Draft

Technical Support Document for

HWC MACT Standards (NODA)

Volume III: Evaluation of Metal Emissions Database to Investigate

Extrapolation and Interpolation Issues

U.S. Environmental Protection Agency

Office of Solid Waste and Emergency Response (5305)

401 M Street, SW

Washington, D.C. 20460

April 1997
ABSTRACT

Existing U.S. EPA guidance on using extrapolation or interpolation to project emission

levels based on measured feed rates and emissions levels is re-evaluated. The evaluation is based

on theoretical considerations as well as recent compilation of metals feed rate and emission results

from many hazardous waste combustor trial burn compliance tests as part of the EPA’s

development of revised emissions standards for hazardous waste combustors.

“Upward” extrapolation (from the origin) is conservative for all metal types and volatilities

(i.e., emission levels predicted at a higher feed rate based on extrapolation from measured

emissions levels at a lower feed rate tend to be greater than or equal to the actual emission levels at

the higher feed rate). This is because the metals system removal efficiency tends to stay the same

or increase with increasing feed rate. This is supported by theory, as well as analysis of a limited

data set. Thus, upward extrapolation continues to be recommended as a valid alternative for setting

metals feed rate limits. “Downward” extrapolation may be appropriate for certain metal types and

feed rate ranges. However, because theory and limited emissions data analysis indicate that it may

not produce conservative results in some cases, it can not be generally recommended. Potential

extrapolation implementation procedures are discussed, including the use of a “universal variability

factor”.

i
ACKNOWLEDGMENTS

This document was prepared by EPA’s Office of Solid Waste, Waste Minimization and

Management Division. Energy and Environmental Research Corporation (EER) provided technical

support under EPA contract No. 68-D2-0164.

ii
CONTENTS

ABSTRACT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . i

ACKNOWLEDGMENTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii

FIGURES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv

TABLE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vi

ACRONYMS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii

1.0 INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

2.0 CURRENT BOILER AND INDUSTRIAL FURNACE RULE GUIDANCE . . . . . . . . 1

3.0 RELATIONSHIP BETWEEN METALS FEED RATE AND EMISSION RATE . . . . . 2

Theoretical Considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

Trial Burn Source Testing Evaluations . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

Individual Metals From the Same Facility . . . . . . . . . . . . . . . . . . . . . 4

Groups of Similar Behaving Metals From the Same Facility . . . . . . . . . 7

Conclusions on Appropriateness of Extrapolation . . . . . . . . . . . . . . . . . . . . . 7

4.0 DEVELOPMENT OF AN EXTRAPOLATION PROCEDURE . . . . . . . . . . . . . . . . . 9

5.0 REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

iii
FIGURES

1 Basis for Boiler and Industrial Furnace Guidance on extrapolation . . . . . . . . . . . . . . . 15

2 Theoretical relationship between metals emissions and feed rate . . . . . . . . . . . . . . . . . 16

3 Relationship between metals emissions and feed rate for metals groupings . . . . . . . . . 17

4 Metals emissions and feed rate relationships -- Hearth incinerator with SD/VD/PBS

(Du Pont Experimental Facility Incinerator, Wilmington, DE; ID No. 700) . . . . . . . . . 18

5 Metals emissions and feed rate relationships -- Rotary kiln incinerator with

WHB/VS/PT/HS (ENSCO, Bridgeport, NJ; ID No. 807) . . . . . . . . . . . . . . . . . . . . 19

6 Metals emissions and feed rate relationships -- Rotary kiln incinerator with VS

(Tennessee Eastman, Kingsport, TN; ID No. 809) . . . . . . . . . . . . . . . . . . . . . . . . . 20

7 Metals emissions and feed rate relationship -- Rotary kiln incinerator with IWS 

(Rollins, Baton Rouge, LA; ID No. 214) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

8a Metals emissions and feed rate relationship -- Liquid injection incinerator with

WHB/FF/VQ/PT (Laidlaw, Roebuck, SC; ID No. 209) . . . . . . . . . . . . . . . . . . . . . . 22

8b Metals emissions and feed rate relationship -- Liquid injection incinerator with

WHB/FF/VQ/PT (Laidlaw, Roebuck, SC; ID No. 209) . . . . . . . . . . . . . . . . . . . . . . 23

9 Metals emissions and feed rate relationships -- Rotary kiln incinerator with 

WS/ESP/PT (3M, Cottage Grove, MN; ID No. 334) . . . . . . . . . . . . . . . . . . . . . . . . 24

10 Metals emissions and feed rate relationships -- Liquid injection incinerator with

VS/PBS (Tennessee Eastman, Kingsport, TN; ID No. 810) . . . . . . . . . . . . . . . . . . . 25

11 Metals emissions and feed rate relationship -- Rotary kiln incinerator with

SD/FF/WS/IWS (Aptus, Coffeyville, KS; ID No. 325) . . . . . . . . . . . . . . . . . . . . . . 26

12 Metal emissions and feed rate relationship -- Rotary kiln incinerator with

SD/FF/WS/WESP (Aptus, Aragonite, UT; ID No. 327) . . . . . . . . . . . . . . . . . . . . . 27

13 Metal emissions and feed rate relationship -- Rotary kiln incinerator with HE/FF

Lake City Army Ammunition Plant, Independence, MO; ID No. 503) . . . . . . . . . . . . 28

14 Metals emissions and feed rate relationships (EPA IRF, Arkansas, rotary kiln

incinerator with VS/PB) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

15 Metals emissions and feed rate relationships -- Cement kilns (Keystone Cement,

Bath, PA; No. 207/208) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

16 Metals emissions and feed rate relationship -- Cement kilns (Holnam, Holly Hill, SC;

ID No. 205/206) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

17 Metals emissions and feed rate relationships -- Cement kiln with FF (Southdown,

Knoxville, TN; ID No. 316) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

18 Metals emissions and feed rate relationships for individual metals and facilities with

multiple conditions -- Cement kilns (Lafarge, Fredonia, KS; ID No. 322/323) . . . . . . . 33

19 Metals emissions and feed rate relationship for individual metals and facilities with

multiple conditions -- Cement kiln (Lone Star Industries, Inc., MO; No. 303) . . . . . . . 34

20 Metals emissions and feed rate relationship for individual metals and facilities with 

multiple conditions -- Cement kilns (Ash Grove Cement Company), Chanute, KS;

ID No. 401/402) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

21 Metals emissions and feed rate relationships -- Light weight aggregate kilns with

FF/VS (Norlite, Cohoes, NY; ID No. 307) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

iv
22a Selected metals emissions and feed rate relationships . . . . . . . . . . . . . . . . . . . . . . . . 37

22b Selected metals emissions and feed rate relationships . . . . . . . . . . . . . . . . . . . . . . . . 38

23a Metals emissions and feed rate relationships for low volatile metals groupings for

individual facilities (cement kilns) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

23b Metals emissions and feed rate relationships for low volatile metals groupings from

individual facilities (cement kilns) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40

24 Metals emissions and feed rate relationship for low volatile metals groupings for 

individual facilities (incinerators and boilers) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

25 Metals emissions and feed rate relationship for low volatile metals groupings for

individual facilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

26 Chromium feed rate and emissions relationship for all hazardous waste burning

combustors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

27 Lead feed rate and emissions relationships for all hazardous waste burning

combustors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44

28 Options for the trial burn metals extrapolation procedure . . . . . . . . . . . . . . . . . . . . . 45

29 Residual analysis for semi volatile metals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46

30 Modified hybrid trial burn metals extrapolation procedure . . . . . . . . . . . . . . . . . . . . . 47

31 Illustration of the conservative impact of extrapolation off of stack gas detection

limit trial burn measurement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

v
TABLE

1 Metals residual analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

vi
ACRONYMS

APCD Air pollution control device

BIF Boilers and industrial furnaces

dcfm dry standard cubic meter

EPA Environmental Protection Agency

ESP Electrostatic precipitator

FF Fabric filter

HE Heat exchanger

HS Hydrosonic eductor scrubber

IRF Incineration Research Facility

IWS Ionizing wet scrubber

MACT Maximum achievable control technology

μg microgram (10-6 gram)

ng nanogram (10-9 gram)

NODA Notice of data availability

PB Packed bed

PBS Packed bed scrubber

SD Spray dryer

SRE System removal efficiency

PM Particulate matter

PT Packed tower

UVF Universal variability factor

VQ Venturi quench

VS Venturi scrubber

WESP Wet electrostatic precipitator

WHB Waste heat boiler

WS Wet scrubber

vii
1.0 INTRODUCTION

This report is the third of three technical support documents for the U.S. Environmental

Protection Agency’s Notice of Data Availability on updates to the proposed “maximum achievable

control technology” (MACT) standards for hazardous waste combustors. The three volumes

include:

• Volume I: MACT Evaluations Based on Revised Database. Re-evaluation of MACT floor

standards for existing and new sources based on proposed rule comments and data

submissions.

