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OCR for page 39
c
Assessing Waste-Reduction Efficiency
INTRODUCTION
SARA Section 313~) charged NAS To
assess the value of obtaining mass balance
information, or portions thereof [e.g.,
production rate], to determine the waste re-
duction efficiency of different facilities, or
categories of facilities, including the effec-
tiveness of toxic chemical regulations pro-
mulgated under laws other than this title."
In analyzing the use of mass balance data for
this purpose, the committee defined ef-
ficiency as progress made by a facility in re-
ducing its waste (see below). The waste un-
der consideration could be contained on site,
released to the environment from the facili-
ty, or contained and shipped off site to
another facility. This chapter evaluates both
EMB and MA practices for use in a program
to track waste-reduction progress according
to their potential for providing indicators of
(a) the amount of waste generated and the
association between the level of manu-
facturing activity, (b) the amount of
reduction at the source of generation (versus
reduction before treatment, such as by
incineration), and (c) the comparability of
the collected data among a wide variety of
manufacturing facilities.
Regarding the "effectiveness of toxic
39
chemical regulations promulgated under laws
other than this title," the committee assessed
mass balance data for its usefulness as a
generic indicator of the effectiveness of any
relevant regulations while accounting for
changes in production rate at a reporting
facility. This approach is consistent with
discussions of this part of the charge by
Congress (U.S. Congress, House, 1986~.
Waste Reduction
In the absence of a widely accepted defi-
nition for waste reduction, the committee
assigned to waste reduction the same defini-
tion given for waste minimization in Form R
(see Appendix C) for TRI reporting. In this
report, therefore, waste reduction includes
any of the following activities performed on
wastes generated within a facility: re-
cycling or reuse on site; recycling or reuse
off site; equipment or technology modifica-
tions, production procedure modifications,
and redesign (modification) or reformation
of a product; substitution of raw materials
and improved housekeeping, training, and
inventory control, as well as any other
technique that results in reduction or
OCR for page 40
40
elimination of waste released to any environ-
mental medium.
This definition is consistent with that
presented in a previous NRC report (NRC,
1985~. Waste reduction was defined in that
report to include "both changes in the pro-
duction processes and recycling and reuse of
hazardous materials either at or away from
the site of generation." Recycling, particu-
larly recycling within manufacturing facili-
ties, is included in this report's definition of
waste reduction, because it is a technique
that usually cannot be divorced from the
manufacturing activity. Furthermore, re-
cycling is clearly different from the treat-
ment of waste before environmental release.
The committee acknowledges that this
definition of waste reduction is broader than
those others have proposed (e.g., Sarokin et
al., 1985; OTA, 1986, 1987; see Appendix I).
However, the committee chose a broad
definition of waste reduction to allow analy-
sis of mass balance information to be applied
to any facility reporting waste information,
regardless of the way the facility deals with
the waste it generates. In discussing the
OTA's findings and conclusions on waste re-
duction, the committee acknowledges that
the OTA's definition of waste reduction
differs from that used in this report.
Waste-Reduction Efficiency
Some measure of waste-reduction
efficiency assists in comparing the waste-
reduction efforts of different facilities and
in determining whether waste reduction is
limited by the type and rate of operation.
Congress defined waste-reduction efficiency
by example: "For example, can this [mass
balance] information reasonably be used to
compare different facilities in the same
business to determine whether one is apply-
ing more rigorous environmental control
than another, or delineate whether reduced
releases of chemicals reflect improved con-
trol or limited operation" (U.S. Congress,
House, 1986~.
For this report, the committee defined
waste-reduction efficiency as a quantitative
measure of progress in waste reduction. A
waste-reduction-efficiency measure is most
useful when it is generally applicable among
facilities of many types.
A consistent definition of the waste that is
~455 BALANCE INFORMS TION
subject to reduction is essential to es-
tablishing any waste-reduction-efficiency
measure, especially for different regulations
that affect similar facilities. Waste defini-
tions in regulations developed under SARA
and the Resource Conservation and
Recovery Act (RCRA) differ, although they
affect similar manufacturing facilities;
therefore, waste-reduction measures
developed from these facilities might vary as
a result.
Total waste is the object of RCRA, but
individual chemicals contained in waste are
the object of SARA. Reductions in total
waste could occur and be documented under
RCRA without being documented under
SARA if specific waste components were not
produced by the manufacturer. Further-
more, no information is collected under
either regulation to indicate whether a
reduction in total waste quantities generally
correlates with reductions in the listed
chemicals within the wastes (see
Appendix I).
DATA FOR ASSESSING
WASTE-REDUCTION EFFICIENCY
Amounts of waste generated as the result
of specific activities from specific sources
within facilities can be reported in three
ways:
· For each source, such as a single
mixing tank.
· For each prodfuctio'' I, such as
phosgene production within a chemical pro-
duction facility.
· For an entire facility, such as each
waste stream exiting the facility into air,
water, or land.
Many different activities (and there-
fore, many different sources) make up a
single production unit, and one or more pro-
duction units are present at any facility.
Collecting data from each individual source
theoretically would achieve the most
accurate reporting. Such source-specific in-
formation often is required for EMB.
However, collecting, reporting, producing,
and evaluating such extensive and detailed
information for all regulated facilities in the
United States would be an enormous task.
