U.S. EPA Background Document
TOXICITY CHARACTERISTIC REGULATORY IMPACT ANALYSIS
Final Report
March 1990
Prepared for
Economic Analysis Staff
Office of Solid Waste
U.S. Environmental Protection Agency
Washington, D.C.

-------
50212-m
ErORT E-XliHaiTATIW
FA5E
1. REPORT NO.
EPA/530-SK-90-083
2.
3.
PB91-101873
4. Title and Subtitle
BADKiWft' DOCUMENT
FINAL REPORT
TOXICITY CHARACTERISTIC REGULATORY IMPACT ANALYSIS
5.	Report Bate
MARCH 1990
6.
7. Authoris)
0?ri/OBW
8. Performing Organnation Kept. No
9. Perfecting Or;a-i:a:icr. Kize and Address
U.S. Erfi
Office of Solid Waste
401 M. Street 5U
Wi=h;r.;ton, K K'HC'
10.	Project/Tasfc/Kort Unit fo.
11.	Contract(C) or Grant(E) No.
(C)
CG)
12. iponsorinj Orjsr.iiitio.- fens and Address
13.	Type of Report J< Period Covered
RIA - 3/90
14.
15. supriesc-ntsry Nates
It. Acstract sLisit: 2-» wsrcs)
/,
This F.ejulatcry Icfart Analysis examines the costs and benefits of an expanded Toxicity Characteristic (TO, which is
used to identify harardsus wastes rejuiated under Subtitle C of RCRS. This docuaent fulfills the represents of
Executive Order 1229!, tftich requires EPA to prepare a RIA for all tajor ruleaatings.
17. fccucerit Analysis a. Descriptors
b. Identifiers/Open-Ended Teres
c. C05ATI Field/Group
18. Availability Statement
19. Security Class (This Report)
21. No. of Fages

UNCLASSIFIED
0
RELEASE UNLIMITED
20. Security Class (This Page)
22. Price

UNCLASSIFIED
0
(See A.NS1-Z39.18)
0PT1
QNAL FORM 272 14-77)
(Foreerly NTIS-35)

-------
TABLE OF CONTENTS
Page
EXECUTIVE SUMMARY			 ES-1
CHAPTER 1:	INTRODUCTION		 		 1-1
1.1	Legislative Framework	 1-1
1.2	Agency Actions in Response to Statutory Provisions	 1-2
1.3	Regulatory Options and Final Rule			 1-6
1.4	Regulatory Analysis Requirements 	 1-8
1.5	Organization of the RIA 				 1-9
CHAPTER 2:	CHARACTERIZATION OF AFFECTED WASTES AND FACIliTlES 	 2-1
2.1	Waste Characterization	 2-1
2.2	Quantities of Waste Exhibiting the TC	 2-7
2.3	Number of Facilities Affected 		2-18
2.4	Limitations and Sensitivity Analyses 	2-27
CHAPTER 3:	COSTS	 3-1
3.1	Definition of Costs	 3-1
3.2	Methodology	 3-3
3.3	Results	 3-6
3.4	Limitations and Sensitivity Analyses 	3-17
CHAPTER 4:	ECONOMIC IMPACTS				 4-1
4.1	Methodology			 4-1
4.2	Results of Overall Economic Impact Analysis			 4-3
4.3	Small Business Analysis 	4-12
4.4	Limitations and Sensitivity Analyses 			4-14
CHAPTER 5:	BENEFITS			 5-1
5.1	Methodology						 5-1
5.2	Results	:	5-18
5.3	Limitations of the Methodology 	5-49
5.4	Sensitivity Analyses 					5-51
REFERENCES

-------
TABLE OF CONTENTS (continued)
APPENDIX A:	Used Oil Analysis
APPENDIX B:	Derivation of the Maximum and Minimum Scenarios
APPENDIX C:	Development of Unit Costs for Waste Management Practices
APPENDIX D:	Benefits Modeling
APPENDIX E:	Calculation of Plume Areas Using a Simplified Semi-Analytical Method
APPENDIX F:	MEI Risk by Constituent
APPENDIX G: Air Emissions from Surface Impoundments
APPENDIX H:	Toxicity Characteristic Impacts on the Cost of Managing Industrial
Wastewaters

-------
EXECUTIVE SUMMARY
This Regulatory Impact Analysis (RIA) examines the costs and benefits of an expanded
Toxicity Characteristic (TC), which is used to identify hazardous wastes regulated under
Subtitle C of the Resource Conservation and Recovery Act (RCRA). This document fulfills
the requirements of Executive Order 12291, which requires EPA to prepare a Regulatory
Impact Analysis for all major rulemakings.
LEGISLATIVE FRAMEWORK
RCRA Section 3001 (b) directs EPA to promulgate regulations identifying characteristics
of hazardous waste. In response to this directive, the Agency developed the Extraction
Procedure Toxicity Characteristic (EPTC) as one of four characteristics of hazardous waste.
To determine whether a waste exhibits the EPTC, regulatory levels (maximum
concentrations) are compared with constituent concentrations in leachate extracted from a
waste during a leaching test, the Extraction Procedure (EP). For wastes containing less
than 0.5 percent solids, the waste, after filtration, is defined as the extract. H a
concentration in the waste leachate equals or exceeds the corresponding regulatory level,
the waste is considered hazardous and is subject to regulation under Subtitle C of RCRA.
EPTC regulatory levels were established tor 14 constituents of concern, eight of which are
metals.
RCRA Sections 3001(g)-(h), which were among provisions Congress added to RCRA
with the Hazardous and Solid Waste Amendment of 1964 (HSWA), direct EPA to evaluate
and modify the EP and to identify additional hazardous waste characteristics including
measures of toxicity. The legislative history accompanying HSWA revealed specific concern
for wastes containing organic constituents, noting that organic wastes were rarely
encompassed by existing characteristics and that relatively few of such wastes were listed.
THE TOXICITY CHARACTERISTIC RULE
EPA is promulgating the Toxicity Characteristic rule to refine and broaden the scope of
the hazardous waste regulatory program and to fulfill specific HSWA mandates. EPA
proposed tha TC rule on June 13,1986. The June 13,1906 Federal Register notice
proposed replacing the existing EP with a newly developed Toxicity Characteristic Leaching
Procedure (TCLP), adding 38 additional organic chemicals to the list of TC toxicants of
concern, and calculating regulatory levels for organics using health-based concentration
thresholds and constituent-specific dilution and attenuation factors (DAFs) developed using
a ground-water transport model.
The final TC rule retains many of the features of the June 13,1986 proposal. It
replaces the EP with the TCLP, and adds 25 new organic constituents to the list of TC
constituents of concern. Regulatory levels for the 25 new constituents, which constitute the
nondegrading constituents (i.e., constituents that do not readily hydrolize) among the
originally proposed 38, are calculated by multiplying each health-based concentration
threshold by a OAF developed using a revised ground-water transport model. EPA has
revised some of the health-based concentration thresholds, or Chronic Toxicity Reference

-------
ES-2
Levels (CTRLs), to reflect new data and better methods. The regulatory levels for the 14
existing EP constituents are unchanged.
REGULATORY OPTIONS
The Agency considered numerous regulatory options for the final TC rule. Factors that
varied among the different options included the approach for determining OAFs, risk
thresholds used for health-based levels for carcinogenic constituents, and the list of
constituents to be regulated.
This RIA examines four regulatory options:
- DAF 33,
. DAF 100,
¦	DAF 250, and
. DAF 500.
The following factors are held constant across all regulatory options examined in this RIA:
•	The list of additional regulated constituents comprises 25 organic
constituents;
¦	Risk-Specific Doses (RSDs) are set at 10"5 risk level;
•	Quantitation Limits supercede calculated Regulatory Levels if the
Quantitation Limits are higher; and
¦	CTRLs are not apportioned among other sources of exposure.
CHARACTERIZATION OF AFFECTED WASTES AND FACILTTIES
The Agency characterized the existing, potentially affected universe of wastes and
facilities (i.e., the pre-regulatory or baseline scenario) by identifying industries to be
examined, accumulating information on the wastes generated by these industries, and
identifying current management practices for the wastes.
EPA prepared a series of industry studies for use in the TC RIA. Preliminary studies
examined a large number of industries, with emphasis on identifying whether or not TC
constituents would be likely to be present in industry wastes. Based on the preliminary
studies, EPA completed detailed profiles for 15 industrial sectors. Based on available
information, EPA conducted that three of these were unlikely to experience significant
impacts under any regulatory option. This RIA presents estimates of the costs, economic
impacts, and benefits attributable to the TC for 12 major industrial sectors including over 25
specific subsectors. EPA also considered the possibility that one wastestream that occurs
in many industries - used oil - might exhibit the TC.

-------
ES-3
The majority of westestreams for which data were available were wastewaters and
associated wastewater treatment sludges. The primary data sources for the industry studies
were development documents from EPA's Effluent Guidelines program. In addition to
analyzing wastewaters and wastewater treatment sludges, EPA also analyzed some solid
process residuals and organic liquids. Hie wastestream characterization data elements
used in the analysis were waste type, total quantity of wastestream generated (expressed
as metric tons per year (MT/year)), range and distribution of concentrations for each TC
constituent in the wastestream, and the number of facilities generating each wastestream.
EPA did not have facility-specific information, but rattier had characterizations of aggregate
wastestreams, each generated by a number of individual facilities.
The Agency used information from its Screening Survey of Industrial Subtitle D
Establishments to characterize baseline management practices for wastes under
consideration for this analysis. The baseline management practices identified for
wastewaters were different types of wastewater treatment prior to discharge under National
Pollutant Discharge Elimination System (NPOES) permit or to Publicly Owned Treatment
Works (POTWs). The Agency used data from the Screening Survey to estimate the number
of facilities that manage wastewaters in Subtitle 0 surface impoundments, since wastes
managed in these units would potentially be affected by the TC. Other facilities managing
wastewaters were assumed to be using baseline management practices already compliant
with Subtitle C regulations, including management in tanks prior to discharge regulated
under the Clean Water Act These tanks are exempt from Subtitle C permitting
requirements (40 CFR 264.1(g)(6)).
EPA identified three likely baseline management practices for sludge or slurry
wastestreams: on-site iandfilling, off-site landfilling, and on-site land treatment for those
wastes suitable for land treatment. For solid residuals, EPA identified two baseline
management practices: on-site and off-site iandfilling. Baseline management was assumed
to occur in Subtitle D units.
The Agency estimated, based on constituent concentration data, the quantity of each
wastestream characterized for the analysis that wc id exhibit the TC. Based on regulatory
levels under consideration, the Agency identified a critical concentration for each constituent
above which the waste would exhibit the TC. Using a computerized database, EPA
compared the concentration range for each constituent in every wastestream with the
critical concentration for that constituent. Based on distribution-specific statistical
calculations tot each constituent, the Agency determined what portion of the wastestream
would exhibit the TC solely by virtue of the presence of that constituent The constituent
that resulted in the largest percentage exhibiting the TC was designated the cost-driving
constituent Multiplying the percentage of the wastestream exhibiting the TC by the total
quantity of the wastestream yielded the estimated quantity exhibiting the TC. By using this
procedure, EPA assumed direct correlation of constituent concentrations, i.e., that the
highest concentrations of one constituent are present along with the highest concentrations
of other constituents in the wastestream. The Agency tested the sensitivity of results to the
direct correlation assumption by adding the percentages of waste exhibiting the TC for each
constituent, instead of picking a driving constituent This sensitivity analysis assumed a
perfect inverse correlation.
An additional step was required for wastewaters to determine affected quantity. As
mentioned, only some facilities in each industry manage their non-hazardous wastewaters in

-------
ES-4
surface impoundments. Other facilities use management practices that would be compliant
with RCRA Subtitle C regulations. EPA multiplied Screening Survey percentages of facilities
managing wastes in surface impoundments by the quantities exhibiting the TC to determine
the wastewater quantities actually affected by the rule. EPA performed sensitivity analysis
on the use of the Screening Survey percentages by alternatively assuming all wastewaters
are managed in surface impoundments. This provided an upper bound for the estimated
quantity of affected wastewaters.
EPA divided the number of facilities generating each wastestream into large and small
facility size categories, using a cutoff of SO employees to separate large from small facilities.
The proportion of "large" and "small" facilities within an SIC was determined using 1982
Census of Manufactures data.
The Agency then estimated the total quantity of each wastestream generated by firms
in each size category. EPA assumed that within each size category, all facilities generate
the same quantity of waste and that waste generation is proportional to value of shipments.
EPA tested the assumption that waste generation by large and small facilities is proportional
to value of shipments by alternatively assuming waste quantities were distributed equally
between large and small facilities (i.e., 50 percent generated by large facilities and 50
percent generated by small facilities}.
To estimate the number of facilities that generate wastes exhibiting the TC, EPA
multiplied the number of facilities (in each size category) generating each wastestream by
the percentage of the total wastestream quantity that exhibits the TC. The quantity of each
wastestream that exhibits the TC was then split evenly (within size category) among the
resulting number of facilities. EPA examined two alternative sensitivity analysis assumptions
for the percent of facilities potentially affected for each wastestream. First, EPA assumed
that rf an intermediate percentage (not 0 percent or 100 percent)1 of a wastestream
exhibited the TC, then 10 percent of facilities generating that wastestream were potentially
affected. This tended to concentrate larger quantities of waste at fewer facilities than in the
initial analysis. Second, EPA assumed that if an intermediate percentage of a wastestream
exhibited the TC, then 90 percent of facilities generating that wastestream were potentially
affected. These two alternative assumptions provided a reasonable upper and tower bound
of a range of affected facilities.
After deriving the number of facilities generating each wastestream that exhibits the TC,
EPA accounted for the possibility that single facilities may generate multiple wastestreams
that exhibit the TC, i.e., that there may be overlap among the facilities that are generating
each separate wastestream in an industry. To account for this overlap, EPA developed two
scenarios to assign wastes that exhibit the TC to model facilities: one scenario portrays the
maximum number of facilities affected and the other the minimum number of facilities
affected. For this RIA, "affected" is defined to mean incurring additional costs as a result of
the final TC rule. Affected facilities are ail facilities generating either 1) wastewaters that will
exhibit the TC and are currently managed in surface impoundments or 2) non-wastewaters
that will exhibit the TC.
1 Clearly, if none or aM of a wastestream exhibits the TC, then no facilities or all facilities are
affected by the rule because of that wastestream.

-------
ES-5
EPA qualitatively addressed the impacts of the TC on generators arid handlers of used
oil. Used oil is generated across a wide variety of industrial sectors, and analysis of
impacts is complicated by the fact that it has economic value and can be sold in
intermediate or end-use markets. Test data were not available to determine whether used
oil would exhibit the TC. Used oil may not fail the TC because of its oily consistency. In
order to develop worst-case estimates of quantities of used oil that may exhibit the TC, EPA
assumed that used oil would pass through the TCLP filter.
COST AND ECONOMIC IMPACT METHODOLOGY
EPA analyzed the incremental costs of the TC final rule in terms of both social costs
and compliance costs to industry (expressed as revenue requirements). Social costs are
the total costs of an activity minus any transfer payments (e.g., taxes, above-average
profits). Compliance costs measure the income that must be generated by an affected
party to offset newty incurred costs and maintain the same level of profit; these include
transfer payments. Incremental costs were calculated by subtracting baseline waste
management costs from post-regulatory waste management costs for model facilities.
Baseline waste management practices were identified during the characterization of affected
wastes and facilities. EPA predicted post-regulatory waste management practices by
assuming that- a generator would choose to manage wastes in the most economical
manner available to the generator.
Post-regulatory costs for wastewaters in this analysis are based on the cost of
management in tanks exempt from Subtitle C requirements. EPA also examined costs of
underground injection and dilution as potential compliance practices, but did not assign
these costs to any facilities because the estimated costs were significantly higher than for
management in exempt tanks.
EPA examined on-site Subtitle C landfills, on-site Subtitle C land treatment, and off-site
Subtitle C commercial facilities as post-regulatory options for sludges, slurries, and solid
residuals. The Agency included the costs of complying with relevant RCRA requirements
for owner/operators in its analysis of on-site Subtitle C waste management costs. In
addition to incorporating normal operating expenses for Subtitle C management, the Agency
also incorporated the costs for RCRA corrective action. Based on information in the
Corrective Action RIA,2 the Agency assumed that approximately 31 percent of ail new
Subtitle C facilities would trigger corrective action at some point in time. Approximately 12
percent would trigger corrective action immediately and 19 percent would trigger corrective
action sometime in the life of the facility. The remaining 69 percent of the facilities would
not trigger any corrective action and were not assigned corrective action costs. The cost
model predicted that the vast majority of model facility owner/operators would select off-site
management over on-site management
To gauge economic impacts, EPA compared compliance costs with average facility
costs of production and with cash from operations, using financial data obtained primarily
from the Census of Manufactures and Annual Survey of Manufactures. The Agency used
two ratios to identity facilities likely to experience adverse economic impacts: compliance
1 Draft Regulatory Impact Analysis for the Proposed Rulemaking on Corrective Action for Solid
Waste Management Units, ICF Incorporated, September 1986.

-------
ES-6
cost divided by cost of production (the COP ratio) and cash from operations divided by
compliance cost (the CFO ratio). The COP ratio represents the percent product price
increase for facility output that would be necessary of the entire compliance cost,
accompanied by facility profit, were to be passed through to consumers. The Agency
criterion is that a COP ratio of five percent or greater indicates a significant adverse
economic impact. The CFO ratio represents the number of times that a facility's profit
would cover the compliance coct if the facility were to hilly absorb the cost. For this ratio,
EPA considers a value of less than 20 to represent a significant adverse impact. A CFO
ratio of less than 2 represents the potential for facility closure.
BENEFITS METHODOLOGY
EPA examined three measures of benefits of the TC final rule. These measures were
reduction in human health risks, reduction in resource damage, and reduction in
groundwater cleanup costs. The methodology for estimating these benefits had two major
parts. EPA first determined the adverse effects resulting from the unregulated management
of wastes (i.e., baseline management). Then, EPA determined which of these adverse
effects would not be present if the wastes were regulated under the TC (i.e., post-regulatory
management).
EPA used simplified models of waste management for the baseline and post-regulatory
cases. In the baseline, EPA assumed that wastewaters are managed in surface
impoundments and non*wastewaters are managed in landfills or land application units. All
baseline units are assumed to be new, unlined units. To analyze the regulatory options,
EPA assumed a regulated waste is property managed in Subtitle C units and that proper
management results in negligible risk, resource damage, or clean-up cost. Under the
regulatory options, baseline damages are assumed to be eliminated when a waste is
regulated.
EPA characterized each potential TC wastestream by the constituents in each
wastestream expected to cause the greatest carcinogenic and non-carcinogenic risk (i.e.,
risk-driving constituents) and the number of facilities managing the wastestream. EPA used
this information in a Monte Carlo model that combined information on the distribution of
waste characteristics with information on the distribution of environmental and exposure
conditions associated with managing these wastes, and calculated the risk and resource
damage resulting from their management. The model produces exposure concentrations
and plume areas which reflect the variations in TC wastestream concentrations and in
hydrogeologic conditions, in the model, leakage from a facility is immediate and the effect
of the leakage is measured In terms of steady-state contaminant concentrations and
contaminated plume areas in the underlying ground water. The transport of constituents is
based on EPA's ground-water transport model, EPACML, and on data from EPA's Municipal
Landfill Survey.
Human health risk was measured in terms of risk to the most exposed individual (MEI)
and population risk. MEI risk was based on the constituent concentrations at the closest
downgradient well, if one was present, tf downgradient wells were not present, there was
no exposure and no MEI risk. Based on information from the Municipal Landfill Survey. 54
percent of the managing facilities do not have downgradient wells. For those facilities with

-------
ES-7
downgradient exposure, carcinogenic and non-carcinogenic MEI risk were estimated from
the lifetime dally doses of the constituents, calculated from the exposure concentrations.
Population risk was estimated for those scenarios with downgradient weiis (i.e., 46
percent of the scenarios). Population risk was based on the number of people affected by
the contaminated plume and was calculated separately for exposure to carcinogens and
non-carcinogens. Carcinogenic population risk was estimated in terms of the expected
number of cancer cases. This was determined by estimating the average individual risk
resulting from the contaminated plume and multiplying it by the affected population. Non-
carcinogenic population risk was estimated in terms of the population exposed above the
Reference Dose (RfD) for the constituent. The Referense Dose is the dose above which
adverse effects are expected to occur. Based on the plume area which exhibits a dose
above the RfD, EPA estimated the number of people exposed above the RfD. EPA
assumed a population density of 1.6 people per acre, based on the Municipal Landfill
Survey, in estimating carcinogenic and non-carcinogenic population risk.
Resource damage measures the cost associated with replacing contaminated ground
water that had been used as a source of drinking water. The resource damage estimates
were based on the costs of designing and constructing an alternative water supply which
meets the demand of the population located in the area with contaminated water. The
contaminated plume area is defined by constituent concentration thresholds, above which
the water is unsuitable for use. EPA used constituent thresholds based on drinking water
standards (i.e., MCLs) where they exist and, alternatively, the lower of taste and odor
thresholds or heatih-based thresholds (with the health-based thresholds limited by detection
limits).
To estimate cleanup costs avoided, EPA assumed that a portion of the facilities
managing TC wastes will require cleanup efforts. Without TC regulation, cleanup at these
sites will likely fall under public programs (either at the state level or under Superfund).
With regulation, the number of facilities requiring such cleanup is reduced. EPA
investigated the cleanup costs avoided due to TC regulation for a range of potentially
affected facilities using an average cleanup cost of $15 million per site. EPA used an
average value due to the lack of information relating the extent of contamination to cleanup
costs at a site. The average value results from an examination of data from 14 Superfund
Records of Decision (RODs). The RODs were selected to reflect sites at which TC
constituents are the primary constituents of concern and ground water is the primary
contaminated medium. EPA also assumed that any cleanup efforts would occur fifteen
years in the future and discounted the cleanup costs accordingly.
AFFECTED WASTES AND FACILITIES RESULTS
Exhibit ES-1 summarizes quantities of wastes and numbers of facilities affected under
the four regulatory options. The quantity of waste that would be affected by the rule
ranges from about 660 million metric tons (MMT) per year under the OAF 500 option to
approximately B40 MMT per year under the DAF 33 option. For all four options,
wastewaters account for over 99 percent of the total affected waste quantity. While large
quantities of wastewaters may be affected by the TC, these wastewater quantities will not
necessarily be brought into the Subtitle C system. This RIA predicts, based on cost
analysis, that handlers of wastewaters affected by the TC will choose to switch from

-------
ES-8
EXHIBIT ES-1
TOTAL QUANTITIES OF WASTE AND NUMBER OF FACILITIES AFFECTED BY THE TC RULE
Regulatory Option
DAF33
DAF 100
DAF 250
DAF 500
Total Quantity
Affacted (MT/vri*
640,000,000
730,000,000
700,000,000
660,000,000
Number of
Facilities Affected
(Minimum to Maximum)
17,000 - 19,000
15,000-17,000
14,000-16,000
14,000-16,000
Wastewaters constitute over 99 percent of total quantities affected.

-------
ES-9
management in surface impoundments to management in tanks exempt from Subtitle C
requirements. Most of the waste under each of the options is generated by targe facilities.
A total of 13 constituents appeared as "cost-driving" constituents in the analysis. For the
DAF 100 option, benzene was the driving constituent for over 60 percent of the affected
waste quantity. Other constituents that appeared as cost-driving constituents were vinyl
chloride, carbon tetrachloride, chloroform, trichlorethylene, 2,4-dinitrotoluene,
tetrachloroethylene, methyl ethyl ketone, pentachlorophenol, chlorobenzene, heptachlor,
2,4,6-trichlorophenol and nitrobenzene. The other 12 constituents analyzed did not appear
as driving constituents, although they were present in wastestream data. These
constituents did not appear as driving constituents but could have been present in
wastestreams for which another constituent was the driving constituent.
The total number of facilities affected for the different regulatory options ranged from
about 14,000 (minimum number affected under OAF 500) to 19,000 (maximum number
affected under OAF 33). Under the most stringent option (DAF 33), about 15,000 to 16,000
small facilities and about 1,900 to 2,600 large facilities would generate wastes affected by
the rule. Under the least stringent option (DAF 500), approximately 13,000 to 15,000 small
facilities and 700 to 1,100 large facilities would be affected by the rule.
COST AND ECONOMIC IMPACT RESULTS
The total annual social costs of the rule, expressed in 1988 dollars, range from
approximately $52 million for DAF 500 to £270 million for DAF 33. The social costs of the
DAF 100 option are $190 million per year and for DAF 250 are $67 million per year. The
total annual costs to industry (compliance costs) range from about $82 million for DAF 500
to approximately $350 million for the DAF 33 option. Compliance costs more than double
from DAF 250 ($110 miliion) to DAF 100 ($250 million). Cost and economic impact results
are summarized in Exhibit ES-2.
The vast majority of compliance costs (over 90 percent) incurred by industry are
concentrated over 5 or 6 industrial sectors (depending on the DAF option): Petroleum
Refining; Pulp and Paper; Wholesale Petroleum Marketing; Synthetic Fibers; Organic
Chemicals; and Pharmaceuticals. The Petroleum Refining industry incurs the largest costs
of any industry under the DAF 33 and DAF 100 options. Wholesale Petroleum Marketing
incurs the largest costs under the DAF 250 option, and Synthetic Fibers incurs the largest
costs under the DAF 500 option. Large facilities incur 80 to 90 percent of the total costs to
industry. Although the quantity of waste exhibiting the TC is driven by wastewaters, the
cost of complying with the TC rule is driven by sludges, slurries, and solid residuals due to
the significantly higher incremental costs tor managing these non-wastewaters.
Benzene was the driving constituent for wastestreams that account for at least 70
percent of total costs for DAF 100 and 80 percent of total costs for DAF 250. Chloroform,
vinyl chloride, and carbon tetrachloride are the other notable cost driving constituents for
these two options. Costs can not be strictly attributed to the driving constituents in
wastestreams, because it is possible that other TC constituents are also present along with
the driving constituents.
Facilities affected by the rule that choose to land dispose wastes on-site will require
permit modifications (if they are currently Subtitle C treatment, storage, or disposal facilities)

-------
ES-10
EXHIBIT ES-2
COSTS OF THE TC RULE AND ECONOMIC IMPACTS*
Number of
Establishments
Reaulatorv Ctotion
Social Cost
{$ million/vri
Compliance Cost
{$ million/vri
with Significant
Impacts
DAF 33
270
350
86
DAF 100
190
250
65
DAF 250
67
110
29
DAF 500
52
82
29
* Costs and economic impacts do not reflect the costs of Subtitle C closure of surface
impoundments; see Section 3.4.9 for discussion. They also do not reflect the
reduction in costs that would result if ol ly wastes do not fail the TC.

-------
ES-11
or will have to seek new RCRA Subtitle C permits. Some facilities treating or storing TC
wastes (but not disposing of them) may also require permit modifications. EPA estimated
the potential number of industrial facilities seeking permit modifications or new permits
under the four regulatory options. Under the least stringent regulatory option (DAF 500),
the Agency would expect up to 130 permit modifications and 17 new permit applications.
Under the most stringent regulatory option (DAF 33), the Agency would expect as many as
230 permit modifications and 260 permit applications. The number .of Subtitle C commercial
TSOFs seeking permit modifications could be as high as 360, the estimated number of
existing commercial TSDFs. Results are presented in Exhibit ES-3.
The number of establishments possibly facing significant impacts under the regulatory
alternatives ranges from 29 (DAF 500) to 86 (DAF 33), as shown in Exhibit ES-2. No facility
closures are anticipated as a result of the regulation. The industries containing
establishments that may have significant economic impacts under the regulatory options
presented are Pulp and Paper; Synthetic Rubber; Celluiosic Synthetic Fibers; and Organic
Chemicals. Under none of the regulatory options do 20 percent or more of small
businesses suffer significant impacts.
Three end-use management practices for used oil may be affected by the TC rule:
road oiling, dumping, and landfilling/inctneration. The largest affected quantity was that
associated with landfilllng/incineration (approximately 405,000 metric tons per year), followed
by dumping (374,000 MT/year), and road oiling (232,000 MT/year). If used oil were to
become hazardous under the TC, it would probably be shifted to other end-use
management practices such as rerefining, burning as fuel, and possibly management in a
Subtitle C landfill. The shift in management practices would impose costs on used oil
generators, the used oil management system (intermediate collectors and processors), and
end-users of used oil.
BENEFrrS RESULTS
Exhibit ES-4 summarizes results of the benefits analysis. A brief discussion of results
for each benefits measure examined follows.
Number of additional cancer cases in 70 years. There are 5.6 cases of cancer
predicted in the baseline case. These are divided roughly evenly between wastewaters and
non-wastewalns. The most stringent option (DAF 33) avoids all of these cancer cases.
DAF 100 and OAF 250 eliminate nearly all the cases. The least stringent option (DAF 500)
reduces the baaefine figure by 93 percent; the residual risk is due to non-wastewaters.
Number of facilities with cancer risk to the most exposed individual exceeding 10'5. In
the baseline case 790 facilities are estimated to pose cancer risks greater than 10~S. Non-
wastewaters account for 62 percent of that amount, and benzene more than 90 percent.
While the most stringent regulatory option brings afl 790 facilities beneath the 10~3
threshold, the less stringent options provide leaser degrees of protection. The DAF 500
option reduces the baseline value by 58 percent (with nearly all of the residual due to non-
wastewaters); the DAF 250 option reduces that value by 92 percent*, a DAF of 100 provides
a 99 percent reduction.

-------
ES-12
EXHIBIT ES-3
PERMIT MODIFICATIONS AND APPLICATIONS*
Regulatory Option
DAF 33
DAF 100
DAF 250
DAF 500
Potential
Permit Modifications**
51 to 230
45 to 220
3 to 220
3 to 130
Potential
Permit Applications
260
180 to 190
15 to 17
15 to 17
* Industrial facilities only. The number of Subtitle C commercial TSDFs seeking permit
modifications could be as high as 360.
** Low end of range includes only disposal permit modifications; high end of ranges
includes potential treatment and storage permit modifications.

-------
ES-13
EXHIBIT i&4
SUMMARY OF BASEUNE RISK AND Rf JULATORY BENEFITS FOR ALL WASTES*
Benefit Measure	Baseline	Benefit for Regulatory Option**
(units)	Risk DAF 33 DAF 100 DAF 250 DAF 500
Cancer cases (Number of cases)	5.6	5.6 5.5 5.5	5.2
Over 70 years
Facilities with cancer risk	790	790 780 730	460
> 10E-5 (Number of Facilities)
People exposed to non-carcinogenic 320	320 320 320 320
constituent concentration >RfD
(Number of People)
Facilities with non-carcinogenic	6.2	8.2 7.6 5.7	5.7
constituent exposure > RfD
(Number of Facilities)
Resource Damage (Billion Dollars) 3.8	3.8 3.8 3.6 2.4
Facilities with Resource Damage 1600 1600 1600 1600 1600
>10E6 dollars (Number of Facilities)
* Benefits estimates do not reflect the benefits from Subtitle C closure of surface
impoundments. They also do not reflect the reduction in benefits that would result if oily
wastes do not exhibit the TC.
** All regulatory option results are reported as reduction from baseline risk (I.e benefit).

-------
ES-14
Number of Individuals exposed to non-carcinogens at levels above the reference dose.
In the baseline case, there are 320 individuals with exposures that exceed the reference
dose for non-carcinogenic substances. Ail of the regulatory options prevent aii of these
exposures. Over 70 percent of the baseline cases are due to pentachlorophenol, and
nearly all are associated with exposures from wastewaters.
Number of facilities with exposures to non-carcinogens for the most exposed individual
exceeding the reference dose. Exposures exceeding the reference dose for non-
carcinogens are predicted to occur at 8.2 facilities in the baseline.3 Nearly 70 percent of
these facilities appear because of pentachlorophenol, and more than 70 percent are due to
exposures from wastewaters. The most stringent regulatory option brings exposures at all
facilities below the reference dose level. The less stringent options (DAFs 250 and 500}
provide only 70 percent of this protection, and do not bring maximum exposures below the
threshold for any of the facilities that appear in the baseline because of non-wastewater
exposures.
Resource damage. Resource damages in the baseline case are estimated tc be $3.8
billion. Non-wastewaters comprise 63 percent of that amount, and benzene is the
constituent responsible for 95 percent. While the most stringent regulatory options reduce
resource damage by nearly 100 percent, the least stringent option provides only a 63
percent reduction and leaves $1.4 billion in damages (essentially ail from non-wastewaters.)
In contrast, the DAF 250 option reduces baseline risks by 95 percent, and the OAF 100
option reduces the baseline value to essentially zero.
Number of facilities with resource damage exceeding $1 million. In the baseline, 1600
facilities are predicted to have resource damages exceeding $1 million. Almost all of these
cases are eliminated by any of the regulatory options presented in this document. (About 2
percent of the non-wastewater contribution to the baseline remains under the OAF 500
option.) The baseline cases are about evenly divided between wastewaters and non-
wastewaters, and 94% are attributable to benzene contamination.
Cleanup costs avoided. EPA estimates avoided cleanup costs at $15 billion for DAFs
33 through 500. This represents the full baseline value for such costs, and reflects the fact
that even the OAF 500 option reduced resource damage below the $1 million cutoff for
substantially ail facilities. Due to the simplified nature of this analysis, there is significant
uncertainty associated with these estimates.
COMPARISON OF COOTS AND BENEFITS
The Agency used cost and benefit estimates to compare relative costs and benefits of
the various regulatory options. Analyses were conducted separately and were not meant to
be used to produce absolute measures of cost effectiveness. Also note that it is difficult to
commensurate the timeframes associated with costs Incurred and benefits accrued. Exhibit
ES-5 shows the present value costs of the rule along with benefits analyses results for the
various measures of benefits. ES-6 presents MEI cancer risk reduction, population cancer
risk reduction, and resource damage reduction in •per dollar" terms, obtained by dividing
3 Fractional fadtties, Hke fractional cancer cases, are statistical projections produced by the
methodology and are not meant to be taken literally.

-------
ES-1S
EXHIBIT EM
PRESENT VALUE COSTS AND BENEFITS OF REGULATORY OPTIONS8
CompHence ME! Cancer
Osdon
Coet
(Preeerrt
Value
MWone of
1908 DoUeial0
Risk Reduction
(Reduotion In
No. el FeeM-
ieeBweadlno
1fr® flMI
MEI NonCancar Rlak
Reduction (Re-
duction In No. of
Feellltlee wtth
RID Exceedanee*)b,h
Population Cancer
Riak Reduction
(Annual Reduction
In No. of C*»e*lb,d
Population
NoivCencar Risk
Reduction (Re-
duction In No. of
Exceedanc*s)b • * •h
Resource Damage
Reduction
(Annualized,
Million* of
1988 Doll«ri)b-f
Cleanup Coata
Avoided
(AnnuaMzed,
mm ,, rj
HMNft Of
l«» Oo«er»|b-
OAF 33
8,200
780
8.2
5.6
320
3,800
15,000
OAF 100
3,700
780
7.8
5.5
320
3,800
15,000 '
OAF 280
1,600
730
5.7
S.5
320
3,600
15,000
*
OAF BOO
1,200
400
5.7
52
320
2,400
15.000
*	Dim to analytical uncertainly, Ow coet and benefit estimate* are mora useful In comparing the rehtfivo coats and benefit* of the regulrtoiy option* than In measuring tha absolute co»U and
benefit* of the opttone.
b	The dlHerer* benel!»» meeeuree are oveiiepping end *houkl not be edded.
6	frwifi ooet* Incurred over SO yarn. Eatlmataa were made aa range*; high and of range la preaenled. Coal* are lota] coat* for all waste type*.
d	Cancer caeee Incurred over TO year*.
*	Norvoanoer axoeedano— beaed on 70 year expoaure.
f	Reeource damage Incurred over 200 yean,
*	Cleanup oo*»* Incurred over 3&year period of cleanup.
h MEI ri*fc end norvcarclnogenJc population risk are baaed on a 70-yaar exposure. Thay are not present value benefit*.
1	Due to elmplMed nature of title analyst*. there la significant uncertainty aaeoclated with theee atUmatae.

