEL = 2 Then
'Calculate loads for both TT and NWPCAM municipal data
v_bod = ttmunselect!BOD * v primary BOD
v_tss = ttmunselect!TSS * v_primary_TSS
v_tn = ttmunselect!TN * v_primary_TN
v_tp = ttmunselect!TP * v_primary_TP
v_fec = ttmunselect!FEC * v_primary_FEC
v_tkn = ttmunselect! TKN * v_primary_TKN
Elself modmunselect!LEVEL = 3 Then
'Calculate loads for both TT and NWPCAM municipal data
v_bod = ttmunselect!BOD * v_advprimary_BOD
v_tss = ttmunselect!TSS * v_advprimary_TSS
v_tn = ttmunselect!TN * v_advprimary_TN
v_tp = ttmunselect !TP * v_advprimary_TP
v_fec = ttmunselect!FEC * v_advprimary_FEC
v_tkn = ttmunselect!TKN * v_advprimary_TKN
Elself modmunselect! LEVEL = 4 Then
'Calculate loads for both TT and NWPCAM municipal data
v_bod= ttmunselect!BOD * v_secondary_BOD
v_tss = ttmunselect!TSS * v_secondary_TSS
v_tn = ttmunselect!TN * v_secondary_TN
v_tp = ttmunselect!TP * v_secondary_TP
v_fec = ttmunselect!FEC * v_secondary_FEC
v_tkn = ttmunselect!TKN * v_secondary_TKN
Elself modmunselect! LEVEL = 5 Then
'Calculate loads for both TT and NWPCAM municipal data
v_bod= ttmunselect!BOD * v_advwtl_BOD
v tss = ttmunselect!TSS * v advwtl TSS
C-15
-------
v_tn = ttmunselectlTN * v_advwtl_TN
v_tp = ttmunselectlTP * v_advwtl_TP
v_fec = ttmunselectlFEC * v_advwtl_FEC
v_tkn = ttmunselectlTKN * v_advwtl_TKN
Elself modmunselect!LEVEL = 6 Then
'Calculate loads for both TT and NWPCAM municipal data
v_bod = ttmunselectlBOD * v_advwt2_BOD
v_tss = ttmunselectlTSS * v_advwt2_TSS
v_tn = ttmunselectlTN * v_advwt2_TN
v_tp = ttmunselectlTP * v_advwt2_TP
v_fec = ttmunselectlFEC * v_advwt2_FEC
v_tkn = ttmunselectlTKN * v_advwt2_TKN
Elself modmunselect! LEVEL = 9 Then
'Calculate concentrations for both TT and NWPCAM municipal data
v_bod= ttmunselectlBOD * v default BOD
v_tss = ttmunselectlTSS * v_default_TSS
v_tn = ttmunselectlTN * v_default_TN
v_tp = ttmunselectlTP * v_default_TP
v_fec = ttmunselectlFEC * v_default_FEC
v_tkn = ttmunselectlTKN * v_default_TKN
End If
'Update NWPCAM industrial select table withTT values by corresponding NPDES
UpdqryStr= "UPDATE indselect SET "& _
"flow = " & v_ttflow & ",bod = " & v_bod & ", tss= " & v_tss & ", tn= " & v_tn & ", tp= " & v_tp &
fec= " & v_fec & " , tkn= " & v_tkn & " " & _
"WHERE npdes = '" & v_npdes & "';"
DoCmd.RunSQL (UpdqryStr)
ttmunselect.MoveNext
Loop
ttmunselect.Close
MsgBox i & " were updated"
DoCmd.SetWarnings False
End Sub
C- 16
------- |