OCR for page 41
ASSESSING WASTE-REDUCTION EFFICIENCY
Collecting production-unit operation and
flow data is a less detailed way to assess
waste reduction. Such data include describ-
ing each step of an activity associated with
each production unit and tracing the flow of
material through each step. The data also
include the amount of material handled in
the entire production unit and the total
amount lost at each step. Production-unit
data can disclose minute changes in waste-
stream composition and flow rate. Although
less detailed than source-specific data, pro-
duction-unit data are much more detailed
than data typically collected through pollu-
tion-control programs, which often focus on
limiting overall releases from facilities (e.g.,
discharges from an on-site waste-water
treatment facility handling waste streams
from multiple production units). Despite
accurate monitoring of waste-reduction
practices, these data are difficult to use for
comparative analysis for several reasons. No
standard nomenclature exists for production
units. Furthermore, production units do not
have fixed boundaries; some facilities
consider transfer activities as part of a pro-
duction-unit process and other facilities
consider these as activities outside of the
production unit. Also, production units with
identical names can vary extensively among
different facilities.
Facility-level data, the least detailed type
of data considered, are collected through
TRI reporting and many pollution-control
programs. For specific chemical reporting
(as for the TRI), facility-level dicta are suf-
ficient to allow measurement of the facili-
ty's waste-reduction efficiency, because all
sources and production units generating
waste within the facility are represented. If
progress were made in reducing the amount
of waste generated from a specific produc-
tion unit, then there would likely be less
waste contributed to streams exiting the
facility.
The committee evaluated only MA in-
formation for practical applications to assess
waste-reduction efficiency. EMB was not
evaluated because it requires a detailed
analysis of all material streams within and
across facility boundaries in order to attain
closure for all mass flows into and out of a
facility. Closure, however, is not a criterion
for assessment of waste-reduction efficiency.
As discussed later in this chapter, individual
components (e.g., production rate) of mass
41
balance data are evaluated for assessing
waste-reduction efficiency, and these data
can be obtained through the MA approach.
Instead of assessing waste-reduction effi-
ciency, EMB can be useful in the identifica-
tion and characterization of sources of waste
within a facility. For example, E.I. du Pont
de Nemours & Co. at Beaumont, Texas, has
used EMB for a mass balance of total car-
bon in its acrylonitrile manufacturing
facility to trace the steps in the process in
which byproducts with high boiling
temperatures are formed (Jordan, 1988~;
Oman and Ham (1988) describe how the
foundry industry uses EMB to locate sources
of waste within the foundry production.
However, OTA concluded (1986) that for an
entire facility EMB typically would have a
level of error such that it would give little
information on where substances appear as
waste in the facility.
REPORTING REQUIREMENTS
A facility-level MA approach was used
as part of the New Jersey Industrial Survey.
Because the survey was not conceived with
waste-reduction efficiency as an explicit
component, the state did not assess the rele-
vance of the MA data for this purpose.
Several organizations, however, have used
these MA data for waste-reduction
investigations.
Based on data collected through the New
Jersey Industrial Survey, the Natural Re-
sources Defense Council (NRDC) has pro-
posed a single waste-reduction performance
standard that would require facilities to
manufacture, produce, or otherwise use
specified chemicals with a minimum level of
eff iciency (Clarence-Smith, l 98Sa; see
Appendix if. In this case, efficiency is de-
fined as the ratio of the total amount of a
chemical released to the environment from a
facility to the total amount of that chemical
routed through the facility in one year. In
addition, INFORM, Inc. (a nonprofit re-
search organization that identifies and
reports on practical actions to protect and
conserve natural resources), used MA data
collected under the New Jersey Industrial
Survey for a preliminary characterization of
waste generation in organic chemical manu-
facturing facilities located in New Jersey
(Sarokin et al., 1985~.
OCR for page 42
42
INFORM, Inc., and OTA concluded that
the government files containing information
are too fragmented and incomplete to assess
waste-reduction progress adequately (Sarokin
et al., 1985; OTA, 1986~. Under the New
Jersey Worker and Community Right-to-
Know Act of 1983, the state now requires
the reporting of waste-minimization infor-
mation, but reporting this same information
on TRI's Form R is optional. As mentioned
in Chapter 3, New Jersey plans to use this
MA information in developing waste-re-
ductioh efforts that consider levels of ef-
ficiency within facilities or across industries.
MA data will be used to set priorities among
industries and facilities for waste-reduction
attention.
The optional "Waste Minimization Sec-
tion" on TRI's Form R requests the following
information:
· Type of modification (waste-minimiza-
tion activity).
· Quantity of the chemical in the waste
stream before treatment or disposal.
· Index (ratio of reporting year produc-
tion to base year production).
~ Reason for minimization action.
However, Form R instructions suggest
that the database will contain an aggregation
of different types of information that could
be used to assess waste-reduction efficiency.
The instructions indicate that the amounts of
waste from cleanups of areas associated with
abandoned operations should not be reported
separately from waste generated from on-
going operations. Therefore, reported
amounts of cleanup wastes and other one-
time wastes will mask the amounts of, and
trends in, wastes generated from ongoing
operations. In addition, facilities are allowed
to present data based on estimates, and any
one facility could use different estimation
methods for reporting in succeeding years.
Trends in wastes reported from one year to
the next' therefore, could be the result of
changes in estimates rather than changes in
operations.
Under RCRA, generators of hazardous
wastes certify on a manifest associated with
each shipment that they have a program to
minimize their wastes. In 1984, Congress
passed the Hazardous and Solid Waste
Amendments (HSWA) (P.L. 98-616; 42 USC
6901), which served to amend RCRA.
M4SS BALANCE INFORM4TION
Under HSWA, generators have been required
to describe their-hazardous-waste-minimiza-
tion program as part of a biennial report on
their hazardous-waste generation. Until re-
cently, there was little guidance or structure
for this waste-minimization report. Now,
however, EPA has released a 1987 Hazardous
Waste Report, the Waste-Minimization Pack-
age [EPA Form 8700-13A(5-80) (Rev. 11-
85) (Rev. 12-87~. The quantities of RCRA
waste in 1986 and 1987 are reported with a
production ratio for the two years. Qualita-
tive information is also requested on any re-
sulting change in the toxicity of the waste
and any change in the impact on air emis-
sions and water discharges. The focus of
this biennial reporting is on RCRA waste
codes, not on specific chemical constituents
and therefore would not add any information
for assessing the efficiency of reducing the
amount of specific chemicals in waste
streams from facilities reporting to the TRI.