• Volume II: Evaluation of CO/HC and DRE Database. Evaluation of the behavior of

principal organic hazardous constituent destruction and removal efficiency with carbon

monoxide and hydrocarbons emissions,

• Volume III: Evaluation of Metals Emissions Database to Investigate Extrapolation and

Interpolation Issues. Re-evaluation of the use of metals extrapolation and interpolation to

set metals feed rate limits based on compliance testing measurements.

Volume III: Evaluation of Metals Emissions Database to Investigate Extrapolation and

Interpolation Issues is a re-evaluation of existing U.S. EPA guidance on using extrapolation or

interpolation to project emission levels based on measured feed rates and emission levels. This is

of interest to the hazardous waste combustor community for reasons including: (1) potentially

eliminating the need to use large quantities of expensive and toxic metals for spiking in future

compliance tests (e.g., trial burns, MACT performance tests); and (2) potentially avoiding retesting

requirements brought about by more stringent metals emissions limits as a result of new risk

assessment procedures and new regulatory requirements. This evaluation is based on theoretical

considerations as well as recent compilation of metals feed rate and emissions results from many

recent hazardous waste combustor trial burn compliance tests as part of the Agency’s development

of revised emissions standards for hazardous waste combustors.

2 . 0 CURRENT BOILER AND INDUSTRIAL FURNACE RULE GUIDANCE

The Boiler and Industrial Furnace Implementation Document (U.S. EPA, 1992) provides

guidance on conducting trial burn metals feed rate and emissions rate interpolation and

extrapolation for setting permit limits on metals feed rates which may be summarized as follows:

• Interpolation -- Interpolation, based on projecting between two trial burn test series at

different feed rates, is recommended as long as the test series are conducted over a

“reasonably limited” feed rate range.

• Extrapolation -- Allowances for upward and downward extrapolation are based on metals

behavior and considerations shown in Figure 1:

1
Upward -- Upward linear extrapolation is recognized to be conservative in principle,

conservative in that a linear upward feed rate projection through the origin (i.e., at a metal

feed and emissions rate of zero) will overestimate the predicted actual emissions due to an

increase in metal system removal efficiency (SRE) as feed rate is increased, as discussed in

great detail in the next section. However, it is not generally recommended for setting

permit limits because of the lack of validation data. Upward extrapolation may be

appropriate if an adequate “safety factor” is used (in cases where the desired feed rate

corresponds to an emissions level that is much lower than the emissions limit). A safety

factor of 10 is suggested as adequate.

Downward -- Downward extrapolation through the origin is not recommended since

theoretical considerations indicate that it may not produce conservative feed rate limits (i.e.,

emissions are predicted to be higher than those based on a downward linear projection due

to a decrease in SRE as feed rate is decreased).

3.0 RELATIONSHIP BETWEEN METALS FEED RATE AND EMISSION

RATE

3.1 THEORETICAL CONSIDERATIONS

A variety of parameter impact metals emissions, including metal feed rate, metals species

and form, waste type and constituents (such as chlorine, sulfur, earth and mineral elements), air

pollution control system type and operation, facility operational practices (dust recycle rates, soot

blowing), and combustor system operating parameters (such as temperatures and temperature

profiles) and design parameters (e.g., rotary kiln, controlled air types). However, for a given

fixed system with all things remaining equal except metals feed rate, the general relationship

between metals feed rate and stack gas emissions that is expected based on theoretical

considerations is shown in Figure 2. There are three distinct regimes, each of which has a linear

relationship between feed rate and emissions, but a different “slope” which is related to the metal

removal efficiency:

• Region A -- In the first regime, bounded from the plot's origin (with a metal feed rate input

and emissions rate of zero) to the upper breakpoint (labeled with a “1”), the metal fully

vaporizes in the combustor since the vapor pressure of the metal at the combustion

temperature is high enough to put the entire metal feed into the vapor phase. All of the

metal feed is carried from the combustor as vapor with the flue gas. In this region, the

metal remains in the vapor phase throughout the entire system, including the lower

temperatures of downstream air pollution control. Typically in the Region A for systems

with traditional air pollution control devices designed for removing solid metal containing

particulate matter and fume such as fabric filters and electrostatic precipitators, metals are

not being controlled (i.e., what is fed flies entirely to the stack as emissions, with a

corresponding SRE of zero). For certain metals, control may be achievable through the

removal of metals vapors with specialized techniques such as absorption (e.g., in wet

scrubbing solutions) or adsorption (e.g., in activated carbon sieves).

2
• Region B -- As the feed rate of a metal continues to increase in Region A, the metal vapor

pressure at the air pollution control device temperature becomes "saturated" with the metal

(the saturated metal vapor pressure is the maximum level of metal that will remain in the

vapor form; additional metal beyond this point will be in a solid condensed form). At this

breakpoint “1”, metals which fully vaporize in the combustion chamber begins to condense

out at the lower temperature air pollution control device. Condensation of metal vapor is

known to take place homogeneously to form fine fume and heterogeneously, preferentially

also on fine entrained and formed particulate. The removal of the condensed metal

(typically contained primarily on submicron particulates) is related directly to the ability of

the air pollution control device to remove this submicron particulate from the flue gas. The

slope of the curve in Region B is determined by the removal efficiency of the fine

particulate matter (PM) containing material. A baghouse with a high fine PM removal

efficiency would be expected to produce a “shallower” slope compared with that from a

lower efficiency wet scrubber. In the case where no air pollution control device is used,

the metal system removal efficiency would remain at zero, as in Region A.

• Region C -- Region C begins and Region B ends when the saturated vapor pressure of the

metal at the combustion temperature is reached. Note that the saturated or “effective” vapor

pressure of a metal depends on a variety of factors, among which temperature and the

concentration of chlorine, oxygen, and sulfur in the gas are some of the most important.

Additional metals fed beyond this point will remain as condensed solids at the waste

burning location (contained in the bottom and fly ash of incinerators, or clinker or light

weight aggregate for industrial process kilns). Metals stack gas emissions and control in

Region C are attributable to the degree of entrainment and subsequent control of metal

containing ash particles (“fly ash”) out of the combustor. Emissions of metals will

continue to increase in Region C as the feed rate increases due to the increased

concentration of metals in the entrained fly ash, but not as rapidly as in Region B since no

more additional metals can vaporize and since air pollution control devices typically collect

larger entrained metals containing particles more efficiently than condensed fines and fumes

of Region B.

The occurrence and significance of these three regions depends on the metal type (e.g.,

lead, mercury, or chromium), and its volatility characteristics. As shown in Figure 3, for the high

volatile metals (such as mercury and selenium) which have very high vapor pressures at both the

combustion and air pollution control device temperatures, Region A may span most typical feed

rates. Note that for mercury when chlorine is present, saturated vapor pressures are extremely

high (on the order of millions of μg/dscm) even at wet scrubber temperatures. This has been

confirmed through detailed source testing work showing very low system removal efficiencies as

well as the dominance of these metals as vapors in stack gas emissions measurement trains (as

indicated by the presence of the metals in the “back-half” fraction of the multiple metals sampling

train). Breakpoint “1” may not be reached in conventional practice. Semi-volatile and lowvolatile metals have extremely low vapor pressures at typical air pollution control device

temperatures (< ng/dscm). This is confirmed through effective removal of these metals in

3
particulate matter air pollution control devices, as well as the major presence of these metals in the

“front-half” of the metals sampling train for stack gas measurements. Thus Region A is relatively

non-existent for semi-- and low-volatile metals. For semi-volatile metals (such as lead, cadmium,

and thallium), Region B dominates over a large range of metals feed rates since the vapor pressure

of these metals at combustion temperatures is typically extremely high (on the order of millions of

μg/dscm). For low-volatile metals (such as chromium, barium, nickel, and beryllium), Region C

may dominate, since Region B may be small due to the small vapor pressures of low-volatile

metals at combustion temperatures.

