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UNITED STATES ENVIRONMENTAL PROTECTION AGENCY

RESEARCH TRIANGLE PARK, NC 27711

JUN 13 20t2

MEMORANDUM

SUBJECT: Particulate Matter Continuous Emission Monitoring System (PM CEMS) orr,".o,

Capabilities AIR OUALITY PLANNING

AND STANDARDS

FROM: ConniesueOldham,Groupleader (** 

OAQPS/AQAD ;- W

TO: Bob Schell, Group Leader

OAQPS/SPPD

The purpose of this memo is to review and summarize current knowledge regarding the capabilities of PM

CEMS technology related to Performance Specifrcation l1 (PS I l) of Appendix B to Part 60 and application to

new and revised New Source Performance Standards (NSPS) and Maximum Achievable Control Technology

(MACT) rules. This memo addresses the particular challenges in developing PS I I correlations when applied to

units using fabric filters as control devices, to units with highly variable fuel or raw feed materials, and in

exhaust streams subject to low PM emissions concentration limits.

Background - PS 11 and PM CEMS Technolosy

Performance Specification I I for PM CEMS is structured differently than other performance specifications

applied to evaluating the performance of a gaseous pollutant Continuous Emission Monitoring System (CEMS).

This is primarily because the pollutant, particulate matter, is defined entirely by the test method specified by

regulation to measure it. There are no independent standard reference materials for particulate matter

concentrations as there are for gaseous pollutants (e.g., National Institute of Standards and Technology (NIST)

traceable compressed gases for SOz or NO.). The only reference standard for determining the PM concentration

in an air or stack gas sample is the test method. In the case of the Portland cement and Commercial/Industrial

Solid Waste Incinerators (CISWI) rules and many other regulations under 40 CFR Parts 60, 61 and 63, that

reference method is EPA Method 5 for measuring filterable particulate matter concentration or mass rate (e.9., in

mg/dscm or lb/hr).

The structure of PS I I is further dictated by the types of CEMS technologies used as PM CEMS. Two basic

types are currently sold commercially and are generally installed by industry: light scattering devices and beta

gauges.

The output or response of light scattering detectors is a function of the index of refraction and size distribution of

the particles in the exhaust stream. In addition to being more sensitive than opacity monitors, light scattering PM

CEMS provide more degrees of design freedom. PM CEMS manufacturers account for characteristics such as

light wavelength, scattering angle, and solid angle of detection in designing instruments with desired response

features.

There are potential drawbacks to using light scattering devices for measuring PM concentrations in industrial

stacks. Light scattering techniques effectively respond to particle shape, size and color rather than particle mass

meaning that using light scattering to infer PM mass concentrations introduces an additional dependence on

particle density. To the extent that stack particles emitted from a process change in density or have multiple and

variable constituents, the ability of a light scattering device to provide consistent responses may be limited. Light

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scattering instruments also will respond to liquid droplets in the sample gas stream meaning that in-situ light

scattering devices type are inappropriate for saturated or nearly saturãted exhaust streamr. iigltt scatterin! devices

that extract and heat the sample gas prior to exposure to the detector may be used on saturateã or nearly sãturated

exhaust streams.

The response correlations for light scattering devices are also vulnerable to changes in the particle size

distribution in the sample stream. Using light scattering instruments on sample ,irearns thai are likely to have

varying particle size distributions can be problematic. There are precautionr one can take to minimize the effects

of changing particle sizes (e.g., by using multiple conelation curïes). One can expect significant variations in particle size distribution particularly from combustion sources burning multiple fùels (eg., mixed biofuel and

fossil fuel boilers, cement kilns that burn waste) or a mixture of feed materiaìs and chemical additives. One

possible result is that the correlations for light scattering PM CEMS can be rendered unreliable when particle

characteristics change even though PM concentrations ãnd mass rates remain constant. The effects offhanging pafticle size distributions and other physical characteristics on the responses from light scattering devices aie difficult to quantify and are discussed further in the EPA's technology background cíocuments (e-.g., Itttp:¡¡www.eoa'eov andftWl/wwwTpa.gov/ttn/emc/cemñ4703-02-

otu{Ð.