NORMALIZATION OF
WASTE-RELATED DATA
Normalization is a procedure for adjust-
ing the reported amount of waste by divid-
ing it with such MA components as amount
of input (e.g., raw material) or output (e.g.,
product). This procedure can help account
for changes in the amount of waste
generated that are due to changes in the rate
of production, i.e., a decrease in the amount
of waste generated at a facility from one
year to the next could be due to manu-
facturing less product, instead of real pro-
gress in waste reduction. Typically, some
measure of product OlltpUt is used as the
normalization factor (Eberhardt, 1987;
Delcambre, 1987; Hollod and McCartney,
1988~. Waste-generation data not correlated
to production can mask waste-reduction suc-
cesses as well as failures (OTA, 1987~. Other
types of normalization factors are discussed
later in this chapter.
Figure 5.1 presents idealized"black-box"
mass balance diagrams to illustrate how
waste-reduction reporting might proceed if
either total waste or waste-component (toxic
chemical) options were pursued and the MA
data were sufficiently accurate to make
quantitative distinctions. This hypothetical
example illustrates that data interpretation is
not straightforward, and interpretation can
OCR for page 43
ASSESSING WASTE-RED UCTION EFFICIENCY
At a Time (To) Before Waste Reduction
Ra`` Mate~ ials
b
D =
A = 100
100
100
43
Products
PRODUCTION UNIT . E = ~ 4B, C = ~ ~ h =
. 30
~ Wastes
b = 10
D = 10
= 5
f = 5
= 10
b = 60
D= 5
E = 10
h= 5
At a Ti~ne (T`,~ ~ Aftet Braste Reduction
Ra`` llate~ ials
A = 100
b = 100
D = 100
PRODUCTIOI~ UNIT
~ lYastes
b =
D = 5
E = 5
f - 5
-
C = 15
5
b = 50
D= 0
E= 0
1l= 20
NOTE: Capital letters refor to TPl-listed chemicals.
and lo~ercasc letEc~s refer to unlisted chemicals.
P~ oduc1-s
E = 159, I
f = 35
FIGURE 5.1 Id~lized mass balance diagrams for production units or facilities before and after waste reduction.
OCR for page 44
44
become difficult as the number of com-
pounds and processes increases. Each box
represents a production unit or an entire
facility that may use and produce a number
of chemicals. In this example, the processes
are presumed to be nonconservative, which
means that chemicals in raw materials react
to form an entirely different set of chem-
ical products. In contrast, conservative pro-
cesses result in no transformations of the in-
put chemical berg., use of a solvent for
cleaning).
The upper box in Figure 5.1 shows three
raw material streams going in, and the out-
flow of two product streams and two waste
streams. The specific chemicals involved are
referred to by letters. Capital letters refer to
chemicals that are TRI-listed; lowercase let-
ters refer to unlisted chemicals. Quantities
have been assigned to each chemical to show
how waste-reduction statistics might be
developed. Since separation processes are
not perfect, some byproducts found in
wastes are also present in the product, and
some of the product chemicals are also found
in the waste. TRI-listed chemicals not fed
into the facility may be produced in the pro-
cess, appearing in the waste or product
streams. The lower box depicts the effects
on the same production unit or facility of
waste reduction through production changes
to improve product yield. The number of
input and output streams remains the same.
Table 5.1 presents the results of three dif-
ferent approaches to calculating waste-
reduction efficiency for the two situations
presented in Figure 5.1. The approaches
represent reduction-efficiency calculations
based on the total amount of waste gen-
erated, an aggregation of all TRI-listed
chemicals contained in the waste, and each
TRI-listed chemical. For each approach the
amount of waste generated is normalized for
production changes by dividing the amount
of waste by the amount of product made or,
alternatively, by the amount of TRI-listed
chemical in the product. Percent changes in
these waste/product ratios are then compared
between the initial (To) and waste-reduced
(TWR) cases. Substantially different figures
for percentage of improvement in reducing
the normalized waste amounts were
obtained, ranging from -30% to +70%, de-
pending on the basis of the calculation. The
minus percentage indicates that waste
generation had increased for chemical C as a
M4SS BALANCE INrFORMATION
result of waste-reduction efforts. Also,
although large-percent reductions for the
majority of TRI-listed chemicals might be
achieved, overall waste reduction might be
less.
After a common point of comparison,
such as production, is chosen, the decision
must be made whether the toxic release is to
be compared with the entire stream or with
the quantity of the same toxic chemical in
that stream. Calculating waste-reduction
efficiency based on some chemical-specific
normalization ratio would lead to significant
nonuniformity in reporting. In some cases,
no interpretation is possible. For example,
chemical D appears in the waste, but not in
the product; no ratio of the compound in
waste to production is possible, although a
ratio based on input is. On the other hand,
chemical C, not present in the input
material, appears in the waste and, in this
case, only a product-based ratio is possible.
Thus, there is a higher likelihood of obtain-
ing consistent and useful ratios if the de-
nominator is based on the total stream rather
than a chemical component therein.
For cases when waste-reduction efforts
include a fundamental production change to
use new input chemicals, evaluation by
examining changes in reduction efficiency
would be meaningless because the composi-
tion and therefore the potential toxicity of
the waste would likely change. Normalized
data by themselves might show a reduction
in waste, but they would not indicate
whether any change in potential toxicity had
occurred.
