Greenhouse Gas (GHG)
Verification Guideline
Series
Parametric Emissions Monitoring
System (PEMS)
Version 1.1
Greenhouse Gas Technology Center
Southern Research Institute
September 2001
Under a Cooperative Agreement With
U.S. Environmental Protection Agency
-------
EPA REVIEW NOTICE
This report has been peer and administratively reviewed by the U.S. Environmental Protection Agency, and approved for
publication. Mention of trade names or commercial products does not constitute endorsement or recommendation for use.
-------
Greenhouse Gas Technology Center
A U.S. EPA Sponsored Environmental Technology Verification ( ^I'l/ ) Organization
Greenhouse Gas Verification Guideline Series
Parametric Emissions Monitoring System
(PEMS)
Prepared by:
Greenhouse Gas Technology Center
Southern Research Institute
PO Box 13825
Research Triangle Park, NC 27709 USA
Telephone: 919/806-3456
Under EPA Cooperative Agreement CR 826311-01-0
U.S. Environmental Protection Agency
Office of Research and Development
National Risk Management Research Laboratory
Air Pollution Prevention and Control Division
Research Triangle Park, NC 27711 USA
EPA Project Officer: David A. Kirchgessner
September 2001
Version 1.1
-------
FOREWARD
The U.S. Environmental Protection Agency (EPA) has created the Environmental Technology Verification
(ETV) program to facilitate the deployment of promising environmental technologies. Under this program,
third-party performance testing of environmental technology is conducted by independent verification
organizations under strict EPA quality assurance guidelines. Southern Research Institute (SRI) is one of six
independent verification organizations operating under the ETV program, and SRI operates the Greenhouse Gas
Technology Center (GHG Center). With full participation from technology providers, purchasers, and other
stakeholders, the GHG Center develops testing protocols and conducts technology performance evaluation in
field and laboratory settings. The testing protocols are developed and peer-reviewed with input from a broad
group of industry, research, government, and other stakeholders. After their development, the protocols are
field-tested, often improved, and then made available to interested users via guideline series reports such as this
one. Typically, verifications conducted by the center involve substantial measurements, so an effort is made
here to recommend only the most important measurements for the guideline.
Guidelines for verifying an alternative method of monitoring exhaust emissions in gas-fired 1C engines are
presented here. This guideline was based upon a verification test conducted by the GHG Center on a parametric
emissions monitoring system (PEMS) developed by ANR Pipeline Company (ANR) of Detroit, Michigan. The
ANR PEMS approach to monitoring exhaust emissions is based on relationships established between engine
operating parameters, as reported by existing engine sensors, and exhaust emissions. The PEMS approach to
monitoring can be applied to other source categories and industry sectors, but the guidelines presented here were
developed specifically for PEMS installations on gas-fired 1C engines.
In the natural gas industry, interstate gas pipeline operators use gas-fired engines to provide the mechanical
energy needed to drive pipeline gas compressors. The patented PEMS approach to emissions monitoring
provides an alternative to instrumental continuous emissions monitoring systems (CEMS), and is potentially
more cost effective. 1C engine PEMS can be designed to predict emissions of carbon dioxide (CO2), carbon
monoxide (CO), total hydrocarbons (THCs), oxygen (O2), and nitrogen oxides (NOX). The parametric approach
to determining air emissions is provided for in 40 CFR Part 64.
The purpose of this guideline is to describe specific procedures for evaluation and verification of 1C engine
PEMS. It is not the intention of the GHG Center that these guidelines become accepted as a national or
international standard. Rather, a significant effort has been devoted to their development, field trial, and
improvement; and this experience and data are recognized as potentially valuable to others. Instrument
descriptions and recommendations presented in this document do not constitute an endorsement by the GHG
Center or the EPA. Readers should be aware that use of this guideline is voluntary, and that the GHG Center is
not responsible for liabilities that result from its use.
Finally, the GHG Center continues to conduct verifications, and will update this guideline with new findings as
warranted. Updates can be obtained on-line at the GHG Center's Web site (www.sri-rtp.com) or at the EPA
ETV Web site (www. epa. gov/etv).