-------
ES-16
EXHIBIT EM
COST EFFECTIVENESS OF REGULATORY OPTIONS BASED ON PRESENT VALUES*
OoUon
MEI Cancar Malt Reduction par
MllUon Dote* (Raductkm in No. of
of FacMaa Bcaaadlng 10-5 OMdad
bv Pmmt Vtkm Comollanca Coattb«e
Population Cancar RItk Raductlon
par Million OoHara (Raductlon In
Praaant Valua No. of Caaaa DMdad
bv Praaant Valua Comollanca Coattb,d
Reduction In Raiouica Dwnaga Par
Million Dollar* (Raductlon In Praaant
Valua Raaourca Damaga DMdad by
Prate rrt Valua Compllanca Coa6b**
OAF 33
.15
0.001
$0.73 million ,
OAF 100
.21
0.002
S1.0 million
OAF 290
.40
,003
$2.3 million
OAF 900
.38
.004
$2.0 million
*	Social ooata Inourrad annually war 20 yaara.
b	Tha dMarant banaMa maaauraa ara avartapplng and ahould not ba addad.
0	ME) ilak to baaad on a 70-yaar axpoaura; It la nol a praaant valua banal*.
d	Cancar caaaa Incunad ovar 70 yaan.
*	Raaouraa damao* Ineurrad ovar 200 yaara.

-------
ES-17
each benefit by total present value cost estimates for the regulatory options. The discount
rate assumed in present value calculations is three percent.
LIMITATIONS
Some important limitations of the analysis would tend to underestimate costs and
economic impacts of the rule:
¦	Some industries and wastes (e.g., contaminated soil, off-spec products,
contaminated debris) not addressed by the RIA may be affected by the
TC.
¦	Some costs that may be incurred by certain facilities are not included,
such as costs for TCLP testing.
¦	Additional costs for closing surface impoundments as Subtitle C units will
be incurred by some facilities. EPA examined an upper bound cost and
economic impact scenario by assuming the additional costs will be
incurred by some facilities.
One major limitation may overstate costs and economic impacts of the rule:
•	Oily sludges in the Petroleum Refining, Wholesale Petroleum Marketing,
and Petroleum Pipelines industries may not pass through the TCLP as
readily as non-oily wastes; thus, in reality, oily wastes may not exhibit
the TC as predicted. To generate lower bound estimates of costs and
economic impacts, the Agency assumed that no oily non-liquid wastes
will exhibit the TC.
Other limitations create uncertainty, and may either understate or overstate costs nd
economic impacts. Since the Agency did not have facility-specific information, there a
substantial amount of uncertainty associated with the average unit costs used. Furth
assumptions were necessaiy in the characterization of affected wastes and facilities, i :he
absence of facility-specific information. There were four important areas where assun ions
were necessary:
¦	Estimating quantities of waste exhibiting the TC;
•	Assigning management practices;
¦	Distributing affected waste quantities to large and small facilities, and
•	Estimating the number of facilities affected by tie TC.
In addition, there are uncertainties inherent in estimating health risks, resource damage
and cleanup costs. Several limitations may underestimate benefits of the rule:
The benefits analysis focused on exposure only via the groundwater medium.

-------
ES-18
¦	Some industries and wastes (e.g., off-spec products contaminated soils,
and contaminated debris) not addressed in the RIA may contribute to
benefits.
. Other benefits measures, such as ecological risks, were not included.
•	The risks estimated in this analysis take into account only the twenty-five
constituents now considered for inclusion in the TC rule. Additional risks
and resource damage may be expected to result from co-controlling
other constituents in wastestreams regulated by this rule. Also, the
characterization of each wastestream by a single risk driver for cancer
risks and a single risk driver for non-cancer exposures may have
masked significant contributions to risk by other contaminants included
in the same wastestream.
•	The current analysis assumes that the TC RIA database accurately
reflects the wastes and wastestreams that will exist upon promulgation of
the TC rule. It neglects the powerful stimulus that the TC rule may
provide for facility owner/operators to enhance pollution prevention
efforts. Pollution prevention has merit on its own. Procedural changes
to adopt less hazardous substitute chemicals or to begin closed-loop
recycling would also reduce the health impacts and resource damages
associated with current patterns of chemical use.
¦	As an upper bound for compliance costs, EPA assumed that some
facilities managing wastewaters in surface impoundments could not
switch to tank management by the effective date of the rule, and would
incur additional costs for Subtitle C closure of surface impoundments.
Benefits for such closure, and possibly for bringing additional facilities
into the Subtitle C system and subjecting them to RCRA corrective
action, were not included.
Other limitations may overstate the benefits of the rule:
•	The methodology assumes that all risk and resource damage observed
in the baseline may be avoided under post-regulatory conditions.
¦	Oily sludges may not fitter in the TCLP and, therefore, may not exhibit
the TC as predicted.
¦	Wastewater benefits are based on concentrations in surface impoundment
influents and do not account for potential constituent loss through volatilization.
¦	The steady-state model does not consider the volume of waste being
managed at any particular facility. Assuming that the contaminated
plume grows immediately leads to overestimates for risk and resource
damage because it may take many years for contaminant plumes to
reach equilibrium size. Moreover, if insufficient contaminant quantities
are actually present in a particular facility, there may not be sufficient
mass of the contaminants to reach the equilibrium plume size.

-------
ES-19
•	The health benefits portion of EPA's methodology does not consider the
possibility of detection and response to groundwater contamination.
Taste and odor problems may alert populations at risk, or State or
Federal monitoring programs may detect the contaminated plume. If
contamination is discovered, residents may switch to bottled water or
formal corrective action procedures may be initiated.
¦	The steady-state model used to develop estimates for the size of
contaminated ground-water plumes does not consider the possibility of
discharge to surface water. Particularly in the humid East, water tables
tend to be close to the surface and contaminant plumes may be
truncated by the discharge of contaminated groundwater to the surface.
This suggests that the plume sizes used in the current analysis may be
overestimates, and that estimates for carcinogenic population risk, non-
cancer population exposure, and resource damage may also be
overestimated.
General uncertainty arises from some assumptions used in the analysis. These
assumptions may either understate or overstate benefits. There are severed areas where
assumptions were necessary:
>	Using environmental and hydrogeologic data from municipal landfills to represent
Subtitle 0 industrial facilities;
•	Using uniform population densities for determining population risk and
resource damage.
¦	Estimating the number of facilities managing TC wastes.
¦	Assigning potency factors for toxic constituents.
>	Using median hydrogeologic environment to calculate plume areas.
SENSITIVITY ANALYSES
With limited information available, the Agency concentrated on gathering data
necessary to quantify the major impacts of the TC rule. In many cases, assumptions were
necessary in order to conduct this RIA in the absence of specific information. The Agency
conducted sensitivity analyses on major assumptions including assumptions made to
estimate waste quantities exhibiting the TC, to distribute waste quantities to large and small
facilities, to estimate numbers of facilities affected, to estimate wastewater quantities
manged in surface impoundments, to predict the behavior of oily wastes in the TCLP, and
to calculate costs associated with TC wastewaters currently managed in surface
impoundments.
Sensitivity analysis showed that cost results are very insensitive to the driving
constituent assumption (i.e., assuming direct correlation of constituent concentrations) used
to estimate quantities of waste that exhibit the TC. For most wastestreams either (1) only

-------
ES-20
the driving constituent is present at levels above the TC regulatory levels, or (2) most of the
wastestream would exhibit the TC by virtue of the driving constituent.
When EPA assumed, in order to establish an upper bound for quantities of affected
wastewaters, that all wastewaters are managed in surface impoundments, affected
wastewater quantities increased substantially. However, since non-wastewaters drive the
cost of the rule, cost estimates were not as sensitive to this assumption. Under this
assumption, total social costs of the rule increased by approximately ten percent. The
increase in costs did not substantially affect economic impacts.
Using the 50/50 (portion of waste generated by small/large facilities) distribution
assumption as an alternative to assuming distribution proportional to value of shipments,
social costs of the rule increased by a little over five percent. Compliance costs to industry
generally decreased for large facilities and increased significantly for small facilities. In
conjunction with small facilities generating larger waste quantities and incurring higher costs
under this assumption, there were greater economic impacts for small facilities.
Instead of linking the estimate of the number of facilities affected to the percentage of
waste that exhibited the TC, the Agency assumed (1) that 10 percent of facilities are
affected and (2) that 90 percent of facilities are affected. The analysis was much more
sensitive to the first alternative assumption (set intermediate percentages to 10 percent)
than to the second (set intermediate percentages to 90 percent). For many industries,
wastestreams driving costs were exhibiting the TC in very large percentages. This resulted
in comparatively low sensitivity to the 90 percent assumption. Setting intermediate
percentages to 10 percent reduced the total social costs of the rule by approximately 50
percent, while setting intermediate percentages to SO percent resulted in only a one percent
decrease. Compliance costs to industry decreased very significantly under the 10 percent
assumption, especially for large facilities. For small facilities, the decreases in compliance
costs ranged from negligible in certain industries to approximately 25 percent in others.
When the Agency assumed that no oily non-liquid waste will exhibit the TC, lower
bound annual compliance costs estimates were $130 million for OAF 100 and $66 million
for OAF 250. Under the upper bound assumption that some facilities will incur additional
costs for waste managed in surface impoundments, total annual compliance costs were
$400 million for the OAF 100 option and $260 under OAF 250.
Only one of the sensitivity analyses described above would have significant
implications in terms of the benefits of the rule. Assuming that all facilities generating
wastewaters manage them on-site in surface impoundments would increase the number of
managing facilities substantially. Accordingly, the number of facilities causing MEI risk
equal to 10"3 or greater, RfD exceedances, or resource damage greater than $100,000
would also increase. Baseline resource damage and cleanup costs for wastewaters would
increase significantly.
EPA also examined the assumption that only 46 percent of facilities managing wastes
on-site have downgradlent drinking water wells. By assuming that all of the facilities were
upgradlent of wells, the Agency determined that the benefits would be larger by a factor of
approximately two.

-------
CHAPTER 1
INTRODUCTION
This Regulatory Impact Analysis (RIA) for the final Toxicity Characteristic (TC) Rule
submitted in accordance with requirements of Executive Order 12291, presents the costs
and the benefits of options considered by EPA in developing the TC Rule.
This chapter outlines the development of the Toxicity Characteristic (TC) Rule from
the original directive issued by Congress in Section 3001 of the Resource Conservation and
Recovery Act (RCRA) to EPA's final analysis of regulatory options for the TC Rule. The
chapter is divided into five parts. The first section reviews the legislative framework
supporting the identification of wastes as hazardous based on intrinsic characteristics of the
waste. The second section summarizes the actions taken by EPA in response to
Congressional mandates within RCRA and the Hazardous and Solid Waste Amendments of
1984 (HSWA) to identify wastes as hazardous based on the characteristic of toxicity. The
third section provides a general description of the regulatory options for the TC evaluated
by EPA within this RIA, as well as other options considered by the Agency. The fourth
section identifies the requirements that the Agency must satisfy in evaluating the impacts of
the TC rule. The final section outlines the organization for the rest of the RIA.
1.1 LEGISLATIVE FRAMEWORK
In Section 3001(b) of RCRA, Congress directs the EPA Administrator to "promulgate
regulations identifying the characteristics of hazardous wastes." RCRA Section 3001 (a)
further specifies that the criteria for identifying characteristics for hazardous wastes should
take into account such factors as 'toxicity, persistence, and degradabiiity in nature, potential
for accumulation in tissue, and other related factors ..." In response to this directive, the
Agency developed the Extraction Procedure Toxicity Characteristic (EPTC) (40 CFR 261.24).
The established test method for this indicator of a waste's toxicity is the Extraction
Procedure (EP), a laboratory test of the potential teachability of specific constituents from a
waste. For solid wastes, the EP exposes the waste to a liquid leaching medium; if the
lee .nate from the test contains any regulated constituents at or above a constituent-specific
Regulatory Laval (RL), the waste is deemed a hazardous waste due to its EP toxicity. For
liquid wastes, the waste is filtered and constituent concentrations in the filtrate are
compared to the constituent-specific RLs.
*
In HSWA, Congress further refined its position regarding the identification of a waste
as hazardous based on characteristics of the waste. Congress added RCRA Section
3001(g), which directs the Administrator to "examine the deficiencies of the extraction
procedure toxicity characteristic [EPTC]... and make changes ... as are necessary to insure
that it accurately predicts the leaching potential of wastes ..." HSWA also corrta;ns
language charging the Administrator with "identifying additional characteristics of hazardous
waste, including measures or indicators of toxicity." [RCRA Section 3001(h)]
Thus, HSWA requires the Administrator to expand the list of characteristics identifying
wastes as hazardous. In response to the HSWA directives to (1) evaluate and modify the

-------
1-2
EPTC, arid (2) expand the list of characteristics used to identify a waste as hazardous, EPA
proposed to revise and expand the RCRA Toxicity Characteristic.
1.2 AGENCY ACTIONS IN RESPONSE TO STATUTORY PROVISIONS
The previous section presented a general description of the Congressional mandate
instructing the Agency to develop characteristics for identification of hazardous wastes.
This section provides a more detailed explanation of the actions taken by the Agency to
fulfill this mandate. Specifically, this section outlines the development of the existing EPTC
and the proposal to revise and expand the TC. The final TC rule is discussed in Section
1.3.
1.2.1 Extraction Procedure Toxicity Characteristic
On May 19,1980, the Agency promulgated the EPTC. "Hie EPTC, devised by the
Agency in response to the aforementioned RCRA directives, was designed to identify
wastes as hazardous based on the characteristic of toxicity, in practical terms, EP toxicity
is a measure of the possibility that specific constituents could migrate from a waste to a
point of exposure and pose a risk to human health. The methodology for evaluating this
characteristic of toxicity involves comparing Regulatory levels (maximum concentrations) for
constituents in a leachate with the concentrations of constituents liberated from a waste
during the leaching test. If the concentration of a constituent in the leachate equals or
exceeds the RL for a constituent, the waste is deemed hazardous based on the
characteristic of toxicity. In choosing an extraction procedure and setting RLs, the Agency
developed a specific "mismanagement* scenario, because RCRA mandates that the Agency
identify hazardous wastes as those wastes that pose a threat to human health and the
environment when improperly managed (RCRA section 1004(5)). The EP was based on a
mismanagement scenario that assumes wastes would be co-disposed with municipal wastes
in an unlined landfill.
Regulatory Levels in the EPTC
The Agency set Regulatory Levels in the EPTC based upon assumptions regarding
the fate and transport of constituents of concern in the environment and information
regarding the toxicity of each specific constituent The first step for developing an RL was
to determine a health-based exposure threshold for each constituent. For the EP
constituents, the Agency used available National Interim Primary Drinking Water Standards
as the health-based thresholds.
The Agency then needed to account for the reduction in constituent concentration
that occurs as constituents in leachate travel downward into ground water and laterally
within an aquifer. The Agency estimated a dilution and attenuation factor (DAF) to
represent the degree to which constituent concentrations would be diminished in the
environment. For the EPTC, the Agency estimated that concentrations for all constituents
would be reduced by a factor of 100 from the time the leachate was produced in a landfill
to the time the constituents reached a drinking water source. A constituent concentration
in the original leachate more than 100 times greater than the health-based level at the
exposure point would therefore pose a risk to human health. Using a back calculation, the

-------
1-3
Regulatory Levels for specific EFTC constituents were determined by multiplying the
Drinking Water Standards for'each constituent by the estimated DAF of 100.
Extraction Procedure (EP)
In order to evaluate whether or not a waste leachate would exceed the Regulatory
Levels for any constituents, a leaching test was also necessary. As described previously,
the EP test is a procedure in which a solid waste is exposed to a liquid leaching medium
so that constituents are liberated from the waste into the liquid. For liquid wastes, the
waste is filtered and the filtrate is considered the leachate. The EP leaching medium for the
solid waste leaching test is an acetic acid solution designed to represent the likely leaching
medium occurring in the mismanagement scenario (i.e., co-disposal with municipal waste).
After the waste is exposed to the acetic acid, the liquid leachate is analyzed to determine
the concentration of constituents in the leachate. The results of this test, when compared
to the Regulatory Levels for each constituent, serve as the basic criterion for establishing
the characteristic of EP toxicity.
Need for Improvement in the EFTC
The Agency recognized several shortcomings of the EPTC that could be improved.
First, the EP was not designed to reflect accurately the leaching potential of many
constituents of concern; for example, the EP did not model accurately the teachability of
organic chemicals. Second, the generic DAF in the EPTC was not scientifically supported.
Finally, since there were no widely-accepted health-based thresholds for many chemicals,
the number of constituents which could be regulated under the EPTC was limited. Because
of these limitations and the directive from Congress in HSWA, the Agency proposed a
revised and expanded TC.
1.2.2 The June 13,1986 Toxicity Characteristic Proposal
EPA proposed the revised and expanded Toxicity Characteristic Rule (TC Rule) on
June 13, 1986 (51 FR 21648), The proposed rule responds to HSWA by establishing a new
characteristic for hazardous wastes (the TC) that is designed to improve upon and replace
the EPTC. The proposed TC included several changes to both the Regulatory Level
cassation process and the procedure used in the EP leaching test, and proposed adding
3E -lore constituents to the list of regulated toxicants.
Reautatoiv Levels - Chronic Toxicity Reference Levels
The proposed TC introduced new health-based levels, termed Chronic Toxicity
Reference Levels (CTRLs), for additional constituents. The CTRLs for 38 proposed new TC
constituents were, when available, the Drinking Water Standards (DWSs) or Maximum
Contaminant Levels (MCLs) that had been developed since the publication of the EP. In
cases where MCLs or DWSs were not available for a particular non-carcinogenic constituent
of concern, the proposed TC used the Reference Dose (RfD) for that constituent as the
CTRL The Reference Dose (RfD) is an estimate of the daily dose of a substance which will
result in no adverse effect even after a lifetime of exposure.
For carcinogens having no MCL or DWS, the Agency used Risk-Specific Doses (RSD)
as the CTRLs. An RSD is the daily intake of a substance that corresponds to a specified

-------
1-4
excess cancer risk over a lifetime of exposure. The likelihood of cancer defines the risk
level, and the RSD is then based on this risk level. For example, if one cancer case in one
million (10~* risk) was chosen as a risk level, then the RSD would be that dose of a
constituent that would statistically result in one additional cancer case in one million
individuals exposed, in the proposed TC, the Agency varied the risk levels for different
carcinogens based on the scientific evidence that the constituent causes cancer in humans.
A Class A carcinogen was considered a definite human carcinogen and therefore for the
purpose of the TC was assigned a higher risk level than a class C carcinogen, which was
only a possible human carcinogen. The risk levels for the proposed TC constituents were
10"5 for Class A and B carcinogens and 10"* for Class C carcinogens.
One aspect of the proposed TC that affected the CTRLs for constituents was
apportionment. For non-carcinogens that used RfDs in the calculation of Regulatory Levels,
the proposed TC accounted for possible alternative routes of exposure. In the proposal,
the Agency apportioned RfDs among exposure routes based on available information about
the presence of constituents in other potential sources of exposure (e.g., food and air). If
no information was available on alternative sources, the Agency used a SO percent
apportionment factor for the RfD. Apportionment effectively reduced the allowable dose of
a constituent in drinking water to account for the existence of other exposure sources.
For carcinogens, the proposed TC did not account tor apportionment because of the
uncertainty involved in the calculation of RSDs. The RSD calculation process was
conservative by design, so that a difference in the daily dose to account for apportionment
would still be well within the margin of uncertainty of the estimated RSD. In addition, since
carcinogenic risk is determined by the daily dose averaged over a lifetime, small variations
around the daily dose have little effect on overall risk.
Regulatory Levels - DAFs
The proposed TC also introduced new DAFs for regulated constituents. To
determine Regulatory Levels (RU) for the 44 organic constituents the proposed TC used
constituent-specific DAFs based on a ground-water transport model. A Monte Carlo
simulation was used to estimate a range of expected DAF values for a variety of
environmental and hydrogeoiogic variables known to influence dilution and attenuation. The
ground-water transport model then calculated a cumulative frequency distribution of DAFs
ge erated by the Monte Carlo simulation for each constituent, using different combinations
of environmental and hydrogeoiogic variables.
The cumulative frequency distribution allowed the Agency to choose DAFs for each
constituent based on the probability that a DAF calculated by the ground-water transport
model (based on the randomly chosen conditions) would not exceed the chosen DAF. The
Agency used the 85th percentile cumulative frequency interval in the proposed TC. Thus,
the constituent-specific DAFs used in the proposal would be expected to exceed the range
of DAFs (as calculated by the model) 85 percent of the time. Conversely, only 15 percent
of the model-calculated DAFs would be smaller than the chosen DAF. The Agency chose
the 85th cumulative percentile DAFs because it believed this to be a reasonably
conservative value.
After the DAFs were chosen, the TC Regulatory Levels for each constituent were
calculated the same way as in the EP. The Chronic Toxicity Reference Level was multiplied

-------
1-5
by the DAF for each constituent, resulting in a constituent concentration that could not be
exceeded in the leachate without posing a threat to human health. The Regulatory Level
was set equal to this calculated value unless current technology did not allow adequate
quantitation of the constituent of concern at this level. In such a case, the Quantitation
limit (QL) became the Regulatory Level for the constituent.
Toxicity Characteristic Leaching Procedure fTCLF}
The proposed TC introduced a second generation leaching procedure (the TCLP),
which is designed to more accurately depict the leaching of constituents that occurs when
a waste is co-disposed with municipal wastes in a landfill. The TCLP contains several
technical modifications to the EP test (e.g., revised analytical methods and zero headspace
extraction for volatiles) that enable the TCLP to determine the teachability of many organic
constituents that could not be addressed accurately by the EP.
After proposing the TC, the Agency published several other follow-up notices of
proposed rulemaking containing possible modifications to the TC. The following sections
discuss two of these notices.
1.2.3 Supplemental Notice - Wastewaters
The Agency received numerous comments from industry concerning the application
of the TC to wastewaters. The commenters were concerned primarily with the application
of the TC mismanagement scenario (co-disposal of wastes with municipal wastes in an
unlined landfill) to wastewaters managed in surface impoundments. They argued these
wastes were virtually never co-disposed with municipal wastes. The commenters
recommended that the Agency consider an alternative mismanagement scenario for
wastewaters that more accurately reflected the likely mismanagement of these wastes.
On May 18, 1987, EPA published a Supplemental Notice of Proposed Rulemaking in
response to these concerns (52 Federal Register 18583). The supplemental notice outlined
several possible alternatives for the application of the TC to wastewaters. In the notice, the
Agency suggested the possibility of developing a separate mismanagement scenario for
wastewaters and presented a series of options for determining whether or not specific
wastes would be eligible for testing under the new scenario. The alternative scenario for
A/a :ewaters assumed that eligible wastes are managed in an unlined impoundment instead
of jeing co-disposed in a municipal landfill. With this additional mismanagement scenario
there would be two separate regulatory levels for each constituent; one regulatory level
would be calculated based on the co-disposal assumption, and the other would be
determined using the impoundment scenario. *
The Agency analyzed data to determine if such a separate scenario war, appropriate
for wastes managed in impoundments. EPA modified the existing fate and transport model
to estimate the dilution and attenuation likely to occur as wastewaters managed in
impoundments infiltrated into ground water. After exhaustive review of applicable data, the
Agency concluded that, while the mechanics of impoundment waste infiltration and leachate
dilution and attenuation are different from those for a landfill, the resulting concentrations cf
constituents in ground water would not vary significantly from those predicted using the
landfill scenario. The presence of lower concentrations of constituents in wastewater and
the absence of an acetic acid leaching medium seem to be offset by the increased

-------
1-6
infiltration of wastewater constituents due to the pressure of hydraulic head in an
impoundment The Agency therefore concluded that ground-water transport of ieachate
from wastes managed in impoundments is adequately represented by the DAFs developed
using the original proposed TC mismanagement scenario.
1.2.4 Notice of Data Availability and Request for Comments on Uae of Generic DAFs
Due to the uncertainties and delays involved with developing sufficiently
representative DAFs for each specific TC constituent, the Agency published a Notice of
Data Availability and Request for Comments on May 19, 1988. In this notice, the Agency
proposed an alternative to the constituent-specific DAFs in the proposed TC. The Agency
presented a two-tiered approach to developing DAFs for the TC. In the first tier, the
Agency would use generic DAFs for all 38 new TC constituents while development of
constituent-specific DAFs proceeded. Once the development of these DAFs was
completed, they would be implemented in the second tier. The Agency specifically
requested comment on the use of a relatively high, generic DAF that would initially result in
regulation of the most toxic wastes. Once constituent-specific DAFs were determined, lower
regulatory levels would result in more waste exhibiting the TC. Since EPA was able to .
resolve issues surrounding the fate and transport model for the constituents to be included
in the final rule, the Agency decided to use the model to develop DAFs.
1.3 REGULATORY OPTIONS AND FINAL. RULE
As previously mentioned, the Agency considered numerous regulatory options for the
TC, including the four major regulatory options defined below. The approach for
determining DAFs varied in many of these options, as did risk levels used to select the
RSDs for carcinogens, and the number of constituents subject to evaluation. For example,
the Agency developed a series of options in which various generic DAFs were used, two
different sets of constituents were included (the proposed constituents and a second list of
additional constituents), and the risk levels for carcinogens were varied. Other series of
options included holding the carcinogen risk levels and constituents constant and varying
the value of the cumulative frequency of DAF from the ground-water transport model.
This RIA examines four regulatory options:
DAF 33,
DAF 100,
DAF 250, and
DAF 500.
The following factors are held constant across all regulatory options examined in this RIA:
¦ The list of additional regulated constituents comprises 25 organic
constituents (listed in Exhibit 1-1);
• RSDs a/e set at 10"5 risk level:

-------
1-7
EXHIBIT 1-1
CONSTITUENTS REGULATED UNDER THE FOUR REGULATORY OPTIONS
AND CORRESPONDING CTRLS1
Reaulated Constituent
CTRL fma/IV
benzene
.005
carbon tetrachloride
.005
chlordane
.0003
chlorobenzene
1
chloroform
.06
1,4-dichlorobenzene
.075
1,2-dichloroethane
.005
1,1-dichloroethyIene
.007
2,4-dinitrotoluene
.0005
heptachlor
.00008
hexachloro-1,3-butadiene
.005
hexachlorobenzene
.0002
hexachloroethane
.03
m-cresot
2
methyl ethyl ketone
2
nitrobenzene
.02
o-cresol
2
p-cresol
2
pentachlorophenol
1
pyridine
.04
tetrachloroethylene
.007
trichloroethylene
.005
2,4,5-trichlorophenol
4
2,4,6-trichlorophenol
.02
vinyl chloride
.002
1	Regulatory levels for the 14 existing EPTC constituents were assumed to stay the same.
Thus, only the 25 organic constituents to be added were analyzed,
2	Regulatory Level = CTRL x DAF.

-------
1-8
• Quantitation Limits supercede calculated Regulatory Levels if the
Quantitation Limits are higher; and
- CTRLs are not apportioned among other sources of exposure.
The general equation for constituent regulatory levels for a regulatory option is RL =
(CTRL) X DAF. Therefore, for carcinogens, the RLs for the four options are the MCLs or
DWSs (if either is established), or the RSD at 10"5, multiplied by the appropriate DAFs, For
non-carcinogens, the RLs are the MCLs or DWSs (again, if either is established), or the RfD,
multiplied by the DAFs. Exhibit 1-1 lists the constituents included in the analysis of these
options and their corresponding CTRLs.
The regulatory option selected for the final TC rule is the DAF 100 option examined
in this RIA. Twenty-five additional organic constituents will be regulated, with the RL for
each constituent equal to the CTRL for that constituent multiplied by 100. CRTLs are,
where available, DWSs or MCLs. Where no DWSs or MCLs are available, CTRLs are RFDs
for non-carcinogens. CRTLs are not apportioned to account for possible alternative routes
of exposure. Regulatory levels for the existing EP constituents are not changing with the
final TC rule. The final TC replaces the EP with the TCLP as the specified test method for
the Toxicity Characteristic.
1.4 REGULATORY ANALYSIS REQUIREMENTS
1.4.1	"Major Rule* Requirement
Executive Order 12291 requires EPA to conduct a complete RIA for all rules that meet
the definition of a "major rule." A major rule is one likely to result in (1) an annual impact
on the economy of $100 million or more, (2) a major increase in costs or prices for
consumers, individual industries, Federal, State, or local government agencies, or
geographic regions, or (3) significant adverse impacts on competition, unemployment,
investment, productivity, innovation, or the ability of United States-based enterprises to
compete in domestic or export markets. The RIA requirement was designed so that
Agencies would conduct detailed assessments of the costs and benefits of any rule that
w: ild have a significant impact on the regulated community. This detailed assessment
wc . d serve as an aid in assessing tradeoffs among regulatory options.
Preliminaiy analysis by the Agency indicated that the final TC Rule was a major rule.
Thus, in fulfillment of the Executive Order, the Agency prepared this RIA to compare the
costs and benefits of the regulatory options outlined above.
1.4.2	Regulatory Flexibility Act
The Regulatory Flexibility Act requires the Agency to assess the impacts of its actions
on small entities. The Act requires the Agency to publish for comment an assessment of
the impacts on small entities in the regulated community unless the Administrator certifies
that the rule will not have a significant impact on a substantial number of small entities.
The analysis of impacts on small entities is discussed in Chapter 4.

-------
1-9
1.5 ORGANIZATION OF THE RIA
Chapters 2 through 5 present a detailed description of the methodologies and results
of the RIA for the four major regulatory options. Chapter 2 describes how wastes and
facilities were characterized. Chapter 3 presents estimates of the costs faced by generators
and handlers of TC wastes. Chapter 4 summarizes how these costs of the regulatory
options translate into impacts on the universe of affected facilities. Chapter S describes the
models used to estimate the benefits of the regulatory options and the results of the
benefits analysis.

-------
Chapter 2 explains the characterization of affected wastes and facilities that served as
a basis for estimating costs, economic impacts, and benefits of the TC rule. The chapter
begins by describing the data that the Agency used to identify industries generating wastes
with the potential to exhibit the TC and to characterize these wastes. Next, the
methodology for estimating quantities of wastes that will be newly hazardous under the TC
is presented. The assumptions and calculations used to "estimate numbers of facilities and
patterns of waste generation at these facilities follow. Results are presented in each of the
sections on affected wastes and affected facilities, after methodologies and assumptions are
explained. Next, limitations of the characterization of affected wastes and facilities are
discussed. The section addressing limitations also discusses sensitivity analyses
conducted. The last section of this chapter discusses estimates of the potential ranges of
affected wastes and facilities. The methodology for characterizing wastes and affected
facilities is summarized graphically in Exhibit 2-1.
2.1 WASTE CHARACTERIZATION
. Characterization of the existing potentially affected universe (i.e., the pre-regulatory cr
baseline scenario) for this analysis consisted of three main elements; identifying industries
to be examined, accumulating information on the wastes generated by these industries, and
identifying current management practices for the wastes.
2.1.1 Industries Examined and Sources of Information
Under EPA direction, a series of industry studies was prepared for use in the TC RIA.
The preliminary studies examined a large number of industries, with emphasis on identifying
whether or not TC constituents would be likely to be present in industry wastes. Based on
the preliminary studies, EPA completed detailed profiles-for 15 major industrial sectors.
These 15 sectors were identified as the industries most likely to generate large quantities of
waste potentially affected by the TC. Exhibit 2-2 lists the industrial sectors for which
detailed profiles ware completed. Report titles for these detailed profiles are listed in the
References sactton.
This RIA presents estimates of the costs, economic impacts, and benefits attributable
to the TC tor al industrial sectors for which detailed profiles were completed except three.
Data in the industry profile for Printing and Publishing indicated that wastes generated by
the industry did not contain TC constituents above regulatory levels under consideration.
Thus, the Printing and Publishing sector was dropped from the analysis because data
indicated that the industry would not experience significant TC impacts. Large volume
wastestreams in the Electrical Services industry were not included in the analysis because
they are currently exempt from Subtitle C regulation. Fossil fuel combustion wastes were
exempted from RCRA Subtitle C pending completion of a Report to Congress on these
wastes and a regulatoiy determination as to whether to regulate these wastes under
Subtitle C of RCRA. There was insufficient information for detailed quantitative analysis for
the third sector, Machinery and Mechanical Products. Also, the limited information that was

-------
Exhibit 2-1
Characterizing Wastes and Affected Facilities
Identify potentially
affected industries.
~
Characterize
wastestreams in
potentially affected
industries.
I
Percentage exhibiting
TC is applied to both
wastestream quantity
	 anil the number of facilities
generating the wastestream.
This yields affected waste
quantity and affected number
of facilities.
v
Calculate quantity of
waste per facility
exhibiting the TC, for
both large and small
affected facilities.
+
Account for
overlap of
wastes at single
facilities by creating
model facilities
based on two
scenarios.
Estimate portion
of each wastestream
exhibiting TC.
Estimate number
of facilities
generating affected
wastes.

-------
2-3
EXHIBIT 2-2
EPA INDUSTRY PROFILES COMPLETED FOR USE IN TC ANALYSIS
Standard Industrial
Industry	Classification a/
Textile Mills*
22
Lumber and Wood Products*
2421. 2499
Pulp and Paper*
261, 262, 263, 266
Printing and Publishing
27
Plastics Materials and Resins*
2821
Synthetic Rubber*
2822
Synthetic Fibers*
2823.2824
Pharmaceuticals*
283
Organic Chemicals*
2865, 2869
Petroleum Refining*
2911
Rubber and Miscellaneous Plastics Products*
30
Machinery and Mechanical Products
34 through 39
Pipelines, except Natural Gas*
461
Electrical Sen/ices
4911
Wholesale Petroleum Marketing"
517
a/ SICs listed are those defining the group considered in this analysis. SICs given at
the two-digit or three-digit SIC level indicate that the analysis applies to all four-digit SICs
contained within the broader category.
* Included in detailed quantitative analysis for the RIA. SIC 2992 (Miscellaneous
Petroleum and Coal Products) was also included in detailed analysis for the RIA, using data
from Composition and Management of Used Oil Generated In the United States.

-------
2-4
available for Machinery and Mechanical Products indicated that wastestreams containing TC
constituents also contain high levels of metals and, thus, may already be hazardous under
the existing Extraction Procedure Toxicity Characteristic (EPTC).
For the industry profiles, information was available for different industries at different
SIC levels (two-digit, three-digit, or four-digit). Data were used in the analysis at the most
specific SIC level available. Throughout the rest of this RIA, in tables and text, industries
may be referred to by either name or SIC. Exhibit 2-3 lists all SICs and corresponding
industry names used in the RIA, for reference when necessary.
In addition to relying on wastestream characterization data in the industrial profiles for
12 major industrial sectors, EPA considered the possibility that one wastestream that occurs
in many industries - used oil - might exhibit the TC. The Agency extracted data from its
1984 report Composition and Management of Used Oil Generated in the United States to
analyze used oil and the used oil collection and distribution industry. (Used oil collectors
and distributors are included in SIC 2992.)
2.1.2 Types of Wastestreams Included and Characterization Data
The majority of wastestreams examined for this analysis are wastewaters and
associated wastewater treatment sludges. Virtually all of these wastewaters, according to
available information, are discharged, after treatment in wastewater treatment systems, to
surface waters under National Pollutant Discharge Elimination System (NPDES) permits or to
Publicly Owned Treatments Works (POTWs). Sludges originate in wastewater treatment
units, mainly tanks and surface impoundments. Treatment processes that occur in these
units include sedimentation, coagulation and flocculation, flotation, activated sludge
treatment, and aeration. As a wastewater stream passes through different steps in a
treatment train, different sludges are formed depending on the treatment taking place. :n
addition to analyzing wastewaters and wastewater treatment sludges, EPA also analyzec
some solid process residuals and organic liquids.
The following wastestream characterization data elements were used in the analysis
•	Waste type as either aqueous liquid, sludge/slurry, solid residual, or organic
liquid;
« Total quantity of waste generated in metric tons per year (MT/yr);
•	Maximum and minimum concentration for each TC constituent present in :re
wastestream;
¦	Estimated concentration distribution (normal, lognormal, or uniform) between
the maximum and minimum concentrations; and
¦	Number of facilities generating each wastestream.
It was in some cases necessary to use best engineering judgement to fill in data gaps, m
oarticular, best engineering judgement was used to classify wastes into waste types ana to
assume concentration distributions for some wastestreams.