MA Data Selection for Normalization
In assessing the utility of any normalizing
factor, several questions must be asked.
Are the relevant data on chemical com-
ponents currently collected; if not, can they
be collected without an extensive effort?
How would the burden of additional
measuring and monitoring requirements af-
fect efforts to make progress in waste reduc-
tion?
Among production units, facilities, or in-
dustries, is there some commonality among
the chemicals that are to be measured? The
greater the diversity of chemicals, the less
meaning such comparisons may have.
Are the points of measurement suf
OCR for page 45
ASSESSING WASTE-REDUCTION EFFICIENCY
TABLE S.1 Vanations in Wast~Reduction Efficiency Calculation
Normalized Waste Amounts
45
Waste Amounts TRI-Listed Chemical in Waste (lb)/
Generated (lb) Waste (Ib)/Product (lb) TRI-Listed Chemical in Product (lb)
Waste
Description To
TWR To TWR
A% To TWR is%
Whole waste 120 105 .67 .54 19
All TRI-listed
chemicals
40
25 .22 .13 41
Chemical C 10 is .06 .os -3010.0 HP
Chemical D 15 5 .08 .03 60NP NP
Chemical E 15 5 .08 .03 60.10 .03 70
Note: Calculations performed on data presented in Figure 5.1.
Kerr. To = Initial process with a production of 180 lb.
TWR = Wast~reduced process with a production of 195 lb.
A% = Percent improvement in reducing the Normalized Waste Amounts.
NP = Chemical "not present" in product system.
ficiently similar among production units, fa-
cilities, or industries to make valid
comparisons? As the diversity of processes
used to manufacture a product increases, the
likelihood diminishes for obtaining com-
parable data among the different processes.
Are the measurements used for nor-
malization performed on the same chemical?
In other words, is the chemical measured in
a waste stream also present in the stream
(e.g., product stream) where measurement is
made for the normalization factor? This
question illustrates the problem of con-
structing a normalization ratio for noncon-
servative processes in which a given chemi-
cal is not necessarily present at all points in
the process.
An evaluation of these practical consid-
erations is presented in Table 5.2. The rela-
tive merit of using different MA compo-
nents (input, mass flow rate within the
facility, and production) for normalization is
given for each consideration. Input would
encompass all data for which inputs are
normally measured; mass flow rate within
the facility would encompass data collected
at some point between the flow of chemicals
into and out of the facility; production
would encompass all data for which outputs
are normally measured. It is assumed that
the amount of waste chemical generated is
known and would be the numerator for a
normalization ratio based on one of the MA
components, which would be the de-
nominator. Although data collected through
MA practice do not require high levels of
accuracy, if the accuracy of the data is poor,
the utility of the waste-reduction assessment
is diminished.
The merit of each MA component for
normalization shown in Table 5.2 is pre-
sented in two different ways. In one
(~Total~), the denominator is the total MA
component (input, production, etc.), and the
second (~Compound") is one chemical of
interest of that component. A qualitative
assessment of the usefulness of each MA
component is presented to indicate that dif
OCR for page 46
46
AL455 BALANCE INFORMATION
TABLE 5.2 The Relative Ment of MA Components for Normalization
Ranking by MA Component
Input
Flow Rate
within the Facility Production
Chemical Chemical Chemical
Consideration Total Compound Total Compound Total Compound
Currently measured? 4 2 2 1 4 1
Measurable? 4 3 2 2 4 2
Commonality of compounds
Between production units? 3 2 3 3 4 3
Between industnes? 1 1 1 1 1 1
Commonality of measuring
point? 4 4 1 1 4 4
Required reporting? 1 1 1 1 4 1
Consistent ratios at
measuring point? 2 1 3 2 3 2
Key:
1 = Seldom.
2 = Sometimes.
3 = Often.
4 = Usually.
ferences in the way data are collected must
be understood before any attempt is made to
standardize waste-reduction accounting pro-
cedures.
.
Comparability of Normalized Data
A primary goal in comparative waste-
reduction assessments among facilities and
industries is that reduction progress be com-
pared, through the normalization of chemi-
cal-specific waste data, to determine
whether one facility or industry is less effi-
cient than another in the handling and use of
a chemical. Comparison of normalized
waste-related -data between facilities must be
done with caution. INFORM, Inc., found
that facilities using similar quantities of
hazardous chemicals generated greatly dif-
ferent quantities of waste. However, some
of the observed differences in quantities of
waste generated were due in part to dif-
ferent processes and uses of chemicals at
each facility (Sarokin et al.' 1985~.
Normalization with any of the types of
MA component data listed in Table 5.2 poses
problems. Manufacturing industries vary
considerably in the types of information
typically obtained and obtainable. Although
most manufacturers usually obtain some
measure of raw material input and product
output, the units can be in pounds or in pro-
ducts such as refrigerators, automobiles,
spools of tape, or square feet of film. This
difference in units imposes a high degree of
nonuniformity in available data.
Even for facilities that manufacture the
same product, raw material inputs can be di-
verse, depending on the exact process used.
Different manufacturing routes also might
OCR for page 47
ASSESSING WASTE-REDUCTION EFFICIENT
result in significant differences in product
contaminants and waste-stream compositions
even in those cases in which a standard pro-
duct, such as a commodity chemical, is pro-
duced. For example, aniline can be manu-
factured through the reduction of nitroben-
zene by using iron and hydrochloric acid;
through ammonolysis with chlorobenzene,
ammonia, and cuprous oxide; or through va-
por-phase hydrogenation of nitrobenzene.
Each method uses a different group of TRI-
listed chemicals.
