# 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”.

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### 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.

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### CONTENTS

ABSTRACT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . i ACKNOWLEDGMENTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . i i FIGURES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . i v TABLE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vi ACRONYMS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vi i

1. 0 INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

2. 0 CURRENT BOILER AND INDUSTRIAL FURNACE RULE GUIDANCE . . . . . . .

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3. 0 RELATIONSHIP BETWEEN METALS FEED RATE AND EMISSION RATE

. . . . . 2 Theoretica l Considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Tria l Bur n Sourc e Testin g Evaluations . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Individua l Metal s Fro m th e Sam e Facility . . . . . . . . . . . . . . . . . . . . . 4 Group s o f Simila r Behavin g Metal s Fro m th e Sam e Facility . . . . . . . . . 7 Conclusion s o n Appropriatenes s o f Extrapolation . . . . . . . . . . . . . . . . . . . . . 7

4. 0 DEVELOPMEN T O F A N EXTRAPOLATIO N PROCEDURE . . . . . . . . . . . . . . . . . 9

5. 0 REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

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### 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

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### 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

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### TABLE

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

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### ACRONYMS

APCD Air pollution control device BI F Boilers and industrial furnaces dcfm dry standard cubic meter EP A Environmental Protection Agency ES P Electrostatic precipitator F F Fabric filter H E Heat exchanger H S Hydrosonic eductor scrubber IR F Incineration Research Facility IWS Ionizing wet scrubber MACT Maximum achievable control technology μ g microgram (10 -6 

### gram) ng nanogram (10 -9 

### gram) NODA Notice of data availability P B Packed bed PB S Packed bed scrubber S D Spray dryer SR E System removal efficiency PM Particulate matter PT Packed tower UV F Universal variability factor V

Q Venturi quench V S Venturi scrubber WESP Wet electrostatic precipitator WH B Waste heat boiler WS Wet scrubber

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### 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 I I : 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 II I : 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:

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### 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).

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### • 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 μ g/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 samplingtrain). 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

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### 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 μ g/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 μ g/dscm for Cr as compared with 500,000

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### μ g/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.

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### • 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,

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### 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, operatingparameters, 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.

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### • 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 basedon 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) R i 

### = C i 

### - C avg


### where C i 

### = log (X i 

### ) C avg 

### = average (C i 

### ) X i 

### : individual run metals stack gas emissions concentration (within a given condition) R i 

### : 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) FR proj = FR ct x ER limit ER unvf

where: FR proj 

### : Extrapolated/interpolated feed rate limit FR ct 

### : Compliance test feed rate (average) ER ct 

### : Compliance test average stack gas emissions rate ER limit 

### : New stack gas emissions limit

10

### and:

(3) ER unvf = 10 [ 

### C avg + 

### UVF ]



### C avg 

### = average (log X i 

### ) X i 

### : 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., ER unvf 

### 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 (FR ct 

### ) and emissions levels (ER hr 

### ), the universal variability factor (ER unvf 

### ), and the desired stack gas emissions level (ER limit 

### ):
Upward Extrapolation:
For projecting to desired emissions levels (ER limit 

### ) between the compliance test highest run (ER hr 

### ) and 2x’s the emissions limit based on the universal variability factor (ER unvf 

### ) (i.e., ER hr 

### < ER limit 

### , 2 x ER unvf 

### ):

(4) FR proj = FR ct 2 ER unvf − ER hr x ER limit − 2 ER hr + 2 ER unvf

where ER hr 

### : Emissions rate of highest individual run of the compliance test condition
For projecting to desired emissions levels (ER limit 

### ) greater than 2x’s the emissions limit based on the universal variability factor (ER unvf 

### ):
use Equation (2)
Downward Extrapolation:
For projecting to desired emissions levels (ER limit) 

### between the compliance test highest run (ER hr 

### ) and 0.5x’s the emissions limit based on the universal variability factor (ER unvf 

### ) (i.e., 0.5 x ER unvf 

### < ER limit 

### < ER hr 

### ):

(5) FR proj = FR ct 2 ER hr − ER unvf x ER limit − ER unvf + ER hr

For projecting to desired emissions levels (ER limit 

### ) less than 0.5x’s the emissions limit based on the universal variability factor (ER unvf 

### ):
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 RateMetal Emission Rate 

### T rial burn point
1

2 4

3 5

Maximum emission level Actual metals emissions curve



### Metal Feed RateMetal Emission Rate



### T rial burn point

1 2

4

3 5 

## Downward Extrapolation

Upward Extrapolation

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

15Metal Stack GasEmissions 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 metals16Metal 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 A17