-------
2-5
EXHIBIT 2-3
STANDARD INDUSTRIAL CLASSIFICATIONS (SICs)
AND CORRESPONDING INDUSTRY NAMES
SIC 3		Industry	
2231	Wool Dyeing and Finishing
225X	Hosiery and Knit Fabric Finishing
2S6X	Woven Fabric Finishing
227X	Carpet Finishing
2299	Wool Scouring
229X	Miscellaneous Textile Manufacturing
22XX	Low Water Use Processing Mills
22YY	Stock and Yarn Processing, Dyeing, and Finishing
2421	Sawmill and Planing Mill and Finishing
2499	Wood Products, Not Elsewhere Classified
26XX	Pulp and Paper Mills
2821	Plastics Materials and Resins
2822	Synthetic Rubber
2823	Synthetic Fibers, Ceilulosic
2824	Synthetic Fibers, Non-Cellulosic
283X	Pharmaceuticals
286X	Organic Chemicals
2911	Petroleum Refining
2992	Miscellaneous Petroleum and Coal Products
3011	Tires and Inner Tubes
3021	Rubber and Plastics Footwear
3031	Reclaimed Rubber
3041	Rubber and Plastics Hose and Belting
3069	Fabricated Rubber Products, Not Elsewhere Classified
3079	Miscellaneous Plastics Products
461	Petroleum Pipelines
517	Wholesale Petroleum Marketing
* Letters (X or Y) indicate that the grouping does not include all four-digit SICs
within the two-digit or three-digit SIC.

-------
2-6
2.1.3 Baseline Management Practices
The Agency used information from its Screening Survey of Industrial Subtitle D
Establishments to characterize baseline (i.e., pre-TC) management practices for wastes
under consideration for this analysis. EPA did not have facility-specific information in its
industry profiles, but rather had characterization of aggregate wastestreams. each generated
by a number of individual facilities. The Agency estimated baseline management practices
for wastestreams via several steps. EPA first identified likely baseline management
practices for each of the four types of wastes included in the analysis: wastewaters,
sludge/slurries, solid residuals, and organic liquids. The Agency then looked to the
Screening Survey for industry-specific and facility size-specific information about the use of
the likely management practices. (Small and large facilities were defined by a 50 employee
cutoff.) The Screening Survey provided industry-specific percentages of facilities using each
management practice for Subtitle D wastes; EPA applied these percentages to the facilities
generating potential TC wastes in order to assign baseline management practices.
Since virtually all wastewaters in this analysis are discharged to surface waters under
NPDES permits or to POTWs after treatment in wastewater treatment systems, it was
necessary to identify management units used in the wastewater treatment systems in order
to characterize the baseline. The Agency used information from the Screening Survey to
estimate the number of facilities (large and small) in each industry that manage wastewaters
in surface impoundments, since wastes managed in these units would potentially be
affected by the TC. Other facilities were assumed to be using baseline management
practices already compliant with Subtitle C; thus these facilities would not have to change
management practices and would not incur incremental waste management costs as a
result of the TC rule. The most notable management practice for wastewaters tnat would
not require change after promulgation of the TC is treatment in tanks prior to discharge
regulated under the Clean Water Act. These tanks are exempt from Subtitle C permitting
requirements (40 CFR 264.1 (g)(6)). Further, since wastewaters managed in exempt tanks
are not considered to be regulated under a "substantive" requirement, they need not be
counted toward generator quantity thresholds. Thus, facilities using exempt tanks are not
subject to generator requirements if there are no other regulated units (e.g., down-line
surface impoundments) or regulated activities (e.g., storage) in the treatment train. Other
baseline wastewater management practices which could continue under Subtitle C include
direct discharge without treatment (compliant with an NPDES permit) and recycling.
•
EPA identified three likely baseline management practices for sludge/slurry
wastestreams; on-site landfilling, off-site landfilling, and on-site land treatment for those
wastes suitable for land treatment. The Screening Survey contained industry-specific
percentages of facilities (large and small) managing wastes on-site in landfills and by land
application. These percentages were applied to facilities generating potential TC wastes in
order to assign baseline management practices. Land application percentages were
applied only for those facilities generating wastes that are physically and chemically suitable
for land treatment. The percentage of facilities using on-site landfills or land treatment was
less than 100 percent for all industries. For the percentage not using on-site landfills or
land treatment, EPA assumed off-site landfilling as the baseline practice.
For solid residuals, EPA divided facilities generating the wastes into two baseline
management practice groups. Screening Survey data provided percentages of facilities

-------
2-7
using on-site landfills; the Agency assumed the other facilities send waste to off-site sanitary
landfills.
Using data from the Office of Solid Waste Industry Studies Data Base (ISDB), the
Agency identified three predominant baseline management practices for organic liquids:
management in tanks followed by discharge under the Clean Water Act, reuse or recovery,
and incineration or burning in boilers. In most cases, these management practices could
continue under Subtitle C without substantial additional cost. Therefore, these wastes were
not included in subsequent analysis.
2.1.4 Used Oil
EPA addressed the impacts of the TC on used oil separately from other wastes for
several reasons. First, used oil is generated across a wide variety of industrial sectors.
Second, assessing costs associated with used oil management is complicated because,
unlike other wastes, it has economic value and can be sold in intermediate or end-use
markets. Also, data on used oil are quite limited. Finally, it is difficult to accurately
estimate quantities of used oil that may exhibit the TC because actual TCLP results for used
oil are sample-specific and more difficult to predict than those for other non-oily wastes.
To assess the impacts of the TC on used oil, EPA first determined the quantity of
used oil potentially affected. Data on used oil quantities, characterization, and management
practices came primarily from Composition and Management of Used Oil Generated in the
United States. Used oil that was already hazardous by characteristic (ignitability or EP
toxicity) or that was recycled or burned as fuel was excluded from the analysis, since it
would not be affected by the TC.
Test data were not available to determine whether used oil would exhibit the TC.
Used oil may not fail the TCLP because of its oily consistency. In order to develop worst-
case estimates of quantities of used oil that might exhibit the TC, EPA assumed that used
oil would pass through the TCLP filter and the quantity of used oil that will exhibit the TC
was estimated by the same method as for other wastes (See Section 2.2.1). Resulting
estimates are presented in Section 2.2.3. Detailed discussion of the used oil analysis is
included in Appendix A.
2.2 QUANTITIES OF WASTE EXHIBITING THE TC
The Agency estimated, based on constituent concentration data, the quantity of each
wastestream characterized for the analysis that would exhibit the TC. Determining what
wastes will be brought into the hazardous waste system serves as the starting point for
estimates of how many facilities will be affected by the TC rule, what cost these facilities
and society will incur, and what benefits will accrue due to TC regulation.
2.2.1 Methodology
To predict the quantity of each wastestream that would exhibit the TC, the Agency
first established regulatory level options for constituents under each regulatory option.1 As
1 Regulatory options are explained in Chapter 1.

-------
2-8
proposed in the June 13, 1986 proposed rule, the quantitation limits for constituents were
used instead of the calculated regulatory levels wherever the quantitation limit exceeded the
calculated regulatory level. Based on these regulatory levels, the Agency identified a critical
concentration for each constituent above which the waste would exhibit the TC. For
wastewaters and organic liquids, this concentration equaled the regulatory level; for non-
liquids, the Organic Leaching Model (OLM) was used to convert the regulatory level to the
corresponding waste concentration. The OLM was developed by the Agency to predict the
leachate concentrations of organic chemicals. It predicts leachate concentrations from total
waste constituent concentrations using a concentration and solubility-based logarithmic
equation (51 Federal Register 41084). The equation can be used in reverse to convert a
leachate concentration to a corresponding waste concentration; this was done to convert
the TC regulatory levels to coiresponding waste concentrations.
Using a computerized database, EPA compared the concentration range for each
constituent in every wastestream with the critical concentration for that constituent.
Constituent concentration distributions were either uniform, normal, or lognormal. Based on
distribution-specific statistical calculations for each constituent, the Agency determined what
portion of the wastestream would exhibit the TC solely by virtue of the presence of that
constituent. The constituent that resulted in the largest percentage exhibiting the TC was
designated the volume-driving constituent. Multiplying the percentage of the wastestream
exhibiting the TC by the total quantity of the wastestream yielded the estimated quantity
that exhibits the TC. By using this procedure, EPA assumed direct correlation of
constituent concentrations; the highest concentrations of one constituent are present along
with the highest concentrations of other constituents in the wastestream. The Agency
tested the sensitivity of results to the direct correlation assumption by adding the
percentages of waste exhibiting the TC for each constituent, instead of picking a driving
constituent. This sensitivity analysis, discussed further in section 2.4. assumed a perfect
inverse correlation.
The Agency used the "driving" constituent concept because, in the absence of data
from specific facilities or concentration correlation data, this approach offered the best
methodology for estimating what wastes would exhibit the TC. It is worth noting that the
driving constituent might "mask" the presence of other TC constituents in the wastestreams.
An additional step was required for wastewaters to determine affected quantity. As
mentioned in Section 2.1.3, only some portion of facilities in each industry manage their
non-hazardoua wastewaters in surface impoundments. Other facilities use management
practices that would be compliant with RCRA Subtitle C regulations, even if the wastewaters
managed were designated hazardous under the TC. EPA multiplied Screening Survey
percentages of facilities managing wastes in surface impoundments by the quantities
exhibiting the TC to determine the wastewater quantities actually affected by the rule. EPA
performed sensitivity analysis on the use of the Screening Survey percentages by
alternatively assuming aH wastewaters are managed in surface impoundments. This
provided an upper bound for the estimated quantity of affected wastewaters (see Section
2.4).
2.2.2 Results
Exhibit 2-4 summarizes quantities of waste that would be affected by the TC for the
four regulatory options being considered. Total affected waste quantities range from 660

-------
2-9
EXHIBIT 2-4
TOTAL QUANTITIES OF WAST! AFFECTED BY THE TC RULE (MT/YEAR)
Regulatory Option
Wastewater
Quantity
Non-Wastewater
Quantity
DAF 33
DAF 100
DAF 250
DAF 500
840,000,000
730,000,000
700,000,000
660,000,000
3,100,000
1,800,000
710,000
510,000

-------
2-10
million metric tons per year (MMT/yr) at DAF 500 to 840 MMT/yr at DAF 33, an increase of
almost 30 percent from the least stringent option to the most stringent option. Between
DAF 100 and DAF 250, wastewater quantities affected drop by 30 MMT (about 4 percent).
Affected non-wastewaters quantities differ more significantly than affected wastewaters
quantities between OAF 250 and 100: affected non-wastewater quantities more than double
from 710,000 MT/yr at OAF 250 to 1.8 MMT/yr at DAF 100,
For all four options, wastewaters account for over 99 percent of the total affected
waste quantity. It is important to note that, while large quantities of wastewaters may be
affected by the TC, these wastewater quantities will not necessarily be brought into the
Subtitle C waste management system. This RIA predicts, based on cost analysis, that
handlers of wastewaters affected by the TC will choose to switch from management in
surface impoundments to management in exempt tanks. Thus, these wastewaters will be
affected because a new management practice will be required; however, for practical
purposes, they will not constitute new hazardous wastes.
Exhibits 2-5 through 2-8 show quantities of affected waste by industry for each
regulatory option. The exhibits also show the estimated split of waste generation between
large and small facilities. The assignment of affected waste quantities to generating
facilities is discussed in section 2.3. The discussion that follows will focus first on
wastewaters and then on non-wastewaters. Discussion of total waste quantity would
correspond to that for wastewaters since wastewaters constitute over 99 percent of affected
waste volume.
The Petroleum Refining Industry generates the largest affected wastewater quantity
under all options. Wastewater from the Petroleum Refining industry constitutes over 60
percent of the total affected wastewater quantity for the DAF 33 option and about 70
percent of the total affected wastewater quantity for the other three options. The
Petroleum Refining wastewater quantity affected is about 500 MMT/yr for all options
(dropping to 470 MMT/yr at DAF 500). The driving constituent for Petroleum Refining
wastewater is benzene. Concentration data used in the TC RIA database corresponded to
the point in the treatment train after API separation and/or DAF flotation.
The Pulp and Paper industry generates the second largest quantity of affected
wastewaters (75 MMT/yr, about 10 percent of total) under the DAF 33 option. Under this
most stringent option, TC wastewaters are predicted to be generated by four sectors of the
industry: papergrade sulfite, de-inking, bleached kraft, and alkaline fine. However, affected
Pulp and Papft,wastewater quantities drop to 3.5 MMT/yr at DAF 100 and to zero by DAF
250. Chloroform and trichloroethylene are driving constituents in Pulp and Paper
wastewaters.
Two industries, Organic Chemicals and Synthetic Fibers, each generate about 10
percent of affected wastewaters under all regulatory options. Organic Chemicals generates
the second largest quantity of affected wastewaters (62 MMT/yr) under the DAF 100 option
and Synthetic Fibers generates the second largest affected wastewater quantity (61 MMT/yr)
under the DAF 250 option. Driving constituents in Organic Chemicals wastewaters include
benzene, chloroform, carbon tetrachloride, vinyl chloride, methyl ethyl ketone, and 2,4-
dinitrotoluene. Driving constituents in Synthetic Fibers wastewaters are benzene for the
celluiosic sector and vinyl chloride for the non-cellulosic sector. Other industries that

-------
EXHIBIT 2-6

QUANTITIES HANDLED BY INDUSTRIES INCURRING COSTS (DAF 33)
SIC**
AFFECTED WASTEWATER QUANTITY

AFFECTED NON-WASTEWATER QUANTITY


(MT/YR)



{MT/YR)


URGE
SMALL
TOTAL*

LARGE
SMALL
TOTAL*
2231
630.000
24,000
650,000

390
0
390
225X
21,000,000
380,000
21,000,000

27,000
3,900
31,000
226X
1,700,000
45,000
1,700,000

48,000
2,900
51,000'
229X
140,000
12,000
150,000

0
0
0
22YY
5,000.000
33,000
S,000,000

530
0
530
2421
1,300
240
1,500

0
0
0
26XX
75.000,000
120,000
75,000,000

630,000
4,600
630,000
2821
26,000,000
680,000
27,000,000

28,000
2,900
31,000
2822
35,000,000
1,800,000
37,000,000

91,000
7,800
99,000
2823
34,000,000
0
34,000,000

130,000
0
130,000
2824
27,000,000
67,000
27,000,000

12,000
34
12,000
283X
31,000,000
660,000
32,000,000

93,000
5,000
98,000
286
72,000,000
2,200,000
74,000,000

140,000
7,100
150,000
2911
500,000,000
0
500,000,000

1,600,000
0
1,600,000
2992
0
0
0

23,000
23,000
46,000
3031
0
0
0

30
0
30
461
900,000
190,000
1,100,000

12,000
6,300
18,000
517
2,800,000
4,600,000
7,400,000

32,000
140,000
170,000
TOTALS*
830,000,000
11,000,000
840,000,000

2,900,000
200,000
3,100,000





.... 	—	
		...... 		
. .... 		
•TOTALS MAY NOT ADD DUE TO ROUNDING
• -SEE EXHIBIT 2-3 FOH SIC CODES COMRI SI'ONDINO IO I*111 I.HCNI INDUS fHlliS

-------
EXHIBIT 2-8
QUANTITIES HANDLED BY INDUSTRIES INCURRING COST (DAF 100)
SIC*
AFFECTED WASTEWATER QUANTITY

AFFECTED NON-WASTEWATER QUANTITY


(MT/YR)



(MT/YR)


LARGE
SMALL
TOTAL*

LARGE
SMALL
TOTAL*
2231
0
0
0

210
0
210,
225X
8,100,000
140,000
8,200,000

9,100
1,300
10,000
226X
1,900,000
45.000
1.900,000

32.000
2,000
34,000
2421
1,300
240
1.500

0
0
0
26XX
3,300,000
210,000
3,500,000

300,000
2,100
300,000
2821
21,000.000
680,000
22,000,000

27,000
2,800
30,000
2822
34,000,000
1.700,000
36,000.000

91.000
6,600
98,000
2823
.34,000,000
0
34,000.000

130,000
0
130,000
2824
27,000,000
67,000
27,000,000

12,000
34
12,000
283X
26,000.000
550.000
27,000.000

77,000
4.100
81,000
286
60,000,000
1.800,000
62,000,000

110.000
5.800
120.000
2911
500,000,000
0
500,000,000

800,000
0
800.000
2992
0
0
0

15,000
15,000
30,000
461
900,000
190,000
1,100.000

11,000
5.300
16.000
517
2,800,000
4.600,000
7.400,000

27,000
110.000
140.000
TOTALS*
720,000,000
10,000,000
730,000.000

1,600,000
160.000
1.800,000
•TOTALS MAY NOT ADD DUE TO ROUNDING
"SEE EXHIBIT 2-3 FOR SIC CODES CORRESPONDING TO DIFFERENT INDUSTRIES

-------
EXHIBIT 2-7

quantities HANDLED BY INDUSTRIES INCURRING COSTS (DAF 250)
«
•
o
CO
AFFECTED WASTEWATER QUANTITY

AFFECTED NON-WASTEWATER QUANTITY


(MT/YR)



(MT/YR)


URGE
SMALL
TOTAL*

URGE
SMALL
TOTAL*
2231
0
0
0

44
0
44
226X
1,300,000
41,000
1,300,000

13,000
810
14,00b
2421
1.300
240
1,500

0
0
0
26XX
0
0
0

17,000
120
17,000
2821
14,000,000
470,000
14,000,000

16,000
1,600
18,000
2822
35,000,000
1,700,000
37,000,000

91,000
6,600
98,000
2823
34,000,000
0
34,000,000

130,000
0
130,000
2824
27,000,000
67,000
27,000,000

12,000
34
12,000
283X
26,000,000
550,000
27,000,000

59,000
3,100
62,000
286
53,000,000
1,500,000
55,000,000

100,000
5,100
110,000
2911
500,000,000
0
500,000,000

70,000
0
70,000
2992
0
0
0

7,900
8,000
16,000
461
900,000
190,000
1,100,000

10,000
5,100
15,000
517
2,800,000
4,600,000
7,400,000

26,000
110,000
140,000
totals-
690,000,000
9,100,000
700,000,000

550,000
140,000
700,000
•TOTALS MAY NOT ADO DUE TO ROUNDING
* "SEE EXHIBIT 2-3 FOR SIC CODES CORRESPONDING TO DIFFERENT INDUSTRIES

-------
EXHIBIT 2-8

QUANTITIES HANDLED BY INDUSTRIES INCURRING COSTS (DAF 500)
SIC**
AFFECTED WASTEWATER QUANTITY

AFFECTED NON-WASTEWATER QUANTITY


(MT/YR)



(MT/YR)


URGE
SMALL
TOTAL*

LARGE
SMALL
TOTAL*
226X
0
34,000
34,000

0
0
0
2421
1,300
230
1,500

0
0
0'
26XX
0
0
0

3,100
22
3,100
2821
13,000,000
350,000
13,000,000

12,000
1,300
13,000
2822
33,000,000
1,600,000
35,000,000

90,000
6,600
97,000
2823
33,000,000
0
33,000,000

130,000
0
130,000
2824
27,000,000
66,000
27,000,000

11,000
34
11,000
283X
23,000,000
480,000
23,000,000

56,000
2,900
59,000
286
52,000,000
1,400,000
54,000,000

77,000
3,900
81,000
2911
470,000,000
0
470,000,000

30,000
0
30,000
2992
0
0
0

5,700
5.900
12,000
461
890,000
190,000
1,100,000

4,600
2,200
6,800
517
2,800,000
4,600,000
7,400,000

12,000
50,000
62,000
TOTALS*
650,000,000
8,800,000
660,000,000

440,000
73,000
510,000
•TOTALS MAY NOT ADD DUE TO ROUNDING
* 'SEE EXHIBIT 2-3 FOR SIC CODES CORRESPONDING TO DIFFERENT INDUSTRIES

-------
2-15
generate significant quantities of wastewater under the DAF 100 and DAF 250 options are
Synthetic Rubber, Plastics and Resins, and Pharmaceuticals.
Petroleum Refining generates the largest quantity of affected non-wastewaters under
the DAF 33 option {1.6 MMT/yr, about 50 percent of total) and DAF 100 option (800,000
MT/yr, about 40 percent of total). Petroleum Refining affected non-wastewaters drop to
70,000 MT/yr at DAF 250 (about 10 percent of total) and to 30,000 MT/yr at DAF 500 (about
6 percent of total). Petroleum Refining non-wastewater wastestreams that exhibit the TC at
DAF 100 include treating clay from extraction/isomerization, treatment clay from clay filtering,
crude storage tank sludge, unleaded storage tank sludge, and primary treatment sludges.
Primary treatment sludges are the largest quantity affected non-wastewater wastestream of
all these; about 700,000 MT/yr exhibit the TC at DAF 100. All of the Petroleum Refining
wastestreams mentioned are also affected under the DAF 250 option except treatment clay
from clay filtering and unleaded storage tank sludge. The driving constituent for all
Petroleum Refining wastestreams is benzene.
The Synthetic Fibers industry generates the largest quantity of affected non-
wastewaters at the DAF 250 and DAF 500 options. The affected non-wastewater quantity
for this industry is fairly constant across all options at around 140,000 MT/yr. About
130,000 MT/yr of this quantity comprises wastewater treatment sludges generated by the
cellulosic sector. The driving constituent for sludges from the cellulosic sector is benzene.
Sludges from the Pulp and Paper industry constitute about 20 percent of affected
non-wastewater quantity under the DAF 33 and DAF 100 options. About 630,000 MT/yr of
affected wastewater treatment sludges are generated by the Pulp and Paper industry under
the DAF 33 option, approximately 300,000 MT/yr under the DAF 100 option, 17,000 MT/yr
under the DAF 250 option, and only 3,100 under the DAF 500 option. Chloroform is the
driving constituent in sludges from the Pulp and Paper industry.
Other industries that generate significant quantities of affected non-wastewaters under
the DAF 100 and 250 options are Wholesale Petroleum Marketing and Organic Chemicals.
About 140,000 MT/yr of Wholesale Petroleum Marketing non-wastewaters are affected under
both options. The affected wastestreams are crude oil tank cleaning sludge and unleaded
gasoline tank cleaning sludge; the driving constituent is benzene. As for Organic
Chemicals non-wastewaters, 120,000 MT/yr are affected under the DAF 100 option and
110,000 under the DAF 250 option. Driving constituents in Organic Chemicals non-
wastewaters include benzene, vinyl chloride, carbon tetrachloride, methyl ethyl ketone,
chloroform, and 2,4-dinitrotoluene.
Exhibits 2-9 and 2-10 present the specific wastestreams that drive the analysis of
non-wastewater quantities affected. Non-wastewaters are presented because, as will be
discussed in Chapter 3, non-wastewaters drive costs. Exhibit 2-9 shows the five largest-
quantity affected non-wastewaters at the most stringent option and the quantities of these
wastestreams that exhibit the TC under the other options. As can be seen in the exhibit, all
five largest-quantity affected non-wastewaters under the DAF 33 option no longer exhibit the
TC under the DAF 500 option. Exhibit 2-10 presents the five largest-quantity affected
wastestreams under the DAF 100 option and the quantities of these five wastestreams that
exhibit the TC under the DAF 250 and 500 options. The affected quantity of primary
treatment sludges from Petroleum Refining decreases significantly from DAF 100 to DAF

-------
EXHIBIT 2-9
DRIVING NON-WASTEWATER WASTESTREAMS FOR DAF 33: QUANTITIES AFFECTED (MT/YR)
UNDER OTHER REGULATORY OPTIONS
REGULATORY
OPTION
(DAF)
SIC 2911
PRIMARY TREATMENT
SLUDGES
SIC 2911
SECONDARY TREATMENT
SLUDGES
SIC 26XX
SEDIMENTATION/OXIDATION
SLUDGE, BLEACHED
KRAFT
SIC 26XX
SEDIMENTATION/OXIDATION
SLUDGE, MISCELLANEOUS
INTEGRATED
SIC 26XX
SEDIMENTATION/OXIDATION
SLUDGE, ALKALINE
FINE
33
770,000
690,000
210,000
170,000
140,000
100
720,000
0
180,000
0
100,000
250
1,200
0
0
0
0
500
0
0
0
0
0

-------
EXHIBIT 2-10
DRIVING NON-WASTEWATER WASTESTREAMS FOR DAF100: QUANTITIES AFFECTED (MT/YR)
UNDER OTHER REGULATORY OPTIONS
REGULATORY
OPTION
(OAF)
SIC 2911
PRIMARY TREATMENT
SLUDGES
SIC 26XX
SEDIMENTATI ON/OXIDATION
SLUDGE. BLEACHED
KRAFT
SIC 26XX
SEDIMENTATION/OXIDATION
SLUDGE, ALKALINE
FINE
SIC 517
CRUDE OIL TANK
CLEANING SLUDGE
SIC 2823
SEDIMENTATION SLUDGE,
CELLULOSIC MAN-MADE
FIBERS
100
720,000
180,000
100,000
76,000
67,000
2S0
1,200
0
0
71,000
67,000
500
0
0
0
0
67,000

-------
2-18
250, and sludges fromthe Pulp and Paper industry drop out of regulation between DAF
100 and DAF 250.
Thirteen constituents appear as volume-driving constituents for the most stringent
regulatory option (DAF 33): benzene, chloroform, tetrachloroethyiene, trichloroethyiene.
methyl ethyl ketone, vinyl chloride, chlorobenzene, nitrobenzene, pentachlorophenol, 2.4-
dinitrotoluene, carbon tetrachloride, heptachlor, and 2,4,6-trichIorophenol. All except the last
one also appear as volume-driving constituents in the other three regulatory options.
Twelve regulated constituents never appear as volume-drivers: chlordane; o-cresol; m-
cresol; p-cresol; 1,4-dichlorobenzene; 1,2-dichloroethane; 1,1-dichloroethylene;
hexachlorobenzene; hexachlorobutadiene; hexachloroethane; pyridine; and 2,4,5-
trichlorophenol. These constituents did not appear as driving constituents because they
were either 1) present in levels below regulatory levels or 2) present in wastestreams for
which another constituent was the driving constituent. Benzene is the driving constituent
for over 60 percent of affected waste under the DAF 100 option. Other volume-driving
constituents for the DAF 100 option include chloroform (25 percent), vinyl chloride (17
percent), and trichloroethyiene (5 percent).
2.2.3 Used Oil
As discussed above, in order to arrive at an upper bound estimate of used oil
exhibiting the TC, EPA assumed that used oil would completely penetrate the filter in the
TCLP. It is difficult to accurately predict actual TCLP results for oily wastes. The Agency
estimates that three categories of used oil could be affected by the TC: oil used for road
oiling, dumped used oil, and used oil disposed of by landfilling or incineration. The
potential affected quantities for these three types are 232,000 MT/year, 374,000 MT/year,
and 405,000 MT/year, respectively.
2.3 NUMBER OF FACILITIES AFFECTED
2.3.1 Methodology
The number of facilities generating each wastestream examined in the analysis is a
subset of the total number of establishments in an industry because some establishments in
an industry may not generate the waste. Characterization data provided numbers of
facilities generating each wastestream included in this analysis. For the RIA, EPA divided
the number of facilities generating each wastestream into large and small facility size
categories, using a cutoff of 50 employees to separate large from small facilities. The
proportion of large and small facilities within an SIC was determined using 1982 Census of
Manufactures data. Facilities generating each wastestream in the database are assumed to
be distributed between large and small facilities in proportion to the split between large and
small facilities for the SIC as a whole.
The Agency then estimated the total quantity of each wastestream generated by firms
in each size category. EPA assumed that within each size category, ail facilities generate
the same quantity of waste. Next, the Agency assumed that waste generation is
proportional to value of shipments. Census of Manufactures data on value of shipments by
size category was used to estimate the percentage of the total quantity of waste generated

-------
2-19
by facilities in each size category.2 Again, EPA assumed that the percentages for the entire
SIC could bo applied to the subset of facilities generating wastes in the database. EPA
tested the sensitivity of assuming that waste generation by large and small facilities is
proportional to value of shipments by alternatively assuming waste quantities were
distributed equally between large and small facilities (i.e., 50 percent generated by large
facilities and 50 percent generated by small facilities).
To estimate tm number of facilities that generate wastes exhibiting the TC, EPA
multiplied the number of facilities (in each size category) generating each wastestream by
the percentage of the total wastestream quantity that exhibits the TC.3 The quantity of each
wastestream that exhibits the TC was split evenly (within size category) among the resulting
number of facilities generating waste that exhibits the TC. EPA examined two alternative
sensitivity analysis assumptions for intermediate percentages (i.e., percentages other than 0
or 100) of wastestreams that exhibit the TC.* First, EPA assumed that if an intermediate
percr.*.t.nge (not 0 percent or 100 percent) of a wastestream exhibited the TC, then 10
percent of facilities generating that wastestream were potentially affected. This tended to
concentrate larger quantities of waste at fewer facilities than in the initial analysis. Second,
EPA assumed that if an intermediate percentage of a wastestream exhibited the TC, then 90
percent of facilities generating that wastestream were potentially affected. These two
alternative assumptions provided an upper and lower bound sensitivity analysis of affected
facilities.
One important assumption is implicit in the method for deriving the number of
facilities generating waste that exhibits the TC. The Agency assumed that if a facility
generates a waste that exhibits the TC, the entire quantity of that facility's waste exhibits the
TC. Thus, the total quantity of any given waste which exhibits the TC is distributed to a
group of facilities by assuming that all of a facility's waste either exhibits the TC or does
not, rather than distributing some portion of each waste exhibiting the TC among all
facilities.
Wastestream characterization data includes the number of facilities generating each
wastestream examined for this analysis. Within any given industry, single facilities may be
generating multiple wastestreams that exhibit the TC. That is, there may be overlap of the
facilities that are generating each separate wastestream in an industry. To account for this
overlap, EPA developed two scenarios to assign wastes that exhibit the TC to model
facilities: one scenario portrays the maximum number of facilities affected and the other the
minimum number of facilities affected.
The Agency derived the maximum and minimum scenarios in conjunction with
preliminary cost estimates. Preliminary estimates of incremental cost per facility per
wastestream were calculated on a wastestream-by-wastestream basis. Next, EPA
considered the possibility of multiple wastes being generated by single facilities. It was
2	For three non-manufacturing SICs (461, 4911, and 517), EPA used number of employees m
lieu of value of shipments data
3	The derivation of this percentage is described above in Section 2.2,
* Clearly, if none or all of a wastestream exhibits the TC, then no facilities or all facilities are
affected by the rule because of that wastestream.

-------
2-20
possible to categorize wastes into groups within each SIC. Each waste group has a
distinct number of generating, facilities associated with it. Assuming that each of the
facilities associated with the waste group could be generating any number of the wastes in
the group. EPA developed the maximum and minimum scenarios when calculating
preliminary total incremental costs per facility. The maximum scenario assumes that wastes
are generated so that the maximum possible number of facilities will incur costs (i.e..
individual wastes that exhibit the TC tend to be generated by different facilities and total
per-facility costs tend to be less). The minimum scenario assumes that wastes are
generated so that the minimum possible number of facilities incur costs (i.e., individual
wastes that exhibit the TC tend to be generated by the same facilities and total per-facility
costs tend to be higher). The resulting maximum and minimum scenarios consist of model
facilities with different configurations of wastes, consistent with information about linkages
between wastes. For example, wastewater treatment sludges were linked to associated
wastewaters. Details of the derivation of the maximum and minimum scenarios are
presented in Appendix B.
The remainder of this section discusses the estimated number of affected facilities for
the four regulatory options examined. For this RIA, "affected" is defined to mean incurring
additional costs as a result of the final TC rule. Affected facilities are all facilities generating
either 1) wastewaters that will exhibit the TC and are currently managed in surface
impoundments or 2) non-wastewaters that will exhibit the TC. Note that important
categories that may be of interest are subsets of affected facilities as defined in this RIA
(e.g., new hazardous waste generators, facilities that already generate hazardous wastes
and will generate additional TC hazardous wastes; new treatment, storage, and disposal
facilities (TSDFs); and facilities that will convert surface impoundments to exempt treatment
tanks.)
2.3.2 Results
Results for the number of facilities affected are presented as ranges in Exhibit 2-11,
which represent the maximum and minimum number of affected facilities under the
scenarios described above. Exhibit 2-12 summarizes the distribution of TC waste quantities
to large and small facilities. The total number of facilities affected for the different regulatory
options ranged from about 14,OCX) (minimum number affected under DAF 500) to 19,000
(maximum number affected under DAF 33). The results are presented, by industry, for each
regulatory option in Exhibits 2-13 through 2-16. We highlight results for small facilities and
large facilities below.
The number of affected small facilities stays relatively constant across all options at
between 13,000 (minimum scenario, DAF 500) and 16,000 (maximum scenario, DAF 33).
The number of affected small facilities under the most stringent and least stringent options
differs by only about 1,000 facilities (about seven percent) under the maximum facilities
affected scenario and by about 2,000 facilities (about 14 percent) under the minimum
facilities affected scenario. The small variation, both across options and between the
maximum and minimum scenarios, can be explained by examining results for the Wholesale
Petroleum Marketing industry. All of the small Wholesale Petroleum Marketing facilities
generating wastes (about 13,000) are affected by the TC under all regulatory options. This
drives the results for number of small facilities affected. Other industries with significant
numbers of small facilities affected at DAF 100 and DAF 250 include Textiles, Miscellaneous
Petroleum and Coal Products, and Petroleum Pipelines.