-------
ACKNOWLEDGEMENTS
The Greenhouse Gas Technology Center wishes to thank all participants in the field verifications used to prepare
this guideline. The GHG Center wishes to thank the staff and employees of Coastal Corporation and its member
company, ANR Pipeline Company, for their invaluable service in hosting the test used in the development of
this guideline. They provided the compressor station to test this technology, and gave technical support during
the setup and field testing of the PEMS technology. Key ANR personnel who should be recognized for
contributing to the success of the testing include Curtis Pedersen, Joseph Weisbrod, Michael Scudder, Ron
Bickel, Mike Haller, Jeff Beach, and George Jirkos.
-------
TABLE OF CONTENTS
FORWARD ii
ACKNOWLEDGMENTS iii
ACRONYMS/ABBREVIATIONS v
FOREWARD
1.0 BACKGROUND AND INTRODUCTION [[[ 1-1
1.1. ETV PROGRAM DESCRIPTION [[[ 1-1
1.2. VERIFICATION SCOPE [[[ 1-2
2.0 PEMS TECHNOLOGY DESCRIPTION [[[ 2-1
2.1. PRINCIPLES OF PEMS TECHNOLOGY [[[ 2-1
2.2. PEMS DESCRIPTION [[[ 2-1
3.0 VERIFICATION GUIDELINE [[[ 3-1
3.1. INTRODUCTION [[[ 3-1
3.2. RELATIVE ACCURACY DETERMINATIONS [[[ 3-1
3.3. OPERATIONAL PERFORMANCE EVALUATIONS [[[ 3-5
3.3.1. PEMS Prediction Capabilities During Abnormal Engine Operation ............................ 3-5
3.3.2. PEMS Response to Sensor Failure [[[ 3-8
4.0 FIELD TESTING AND CALCULATION PROCEDURES [[[ 4-1
4.1. OVERVIEW [[[ 4-1
4.1.1. Determination of Relative Accuracy [[[ 4-1
4.2. SAMPLE HANDLING AND TESTING METHODS [[[ 4-3
4.2.1. Sample Conditioning and Handling [[[ 4-3
4.2.2. Calibrations [[[ 4-5
4.2.3. Reference Method 3 A - Determination of Oxygen & Carbon Dioxide
-------
ACRONYMS/ABBREVIATIONS
ANR
ATDC
BHp
BTDC
CEMS
cfh
CFR
CH4
CO
CO2
DQO
DP
EPA
ETV
ft3
Ft-lbs
g
GHG Center
H2O
Hp
hr
inches Hg
KV
Lb
MMBtu
Msec
NOX
02
PEMS
ppm
ppmvd
PSIG
QA
RA
RATA
RPM
SCF
SRI
THCs
WC
°F
ANR Pipeline Company
after top dead center
brake horsepower
before top dead center
continuous emissions monitoring system
cubic feet per hour
Code of Federal Regulations
methane
carbon monoxide
carbon dioxide
data quality objective
differential pressure
United States Environmental Protection Agency
Environmental Technology Verification
cubic feet
foot-pounds
gram
Greenhouse Gas Technology Center
water
horsepower
hour
inches mercury
kilovolt
pounds
million British thermal units
milli second
nitrogen oxides
oxygen
parametric (also Predictive) emissions monitoring system
parts per million
parts per million volume dry
pounds per square inch gauge
quality assurance
relative accuracy
relative accuracy test audit
revolutions per minute
standard cubic feet
Southern Research Institute
total hydrocarbons
water column
degrees Fahrenheit
-------
-------
1.0 BACKGROUND AND INTRODUCTION
1.1. ETV PROGRAM DESCRIPTION
The U.S. Environmental Protection Agency's Office of Research and Development (EPA-ORD) operates a
program to facilitate the deployment of innovative technologies through performance verification and
information dissemination. The goal of the Environmental Technology Verification (ETV) program is to further
environmental protection by substantially accelerating the acceptance and use of improved and innovative
environmental technologies. ETV is funded by Congress in response to the belief that there are many viable
environmental technologies that are not being used for the lack of credible third-party performance data. With
performance data developed under ETV, technology buyers, financiers, and permitters in the United States and
abroad will be better equipped to make informed decisions regarding environmental technology purchase and
use.