## Pb y = 0.1943x - 303.37
R 2 = 0.8582

0 20000 40000 60000 80000 100000 120000

0 100000 200000 300000 400000 500000Metal 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
R 2 = 0.6071

0 200 400 600 800 1000

0 1000 2000 3000 4000 5000 6000 

### Metal Feed Rate MTEC ( μ g/dscm)Metal Emissions(μg/dscm) 

## Cd

y = 0.1817x + 34.138
R 2 = 0.9368 0 100 200 300 400 500 600

0 500 1000 1500 2000 2500 3000Metal Emissions(μg/dscm)



## Be y = 0.0734x + 2.5094
R 2 = 0.8957

0 20 40 60 80

0 100 200 300 400 500 600 700Metal Emissions(μg/dscm)



## As

y = 0.1626x + 3.6335
R 2 = 0.8989 0 100 200 300 400 500

0 500 1000 1500 2000 2500Metal Emissions(μg/dscm)



### 1 8

## As y = -9E-05x + 15.82
R 2 = 0.0028

0 10 20 30 40

0 5000 10000 15000 20000 25000 30000 35000 40000Metals Emissions(μg/dscm )



## Ba

y = 7E-05x + 24.015
R 2 = 0.2222
0 10 20 30 40

0 20000 40000 60000 80000 10000 0 12000 0 14000 0 16000 0 180000Metals Emissions(μg/dscm)



## Cd

y = 0.0018x + 23.783
R 2 = 0.067

0 20 40 60 80 100 120

0 5000 10000 15000 20000 25000Metals Emissions(μg/dscm) 

## Cr

y = -9E-06x + 22.212
R 2 = 0.0032 0 10 20 30 40

0 50000 100000 150000 200000 250000 300000 350000Metals Emissions(μg/dscm)



## Pb y = 0.0012x + 1.8288
R 2 = 0.5481

0 50 100 150 200 250 300 350

0 50000 100000 150000 200000 250000 

### Metal Feed Rate MTEC ( μ g/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).

1 9

## Sb

0 2000 4000 6000 8000

0 200000 400000 600000 800000 1000000Metals Emissions(μg/dscm)



## As

0 50 100 150 200 250 300

0 5000 10000 15000 20000 25000 30000 35000Metals Emissions(μg/dscm)



## Cd

0 500 1000 1500 2000

0 5000 10000 15000 20000Metals Emissions(μg/dscm) 

## Cr

0 100 200 300 400 500 600

0 50000 10000 0 15000 0 20000 0 25000 0 30000 0 35000 0 40000 0 450000Metals Emissions(μg/dscm)



## Pb

0 5000 10000 15000 20000 25000

0 50000 100000 150000 200000 250000 

### Metal Feed Rate MTEC ( μ g/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 700000Metals Emissions(μg/dscm)



## Cd

0 100 200 300 400 500 600 700

0 50000 100000 150000 200000 250000 300000 350000 

### Metal Feed Rate MTEC ( μ g/dscm)Metals Emissions(μg/dscm) 

## Cr

0 10 20 30 40 50 60 70 80

0 50000 100000 150000 200000Metals Emissions(μg/dscm)



## Pb

0 100 200 300 400 500 600 700

0 50000 100000 150000 200000 250000 300000 350000Metals 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 200000Metals Emissions(μg/dscm)



### As

0 0.2 0.4 0.6 0.8

1 1.2

0 10000 20000 30000 40000 50000 60000 70000Metals Emissions(μg/dscm)



### Ba

0 5 10 15 20 25 30 35

0 100000 200000 300000 400000 500000 600000 700000Metals Emissions(μg/dscm)



### Cr

0 5 10 15 20 25

0 10000 20000 30000 40000 50000 60000 70000 80000 

### Metal Feed Rate MTEC ( μ g/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 140000Metals Emissions (μg/dscm)



## Pb

0 2 4 6 8 10 12 14 16 18

0 20000 40000 60000 80000 100000 120000 140000 160000Metals Emissions (μg/dscm)



## Tl

0 5 10 15 20 25 30

0 5000 10000 15000 20000 25000 30000 35000 40000 

### Metal Feed Rate MTEC ( μ g/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).

2 3

## As

0 10 20 30 40

0 200 400 600 800 1000Metals Emissions(μg/dscm)



## Ba

0 200 400 600 800 1000 1200

0 50000 100000 150000 200000 250000 300000 350000 400000Metals Emissions(μg/dscm)



## Cd

0 200 400 600 800 1000 1200 1400

0 2000 4000 6000 8000 10000 12000Metals Emissions(μg/dscm) 