-------
EXHIBIT 2-11
NUMBER OF FACILITIES INCURRING COSTS FOR EACH OPTION
OPTION
LARGE FACILITIES
SMALL FACILITIES
ALL FACILITIES
NUMBER OF
INCURRI
FACILITIES
NG COSTS
NUMBERO
INCURF
F FACILITIES
IING COSTS
NUMBER OF FACILITIES
INCURRING COSTS
33
100
250
500
MINIMUM
1,900
1,100
870
700
MAXIMUM
2,600
1,800
1,300
1,100
MINIMUM
15,000
14,000
13,000
13,000
MAXIMUM
16,000
16,000
15,000
15,000
MINIMUM
17,000
15,000
14,000
14,000
MAXIMUM
19,000
17,000
16,000
16,000

-------
EXHIBIT 2-12
WASTE QUANTITIES EXHIBITING THE TC
REGULATORY OPTION
(OAF)
AFFECTED WASTEWATER QUANTITY
(MT/YR)

AFFECTED NON-WASTEWATER QUANTITY
(MT/YR)

LARGE
SMALL
TOTAL*

LARGE
SMALL
TOTAL'
33
830.000,000
11.000.000
840,000.000

2,900,000
200,000
3,100,000
too
720,000,000
10,000,000
730,000,000

1,600,000
160,000
1,800,000
250
690,000,000
9,100,000
700,000.000

560,000
140,000
710,000
500
650.000,000
8,600,000
660,000,000

440,000
73,000
510,000
•TOTALS MAY NOT ADD DUE TO BOUNDING

-------
EXHIBIT 2-13

NUMBER OF FACILITIES INCURRING COSTS (DAF 33)

LARGE FACILITIES
SMALL FACILITIES
ALL FACILITIES

NUMBER OF FACILITIES
NUMBER OF FACILITIES
NUMBER OF FACILITIES
SIC"
INCURRI
NG COSTS
INCURRING COSTS
INCURRING COSTS

MINIMUM
MAXIMUM
MINIMUM
MAXIMUM
MINIMUM
MAXIMUM
2231
46
48
1
1
47
49
225X
560
620
880
1.000
1,400
1,600
226X
67
69
170
180
240
250
229X
1
1
1
1
2
2
22YY
270
510
3
3
270
510
2421
18
18
59
59
77
77
26XX
130
130
23
23
150
150
2821
64
200
85
270
150
470
2822
7
7
10
11
17
18
2823
16
16
0
0
16
16
2824
4
4
1
3
5
7
283X
54
54
170
170
220
220
286
62
280
88
360
150
640
2911
220
220
0
0
220
220
2992
34
61
210
370
240
430
3031
6
6
0
0
6
6
461
29
29
200
200
230
230
517
310
310
13,000
13,000
13,000
13,000
TOTAL-
1.900
2,600
15.000
16,000
17.000
19,000
•TOTALS MAY NOT ADD DUE TO ROUNDING
• 'SEE EXHIBIT 2-3 FOR SIC CODES CORRESPONDING TO DIFFERNT INDUSTRIES

-------
EXHIBIT 2-14

NUMBER OF FACILITIES INCURRING COSTS (DAF 100)

LARGE FACILITIES
SMALL FACILITIES
ALL FACILITIES

NUMBER OF FACILITIES
NUMBER OF FACILITIES
NUMBER OF FACILITIES
SIC**
INCURRI
NG COSTS
INCURRING COSTS
INCURRING COSTS

MINIMUM
MAXIMUM
MINIMUM
MAXIMUM
MINIMUM
MAXIMUM
2231
39
48
0
0
39
48
225X
170
440
330
830
500
1,300
226X
58
59
150
150
210
210
2421
18
18
59
59
77
77
26XX
49
49
8
8
57
57
2821
62
200
83
270
150
470
2S22
6
6
9
9
15
15
2823
16
16
0
0
16
16
2824
4
4
1
3
5
7
283X
54
54
170
170
220
220
286
62
260
88
340
150
600
2911
220
220
0
0
220
220
2992
34
61
210
370
240
430
461
29
29
200
200
230
230
517
310
310
13,000
13,000
13,000
13,000
TOTAL*
1,100
1,800
14.000
16,000
15,000
17,000
•TOTALS MAY NOT ADD DUE TO ROUNDING
• 'SEE EXHIBIT 2-3 FOR SIC CODES COHHESPONDING 10 OlFf UHENT INDUSTBIES

-------
EXHIBIT 2-16

number OF FACII
~TIES INCURRING COSTS (DAF 250)

LARGE FACILITIES
SMALL FACILITIES
ALL FACILITIES

NUMBER OF FACILITIES
NUMBER OF FACILITIES
NUMBER OF FACILITIES
sic*#
INCURRI
NG COSTS
INCURRING COSTS
INCURRING COSTS

MINIMUM
MAXIMUM
MINIMUM
MAXIMUM
MINIMUM
MAXIMUM
2231
11
22
0
0
11
22
226X
24
25
62
63
86
88
2421
18
18
59
59
77
77
28XX
18
18
3
3
21
21
2621
55
200
74
200
130
400
2822
6
6
9
9
15
15
2823
16
16
0
0
16
16
2824
4
4
1
3
5
7
283X
61
61
150
150
210
210
286
62
230
88
310
150
540
2911
220
220
0
0
220
220
2992
34
47
210
290
240
337
461
29
29
200
200
230
230
517
310
310
13,000
13,000
13,000
13,000
total-
870
1,300
13,000
15,000
14,000
16,000
•TOTALS MAY NOT ADD DUE TO ROUNDING
• 'SEE EXHIBIT 2-3 FOR SIC CODES CORRESPONDING TO DIFFERENT FACILITIES

-------
EXHIBIT 2-18

NUMBER OF FACILITIES INCURRING COSTS (DAF 500)

URGE FACILITIES
SMALL FACILITIES
ALL FACILITIES

NUMBER OF FACILITIES
NUMBER OF FACILITIES
NUMBER OF FACILITIES
SIC"
INCURRING COSTS
INCURRING COSTS
INCURRING COSTS

MINIMUM
MAXIMUM
MINIMUM
MAXIMUM
MINIMUM
MAXIMUM
2421
17
17
57
57
74
74
26XX
3
3
1
1
4
4
2821
31
93
41
120
72
210
2822
6
6
9
9
15
15
2823
16
16
0
0
16
16
2824
4
4
1
3
5
7
283X
61
61
150
150
210
210
286
62
200
88
270
150
470
2911
120
220
0
0
120
220
2992
34
34
210
210
240
240
461
29
29
200
200
230
230
517
310
380
13,000
14,000
13,000
14,000
TOTAL-
700
1,100
13,000
15,000
14,000
16,000
•TOTALS MAY NOT AOD DUE TO BOUNDING
* 'SEE EXHIBIT 2-3 FOR SIC CODfIS COnHESPONWNG TO DirFfnLNr INDUSTH1ES

-------
2-27
The number of affected large facilities varies between 700 (minimum scenario, DAF
500} and 1,900 (maximum scenario, DAF 33). At both DAF 100 and DAF 250, all Petroleum
Refineries (220) and all large Wholesale Petroleum Marketers (310) are affected by the TC.
Many large Textiles mills are affected under the DAF 33 option (940 to 1,200). The number
of large Textiles mills affected drops at DAF 100 (270 to 550), then to around 40 at DAF
250. No Textiles mills (large or small) are affected at DAF 500. Other industries with
significant numbers of large facilities affected at DAF 100 and DAF 250 include Organic
Chemicals, Plastics and Resins, Miscellaneous Petroleum and Coal Products, and
Pharmaceuticals.
2.4 LIMITATIONS AND SENSITIVITY ANALYSES
This section identifies important limitations to the characterization of affected wastes
and facilities, and explains the implications of the limitations. Most of the limitations to the
characterization of affected wastes and facilities stem from data gaps.
2.4.1 Industries and Wastes Not Included
Perhaps the most important limitation of the characterization of affected wastes and
facilities is that this RIA addresses a limited number of industries and wastestreams. Unlike
hazardous waste listings, which are specific in nature, the TC is designed to identify broad
categories of wastes that are hazardous. Many of the TC toxicants are common and are
found in a variety of substances. TC toxicants could potentially be found in the
wastestreams of hundreds of manufacturing and non-manufacturing industries. End-users
as well as producers of substances containing TC toxicants may be affected by the rule.5
As it would be impossible to quantify the full range of effects of this regulation, the Agency
has concentrated on industries most likely to generate large quantities of potentially affected
waste. EPA acknowledges that the industry coverage of this RIA is not complete.
The difficulty in pinpointing impacts of unusually broad scope was exacerbated by a
lack of data on non-hazardous wastes. Unlike regulations for managing hazardous wastes,
this regulation will affect wastes currently classified as non-hazardous. These wastes are
currently outside the Subtitle C system, and requirements for information gathering related
to these wastes are minimal.
Most of the available characterization data used in developing industry profiles were
collected during the development of Clean Water Act Effluent Guidelines. Thus, the Agency
was able to focus the most detailed analysis on wastewater treatment related wastes;
aqueous wastes and associated sludges and residuals. Data on sludges were quite limited
and, for the industry profiles, sludge concentrations were often predicted based on
associated wastewater concentrations. Data on other process residuals and on wastes
associated with the end use of substances containing TC toxicants are extremely scarce
and few wastes of this type were analyzed. Some other types of wastestreams that could
possibly be affected by the TC are not included (e.g., contaminated soils).
5 For example, although vehicle maintenance facilities do not manufacture waxes and solvents,
they may use them in their operations. It is conceivable that a vehicle maintenance facility could
generate wastes, such as washwater and spent products, that contain TC constituents due to the
use of the waxes and solvents.

-------
2-2B
TC regulatory levels are not being promulgated as cleanup trigger levels or cleanup
standards for hazardous site cleanups under RCRA or CERCLA. The TC will, however, be
applicable to wastes generated during cleanup of sites. Some excavated soils or other
contaminated media generated during CERCLA cleanups or RCRA corrective actions may
exhibit the TC and thus require management under Subtitle C. However, most wastes
generated during cleanup of hazardous RCRA or CERCLA sites are already managed as
hazardous. The TC is not expected to result in significant impacts on the costs of RCRA or
CERCLA cleanups.
2.4.2	Predicting the Behavior of Oily Wastes in the TCLP
Wastes that are oily in nature behave differently when analyzed in the TCLP than
other non-oily sludges and solids. Actual TCLP results have shown that wastes composed
of an oily matrix may escape TC regulation due to difficulties in performing the leaching
procedure. Technical difficulties during the filtration step of the TCLP may result in either
non-leaching of hazardous constituents contained in the oil phase of the waste or the
inability to obtain reproducible results.
The results presented in Section 2.2 and 2.3 assume that oily sludges behave like
other non-oily solids in the TCLP test. This would tend to result in an overestimate in the
quantities of affected wastes and number of affected facilities. The non-aqueous wastes
considered in this analysis in the Petroleum Refining, Wholesale Petroleum Marketing, and
Petroleum Pipelines industries are almost all oily in nature.6 These oily wastes constitute
about 50 percent of affected non-wastewaters under the DAF 100 option and over 30
percent of affected non-wastewaters under the DAF 250 option. The Petroleum Refining
industry generates the largest quantity of oily wastes of any industry considered in the RIA.
Given the potential importance of an overestimate of affected wastes and facilities,
EPA calculated lower bound estimates assuming that no oily wastes will exhibit the TC.
Under the lower bound assumption for the DAF 100 option, only about 050,000 MT/yr of
non-wastewaters will be affected by the rule. In reality, it is likely that some oily sludges will
exhibit the TC, even considering filtration problems. Further, if test results are not
reproducible and wastes do contain TC constituents in relatively high concentrations, it is
likely that some generators would be obligated to manage their wastes as hazardous based
on their knowledge of any hazardous characteristics of the waste (40 CFR 262.11 (c)(2)).
2.4.3	Waste Quantities Exhibiting the TC
EPA estimated the portion of each wastestream that would exhibit the TC by
assuming a direct correlation of constituent concentrations in any given wastestream. In
other words, the Agency assumed that the highest concentrations of one constituent are
present along with the highest concentrations of other constituents in the wastestream and,
therefore, that the wastestream would fail for only a single driving constituent After every
constituent in a wastestream had been compared with the corresponding critical
concentration, the constituent that resulted in the largest percent exhibiting the TC was
picked as the driving constituent. This largest percent was multiplied by the total quantity
of the wastestream to estimate the quantity that exhibits the TC. EPA tested the sensitivity
6 Spent catafysts and fines and secondary treatment sludges in the Petroleum Refining
industry are not oily.

-------
2-29
of the results to the direct correlation assumption, for the DAF 100 option, by adding
percentages of waste exhibiting the TC for each constituent instead of picking a driving
constituent. This sensitivity analysis assumed a perfect inverse correlation. The analysis
showed that results are very insensitive to the driving constituent assumption. For most
wastestreams, either 1).only the chosen driving constituent is present at levels above TC
regulatory levels, or 2) all of the wastestream would be brought into the system by virtue of
the driving constituent. For the case where all of a wastestream is brought into the system
by virtue of the driving constituent, there may be other constituents present at levels above
their respective TC regulatory levels.
2.4.4	Wastewaters Managed in Surface Impoundments
As mentioned earlier, the Agency used data from the Screening Survey of Industrial
Subtitle D Establishments to estimate industry-specific percentages of large and small
facilities managing wastewaters in surface impoundments, and also applied these
percentages to the total wastewater quantities generated. For sensitivity analysis, EPA
assumed all wastewaters are managed in surface impoundments, to produce an upper
bound of affected wastewater quantities. The DAF 100 option was examined. When it was
assumed that all facilities generating wastewaters are currently managing them in surface
impoundments, affected wastewater quantities increased significantly.
2.4.5	Distribution of Affected Waste Quantities to Large and Small Facilities
For sensitivity analysis, the Agency assumed 50 percent of affected waste was
generated by large facilities and 50 percent was generated by small facilities. This
distribution is significantly different than the initial waste generation distribution assumption,
which assumed that waste generation was proportional to value of shipments for large and
small facilities. Using the value of shipments assumption, large facilities accounted for over
98 percent of waste generation. As defined by the 50 employee cutoff, data indicated that
there are no small facilities in the Petroleum Refining and Cellulosic Synthetic Fibers
industries. This sensitivity analysis did not affect these industries. The equal waste
distribution sensitivity assumption changes large and small facility waste generation most
significantly in those industries for which value of shipments for large facilities was much
greater than 50 percent. Value of shipments for large facilities was over 90 percent of total
industry value of shipments for all industries except three: Miscellaneous Petroleum and
Coal Products, Petroleum Pipelines, and Wholesale Petroleum Marketing.
2.4.6	Percentage of Facilities Affected
For the RIA, EPA assumed, that the percentage of facilities affected by the TC rule
equalled the percentage of waste, generated by those facilities, that exhibited the TC. For
sensitivity analysis, instead of linking the estimate of the number of facilities affected to the
percentage of waste that exhibited the TC, the Agency assumed (1) that 10 percent of
facilities are affected and (2) that 90 percent of facilities are affected.7
The analysis was much more sensitive to the first alternative assumption (setting
percentages affected to 10 percent) than to the second (setting percentages to 90 percent).
7 If aN or none of a wastestream exhibited the TC, all or no facilities were considered affected
and the alternative percentages were not assumed

-------
2-30
Setting percentages to-10 percent for the DAF 100 option reduced the number of affected
facilities across industrial sectors by up to 30 percent, while setting percentages to 90
percent resulted in about a S percent decrease. For most wastestreams that exhibit the TC,
over 90 percent of the wastestream fails.

-------
CHAPTER 3
COSTS
Chapter 3 describes the methodology used to estimate the cost of the Toxicity
Characteristic (TC) Rule, The chapter defines the costs relevant to EPA's analysis of the TC
Rule and explains the model used to estimate costs of the rule. It also presents the results
generated by the model in terms of both social costs and compliance costs to industry,
and discusses factors driving the costs results. Also, possible numbers of new RCRA
permit applications and permit modifications ere estimated in the discussion of the cost
model's predictions of compliance practices. Potential costs associated with used oil are
discussed. Finally, the limitations of the cost analysis and relevant results of sensitivity
analyses are presented. Exhibit 3-1 summarizes the approach for estimating costs of the
TC rule.
3.1 DEFINITION OF COSTS
EPA analyzed the incremental costs of the TC Rule in terms of both social costs and
compliance costs to industry expressed as revenue requirements. These terms are defined
below.
The Agency, in order to calculate the incremental costs of the TC Rule, concentrated
on two different types of costs: social costs and costs to industry expressed as revenue
requirements. Social costs are a measurement of the loss to society of goods and services
that would be available if an activity - in this case, the management of certain wastes as
hazardous wastes • were not pursued. In more practical terms, these are the total costs of
the activity minus any transfer payments (including taxes). For example, an owner/operator
of a Subtitle C landfill may charge $200 per metric ton to dispose of hazardous waste in his
or her landfill. If the actual cost to the owner/operator is only $105, the additional $95
dollars is a transfer payment from the generator to the owner/operator and does not add to
social cost, as this money can be spent on a good or service at a later date.
Taxes are another form of transfer payment. Resources collected by the government
in taxes will later be transferred back into society and are not lost to society. Thus, an
important distinction can be made between before-tax costs and after-tax revenue
requirements. Before-tax costs of an activity are closely associated with social costs, while
after-tax revenue requirements measure the necessary income that must be generated by
an owner/operator to offset the newly incurred costs and maintain the same profits. These
revenue requirements, or compliance costs to firms, are what will govern an
owner/operator's economic decisions. The Agency used compliance costs of new waste
management practices when assessing management practice alternatives because
compliance costs for firms are what ultimately influence profits. EPA also used compliance
costs to assess economic impacts (Chapter 4).
Social costs may be less than revenue requirements because they do not include
transfer payments. However, social costs mil not always be lower than revenue
requirements since tax considerations affect the actual cost to the owner/operator.
Specifically, capital improvements can be depreciated for tax purposes while operating and

-------
Exhibit 3-1
Estimating Costs of the TC Rule
Identify possible
post-regulatory
waste management
practices for each
waste type.
Develop unit cost
curves for
baseline and
post-regulatory
practices.
For each set of
model facilities,
calculate revenue
requirements
associated with
each post-regulatory
option.
Choose most
economical post-
regulatory
practices for each
set of model
facilities.
Calculate incremental
cost of waste
management (post-
regulatory cost minus
baseline cost) in terms
of both social cost
and compliance cost
to industry.

-------
3-3
maintenance costs can-be claimed as expenses. The costs associated with those items
still exist, but the government-has made a transfer payment to the owner/operator in the
form of lax breaks* that reduce the revenue requirements necessary to offset the costs of
the improvements. Social costs are difficult to measure because factors such as above-
average profits must be accounted for. For this reason, the social costs measured in the
RIA are only an approximation of actual social costs. Further details on the difference
between social cost and after-tax revenue requirements can be found in Appendix C.
The Agency was concerned with only the new social and compliance costs that
would be incurred as a direct result of the TC rule. Therefore, EPA calculated the cost of
managing the affected wastestreams under the TC rule and subtracted the current cost of
managing the same wastes. This gives an incremental cost associated with the TC rule.
3.2 METHODOLOGY
The Agency used a computer model to estimate the impacts of the TC Rule. First,
as described in Chapter 2. EPA estimated the quantity exhibiting the TC for each
wastestream in the analysis. The Agency then distributed the wastestreams exhibiting the
TC among the facilities in the corresponding industries. EPA distributed wastes to model
facilities using two different algorithms, one which minimized the number of facilities
generating the affected wastes and one which maximized the number of facilities generating
the affected wastes. Finally, the Agency calculated the incremental cost incurred by each
set of model facilities and the resultant economic impacts. The remainder of this chapter
describes the methodology used to calculate costs, given the characterization of wastes
and affected facilities outlined in Chapter 2, and provides the results of the cost analysis.
Resulting economic impacts are discussed in Chapter 4.
3.2.1	Unit Costs for Management Practices
As described in Section 3.1.1, the Agency examined the incremental cost of the TC
Rule in terms of both social costs and compliance costs in order to determine the potential
impacts of the TC. EPA developed unit costs (1988 dollars/metric ton) of managing wastes
for each management practice in both the baseline and the post-regulatory situations. In
some cases, such as managing wastewaters in tanks and sludges in on-site landfills, unit
costs were based on cost curves and were dependent on the quantity of waste managed
using that practice. In other cases, such as management of sludges in off-site landfills or
land treatment facilities, the cost was a flat rate per metric ton. Appendix C details the
methods used for the development of these unit costs and presents the unit costs and cost
curves used in this analysis.
3.2.2	Choosing Post-Regulatory Management Practices
Baseline (i.e., pre-regulatory) management practices are discussed in Chapter 2.
EPA simulated the selection of post-regulatory practices by totalling the quantities of waste
of each type for each set of model facilities and choosing the least expensive method of
managing that waste type. Thus, if a facility generated tour different wastewaters, it would
co-manage those wastewaters and reap the benefits of economies of scale.

-------
3-4
Once wastes of-similar types had been totalled, EPA assumed that a generator
would choose to manage those wastes in the most economical manner available, based on
compliance costs. Compliance costs for each management practice represent the actual
cost to the decision-making party and have a direct impact on firm profits.
Exhibit 3-2 presents the assumptions used in this analysis about the current
(baseline) waste management practices and the options available for owner/operators as
post-regulatory waste management practices. For further discussion about current waste
management practices see Section 2.1.3 in this RIA. For further discussion of the post-
regulatory waste management options see Sections 3.2.3 and 3.2.4 below.
3.2.3	Post-Regulatory Practices: Wastewaters
Post-regulatory costs for wastewaters in this analysis are based on the cost of
management in tanks exempt from Subtitle C requirements. EPA also examined costs of
underground injection and dilution as potential compliance practices, but did not assign
these costs to any facilities because the estimated costs were significantly higher than for
management in exempt tanks. A brief summary of underground injection and dilution costs
follows.
EPA estimated that large quantities of hazardous wastewater cost about S7 per
metric ton to inject underground. Comparing this with less than SO. 50 per metric ton for
managing wastewaters in exempt tanks indicates that waste handlers would select tanks
over underground injection, tt is worth noting that there are many factors beyond the
scope of EPA's analysis which could make underground injection a viable alternative for
some facilities. These factors include geographic location, treatment that would be
necessary to meet NPDES requirements, dual use of wells or drilling equipment in certain
industries, and waste properties not characterized in TC data.
EPA estimated that diluting a waste with one part water to one part waste would be
less costly than management in exempt tanks for quantities in excess of 300,000 metric
tons per year. The Agency examined data for each wastewater affected by the TC Rule
and concluded that a 1 to 1 dilution of these wastewaters would not change their status
under the TC rule since the resulting constituent concentrations would still cause the
wastes to exhibit the TC. A greater dilution ratio would not be more economical than tank
management for any quantity.
While it is conceivable that specific facilities might find underground injection or
dilution to be desirable alternatives, Agency cost estimates indicate that, in general,
management in exempt tanks is significantly less costly. Thus, post-regulatory costs for all
wastewaters are based on the cost of management in exempt tanks.
3.2.4	Post-Regulatory Practices: Non-Waatewaters
EPA examined on-site landfills, on-site land treatment, and the use of off-site
hazardous waste facilities as post-regulatory options for sludges, slurries, and solid
residuals. The Agency included the costs of complying with relevant RCRA requirements
for owner/operr*ors in its analysis of on-site Subtitle C waste management costs. These
costs include waste analysis, personnel training, contingency plan preparation, liability
insurance, permit application, and closure plan development and execution. For off-site

-------
3-5
EXHIBIT 3-2
MANAGEMENT PRACTICE ASSUMPTIONS
WASTE TYPE
BASELINE
Wastewater
Surface impoundment
or
Practice permissible
under Subtitle C (tank
followed by NPDES or
PQTW discharge, indirect
or direct discharge
without treatment, or
recycle)
POST-REGULATORY
Exempt tanks or
Discharge to POTW
Sludge/slurry
On-site landfill
or
On-site land treatment unit
or
Off-site landfill
Off-site Subtitle C
landfill
or
On-site Subtitle C
landfill
or
On-site Subtitle C
land treatment unit
Solid residual
On-site landfill
or
Off-site landfill
Off-site Subtitle
C landfill
or
On-site Subtitle C
landfill
Organic Liquid
Practice permissible
under Subtitle C
Identical to current
practice

-------
3-6
management of non-wastewaters, EPA used the cost charged by commercial facilities (plus
transportation costs) to calculate compliance costs to generating facilities. EPA used an
estimate of the waste management cost to the commercial facility (lo*er than price
charged) in the calculation of social costs.
In addition to incorporating normal operating expenses for on-site Subtitle C
management, the Agency also incorporated expected costs for RCRA corrective action.
Expected corrective action costs are included in the price of off-s-.te Subtitle C management.
To assess expected corrective action costs associated with on-site management. EPA used
data from the Corrective Action Regulatory impact Analysis to estimate the expected
corrective action costs for a TC waste handler choosing to enter the Subtitle C system as a
TSDF. Based on information in the Corrective Action RIA. the Agency assumed that
approximately 31 percent of all new Subtitle C facilities would trigger corrective action at
some point in time. Approximately 12 percent would trigger corrective action immediately
and 19 percent would trigger corrective action sometime in the life of the facility. The
remaining 69 percent of the facilities would not trigger any corrective action and were not
assigned corrective action costs. The Agency assumed that facility owner/operators can
determine whether they will trigger corrective action based on existing facility conditions.
Based on this assumption, the Agency added the present value of corrective action costs
(annualized at a discount rate of 9 percent for compliance costs and 3 percent for social
costs) to the yearly cost of on-site management for 31 percent of the facilities. Thus, those
model facilities choosing on-site management as the least costly method of managing
sludges, slurries, and solid residuals incorporate expected corrective action costs into the
decision.
3.2.5 Calculating Incremental Cost
Once a compliance practice had been selected using compliance revenue
requirements, EPA calculated both the incremental social costs and incremental revenue
requirements (i.e., compliance costs) for each facility. By summing the incremental costs
for each facility, the Agency was able to estimate the total incremental social cost of the TC
Rule and the incremental compliance costs to each industry included in the analysis.
3.3 RESULTS
The Agency estimated costs based on two potential distributions of wastes exhibiting
the TC. One distribution concentrates all waste exhibiting the TC in an industry in as few
facilities as possible and the other distributes waste exhibiting the TC over as many facilities
as possible. The two distributions yield different costs for model facilities in each industry.
A concentrated distribution (i.e., distributing to as few facilities as possible) tends to result
in greater economies of scale. Both distributions estimate the costs for the same quantities
of waste and the same number of wastestreams; the independent variable between the two
distributions is the number of facilities affected by the TC Rule. As it turns out for the
options considered, costs corresponding to the minimum number of facilities affected and
maximum number facilities affected were identical or very close to each other for all
industries. This indicates that costs are proportional to the quantities of waste that exhibit
the TC, and are relatively insensitive to the distribution of TC wastes among affected
facilities.

-------
3*7
Therefore, only one set of costs are presented in the following section - those
corresponding to the maximum facilities affected scenario.
3.3.1	Total Annual Social Costs
EPA calculated the total annual social costs for each of the four regulatory options.
The costs, expressed in 1988 dollars, are presented in Exhibit 3-3.
The predicted annual social costs of the TC range from $52 million at DAF 500 to $270
million at DAF 33. Annual social costs at DAF 100 ($190 million) are almost three times
higher than at DAF 250 ($67 million). The drop in social costs from DAF 100 to DAF 250 is
mainly attributable to a decrease in the number of wastestreams that exhibit the TC under
each option. Approximately 150 wastestreams are affected under the DAF 100 option while
120 exhibit the TC at DAF 250. In addition to 30 wastestreams dropping out of regulation
from DAF 100 to DAF 250, some wastestreams regulated under both options have a smaller
percentage affected under the DAF 250 option.
3.3.2	Annual Compliance Costs to Industry
Compliance costs to industry differ from social costs because the costs to industry
include the transfer payments paid by facility owner/operators such as taxes and off-site
hazardous waste management facility profits. Annual compliance costs to industry are the
actual operating costs that owner/operators must face each year as a result of the TC Rule.
The total compliance costs to industry for the four regulatory options are presented in
Exhibit 3-4.
The total annual compliance costs to industry range from $82 million under the DAF
500 option to $350 million at DAF 33. Costs more than double from DAF 250 ($110 million)
to DAF 100 ($250 million). The difference in costs between DAF 100 and DAF 250 can be
traced to the difference in non-wastewater quantities between the two options, as will be
further discussed in Section 3.3.5. These compliance costs represent the total amount of
additional revenue that industry would have to generate annually in order to comply with
the TC Rule without reducing profits. The economic impacts on facilities resulting from
these costs are discussed in Chapter 4.
Although 90 to 95 percent of the model facilities affected by this rule are small
facilities, only about 10 to 20 percent of the total costs to industry are incurred by small
facilities. Smafl facilities incur costs of nearly $35 million for the DAF 33 option,
approximately $28 million for the DAF 100 option, about $25 million for the DAF 250 option,
and around $13 million for the DAF 500 option. Large facilities, which comprise five to 10
percent of affected facilities, incur 80 to 90 percent of the total costs to industry. Large
facilities incur approximately $320 million in compliance costs under the DAF 33 option,
nearly $220 million under the DAF 100 option, about $89 million under the DAF 250 option,
and $68 million under the DAF 500 option.
The fact that a relatively small number of large facilities incurs the majority of
compliance costs may, to some extent, result from analytical assumptions made in the RIA
concerning distribution of waste to affected facilities. EPA tested the sensitivity of results to
these assumptions; further discussion is found in Section 3.4.7.

-------
EXHIBIT 3-3
ANNUAL SOCIAL COSTS TO
INDUSTRY FOR EACH OPTION
OPTION
SOCIAL COSTS
($ MILLIONS)
33
270
100
190
250
67
500
52

-------
EXHIBIT 3-4
TOTAL COMPLIANCE COSTS FOR EACH OPTION

LARGE FACILITIES
SMALL FACILITIES
ALL FACILITIES
OPTION
TOTAL COST
TO INDUSTRY
NUMBER OF FACILITIES
INCURRING COSTS
TOTAL COST
TO INDUSTRY
NUMBER OF FACILITIES
INCURRING COSTS
TOTAL COST
TO INDUSTRY


MINIMUM
MAXIMUM

MINIMUM
MAXIMUM

33
320,000.000
1,900
2,600
35,000,000
15,000
16,000
350,000,000
100
220,000,000
•
1,100
1,800
28,000,000
14,000
16,000
250,000,000
250
89,000,000
870
1,300
25,000,000
13,000
15,000
110,000,000
500
68,000,000
700
1,100
13,000,000
13,000
15,000
82,000,000
TOTALS FOR ALL FACILITIES MAY NOT ADD DUE TO ROUNDING

-------
3-10
3.3.3	Distribution of Compliance Costs Across Industries
Exhibits 3-5 through 3-8 present the distribution of annual compliance costs among
affected industries. The split between costs associated with wastewaters and non-
wastewater costs is shown. Under all options, five or six major industrial sectors incur over
90 percent of total costs. Petroleum Refining. Pulp and Paper, and Wholesale Petroleum
Marketing are the three industries incurring the largest costs (about 70 percent of total)
under the DAF 33 and DAF 100 options. Wholesale Petroleum Marketing, Synthetic Fibers,
and Organic Chemicals are the three industries predicted to experience the largest costs
(approximately 60 percent of total) under the DAF 250 and DAF 500 options.
The Petroleum Refining industry incurs the largest costs of any industry under the DAF
33 options (S140 million) and DAF 100 option (S99 million.) Costs for the Petroleum
Refining industry drop to S17 million for the DAF 250 option, and to $9 million under the
DAF 500 option. There is also a significant variation of costs among options for the Pulp
and Paper industry. The Pulp and Paper industry incurs costs of about $85 million under
the DAF 33 option, dropping to half that ($42 million) at DAF 100. Costs to the Pulp and
Paper industry are only about S3 million at DAF 250 and $530,000 at DAF 500.
Costs to the Wholesale Petroleum Marketing industry differ by about a factor of three
from the least stringent option ($12 million) to the most stringent option ($30 million).
Wholesale Petroleum Marketing costs are similar for the DAF 100 ($25 million) and DAF 250
($24 million) options. Costs to the Synthetic Fibers industry are estimated to be the same
($22 million) for ail four options. Other industries that incur a significant portion of costs for
the DAF 100 and DAF 250 options are Organic Chemicals, Pharmaceuticals, and Synthetic
Rubber.
3.3.4	Factors Driving Costs
Although the quantity of waste exhibiting the TC is driven by wastewaters, the cost of
complying with the TC Rule is driven by sludges, slurries, and solid residuals. The
incremental compliance cost of managing sludges, slurries and solid residuals ranged from
about 75 to 200 dollars per metric ton. However, the incremental cost of managing
wastewaters was 0.01 to 0.53 dollars per metric ton. Non-wastewater costs account for
over 95 percent of total costs. Thus, those industries with large quantities of sludges,
slurries, and solid residuals incur the highest annual compliance costs and those
constituents that cause the most sludges, "slurries, and solid residuals to exhibit the TC can
be considered the cost driving constituents.
Sludges from Petroleum Refining, Wholesale Petroleum Marketing, Synthetic Fibers,
Organic Chemicals, and Synthetic Rubber all exhibit the TC mainly due to the presence of
benzene. Thus, benzene is the driving constituent for wastestreams associated with at least
70 percent of total costs for DAF 100 and 80 percent of total costs for DAF 250.
Chloroform, vinyl chloride, and cartoon tetrachloride are the other notable cost driving
constituents for these two options.
3.3.5	Coat Model Predictions of Compliance Practices
Using its cost model which compares compliance costs of each post-regulatory waste
management option, the Agency predicted that the vast majority of model facility

-------
EXHIBIT 3-5
COSTS TO INDUSTRY SPLIT BY WASTEWATERS AND NON-WASTEWATERS (DAF 33)


WASTEWATER
NON-WASTEWATER
TOTAL
SIC
INDUSTRY
COST
COST
COST
22
TEXTILE MANUFACTURING
800,000
14,000,000
15,000,000
2421
SAWMILL AND PLANNING MILL AND FINISHING
820
0
820
26
PULP AND PAPER MILLS
360,000
84,000,000
85,000,000
2821
PLASTICS MATERIALS AND RESINS
310,000
5,300,000
5,600,000
2822
SYNTHETIC RUBBER
200,000
8,300,000
8,400,000
2823,4
SYNTHETIC FIBERS
350,000
22,000,000
22,000,000
283
PHARMACEUTICALS
330,000
17,000,000
17,000,000
286
ORGANIC CHEMICALS
730,000
25,000,000
25,000,000
2911
PETROLEUM REFINING
4,000,000
130,000,000
140,000,000
2992
MISCELLANEOUS PETROLEUM AND COAL PRODUCTS
0
7.900,000
7,900,000
30
RUBBER AND MISCELLANEOUS PLASTIC PRODUCTS
0
6,100
6,100
461
PETROLEUM PIPELINES
59,000
3.200,000
3,300,000
517
WHOLESALE PETROLEUM MARKETING
1,000,000
29,000,000
30.000,000
TOTAL*
8,200,000
350,000,000
350,000,000
•TOTALS MAY NOT ADD DUE TO HOUNDING
FOOTNOTE: COSTS CORRESPOND TO THE SCENARIO WITH THE MAXIMUM NUMBER OF FACILITIES AFFECTED

-------
EXHIBIT 3-6
COSTS TO INDUSTRY SPLIT BY WASTEWATERS AND NON-WASTEWATERS (DAF 100)


WASTEWATER
NON-WASTEWATEB
TOTAL
SIC
INDUSTRY
COST
COST
COST
22
TEXTILE MANUFACTURING
230,000
7,600,000
7,800,000
2421
SAWMILL AND PLANNING MILL AND FINISHING
820
0
820
26
PULP AND PAPER MILLS
35,000
42,000,000
42,000.006
2821
PLASTICS MATERIALS AND RESINS
240,000
5,100,000
5,300,000
2822
SYNTHETIC RUBBER
190.000
8,100,000
8,300,000
2823,4
SYNTHETIC FIBERS
350.000
22,000,000
22,000,000
283
PHARMACEUTICALS
270,000
14,000,000
14,000,000
286
ORGANIC CHEMICALS
600.000
20,000,000
21,000,000
2911
PETROLEUM REFINING
4,000.000
95.000,000
99.000,000
2992
MISCELLANEOUS PETROLEUM AND COAL PRODUCTS
0
5.300,000
5,300,000
461
PETROLEUM PIPELINES
60,000
2,700,000
2,800,000
517
WHOLESALE PETROLEUM MARKETING
1.000.000
24,000,000
25,000,000
TOTAL*

7,100.000
250,000.000
250,000,000
•TOTALS MAY NOT ADO OUE TO ROUNDING
FOOTNOTE: COSTS CORRESPOND TO 1 HE SCENARIO Will II ME MAXIMUM NUMUER OF FACILIIIES AII'EC 1EP

-------
EXHIBIT 3-7
COSTS TO INDUSTRY SPLIT BY WASTEWATERS AND NON-WASTEWATERS (DAF 250)


WASTEWATER
NON-WASTEWATER
TOTAL
SIC
INDUSTRY
COST
COST
COST
22
TEXTILE MANUFACTURING
20,000
2,400,000
2,500,000
2421
SAWMILL AND PLANNING MILL AND FINISHING
820
0
820
26
PULP AND PAPER MILLS
0
2.900,000
2,900,000
2821
PLASTICS MATERIALS AND RESINS
130,000
3,000,000
3,100,000
2822
SYNTHETIC RUBBER
190,000
8,100,000
8,300,000
2823,4
SYNTHETIC FIBERS
350,000
22,000,000
22,000,000
283
PHARMACEUTICALS
250,000
11,000,000
11,000,000
286
ORGANIC CHEMICALS
530,000
18,000,000
Id,000,000
2911
PETROLEUM REFINING
4,000,000
13,000,000
17,000,000
2992
MISCELLANEOUS PETROLEUM AND COAL PRODUCTS
0
2,700,000
2,700,000
461
PETROLEUM PIPELINES
58,000
2,600,000
2,700,000
517
WHOLESALE PETROLEUM MARKETING
1,000,000
23,000,000
24,000,000
TOTAL-
6,600,000
110,000,000
110,000,000
•TOTALS MAY NOT ADD DUE TO ROUNDING
FOOTNOTE: COSTS CORRESPOND TO THE SCENARIO WlHI THE MAXIMUM NUMBER OF FACILITIES AFFECTED

-------
EXHIBIT 3-8
COSTS TO INDUSTRY SPLIT BY WASTEWATERS AND NON-WASTEWATERS (DAF 500)


WASTEWATER
NON-WASTEWATER
TOTAL
SIC
INDUSTRY
COST
COST
COST
22
TEXTILE MANUFACTURING
2,400
0
2,400
242t
SAWMILL AND PLANNING MILL AND FINISHING
780
0
, 780
26
PULP AND PAPER MILLS
0
530,000
530,000
282!
PLASTICS MATERIALS AND RESINS
110,000
2,300,000
2,400,000
2822
SYNTHETIC RUBBER
180,000
8,100,000
8,200,000
2823,4
SYNTHETIC FIBERS
340,000
22,000,000
22,000,000
283
PHARMACEUTICALS
220,000
10,200,000
10,400.000
286
ORGANIC CHEMICALS
502,000
14,000,000
14.000.000
29! 1
PETROLEUM REFINING
3,800.000
5,400,000
9,200,000
2992
MISCELLANEOUS PETROLEUM AND COAL PRODUCTS
0
2,000,000
2,000,000
46!
PETROLEUM PIPELINES
60,000
1,200.000
1,200,000
517
WHOLESALE PETROLEUM MARKETING
1,040,000
11.000,000
12,000,000
TOTAL-