For any industry that produces manu-
factured goods, more often than not there
are significant differences in the chemical
content of the product (e.g., the use of vari-
ous alcohols and dyes or the use of mercury
in glass thermometers). When measuring a
chemical flowing through some point within
a facility that produces manufactured goods,
one finds that common chemicals (among
facilities) become even less likely because of
the number and degree of material
transformations within the facility as a
function of the manufacturing process.
If meaningful comparisons in waste-
reduction progress are to be made, even be-
tween similar facilities that manufacture the
same product, the point at which normaliza-
tion data are measured must be the same or
very similar. Because all manufacturing
facilities have material inputs and product
outputs, these would be the obvious points to
consider for obtaining data relevant to
waste-reduction progress.
As indicated in Table 5.2, product output
is the only point required to be reported
under current environmental regulations. As
discussed previously, total production can be
reported to the TRI as an index and in the
RCRA biennial report as a production ratio
so that confidential business information is
not disclosed. OTA concluded that to pro-
vide a reliable measure of waste reduction,
data must be correlated with production
(OTA, 1986~.
An alternative to using points of input or
output is to measure some point of material
flow within a facility. However, this alter-
native could lead to nonuniformity because
the diversity of manufacturing processes
would result in the inability to establish a
common appropriate point of reference
within the facility. Some meaningful
measuring point might be found in a linear
production line in which all the chemicals of
47
concern could be measured; however, the
problem becomes increasingly intractable
when multiple conversions take place in
complex interconnected manufacturing sys-
tems. For example, Bodwitch (1988) states
that "in an automotive assembly facility there
may be a single chemical component which
is contained in over 2,000 separate chemical
mixtures used as part of the hundreds of
specific assembly operations required to
manufacture motor vehicles." A similar
problem arises in a complex chemical man-
ufacturing operation, in which chemical
transfers and transformations take place
throughout. When highly controlled studies
of the internal workings of a process have
been undertaken, difficulties in obtaining
chemical-specific data forced the use of sur-
rogates, such as carbon (Iordan; 1988;
Nickolaus, 1988), equivalent pounds
(Redington, 1988), or methyl group (Supple,
1988~.
Although Table 5.2 presents qualitative
figures, it indicates that a normalizing factor
based on a total stream MA component
would be more practicable than one based on
individual chemicals. The concentration of
individual chemicals can vary, even among
facilities manufacturing the same product,
because of the diversity of processes used.
Furthermore, the concentration of individual
chemicals in raw materials or products rare-
ly is monitored, except when quality control
for that component is important, and the
mass streams are relatively homogeneous. In
petroleum refining, for example, the content
of trace metals in the crude petroleum input
or in the products typically would not be
measured because the heterogeneous nature
of the material handled makes such
measurement highly impractical. The foun-
dry industry provides another example of
variable feedstock composition: it is virtual-
ly impossible to measure reliably the lead
concentration of scrap metal input (Oman
and Ham, 1988~. Likewise, measurement of
the constituents in the product becomes less
practical when nonhomogeneous products,
such as automobiles, are involved (e.g., the
amount of heavy metals in the paint or
chrome on the bumpers and accessories exit-
ing in each different automobile).
No one method of normalization is
generally applicable. Comparisons among
production units, facilities, and industries
become meaningless if the normalization
OCR for page 48
48
factor is based on the specific chemicals. In
addition, no particular advantage is apparent
in using the input component or an internal
measure of mass flow rate compared with
using the production component to normalize
reduction reporting.
AGGREGATION OF WASTE
REDUCTION-EFFICIENCY DATA
A normalizing factor could be used in
many ways to measure progress. The most
obvious way is to compare waste generation
between different periods by comparing the
waste-generation ratios (e.g., waste genera-
tion/production). A decrease in this ratio
indicates a reduction in waste generation.
This method of assessment provides unam-
biguous results for specific waste streams
generated within a single production unit.
Such ratios become less meaningful as waste
data are aggregated from various production
units within one facility.
Table 5.3 shows how the waste-genera-
tion ratio could be calculated for the wastes
generated in different production units
(designated 1, 2, and 3) and for the entire
facility when the data are combined. This
hypothetical example illustrates the
limitations of using aggregated data even
though it is normalized. The generation
ratio for each production unit is shown in
Table 5.3 for a base (starting) year and for a
comparison (later) year. Even though the
generation ratio decreased for each produc-
tion unit, there was no change in the over-
all generation ratio, which could lead to the
erroneous conclusion that the facility as a
whole did not improve its waste-reduction
efficiency. The same phenomenon may
occur when multiple wastes are aggregated
for all the waste generated from a produc-
tion unit where multiple products are pro-
duced (Benforado, 1988) and, on a larger
scale, when facility statistics are combined to
form industry-wide and national statistics.
If such accounting procedures are to be of
benefit in managing wastes, they should be
maintained at the smallest practical produc-
tion-unit level. A more general nationwide
statistic developed by weighting individual
facility information would probably cause
progress to appear to be slower than it truly
was. OTA (1986) also concluded that waste-
reduction data should be process-specific or
~455 BALANCE INFO~TION
production- unit-specific, because facility-
level reporting would be too complex to ob-
tain meaningful data.
Waste-Reduction
Efficiency-Weighting Statistics
The problem of masking waste-reduction
progress through data aggregation can be
mitigated by using either of two calculation
procedures that weights annual changes in
generation ratios (e.g., waste generation/
production) for each production unit accord-
ing to either (1) relative amounts of waste
generated or (2) amount of waste generation
expected, based on changes in annual pro-
duction. These options are demonstrated in
Figure 5.2, using the hypothetical numerical
information from Table 5.3.