The Greenhouse Gas Technology Center (GHG Center) is one of six verification organizations operating under
ETV. The GHG Center is managed by the EPA's partner verification organization, Southern Research Institute
(SRI), which conducts verification testing of promising GHG mitigation and monitoring technologies. The
GHG Center's verification process consists of developing verification protocols, conducting field tests,
collecting and interpreting field and other test data, obtaining independent peer review input, and reporting
findings. Performance evaluations are conducted according to externally reviewed verification Test and Quality
Assurance Plans and established protocols for quality assurance.
The GHG Center is guided by volunteer groups of stakeholders. These stakeholders offer advice on specific
technologies most appropriate for testing, help disseminate results, and review Test Plans and verification
reports. The GHG Center's stakeholder groups consist of national and international experts in the areas of
climate science and environmental policy, technology, and regulation. Members include industry trade
organizations, technology purchasers, environmental technology finance groups, governmental organizations,
and other interested groups. In certain cases, industry specific stakeholder groups and technical panels are
assembled for technology areas where specific expertise is needed. The GHG Center's Oil and Gas Industry
Stakeholder Group offers advice on technologies that have the potential to improve operation and efficiency of
natural gas transmission activities. They also assist in selecting verification factors and provide guidance to
ensure that the performance evaluation is based on recognized and reliable field measurement and data analysis
procedures.
In a June 1998 meeting in Houston, Texas, the Oil and Gas Industry Stakeholder Group voiced support for the
GHG Center's mission, identified a need for independent third-party verification, prioritized specific
technologies for testing, and identified verification test parameters that are of most interest to technology
purchasers. At this meeting, ANR Pipeline Company, of Detroit, Michigan, requested the GHG Center conduct
a verification test on a parametric (or sometimes referred to as predictive) emissions monitoring system (PEMS)
they had developed. Verification of the PEMS was conducted in August 1999. Details on the verification test
design, measurement test procedures, and Quality Assurance/Quality Control (QA/QC) procedures for the
PEMS verification can be found in the test plan titled Testing and Quality Assurance Plan for the ANR Pipeline
Company Parametric Emissions Monitoring System (PEMS) (SRI 1999). It can be downloaded from the GHG
Center's Web site (www.sri-rtp.com) or the EPA's ETV Web site (www.epa.gov/etv). Results of the ANR
verification can be found in the test report titled Environmental Technology Verification Report for the ANR
Pipeline Company Parametric Emissions Monitoring System (PEMS) (SRI 2000) which is available at the same
Web sites. The verification guidelines presented in this document were developed in support of that
performance verification test.
1-1
-------
The purpose of this guideline is to describe specific procedures for evaluation and verification of 1C engine
PEMS. It is not the intention of the GHG Center that these guidelines become accepted as a national or
international standard. Although the guidance has been field tested, it may not be applicable to all gas-fired
internal combustion engines and installations. This guideline should also be considered dynamic, because the
GHG Center continues to conduct technology verifications, and this document may be updated regularly to
include new findings and procedures as warranted. Updates of this document can be obtained on-line at the
GHG Center's Web site or EPA's ETV Web site as referenced above
Following the planning, execution, and post-test analysis phases of each field verification, the GHG Center
identifies field or other procedures that performed poorly or were marginally necessary, and then revises the
protocol. All procedural changes instituted from this effort are included here.
1.2. VERIFICATION SCOPE
Natural gas transmission companies often use large gas-fired 1C engines to drive gas compressors that transport
gas through the transmission network in the United States. There are several approaches to monitoring the
exhaust emissions from these gas-fired engines, one of which is the PEMS. The PEMS approach to monitoring
exhaust emissions is based upon establishing relationships between engine operating parameters, as determined
by commonly used sensors, and exhaust emissions.
PEMS provides a potentially more cost-effective alternative to instrumental continuous emissions monitoring
systems (CEMS). 1C engine PEMS can be designed to predict emissions of nitrogen oxides (NOX), carbon
monoxide (CO), total hydrocarbons (THCs), oxygen (O2), and carbon dioxide (CO2). The parametric approach
to determining air emissions is provided for in 40CFR64.