6,300,000
76,000.000
82,000.000
•TOTALS MAY NOT ADD DUE TO ROUNDING
FOOTNOTE: COSTS CORRESPOND TO THE SCENARIO WITH THE MAXIMUM NUMBER OF FACILITIES AR EC1ED

-------
3-15
owner/operators would" select off-site management over either on-site landfilling or on-site
land treatment. Based on the cost curves used in the RIA, in order for on-site management
to be economical, a facility must manage at least 6,760 MT/yr of waste in a landfill or more
than 1,000 MT/yr in an on-site land treatment facility. If the facility expects corrective action
costs as a result of managing waste on-site, the quantities must be even higher to make
on-site management economical.
Although the number of facilities predicted to choose on-site management is relatively
small, these facilities generate large quantities of waste. Using the cost model results, EPA
estimates that approximately two-thirds of the total non-wastewater TC wastes will be
managed on-site under the DAF 100 option; the other one-third will be sent off-site. Under
the DAF 250 option, only 20 percent of affected non-wastewaters are predicted to be
managed on-site and about 80 percent (500,000 MT/yr) are expected to be sent off-site, in
either case, the waste quantities sent off-site for disposal (500,000 to 600,000 MT/yr) will be
substantial and potentially could have an impact on the price of off-site commercial
hazardous waste management.
The Agency used the cost model predictions to establish preliminary estimates of the
new permit applications and permit modifications that will result from the TC rule. These
estimates are presented in Exhibit 3-9. The number of facilities that will apply for new
Subtitle C land'disposal permits was estimated as follows: the number of facilities
predicted to manage non-wastewaters on-site was multiplied by the percentage of facilities
in corresponding industries that do not currently have Subtitle C treatment, storage, or
disposal facility (TSDF) status. Low and high estimates correspond to the minimum and
maximum facilities affected scenarios. The remaining facilities predicted to manage non-
wastewaters on-site that already have Subtitle C permits or interim status are predicted to
require permit modifications or changes to interim status to land dispose newly hazardous
TC wastes. This number of facilities constitutes the low estimates of permit modifications in
Exhibit 3-9. To derive a high estimate of permit modifications required, EPA used the total
number of facilities managing non-wastewaters (on-site or off-site) that are estimated to
already have TSDF status. This high estimate assumes that any interim status or permitted
facility that generates newly hazardous TC wastes will require a permit modification; it
includes treatment and storage facilities in addition to land disposal facilities.
3.3.6 Potential Costs Associated with Used Oil
Used oil is generated across a wide variety of industrial sectors. Some generators
manage or dispose of their used oil directly while others provide their used oil to the used
oil management system (UOMS), a system of intermediate collectors and processors. Firms
in the UOMS then re-refine the used oil and/or Jjell it for various end uses.
EPA determined that three end-use management practices for used oil may be affected
by the TC rule; road oiling, dumping, and landfilling/incineration. The largest affected
quantity was that associated with landfilling/incineration (approximately 405,000 metric tons
per year), followed by dumping (374,000 MT/year), and road oiling (232,000 MT/year).
If used oil were to become hazardous under the TC, it would probably be shifted to
other end-use management practices. Much of the used oil that is currently dumped or
applied directly to roads by generators would probably be collected and sold to the UOMS.
Firms in the UOMS that currently sell used oil for road oiling would generally shift this oil to

-------
EXHIBIT 3-9
RANGE OF PERMIT APPLICATIONS
AND MODIFICATIONS
OPTION
PERMIT
APPLICATIONS
PERMIT
MODIFICATIONS

LOW
HIGH
LOW
HIGH
33
260
260
51
230
100
180
190
45
220
250
15
17
3
220
500
15
17
3
130

-------
3-17
other management practices, such as re-refining or burning as a fuel. Used oil that is
managed by landfilling or incineration in Subtitle D units would be shifted to management in
Subtitle C units.
The shift in management practices would impose costs on used oil generators, the
UOMS, and end-users of used oil. Used oil generators currently providing used oil to the
UOMS would be likely to pay somewhat higher collection costs due to pass-through of
compliance costs by firms in the UOMS. (These compliance costs would be associated
with the disposal of used oil-related wastes, which would potentially be TC hazardous.)
Generators directly managing their wastes by road oiling would incur storage and collection
costs for their used oil as well as costs for a road-oiling substitute. Generators directly
managing their wastes by dumping would incur costs for storage and collection. Firms in
the UOMS that sell used oil for road oiling would be forced to sell the oil in less profitable
markets, and some firms could close if unable to enter another market. Firms in the UOMS
could also incur costs for disposal of low quality used oil and related wastes in Subtitle C
(rather than Subtitle D) units if these wastes were TC hazardous. As discussed above,
some of these costs could be passed on to used oil generators. Firms that re-refine used
oil could benefit from the TC rule, since a greater volume of used oil would potentially be
available at a lower price. Finally, end-users that purchase used oil for road oiling would
incur costs for an alternative dust suppressant.
3.4 LIMITATIONS AND SENSITIVITY ANALYSES
The limitations associated with characterization of wastes and affected facilities carry
over into estimates of costs associated with the TC rule. As discussed in Chapter 2, EPA
conducted sensitivity analyses of the most important assumptions. The subsections below
discuss focus on limitations introduced by the cost methodology itself. Some of the
limitations of this analysis tend to underestimate costs of the TC rule; others tend to
overestimate costs. The Agency has attempted to quantify potential overestimates or
underestimates wherever possible.
3.4.1 Industries and Wastes Not Included
As noted in Chapter 2, the Agency has used available data to identify industries likely
to generate large quantities of waste exhibiting the TC. Given the potentially broad scope
of the rule and the scarcity of data on currently non-hazardous wastes, it is likely that some
industries not addressed in this RIA may also be affected by the TC.
In addition to potentially incomplete industry coverage, there is incomplete wastestream
coverage in this RIA. Wastestream analysis focused on wastewaters and associated
wastewater treatment sludges. It was very difficult to locate data on other process
residuals, which would be costly to manage as hazardous. There were no data readily
available on some types of potentially affected wastestreams such as contaminated soils.
Incomplete industry and waste coverage, as an independent factor, underestimates the
costs of the TC rule.

-------
3-18
3.4.2	Uncertainty Concerning Oily Wastes
As discussed in Section 2.4.2, this analysis may overestimate the quantities of affected
non-wastewaters in three industries; Petroleum Refining, Wholesale Petroleum Marketing,
and Petroleum Pipelines. Most of the sludges from these industries are oily in nature, and
hazardous constituents in these oily wastes may not pass through the TCLP as readily as
for non-oily wastes.
Since costs for managing sludges and solids are the driving costs of this analysis, any
overestimate of the quantities of affected non-wastewaters introduces a corresponding
overestimate in the cost analysis. Costs associated with oily wastes in Petroleum Refining.
Wholesale Petroleum Marketing, and Petroleum Pipelines industries constitute roughly 50
percent of total costs of the rule for the DAF 33 and DAF 100 options, about 40 percent
under the DAF 250 option, and 20 percent for DAF 500.
Given the significance of the potential cost overestimates just discussed, the Agency
conducted a lower bound analysis by alternatively assuming that no oily wastes will exhibit
the TC. Lower bound annual compliance cost estimates are $130 million for DAF 100 and
S66 million for DAF 250.
3.4.3	Identification of Management Practices and Development of Unit Costs
The TC RIA cost methodology was developed to be used in the absence of facility-
specific data. Baseline management practices were assigned using statistical information
from the Agency's Subtitle D Screening Survey. EPA predicted post-regulatory management
practices using economic logic to evaluate a range of likely waste management alternatives.
Unit costs (in some cases, cost curves) were developed for both baseline and post-
regulatory alternatives. The baseline and post-regulatory waste management practices and
associated costs, in reality, will vary significantly for individual facilities. Factors influencing
actual costs include location, total waste quantities managed and ability to co-manage
wastes, existing waste management facilities available and associated capacity, and
treatment necessary (for example to meet NPDES requirements). Since the Agency did not
have facility-specific information, there is a substantial amount of uncertainty associated with
the average unit costs used. This may result in either an underestimate or overestimate of
costs.
3.4.4	Costs Not Included
Cost estimates in this RIA include costs the Agency identified as significant costs
incurred wtien new wastes are brought into the hazardous waste system. For example, in
the estimates of the cost of Subtitle C management the Agency considered items including
corrective action, liability insurance, personnel training, and contingency planning. The
Agency recognizes that many different cost elements, not just those related to waste
management technologies, constitute significant costs.
While this RIA attempts to thoroughly assess costs industries may incur as a result of
the TC, some costs are not included. In particular, EPA has not quantified the additional
TCLP testing costs that may result after promulgation of the TC. There is no RCRA
requirement for generators to test their wastes; the determination of hazardousness may be
made based on either laboratory analysis of the waste or on knowledge of the waste, raw

-------
3-19
materials, and production processes. The Agency expects that many generators will rely on
the latter method, and elect not to perform the TCLP. The Agency is still considering
promulgating a testing requirement at a future date. If a testing requirement is proposed,
potential costs of testing will be analyzed in detail.
Another cost, not included, that may be incurred by some facilities that choose to land
dispose wastes is the cost of performing a RCRA Facility Investigation (RFI) in conjunction
with the Subtitle C corrective action program. This cost was not included because it is
highly variable and because the number of facilities that may incur this cost is
unpredictable.
3.4.5	Waste Quantities Exhibiting the TC
As described in Sections 2.2.1 and 2.4.3, EPA tested the driving constituent
assumption by adding together the percentages of the wastestream exhibiting the TC for
each constituent in the wastestream. Since the quantity of waste exhibiting the TC was
extremely insensitive to this assumption, all downstream results - including costs - were also
insensitive to this assumption. For example, the total social costs of the rule increased by
less than 1 percent under this sensitivity analysis.
3.4.6	Wastewaters Managed in Surface Impoundments
As discussed in Chapter 2, only wastewaters managed in surface impoundments are
potentially affected by the TC rule. To estimate what quantities of wastewater are managed
in surface impoundments and how many facilities use surface impoundments, the Agency
used industry-specific percentages from the screening survey of facilities managing
wastewaters in surface impoundments for both small and large facilities. These
percentages were applied to both wastewater quantities and numbers of facilities generating
wastewaters to estimate potentially affected waste quantities and numbers of affected
facilities. EPA considered the possibility that this methodology could underestimate affected
waste quantities and numbers of affected facilities.
For sensitivity analysis, EPA assumed all wastewaters are managed in surface
impoundments to produce an upper bound of affected wastewater quantities and costs
associated with them. As with other sensitivity analyses, the DAF 100 option results were
tested. As noted in Chapter 2, this alternative assumption increased estimates of total
affected wastewater quantity significantly. Increases in cost estimates, however, were not as
significant. They would be potentially significant if facilities incur additional Subtitle C costs
for surface impoundment closure (see Section 3.4.9).
Under the assumption that all wastewaters are managed in surface impoundments,
total social costs of the rule increased by about 10 percent for the OAF 100 option.
Compliance costs to industry increased for all industries generating affected wastewaters.
The extent of the increase depended on whether or not there were significant costs
associated with sludges in any particular industry, because sludges drove costs where there
were significant sludge quantities affected. For example, for large facilities in both the Pulp
and Paper sector and the Petroleum Refining sector, compliance costs increased by only
about 1 percent. On the other hand, in the Hosiery and Knit Fabric Finishing sector there
were very small quantities of sludge affected, and the increase in wastewater costs resulted
in a doubling in total compliance costs for the sector.

-------
3-20
3.4.7	Distribution of Affected Waste Quantities to Large ami Small Facilities
In the absence of facility-specific data, waste quantities were distributed between large
and small facilities using value of shipments data. This assumption tends to assign
relatively small quantities of waste to small facilities, which might result in an underestimate
of the costs and impacts experienced by small facilities.
In order to test the sensitivity of the waste distribution assumption, the Agency
analyzed the DAF 100 option using the alternative assumption that small facilities in each
industry generate 50 percent of total industry waste. (Using the value of shipments
assumption, quantities assigned to small facilities ranged from one to 45 percent, with the
majority being less than 10 percent.)
Using the 50/50 (portion of waste generated by small/large facilities) distribution
assumption for the OAF 100 option, social costs of the rule increased by a little over five
percent. The resulting general increase in estimates of social costs is attributable to lost
economies of scale. When distributing wastes by value of shipments, large facilities were
almost always assigned greater than 50 percent of waste generation. Wastes quantities
assigned to large facilities in the initial analysis are not managed as efficiently when spread
among the greater number of small facilities.
Under the 50/50 distribution assumption, compliance costs to industry generally
decreased for large facilities because waste quantities per facility were smaller. The smaller
waste quantities managed result in lost economies of scale for some industries; for example
fewer large facilities choose to manage on-site, which indicates they no longer had an
option more economical than off-site management Compliance costs to industry increased
significantly for small facilities. For example, for small facilities, in Pulp and Paper costs
were 7 times higher than in the initial analysis, in Plastics and Resins 5 times higher, in
Synthetic Rubber 7 times higher, and in Pharmaceuticals 10 times higher.
3.4.8	Percentage of Facilities Affected
The number of affected facilities is a determinant of the quantity of waste exhibiting the
TC per facility, because affected waste quantities are spread over the number of affected
facilities as described in Chapter 2. This estimate of quantity of waste exhibiting the TC per
facility, in turn, is used as an input to the cost methodology.
EPA assumed that the percentage of facilities affected by the TC rule tor a
wastestream directly corresponds to the percentage of waste that exhibits the TC. For
example, if 10 percent of a wastestream exhibits the TC, then 10 percent of the facilities
generating that wastestream are potentially affected by the TC rule.1 Clearly, if none or all
of a wastestream exhibits the TC, then no facilities or an facilities are affected by the rule
because of that wastestream. The Agency examined two alternative assumptions for
intermediate percentages of wastestreams that exhibit the TC, for the purposes of the
sensitivity analysis. The sensitivity analysis was performed on the OAF 100 option.
1 For wastewaters, the number of fadNtos affected is funhar adjurted to account tor the fact
that only some facilities are currently managing wa^e^ iq pucface impoundments.

-------
3-21
First, EPA assumed that if an intermediate percentage (not 0 percent or 100 percent)
of a wastestream exhibited the TC, then 10 percent of facilities generating that wastestream
would potentially be affected. This would tend to test the implications of distributing larger
quantities of waste to fewer facilities. Second, the Agency assumed that if an intermediate
percentage of a wastestream exhibited the TC, then 90 percent of facilities generating that
wastestream potentially would be affected. The total amount of waste affected by the TC
was held constant. Thus, the two alternative assumptions give an upper and lower bound
of affected facilities and associated costs.
The analysis was much more sensitive to the first alternative assumption (set
intermediate percentages to 10 percent) than to the second (set intermediate percentages
to 90 percent). For many industries (e.g., Sawmills and Planing mills, Plastics and Resins,
Synthetic Rubber, Synthetic Fibers) wastestreams driving costs were exhibiting the TC in
very large percentages. This resulted in comparatively low sensitivity to the 90 percent
assumption, (if, for example, 95 percent of a wastestream exhibits the TC, assuming that
90 percent of facilities are affected was quite close to the assumption in the initial analysis.)
Setting intermediate percentages to 10 percent reduced the total social costs of the
rule by 48 to 55 percent, while setting intermediate percentages to 90 percent resulted in
only a one percent decrease. The significant decrease in total social costs under the 10
percent assumption resulted from economies of scale; fewer facilities are managing larger
quantities of waste and doing so more efficiently than a greater number of facilities would.
Compliance costs to industry decreased very significantly under the 10 percent
assumption, especially for large facilities. For example, the decrease was over 70 percent
for large facilities in Pulp and Paper, Synthetic Fibers, and Petroleum Refining. Decreases
were smaller in other industries, but still significant (e.g., 40 percent in Plastics and Resins,
53 percent in Synthetic Rubber, 18 percent in Organic Chemicals, and 3 percent in
Wholesale Petroleum Marketing). For small facilities, the decreases in compliance costs
ranged from negligible to approximately 25 percent
Compliance costs to industry did not vary as significantly for the 90 percent
assumption as for the 10 percent assumption. Also, compliance costs increased in some
cases, while decreasing in others. Changes in compliance costs were generally less than
10 percent
3.4.9 AddMorari Costs for Wastewaters Msnsgsd in Surfscs Impoundments
On the effective dats of ths TC, facilities managing affected wastewaters will be
required to manege ths wastss in s manner psrmissibls under Subtitle C. To calculate the
post-regulatory costs of managing wastewaters affected by ths TC, EPA assumed that
facilities would convert to wastewater tanks for management of TC wastewaters (See
Section 3.2.) Wastewater treatment tanks operated by facilities subject to regulation under
the Clean Water Act are exempt from Subtitle C permitting and interim status standards (40
CFR 264.1 (g)(6) and 40 CFR 266.1 (c)(10)).
The Agency calculated costs presented in Section 3.3. based on the assumption that
affected facifities would be able to switch from surface impoundment management to tank
management for TC wastewaters within six months of the promulgation of the final rule (i.e.,
by ths effective dats of ths mis). As an upper bound scenario, ths Agency examined the

-------
3-22
possibility that some facilities could not accomplish the switch to tank management by the
effective date of the rule. These facilities would incur additional costs.
EPA examined potential additional costs to facilities not able to switch to tank
management by the effective date of the rule based on the following scenario;
•	Facilities choose to install new wastewater tanks for management of wastewaters
that exhibit the TC, but they are not able to have the new units operable by the
effective date of the rule.
•	Facilities either obtain interim status by submitting a Part A permit application
(newly regulated facilities), obtain permit modifications (permitted facilities), or file
amended Part A permit applications (interim status facilities) in order to continue
surface impoundment management.
•	For the period of time between the effective date of the rule and the operation
date of new units, surface impoundment management continues.
•	Since surface impoundments used for managing the waste newly designated as
hazardous under the TC will have received hazardous waste, they will require
Subtitle C closure.
¦	Some facilities newly brought into the RCRA Subtitle C system may require
corrective action, either immediately or in the future.
This scenario represents a least-cost scenario for facilities that are not able to install
operable wastewater treatment tanks within six months. Other options exist, e.g.,
construction of new Subtitle C surface impoundments or retrofitting existing surface
impoundments within four yean to meet Subtitle C minimum technology requirements, but
in most cases these would be more costly than the above scenario.
The upper bound analysis consisted of two basic steps:
¦	Estimate the number of facilities that might not be able to achieve tank
management of TC wastewaters within six months.
¦	Estimate the additional costs incurred by facilities that would be unable to install
operable tank units within six months.
The specific methodology and assumptions used to conduct these steps of the upper
bound analysis are det&Hed in Appendix H. Under the OAF 100 option, 175 facilities are
estimated to incur additional costs for TC wastes managed In surface impoundments; 168
facilities are predicted to incur additional costs under the DAF 250 option. Exhibit 3-10
presents upper bound annual compliance cost estimates, based on adding extra costs for
TC wastes managed In surface impoundments, for the DAF 100 option and DAF 250
options. Compliance costs increase by 60 percent under the DAF 100 option, and more
than double under the DAF 250 option.

-------
EXHIBIT 3-1Q
TOTAL COSTS TO INDUSTRY FOR EACH OPTION ($ MILLION)
OPTION
WASTEWATER
COST
WASTEWATER COST
WITH ADDITIONAL
COSTS FOR SIS*
NON-WASTEWATER
COST
TOTAL
COST
TOTAL COST
WITH ADDITIONAL COSTS
FOR SURFACE IMPOUNDMENTS
100
7.1
150
250
250
400
250
6.6
150
110
110
260
'ADDITIONAL SURFACE IMPOUNDMENT COSTS INCLUDE SUBTITLE C LANDFILL CLOSURE AND EXPECTED CORRECTIVE ACTION COSTS FOR
SURFACE IMPOUNDMENTS NOT ABLE TO BE CONVERTED TO TANKS WITHIN SIX MONTHS.

-------
CHAPTER 4
ECONOMIC IMPACTS
Chapter 4 assesses the economic impacts of the final Toxicity Characteristic rule.
These impacts reflect the difference between projections of industry performance in the
absence of the regulation (baseline conditions) and projections of industry performance
following compliance with the regulation. The imposition of the regulation will have direct
impacts on an industry when compliance requires expenditures that will not contribute
directly to improved operating efficiency or will require excessive price increases. In these
cases, the regulation results in lower industry profits, a lower return on investment, and a
reduced capacity for affected establishments to compete as sellers in product markets and
as buyers in capital markets.
For each industry included in the TC RIA database, EPA collected financial data for
both small and large establishments. Theue financial data were used with the Agency's
compliance cost estimates to calculate two ratios for small and large model establishments
in each industry: the cost of production ratio (COP ratio) and the cash from operations
ratio (CFO ratio). The COP ratio is a surrogate for the percentage price increase necessary
for a producer to pass all compliance costs through to buyers; the CFO ratio is a surrogate
indicator of the ability of the producer to absorb compliance costs if no price increase is
possible. EPA used these ratios to identify those facilities that may suffer significant
economic impacts as a result of the TC rule.
This chapter also includes a separate assessment of impacts on small entities, as
required by the Regulatory Flexibility Act (5 USC 601 et segj. Although "small entities" are
defined as including small businesses, small organizations, and small government
jurisdictions, because of data limitations, only effects on small businesses were addressed
in this analysis. The relative impacts of the TC rule on small and large businesses were
evaluated by examining another ratio, the value of shipments ratio (VOS ratio), for
establishments in each size category.
Chapter 4 first explains the methodology used by the Agency to predict economic
impacts from the TC rule. Next, the overall results of the analysis are presented. The third
section focuses on the analysis of impacts on small businesses. The last three sections
discuss the BmHations of EPA's economic impacts analysis, implications of sensitivity
analyses as they pertain to economic impacts, and range estimates for economic impacts.
4.1 METHODOLOGY
EPA collected aggregate financial data for each of the Standard Industrial
Classification codes (SICs) included in the RIA and derived financial parameters for small
and large model facilities. These parameters were compared with estimated compliance
costs to predict facility impacts. This section provides a detailed explanation of the data
collection process and the ratios used in the analysts.

-------
4-2
4.1.1 Sources of Financial Data
EPA collected financial data for this analysis primarily from the Annual Survey of
Manufactures (1985), the most recent source available, and the Census of Manufactures
(1962). Both references contain data by SIC code on the total number of employees, total
cost of materials, total value of shipments, and total payroll for the year. However, the
Census of Manufactures includes some types of data that are not reported in the Annual
Survey, such as the total number of establishments in the SIC, and establishment size by
number of employees. The Census also presents the financial data distributed by
establishment size. EPA chose to use the more recent data from the Annual Survey, but to
distribute them to small (less than 50 employees) and large (50 or more employees)
establishments according to the proportions indicated in the 1982 data.
The total number of establishments for each SIC in 1965 was estimated by dividing
the number of employees in 1985 by the average number of employees per establishment
from the 1982 Census data. Next, to approximate the numbers of small and large facilities,
EPA obtained the appropriate percentages of small and large facilities for each SIC from the
Census, and applied these to the derived 1985 total number of establishments. Similarly,
the 1985 total cost of materials, value of shipments, and payroll were distributed between
small and large facilities in each SIC according to the corresponding 1982 distributions.
The aggregate variable cost of production for each size category in each SIC was
calculated by adding the appropriate values for cost of materials and payroll, and the
aggregate cash from operations obtained by subtracting the variable cost of production
from the value of shipments. Because EPA calculated the costs of complying with the TC
rule in 1988 dollars, the producer price index (April 1988) was used to adjust all financial
data to 1988 dollars.
Because SICs 481 (Petroleum Pipelines) and 517 (Wholesale Petroleum Marketing)
are not manufacturing industries, data for these industries are not available in the Annual
Survey of Manufactures or the Census of Manufactures. Thus, it was necessary to use
alternative sources of information. For SIC 461, the Agency used data from the County
Business Patterns (1985) on the number of small and large establishments, number of
employees at small and large establishments, and payroll. EPA also extracted data from
the Statistical Abstract of the United States 1988 for "Petroleum Pipeline Companies," using
net income figures for "cash from operations," and operating revenues in lieu of "value of
shipments." The coat of production was then calculated by subtracting the cash from
operations value from the value of shipments. To distribute these variables to small and
large establishments, EPA used the percentages of employees al small and large
establishments from the County Business Patterns.
For SIC 517, EPA used the Census of Wholesale Trade (1982) to obtain the number
of small and large establishments, the number of employees at small and large
establishments, payroH, sales, operating expenses, and costs of goods sold. Cost of
production was calculated by adding cost of goods sold to operating expenses; sales were
assumed to be equivalent to value of shipments. These data were also adjusted to 1988
dollars with the producer price index (April 1988).

-------
4-3
4.1.2 Financial Ratios
The Agency's analysis of the economic impacts of the Toxicity Characteristic rule is
based on two financial ratios. The ratios were calculated on a per facility basis, using
model facilities from the TC RIA database. The cost of production ratio (COP ratio) is
defined as the annual compliance cost of the regulation divided by the annual variable cost
of production (cost of materials plus payroll). It represents the percentage increase in
product price that would be required for the establishment to pass the entire compliance
cost through to consumers in the form of higher prices. If the COP ratio is greater than
0.05 (i.e., prices would have to increase by more than 5 percent) the establishment is
considered to have significant impacts. Because the cost of production does not include
fixed costs such as rent and costs of capital, this ratio serves as a worst-ease screen. If
fixed costs were added, fewer firms would be predicted to have significant impacts.
The cash from operations ratio (CFO ratio) is defined as the cash from operations
(value of shipments minus variable cost of production) divided by the compliance cost. The
CFO ratio represents the number of times that an establishment's cash from operations
covers the regulatory compliance costs, if none of the compliance cost is passed through
to buyers via price increases. If the CFO ratio is less than 20, the establishment is
considered to have significant impacts. A CFO ratio less than 2 suggests a potential for
closure. Because the cost of production excludes fixed costs, this ratio also serves as a
screen. Establishments that have CFO ratios greater than 20 and thus show no impacts
would not necessarily yield CFO ratios as high if the fixed costs were added. If fixed costs
were added, more firms would be predicted to have significant impacts.
Both criteria for significance (i.e., COP > 0.05 and CFO < 20) provide a general
point of reference but do not apply uniformly across industries. The ability of an
establishment to pass compliance costs through to buyers depends on whether competing
firms (producing identical or substitute products) incur similar costs and on overall
competitive conditions in the relevant product market. Establishments that sell products in
highly competitive markets may suffer significant impacts if they attempt to increase their
product prices even by less than S percent (COP ratio < 0.05). On the other hand, the
ability of an establishment to absorb compliance costs by accepting lower profits depends
on how competitive the establishment needs to be in capital markets. Establishments that
are involved in capital-intensive production and rely to a large extent on investment funds
may have significant impacts if returns to capital fall significantly.
4.2 RESULTS OF OVERALL ECONOMIC IMPACT ANALYSIS
In this section, the Agency presents the results of its economic impact analysis in
two parts. Section 4.2.1 provides estimates for each regulatory option of the total number
of establishments in all industries that are expected to incur significant impacts and the
number of potential closures. In Section 4.2.2, the specific industries suffering significant
economic impacts from the TC rule are discussed separately, with attention given to
possible changes in market conditions attributable to the impacts.

-------
4-4
4.2.1 Number of Establishments with Significant Economic Impacts
The results of the analysis for each regulatory option are presented in Exhibits 4-1
through 4-5. Exhibit 4-5 provides a comparison of the estimated significant economic
impacts across the options.
The total number of establishments predicted to experience significant impacts as a
result of the final TC rule ranges from 29 under the OAF 250 and DAF 500 options to 86
under the DAF 33 option. No facility closures are expected under any of the options
examined. Under the OAF 100 option, 65 facilities (51 large and 13 to 14 small) are
predicted to have significant impacts. As can be seen in Exhibit 4-2, these facilities are in
four industries: Pulp and Paper (SIC 26XX), Synthetic Rubber (SIC 2622), Synthetic Fibers,
Cellulosic (SIC 2823), and Organic Chemicals (SIC 286). Twenty-nine facilities (21 large and
8 small) may experience significant impacts under the OAF 250 option. The 29 facilities
affected under the DAF 250 option are in two industries; Synthetic Rubber and Synthetic
Fibers, Cellulosic (SIC 2823). The same thirteen Synthetic Rubber facilities and 16 Synthetic
Fibers, Cellulosic facilities are affected under both the DAF 100 and DAF 250 options. The
difference between the DAF 100 and OAF 250 options is that 35 facilities in the Pulp and
Paper industry and one facility in the Organic Chemicals industry are significantly affected
under the OAF 100 option but not under the DAF 250 option. It is worth noting that the 16
facilities in the Synthetic Fiber, Cellulosic industry, which are significantly affected under all
options, comprise all of the facilitigs in that industry.
For all of the regulatory options, the total number of large facilities with significant
economic impacts is greater than the number of small facilities, by a margin of roughly
three to one. This outcome appears counterintuitive, because-it is generally presumed that
smaller facilities have less efficient production processes and are more likely to be affected
by regulatory costs than large facilities. Two reasons, however, account for the
predominance of large facilities in this analysis. One is the fad that two of the industrial
sectors with significantly affected establishments have many more large establishments than
small establishments. The Pulp and Paper Mill sector (SIC 26XX), which is the major
contributor to the pool of significantly affected facilities, includes over 5 times as many large
facilities as small facilities. The CeMuiosic Synthetic Fibers industry (SIC 2823), according to
the extrapolations from the 1962 Census of Manufactures data, contains no small
establishments at all. The second explanation for the preponderance of large facilities with
significant impacts Ilea in the observation that, in the model used for this RIA that assumes
waste quantities are proportional to value of shipments, large facilities generally produce
much greater quantities of waste than small facilities, and thus would incur much higher
compliance costs. Possible economies of scale, which could lower waste management
costs, are not sufficient to offset the differential in compliance costs which result from
differentials in waste generation quantities.
m.9.9 industries wWli Significant Impacts
The industries containing establishments that may have significant economic impacts
under the regulatory options presented are Pulp and Paper (SIC 26XX); Synthetic Rubber
(SIC 2622); Cellulosic Synthetic Fibers (SIC 2823); and Organic Chemicals (SIC 286). Each
of these industries is considered separately below, with qualitative discussion of possible
effects on market conditions where appropriate.

-------
EXHIBIT 4-1
NUMBER OF ESTABLISHMENTS WITH SIGNIFICANT ECONOMIC IMPACTS (DAF 33)



TOTAL NUMBER OF



NUMBER OF


TOTAL NUMBQR OF
ESTABLISHMENTS
NUMBER OF
NUMBER OF
TOTAL NUMBER OF
ESTABLISHMENTS

FACILITY
ESTABLISHMENTS
INCURRING COMPLIANCE
ESTABLISHMENTS
ESTABLISHMENTS
ESTABLISHMENTS WITH
CFO RATIO <2
SIC
S17F
IN INDUSTRY
COSTS (a)
COP RATIO >.05
CFO RATIO <20
SIGNIFICANT IMPACTS
(POTENTIAL CLOSURES)
26XX
LARGE
500
132
16
46
46
0

SMALL
90
23
4
8
8
0
2822
LARGE
30
7
0
5
5
0

SMALL
47
10-11
1
9
9
0
2823
LARGE
16
16
0
16
16
0
286
SMALL
520
88-358
0
0-2
0-2
0
TOTAL*
LARGE
550
155
16
67
67
0

SMALL
660
121-392
5
17-19
17-19
0
(a) WHERE RESULTS FROM MINIMUM AND MAXIMUM MODEL FACILITIES SCENARIOS DIFFER, RANGE REPORTED
•TOTALS MAY NOT ADD DUE TO ROUNDING

-------
EXHIBIT 4-2
NUMBER OF ESTABLISHMENTS WITH SIGNIFICANT ECONOMIC IMPACTS (DAF100)



TOTAL NUMBER OF



NUMBER OF


TOTAL NUMBBI OF
ESTABLISHMENTS
NUMBER OF
NUMBER OF
TOTAL NUMBER OF
ESTABLISHMENTS

FACILITY
ESTABLISHMENTS
INCURRING COMPLIANCE
ESTABLISHMENTS
ESTABLISHMENTS
ESTABLISHMENTS WITH
CFO RATIO <2
IMA
OA#
RI7P
IN INDUSTRY
COSTS (a)
COP RATIO >.06
CFO RATIO <20
SIGNIFICANT IMPACTS
(POTENTIAL CLOSURES)
26XX
URGE
500
49
9
30
30
0

SMALL
90
8
0
5
5
0
2822
LARGE
30
6
0
5
5
0

SMALL
47
9
0
8
8
0
2823
LARGE
16
16
0
16
16
0
286
SMALL
520
86-338
0
0-1
0-1
0
TOTAL*
URGE
550
71
9
51
51
0

SMALL
660
105-355
0
13-14
13-14
0
(a) WHERE RESULTS FROM MINIMUM AND MAXIMUM MOOEL FACILITIES SCENARIOS DIFFER, RANGE REPORTED
•TOTALS MAY NOT ADD DUE TO ROUNDING

-------
EXHIBIT 4-3
NUMBER OF ESTABLISHMENTS WITH SIGNIFICANT ECONOMIC IMPACTS (DAF 250)



TOTAL NUMBER OF



NUMBER OF


TOTAL NUMBER OF
ESTABLISHMENTS
NUMBER OF
NUMBER OF
TOTAL NUMBER OF
ESTABLISHMENTS

FACILITY
ESTABLISHMENTS
INCURRING COMPLIANCE
ESTABLISHMENTS
ESTABLISHMENTS
ESTABLISHMENTS WITH
CFO RATIO <2
SIC
RI7F
IN INDUSTRY
COSTS (a)
COP RATIO >.05
CFO RATIO <20
SIGNIFICANT IMPACTS
(POTENTIAL CLOSURES)
2822
LARGE
30
6
0
5
5
0

SMALL
47
9
0
8
8
0
2623
LARGE
16
16
0
16
16
0
TOTAL
LARGE
46
22
0
21
21
0

SMALL
47
9
0
6
8
0
(a) WHERE RESULTS FROM MINIMUM AND MAXIMUM MODEL FACILITIES SCENARIOS DIFFER, RANGE REPORTED

-------
EXHIBIT 4-4
NUMBER OF ESTABLISHMENTS WITH SIGNIFICANT ECONOMIC IMPACTS (DAF 500)



TOTAL NUMBER OF



NUMBS) OF


TOTAL NUMBER OF
ESTABLISHMENTS
NUMBER OF
NUMBER OF
TOTAL NUMBER OF
ESTABLISHMENTS

FACILITY
ESTABLISHMENTS
INCURRING COMPLIANCE
ESTABLISHMENTS
ESTABLISHMENTS
ESTABLISHMENTS WITH
CFO RATIO <2
SIC

IN INDUSTRY
COSTS (a)
COP RATIO > 05
CFO RATIO <20
SIGNIFICANT IMPACTS
(POTENTIAL CLOSURES)
2822
LARGE
30
6
0
5
3
0

SMALL
47
S
0
8
8
0
2823
LARGE
16
16
0
16
16
0
TOTAL
LARGE
46
22
0
21
21
0

SMALL
47
9
0
8
8
0
(a) WHERE RESULTS FROM MINIMUM AND MAXIMUM MODEL FACILITIES SCENARIOS DIFFER, RANGE REPORTED

-------
EXHIBIT 4-5
NUMBER OF ESTABLISHMENTS WITH SIGNIFICANT ECONOMIC IMPACTS


TOTAL FOR ALL INDUSTRIES






NUMBER OF
REGULATORY

NUMBER OF
NUMBER OF
TOTAL NUMBER OF
ESTABLISHMENTS
OPTION
FACtUfY
ESTABLISHMENTS
ESTABLISHMENTS
ESTABLISHMENTS WITH
CFO RATIO <2
(OAF)
SIZE
COP RATIO >.05
CFO RATIO <20
SIGNIFICANT IMPACTS
(POTENTIAL CLOSURES)
33
LARGE
16
67
67
0