3.2 TRIAL BURN SOURCE TESTING EVALUATIONS

Hazardous waste combustor trial burn and compliance test metals feed rate and emissions

rate data were evaluated in a couple of different ways to assess the relation between metals feed

rates and emissions. These are discussed below. Note that stack gas emissions test data are

considered only when measure at levels above the analytical method detection limit; consideration

of data reported at the method detection limit may provide misleading results.

3.2.1 Individual Metals From the Same Facility

Emissions and feed rate data from the same facility (or similar units on the same site) and

same metal were evaluated in cases where a large range of feed rates were available. This was

usually true only when multiple test conditions were associated with the same facility. These are

shown in Figures 4 through 14 for incinerators. More limited data for cement kilns is shown in

Figures 15 through 20. Data from only one light weight aggregate kiln are shown in Figure 21;

no examples for boilers were available.

The data in Figure 4 are of more importance than the others since they are a product of

testing conducted under very well controlled conditions during the same time period. Additionally,

they constitute the only testing that was conducted with the intention of directly evaluating the

relationship between feed rate and stack gas emissions rate (Hinshaw et al., 1993). Testing is

from the Du Pont Experimental Station at the Wilmington, Delaware unit which includes a

monohearth incinerator with spray dryer, reverse jet cooler, venturi scrubber, and three stage baffle

absorber air pollution control system. Liquid and solid wastes were spiked with liquid metals

solutions containing Be, Cd, As, Cr, and Pb. The tests were conducted at 2,000 ̊F combustion

temperature with high chlorine levels (4 to 10% by weight). Best fit linear regressions are shown

on each plot. The relation between stack gas emissions and feed rate is highly linear through the

origin for Be, Cd, As, and Pb over the entire range of feed rates tested. This would appear to

support a reasonable extrapolation upward or downward to different feed rates linearly through the

origin. For Cr however, one may imagine that there are two regions based on theory, where the

slope of the line at the lower feed rates starts out relatively steep, and levels off as the feed rate is

increased. Keep in mind that even for this highly controlled set of tests, there is wide data scatter

at the high feed rates. Also, note that for lower volatile metals of Be, As, and Cr, the maximum

feed rate that was used was not that high (6000 μg/dscm for Cr as compared with 500,000

4
μg/dscm for Pb), thus the point at which the curve begins to flatten out (in particular for Be and

As) may occur at higher feed rates that were not used in the testing.

Interestingly, for the semi-volatile metals of Cd and Pb, the system removal efficiencies

(indicated by the slope of the feed rate and emissions rate curve) are very similar (both at 80%),

indicating that Cd and Pb may be effective surrogates for each other. Additionally, since they have

the same SRE, they would fall on the exact same line if shown on the same feed rate and emissions

plot. This appears to support a linear relationship through the origin for semi-volatile metals over a

very large range of feed rates. In a similar manner, Be, As, and Cr also have relatively comparable

SREs (Be of about 93%, Cr also at 93%, and As at 84%). This would indicate that Be and Cr

could potentially be used as surrogates for each other, but not for As.

Data from the other incinerator, cement kiln, and light weight aggregate facilities shown in

Figures 5 through 21 are discussed briefly. Generally, data scatter makes it difficult to determine

relationships. However, keep in mind the following general trends as the facility data are

reviewed:

• Emissions tend to increase as feed rate increases.

• The relationship between emissions rate and feed rate for lower volatile metals tends to be

very flat (not a strong function of feed rate). This is because SRE strongly tends to

increase with increasing feed rate (i.e., the curve between metals emissions and feed rate is

concave in shape since emissions levels increases are not generally proportional to feed rate

increases).

• The relationship between emissions and feed rate for high- and semi-volatile metals tends to

be stronger than that for low volatile metals (i.e., there is a more proportional relationship

between emissions and feed rates).

Note that for most of these facilities, testing was generally conducted years apart which

may be contribute to some of the data spread and variability due to changes in facility

characteristics, conditions, and operating practices.

• Figure 5 (incinerator, ID No. 807) -- The feed rate and emissions rate for Pb and Cd is

fairly proportional, with Pb being fed at much higher feed rates and being controlled about

twice as effectively. The relationships for Cr, As, and Ba are very “flat” (no strong

correlation between emissions and feed rate) with lots of data scatter.

• Figure 6 (incinerator, ID No. 809) -- Data are available from this site at vary low and very

high feed rates. A proportional fit through the origin appears reasonable for all metals

except Cr, which may have some type of breakpoint as based on theory (i.e., two linear

regions with different slopes). Additional data at intermediate feed rates are needed to

confirm this.

5
• Figure 7 (incinerator, ID No. 214) -- There is no strong relationship (extremely flat) for the

lower volatile Ba and Cr. There is a slightly stronger relationship for Cd and Pb, which

both have similar SREs.

• Figures 8a and 8b (incinerator, ID No. 209) -- There is no strong relationship (extremely

flat) for the lower volatile Cr, Sb, As, and Ba. It is also flat for Cd and Pb. There is a

stronger relationship for Tl.

• Figure 9 (incinerator, ID No. 334) -- There is a fairly proportional relationship for As and

Ba. For Cd and Pb, the data at the low feed rates are suspect since SREs are < 0. Data

scatter for Cr makes it difficult to assess. 

• Figure 10 (incinerator, ID No. 810) -- Like Figure 6 (facility ID No. 809), data are

available from very low and very high feed rates. Unlike ID No. 809, it indicates that a

linear proportional fit through the origin may not be appropriate. It may support the two

region break point, where at low feed rates in Region 1 the curve has a large slope,

followed by flattening off at higher feed rates in Region 2. However, additional

intermediate feed rate data are needed to confirm this. The low feed rate data may be in

error.

• Figure 11 (incinerator, ID No. 325) -- There is no relationship for any of the metals (all

“flat”). Lots of data scatter.

• Figure 12 (incinerator, ID No. 327) -- There is no relationship for any of the metals except

possibly for Ba. Lots of data scatter.

• Figure 14 (incinerator) -- A series of parametric tests were conducted at the EPA’s IRF

facility to assess As behavior for two different waste types. Emissions increase at higher

feed rates, although not proportionally through the origin since the SRE at the higher feed

rate is lower than that of the lower feed rate, as opposed to theoretical predictions and most

of the other facility data. This highlights effects that may be due to differences in waste

types and arsenic types that may make it difficult to evaluate the feed rate and emissions

relationship for testing done at different conditions.

• Figure 15 (cement kiln, ID Nos. 207/208) -- There is a fairly strong relationship for Cd,

Pb, and Ag. Flat for Cr and Ni.

• Figure 16 (cement kiln, ID Nos. 205/206) -- This data set is interesting because it is from

the same cement kiln during two different testing periods (1992 and 1995). There is

relatively high variability in the emissions data from the different test series that were

conducted at similar feed rates; illustrating the difficulty in comparing different trial burn

results even from the same facility. This is due to a variety of factors associated with

emissions source testing in full scale systems that effect measurement repeatability,

6
including facility “memory” effects, differences in operating conditions, equipment

conditions, and a host of sampling and analytical considerations.

• Figures 17 through 21 (cement kilns and one light weight aggregate kiln) -- There is a

general increase in emissions with feed rate, typically stronger for Cd and Pb. However,

with limited feed rate ranges and data scatter, it is not possible to identify regions and

breakpoints.