## Cr

0 200 400 600 800 1000

0 5000 10000 15000 20000 25000 30000 35000 40000Metals Emissions(μg/dscm)



## Pb

0 2000 4000 6000 8000 10000 12000 14000

0 50000 100000 150000 200000 250000 300000 

### Metal Feed Rate MTEC ( μ g/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).
2 4

## Sb

0 200 400 600 800

0 200000 400000 600000 800000 1000000 1200000 1400000Metals Emissions(μg/dscm)



## As

0 20 40 60 80

0 10000 20000 30000 40000 50000Metals Emissions(μg/dscm)



## Cd

0 50 100 150 200

0 10000 20000 30000 40000 50000 60000Metals Emissions(μg/dscm) 

## Cr

0 20 40 60 80 100 120

0 200000 400000 600000 800000 1000000Metals Emissions(μg/dscm)



## Pb

0 500 1000 1500 2000

0 100000 200000 300000 400000 500000 600000 700000 

### Metal Feed Rate MTEC ( μ g/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).

2 5

## Cd

0 20 40 60 80 100

0 100 200 300 400 500 600 700MetalsEmissions(μg/dscm)



## Pb

0 100 200 300 400

0 5000 10000 15000 20000 25000MetalsEmissions(μg/dscm)



## Tl

0.0 0.5 1.0 1.5 2.0

0 200 400 600 800 1000 1200MetalsEmissions(μg/dscm)



## Ba

0 50 100 150 200

0 5000 10000 15000 20000 25000 30000 35000 40000Metals Emissions(μg/dscm)



## Cr

0 50 100 150 200

0 1000 2000 3000 4000 5000 6000Metals Emissions(μg/dscm)



## Ni

0 50 100 150 200

0 1000 2000 3000 4000 5000 6000 7000 8000 9000 

### Metal Feed Rate MTEC ( μ g/dscm)MetalsEmissions(μg/dscm)



### Figure 11. Metals emissions and feed rate relationship -- Rotary kiln incinerator with SD/FF/WS/IWS (Aptus, Coffeyville, KS; ID No. 325). 2 6

## Ba

0 5 10 15 20

0 10000 20000 30000 40000 50000 60000 70000 80000 90000Metals Emissions(μg/dscm)



## Cd

0 10 20 30 40 50

0 1000 2000 3000 4000 5000Metals Emissions(μg/dscm) 

## Cr

0 5 10 15 20 25 30

0 10000 20000 30000 40000 50000 60000 70000 80000 90000Metals 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 ( μ g/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).

270 200 400 600 800 1000 1200 1400

0 100000 200000 300000 400000 500000 600000 

### Metal Feed Rate MTEC ( μ g/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)

2 8

### 0 50 100 150 200 250 300 350

0 500 1000 1500 2000 2500 3000 3500 4000Arsenic Stack Gas Emissions (μg/dscm @ 7% O2)



### Arsenic Feed Rate MTEC (μg/dscm @ 7% O 2 

### ) 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).

2 9

## Ni

0 2 4 6 8 10

0 1000 2000 3000 4000 5000 6000 7000 8000 9000 

### Metal Feed Rate MTEC ( μ g/dscm)MetalsEmissions(μg/dscm) Facility 207 (condition 1) Facility 208 (condition 1) 

## Cd

0 100 200 300 400 500

0 10000 20000 30000 40000 50000Metals 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 70000Metals 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 25000Metals 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 345Metals 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 60000Metals 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 6000Metals 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 180000Metals 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 16000Metals 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 ( μ g/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 90000Metal 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 8000Metals Emissions (μg/dscm)



## Pb

0 1 2 3 4 5 6

0 20000 40000 60000 80000 100000 120000 

### Metal Feed Rate MTEC ( μ g/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 90000Metals 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 6000Metals Emissions(μg/dscm) Facility 322 Facility 323



## Pb

0 200 400 600 800 1000 1200 1400

0 20000 40000 60000 8000 0 10000 0 12000 0 14000 0 16000 0 18000 0 200000 

### Metals Feed Rate MTEC ( μ g/dscm)Metals Emissions(μg/dscm) Facility 322 Facility 323 

## Cr

0 10 20 30 40 50 60

0 20000 40000 60000 80000 10000 0 12000 0 14000 0 16000 0 180000Metals Emissions(μg/dscm) Facility 322 Facility 323 

## Cd

0 20 40 60 80 100

0 2000 4000 6000 8000 10000 12000Metals 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).