The first option described by OTA (1986)
allows no credit if, for example, a produc-
tion unit is changed to produce no waste. As
shown in Figure 5.2, if Reporting Unit 1
waste generation drops to zero, the weighted
statistic (R) remains approximately the same
( 1 1.6% compared with 1 1.3%~.
The second option compares the actual
waste generation in the comparison year with
the amount of waste generation expected if
no change in waste reduction had occurred
for the comparison year. This option has the
advantage that credit is given for eliminat-
ing a waste stream. In this case if Unit 1
waste dropped to zero, the percentage of
overall waste reduction would improve to
57o/o.
Both approaches require that data sum-
mations be calculated from the original indi-
vidual production-unit information. Conse-
quently, the number of calculations that
must be performed to compile meaningful
facility, industry, and national statistics can
escalate enormously. The experience with
collecting waste data under RCRA shows
that it would be very difficult for the
government to collect and analyze accurate
and timely data from a very large number of
facilities and for an even larger number of
processes and waste streams (OTA, 1986~. In
the context of TRI reporting, each chemical
requires a specific normalizing factor (be-
cause of different production quantities as-
sociated with each chemical at each facility).
For example, EPA initially estimated about
320,000 TRI reports from 32,000 facilities
(Federal Register, 1988a), which, if
OCR for page 49
49
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OCR for page 50
50
OTA Method
R
-
N
[(Unit) Waste Quantity)c(Uniti Generation Ratio % Change)c]
~-1
N
~ tUniti Waste Quantity)c
i=1
R
(75)(11) + (65)(11) ~ 5(20)
75 + 65 + 5 1.3%
If Reporting Unit 1 waste generation in comparison year approaches zero,
(65)( 1 1 ) ~ 5(20)
R65 + 5
Alternate Method
"4SS BAlANCE INFORMATION
= 1 1.6%
N N
~ [(Unit) Production~c(Uniti Generation Ratiob] - ~ (Unit) Waste Quantity)c
i=1 i=1
N
~ [(Unit) Waste Quantity)c(Uniti Generation Ratio)b]
i=1
R=
(310)(.27) + (105)(.70) + (122)(.05) - (75 + 65 + 5)
(310)(.27) ~ (105)(.70) + (122)(.05)
- x 100 = 11%
If Reporting Unit 1 waste generation in comparison year approaches zero'
R=
(310)(.27) + (105)(.70) + (122)(.05) - (65 + 5)
(310)(.27~) + (105)(.70) + (122)(.05)
Where: R = Weighted waste reduction statistic (%)
c = Comparison year
b = Base year
100 = 57%
FIGURE 5~ Wast~reduction weighting methods using data from Table 53. (Source: OTA, 1986; alternate method
adapted from N~cic, 1987)
OCR for page 51
ASSESSING WASTE-REDUCTION EFFICIENCY
developed on a production-unit basis, could
require annual accounting for millions of
production units, or for hundreds of millions
of wastes if reported on a chemical-specific
basis. For the first cycle of TRI reporting,
approximately 1S,000 facilities reported.
This lower-than-expected response is at least
partially due to noncompliance.
Indexing
Normalization factors account for the fact
that the amount of chemicals released is
often a function of the amount of product
made. An increase in waste could reflect an
increase in production. On the TRI Form R.
normalization factors called indexes can be
calculated from virtually any production in-
formation that "closely reflects activities
involving the chemical" (Appendix C). The
instructions to Form R list several acceptable
examples of indexes, including the following:
the amount of chemical or paint produced in
1987/amount produced in 1986; appliances
coated in 1987/appliances coated in 1986;
and value of sales in 1987/value of sales in
1986. If the index is based on mass for all
manufacturers, then there can be a com-
parison of information between, for ex-
ample, facilities or industries (if the pre-
viously described problems associated with
aggregated data are recognized). The use of
an index based on the number of product
units simplifies reporting for those industries
that traditionally report production in non-
mass units, but it prevents the compilation
of summary statistics of disparate units, such
as automobiles and refrigerators. The use of
dollar sales in indexing produces a statistic
that can be aggregated, but it is much less
dependable as a quantitative measure be-
cause prices for various commodities change
from year to year.
Several issues related to industrial diver-
sity merit consideration when indexing is
used to compile a national waste-reduction
database. One option would be to require all
facilities to report in the same units, which
would result in data that could be compared
and aggregated easily. The data would,
however, lose substantial accuracy. There
would be cases in which forcing the use of
the same units would distort the data, al-
though taken as a whole, the data would be
in a useful form for policymakers and for
51
revealing general waste reduction trends. A
variant of this option would be to specify
the measurement units to be used industry
by industry, thereby ensuring comparison
within an industrial sector at the expense of
some cross-industrial comparisons.
Another option would be to allow facili-
ties to choose their own units. This option
would most likely result in the most accurate
facility-level data. Aggregating these data,
however, would be impossible. This ap-
proach possibly would decrease the useful-
ness of the database for policymakers.
It is also possible to assess improvements
in waste-reduction efficiency by multiplying
the amounts of waste generated by produc-
tion after both have been indexed to the
same base year, for example, waste-reduc-
tion efficiency = (production index>(waste
index).
Such a calculation, based on mass or
other physical-unit production, could be
made for progress reporting at the appro-
priate level (e.g., production unit or facility)
without divulging production information.
It must be kept in mind that the larger the
reporting unit, the greater the problem as-
sociated with aggregation of data. If such a
system were used for reporting, it could be
used as an indication of progress by that re-
porting unit, but it could not be further ag-
gregated to show progress of a group of re-
porting units, for example, on a national
basis, because of the nearly insurmountable
problems of properly compiling an accurate,
meaningful national statistic for waste-re-
duction efficiency.