3.2.2 Groups of Similar Behaving Metals From Similar Types of Facilities

Individual metal data from similar types of facilities were compared. Groupings included:

(1) different source categories including boilers, incinerators, cement kilns, and light weight

aggregate kilns; and (2) groups from the same source category using the same type of air pollution

control device. Examples of these are shown in Figure 26 for chromium and Figure 27 for lead for

different source categories (each differentiated by a different symbol). This analysis demonstrates

that it is difficult to observe trends in data taken from a number of facilities (even of common type)

because of the variances produced from differences in control device, feed rates, operating

parameters, and measurement techniques. However, generally for chromium (and other lowvolatile metals), emissions tend to not be a strong function of feed rate (i.e., system removal

efficiency tends to increase as the feed rate increases, as might be expected based on theoretical

considerations). For lead (and other semi-volatile metals), emissions tend to be a stronger function

of feed rate (increasing with feed rate), although system removal efficiency tends to increase with

feed rate as it does with low volatile metals. Note that feed rates are shown on log scale; system

removal efficiency only decreases rapidly at very low feed rates.

3.3 CONCLUSIONS ON APPROPRIATENESS OF EXTRAPOLATION

Theoretical volatility predictions indicate that the relationship between feed rate and

emissions rate is not strictly linear for semi- and low-volatile metals, although it may be linear over

a generally large range of feed rates for semi-volatiles, and also for very low volatiles. Scatter in

data and/or lack of feed rate ranges makes it difficult to determine a relationship for much of the

trial burn data. Inability to determine regions and breakpoints as predicted from theory may be due

to either insufficient data (not enough spread of feed rates), change in slope being too small to

notice, or absence of such behavior in actual practice. In any case, the following conclusions are

drawn:

• Emissions data generally confirm that for individual facilities, an increase in feed rate

produces an increase in emissions, as expected.

• For the semi-volatile metals (Cd, Pb, and Tl), most of the available trial burn emissions

data tend to generally confirm a proportional relation through the origin between emissions

and feed rates over a large range of feed rate, as based on theory.

7
• For lower-volatile metals (Cr, Ba, As, Be, Ni), due to low emissions levels from typically

high SREs compared with those of semi-volatile metals, the relationship is more “flat” due

to SRE increasing with increasing feed rate. Note that it is difficult to evaluate the precise

relationship based on the trial burn data for many of the facilities due to the influence of

measurement “noise” at the low emissions levels. Theory indicates that the “breakpoint”

of the relationship may fall within a typically encountered feed rate for metals that have

“medium” volatility, such as As or Sb.

• Fairly strong proportional relationships are shown for some limited facilities and metals

types and feed rate ranges (both semi- and low-volatile metals). This is particularly evident

from data from one well controlled series of tests designed specifically to evaluate feed rate

impacts.

• Emissions data from common groups of facilities indicates a general trend for SRE to

decrease with decreasing feed rates, as expected based on theory, although not until very

low feed rates.

Based on these conclusions, the following recommendations are made on the

appropriateness of upward and downward extrapolation:

• Upward Extrapolation -- Upward extrapolation through the origin can be implemented in a

manner that is conservative for all metal types and volatilities since SRE tends to stay the

same or increase with increasing feed rate (i.e., emission levels predicted at a higher feed

rate base on extrapolation from measured emission levels at a lower feed rate tend to be

greater than or equal to the actual emission levels at the higher feed rate). This is supported

by theory, as well as limited emissions data analyses. Thus it continues to be

recommended.

• Downward Extrapolation -- Theory and limited emissions data analysis indicates that the

relationship between metals feed rates and emissions may be proportional over large ranges

of feed rates; however, breakpoints separating different linear regimes may be present as

discussed in detail previously. For high- and semi-volatile metals this breakpoint is present

at extremely high feed rates. Thus, downward extrapolation through the origin may be

appropriate for semi and high volatile type metals. For lower volatile metals, however, the

position of the regime transition point is not as clear. Based on limited trial burn data, it

may be reasonable to interpolate linearly through the origin for very low volatile metals

such as Be. However, theory and other limited data indicate that it may not produce

conservative results in some cases. Thus, based on the available data and theoretical

consideration, it can not be generally recommended to extrapolate downward through the

origin for lower volatile metals.

8
4 . 0 DEVELOPMENT OF EXTRAPOLATION PROCEDURE

A variety of options may be considered for the implementation of metals extrapolation and

interpolation, including, as shown in Figure 28, projection from the:

(a) highest compliance test run;

(b) average of the compliance test runs;

(c) level based on statistical evaluation of the compliance test runs; or

(d) level based on the average of the compliance test runs with the consideration of a “universal

variability factor” applied to the average.

Although less conservative, option (c) has an advantage over option (d) in that it would not

penalize facilities that had low within-test condition emissions variability. Under this option, a

site-specific variability factor could be determined from actual compliance test data, perhaps based

on the test average emissions plus the standard deviation of the runs multiplied by a confidence tfactor.

The following discussions pertain to option (d). Under this option, a “universal variability

factor” (UVF) would be identified. This is done by evaluating the within-test condition variability

of all available hazardous waste combustor trial burn and BIF certification testing metals stack gas

emissions measurements. Within condition, individual run “residuals” were evaluated as:

(1) Ri = Ci - Cavg

where Ci = log (Xi)

Cavg = average (Ci)

Xi : individual run metals stack gas emissions concentration (within a given condition)

Ri : individual run residual

Examples of the results of the residual analysis are shown in Figures 29 for semi-volatile

metals. Residuals are shown both as a function of condition geomean as well as a probability plot

of the absolute value of the residuals. Note that the residuals are evenly distributed about 0, and

are not a function of the geomean, as expected after having been transformed to the log plane. The

UVF would be established as the 95th percentile residual (meaning the level at which 95 percent of

the residual population is at or below). The 95th percentile residual was determined based on the

probability plots as well as with a statistical analysis of the residual data set. Both procedures

produced very similar results. Table 1 shows the 95th percentile residuals for the various metals

groupings and individual metals. Residuals tend to be the highest for high-volatile metals, and

similar and lower for low- and semi-volatile metals.

9
The UVF could be used for extrapolations under several approaches: (1) using a metalspecific UVF, where the multipliers to the average compliance test emissions would range from

1.9x’s to 5.1x’s; (2) using a common UVF for all metals as the average of the metal-specific

UVFs, where the multiplier would be 3.5x’s; or (3) using a UVF for each volatility group based

on either the highest UVF for each metal in the group or the average UVF for metals in the group.

Under option 3 where the UVF is based on the highest UVF for each metal in the group, the

multipliers would be 5.1x’s for high-volatile metals, 3.6x’s for semi-volatile metals, and 4.3x’s

for low-volatile metals. Alternatively, where the UVF is based on the average UVF for metals in

the group, the multipliers would be 5.0x’s for high-volatile metals, 3.1x’s for semi-volatile metals,

and 3.4x’s for low-volatile metals. Given that the UVFs are higher for high-volatile metals, and

that the metal-specific UVFs vary considerably for semi- and low-volatile metals, it may

appropriate to use the option 3 approach where the UVF is based on the highest UVF for each

metal in the volatility group.

Note that the higher UVFs for high-volatile metals may be attributable to the difficulty in

sampling and analysis for more volatile species due to losses and errors associated with the

capture, recovery, digestion, analysis, etc. Higher variability may also be attributable to the

extremely low levels of the high-volatile metals--Hg and Se--that are typically present in

combustion stack gases. However, this argument is not entirely consistent for low-volatile metals,

where the variability for Be is lower than that of Cr even though Be is usually only a small fraction

of the Cr level in the stack gas. In any case, within-test condition variability can be attributable to a

variety of factors including:

• Differences in feed rates within condition;

• Variability in waste types and operating conditions;

• System non-equilibrium and memory effects; and

• Accuracy and precision of the multiple metals train EPA Draft Method 29 (+ 20% according

to the method developers).

Extrapolated feed rate and emission limits would be set based on the universal variability

factor application as:

(2) FRproj = FRct x 

ERlimit

ERunvf

where: FRproj : Extrapolated/interpolated feed rate limit

FRct : Compliance test feed rate (average)

ERct : Compliance test average stack gas emissions rate

ERlimit : New stack gas emissions limit

10
and:

(3) ERunvf = 10

[ C avg + UVF] 

Cavg = average (log Xi)

Xi : individual compliance test stack gas emissions rates

UVF : Universal variability factor in log plane (95th percentile residual for the metal

grouping of interest)

Note that the UVFs (in the log plane) shown in Table 1 have a value of about 0.3 to 0.7. When

applied to the trial burn condition average emissions level in Equation (3), they increase the level

by about a factor of about 3 (i.e., ERunvf is about equal to 3 times the compliance test condition

average emissions level).