SMALL
5
17-19
17-19
0
100
LARGE
9
51
51
0

SMALL
0
13-14
13-14
0
250
LARGE
0
21
21
0

SMALL
0
8
8
0
500
LARGE
0
21
21
0

SMALL
0
8
8
0
(a) WHERE TOTALS FROM MINIMUM AND MAXIMUM MODEL FACILITIES SCENARIOS DIFFER. RANGE REPORTED

-------
4-10
4.2.2.1 Pulp and Paper Industry (only facilities with pulping operations: SIC 26XX1
In this sector, significantly affected facilities are expected under the DAF 33 and DAF
100 options. Pulp and paper mills are the most numerous type of establishment among
those expected to be significantly affected under the DAF 33 and DAF 100 options. Under
these two options, the Pulp and Paper industry accounts for 50 to 60 percent of
establishments with significant economic impacts. No pulp and paper mill facilities are
expected to close under any of the regulatory options.
SIC 26 encompasses the large number of firms which process fibers from trees,
wastepapers and other materials into pulp, paper, and paperboard products. Millions of
metric tons of wastes are produced during the overall production process, but EPA's
analysis predicts that the wastes which will exhibit the TC are limited to those generated in
one general process category-the wastewaters end wastewater treatment sludges derived
from chemical pulping and bleaching operations.
The primarily Southern-based pulp mill sector is capital-intensive, which suggests
that the market is difficult to enter. This factor and the expectation that demand for paper
will remain strong suggest that much of the cost incurred by pulp manufacturers due to the
TC can be passed on to buyers in the short term. However, domestic pulp producers are
facing growing competition from foreign producers with lower labor costs and weaker local
currencies, and this implies less ability to pass costs forward to buyers. Rapid expansion in
the industry has created excess capacity which will only be exacerbated by predicted
increases in recycling. Combined, these factors suggest that some portion of compliance
costs mil be passed on to buyers in the form of higher prices, and the remainder will be
absorbed by pulp manufacturers in the form of lower profits.
4.2.2L2 Synthetic Rubber Industry fSIC 28221
The numbers of establishments expected to suffer significant impacts in this industry
are five large and nine small for the DAF 33 option, and five large and eight small for the
other three options. In this relatively small industry (30 large and 47 small establishments
total), these numbers constitute about 20 percent of the total number of facilities in the
industry.
The Synthetic Rubber industry is composed predominantly of divisions or
subsidiaries of major rubber product manufacturers, chemical companies, and oil
companies. Its principal inputs are derivatives of crude oil or natural gas, and it is therefore
designated as a petrochemical industry. Synthetic rubbers are defined as rubber-like
materials produced by polymerization or copotymerization, and capable of vulcanization.
There are three major operations within synthetic rubber production: emulsion crumb
production, solution crumb production, and latex production. TTie Agency's analysis for the
DAF 100 option predicts that some wastewaters from all three processes (over 99 percent
of emulsion and solution crumb wastewaters, but less than one percent of latex
wastewaters), as well as wastewater treatment sludges from the solution crumb process, will
exhibit the TC.
The largest markets for synthetic rubber are tires and various fabricated products for
motor vehide production and use. Recently, imports of rubber products and automobiles,
along with substitution of plastic materials, have suppressed domestic demand for general

-------
4-11
purpose synthetic rubbers. The promulgation of the TC could therefore significantly affect
the profit levels of some synthetic rubber producers, who will likely be forced to carry most
of the cost of regulation themselves. Thus far, falling petroleum prices have helped enable
manufacturers to maintain profits in the face of reduced demand, but petroleum market
stability is difficult to predict.
4.2.2.3	Cellulosic Synthetic Fibers Industry (SIC 2823^
EPA's analysis indicates that all establishments in the industry (16 large
establishments) may face significant economic impacts under all of the regulatory options.
No facilities are expected to close, however, under any of the regulatory options.
SIC 2823 contains establishments which manufacture cellulosic fibers (such as
cellulosic acetate and rayon) in the form of monofilament, yarn, staple, or tow. In the
production process, naturally occurring polymeric materials, such as cellulose, are dissolved
or dispensed into an appropriate solvent, and then spun into fine filaments. These
filaments are further processed in other textile industries on spindles, looms, knitting
machines, and other equipment. EPA's analysis predicts that with a DAF of 100, over 99
percent of the wastewaters generated in the industry will exhibit the TC. primarily due to the
presence of benzene in waters from the production of acetate. Wastewater treatment
sludges will also exhibit the TC.
In recent years, domestic demand for synthetic fibers has been dampened by
increasing apparel imports and consumer preference for natural fibers. In response, both
the Cellulosic and Noncellulosic Synthetic fiber industries have reduced productive capacity,
and diversified into more industrial and household product areas. The implementation of
the TC could affect the industry, as higher costs drive textile manufacturers away from
cellulosic synthetic fibers altogether, and toward noncellulosic and natural fibers. Unless
technological adjustments make it possible to reduce the amount of hazardous waste
generated, the industry is likely to experience reductions in profit levels.
4.2.2.4	Organic Chemicals Industry (SIC 286)
For the DAF 33 and DAF 100 options, one or two small establishments are expected
to face significant economic impacts. Because the number of small facilities in this
industrial sector is relatively large (515), these one or two significantly affected small
facilities comprise less than one percent of the total number of small facilities in the
industry. Agency analysts predicts no facility closures in this industry.
Die Organic Chemicals industry is a leading sector of the U.S. economy, with its
products feeding into hundreds of other industrial sectors. Over 90 percent of its output is
based on petroleum or natural gas, and the remainder originates from coal or agricultural
products. Principal products include derivatives of ethylene, propylene, benzene, toluene,
xylene and methane. Because of the great diversity of organic chemicals and production
processes, it was necessary to limit the evaluation of waste to that generated torn the
production of major chemicals, and examine only the generic early feedstock processes to
identify those with currently non-hazardous wastestreams potentially containing one or more
of the proposed TC constituents. EPA's analysis predicts that over half of the selected
wastestreams would exhibit the TC, in portions ranging from less than one percent to over
99 percent.

-------
4-12
The demand tor the products of the organic chemicals industry has grown at a
relatively modest average rate of about three percent over the last few years. Because of
its major role as a supplier to other industries, growth in SIC 286 generally reflects the
overall growth of the national economy. In recent years, the industry benefited from lower
oil and natural gas prices, which lead to higher profit margins. Also, the decline in the
value of the U.S. dollar helped the domestic industry's international trade position relative to
that of foreign competitors. This latter factor may become less significant, however, as the
dollar regains strength, and as energy-rich developing countries such as Saudi Arabia and
Kuwait, as well as the Pacific Rim countries, develop their chemical industries. The value of
the U.S. dollar has relatively little effect on the prices of chemicals exported by these
countries, which have very low production costs, relative to the U.S. Unless the overall
economy expands significantly, the TC will have an effect on the organic chemicals
industry, as firms will be limited in how much of the cost posed by the regulation can be
passed on to consumers. Domestic producers will have to squeeze profit margins in order
to maintain competitiveness with foreign firms. Another induced effect might be a decrease
in the demand for chemicals that are TC constituents, if chemical users switch to
substitutes so that their wastes will not exhibit the TC.
4.3 SMALL BUSINESS ANALYSIS
The Regulatory Flexibility Act requires Federal agencies to analyze the effect of their
regulations on small entities and to examine ways to minimize adverse economic effects on
this group. The act requires agencies to prepare an initial Regulatory Flexibility Analysis
(RFA) to accompany any notice of proposed rulemaking (see USC 603). A final RFA that
incorporates public comment must accompany a final rule. The purpose of the RFA is to
evaluate the impact of rules on small entities. The Act specifies that the RFA must identify
the categories of small entities affected by the regulation and analyze alternatives that may
reduce the economic burden on these small entities without compromising the goals of the
rule. An exemption from the requirement for preparing a full RFA is available if the Agency
can certify that the rule will not have a significant economic impact on a substantial number
of small entities (see 5 USC(b)).
The Regulatory Flexibility Act defines 'small entities" as including small businesses,
small organizations, and small government jurisdictions. However, no organizations fitting
the latter two definitions were identified in the industry and wastestream reports prepared
for the TC RIA. Therefore, EPA addresses only impacts on small businesses in this
analysis.
4.3.1 Criteria end Methodology
This analysis examines whether the TC rule will significantly affect a substantial
number of small businesses, and hence whether a full RFA Is required. EPA has issued
guidelines for making this determination in accordance with the requirements of the
Regulatory Flexibility Act1 The guidelines address procedures for:
1 Memorandum from the EPA Administrator to Associate Administrators, Assistant
Administrators, Regional Administrators, and Office Directors, 'EPA Implementation of the Regulatory
Flexibility Act,* February, 1982.

-------
4-13
¦ Identifying the small entities affected by the rule;
•	Determining if a "substantial number" of small entities are
affected by the rule; and
•	Evaluating if the rule has "significant" impacts on these small
entities.
The Regulatory Flexibility Act defines small businesses as those firms that satisfy the
criteria established under Section 3 of the Small Business Act. The Agency may use an
alternative definition of "small business" after consultation with the Small Business
Administration (SBA) and public comment. The SBA criteria apply to firm size, whereas the
impact analysis for this rule is conducted at the plant or facility level. For single-plant firms,
the SBA criteria can be applied using information from the U.S. Census or other sources on
the number of employees at the establishment level. For firms owning more than one plant,
applying the SBA criterion at the firm level implies use of a lower employee definition of
small business at the facility or plant level. Development of alternative size definitions for
each industry would require considerable analysis of the economic structure of each
industry. Lacking this detailed information, EPA used a single 50-employee cut-off to define
small facilities. Financial data came primarily from the Census of Manufactures and Annual
Survey of Manufactures.
As noted previously, the Regulatory Flexibility Act specifies that a full RFA is required
only if a substantial number of small entities is likely to suffer significant adverse economic
impacts. The Act does not specify, however, the criteria for determining if a "substantial
number" of small entities are significantly affected. The Agency has established a standard
threshold of 20 percent; if the proposed rule has a significant impact on 20 percent or more
of the universe of small entities subject to the regulation, then an RFA is required.
The EPA guidelines suggest that four criteria be applied to evaluate whether a
regulation will have a significant impact on a small entity. Satisfaction of any of the criteria
indicates a significant impact. The four criteria are as follows:
1.	Annual compliance costs increase the relevant production costs for
small entities by more than five percent;
2.	The ratio of compliance costs to sales will be 10 percent higher for
small entities than for large entities;
3.	Capital costs of compliance represent a significant portion of the
capital available to small entities, taking into account internal cash flow
plus external financing capabilities; and
4.	The costs of the regulation are likely to result in closure of small
entities.
In applying the first and fourth criteria, the COP and CFO ratios for small facilities
were used. A COP ratio of greater than 0.05 would satisfy the first measure, and a CFO
ratio of less than two would indicate closure and satisfy the fourth. The third measure, the

-------
4-14
effect of compliance costs on capital availability, was not employed, due to the absence of
facility-specific data.
For the second criterion, comparing the ratios of compliance costs to sales for large
and small facilities, industry-level ratios were calculated. Value of shipments (VOS) was
used as a proxy for sales (the ratios are hereafter referred to as VOS ratios). Once the
VOS ratios are calculated, however, the EPA guidelines are ambiguous with respect to the
specific methodology of the comparison. The language of the guidelines leaves open the
question of whether the test for the ten percent difference should involve the subtraction of
the large facility VOS ratio from the small facility VOS ratio or the division of the small
facility ratio by the large facility ratio. The division approach may be somewhat misleading,
as it could indicate significant impacts on small facilities in cases where small facility
compliance costs are only a minuscule percentage of sales, but the corresponding
percentage is even lower for large facilities. For this reason, the subtraction approach was
used in this analysis, but the division approach was examined as well.
4.3.2 Results of Small Business Analysis
The results of EPA's small business analysis for the TO rule are presented in Exhibit
4-6. The comparison of small and large VOS ratios shown in the table uses the subtraction
approach. Under none of the regulatory options do 20 percent or more of small
businesses suffer significant impacts according to the criteria listed above. In fact, the only
regulatory option under which EPA identified any small businesses with significant impacts
was the DAF 33 option, and the total number of these businesses was just 5,
corresponding to a percentage of 0.01. For no industries, under any of the regulatory
options, was the difference of VOS ratios larger than 10 percentage points.
Using the division approach for comparing the VOS ratios, EPA observed that small
businesses in four sectors (Pulp and Paper, Synthetic Rubber, Organic Chemicals, and
Wholesale Petroleum Marketing) appeared to suffer significant impacts. However, because
in all cases both facility VOS ratios were low (no small facility ratio was greater than 0.03),
the Agency does not consider the results of the division approach to be indicative of truly
significant impacts on small facilities. The Agency concludes therefore that the TC rule will
not result in significant impacts on a substantial number of small businesses, and that the
performance of a full Regulatory Flexibility Analysis is not required for this rule.
4.4 LIMITATIONS AND SENSITIVITY ANALYSIS
Since cost results (Chapter 3) were used' as input to the economic impacts analysis,
limitations of the cost methodology cany over to the economic impacts analysis. Any
significant overestimate or underestimate of costs could be paralleled by an overestimate or
underestimate of economic impacts, though not necessarily of corresponding magnitude.
Marty of the limitations of the cost estimates stemmed from assumptions necessary In the
characterization of affected wastes and facilities; the Agency conducted sensitivity analyses
on the most important of these assumptions.

-------
4-15
EXHIBIT 4-6
SMALL BUSINESSES SUFFERING SIGNIFICANT IMPACTS
VOS RATIO (small)- Total Number of	Percentage of
Regulatory	COP	CFO VOS Ratio (large) Small Businesses With Small Businesses With
Option	Ratio > .05 Ratio <2	> .10	Significant Impacts Significant Impacts
DAF 33
5
0
0
5
0.01%
DAF 100
0
0
0
0
0.00%
DAF 250
0
0
0
0
0.00%
DAF 500
0
0
0
0
0.00%

-------
4-16
4.4.1	Financial Ratios
Due to data limitations, the two financial ratios used here to determine if
establishments incur significant economic impacts are imperfect surrogates for better
theoretical measures. In the case of the cost of production (COP) ratio, use of the surrogate
results in an overestimation of the number of establishments that may incur significant
economic impacts. In the case of the cash from operations (CFO) ratio, use of the
surrogate results in an underestimation of the number of establishments that may experience
significant impacts.
A major source of error in both cases is the use of cost of production estimates that
exclude fixed costs such as rent, lease fees, debt service, depreciation, insurance, and
professional fees. Because the estimates of COP used in the analysis do not include these
costs, they are clearly lower than the true cost of production values. Similarly, the CFO
estimates, because they are calculated by subtracting COP from the value of shipments
(VOS), are higher than their true values.
The results of the bias introduced into the analysis by computing financial ratios on
the basis of ]ow COP estimates and high CFO estimates are as follows:
•	Low COP estimates will overstate impacts because compliance
costs will appear misleadingly large relative to the COP
estimates, resulting in the calculation of inflated COP ratios.
Compliance costs that may actually be very minor relative to total
production costs (including rent, debt service, insurance, etc.),
could appear to be quite high when compared to COP estimates
which include only operating costs and not fixed costs.
•	High CFO estimates will understate impacts because compliance
costs will appear deceptively small relative to the CFO estimates,
resulting in the calculation of misleadingly high CFO ratios.
Establishments with high fixed costs, for which covering the cost
of compliance could be a significant hardship, may not be
identified.
4.4.2	Predicting Significant Impacts on Small Facilities
Within the small business analysis, in addition to the COP and CFO ratios, the
subtraction and division approaches for comparing small and large facility VOS ratios could
also be cited as providing a potential for misperception. As explained in Section 4.3.1, the
division approach may indicate significant impacts on small businesses even when
compliance costs actually represent a very low percentage of the value of shipments for
small businesses, if the corresponding percentage for large businesses is even lower. For
this reason, the results of this approach should be interpreted with caution. One should
also be careful when using the subtraction approach, however, because it could lead to the
failure to recognize significant Impacts in cases where the small facility VOS ratio is very
high, but less than 10 percentage points higher than the large facility ratio. For instance, a
rule which imposed very high costs on all facilities in an industry (and thus significantly
affected the entire industry) could result in a small facility ratio of 50 percent and a large
facility ratio of 43 percent. Using the subtraction approach, which indicates small business

-------
4-17
impacts relative to large business impacts, would not indicate significant impacts for small
facilities.
4.4.3	Distribution of Affected Waste Quantity to Large and Small Facilities
As previously explained (Sections 2.3.1, 2.4, and 3.4) the Agency tested the
distribution of waste quantities between large and small facilities using value of shipments
data by alternatively assuming 50 percent of waste is generated by large facilities and 50
percent by small facilities. In conjunction with small facilities generating larger waste
quantities and incurring higher compliance costs, there were greater economic impacts for
small facilities when EPA assumed that small facilities generate 50 percent of wastes, About
40 additional small facilities were affected, with around 10 potential closures.
4.4.4	Percentage of Facilities Affected
The Agency conducted sensitivity analysis on the assumption that the percentage of
facilities affected by the TC equalled the percentage of total wastestream affected by
alternatively assuming (1) that 10 percent of facilities generate the total affected wastestream
quantity, and (2) that 90 percent of facilities generate the total affected wastestream quantity.
Economic impacts results were insensitive to the 90 percent assumption. On the
other hand, the 10 percent assumption slightly decreased impacts on large facilities and
increased impacts on small facilities, adding potential closures in Pulp and Paper and
Synthetic Rubber. Although total compliance costs to industry generally decreased under
the 10 percent assumption, costs per facility were higher, thus resulting in the increase in
impacts on small facilities.
4.4.5	Additional Costs for Surface Impoundments
EPA calculated an upper bound estimate of economic impacts by assuming 175
facilities incur costs for Subtitle C closure of surface impoundments. The Agency used the
upper bound compliance costs to calculate upper bound COP ratios and CFO ratios.
Adding surface impoundment closure costs to compliance costs (the upper bound
assumption) would cause additional facilities to be significantly affected. The upper bound
estimate of significantly affected facilities for the DAF 100 option is 81 total facilities (as
opposed to 65). The additional significantly affected facilities comprise the following: one
large facility in the Pulp and Paper industry (a potential closure), one large and one small
facility in the Synthetic Rubber industry, two large facilities in the Organic Chemicals industry,
one large facility in the Textiles industry, three large facilities in the Pharmaceuticals industry,
and seven large facilities In the Plastics and Resins industry.

-------
CHAPTER 5
BENEFITS
This chapter analyzes the benefits of regulating wastes that exhibit the toxicity
characteristic. The Agency examined three benefits measures: reduction in resource
damage, reduction in human health risks, and reduction in groundwater cleanup costs.
These benefits result from managing wastes that exhibit the TC in Subtitle C facilities rather
than in unregulated management facilities.
Section 5.1 describes the methodology for estimating the benefits measures. Section
5.2 presents our results in detail fcr each of the benefits measures under each regulatory
option. Section 5.3 discusses limitations of the methodology and Section 5.4 discusses the
results of sensitivity analyses of benefits.
5.1 METHODOLOGY
This section presents the methodology for estimating reductions in adverse effects to
human health and the environment under the TC rule. The methodology for estimating
these benefits of the TC has two major parts. First, it determines the adverse effects
resulting from the unregulated management of wastes, i.e., baseline damages. Then it
determines which of these adverse effects would not be present if the wastes were
regulated under the TC. The reductions in adverse effects constitute the benefits of the
rule. There are seven steps (shown in Exhibit 5-1) in determining the reductions in adverse
effects resulting from the regulation of wastes. These steps are described in detail below.
5.1.1 Selection of TC Wastes
For the benefits analysis. EPA selected a subset of the wastestreams in the TC RIA
database (described in Section 2). To formulate a baseline, EPA selected those
wastestreams that would be affected by the TC (i.e., wastestreams having some quantity of
waste with concentrations of at least one TC constituent above the regulatory level) under
the originally proposed rule (where regulatory levels were based on a dilution and
attenuation factor of 14).
The resulting baseline data set consists of 218 wastestreams. Of these wastestreams
127 are non-wastewaters (i.e., sludges/slurrys or solid residuals) and 91 are wastewaters
(i.e., aqueous liquids). Organic liquids are not included in this data set since management
of these wastes would not be affected by the regulation.

-------
EXHIBIT 5-1
Estimating Benefits of the TC Rule
Select wastes for
baseline which
potentially exhibit
the TC
\r
Characterize the
constituents and
management of
wastes in baseline
n
Assume baseline
and post-regulatory
management practices
for the wastes
Simulate exposure
concentrations and
plume areas in the
baseline
Calculate risk,
resource damage,
and cleanup costs
in the baseline
Determine which wastes
would be regulated
and contribute to
benefits of the TC
Determine reductions
in risk and resource
damage aod cleanup
costs avoided

-------
5-3
5.1.2 Characterization of Wastestreams
The wastestreams are characterized by the following information:
¦	Type of waste (wastewater or non-wastewater);
¦	Number of managing facilities;
¦	Constituent concentrations; and
¦	Risk-driving and resource damage-driving constituents.
After describing briefly ail of these elements, special assumptions for the number of
managing facilities and risk-driving constituents will be explained in more detail,
EPA identified the type of waste as either wastewater or non-wastewater because
different management practices are required for each. Wastewaters are assumed to be
managed in surface impoundments and non-wastewaters are assumed to be managed in
landfills or land application units. EPA also estimated the number of facilities managing TC
wastes because it is at the managing facilities that the risk and resource damage occur.
Individual wastestreams that may be subject to TC regulation are composed of multiple
constituents. Only those benefits associated with regulating the 25 constituents covered by
the regulatory options were assessed.
Risk-Driving Constituents. EPA determined which of the constituents in each
wastestream would result in the greatest carcinogenic risk and the greatest non-
carcinogenic exposure upon leaching into the ground water. These constituents are called
the "risk-driving" constituents. "Resource damage-driving" constituents are closely related to
them, and are defined in a similar manner.
Analyzing risk-driving and resource damage-driving constituents simplifies the benefits
estimation process without substantially reducing the accuracy of the results. EPA selected
risk-driving constituents by first calculating the mean concentration of each of the
constituents in each wastestream. Then, the corresponding leachate concentration was
calculated: for wastewaters, this is identical to the waste concentration; for non-wastewaters,
this is calculated by use of the Organic Leaching Model (discussed later in this section).
The Agency then calculated an exposure concentration for each constituent. The exposure
concentration is calculated by dividing the leachate concentration by a DAF of 100. The
exposure concentrations were then converted to doses by assuming a drinking water intake
of 2 L/day and a mean body weight of 70 kg. The carcinogenic risk driver in each
wastestream is the constituent with the largest risk as determined by the dose times the
constituent's potency factor. The non-carcinogenic risk-driver is the constituent with the
highest ratio of dose to RfD.
In all cases, the concentrations of the carcinogenic and non-carcinogenic risk drivers
are assumed to be perfectly correlated with the concentration of the cost-driver. That is.
EPA assumes that the 50th percentile concentration of the cost-driving constituent will occur

-------
along with the 50th percentile of the risk-drivers; the 75th percentile of the cost-driver
occurs along wtth the 75th percentile of the risk-drivers: ana so on.
After selecting the risk driving constituents for a wastestream, EPA simulated the
resource aamage due to both the carcinogenic and non-carcmogemc risk drivers (resource
damage is defined, and our methods for analyzing it are described, later in this chapter).
The risk driver with the greater simulated resource damage was designated as the ground
water resource damage driver for each wastestream.
Managing Facilities. EPA estimated the number of facilities managing each wastewater
and the number of facilities managing each non-wastewater independently. Then EPA
adjusted these numbers to account for the fraction of those facilities believed to include
both RCRA Subtitle D and Subtitle C units. Ground-water monitoring and/or corrective
action activities associated with Subtitle C units are assumed to effectively prevent or
remediate ground-water contamination at these sites.
In total. EPA estimates that 1,900 facilities manage wastewaters potentially exhibiting
the TC m surface impoundments. EPA obtained this estimate by adding indusfry-by-
industry estimates for each industrial sector with wastes that were characterized. The
percentage of facilities managing wastewaters in surface impoundments was estimated for
each sector by using waste management information from the Screening Survey of
Industrial Subtitle D Facilities (Screening Survey) in conjunction with facility size information
from the Census of Manufactures. Exhibit 5-2 displays estimates for each industry
examined in the benefits analysis. It also shows the estimated number of managing
facilities (i.e., number of facilities with on-site surface impoundments) for each industry.
For example, this exhibit shows that 11.7 percent of the facilities generating
wastewaters in the Organic Chemicals Industry (SIC 286) manage the wastewaters in
surface impoundments, yielding 64 facilities with surface impoundments for the industry.
The percentage of 11.7 is generated by adding separate estimates for large facilities and
small facilities. EPA estimated a value for large facilities managing wastes in surface
impoundments at sites which are not Subtitle C facilities by multiplying the percentage of
large facilities in each industry (41) by the percentage of large facilities with surface
impoundments (23) and by the percentage of large facilities involved in land-management
which are not Subtitle C facilities (100 minus 41.7). This large facilities percentage is added
to a similar value for small facilities, which is obtained in the same manner (i.e., 0.59 times
0.13 times the difference between 1.00 and 0.188).
These estimates assume that the land-management percentages in the Screening
Survey accurately describe facilities likely to generate TC wastes, although this universe of

-------
5-5
EXHIBIT 5-2
ESTIMATION OF NUMBER OF SURFACE IMPOUNDMENTS BY SIC
SIC
Percent of
Facilities in
the Industry
Larae Small
Percent of
Facilities
With Surface
Impoundments
Large Small
Percent of
Facilities
with Subtitle
C units
Large Small
Percent of
Facilities with Estimated Number
Only Subtitle D of Facilities
Surface with Surface
Impoundments Impoundments
2231
37
63
15
2
1.4
0
6.8
9
22SX
34
66
15
2
1.4
0
6.3
95
226X
28
72
15
2
• 4
0
5.6
23
227X
32
68
15
2
1.4
0
6.1
0
2299
6
94
15
2
1.4
0
2.3
8
229X
31
69
15
2
1.4
0
6.0
8
22XX
44
56
15
2
1.4
0
7.6
0
22 YY
57
43
15
2
1.4
0
9.3
83
2421
11
89
13*
7*
9.6*
0.3*
7.5
56
2499
8
92
13'
7*
9.6*
0.3*
7.4
1
26XX
42
58
12
0.3
4.5
0
6.6
21
2821
43
57
24
1
37.0
0
7.1
39
2822
39
61
10
0.2
32.4
0
3.9
2
2823
100
0
10
0.2
32.4
0
6.8
1
2824
77
23
10
0.2
32.4
0
5.7
3
283X
29
71
13*
7*
9.6*
0.3*
8.4
52
286X
41
59
23
13
41.7
18.8
11.7
64
2911
100
0
73
13
36.1
0.3
53.9
98
2992
14
86
13*
7*
9.6*
0.3*
7.6
0
3011
51
49
3
0.4
10.1
0
1.6
0
3021
49
51
3
0.4
10.1
0
1.5
0
3031
23
77
3
0.4
10.1
0
0.9
0
3041
50
50
3
0.4
10.1
0
1.5
0
3069
29
71
3
0.4
10.1
0
1.1
0
3079
22
78
3
0.4
10.1
0
0.9
0
461
13
87
13*
7*
9.6*
0.3"
7.6
53
4911
31
69
34
15
3.7
0
20.5
0
517
2
98
10"
10"
9.6*
0.3*
10.0
1,292
Total 1,909
based on averages for all industries in the Subtitle D phone survey
from MRI industry report for Petroleum Products Distribution and Wholesaling Systems
**" See Exhibit 2-3 lor the industry names for these SICs.

-------
5-6
facilities is somewhat different than the universe of generators of all non-hazardous industrial
wastes, which was the actual population targeted by the Screening Sun/ey.
These estimates may overstate the number of affected facilities managing wastewaters
because some wastestreams in the database are generated by the same facilities, rather
than being generated by different facilities and managed in distinctly different units. Due to
the uncertainty in identifying which wastestreams may be generated by the same facilities,
EPA assumes each wastewater wastestream is generated at an independent location. As an
example of the potential difficulty this can create, assume that there are three potential TC
wastewater streams generated in a particular industry. The number of facilities generating
each wastestream would be multiplied by the fraction of facilities for that industry believed to
manage wastewaters in unregulated surface impoundments, providing an overestimate for
the number of managing facilities in that industry under some circumstances.
The number of facilities managing potential TC wastewaters in surface impoundments in
each industry is listed in Exhibit 5-2 and is based on this assumption of independent
facilities. The Agency believes that this assumption has not led to unreasonable estimates,
in part because the estimate of 1,900 facilities is well below the total of 6,700 facilities with
surface impoundments estimated to receive all industrial wastes in the Screening Survey.
EPA estimates that a total of 8,600 facilities with landfills and land application units
manage non-wastewaters (i.e.. sludges/slurrys and solid residuals) that are potentially TC
wastes. To derive this number EPA used a somewhat different approach from the one used
above for facilities managing wastewaters. This is because individual facilities frequently
generate multiple sludges during the management of a single wastewater. Simply applying
the percentage of generating facilities that also land-manage their sludges to each sludge
wastestream would result in a large overestimate of the number of landfills and land
application units used to manage these wastes.
Instead. EPA identified the total number of facilities with landfills and land application
units available to receive TC wastes. These include facilities with on-site landfills and land
application units as well as municipal landfills. The number of facilities with on-site units was
determined from the Screening Survey and is shown and totalled in Exhibit 5-3. There are a
total of 2669 facilities with on-site units.1 This number was subsequently adjusted to remove
facilities believed to already be Subtitle C facilities (6.7 percent overall) leaving an estimated
2490 on-site facilities not already covered by Subtitle C. The number of municipal landfills
was obtained from the National Survey of Solid Waste (Municipal Landfill Survey) and totals
6,024 facilities.2
1	The number of facilities with landfills may be added to the number of facilities with land
application units because the Screening Survey shows that there are very few facilities which have
both types of units (less than 2 percent of the facilities with units).
2	U.S. EPA, National Survey of Solid Waste (Municipal Landfill Facilities). Final Report. Office of
Solid Waste, October, 1988.

-------
5-7
EXHIBIT 5-3
ESTIMATION OF NUMBER OF FACILITIES MANAGING NON-WASTEWATERS ON SITE
SIC
Subtitle D
Industry Name
Number of
Facilities with
Landfills
Number of
Facilities with
Land Application
Units 	
Total
2231
225X
226X
227X
2299
229X
22XX
22YY
2421
2499
26XX
2821
2822
2823
2824
283X
286X
2911
2992
3011
3021
3031
3041
3069
3079
Textile
Manufacturing
Pulp and Paper
Plastics and Resins
Selected Chemicals
and Allied Products
Organic Chemicals
Petroleum Refining1*
Rubber and
Miscellaneous
Plastics
25
182
123
180
28
19
38
13
95
12
36
65
170
91
75
15
15
35
24
163
11
16
90
352
214
255
43
34
73
37
258
23
52

-------
5-8
EXHIBIT 5-3 (continued)
ESTIMATION OF NUMBER OF FACILITIES MANAGING NON-WASTEWATERS ON SITE
Number of
Number of	Facilities with
SIC
Subtitle D
Industry Name
Facilities with
Landfills
Land Application
Units
Total
461
S
16
15
31
49t 1
Electric Power Gen.
126
34
150
517
a
542
505
1047

Total
1435
1234
2669
* based on averages for all industries in the Screening Survey
b based on data from the Census of Manufactures.

-------
5-9
To determine the number of facilities managing a particular non-wastewater
wastestream. the analysis apportioned the 8,600 landfills and land application units over the
generators of non-wastewaters in proportion to the number of generators of each sludge or
solid residual. The generators of non-wastewater wastes sum to 79,600 facilities.
Therefore, the reduction factor applied to the number of generators of each wastestream is
0.108 {i.e., 8,600 divided by 79,600).
For example, there are two sludges generated by facilities in the Miscellaneous
Plastics Products Industry (SIC 3079). Each sludge is generated by 11,653 facilities.
Applying the reduction factor to these generators results in 1.258 managing facilities being
affected by each of these wastestreams.
This weighting process may place inappropriate emphasis on some of the
wastestreams and facilities because facilities generating multiple wastestreams will be
reflected more frequently than those generating a single stream.
5.1.3	Waste Management Assumptions
EPA uses simplified models of waste management for the baseline and post-regulatory
cases. These assumptions are consistent with the approach the Agency has taken in
developing the mismanagement scenario for the TC. In the baseline, EPA assumes that
unregulated wastes are managed in new, unlined units - non-wastewaters are managed in
landfills, and wastewaters are managed in surface impoundments. This assumption has
allowed the RIA to build directly on the analytic effort undertaken to develop distributions of
DAFs, and to use those DAFs in simulating exposures and risks. It also allows the use of
simplifying assumptions to correlate waste characteristics to leachate quality, as described
below. And as described above, the Agency has developed methods to correlate
regulation of generators (which the rule directly affects) with benefits that accrue at land
disposal facilities (where the principal environmental damages posed by TC wastes are
most likely to occur).
To analyze the regulatory options, EPA assumes a regulated waste is properly
managed in Subtitle C units and that proper management results in negligible ground-water
contamination. Thus, the analysis assumes that all of the baseline risk and resource
damage posed by wastes are eliminated if those wastes are regulated by the TC.
5.1.4	Simulation of Exposure Concentrations and Plume Areas
EPA modeled risk and resource damage for all of the wastes that were characterized
across a spectrum of hydrogeologic and exposure situations. This was accomplished with
a Monte Carlo model that combined information on the distribution of waste characteristics
with information on the distribution of environmental and exposure conditions associated
with managing these wastes, and calculated the risk and resource damages resulting from
their management. It is important to take note of the fact that once the specific portion of
a wastestream to be regulated by the TC is determined using the "cost-driving" constituent

-------
5-10
described in Chapter 2, the Agency models benefits using risk-driving constituents only.3
"Cost-driving" constituents themselves are not used in the risk calculations.
In the model, leakage from a facility is assumed to be immediate and the extent of
leakage is measured in terms of steady-state contaminant concentrations and steady-state
contaminated piume areas in the underlying ground water. This subsection describes the
stochastic model that calculates the exposure concentrations and plume areas upon which
the risk and resource damage estimates are based. Subsection 5.1.5, which follows,
describes the methods used for calculating risk and resource damage.
The model produces exposure concentrations and plume areas reflecting variations in
wastestream concentrations and a range of hydrogeologic conditions. This is
accomplished, in part, by developing many individual synthetic wastestreams for each of the
characterized wastes. There is a four step sequence that produces exposure
concentrations and plume areas for each wastestream:
¦	Determine waste concentrations of risk-driving constituents from
distributions of concentrations;
¦	Determine leachate concentrations of risk-driving constituents;
o Determine exposure concentrations; and
¦	Determine area of the contaminated plume.
This sequence of calculations is performed 250 times for each wastestream. After this
number of iterations, the mean health risk and resource damage estimates for a waste of a
particular characterization have stabilized (i.e., do not change significantly with additional
iterations). The steps are described below and in more detail in Appendix D.
Waste Concentrations. The model randomly selects a percentile concentration value
to be used in selecting appropriate waste concentrations for each iteration. The same
percentile value is used to determine the concentration for the carcinogenic risk-driver and
the non-carcinogenic risk-driver. For example, on the 43rd iteration for a particular
wastestream the model may select the 17th percentile concentration value; the actual
concentration for the carcinogenic risk driver would be the 17th percentile value as
determined by the statistical distribution for that particular contaminant in that wastestream.
The actual concentration for the non-carcinogenic risk driver would also be the 17th
percentile value, based on its own statistical distribution of values. Note that the
concentration distributions for constituents in wastewaters are surface impoundment influent
concentrations and do not incorporate volatilization or other avenues for contaminant loss
Leachate Concentrations. The leachate concentrations are determined from the waste
concentrations. If the waste is a wastewater, the leachate concentration is the same as tne
3 Note that the cost-driving constituent and the risk-driving constituent may actually be ident.ca
in some cases.