Other PM CEMS technologies are based more directly on mass measurement than are the light scattering pM

lltvtS tecnnologies. One of these technologies relies on beta-attenuation and is often refegãd to as beta'gauge

lM CEMS. A beta gauge PM CEMS extracts a sample from the stack gas and collects the pM on a filteräpe.

The device periodically advances the tape from the iampling mode to an area where the sample is exposed îo beta

radiation. After exposure, the detector measures the differenie between a baseline beta count and the beta count of

the sample. This difference is directly proportionalto the mass of the pM sample.

Beta gauge PM CEMS have a weak dependence on particle composition and a strong correlation to particle mass.

The main issues associated with the use of a beta gauge PM CEMS or other extractive type pM CEMS are

practical ones. Maintainjng isokinetic sampling may be necessary to assure representative measurements. Because

the sample is extracted from the stack, there may be some samplà loss in the extractive probe. Also, the beta

gauge PM CEMS detection limit capabilities are dependent on the PM mass collected on the filter. That means

that one can improve (decrease) the beta gauge CEMS detection limits with longer sampling times but there may

be other physical or regulatory limitations to the degree of adjustment possible.

Sjnce beta gauge type instruments are much less sensitive to changes in particle size and other physical

characteristics of PM than are light scattering instruments, beta gaug" pVt CEN4S may be *o.. uppropriate for

exhaust streams that are likely to have varying particle size distrìbutions (e.g., following an electióstaiic

precipitator, sources that combust multiple fuels or apply variable raw feed ir'aterials). Ãny pM CEMS that

extracts and heats the sample gas, including beta gauge PM CEMS, may be more appropriate for exhaust streams

that are saturated or nearly saturated with water.

Another PM mass detector projected for greater use in PM CEMS in the near future is the tapered element

oscillating microbalance (TEOM). Often used in measuring ambient levels of PM, the TEOù operates on a basic

principle that can be made traceable to NIST standards. The TEOM can provide acontinuou, rèuru.e of pM

mass in a sample extracted from the stack and routed to the detector. At ihis time, a TEoM-based pM GEMS is

not yet commercially available.

PS I I provides procedures and acceptance criteria for evaluating the performance of any type of pM CEMS

technology. There are multiple instrument and data reporting operational performance ctreti<s in pS I I that are

similar in concept to those for gaseous pollutant CEMS. There is one prinbipal PM CEMS performance
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requirement that is distinctly different than in CEMS performance specifications for gaseous pollutants. PS I I

requires development of a site-specific PM CEMS conelation or mathematical response curve. There are two key

procedural elements to developing that correlation according to PS I l. First, PS I I requires that the source

conduct multiple PM emission test runs using an EPA PM reference test method (e.g., Method 5) and

simultaneously collect PM CEMS output data.

The second key procedural requirement specific to developing PS 1l correlations is that the source must vary the

operation of the control device or process manually in order to produce a range of PM concentrations. PS I I

requires at least fîve test runs at each ofthree different operating conditions (i.e., PM concentrations) that are to

range from 25 to I 00 percent of the allowable emissions for a total of I 5 or more test runs. Then the source must

use the test method data and the coresponding PM CEMS ouþut data to develop an equation (i.e., a calculated

linear or nonlinear curve) that will be used to define the relationship between the PM CEMS output and the test

method measured PM concentrations. Each site-specific correlation must meet several PS I I acceptance criteria

including limits on the calculated confrdence interval and tolerance interval.

Perturbing the PM control device operations to produce a range of PM concentrations is more challenging for

some control devices than for others. One can adjust the secondary power to an ESP to produce relatively

controllable changes to outlet PM concentrations. Likewise, one can adjust gas flow rate or water flow rate to a

venturi scrubber to produce changes to outlet PM concentrations. Producing a range ofPM concentrations at the

outlet of a fabric filter control devices is more challenging. For example, there are typically no physical

adjustments one can apply to a fabric filter or to an associated combustion process to change the outlet PM

concentration in the range needed for conelation development. A well operating fabric filter produces essentially

a constant outlet concentration even with changes to the inlet loading or flow (see

http://www.epa.gov/ttnchiel/mkb/documents/ff-pulse.pdÐ. Testers have applied some techniques (e.g., bypass

ducts, loosening seals around bags) for perturbing fabric filter control devices, but these can produce

unpredictable emissions levels, stratified stack PM concentrations, and altered physicalcharacteristics of the

particles.