However, strict use of the universal variability factor procedure of Equation (1) would not

be useful if: (1) the maximum allowable emission rate is close to the compliance test emission rate;

and (2) the UVF-adjusted emission rate is higher than the highest run (as it will generally be).

Additionally, the use of the conservative UVF may not be warranted when projecting near the

compliance test feed rate since the potential errors associated with the compliance test

measurements (such as those from feed rates and emissions stack gas measurements) will not be

significantly magnified when projecting near to the compliance test emission level. However, as

the projection increases significantly beyond that emission level, the magnification of errors may

become more important. Thus, the use of the UVF approach is warranted at feed rates

significantly different than that of the trial burn. Note that with the UVF approach, a variance

factor is used as opposed to a fixed increment; the variance factor acts to magnify the safety margin

as the projected feed rate increases (i.e., the safety factor remains constant as the feed rate

increases). 

Based on these considerations, the following UVF implementation approach may be

appropriate, as illustrated in Figure 30:

• When extrapolating to feed and emission rates significantly beyond that of the compliance

test, use the UVF.

• When extrapolating to feed and emission rates near that of the compliance test, use a

combination of extrapolating using the UVF and extrapolating from the highest compliance

test run. Assuming it would be appropriate to use this less conservative approach to

extrapolate emissions upward in the range from the highest run of the compliance test to an

emission level of, for example, 2x’s the compliance test average emissions adjusted by the

UVF, the extrapolation would be based on a line drawn from the highest compliance test

run to that emission level (i.e., 2x’s the compliance test average emissions adjusted by the

UVF). If it were appropriate to extrapolate emissions downward, the extrapolation line

11
could be drawn from the highest compliance test run to an emission level of, for example,

0.5x’s the compliance test average emissions adjusted by the UVF.

This corresponds to the use of the following equations for the determination of the

projected feed rate, based on the compliance test feed rate (FRct) and emissions levels (ERhr), the

universal variability factor (ERunvf), and the desired stack gas emissions level (ERlimit):

Upward Extrapolation:

For projecting to desired emissions levels (ERlimit) between the compliance test highest run

(ERhr) and 2x’s the emissions limit based on the universal variability factor (ERunvf) (i.e.,

ERhr < ERlimit , 2 x ERunvf):

(4) FRproj = 

FRct

2 ERunvf − ERhr

 x ERlimit − 2 ERhr + 2 ERunvf

where ERhr : Emissions rate of highest individual run of the compliance test

condition

For projecting to desired emissions levels (ERlimit) greater than 2x’s the emissions limit

based on the universal variability factor (ERunvf):

use Equation (2)

Downward Extrapolation:

For projecting to desired emissions levels (ERlimit) between the compliance test highest run

(ERhr) and 0.5x’s the emissions limit based on the universal variability factor (ERunvf)

(i.e., 0.5 x ERunvf < ERlimit < ERhr):

(5) FRproj = 

FRct

2 ERhr − ERunvf

 x ERlimit − ERunvf + ERhr

For projecting to desired emissions levels (ERlimit) less than 0.5x’s the emissions limit

based on the universal variability factor (ERunvf):

use Equation (2)

Note the additional following considerations when extrapolating metals feed rates and

emissions levels upward and downward:

12
• If an individual compliance test run is higher than the limit based on the condition average

plus the UVF, then the highest run is used for the projection.

• Extrapolation (upward or downward) from detection limit stack gas measurements is

conservative and appears to be appropriate, as shown in Figure 31.

• As per current practice when determining metals feed rates used during trial burns and BIF

certifications, non-detects in feed streams (metals measurements at the detection limit) are

treated as zero. Thus facilities which have non-detect measurements in all feed streams

would continue to be required to spike metals in order to set meaningful non-zero metal

feed rate limits.

• The use of the universal variability factor procedure penalizes facilities with compliance test

with low data spread. The procedure does not consider the variability of the actual

emissions data to determine the upper limit. As mentioned above, an alternative, less

conservative procedure might be considered which would be based on the projection from a

statistically determined limit based on the actual individual compliance test data (such as the

condition average of the stack gas emissions measurements plus the standard deviation of

the runs multiplied by a confidence t-factor, which would be evaluated at the degrees of

freedom of the number of runs and at some confidence level).

• Projection from compliance test feed rates based on metals spiking and/or homogeneous

metals waste analysis (such as those from liquids) should be encouraged. Feed rates from

these types of streams are typically much more accurate than those from waste analysis

measurements from difficult streams such as heterogeneous solid waste and raw material

and fuel streams. Projection of spiked and liquid metals feed rate data should generally be

more accurate. Note that solid waste feed rate measurements will typically systematically

err conservatively on the low side due to extraction problems and others associated with

losses during sampling and analytical activities. Laboratory contamination (resulting in

high side errors) are not typically as important for metals for example compared with

organics.

• Errors associated with the extrapolation procedure are due to inaccurate compliance test

data. To help prevent this, it is recommended that the quality assurance and quality control

associated with the compliance test measurements and operations (such as recoveries,

accuracy, precision, etc.) be conducted as required and documented and reviewed prior to

the extrapolation.

5 . 0 REFERENCES

Hinshaw, G., P.S. Murowchick, and R.F. Oranzi, “Parametric Testing of Metals Emissions From

the Du Pont Experimental Station Hazardous Waste Incinerator,” Proceedings of the 1993

Incineration Conference, pp. 823-829, Knoxville, Tennessee, May 3-7, 1993.

13
U.S. Environmental Protection Agency (U.S. EPA), “Technical Implementation Document for

EPA's Boiler and Industrial Furnace Regulations,” EPA 530-R-92-01, U.S. EPA Office of Solid

Waste and Emergency Response (OS-322), March, 1992.

14
Maximum

emission level

Actual metals

emissions curve

Metal Feed Rate

Metal Emission Rate

Trial burn point

1

2

4

5 3

Maximum

emission level

Actual metals

emissions curve

Metal Feed Rate

Metal Emission Rate

Trial burn point

1

2

4

3 5

Downward Extrapolation

Upward Extrapolation

Figure 1. Basis for Boiler and Industrial Furnace Guidance on extrapolation.

15
Metal Stack Gas

Emissions Rate

Metal Feed Rate

Figure 2. Theoretical relationship between metals emissions and feed rate.

Emissions level related to metal saturated vapor level at APCD temperature

Emissions break related to metal saturated vapor level at the combustion temperature

Breakpoints:

Regimes:

Slope related to capture of condensed fine fume PM

Slope related to capture of entrained larger PM

1

A

B

2

C

A

B

C

1

2

Slope related to capture of volatile metals

16
Metal Stack Gas Emissions Rate

Metal Feed Rate

Figure 3. Relationship between metals emissions and feed rate for metals groupings.

High

Volatile

Metals

Low

Volatile

Metals

Semi

Volatile

Metals

1 2

2

C

C

B

A

17
Pb y = 0.1943x - 303.37

R2

 = 0.8582

0

20000

40000

60000

80000

100000

120000

0 100000 200000 300000 400000 500000

Metal Emissions 

(μg/dscm)

Figure 4. Metals emissions and feed rate relationships -- Hearth incinerator with SD/VS/PBS 

(Du Pont Experimental Facility Incinerator, Wilmington, DE; ID No. 700).