-------
5-11
waste concentration. If the waste is a non-wastewater, the Organic Leaching Model (OLM)
is applied to the waste concentration to yield the leachate concentration. (The OLM is
discussed in Section 2.2.1.)
Exposure Concentrations. The model calculates exposure concentrations from the
leachate concentrations by accounting for the dilution and attenuation that occurs between
the source of leakage and an exposure point. This is accomplished by randomly selecting
DAFs from a distribution of DAFs. The distribution of DAFs is taken directly from the output
of EPA's EPACML model, and is identical for all 25 constituents modeled in the RIA. Each
DAF corresponds to a particular hydrogeologic setting and a particular distance to the
nearest point of exposure. The DAFs reflect steady-state conditions.
Plume Areas. The model calculates plume areas from leachate concentrations. The
plume areas are based on an EPA modei which predicts the surface area of the
contaminated groundwater plume as a function of the ratio between initial (leachate)
concentration and the specified downgradient concentration. (See Appendix E for a
description of this methodology). The basic output of this model is expressed as a table
showing plume surface area corresponding to each of a series of different concentration
ratios.
The plume areas in this table represent steady-state conditions, and are based only on
median values for hydrogeologic parameters. Thus, unlike the exposure concentrations, the
plume areas do not account for variability in hydrogeology.
5.1.5 Estimation of Health Risk, Resource Damage, and Cleanup Costs
This subsection describes the methods and assumptions used to calculate the human
health risk and resource damage based on exposure concentrations and contaminated
plume areas. It also describes the methods and assumptions for estimating cleanup costs.
Human health risk is measured in terms of risk to the most exposed individual (i.e., MEl)
and population risk. Resource damage is measured in terms of the dollar value to replace
contaminated water supplies. Cleanup cost is measured in terms of the dollar value to
clean up groundwater to meet applicable cleanup targets.
In all cases, the description in this subsection is for predicting baseline damages.
Under the regulatory options, these damages are assumed to be eliminated when a waste
is regulated. The approach for calculating damages under the regulatory options is
described more fully in subsections 5.1.6 and 5.1.7.
MEl Risk
MEl risk is based on the constituent concentrations at the closest downgradient well, if
one is present. If downgradient wells are not present, there is no exposure and no MEl
risk. Based on information from the Municipal Landfill Survey, EPA assumes that 54
percent of the managing facilities do not have downgradient wells.
For those facilities with downgradient wells, carcinogenic and non-carcinogenic MEl
risk are estimated from the lifetime daily doses of the constituents calculated from the

-------
5-12
exposure concentrations. The doses assume daily ingestion of 2 liters of the ground water
for 70 years (the average lifetime) by a 70 kilogram person. Carcinogenic ME1 risk is
calculated with a one-hit model using the dose and a risk potency factor for the constituent.
Non-carcinogenic MEi risk is measured in terms of the ratio of the dose to the RfD for the
constituent. Appendix D describes the specific models.
Population Risk
Population risk is also estimated for those scenarios with downgradient wells (i.e.. 46
percent of the scenarios4}. Population risk is based on the number of people affected by
the contaminated plume and is calculated separately for exposure to carcinogens and non-
carcinogens.
EPA uses the results of the plume area analysis rather than the results of the MEI risk
modeling to generate estimates of population risk. Thus, the population risk estimates are
based on a hydrogeologic scenario that corresponds to the median values for each of the
parameters in the EPACML, i.e., hydrogeologic variability is not accounted for by this
approach.
Based on results from the Municipal Landfill Survey, EPA assumes that 1.6 people per
acre are affected by the dose calculated for each portion of the plume. EPA also assumes
a 60 meter buffer strip between each facility and the exposed population. The 60 meter
value was chosen to be consistent with the assumptions employed in EPA's Liner Location
Model, and is in the middle of the distribution of such values that was developed for the
Cross-Regulatory Analysis of land disposal programs.
Carcinogenic population risk is estimated in terms of the expected number of cancer
cases. This is determined by estimating the individual risk resulting from the contaminated
plume and multiplying it by the affected population. Because the risk levels decrease as
one proceeds further downgradient and further from the plume centerline, individual risk is
calculated for different portions of the plume.
Non-carcinogenic population risk is estimated in terms of the population exposed
above the RfD for the constituent. Based on the plume area exhibiting a dose above the
RfD, EPA estimates the number of people exposed above the RfD by assuming a
population density of 1.6 people per acre.
Resource Damage
Resource damage measures the cost associated with replacing contaminated ground
water that had been used as a source of drinking water. Resource damage represents the
cost of replacing an existing water supply source (i.e., groundwater downgradient of a
waste management facility) with a substitute source of drinking water. The cost of the
substitute drinking water supply is taken to be an approximation of the economic value of
4 The 46 percent figure was taken from EPA's Municipal Landfill Survey, and reflects
populations near municipal landfills.

-------
5-13
the groundwater resource prior to contamination. The resource damage estimates are
based on the costs of designing and constructing an alternative water supply which meets
the demand of the population with contaminated water.5
EPA uses the following assumptions for the major components of the resource
damage approach:
Area of contaminated plume. The contaminated plume area is the area exhibiting
concentrations above the thresholds defining the suitability of the water for use. EPA uses
thresholds based on drinking water standards (i.e., MCLs) when they exist and alternatively
the lower of taste and odor thresholds or health-based thresholds (with the health-based
thresholds limited by detection limits). Exhibit 5-4 presents the thresholds for the
constituents examined in this analysis. EPA determines steady-state plume areas based on
these thresholds for both carcinogenic and non-carcinogenic risk-driving constituents, when
both types of constituents are present in a wastestream. EPA uses the larger of the iwo
plumes to calculate resource damage.
Source of replacement water. EPA assumes that alternative water will be available in
each situation from a ground-water source within one mile of the contaminated source.
This replacement scenario is the least costly of the likely alternatives. The other alternatives
include more distant ground water, nearby surface water, or more distant surface water.
Use scenario. EPA calculates resource damage under two scenarios. For the 46
percent of the facilities with existing downgradient wells, EPA assumes the entire population
within the plume uses the contaminated water, and EPA calculates a "use" value which is
the replacement cost for water currently in use. For the 54 percent of the facilities without
downgradient wells, EPA assumes the population retains the option to use the water as a
drinking water source in the future, and EPA calculates an "option" value. The option value
weights the resource damage by the probability the resource will be used in the future.
EPA assumed that the probability of use would increase by approximately 1.6 percent per
year, based on U.S. Geological Survey water supply summaries in the early 1980s (which
indicated this annual rate of increase for ground-water withdrawals overall). The resource
damage results reflect both types of values.
Number of people affected. Based on results from the Municipal Landfill Survey, EPA
assumes a population density of 1.6 people per acre in the vicinity of each facility. EPA
uses this assumption both for existing populations and for those which retain the option to
use the water in the future. The total number of people affected is equal to the area of
the plume (i.e., groundwater contaminated at concentrations exceeding the threshold) times
the population density.
Period of Operation. EPA assumes that the contaminated water is replaced immediately
and will be required for 200 years.
5 ICF Incorporated, 'OSWER Comparative Risk Project: Ground-Water Valuation Task Force
Report. Draft*, Prepared for U.S. EPA, Office of Underground Storage Tanks, February 4, 1988.

-------
5-14
EXHIBIT 5-4
RESOURCE DAMAGE THRESHOLDS FOR THE TC CONSTITUENTS a/
Resource

Carcinogen
Damage
Source of
Constituent
Class
Threshold
(mg/l)
Threshold
1.1-Dichloroethylene
C
.007
MCL
1.2-Dichloroethane
B2
.01
detection limit
2.4,5-Trichlorophenol
N
4.0
health-based
2,4,6-Trichlorophenol
B2
.05
detection limit
2.4-Dinitrotoluene
B2
.25
detection limit
Benzene
A
.005
MCL
Carbon Tetrachloride
B2
.005
MCL
Chlordane
B2
.0005
detection limit
Chlorobenzene
N
.1
odor threshold - B
Chloroform
B2
.06
health-based
Heptachlor
B2
.0001
detection limit
Hexachlorobenzene
B2
.025
detection limit
Hexachlorobutadiene
C
.006
odor threshold - A
Hexachloroethane
C
.01
odor threshold - A
Methyl Ethyl Ketone (MEK)
N
1.0
odor threshold - A
Nitrobenzene
N
.025
detection limit
Pentachlorophenol
N
.3
taste threshold - B
Pyridine
N
.1
odor threshold - A
Tetrachloroethylene
B2
.01
detection limit
Trichloroethylene
B2
.005
MCL
Vinyl Chloride
A
.001
MCL
m-cresol
N
.25
odor threshold - B
o-cresol
N
.26
odor threshold - B
p-cresol
N
.055
odor threshold - B
p-Dichlorobenzene
C
.075
MCL
'•*_ Resource Damage thresholds are MCLs if they exist, or the lower of the taste arid
odor threshold or the health-based threshold based on a risk level of 10"s with
the health-based threshold at least as large as the detection limit.
^ The references for the taste and odor thresholds are as follow:
A * Handbook of Environmental Data for Organic Chemicals, Verschueren, Von Nostrand
Reinhold, 1983.
B - "Compilation of Odour Threshold Values in Air and Water," National Institute for Water
Supply, Voorburg, Netherlands, Central Institute for Nutrition and Food Research TNO,
Zerst, Netherlands, pages 37-50, June 1987.
C - Oil and Hazardous Materials - Technical Assistance Data Systems (OHM-TADS),
Database prepared by U.S. Environmental Protection Agency, Oil and Special Materials
Controls Division. Office of Water Program Operations, Washington, D.C. 1983.

-------
5-15
Cleanup Costs
This section describes the methodology used to estimate cleanup costs in the absence
of regulation of TC wastes. In general, this methodology assumes that a portion of the
facilities managing potential TC wastes will require cleanup. Without TC regulation, the
cleanup will be performed, with public funds, either at the state or local levels or through
Superfund. With TC regulation, a portion of these cleanup costs will be avoided. Further
descriptions of the cleanup cost scenario and the estimation of an average site cleanup
cost are provided below.
Cleanup Cost Scenario. EPA assumes cleanup is required at facilities managing
potential TC wastes which have downgradient wells and substantial ground-water
contamination. The Agency assumed that those facilities with sufficient ground-water
contamination to exceed $1 million (present value) in resource damage would warrant
cleanup. To allow for growth and detection of the plumes, EPA assumes that cleanup will
begin 15 years hence, and all costs are discounted accordingly at an annual rate of 3
percent.
Average Cleanup Cost. EPA estimated an average per site cleanup cost of S15 million
using Superfund Record of Decision (ROD) data. The Agency examined RODs from 1986
and 1987 which listed TC constituents as the primary constituents of concern and which
required groundwater remediation. EPA examined only relatively recent RODs in order to
reflect the preference for permanent remedies resulting from the Superfund Amendments
and Reauthorization Act (SARA). Exhibit 5-5 provides information on the subset of RODs
used to estimate the average cleanup cost. These costs may understate the actual costs
of cleanup, since they do not include any expenses (private, state, or local) incurred prior
to the Superfund evaluation of the sites.
These costs are similar to estimates of the cost of a typical cleanup estimated in the
National Contingency Plan (NCP) RIA.6 The NCP RIA estimated that an average Superfund-
like cleanup would require an initial capital cost of $14.7 million and annual O&M costs of
$394,000. These estimates are based on 30 RODs signed between FY 1982 and FY 1986.
The NCP RIA stated that there was no information to determine how representative these 30
RODs are of all ROD sites.
5.1.6 Determination of Which Wastes Are Regulated in Each Option
By performing the preceding steps, EPA established the level of health risks, resource
damages, and ctoanup costs in the baseline. For each of the wastestreams described in
Section 5.1.1, EPA had computerized data sets containing the following information for each
of the 250 iterations of the model:
6 U.S. EPA, 'Regulatory Impact Analysis in Support of the Proposed Revisions to the National
Oil and Hazardous Substances Pollution Contingency Plan.' Office of Solid Waste and Emergency
Response, prepared by ICF Incorporated. 1988.

-------
5-16
EXHIBIT 5-5
RECORD OF DECISION DATA USED TO ESTIMATE AVERAGE CLEANUP COSTS
Site
Year of
ROD
Constituents of Concern
Cleanup Cost
(1988 dollars)
Ottati & Goss
87
VOCs, acid and base neutral
compounds, pesticides, metals
43,900.000
Gold Coast
87
TCE, PCE, VOCs, and metal
5.334.000
Sodyeco Site
87
TCE. PAHs, and VOCs
3,981.000
Geiger (C&M Oil)
87
arsenic, toluene, organics,
PCB, and metals
8.061.000
Palmetto Wood
Preserving
87
pentachlorophenol, chromium,
and arsenic
1.569.000
Seymour Recycling
87
VOCs, organics, TCE, DEE,
benzene, toluene, and metals
750,000
FMC Corporation
87
TCE, PCE, benzene, toluene, and
other VOCs
1.519,000
Conservation
Chemical
87
inorganics, organics, VOCs,
metals, and dioxin
21.400.000
Colbert Landfill
87
VOCs. TCA, and TCE
24.700.000
Blosenski
Landfill
86
VOCs and inorganics
24,900.000
Coleman Evans
86
PCP and other VOCs
3,700,000
Syncon Resins
86
VOCs and chlordane
10,300,000
Tinkham Garage
86
VOCs and TCE
10,900,000
Union Pacific
86
Creosote and PCPs
48,700,000
Average
14,978,000

-------
5-17
¦	waste concentration (this is an input, drawn from a distribution of concentrations)
¦	the number of facilities represented by the iteration (calculated as the total number
of facilities managing the wastestream divided by 250)
¦	leachate concentration (equal to waste concentration for wastewaters, calculated by
using the Organic Leaching Model for non-wastewaters)
¦	MEI risk (cancer and non-cancer)
¦	Population risk (cancer and non-cancer)
¦	Resource damage
¦	Cleanup cost.
EPA r inipulated these data sets to establish the level of benefits attributable to each of the
regu.atory options.
The Agency determined which wastes are regulated in each option. Specifically, based
on the cost analysis (described in Section 3), the Agency determined the proportion of each
wastestream that is regulated under each set of DAFs by comparing leachate concentrations
to regulatory levels. EPA then sorted each of the wastestream data sets based on leachate
concentration. Because the concentrations of the risk-driving constituents are assumed to
be directly correlated to the concentrations of the cost-driving constituent, the highest risk-
driving constituent concentrations would be the first to be regulated; e.g., if 10 percent of
the wastestream was regulated (based on comparing cost-driver leachate concentrations to
the regulatory level), then the top 10 percent of risk-driver leachate concentrations would be
regulated.
That portion of each wastestream regulated under each option is assumed to be
managed in Subtitle C-compIiant units after regulation. As previously mentioned, EPA
assumes that Subtitle C management results in essentially eliminating the baseline damages.
Thus, to create estimates of the post-regulatory damages for each option, the Agency
"zeroed our the baseline risks, resource damage, and cleanup cost for each iteration where
the leachate concentration was above the level that would be regulated.
5.1.7 Determination of Reductions in Risk, Resource Damage, and Cleanup Costs
The final step in the methodology involved aggregating information across wastestreams
for each option. The risk, resource damage, and cleanup cost estimates for each iteration
were weighted by the number of managing facilities, and summed across all wastestreams.
In the ensuing discussion of results, the Agency discusses benefits in terms of the
difference between baseline damages and post-regulatory damages, i.e., the extent of human
health risk avoided, resource damage avoided, and cleanup costs avoided.

-------
5-18
5.2 RESULTS
This section presents the results of the benefits analysis for the baseline case and for
each of four regulatory options. An overview of the basic characteristics of the baseline,
and the general patterns of the results for the regulatory options are presented in section
5.2.1. The distinctions between the baseline and the various regulatory options are
discussed in more detail for each of the measures considered in our analysis in sections
5.2.2 through 5.2.8. This section concludes with a qualitative analysis of the effects of the
TC on used oils.
5.2.1 Overview
Summary information for the baseline and for regulatory options with DAFs of 33. 100.
250. and 500 is presented in Exhibit 5-6; results are reported for six different measures
covering carcinogenic risk, non-carcinogenic exposures, and resource damages. Similar
information is presented separately for wastewaters and non-wastewaters in Exhibits 5-7 and
5-8.
Both wastewaters and non-wastewaters make significant contributions to the baseline
damages for five of the six measures EPA considered. (All of the non-carcinogenic
exposures exceeding the reference dose in the baseline are attributable to wastewaters.)
However, wastewaters and non-wastewaters are affected much differently across the various
regulatory options. For most measures, all four of the regulatory options reduce the
damages posed by wastewaters to essentially zero; the greatest residual damage, even
under the DAF 500 option, is 3 percent of the baseline value {as measured in terms of the
number of facilities with cancer risks exceeding 10"S). Benefits attributable to the different
regulatory options vary much more for non-wastewaters, as shown in Exhibit 5-8.
The specific results are largely determined by a limited number of contaminants from just
a few different wastestreams in particular SICs. For example, benzene from the Wholesale
Petroleum Marketing SIC dominates baseline risk for both measures of carcinogenic risk and
for both measures of resource damage. Wastewater {Stormwater Runoff and Tank Water
Draws) and non-wastewater (Unleaded Gasoline Tank and Crude Oil Tank Cleaning Sludges)
wastestreams provide the major benzene exposures in this SIC.
Similarly, pentachlorophenol dominates baseline risk for both measures of non-
carcinogenic risk. The principal source for pentachlorophenol is the Sawmill and Planing Mill
SIC, specifically the Treated Wood Drippage Wastewater wastestream.
This overview continues with a summary of results for each of the benefits measures.
Number of additional cancer cases in 70 years. There are 5.6 cases of cancer predicted
in the baseline case. These are divided roughly evenly between wastewaters and non-
wastewaters. The most stringent option (DAF 33) eliminates all of these cancer cases. The
least stringent option (DAF 500) reduces the baseline figure by 93 percent; the residual risk
is due to non-wastewaters.

-------
EXHIBIT 5-0
SUMMARY OF BASELINE RISK AND REGULATORY BENEFITS FOR ALL WASTES
BENEFIT MEASURE
(UNITS)
BASELINE
RISK

¦ BENEFIT FOR REGULATORY OPTION'



DAF33
DAF100
DAF 250
DAF 500
CANCER CASES (NUMBER OF CASES)
OVER 70 YEARS
5.6

5.6
5.5
5.5
5.2
FACILITIES WITH CANCER
RISK > 10E-S (NUMBER OF FACILITIES)
790

790
780
730
460
PEOPLE EXPOSED TO NON-CARCINOGENIC
CONSTITUENT CONCENTRATION > RFD
(NUMBER OF PEOPLE)
320

320
320
320
320
FACILITIES WITH NON-CARCINOGENIC
CONSTITUENT EXPOSURE > RFD
(NUMBER OF FACILITIES)
8.2

8.2
7.6
5.7
5.7
RESOURCE DAMAGE (BILLION DOLLARS)
3.8

3.8
3.8
3.6
2.4
FACILITIES WITH RESOURCE DAMAGE
> 10E6 DOLLARS (NUMBER OF FACILITIES)
1600

1600
1600
1600
1600
•ALL REGULATORY OPTION RESULTS ARE REPORTED AS REDUCTION FROM BASELINE RISK (I.e. BENEFIT)

-------
EXHIBIT 5-7
SUMMARY OF BASELINE RISK AND REGULATORY BENEFITS FOR WASTEWATERS
BENEFIT MEASURE
(UNITS)
BASELINE
RISK

BENEFIT FOR REGULATORY OPTION*



DAF 33
DAF 100
DAF 250
DAF 500
CANCER CASES (NUMBER OF CASES)
OVER 70 YEARS
2.9

2.9
2.9
2.9
2.9
FACILITIES WITH CANCER
RISK > 10E-5 (NUMBER OF FACILITIES)
300

300
300
290
290
PEOPLE EXPOSED TO NON-CARCINOGENIC
CONSTITUENT CONCENTRATION > RFD
(NUMBER OF PEOPLE)
320

320
320
320
320
FACILITIES WITH NON-CARCINOGENIC
CONSTITUENT EXPOSURE > RFD
(NUMBER OF FACILITIES)
5.8

5.8
5.8
5.7
5.7
RESOURCE DAMAGE (BILLION DOLLARS)
1.4

1.4
1.4
1.4
1.4
FACILITIES WITH RESOURCE DAMAGE
> 10E6 DOLLARS (NUMBER OF FACILITIES)
770 .

770
770
770
770
•ALL REGULATORY OPTION RESULTS ARE REPORTED AS REDUCTION FROM BASELINE RISK (i o. BENEF IT)

-------
EXHIBIT 5-8
SUMMARY OF BASELINE RISK AND REGULATORY BENEFITS FOR NON-WASTEWATERS
BENEFIT MEASURE
(UNIT8)
BASELINE
RISK

BENEFIT FOR REGULATORY OPTION*



DAF33
DAF 100
DAF 250
DAF 500
CANCER CASES (NUMBER OF CASE8)
OVER 70 YEARS
2.7

2.7
2.7
2.6
2.3
FACILITIES WITH CANCER
RISK > 10E-5 (NUMBER OF FACILITIES)
490

490
490
440
170
PEOPLE EXPOSED TO NON-CARCINOGENIC
CONSTITUENT CONCENTRATION > RFD
(NUMBER OF PEOPLE)
0

0
0
0
0
FACILITIES WITH NON-CARCINOGENIC
CONSTITUENT EXPOSURE > RFD
(NUMBER OF FACILITIES)
2.5

2.5
1.9
0
0
RESOURCE DAMAGE (BILLION DOLLARS)
2.4

2.4
2.4
2.2
0.96
FACILITIES WITH RESOURCE DAMAGE
> 1CE6 DOLLARS (NUMBER OF FACILITIES)
800

800
800
790
780
•ALL REGULATORY OPTION RESULTS ARE REPORTED AS REDUCTION FROM BASELINE RISK (I.e. BENEFIT)

-------
5-22
Number of facilities with cancer risk to the most exposed individual exceeding 10'5. In
the baseline case 790 facilities are estimated to pose cancer risks greater than 10"s. (This
represents about 7.5% of the 10.500 Subtitle D landfills, land application units, and industrial
surface impoundments.) Non-wastewaters account for 62 percent of the total baseline risk.
Benzene accounts for more than 90 percent of the baseHne risk. While the most stringent
regulatory option brings all 790 facilities beneath the 10"5 threshold, the less stringent
options provide lesser degrees of protection. The DAF 500 option reduces the baseline
value by 58 percent {with nearly all of the residual due to non-wastewaters); the DAF 250
option reduces that value by 92 percent; a DAF of 100 provides a 99 percent reduction.
Number of individuals exposed to non-carcinogens at levels above the reference dose.
In the baseline case, there are 320 individuals with exposures that exceed the reference
dose for non-carcinogenic substances. All of the regulatory options presented here prevent
all of these exposures. Over 70 percent of the baseline cases are due to
pentachlorophenol, and nearly all are associated with exposures from wastewaters.
Number of facilities with exposures to non-carcinogens for the most exposed individual
exceeding the reference dose. Exposures exceeding the reference dose for non-carcinogens
are predicted to occur at 8.2 facilities.7 Nearly 70 percent of these facilities appear because
of pentachlorophenol, and more than 70 percent that overall value are due to exposures
from wastewaters. The most stringent regulatory option brings exposures at all facilities
below the reference dose level. The less stringent options (DAFs 250 and 500) provide only
70 percent of this protection, and do not bring maximum exposures below the threshold for
any of the facilities that appear in the baseline because of non-wastewater exposures.
Resource damage. Resource damages in the baseline case are estimated to be S3.8
billion. Non-wastewaters comprise 63 percent of that amount, and benzene is the
constituent responsible for 95 percent. While the most stringent regulatory options reduce
resource damage by nearly 100 percent, the least stringent option provides only a 63
percent reduction and leaves S1.4 billion in damages (essentially all from non-wastewaters.)
The DAF 100 and DAF 250 options reduce resource damage by 100 percent and 95
percent, respectively.
Number of facilities with resource damage exceeding Si million. In the baseline, 1600
facilities are predicted to have resource damages exceeding S1 million. Almost all of these
cases are eliminated by any of the regulatory options presented in this document. (About 2
percent of the non-wastewater contribution to the baseline remains under the DAF 500
option.) The baseline cases are about evenly divided between wastewaters and non-
wastewaters, and 94% are attributable to benzene contamination.
7 Fractional facilities, like fractional cancer cases, are statistical projections produced by the
methodology and are not meant to be taken literally.

-------
5-23
Cleanup costs avoided. EPA estimates avoided cleanup costs at S15 billion for DAFs 33
through 500. This represents the elimination of all baseline cleanup costs, and reflects the
fact that even the DAF 500 option reduced resource damage below the S1 million cutoff for
substantially all facilities.8
5.2.2	Cancer Cases
EPA evaluated the differences between the various regulatory options in reducing
number of cases of cancer over a 70 year period; there is at most a 7 percent difference in
benefits between regulatory options. Detailed information on the constituents, SICs, and
wastestreams contributing to baseline risk are presented in Exhibits 5-9, 5-10, and 5-11.
The 5.6 cases of cancer in the baseline are primarily attributable to exposures to
benzene (63 percent), vinyl chloride (23 percent) and carbon tetrachloride (13 percent). The
Wholesale Petroleum Marketing SIC poses 52 percent of this risk, with lesser amounts from
Plastics Materials and Resins (21 percent) and Organic Chemicals (14 percent). Two
Wholesale Petroleum Marketing wastestreams provide half of the total risk (41 percent from
Stormwater Runoff and Tank Water Draws, and 9 percent from Unleaded Gasoline Tank
Cleaning Sludge.) Two Plastics Materials and Resins wastestreams (both PVC sludges)
each also provide 9 percent of this risk.
The DAF 33 option reduces the baseline risk to essentially zero. The DAF 100 and DAF
250 options reduce the baseline value by 98 percent, arid the DAF 500 option reduces it by
93 percent. Essentially all of the differences between the regulatory options are from
changes in benzene exposure in the Wholesale Petroleum Marketing SIC. All of the
regulatory options address the baseline cancer cases due to wastewaters completely.
5.2.3	Facilities with Cancer Risk exceeding 10"5
EPA evaluated the differences between the various regulatory options in reducing the
number of facilities posing cancer risks above 10"' to the most exposed individual. Detailed
information on the constituents, SICs, and wastestreams contributing to baseline risk are
presented in Exhibits 5-12, 5-13, and 5-14.
The 790 facilities with cancer risks exceeding 10*s in the baseline are primarily
attributable to exposures to benzene (91 percent) and tetrachloroethylene (6 percent). The
Wholesale Petroleum Marketing SIC provides 68 percent of this total, with the next largest
amount (16 percent) from the Miscellaneous Plastics Products SIC. Three Wholesale
Petroleum Marketing wastestreams provide 68% of the total (33 percent from Stormwater
Runoff and Tank Water Draws, and 18 percent each from Unleaded Gasoline Tank Cleaning
Sludge and Crude Oil Tank Cleaning Sludge.) Oily Machinery and Lube Wastes, a
Miscellaneous Plastics Products wastestream, provides an additional 16 percent.
* There are slight differences in cleanup costs avoided for the various regulatory options.
Benefits under the OAF 500 option are approximately 1 percent below the full baseline amount, but
rounding to two significant figures yields $15 billion for both values.

-------
EXHIBIT 5-9
SUMMARY OF BASELINE RISK AND REGULATORY BENEFIT

BY
CONSTITUENT FOR CANCER CASES



BASELINE





CONSTITUENT
RISK

CANCER CASES AVOIDED

(CANCER CASES)








DAF 33
DAF 100
DAF 250
DAF 500
BENZENE
3.5

3.5
3,4
3.4
3.1
VINYL CHLORIDE
1.3

T.3
1.3
1.3
1.3
CARBON TETRACHLORIDE
0.7

0.7
0.7
0.7
0.7
TETRACHLOROETHYLENE
0.1

0,0
0.0
0.0
0.0
2,4-DINITROTOLUENE
0.0

0.0
0.0
0.0
0.0
CHLOROFORM
0.0

0.0
0.0
0.0
0.0
HEPTACHLOR
0.0

0.0
0.0
0.0
0.0
2,4,6-TRICHLOROPHENOL
0.0

0.0
0.0
0.0
0.0
TRICHLOROETHYLENE
0.0

0.0
0.0
0.0
0.0
HEXACHLOROBENZENE
0.0

0.0
0.0
0.0
0.0
P-DICHLOROBENZENE
0.0

0.0
0.0
0.0
0.0
TOTAL
5.6

5.6
5.5
5.5
5.2

-------
EXHIBIT 6-10
BASELINE RISK AND REGULATORY BENEFIT SUMMARY
BY SIC CODE FOR CANCER CASES
SIC"*
BASELINE
RISK
(CANCER CASES)

CANCER CASES AVOIDED



DAF33
DAF 100
DAF 250
DAF 500
517
2.9

2.9
2.9
2.9
2.8
2821
1.2

1.2
1.2
1.2
1.2
286
CO
o
•

0.8
0.8
0.8
0.8
OVERALL
TOTAL*
5.6

5.6
5.5
5.5
5.2
•TOTALS MAY NOT ADD DUE TO ROUNDING OR BECAUSE SICS WITH MINOR CONTRIBUTIONS ARE NOT LISTED
* - SEE EXHIBIT 2-3 FOR SIC CODES CORRESPONDING TO DIFFERENT INDUSTRIES

-------
EXHIBIT 5-11
WASTESTREAMS WfTH SIGNIFICANT CONTRIBUTIONS TO CANCER RISK
WASTE NAME
SIC*
WASTE TYPE"
PERCENTAGE OF
BASELINE RISK
PERCENTAGE OF
REGULATORY BENEFIT
DAF 100
PERCENTAGE OF
REGULATORY BENEFIT
DAF 250
STORM WATER RUNOFF AND
TANK WASTE WATER DRAW
517
WW
41
41
42
POLYVINYL CHLORIDE
SLUDGE/COAGULATION
2821
NW
9
9
9
POLYVINYL CHLORIDE
SLUDGE/SEDIMENTATION
2821
NW
9
9
9
UNLEADED GASOLINE TANK
CLEANING SLUDGE
517
NW
9
9
9
AGGREGRATE SLUDGE/
COAGULATION/FLOCCULATION
288
NW
7
7
7
AGGREGRATE SLUDGE
SEDIMENTATION
286
NW
3
3
3
CRUDE OIL TANK CLEANING
SLUDGE
517
NW
3
3
3
OILY MACHINERY AND
LUBE WASTES
3079
NW
2
2
2
•SEE EXHIBIT 2-3 FOR SIC CODES CORRESPONDING TO DIFFERENT INDUSTRIES
"WW-WASTEWATERS, NW-NON-WASTEWATERS

-------
EXHIBIT 5-12
SUMMARY OF BASELINE RISK AND REGULATORY BENEFIT BY CONSTITUENT
FOR NUMBER OF FACILmES WITH MEI CANCER RISK > 10E-5
CONSTTTUENT
BASEUNE
(NUMBER OF FACILITIES)

REDUCTION IN NUMBER OF FACILITIES
WITH CANCER RISK> 10E-5



DAF33
DAF100
OAF 250
OAF 500
06NZ6H&'-
cAft^rmr«AQHto«©i
VINYL CHLORIDE
HEPTACHLOR
TRICHLOROETHYLENE
CHLOROFORM
2,4-OINITROTOLUENE
2,4,6-TRICHLOROPHENOL
HEXACHLOROBENZENE
P-DICHLOROBENZENE
m
:lrr. ' <1 r1'
13
S
4
3
2
1
0
0
0

720
41
13
5
4
3
2
1
0
0
0
720
38
13
5
4
3
1
1
0
0
0
710
5
12
5
0
3
0
1
0
0
0
440
3
12
5
0
0
0
1
0
0
0
TOTAL*
790
'4 ¦
700
780
730
460
¦TOTALS MAY NOT ADO DUE TO ROUNDING
I

-------
EXHIBIT 5-13
SUMMARY OF BASELINE RISK AND REGULATORY BENEFIT BY, SIC CODE,

FOR NUMBER OF FACILITIES WITH MEI CANCER RISK > 10E-5

BASELINE






(NUMBER OF

REDUCTION IN NUMBER OF FACILITIES
SIC**
FACILITIES)


WITH MEI CANCER RISK > 10E
-5



DAF 33
DAF 100
DAF 250
DAF 500
517
540

540
540
540
400
3079
130

130
130
130
0
225X
33

33
28
0
0
2911
20

20
20
12
12
461
18

18
18
18
16
286
15

15
15
15
13
2821
12

12
12
7
5
283X
10

10
10
8
8
2992
8

8
8
5
3
2231
4

4
4
0
0
226X
3

3
3
3
0
26XX
2

2
1
0
0
2824
1

1
1
1
1
2822
1

1
1
1
1
OVERALL






TOTAL*
790

790
780
730
460
* TOTAIS MAY NOT AOD DUE TO ROUNDING Of! BECAUSE SICS WITH MINOR CON 1RIBU1 IONS ARE NOI IISILI)
• -SU: EXIMHI 12 31 OR SIC CODES CORRESPONDING 10 DIFFERENT INDUSTRIES

-------
EXHIBIT 5-14
WASTESTREAMS WITH SIGNIFICANT CONTRIBUTIONS TO THE NUMBER
OF FACILITIES WITH MEI CANCER RISK > 10E-5
WASTE NAME
SIC*
WASTE TYPE**
PERCENTAGE OF
BASELINE RISK
PERCENTAGE OF
REGULATORY BENEFIT
DAF 100
PERCENTAGE OF
REGULATORY BENEFIT
DAF 250
STORMWATER RUNOFF AND
TANK WASTE WATER DRAWS
517
WW
33
33
35
UNLEADED GASOLINE TANK
CLEANING SLUDGE
517
NW
18
18
19
CRUDE OIL TANK CLEANING
SLUDGE
517
NW
18
18
19
OILY MACHINERY AND
LUBE WASTE
3079
NW
16
16
17
•SEE EXHIBIT 2-3 FOR SIC CODES CORRESPONDING TO DIFFERENT INDUSTRIES
• -WW-WASTEWATERS, NW-NON-WASTCWATERS

-------
5-30
The DAF 33 option eliminates substantially ail of the baseline situations where cancer
risk exceeds 10"s, and DAF 100 reduces 99 percent of them. While the DAF 250 option
reduces the total by 92 percent, the DAF 500 option controls only 58 percent of those
cases, leaving 330 facilities exceeding that risk level. All but 10 of those remaining facilities
manage non-wastewaters. As is typical for the results, the primary differences between the
regulatory options are due to distinctions among non-wastewaters for the dominant SICs and
the most frequently occurring risk-driving constituents (for this measure of benefits, benzene
and tetrachloroethylene.)
The 10's risk level is a common benchmark, but it is important to consider the
performance of the various regulatory options at other risk levels as well. Exhibit 5-15
shows a plot of exceedance probabilities (which equate to the number of managing facilities
in our methodology) against risk, on a log scale, for the baseline case and each of the
regulatory options. The uppermost curve shows the numbers of facilities posing various
levels of risk in the baseline case. All of the regulatory options plot below and to the left of
the baseline case, showing significant reductions in the number of facilities at each risk level,
and clear reductions in the risk posed by the worst facilities. Note that the differences
between the regulatory options are more pronounced at the 10"* risk level than at 10"5.
Across a wide range of risks, however, the DAF 100 and DAF 250 options provide similar
results. The DAF 500 option provides less risk reduction than the DAF 100 or DAF 250
options across a wide risk range; the DAF 33 option provides greater risk reduction across
that range. However, all of the regulatory options show reductions in risk from the baseline
case.
5.2.4 Individuals With Non-cancer Exposures Above the Reference Dose
All of the regulatory options from DAF 33 through DAF 500 eliminate all of the non-
cancer exposures above the reference dose in the baseline. Detailed information on the
constituents. SICs, and wastestreams contributing to baseline risk are presented in Exhibits
5-16. 5-17, and 5-18.
Across all managing facilities, the total population exposed to doses above the RfD is
320. All of these exposures in the baseline are attributable to wastewaters. These are
primarily from exposures to pentachlorophenol (71 percent) from Treated Wood Drippage
Wastewater in the Sawmill and Planing Mill SIC, and methyl ethyl ketone (29 percent) in two
Organic Chemicals SIC wastestreams. (26 percent of this MEK is from the wastestream
known as "MEK from Dehydrogenation," and an additional 3 percent is included in "Acetic
Anhydride from Pyrolysis/Dehydration.")