A national statistic that could be
compiled from such data would be of three
tallies: (a) those facilities or production un-
its showing improvement in waste-reduction
efficiency, (b) those showing no change, and
(c) those showing a decrease. Such a statistic
would be meaningful from year to year only
for a nominal measurement of progress (i.e.,
low level of information).
Evaluation of
Waste- Reduction- Efficiency Data
The previously described concepts for
evaluating waste-reduction efficiency are
variations of a single approach that might
best be described as mass (of waste)-based
systems. The two major measurement para
OCR for page 52
52
meters are (a) the mass of waste per unit of
time (e.g., pounds of waste per year) and (b)
the mass of waste per unit of manufactured
product (e.g., pounds of waste per ton of
ethylene produced). Both of these measure-
ments are made on absolute scales because
the data can be expressed on a scale that has
zero as the lowest value. One limitation of
this type of scale is that the focus can be
drawn to an endpoint, such as zero, without
differentiating the degrees of difficulty in
achieving waste reduction progress, as shown
in Figure 5.3.
Several significant anomalies must be
dealt with when one uses mass-based ab-
solute scales for assessing waste-reduction
progress. The first anomaly is that no credit
accrues for past implementation of produc-
tion modification or recycling and reuse to
reduce waste. Facilities with past substantial
waste reduction successes, therefore, could
be perceived as making insufficient progress
in subsequent years, if less opportunity were
to exist for waste reduction.
A second anomaly derives from the di-
versity among private-sector manufacturing
technologies. The relationship between a
particular manufacturing technology and its
specific opportunities for waste reduction is
an important factor that leads to very dif-
ferent possibilities for waste reduction
among industries (Royston, 1979~. The dif-
ferences among processes might substantially
affect the waste-generation rate, even when
the same product is manufactured. When
comparing waste-reduction progress between
two facilities making different products,
technical expertise is sometimes needed to
distinguish actual from apparent progress.
For example, one of the facilities could ap-
pear to make greater waste-reduction prog-
ress because it makes a product that can
contain relatively large amounts of waste
without affecting quality or performance.
The other facility produces a product that
cannot tolerate any additional impurities and
thus less opportunity exists for waste
reduction.
The third anomaly is that the rate at
which new modifications are implemented
can be related to a series of larger manu-
facturing and related financial decisions.
Those improvements that demonstrate the
greatest cost-effectiveness compared with
the present technology are instituted first.
Waste reduction, therefore, competes on a
M45S BALANrCE INFOR~4TION
substantially different basis for capital in-
vestment funds from one facility to another
and will result in different constraints on the
timing of introducing waste-reduction prac-
tices and different amounts of waste re-
duction achieved between facilities.
A fourth anomaly of the mass-based as-
sessment techniques is that they depend
heavily on the actual amount of production.
The amount of production is controlled by
numerous market factors, and therefore
variations in production lead to increases or
decreases in the amount of waste generation
per year. Normalizing waste generation by
production does not necessarily remove this
anomaly, because there might be a nonlinear
relationship between waste and production.
Waste-reduction progress can be more
realistically evaluated if the data are coupled
with a description of each new reduction
technology introduced at a facility. Many
factors other than the mass of waste are im-
portant in making progress in waste reduc-
tion, and a mass-based system does not re-
flect these other factors. For example, re-
ducing the amount of a trace toxic con-
stituent in a waste stream would indicate lit-
tle progress in mass waste reduction but
might be more beneficial than reducing large
amounts of less toxic constituents. Conse-
quently, even though a properly constructed,
mass-based waste-reduction-efficiency
statistic might allow for some comparisons
within and among the manufacturing in-
dustries, it would not be proper to require
uniform standards of waste-reduction
efficiency, irrespective of waste toxicity
differences and manufacturing diversity.
OTA also concluded that if government were
to require waste reduction, it would face
major difficulties in determining what is
technically and economically feasible or
practical for a specific industrial operation
(OTA, 1986~.
Alternative MA Practice Systems
The approaches to waste-reduction re-
porting discussed thus far focused on
specific mass balance components, such as
production, to provide a better under-
standing of the amounts of waste generated
at reporting facilities. This section contains
a discussion of three alternatives to the use
of specific MA components. The commit
OCR for page 53
ASSESSING WASTE-REDUCTION EFFICIENCY
Mass of waste
generated
o
\
\
\
\ B
\A \
T.
Ime
FIGURE 53 Patterns of waste generated over tune at different manufacturing facilities. Each cume (A, B. and C)
represents a hypothetical facility.
tee did not perform any comparative analy-
ses for these alternatives to collecting MA
data; in-depth analyses of these alternatives
were considered to be beyond the
committee's charge.
Throughput Systems
A throughput measure, which would have
no one point of measurement, was suggested
by Clarence-Smith (1988a) as an attempt to
address the problem that no one measuring
point within a facility is perfectly suitable
for normalization of data waste. The
throughput accounting procedure is an ap-
proach for mandating a waste-reduction
standard, as described in Appendix ]. In
this context, throughput is defined as the
sum of all mass quantities flowing out of a
facility allowing for chemical conversions
and including inventory changes. Obtain-
ing these data in a meaningful way multi-
plies the problems associated with the in-
dividual MA components described earlier in
the chapter.
This conceptual approach does little to
resolve the problem of nonuniformity of re-
porting or the analysis of such data when
53
analyses are done on a chemical-specific
basis in a nonconservative production.
Generally, the throughput model is seriously
flawed in its attempt to treat all industries
and all facilities uniformly. A discussion of
several additional problems witl7 this pro-
posal is given in Appendix J.