3 3

## As

0.0 0.5 1.0 1.5 2.0 2.5 3.0

0 1000 2000 3000 4000 5000 6000 7000Metals Emissions(μg/dscm)

Condition 1 Condition 3



## Cr

0 5 10 15 20 25 30 35 40

0 5000 10000 15000 20000 25000 30000 35000Metals Emissions(μg/dscm) Condition 1 Condition 3



## Cd

0 5 10 15 20 25

0 2000 4000 6000 8000 10000 12000Metals 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 ( μ g/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).

3 4

## Cd

0 50 100 150 200 250

0 1000 2000 3000 4000 5000 6000 7000 8000 9000 Metals Feed Rate MTEC ( μ g/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)

3 5

## Cr

0 100 200 300 400 500 600 700 800

0 20000 40000 60000 80000 100000 120000 140000Metals 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 ( μ g/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)

3 6

## As: LWAK (Solite, FL; 227)

0 2 4 6 8 10 12

0 20000 40000 60000 80000 100000 120000 140000Metals Emissions(μg/dscm)



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

0 5 10 15 20 25

0 20000 40000 60000 80000 100000Metals Emissions(μg/dscm)



## Cr: Boiler (Merichem Company, TX; 724)

0 5 10 15 20 25

0 100 200 300 400 500 600 700Metals 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 ( μ g/dscm)Metals Emissions(μg/dscm)



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

3 7

## Cd: LWAK (Solite, NC; 227)

0 2 4 6 8 10 12

0 50000 100000 150000 200000 250000Metals 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 4500Metals Emissions(μg/dscm)



## Hg: LWAK (Solite, NC; 224)

0 5 10 15 20

0 5 10 15 20 25 30 35Metals 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 ( μ g/dscm)Metals Emissions(μg/dscm)



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

3 8

## Holnam Inc., MS (203)

0 2 4 6 8 10 12 14 16 18 20

0 10000 20000 30000 40000 50000Metals 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 140000Metals 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 10000 0 12000 0 14000 0 16000 0 180000Metals Emissions(μg/dscm) Sb As Ba Cr Ni



## Southdown, OH (315)

0 2 4 6 8 10 12 14

0 50000 100000 150000 200000 250000Metals Emissions(μg/dscm)

As Be Cr



### Metals Feed Rate MTEC ( μ g/dscm)
Figure 23a. Metals emissions and feed rate relationship for low volatile metals groupings for individual facilities (cement kilns).

3 9

## Southdown, TN (316)

0 2 4 6 8 10 12

0 10000 20000 30000 40000 50000 60000 70000 80000 90000Metals Emissions(μg/dscm)

Be Cr



## Lafarge, KS (322/323)

0 10 20 30 40 50 60

0 20000 40000 60000 80000 10000 0 12000 0 14000 0 16000 0 180000Metals 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 25000Metals Emissions(μg/dscm) Sb As Ba Be Cr



### Metals Feed Rate MTEC ( μ g/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 16000Metals 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 700000Metals 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 700000Metals 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 ( μ g/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).

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

0 10 20 30 40 50 60 70 80

0 20000 40000 60000 80000 100000 120000 140000 160000Metals 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 600000Metals 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 ( μ g/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 ( μ g/dscm)Cr Penetration

Boilers Cement Kilns LWAKs Incinerators Other IFs



### 1 10 100 1000

10 100 1000 10000 100000 1000000 

## Cr Feed Rate MTEC ( μ g/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.

4 3

### 0.00001 0.0001

0.001

0.01

0.1 1

10 100 1000 10000 100000 1000000 

## Pb Feed Rate MTEC ( μ g/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 ( μ g/dscm)Pb Emissions (μg/dscm) Boilers Cement Kilns LWAKs Incinerators



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

4 4Metal Stack GasEmissions 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 data45

## 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 2 0 4 0 6 0 8 0 10 0 

## Sample PercentileResidual (Absolute Value)



### Figure 29. Residual analysis for semi volatile metals.

4 6

### Highest trial burn run (ER hr 

### )

Trial burn average Emissions rate with universal variability factor (ER unvf 

### )



## Metal Feed RateMetal Stack Gas Emissions Rate



### Trial burn feed rate (FR trbrn 

### ) 0.5 * FR trbrn 

### 2 * FR trbrn 

### 2 * ER unvf



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

### 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 RateMetal Stack Gas Emission Rate



### Figure 31. Illustration of the conservative impact of extrapolation off of stack gas detection limit trial burn measurement.48

### TABLE 1. METALS RESIDUAL ANALYSIS

Metal Group/Species Residual (log10) (95th percentile)

Low Volatile Metals 0.53 S b 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 P b 0.48 Tl 0.27
High Volatile Metals 0.70 Hg 0.71 Se 0.62

All Metals Together 0.54

4 9