-------
EXHIBIT 5-15
Carcinogenic MEI Risk
Wastewater and Non-Wastewater
-10
LEGEND
Baseline
-6 -5
Log Risk
DAF033 	DAF100
DAF250
DAF500

-------
EXHIBIT 5-J 8
SUMMARY OF BASELINE RISK AND REGULATORY BENEFIT, BY CONSTITUENT, FOR
POPULATION EXPOSED TO NON-CARCINOGENIC CONSTITUENT CONCENTRATION > RFD
CONSTITUENT
BASELINE
EXPOSURES
230
%
0
0

REDUCTION IN POPULATION EXPOSED TO NON-
CARCINOGENIC CONCENTRATION > RFD
PENTACHLOROPHiHOL : i
METHYL STHVL KETONi (MBK)
CHLOROBENZENE
O-CRESOL
DAF33
880
W
0
0
DAF100
230
93
0
0
DAF250
230
93
0
0
DAF 500
230
93
0
0
TOTAL*
320

320
320
320
320
•TOTALS MAY NOT ADO DUE TO ROUNDING

-------
EXHIBIT 5-17
SUMMARY OF BASELINE RISK AND REGULATORY BENEFIT, BY SIC, FOR POPULATION
EXPOSED TO NON-CANCER CONSTITUENT CONCENTRATION >RFD
SIC**
BASELINE
EXPOSURES

REDUCTION IN POPULATION EXPOSED TO NON-CANCER
CONSTITUENT CONCENTRATION > RFD



DAF 33
DAF 100
DAF 250
DAF 500
2421
230

230
230
230
230
286
93

93
93
93
93
OVERALL
TOTAL*
320

320
320
320
320
•TOTALS MAY NOT ADD DUE TO ROUNDING OR BECAUSE SICS WITH MINOR CONTRIBUTIONS ARE NOT LISTED
• - SEE EXHIBIT 2-3 FOR SIC CODES CORRESPONDING TO DIFFERENT INDUSTRIES

-------
EXHIBIT 6-18
WASTESTREAMS WITH SIGNIFICANT CONTRIBUTIONS TO NON-CANCER RISK
WASTE NAME
SIC*
WASTE TYPE**
PERCENTAGE OF
BASEUNE RISK
PERCENTAGE OF
REGULATORY BENEFIT
DAF100
PERCENTAGE OF
REGULATORY BENEFIT
DAF 250
TREATED WOOD DRIPPAGE
WASTEWATER
2421
WW
71
71
71
METHYL EHTYL KETONE
FROM DEHYDROGENATION
288
WW
26
26
26
ACETIC ANHYDRIDE
FROM PYROUDEHYDRATION
266
WW
3
3
3
•SEE EXHIBIT 2-3 FOB SIC COOES CORRESPONDING TO DIFFERENT INDUSTRIES
• 'WW-WASTEWATERS, NW-NON-WASTEWATERS

-------
5-35
5.2.5 Facilities wttti Non-Cancer Exposures above the Reference Dose
EPA evaluated the differences between the various regulatory options in reducing the
number of facilities where the most exposed individual would receive exposures exceeding
the reference dose for a non-carcinogenic contaminant,9 Detailed information on the
constituents, SICs, and wastestreams contributing to non-cancer MEI risks are presented in
Exhibits 5-19, 5-20, and 5-21.
The 8.2 facilities estimated to have such exposures in the baseline primarily manage
pentachiorophenol (68 percent), methyl ethy! ketone (26 percent) and chlorobenzene (7
percent). The Sawmill and Planing Mill SIC provides 68 percent of this risk (through the
Treated Wood Drippage wastestream), with 20 percent from the Plastics Materials and
Resins SIC (the Alkyd Resins Filter Residuals wastestream), 7 percent from the Reclaimed
Rubber SIC (via a pair of treatment sludge wastestreams), and 6 percent from the Organic
Chemicals SIC.
The DAF 33 option eliminates all of the baseline cases, and the DAF 100 option
eliminates 93 percent. Both the DAF 250 and DAF 500 options reduce this value by only 70
percent, leaving exposures above the reference dose at an estimated 2.5 facilities. This
difference is due to non-wastewater wastestreams. The wastestream posing highest risk
(Treated Wood Drippage) is a wastewater that is almost completely regulated by all of the
regulatory options. All of the other high-risk wastestreams are non-wastewaters. They are
completely regulated at DAF 33; they are virtually uncontrolled at DAF 250 and DAF 500; at
DAF 100 they are partially controlled.
While the reference dose is a key benchmark for non-carcinogenic exposures, exposures
below the reference dose are of interest as well. Exhibit 5-22 shows a plot of exceedance
probabilities (which equate to the number of managing facilities in our methodology) against
the ratio of MEI exposure to the reference dose (on a log scale) for the baseline case and
each of the regulatory options. On this log scale, a value of zero corresponds to a ratio of
1 (i.e.. the predicted dose is equal to the reference dose); a value of 1 corresponds to a
ratio of 10; and so on. The plot shows clearly that the vast majority of the model runs result
in predicted exposures well below the reference dose.
The uppermost curve shows the numbers of facilities posing various levels of exposure
in the baseline case. AH of the regulatory options are arrayed below and to the left of the
baseline case, showing significant reductions in the number of fatalities at each exposure
level, and clear reductions in the exposures at the worst facilities in each of the regulated
scenarios. As with carcinogenic risk, the DAF 100 and DAF 250 options provide similar
results across a wide range of exposure levels. The DAF 500 option reduces fewer
exposures and the DAF 33 reduces more, but all of the regulatory options show
demonstrable reductions in exposures compared to the baseline case.
9 The reason for the apparent inconsistency between the non-cancer results for populations
versus MEls is that the population estimates are derived using the plume area calculations (based
on a single hydrogeologic setting) while the MEI estimates are derived using the full distribution of
DAFs (based on variable hydrogeology and well locations).

-------
EXHIBIT 6-) 9
SUMMARY OF BASELINE RISK AND REGULATORY BENEFITS, BY CONSTITUENT, FOR NUMBER
OF FACILITIES WITH NON-CANCER MEI EXPOSURE > RFD


BASELINE






(NUMBER

REDUCTION IN NUMBER OF FACILITIES WITH NON-
CONSTITUENT
FACILITIES)

CARCINOGENIC MEI EXPOSURE > RFD



DAF33
DAF 100
DAF 250
DAF 500
PENTACHLOROPHEKOL
6.6

5.6
5.6
5.6
5.6
METHYL BIHYL KETONE (MEK)
.'¦>'¦2.1 .

2.1
2.1
0.1
0.1
CHLOROBENZENE
0.6

0.6
0.0
0.0
0.0
O-CRESOL
0.0

0.0
0.0
0.0
0.0
TOTAL*
8.2

8.2
7.6
5.7
5.7
•TOTALS MAY HOT ADD DUE TO ROUNDING

-------
EXHIBIT 6-20
SUMMARY OF BASELINE RISK AND REGULATORY BENEFIT BY, SIC CODE,
FOR NUMBER OF FACILITIES WITH NON-CANCER MEI EXPOSURE > RFD
SIC**
BASELINE
(NUMBER OF
FACILITIES)

REDUCTION IN NUMBER OF FACILITIES WITH EXPOSURE TO
NON-CARCINOGENIC CONSTITUENT CONCENTRATION > RFD



DAF33
DAF 100
DAF 250
DAF 500
2421
5.6

5.6
5.6
5.6
5.6
2821
1.6

1.6
1.6
0.0
0.0
3031
0.56

0.56
0.0
0.0
0.0
286
0.51

0.51
0.47
0.12
0.12
OVERALL
TOTAL*
8.2

8.2
7.6
5.7
5.7
•TOTALS MAY NOT ADD DUE TO ROUNDING OR BECAUSE SiCS WITH MINOR CONTRIBUTIONS ARE NOT LISTED
~ 'SEE EXHIBIT 2-3 FOR SIC CODES CORRESPONDING TO DIFFERENT INDUSTRIES

-------
EXHIBIT 5-21
WASTESTREAMS WITH SIGNIFICANT CONTRIBUTIONS TO THE NUMBER
OF FACILITIES WITH NON-CANCER MEI EXPOSURE >RFD
WASTE NAME
SIC*
WASTE TYPE**
PERCENTAGE OF
BASELINE RISK
PERCENTAGE OF
REGULATORY BENEFIT
DAF100
PERCENTAGE OF
REGULATORY BENEFIT
DAF 250
TREATED WOOD DRIPPAGE
WASTEWATER
2421
WW
68
73
98
ALKYD RESINS FILTER
RESIDUAL
2821
NW
20
21
0
COAGULATION/FLOCCULATION
SLUDGE - RECLAIM
3031
NW
4
0
0
SEDIMENTATION SLUDGE
RESIDUAL RUBBER
3031
NW
4
0
0
SPENT CATALYST - OXIDATION
GLYCEROUGL
286
NW
2
3
0
•SEE EXHIBIT 2-3 FOR SIC COOES CORRESPONDING TO DIFFERENT INDUSTRIES
• * WW-WASTEWATERS, NW-NON-WASTEWATERS

-------
EXHIBIT 5-22
Non - Carcinogenic MEI Risk
Wastewater and Non-Wastewaters
5000
M
4000 ®
a
g
I
n
3000 g
F
a
c
2000 !
e
1000 s
LEGEND
Baseline
-4 -3	-2
Log Ratio (MEI Exposure / RfD)
DAF033 	DAF100
DAF250
DAF500

-------
5-40
5.2.6	Resource Damages
EPA evaluated the differences between the various regulatory options in reducing
resource damage. Detailed information on the constituents, SICs, and wastestreams
contributing to resource damages are presented in Exhibits 5-23, 5-24, and 5-25.
The $3.8 billion resource damage in the baseline is almost exclusively attributable to
benzene contamination (95 percent). Wastewaters account for 37 percent of the baseline
figure.
The Wholesale Petroleum Marketing SIC contributes 71 percent of the damage through
three wastestreams (Stormwater Runoff and Tank Water Draws at 32 percent, Unleaded
Gasoline Tank Cleaning Sludge at 21 percent, and Crude Oil Tank Cleaning Sludge at i8
percent). An additional 16 percent comes from the Miscellaneous Plastics Products SIC
through the Oily Machinery and Lube Wastes wastestream.
Both the DAF 33 and DAF 100 options eliminate nearly all of the baseline risk. The DAF
250 option reduces this value by 95 percent. The DAF 500 option reduces it by only 63
percent, leaving S1.4 billion in resource damage. Damages from wastewaters (i.e.,
Stormwater Runoff and Tank Water Draws) are eliminated nearly completely under all of
these regulatory options. The differences between regulatory options are from changes in
benzene exposure from non-wastewater sources.
5.2.7	Facilities with Resource Damage Exceeding $1 Million
All of the regulatory options from DAF 33 through DAF 500 eliminated essentially all of
the instances in the baseline where resource damage exceeds $1 million. Detailed
information on the constituents, SICs, and wastestreams contributing to the baseline value
are presented in Exhibits 5-26, 5-27, and 5-28.
The 1.600 facilities with resource damage in excess of $1 million are almost exclusively
attributable to benzene contamination (94 percent). The Wholesale Petroleum Marketing SIC
contributes 81 percent of the facilities with resource damage, roughly equally divided
between two wastestreams (Unleaded Gasoline Tank Cleaning Sludge, and Stormwater
Runoff and Tank Water Draws.) Wastewaters are responsible for 48 percent of the facilities
that exceed this damage threshold in the baseline.
The reason that each of these regulatory options brings damages below the $1 million
threshold is shown readily in Exhibit 5-29. This is a plot of exceedance probabilities (which
equate to the number of managing facilities in our methodology) against resource damage,
on a log scale, for the baseline case. The uppermost curve shows resource damages in the
baseline case for the worst facilities. It has a clear "elbow" just above the $1 million mark,
meaning that the number of facilities with more damage than that drops off very rapidly.
Even the worst of those facilities do not have damages very far above $1 million, so modest
measures can reduce resource damages at nearly all facilities below the $1 million threshold.
The two additional curves are for the DAF 250 and DAF 500 options. The fact that these
appear at all in this exhibit indicates that they do not address all of the resource damage in

-------
EXHIBIT 5-23
SUMMAR
Y OF BASELINE RISK AND REGULATORY BENEFIT,
BY CONSTITUENT, FOR RESOURCE DAMAGE
CONSTITUENT
BASELINE
RISK
(DOLLARS)

RESOURCE DAMAGE AVERTED
PRESENT VALUE
BENZENE
PENTACHLOROPHENOL
CARBON TETRACHLORIDE
VINYL CHLORIDE
TETRACHLOROETHYLENE
METHYL ETHYL KETONE (MEK)
TRICHLOROETHYLENE
CHLOROBENZENE
HEPTACHLOR
CHLOROFORM
2,4-DINITROTOLUENE
HEXACHLOROBENZENE
2,4,0-TRICHLOROPHENOL
P-DICHLOROBENZENE
3,600,000,000
70,000,000
54,000,000
22,000,000
14.000,000
11,000,000
5,400,000
3,500,000
2,800,000
2,200,000
1,200,000
0
0
0

DAF33
3,600,000,000
59,000,000
54,000,000
22,000,000
14,000,000
11.000,000
5,400,000
3,300,000
2,800,000
2,200,000
1,200,000
0
0
0
DAF 100
DAF 250
DAF 500
3,600,000,000
59,000,000
54,000,000
22,000,000
14,000,000
11,000,000
5,400,000
0
2,800,000
2,200,000
1,200,000
0
0
0
3,400,000,000
59,000,000
54,000,000
20,000,000
14,000,000
5,800,000
2,800,000
0
2,800.000
2,200,000
1,200,000
0
0
0
2,200,000,000
59,000,000
53,000,000
20,000,000
14,000,000
840,000
0
0
0
800,000
1,200,000
0
0
0
TOTAL*
3,800,000,000

3,800,000,000
3,800,000,000
3,600,000,000
2,400,000,000
•TOTALS MAY NOT ADO DUE TO ROUNDING

-------
EXHIBIT 5-24

SUMMARY OF BASELINE RISK AND REGULATORY BENEFITS

BY SIC CODE FOR RESOURCE DAMAGE


BA8EU&E






RISC

DOLLARS OF RESOURCE DAMAGE AVERTED
SIC**
(DOLLARS)


PRESENT VALUE



f i'Jlj
DAF33
DAF 100
DAF 250
DAF 500
617
2,700,000,000

2,700,000,000
2,700,000,000
2,700,000,000
2,000,000,000

1 880,000,000

630,000,000
630.000,000
510,000,000
0
4ai
92,000.000
:••• ;;rv
92,000,000
92,000,000
92,000,000
79,000,000
2911
74,000,000

74,000,000
74,000,000
72,000,000
66,000,000
286
72,000,000

72,000,000
72,000,000
71,000,000
66,000,000
2421
70,000,000

59,000,000
59,000,000
59,000,000
59,000,000
2821
50,000,000

50,000,000
50,000,000
40,000,000
20,000.000
283X
34,000,000

34,000,000
34,000,000
34,000,000
33,000,000
2992
14,000,000

14,000,000
14,000,000
14,000,000
14,000,000
226X
5.400,000

5,400,000
5,400,000
2,800,000
0
26XX
4,900,000

4,900,000
4,900,000
4,900,000
4,900,000
2824
3,500,000

3,500,000
3,500,000
3,500,000
3,500,000
3031
3,300,000

3,100,000
0
0
0
2823
3.000,000

3,000,000
3,000,000
3,000,000
3,000,000

2,900,000

2,900,000
2,900,000
2.900,000
2,700,000
OVERALL






TOTAL*
3,800,000,000

3,800,000,000
3,800,000,000
3,600,000,000
2,400,000,000
•TOTALS MAY NOT ADD DUE TO ROUNDING
* 'SEE EXHIBIT 2-3 FOB SIC CODES CORRESPONDING TO DIFFERENT INDUSTRIES

-------
EXHIBIT S~2fi
WASTESTREAMS WITH SIGNIFICANT CONTRIBUTIONS TO RESOURCE DAMAGE
WASTE NAME
SIC*
WASTE TYPE**
PERCENTAGE OF
BASELINE RISK
PERCENTAGE OF
REGULATORY BENEFIT
DAF100
PERCENTAGE OF
REGULATORY BENEFIT
DAF 250
STORM WATER RUNOFF AND
TANK WASTE WATER DRAW
517
WW
32
32
33
UNLEADED GASOLINE TANK
CLEANING SLUDGE
517
NW
21
21
23
CRUDE OIL TANK CLEANING
SLUDGE
517
NW
18
18
19
OILY MACHINERY AND
LUBE WASTE
3079
NW
16
16
14
TREATED WOOD DRIPPAGE
WASTEWATER
2421
WW
2
2
2
WASTEWATER
fAPI AFFLUENT!
2911
WW
2
2
2
•SEE EXHIBIT 2-3 FOR SIC CCX>ES CORRESPONDING TO DIFFERENT INDUSTRIES
• •WW-WASTEWATERS, NW-NON-WASTEWATERS

-------
EXHIBIT 5-28
SUMMARY OF BASELINE RISK AND REGULATORY BENEFIT BY CONSTITUENT
FOR FACILITIES WITH RESOURCE DAMAGE > 1 MILLION DOLLARS

BASELINE






(NUMBER OF

REDUCTION IN NUMBER OF FACILITIES WITH
CONSTITUENT
FACILITIES)

RESOURCE DAMAGE > 10E6 DOLLARS



DAF33
DAF 100
DAF 250
DAF 500
Benzene
1BOO

1500
1500
1500
1500
<&rtxmT0trw*Sorf
-------
EXHIBIT ft-27
SUMMARY OF BASELINE RISK AND REGULATORY BENEFIT FOR
NUMBE
R OF FACILITIES WITH RESOURCE DAMAGE > 1 MILLION DOLLARS

BASELINE






(NUMBER OF

REDUCTION IN NUMBER OF FACILITIES
SIC**
FACILITIES)

WITH RESOURCE DAMAGE > 1 MILLION DOLLARS



DAF33
DAF 100
DAF 250
DAF 500
517
1,300

1,300
1,300
1,300
1,300
2911
62

62
62
62
57
461
52

52
52
52
52
286
37

37
37
37
35
2421
28

28
28
28
28
283X
19

19
19
19
19
2821
17

17
17
15
10
2992
5

5
5
5
5
3031
3

3
0
0
0
2823
2

2
2
2
2
2824
2

2
2
2
2
2822
2

2
2
2
2
26XX
1

1
1
1
0
OVERALL






TOTAL*
1,600

1,600
1,600
1,600
1,600
•TOTALS MAY NOT ADD DUE TO ROUNDING OR BECAUSE SICS WITH MINOR CONTRIBUTIONS ARE NOT LISTED
• 'SEE EXHIBIT 2-3 FOR SIC CODES CORRESPONDING TO DIFFERENT INDUSTRIES
-------
EXHIBIT 6-28
WASTESTREAMS WITH SIGNIFICANT CONTRIBUTIONS TO THE NUMBER
OF FACILITIES WITH RESOURCE DAMAGE > $ 1 MILLION
WASTE NAME
SIC*
WASTE TYPE"
PERCENTAGE OF
BASELINE RISK
PERCENTAGE OF
REGULATORY BENEFIT
DAF100
PERCENTAGE OF
REGULATORY BENEFIT
DAF250
UNLEADED GASOLINE TANK
SLUDGE
517
NW
44
44
44
STORMWATER RUNOFF AND
TANK WATER DRAWS
517
WW
41
41
41
WASTEWATER
(API AFFLUENT)
2911
WW
3
3
3
TREATED WOOD DRIPPAGE
WASTEWATER
2421
WW
2
2
2
•SEE EXHIBIT 2-3 FOR SIC CODES CORRESPONDING TO DIFFERENT INDUSTRIES
* * WW-WASTEWATERS. NW-NON-WASTEWATERS
-------
EXHIBIT 5-29
Resource Damage
Wastewater and Non-Wastewater
3000
2000
1000
LEGEND
— Baseline
Log of Dollars
DAF033 	DAF100
DAF250
DAF500
Resource Damage equals zero for all Regulatory options
-------
5-48
the baseline (as DAF 33 and DAF 100 do.) However, both curves stop just short of the S1
million mark, showing that these options can leave some resource damages without
broaching the S1 million threshold at any particular facility.
5.2.8	Cleanup Costs Avoided
Our simplified methodology calculates avoided cleanup costs on the basis of the
number of facilities with resource damages exceeding S1 million. The approximately 1.600
facilities with damages above S1 million in the baseline, when multiplied by the S15 million
per facility cleanup cost described in section 5.1 and discounted over 15 years, result in S15
billion as an estimate of baseline cleanup costs. EPA's results indicate all four of the DAFs
eliminate essentially all such costs. Thus the avoided cleanup costs under all of the options
considered in this document are approximately S15 billion.10 Due to the simplified nature of
this analysis, there is significant uncertainty associated with these estimates.
5.2.9	Benefits of Regulating Used Oil
This section discusses, in qualitative terms, the benefits that may result from the
regulation of used oil by the TC. This supplementary analysis was done in conjunction with
the cost analysis described in section 3.3.6. A more detailed discussion is provided in
Appendix A.
Assuming that used oil would not create TCLP filtration problems. EPA found that
virtually all used oil would fail the TC. EPA determined that three end-use management
practices for used oil would be affected; landfilling/incineration. dumping, and road oiling.
The oil managed in these practices would be shifted to other end-use management
practices. For example, much of the used oil that is currently dumped or applied directly to
roads by generators would probably be collected and sold to the used oil management
system (UOMS). Firms in the UOMS that currently sell used oil for road oiling would
generally shift this oil to other management practices, such as re-refining or burning as fuel.
Used oil that is managed by landfilling or incineration in Subtitle D units would likely be
shifted to management in Subtitle C units.
The shift in management practices could result in some benefits. Based on a very
limited analysis of carcinogenic effects, it appears that eliminating the dumping of used oil
would result in some benefits because other management practices (with the possible
exception of burning in boilers) would present lower risks. Eliminating road oiling appears to
have some benefits, particularly for reduction of ecotoxicity and for protection of
groundwater. However, substitute management practices such as burning in boilers (or
possibly disposal in landfills) may themselves contribute to exposure and risk in ways that
are difficult to quantify, so net benefits from such management changes are also difficult to
quantify.
10 The various regulatory options do not produce identical answers. When rounded to two
significant figures, however, each value is $15 billion.
-------
5-49
5.3 LIMITATIONS OF THE METHODOLOGY
There are many uncertainties inherent in estimating health risks and resource damage.
These uncertainties arise from data limitations such as the variability in wastes, waste
management practices, waste management environments, and risk assessment factors. This
section discusses factors introducing uncertainty into the benefits estimates and whether
these factors underestimate or overestimate benefits.
The Methodology is Based on a Steady-state Model, The steady-state model does not
consider the volume of waste being managed at any particular facility. Assuming that the
contaminated plume grows immediately leads to overestimates for risk and resource damage
because it may take many years for contaminant plumes to reach equilibrium size.
No Current Contamination. EPA's methodology assumes that all units newly regulated
under the TC rule will avoid all contamination, thus avoiding 100 percent of baseline risk.
This can overstate benefits for existing units, where some degree of contamination may
already have occurred.
Median Hydrooeoloaic Conditions. The use of plume areas representing a single, 50th
percentile hydrogeologic environment does not capture the full range of variability of actual
hydrogeologic environments. This creates uncertainty in benefits estimates for population
risk, resource damage, and cleanup cost.
Discrete Plume Areas. The use of a discrete plume area distribution (rather than a
continuous one) contributes some additional error to benefits estimates. The resource
damage, non-cancer exposure, and carcinogenic risk analyses employ different conventions
for choosing a plume area when calculations fall between two listed values. However, the
uncertainties contributed by the discrete plume distribution are not expected to be significant
relative to other uncertainties associated with EPA's methodology.
Surface Impoundment Closures. The Agency's methodology assumes that potentially
affected surface impoundment owner/operators will be able to switch to exempt tanks before
the effective date of the TC rule; this may not be true. Facilities that do not make such a
switch before that deadline will have to close as Subtitle C landfills, and will be subject to
facility-wide corrective action. Although the relevant costs have been considered for these
surface impoundments, the benefits have not been quantified and wero not included in the
benefits analyses. Thus, the reported estimates for benefits may be underestimated.
Assumptions About the Number of Managing Facilities. There is uncertainty about the
actual number of facilities managing the wastewaters and non-wastewaters, and little is
known about co-management of wastestreams. Also, the methodology specifically omits any
benefits that might accrue at facilities that also have Subtitle C units on-site; the assumption
of no unaddressed contamination at those units may not be correct, and this may cause the
current results to underestimate benefits. Taken together, these uncertainties could result in
underestimates or estimates of benefits.
Other Benefits. Additional benefits (e.g., reductions in ecorisk) may occur as a result of
the TC rule. Thus the current analysis may underestimate benefits.
-------
5-50
Wastewater Concentrations. Concentrations of the risk-driving constituents in
wastewaters are based on influent concentrations. These concentrations may lead to
overestimates of risk and resource damage because volatilizatic.i and other avenues for
constituent loss are not considered.
Population Densities. Based on the Municipal Landfill Survey, EPA assumed uniform
population densities in calculating population risk and resource damage. The results from
the Survey may not be appropriate for all facilities managing TC wastes. This assumption
may either underestimate or overestimate risk and resource damage.
Contaminants Considered. The risks estimated in this analysis take into account only
the twenty-five constituents now considered for inclusion in the TC rule. Additional risks and
resource damage may be expected to result from other constituents in wastestreams
proposed for regulation under this rule. Also, the characterization of each wastestream by a
single risk driver for cancer risks and a single risk driver for non-cancer exposures may have
masked significant contributions by other contaminants included in the same wastestream,
even if they are included in the proposed regulation. Significant additional benefits may
accrue to the regulatory options considered, and baseline risks may be underestimates.
Responses to Contamination. The health benefits portion of EPA's methodology does
not consider the possibility of detection and response to groundwater contamination. Taste
and odor problems may alert populations at risk, or State or Federal monitoring programs
may detect the contaminated plume. If contamination is discovered, residents may switch to
bottled water or formal corrective action procedures may be initiated. Either prospect would
reduce the actual health impacts of the contamination, and so the health benefits of the
regulatory options considered in the current analysis may be overestimated.
Oily Wastes. The methodology assumes that oily wastes will be analyzed accurately by
the TCLP and that benefits will result from the regulation of these wastes. However, it is
possible that non-wastewaters with an oily component will not be properly identified as
hazardous. A large proportion of facilities managing non-wastewaters and causing high risk
may be managing oily wastes. Thus, the benefits oi the TC rule for the regulation of non-
wastewaters may be overstated.
Other Exposure Pathways. The methodology examines only one pathway for exposure,
ingestion of groundwater. The model does not account for inhalation of air, ingestion of
contaminated surface water, ingestion of contaminated fish, or adsorption through skin.
Therefore, overall risks may be underestimated.
In other studies, EPA considered air risks from inhalation of airborne contaminants which
have volatilized from potential TC wastewaters. These studies estimate ME! air risk (i.e., risk
to an individual located 200 meters downwind from the facility). They show that in sectors
other than Wholesale Petroleum Marketing, approximately 20 percent of modeled facilities
had carcinogenic risk greater than 10"s. However, MEI air risks from Wholesale Petroleum
Marketing, a sector with a significant number of managing facilities, were less than 10"*.
These results reflect all of the wastewaters in the TC RIA database. They tend to be
conservative estimates because (1) risks resulting from each constituent in a wastestream
-------
5-51
were summed to determine the total air risk associated with a wastestream and (2)
wastewaters were assumed to be managed with little dilution (i.e., in surface impoundments
ranging from .25 to 2 acres in area). More dilution may occur in practice.
Groundwater Discharge to Surface Water. The steady-state model used to develop
estimates for the jize of contaminated ground-water plumes does not consider the possibility
of discharge to surface water. Particularly in the humid East, water tables tend to be close
to the surface and contaminant plumes may be truncated by the discharge of contaminated
groundwater to the surface. This suggests that the plume sizes used in the current analysis
may be overestimates, and that estimates for carcinogenic population risk, non-cancer
population exposure, and resource damage may also be overestimated.
Stimulus for Pollution Prevention. The current analysis assumes that the TC RIA
database accurately reflects the wastes and wastestreams that will exist upon promulgation
of the TC rule. It neglects the powerful stimulus that the TC rule may provide for facility
owner/operators to enhance pollution prevention efforts.
Pollution prevention has merit on its own. Procedural changes to adopt less hazardous
substitute chemicals or to begin closed-loop recycling would also reduce the health impacts
and resource damages associated with current patterns of chemical use. Thus the benefits
presented in this analysis may be somewhat underestimated.
5.4 SENSITIVITY ANALYSES
As described in previous chapters, EPA examined the sensitivity of waste volumes,
number of facilities affected, costs, and economic impacts at DAF 100 to changes in certain
analytical assumptions. EPA analyzed the sensitivity of the benefits analysis to many of the
same factors. In addition, EPA performed sensitivity analyses on alternative population
assumptions. These impacts are discussed below.
Effects of Sensitivity Analysis Factors Addressed in the Cost Analysis. EPA performed
four sensitivity analyses on the cost of the TC rule (see Section 3.5). The implications for
the benefits of the rule are discussed below.
Percentage of Facilities Affected. As sensitivity analyses, EPA assumed first that 10
percent and than 90 percent of the facilities in each industrial sector are affected by the
TC. EPA examined these alternative assumptions so as to vary the waste quantity •
generated by each facility. Because the benefits analysis is based on the number of
managing facilities, and not the quantity of waste managed, this alternative does not
affect benefits estimates.
Wastewaters Managed in Surface Impoundments. EPA assumed all facilities
generating wastewaters manage them on-site in surface impoundments as an
alternative to using the number of managing facilities derived from the Screening
Survey. The current assumption is that 1,900 facilities manage wastewaters
(approximately 10 percent of the facilities generating wastewaters are estimated to
manage wastes in surface impoundments.) The alternative assumption has a large
-------
5-52
affect on the benefits analysis, multiplying the estimate of 1,900 by up to a factor of
10. The number of facilities causing significant risk, RfD exceedences, or resource
damage would each increase correspondingly for wastewaters.
Distribution of Affected Waste Quantities to Large and Small Facilities. As a
sensitivity analysis for costs, waste quantities were split equally between large and
small facility size groups. This split was made as an alternative to splitting the
waste quantity between small and large facility size groups based on value of
shipments. This alternative split of waste quantities among facilities does not affect
the benefits results since the benefits are not based on the quantity of waste
handled, but on the number of sites managing the wastes. The number of sites
managing the wastes would not be affected.
Waste Quantities Exhibiting the TC. EPA assumed the percentage of waste
exhibiting the TC is based on the sum of percentages exceeding regulatory levels
for all constituents as an alternative to being based solely on the cost-driving
constituent. This assumption leads to higher estimates of wastes failing the TC.
This assumption will affect the quantity of waste at each facility. It will not affect the
results of the benefits analysis since these results are not based on quantity.
Benefits Results Using an Alternative Population Assumption. One of the major
assumptions in the benefits analysis is that downgradient populations are present at only 46
percent of waste managing facilities. This value is taken from EPA's Municipal Landfill
Survey and, therefore, reflects populations near municipal landfills. It may be an inaccurate
representation of the presence of populations near generating facilities managing their
wastes on site. This section re-examines the risk and resource damage results presented
above assuming all facilities have downgradient populations. This determines the upper
bound of the effects of this assumption, (Assuming that none of the facilities have
downgradient wells would eliminate potential benefits and provide a lower bound.)
Assuming downgradient populations at all facilities increases the baseline damages by a
factor of roughly 2.2 (i.e., 100 divided by 46), and correspondingly, increases the benefits by
slightly more than a factor of two. For example, the total number of facilities with MEI
cancer risk equal to 10"S or greater in the baseline would increase from 790 to about 1710
(i.e., 790 times 2.2). The reduction in the number of high-risk facilities would be more than
doubled, increasing from 780 (at DAF 100) to about 1690, Except for resource damage, all
of the other benefit measures would increase linearly, as well. In calculating resource
damage, EPA attributed some damages even when plumes are formed in the absence of
existing populations (i.e., there is some "option value" as explained in Section 5.1); thus, the
resource damage estimates for the baseline and regulatory options increase by a factor less
than 2.2.
-------
REFERENCES
(1)	Regulatory Impact Analysis of Proposed Standards for the Management of Used Oil -
- Prepared by Temple, Barker, and Sloane, Inc., for U.S. EPA, November 1985.
(2)	1982 Census of Manufactures. Volume II. Industry Statistics. U.S. Department of
Commerce, Bureau of the Census.
(3)	1985 Annual Survey of Manufactures. Statistics for Industry Groups and Industries. U.S.
Department of Commerce, Bureau of Census.
(4)	Screening Survey of Industrial Subtitle D Establishments (Draft Final Report). U.S. EPA
Contract 68-01-7359, December, 1987.
(5)	Organic Leaching Model, U.S. EPA (51 FR 41084), November 13, 1986.
(6)	Background Document on Subsurface Fate and Transport Model, U.S. EPA/OSW, 1988.
(7)	Final Report. National Survey of Solid Waste (Municipal Landfill Facilities). U.S. EPA
Office of Solid Waste, October, 1988.
(8)	"Wastewater Treatment Profiles for Industrial Sectors Impacted by Proposed Toxicity
Characteristic," EPA Contract No. 684)1-7287, Work Assignment No. 46. Memorandum
to John-Goodrich Mahoney, U.S. EPA, from Midwest Research Institute, August 19,
1988.
(9)	"Wastewater Treatment Profiles for Industrial Sectors Impacted by Proposed Toxicity
Characteristic," EPA Contract No. 68-01-7287, Work Assignment No. 46, MRI Project No.
9101 -L(46). Memorandum to John-Goodrich Mahoney, U.S. EPA, from Midwest
Research Institute, August 24, 1988.
(10)	Estimates of Waste Generation by Cellulosic Manmade Fibers. Synthetic Organic Fibers.
Petroleum Refining. Rubber and Miscellaneous Plastics Products. Leather Tanning and
Finishing. Oil and Gas Transportation Industries, and the Laundry. Cleaning, and
Garment Services. Draft Report, prepared by Midwest Research Institute for U.S.
EPA/Office of Solid Waste, May 27, 1987.
(11)	Estimates of Waste Generation by the Lumber and Wood Products Industry. Final Draft
Report, prepared by Midwest Research Institute for U.S. EPA/Office of Solid Waste,
December 9, 1987.
(12)	Estimates of Waste Generation bv the Organic Chemicals Indusfav. Final Draft Report.
prepared by Midwest Research Institute for U.S. EPA/Office of Solid Waste, December
7, 1987.
-------
(13)	Estimates of Waste Generation for Petroleum Crude Oil and Petroleum Products
Distribution and Wholesale Systems, Final Draft Report, prepared by Midwest Research
Institute for U.S. EPA/Office of Solid Waste, Novamber 13,1987,
(14)	Estimates of Waste Generation by the Petroleum Refining Industry. Final Draft Report.
prepared by Midwest Research Institute for U.S. EP/VOffice of Solid Waste, November
13, 1987.
(15)	Estimates of Waste Generation bv the Pharmaceutical Industry. Final Draft Report,
prepared by Midwest Research Institute for U.S. EPA/Office of Solid Waste, November
16, 1987.
(16)	Estimates of Waste Generation bv the Pulo and Paper Industry. Draft Report, prepared
by Midwest Research Institute for U.S. EPA/Office of Solid Waste, August 12, 1987.
(17)	Estimates of Waste Generation bv the Synthetic Fibers Industry. Final Draft Report.
prepared by Midwest Research Institute for U.S. EPA/Office of Solid Waste, November
16, 1987.
(18)	Estimates of Waste Generation bv Textile Mills. Final Draft Report, prepared by Midwest
Research Institute for U.S. EPA/Office of Solid Waste, December 15, 1987.
(19)	Synthetic Rubber industry. Final Draft Report, prepared by Midwest Research Institute
tor U.S. EPA/Office of Solid Waste, November 24,1987.
(20)	Composition and Management of Used Oil Generated in the United States, prepared
by Franklin Associates Ud for U.S. EPA, September, 1984.
(21)	Risk Assignment of Proposed Waste Oil Standards for the Management of Used Oil.
prepared for U.S. EPA Office of Solid Waste Economic Analysis Stall, August 7, 1985.
-------