Toxicity-Based System
Fatkin (1988) describes an approach to
track the reduction or replacement of highly
toxic chemicals while reducing the presence
of other chemicals in the waste. The amount
of chemicals designated as highly toxic that
are input to a facility (rather than contained
in the waste) is used as the numerator, and
the denominator is the quantity of the pro-
duct derived from the use of those chemi-
cals. For chemicals considered less toxic, the
amount of waste generated would constitute
the numerator. With this approach, incon-
sistencies in reporting could occur if a high-
ly toxic chemical were totally replaced with
a less toxic one. In this case, the numerator
of the statistic would change from the input
amount to the amount in the waste. Conse-
quently, progress, or the lack of it, shown in
OCR for page 54
54
each statistic would have to be explained and
documented as these transfers take place
from year to year. In addition, such a
method requires the construction of a system
to classify materials by their relative toxici-
ties. This can be a time-consuming, con-
troversial, and complex task. It would, how-
ever, have the advantage of focusing on the
most important toxicants and limiting the
number of chemicals that must be accounted
for if consensus can be reached on the
toxicity criteria. OTA concluded that the
best way to measure waste reduction is to
determine the changes in the absolute
amounts of hazardous components. How-
ever, government might have to assist waste-
generating facilities in selecting the most
hazardous components of waste for reduc-
tion (OTA, 1986~.
Successful Project Reporting
A third approach does not emphasize
establishing ~ baseline or calculating changes
from year to year. Rather, this approach
would have facilities report their successful
projects and estimates of the amount of
waste prevented from being generated by
those projects (Benforado, 1988~. A national
collection of this information would help to
establish a database on successfully applied
methods that reduce toxic chemical releases.
Such a database would provide the informa-
tion needed for a successful technical as-
sistance program. It would be extremely
useful to individuals in charge of assistance
programs to know methods that work and
those that are failures before they recom-
mend them to facility managers. The
disadvantage to the reduction database is
that, when used alone, it may not supply
enough information on the actual changes in
waste generation from year to year.
CONCLUSIONS
The necessary components of a program to
track waste-reduction progress are
knowledge of the waste generated and its re-
lation to the level of manufacturing activity,
the extent of waste reduction at the source
(versus reduction after treatment), and the
comparability of the collected data among a
wide variety of facilities.
~4SS BALANCE INFORM TION
Mass balance information obtained
through EMB or MA practices is not
generally useful for strict determination of
waste-reduction efficiency or progress in
waste reduction. Both practices fail to
recognize technological and economic limita-
tions in achieving waste reduction, within
and between industries, or the progress that
was made before an accounting program was
instituted. Consequently, uniform absolute
goals such as a fixed rate of reduction of
waste per year or a fixed efficiency require-
ment over a period of a year are inap-
propriate.
Any measure of waste-reduction ef-
ficiency must be based upon an unam-
biguous definition of the "waste" subject to
reduction. Reporting of waste-reduction
progress on a chemical-specific basis is most
feasible if a normalizing factor is used.
Because no single normalizing scheme is
generally applicable to all manufacturing
facilities, attempts to calculate a ratio of the
amount of a chemical in the waste to the
amount of the same chemical in one or more
mass balance components would lead to a
lack of uniformity in reporting and inter-
pretation.
Actual waste-reduction progress is best
defined and monitored by the generator at
the production-unit level. Progress in
reduction is masked when the mass balance
data from a smaller reporting unit, such as a
production unit, are used to develop an
industry-wide or national statistic. This
masking of progress associated with a
specific product also takes place when a pro-
duction unit produces many products and
generates multiple wastes that are accounted
for in a combined fashion.
A production-normalized weighting sta-
tistic could be used to measure waste-reduc-
tion progress at the facility or industry level.
However, the diversity of chemical products
and manufactured goods that involve the use
of toxic chemicals often makes it difficult to
normalize waste data on a consistent and
comparable basis. Specific data on produc-
tion units must be used if meaningful waste-
reduction statistics are desired at a national
level; it would be difficult to assemble the
data at this level. The use of chemical-spe-
cific data for normalization further increases
calculational problems significantly and
raises serious concerns about confidentiality
because of the detailed data that must be
OCR for page 55
ASSESSING WASTE-REDUCTION EFFICIENCY
supplied. Even such a normalized statistic
must be interpreted with caution, because
the relationship between waste generation
and production might not be linearly corre-
lated.
MA data, such as waste reports,
production reports, and descriptions of
waste-handling practices, coupled with
descriptions of the results of implemented
waste-reduction techniques, could in some
cases contribute to forming a useful picture
of waste-reduction progress and help
provide information on reduction techniques.
Such reporting could not, however, be
meaningfully aggregated at the industry or
national levels because too much information
on indiviclual production processes is lost,
and waste-reduction progress would likely
be obscured. There is no advantage in
providing the raw material input informa-
tion in reporting waste-reduction progress.
The greater the number of listed and un-
listed chemicals involved with this approach,
55
the more intractable the problem of inter-
pretation and comparison of progress within
between, or among industries.
Basing evaluation of waste-reduction
progress data on the reduction of specific
chemicals is not necessarily more effective
than basing it on the reduction in total
quantity of waste-chemical constituents or
waste toxicity. The reduction of a listed
chemical might not reduce the total waste
stream and could increase the quantity
through greater use of a nonreguiated
material of unknown hazard or toxicity.
Expert analytic assistance as an adjunct to
an MA data collection program would be
helpful in addressing whether waste reduc-
tion has been accomplished by replacing a
chemical of known health effects with a dif-
ferent chemical of unknown health effects.
Normalized data by themselves might show a
reduction in waste, but they would not indi-
cate whether any change in potential health
effects had occurred.
OCR for page 56
Representative terms from entire chapter:
waste generated