PS 1l allows some flexibility when control device perturbations are not possible. In such cases, the resulting

correlation would apply for only the naffow range of concentrations measured during the testing, presumably at a

concentration below the applicable compliance limit. Without the ability to calculate emissions should the fabric

filter performance change (e.g., bag leaks begin to develop), a comelation based on essentially a single emissions

level would be rendered unreliable for calculating emissions concentrations or emissions rates when emissions are

significantly different (e.g., more than 125 percent of the highest PM CEMS response) from those used for the

correlation curve.

Another challenge to meeting PS I I correlation requirements would be very low PM concentrations with a

corresponding low applicable emissions limit. In addition to the measurement uncertainty, sample

representativeness, and the effects of changing particle characteristics that apply to the PM CEMS data, the data

quality capabilities of the reference test method is a significant factor in successful development of a PM CEMS

Correlation. The Method 5 method detection limit, or MDL, is about 2 mg/dscm for a l-hour test run. The

uncertainty of a measurement at this PM concentration would be from 50 to 100 percent (i.e., +1 to 2 mg/dscm).

The Method 5 practical quantitation limit (PQL), using -3 x MDL, would then be approximately 6 mg/dscm with

a measurement unceftainty from l0 to 20 percent or +0.6 to 1.2 mg/dscm. This means that for a PM CEMS

measuring compliance with an emission limit equivalent to l0 mg/dscm, the inherent uncertainty associated with

the Methõd 5 measurement alone would be about half of PS I I correlation acceptance threshold of *25 percent

of the applicable limit.

One can improve the method detection capabilities of the Method 5 or other filterable PM test methods by

increasing sampling volume and run time. For example, the PQL for a2 hour test run would be 3 mg/dscm with a

measur.,ient uncertainty from +0.3 to 0,6 mg/dscm. A test run time of 4 hours would improve the Method 5
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PQL to about 1.5 mg/dscm and a measurement uncertainty of+O.15 to 0.3 mg/dscm. To achieve a PQL of I

mg/dscm (as would be necessary to demonstrate compliance with a2 to 3 mg/dscm emissions limit), one would

need to conduct a Method 5 test run of 6 hours or longer. The measurement uncertainty associated with a 6-hour

Method 5 test run at this concentration would be +0.1 to 0.2 mg/dscm.

Using data from longer Method 5 test runs will improve the probability of a PM CEMS meeting PS 1l

corelation requirements but will also raise practicality concerns. The time to complete l5 l-hour test runs under

three different emissions conditions would nominally involve three to six days of field work. The time to

complete l5 6-hour test runs under three different emissions conditions would require at least two weeks of field

work and very likely longer in order to produce and maintain the operating conditions associated with three

different emissions rates. For processes that utilize multiple fuels, produce widely varying particle characteristics

or experience widely varying load conditions, the effect could be even longer comelation test program durations.

For some operations, certain process conditions are available only a few hours per week and to complete l5 6-

hour test runs could take longer than two weeks.

For the low PM emissions level range particularly, the stack concentration level would have to remain steady

during each test run to capture the relevant corelation values. It is worth repeating that meeting PS I I corelation

requirements becomes increasingly problematic with decreasing numerical emissions limits given that

confidence and tolerance intervals âre expressed as a percent of the emissions limit.