Cr y = 0.0755x + 121.67

R2

 = 0.6071

0

200

400

600

800

1000

0 1000 2000 3000 4000 5000 6000

Metal Feed Rate MTEC (μg/dscm)

Metal Emissions 

(μg/dscm)

Cd

y = 0.1817x + 34.138

R2

 = 0.9368

0

100

200

300

400

500

600

0 500 1000 1500 2000 2500 3000

Metal Emissions 

(μg/dscm)

Be y = 0.0734x + 2.5094

R2

 = 0.8957

0

20

40

60

80

0 100 200 300 400 500 600 700

Metal Emissions 

(μg/dscm)

As

y = 0.1626x + 3.6335

R2

 = 0.8989

0

100

200

300

400

500

0 500 1000 1500 2000 2500

Metal Emissions 

(μg/dscm)

 18
As y = -9E-05x + 15.82

R2

 = 0.0028

0

10

20

30

40

0 5000 10000 15000 20000 25000 30000 35000 40000

Metals Emissions 

(μg/dscm )

Ba

y = 7E-05x + 24.015

R2

 = 0.2222

0

10

20

30

40

0 20000 40000 60000 80000 100000 120000 140000 160000 180000

Metals Emissions 

(μg/dscm)

Cd

y = 0.0018x + 23.783

R2

 = 0.067

0

20

40

60

80

100

120

0 5000 10000 15000 20000 25000

Metals Emissions 

(μg/dscm)

Cr

y = -9E-06x + 22.212

R2

 = 0.0032

0

10

20

30

40

0 50000 100000 150000 200000 250000 300000 350000

Metals Emissions 

(μg/dscm)

Pb y = 0.0012x + 1.8288

R2

 = 0.5481

0

50

100

150

200

250

300

350

0 50000 100000 150000 200000 250000

Metal Feed Rate MTEC (μg/dscm)

Metals Emissions 

(μg/dscm)

Figure 5. Metals emissions and feed rate relationships -- Rotary kiln incinerator with 

WHB/VS/PT/HS (ENSCO, Bridgeport, NJ; ID No. 807).

 19
Sb

0

2000

4000

6000

8000

0 200000 400000 600000 800000 1000000

Metals Emissions 

(μg/dscm)

As

0

50

100

150

200

250

300

0 5000 10000 15000 20000 25000 30000 35000

Metals Emissions 

(μg/dscm)

Cd

0

500

1000

1500

2000

0 5000 10000 15000 20000

Metals Emissions 

(μg/dscm)

Cr

0

100

200

300

400

500

600

0 50000 100000 150000 200000 250000 300000 350000 400000 450000

Metals Emissions 

(μg/dscm)

Pb

0

5000

10000

15000

20000

25000

0 50000 100000 150000 200000 250000

Metal Feed Rate MTEC (μg/dscm)

Metals Emissions 

(μg/dscm)

Figure 6. Metals emissions and feed rate relationships -- Rotary kiln incinerator with VS 

(Tennessee Eastman, Kingsport, TN; ID No. 809).

20
Ba

0

10

20

30

40

50

0 100000 200000 300000 400000 500000 600000 700000

Metals Emissions 

(μg/dscm)

Cd

0

100

200

300

400

500

600

700

0 50000 100000 150000 200000 250000 300000 350000

Metal Feed Rate MTEC (μg/dscm)

Metals Emissions 

(μg/dscm)

Cr

0

10

20

30

40

50

60

70

80

0 50000 100000 150000 200000

Metals Emissions 

(μg/dscm)

Pb

0

100

200

300

400

500

600

700

0 50000 100000 150000 200000 250000 300000 350000

Metals Emissions 

(μg/dscm)

Figure 7. Metals emissions and feed rate relationship -- Rotary kiln incinerator with IWS 

(Rollins, Baton Rouge, LA; ID No. 214)

21
Sb

0

5

10

15

20

25

30

35

0 50000 100000 150000 200000

Metals Emissions 

(μg/dscm)

As

0

0.2

0.4

0.6

0.8

1

1.2

0 10000 20000 30000 40000 50000 60000 70000

Metals Emissions 

(μg/dscm)

Ba

0

5

10

15

20

25

30

35

0 100000 200000 300000 400000 500000 600000 700000

Metals Emissions 

(μg/dscm)

Cr

0

5

10

15

20

25

0 10000 20000 30000 40000 50000 60000 70000 80000

Metal Feed Rate MTEC (μg/dscm)

Metals Emissions 

(μg/dscm)

Figure 8a. Metals emissions and feed rate relationship -- Liquid injection incinerator 

with WHB/FF/VQ/PT (Laidlaw, Roebuck, SC; ID No. 209).

22
Cd

0

0.5

1

1.5

2

2.5

3

0 20000 40000 60000 80000 100000 120000 140000

Metals Emissions (

μg/dscm)

Pb

0

2

4

6

8

10

12

14

16

18

0 20000 40000 60000 80000 100000 120000 140000 160000

Metals Emissions (

μg/dscm)

Tl

0

5

10

15

20

25

30

0 5000 10000 15000 20000 25000 30000 35000 40000

Metal Feed Rate MTEC (μg/dscm)

Metals Emissions (

μg/dscm)

Figure 8b. Metals emissions and feed rate relationship -- Liquid injection incinerator 

with WHB/FF/VQ/PT (Laidlaw, Roebuck, SC; ID No. 209).

 23
As

0

10

20

30

40

0 200 400 600 800 1000

Metals Emissions 

(μg/dscm)

Ba

0

200

400

600

800

1000

1200

0 50000 100000 150000 200000 250000 300000 350000 400000

Metals Emissions 

(μg/dscm)

Cd

0

200

400

600

800

1000

1200

1400

0 2000 4000 6000 8000 10000 12000

Metals Emissions 

(μg/dscm)

Cr

0

200

400

600

800

1000

0 5000 10000 15000 20000 25000 30000 35000 40000

Metals Emissions 

(μg/dscm)

Pb

0

2000

4000

6000

8000

10000

12000

14000

0 50000 100000 150000 200000 250000 300000

Metal Feed Rate MTEC (μg/dscm)

Metals Emissions 

(μg/dscm)

Figure 9. Metals emissions and feed rate relationships -- Rotary kiln incinerator with 

WS/ESP/PT (3M, Cottage Grove, MN; ID No. 334).

 24
Sb

0

200

400

600

800

0 200000 400000 600000 800000 1000000 1200000 1400000

Metals Emissions 

(μg/dscm)

As

0

20

40

60

80

0 10000 20000 30000 40000 50000

Metals Emissions 

(μg/dscm)

Cd

0

50

100

150

200

0 10000 20000 30000 40000 50000 60000

Metals Emissions 

(μg/dscm)

Cr

0

20

40

60

80

100

120

0 200000 400000 600000 800000 1000000

Metals Emissions 

(μg/dscm)

Pb

0

500

1000

1500

2000

0 100000 200000 300000 400000 500000 600000 700000

Metal Feed Rate MTEC (μg/dscm)

Metals Emissions 

(μg/dscm)

Figure 10. Metals emissions and feed rate relationships -- Liquid injection incinerator with 

VS/PBS (Tennessee Eastman, Kingsport, TN; ID No. 810).

 25
Cd

0

20

40

60

80

100

0 100 200 300 400 500 600 700

Metals 

Emissions 

(μg/dscm)

Pb

0

100

200

300

400

0 5000 10000 15000 20000 25000

Metals 

Emissions 

(μg/dscm)

Tl

0.0

0.5

1.0

1.5

2.0

0 200 400 600 800 1000 1200

Metals 

Emissions 

(μg/dscm)

Ba

0

50

100

150

200

0 5000 10000 15000 20000 25000 30000 35000 40000

Metals Emissions 

(μg/dscm)

Cr

0

50

100

150

200

0 1000 2000 3000 4000 5000 6000

Metals Emissions 

(μg/dscm)

Ni

0

50

100

150

200

0 1000 2000 3000 4000 5000 6000 7000 8000 9000

Metal Feed Rate MTEC (μg/dscm)

Metals 

Emissions 

(μg/dscm)

Figure 11. Metals emissions and feed rate relationship -- Rotary kiln incinerator with 

SD/FF/WS/IWS (Aptus, Coffeyville, KS; ID No. 325).

 26
Ba

0

5

10

15

20

0 10000 20000 30000 40000 50000 60000 70000 80000 90000

Metals Emissions 

(μg/dscm)

Cd

0

10

20

30

40

50

0 1000 2000 3000 4000 5000

Metals Emissions 

(μg/dscm)

Cr

0

5

10

15

20

25

30

0 10000 20000 30000 40000 50000 60000 70000 80000 90000

Metals Emissions 

(μg/dscm)

Pb

0

10

20

30

40

50

60

0 2000 4000 6000 8000 10000 12000 14000 16000 18000

Metal Feed Rate MTEC (μg/dscm)

Metals Emissions 

(μg/dscm)

Figure 12. Metal emissions and feed rate relationships -- Rotary kiln incinerator with 

SD/FF/WS/WESP (Aptus, Aragonite, UT; ID No. 327).