The quality of the Method 5 data (i.e., precision and accuracy) factors into achieving the PS I I acceptance

criteria regardless of the type of PM CEMS technology used. One may improve the quality of the Method 5 data

with co-located dual sampling trains, often called paired trains. With paired trains, one discards any pairs of data

showing poor precision, thus, increasing the likelihood of high quality reference method data. PS I I recommends

but does not require paired sampling trains. Conducting tests with paired trains will increase the cost of PS I I

correlation development. Typical costs to perform l5 6-hour (non-paired) test runs are at least $25,000 plus

approximately $900 dollars for each additional test run not including the time required to perturb and fix the

control device operations. Correlation test costs could increase dramatically if a source has intermittent process

operations or uses multiple fuels necessitating development of multiple correlations.

Review of Existing PM CEMS Correlation Data

We reviewed a series of PM CEMS correlation tests available to us. Of the eighteen PS I I comelation tests we

have on hand, the majority were conducted using light scattering PM CEMS. Only three were for beta gauge PM

CEMS. Fourteen of the PM CEMS operated on combustion units that burned only coal, three were installed on

units that burned a combination of fuels, such as natural gas, sludge and bark, while only one PM CEMS was

installed on a unit that would be considered a biomass unit.

Only one of the sources had a PM emissions limit of l0 mg/dscm or below. The test report for this unit indicated

that the PM CEMS correlations met the PS I I requirements. Six of the units were subject to emissions limits

between I I mg/dscm and20 mg/dscm. Five of the PM CEMS installed on these units produced correlations that

met PS I I criteria. Fourteen of the units tested were subject emissions limits of 2l mg/dscm or greater. Thirteen

of the PM CEMS on these units produced an acceptable comelation.

PS I I provides for developing several different correlation relationships (e.9., linear, nonlinear, logarithmic).

Fourteen of the eighteen PM CEMS in our database met PS I I requirements using a linear correlation

relationship. Another two could not pass using a linear comelation relationship but passed using another

relationship and the final trvo did not pass using any possible relationship. For the correlations for which we have

raw data, it appears that most used 60 minute test runs.
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In some instances, the actual emissions during the test were well below 50 percent of the source's emissions

limit. As noted above, only one of the reports we have is for a source with an emissions limit less than l0

mgldscm. To simulate how the PM CEMS in other cases would perform relative to PS I I requirements for low

emissions limits, we recalculated the correlations using data from tests of a few units with low emissions results

substituting a lower emissions limit in the conelation calculation. For two of these correlation test projects, the

testers collected larger sample volumes to improve measurement data quality. ln at least one case, the PM CEMS

would have failed the PS I I corelation requirements calculated using the lower (e.g., < l0 mg/dscm) emissions

limit.

Conclusions

In summary, there are different analytical technologies used for PM CEMS and each has capabilities variably

suited to different stack conditions and process applications. It is imperative that facilities weigh the pros and

cons of the available technologies when choosing a PM CEMS for their specific application.

We also conclude that acceptable corelations for PM CEMS installed on units with very low emission limits,

which burn multiple fuels or which have varying load conditions, are possible but require special care. One factor

already mentioned is the technology selected. A second consideration is the cost of the testing that may increase

dramatically if it is necessary to conduct longer test runs. Additionally, this type of testing requires avery

experienced test crew to ensure that samples are collected and handled properly to minimize the error so critical

at these lower emissions levels. Furthermore, as we have described above, developing a PS I I correlation for a

unit that employs a fabric filter control device may result in a correlation that can be used only for a limited range

of emissions.

References

"Current Knowledge of Particulate Matter (PM) Continuous Emission Monitoring." EPA-454/R-00-039. U.S.

Environmental Protection Agency, Research Triangle Park, NC. September 2000.

Air Pollution Control Technology Fact Sheet: Fabric Filter - Pulsed-Jet Cleaned Type" EPA-452/F-03-025. U.S.

Environmental Protection Agency, Research Triangle Park, NC.

40 CFR 60, Appendix B, "Performance Specification I I - Specifications and Test procedures for Particulate

Matter Continuous Emission Monitoring Systems at Stationary Sources."

"PS I I Data Summary." Spreadsheet. Environmental Protection Agency, Research Triangle Park, NC. June 5,

1012.

OAQPS/AQAD/MTG/KGarnett, ext. I158, E'43-02/PM CEMS Capabilities Memo - 6-13-20l2ldca