 27
0

200

400

600

800

1000

1200

1400

0 100000 200000 300000 400000 500000 600000

Metal Feed Rate MTEC (μg/dscm)

Metals Emissions (

μg/dscm)

Sb

Ba

Pb

Figure 13. Metal emissions and feed rate relationship -- Rotary kiln incinerator with HE/FF 

(Lake City Army Ammunition Plant, Independence, MO; ID No. 503)

 28
0

50

100

150

200

250

300

350

0 500 1000 1500 2000 2500 3000 3500 4000

Arsenic Stack Gas Emissions (μg/dscm @ 7% O

2)

Arsenic Feed Rate MTEC (μg/dscm @ 7% O2)

synthetic matrix

superfund soil

IRF Testing

Rotary kiln VS/PBS system

Combustion temp: 1500-1800°F

Figure 14. Metals emissions and feed rate relationships (EPA IRF, Arkansas,

rotary kiln incinerator with VS/PB).

29
Ni

0

2

4

6

8

10

0 1000 2000 3000 4000 5000 6000 7000 8000 9000

Metal Feed Rate MTEC (μg/dscm)

Metals 

Emissions 

(μg/dscm)

Facility 207 (condition 1)

Facility 208 (condition 1)

Cd

0

100

200

300

400

500

0 10000 20000 30000 40000 50000

Metals Emissions 

(μg/dscm)

Facility 207 (condition 1)

Facility 207 (condition 2)

Facility 208 (condition 1)

Facility 208 (condition 2)

Pb

0

50

100

150

200

250

300

350

0 10000 20000 30000 40000 50000 60000 70000

Metals Emissions 

(μg/dscm)

Facility 207 (condition 1)

Facility 207 (condition 2)

Facility 208 (condition 1)

Facility 208 (condition 2)

Cr

0

10

20

30

40

50

0 5000 10000 15000 20000 25000

Metals Emissions 

(μg/dscm)

Facility 207 (condition 1)

Facility 207 (condition 2)

Facility 208 (condition 1)

Facility 208 (condition 2)

Ag

0

0.5

1

1.5

2

0 1 2 345

Metals Emissions 

(μg/dscm)

Facility 207 (condition 1)

Facility 208 (condition 1)

Figure 15. Metals emissions and feed rate relationships -- Cement kilns (Keystone 

Cement, Bath, PA; ID No. 207/208).

30
Sb

0

20

40

60

80

100

0 10000 20000 30000 40000 50000 60000

Metals Emissions 

(μg/dscm)

Facility 205 (1992)

Facility 205 (1995)

Facility 206 (1992)

Facility 206 (1995)

Be

0

0.5

1

1.5

2

2.5

3

0 1000 2000 3000 4000 5000 6000

Metals Emissions 

(μg/dscm)

Facility 205 (1992)

Facility 205 (1995)

Facility 206 (1992)

Facility 206 (1995)

Cr

0

5

10

15

20

25

30

0 20000 40000 60000 80000 100000 120000 140000 160000 180000

Metals Emissions 

(μg/dscm)

Facility 205 (1992)

Facility 205 (1995)

Facility 206 (1992)

Facility 206 (1995)

Cd

0

50

100

150

200

0 2000 4000 6000 8000 10000 12000 14000 16000

Metals Emissions 

(μg/dscm)

Facility 205 (1992)

Facility 205 (1995)

Facility 206 (1992)

Facility 206 (1995)

Pb

0

200

400

600

800

1000

1200

1400

0 40000 80000 120000 160000

Metal Feed Rate MTEC (μg/dscm)

Metals Emissions 

(μg/dscm)

Facility 205 (1992)

Facility 205 (1995)

Facility 206 (1992)

Facility 206 (1995)

Figure 16. Metals emissions and feed rate relationship -- Cement kilns (Holnam, Holly Hill, 

SC; ID No. 205/206)

31
Cr

0

2

4

6

8

10

12

0 10000 20000 30000 40000 50000 60000 70000 80000 90000

Metal Emissions (

μg/dscm)

Cd

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

0 1000 2000 3000 4000 5000 6000 7000 8000

Metals Emissions (

μg/dscm)

Pb

0

1

2

3

4

5

6

0 20000 40000 60000 80000 100000 120000

Metal Feed Rate MTEC (μg/dscm)

Metals Emissions 

(μg/dscm)

Figure 17. Metals emissions and feed rate relationships -- Cement kiln with FF 

(Southdown, Knoxville, TN; ID No. 316).

32
As

0

10

20

30

40

50

0 10000 20000 30000 40000 50000 60000 70000 80000 90000

Metals Emissions 

(μg/dscm)

Facility 322

Facility 323

Be

0

0.2

0.4

0.6

0.8

1

1.2

0 1000 2000 3000 4000 5000 6000

Metals Emissions 

(μg/dscm)

Facility 322

Facility 323

Pb

0

200

400

600

800

1000

1200

1400

0 20000 40000 60000 80000 100000 120000 140000 160000 180000 200000

Metals Feed Rate MTEC (μg/dscm)

Metals Emissions 

(μg/dscm)

Facility 322

Facility 323

Cr

0

10

20

30

40

50

60

0 20000 40000 60000 80000 100000 120000 140000 160000 180000

Metals Emissions 

(μg/dscm)

Facility 322

Facility 323

Cd

0

20

40

60

80

100

0 2000 4000 6000 8000 10000 12000

Metals Emissions 

(μg/dscm)

Facility 322

Facility 323

Figure 18. Metals emissions and feed rate relationship for individual metals and facilities 

with multiple conditions -- Cement kilns (Lafarge, Fredonia, KS; ID No. 322/323).

 33
As

0.0

0.5

1.0

1.5

2.0

2.5

3.0

0 1000 2000 3000 4000 5000 6000 7000

Metals Emissions 

(μg/dscm)

Condition 1

Condition 3

Cr

0

5

10

15

20

25

30

35

40

0 5000 10000 15000 20000 25000 30000 35000

Metals Emissions 

(μg/dscm)

Condition 1

Condition 3

Cd

0

5

10

15

20

25

0 2000 4000 6000 8000 10000 12000

Metals Emissions 

(μg/dscm)

Condition 1

Condition 3

Pb

0

5

10

15

20

25

30

35

40

0 5000 10000 15000 20000 25000 30000

Metals Feed Rate MTEC (μg/dscm)

Metals Emissions 

(μg/dscm)

Condition 1

Condition 3

Figure 19. Metals emissions and feed rate relationship for individual metals and facilities 

with multiple conditions -- Cement kiln (Lone Star Industries, Inc., MO; ID No. 303).

 34
Cd

0

50

100

150

200

250

0 1000 2000 3000 4000 5000 6000 7000 8000 9000

 Metals Feed Rate MTEC (μg/dscm)

Metals Emissions (

μg/dscm)

Facility 401 (condition 1)

Facility 401 (condition 5)

Facility 402 (condition 1)

Facility 402 (condition 4)

Figure 20. Metals emissions and feed rate relationship for individual metals and facilities 

with multiple conditions -- Cement kilns (Ash Grove Cement Company, Chanute, KS; ID No. 

401/402)

 35
Cr

0

100

200

300

400

500

600

700

800

0 20000 40000 60000 80000 100000 120000 140000

Metals Emissions (

μg/dscm)

Ni

0

50

100

150

200

250

300

350

400

450

500

0 20000 40000 60000 80000 100000 120000

Metal Feed Rate MTEC (μg/dscm)

Metals Emissions (

μg/dscm)

Figure 21. Metals emissions and feed rate relationships -- Light weight aggregate kiln with 

FF/VS (Norlite, Cohoes, NY; ID No. 307)

 36
As: LWAK (Solite, FL; 227) 

0

2

4

6

8

10

12

0 20000 40000 60000 80000 100000 120000 140000

Metals Emissions 

(μg/dscm)

Pb: CK (National Cement Plant, Lebec, CA; 306) 

0

5

10

15

20

25

0 20000 40000 60000 80000 100000

Metals Emissions 

(μg/dscm)

Cr: Boiler (Merichem Company, TX; 724) 

0

5

10

15

20

25

0 100 200 300 400 500 600 700

Metals Emissions 

(μg/dscm)

Cr: Incinerator (Pennwalt Corp., NJ; 824)

0

10

20

30

40

50

60

70

80

90

0 500 1000 1500 2000 2500 3000 3500 4000 4500

Metals Feed Rate MTEC (μg/dscm)

Metals Emissions 

(μg/dscm)

Figure 22a. Selected metals emissions and feed rate relationships.

 37
Cd: LWAK (Solite, NC; 227)

0

2

4

6

8

10

12

0 50000 100000 150000 200000 250000

Metals Emissions 

(μg/dscm)

Cd: CK (National Cement Plant, Lebec, CA;306)

0

0.5

1

1.5

2

2.5

3

3.5

0 500 1000 1500 2000 2500 3000 3500 4000 4500

Metals Emissions 

(μg/dscm)

Hg: LWAK (Solite, NC; 224)

0

5

10

15

20

0 5 10 15 20 25 30 35

Metals Emissions 

(μg/dscm)

Hg: LWAK (Solite, KY; 310)

0

5

10

15

20

25

0 2 4 6 8 10 12 14 16

 Metals Feed Rate MTEC (μg/dscm)

Metals Emissions 

(μg/dscm)

Figure 22b. Selected metals emissions and feed rate relationships.

 38
Holnam Inc., MS (203)

0

2

4

6

8

10

12

14

16

18

20

0 10000 20000 30000 40000 50000

Metals Emissions

(μg/dscm)

As

Ba

Be

Cr

Heartland Cement Company, KS (202)

0

5

10

15

20

25

0 20000 40000 60000 80000 100000 120000 140000

Metals Emissions

(μg/dscm)

Sb

As

Ba

Be

Cr

Holnam Inc., SC (205/206)

0

10

20

30

40

50

60

70

80

90

100

0 20000 40000 60000 80000 100000 120000 140000 160000 180000

Metals Emissions 

(μg/dscm)

Sb

As

Ba

Cr

Ni

Southdown, OH (315)

0

2

4

6

8

10

12

14

0 50000 100000 150000 200000 250000

Metals Emissions

(μg/dscm)

As

Be

Cr

Metals Feed Rate MTEC (μg/dscm) 

Figure 23a. Metals emissions and feed rate relationship for low volatile metals 

groupings for individual facilities (cement kilns).

 39
Southdown, TN (316)

0

2

4

6

8

10

12

0 10000 20000 30000 40000 50000 60000 70000 80000 90000

Metals Emissions

(μg/dscm)

Be

Cr

Lafarge, KS (322/323)

0

10

20

30

40

50

60

0 20000 40000 60000 80000 100000 120000 140000 160000 180000

Metals Emissions

(μg/dscm)

As

Be

Cr

Ash Grove Cement Company, KS (401/402)

0

5

10

15

20

25

30

35

40

45

50

0 5000 10000 15000 20000 25000

Metals Emissions

(μg/dscm)

Sb

As

Ba

Be

Cr

Metals Feed Rate MTEC (μg/dscm)

Figure 23b. Metals emissions and feed rate relationships for low volatile metals 

groupings from individual facilities (cement kilns).

40
Occidental Chem. Corp., NY (348)

0

2

4

6

8

10

0 2000 4000 6000 8000 10000 12000 14000 16000

Metals Emissions 

(μg/dscm)

As

Cr

Ni

Laidlaw Environ., SC (209)

0

5

10

15

20

25

30

35

0 100000 200000 300000 400000 500000 600000 700000

Metals Emissions

(μg/dscm)

Sb

As

Ba

Be

Cr

Rollins Environ., LA (214)

0

10

20

30

40

50

60

70

80

0 100000 200000 300000 400000 500000 600000 700000

Metals Emissions 

(μg/dscm)

Ba

Cr

Tennessee Eastman Co., TN (716)

0

20

40

60

80

100

120

140

0 2000 4000 6000 8000 10000

 Metals Feed Rate MTEC (μg/dscm)

Metals Emissions 

(μg/dscm)

Ba

Be

Cr

Figure 24. Metals emissions and feed rate relationship for low volatile metals 

groupings for individual facilities (incinerators and boilers).

41
Cement Kilns -- Holnam Inc., MO (204)

0

10

20

30

40

50

60

70

80

0 20000 40000 60000 80000 100000 120000 140000 160000

Metals Emissions

(μg/dscm)

Sb

As

Ba

Be

Cr

Cement Kiln -- National Cement Plant, CA (306)

0

5

10

15

20

25

30

35

0 100000 200000 300000 400000 500000 600000

Metals Emissions

(μg/dscm)

Sb

As

Ba

Be

Cr

Incinerator -- Pennwalt Corporation, NJ (824)

0

10

20

30

40

50

60

70

80

90

0 2000 4000 6000 8000 10000 12000

Metals Feed Rate MTEC (μg/dscm)

Metals Emissions

(μg/dscm)

As

Ba

Cr

Ni

Figure 25. Metals emissions and feed rate relationship for low volatile metals groupings for 

individual facilities.

42
0.00001

0.0001

0.001

0.01

0.1

1

10 100 1000 10000 100000 1000000

Cr Feed Rate MTEC (μg/dscm)

Cr Penetration

Boilers

Cement Kilns

LWAKs

Incinerators

Other IFs

1

10

100

1000

10 100 1000 10000 100000 1000000

Cr Feed Rate MTEC (μg/dscm)

Cr Emissions (

μg/dscm)

Boilers

Cement Kilns

LWAKs

Incinerators

Other IFs

Figure 26. Chromium feed rate and emissions relationship for all hazardous waste burning 

combustors.

 43
0.00001

0.0001

0.001

0.01

0.1

1

10 100 1000 10000 100000 1000000

Pb Feed Rate MTEC (μg/dscm)

Pb Penetration

Boilers

Cement Kilns

LWAKs

Incinerators

Other IFs

1

10

100

1000

10000

100000

10 100 1000 10000 100000 1000000

Pb Feed Rate MTEC (μg/dscm)

Pb Emissions (

μg/dscm)

Boilers

Cement Kilns

LWAKs

Incinerators

Figure 27. Lead feed rate and emissions relationship for all hazardous waste burning 

combustors.

 44
Metal Stack Gas

Emissions Rate

Metal Feed Rate

Trial burn

condition

average

Desired

Extrapolated

Emission

Limit

Desired

Extrapolated

Emission

Limit

Extrapolated

Feed Rate

Limit

Extrapolated

Feed Rate

Limit

Universal variance factor

Trial Burn

Feed Rate

Figure 28. Options for the trial burn metals extrapolation procedure.

Trial Burn

Data

Points

Trial burn

highest run

Statistical evaluation

of trial burn data

4

5
Semi Volatile Metals Residuals

-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

-1 012345

Average (logXi)

Residual (logXi - Average)

Probability Plot for Semi Volatile Metals Residuals

0

0.5

1

1.5

2

2.5

0 20 40 60 80 100

Sample Percentile

Residual (Absolute Value)

Figure 29. Residual analysis for semi volatile metals.

 46
Highest trial burn run

(ERhr)

Trial burn average

Emissions rate with universal

variability factor (ERunvf)

Metal Feed Rate

Metal Stack Gas Emissions Rate

Trial burn feed rate

(FRtrbrn)

0.5 * FRtrbrn 2 * FRtrbrn

2 * ERunvf

Figure 30. Modified hybrid trial burn metals extrapolation procedure.

4

7
Detection limit

stack gas

measurement

Actual

value

Trial burn

feed rate

Downward

extrapolated feed

rates

Upward

extrapolated

feed rates

Desired stack

gas emissions

level

Desired stack

gas emissions

level

Metal Feed Rate

Metal Stack Gas Emission Rate

Figure 31. Illustration of the conservative impact of extrapolation off of stack gas detection limit trial burn measurement.

4

8
TABLE 1. METALS RESIDUAL ANALYSIS

Metal Group/Species Residual (log10)

(95th percentile)

Low Volatile Metals 0.53

Sb 0.38

As 0.43

Ba 0.55

Be 0.44

Cr 0.63

Ni 0.58

Ag 0.50

Semi Volatile Metals 0.49

Cd 0.56

Pb 0.48

Tl 0.27

High Volatile Metals 0.70

Hg 0.71

Se 0.62

All Metals Together 0.54

 49