This guide recommends an approach to evaluate the functionality and accuracy of a PEMS on a gas-fired 1C
engine. Basically, the PEMS is evaluated by comparing its emission predictions to emissions data collected
simultaneously using instrumental procedures. There are two classes of verification parameters recommended:
(1) emission monitoring relative accuracy determinations, and (2) PEMS operational performance
determinations. The relative accuracy determinations provide a statistical comparison between PEMS emission
prediction values and emissions measurements obtained using EPA Reference Methods during normal engine
operations. PEMS operational performance evaluations include determination of the PEMS ability to respond to
adverse engine operating conditions and sensor drift or failure. The following specific verification parameters
should be considered during the PEMS evaluation and are described individually in the following sections:
PEMS relative accuracy for emissions of each pollutant predicted
PEMS prediction capabilities during abnormal engine operation
PEMS ability to respond to sensor failure
The remainder of this guideline provides descriptions and explanations of PEMS functions and a proposed
verification methodology. The document is organized as follows:
Section 2 provides an overview of PEMS principals and describes a typical 1C engine
PEMS design, set-up, and operation;
Section 3 discusses verification parameters and approach;
Section 4 describes testing and analytical procedures to be used;
Section 5 describes data validation process and quality assurance goals;
-------
Section 6, the Bibliography, provides references relevant to this Guideline, including
references to detailed, step-by-step procedures for the recommended Reference Methods.
Certain limitations of this guideline must be stated. First, the verification test described in this guideline is not
intended to characterize PEMS accuracy when the monitored engine is operating abnormally. Also, these
verification guidelines may not be applicable to all types of engines operating under a wide range of conditions.
The verification that was used to develop these guidelines was conducted on a 6,000 hp Ingersoll-Rand engine
fired with pipeline quality natural gas.
1-1
-------
-------
2.0 PEMS TECHNOLOGY DESCRIPTION
2.1. PRINCIPLES OF PEMS TECHNOLOGY
The PEMS approach to monitoring exhaust emissions is based upon establishing relationships between engine
operating parameters, as determined by commonly used engine sensors, and exhaust emissions. As such, PEMS
are fundamentally computerized algorithms that describe the relationships between operating parameters and
emission rates, and which estimate emissions without the use of continuous emission monitoring systems.
Advantages that the PEMS approach to monitoring provides over CEMS applications include eliminating costs
associated with monitoring instrumentation and the cost of maintaining the sampling and analysis systems, and
procurement of analyzer calibration gases. Some sensors may be needed for installation of a PEMS, but many
engines are already equipped with the sensors needed. Disadvantages associated with the PEMS are that they
are currently not widely accepted in many industries, and setup and engine mapping (i.e., determination of
engine emissions using conventional methods over a wide range of engine operating regimes) costs may be
high.
2.2. PEMS DESCRIPTION
Each engine produces unique relationships between emissions and engine operational functions, so initial
parameterization of a PEMS must be engine specific. Engine and emission relationships established for a site
can be a function of engine speed and engine load (as torque), but other operational parameters that may be used
include: engine efficiency (calculated fuel consumption/actual fuel consumption), ignition timing, combustion
air manifold temperature, and combustion air manifold pressure. Relative humidity may not be applicable to
reciprocating engines, and therefore may be an operational parameter not considered in some PEMS.
Figure 2-1 illustrates several important PEMS prediction features for gas-fired 1C engines. The figure indicates
that engine speed and torque may be primary determinants of emissions, and that with values for speed and
torque, the baseline emissions for an engine can be defined. Baseline emissions are representative of a normally
functioning and well-tuned engine, but as engine operational changes occur, indicators of engine efficiency,
ignition timing, air manifold temperature, and air manifold pressure may be used to adjust emission values.
Within a given type of PEMS, monitored and estimated values for these five key parameters may be used to
increase or decrease predicted emission from the baseline level as shown in Figure 2-1. Table 2-1 describes
typical engine sensors from which values for these operational parameters might be derived.
Figure 2-2 illustrates general PEMS operational steps and outputs. The PEMS evaluated by the GHG Center
contained several different functions including the prediction of continuous emissions, the reporting of total
emissions and high emission alarms/alerts, the monitoring of engine sensor performance, and the reporting of
potential sensor malfunctions. Other PEMS may offer different features.
?-/
-------
Figure 2-1. PEMS Operations Features
Alarm Level
Alarm Level
Emissions Adjusted or
Biased Based on Key
Engine Operational Parameters
Engine Speed and Torque
Table 2-1. Example Engine Parameters/Sensors Used by the PEMS
Verified by the GHG Center
Sensor
Ignition timing
feedback
Fuel DP (flow)
Fuel temperature
Air manifold
pressure
Air manifold
temperature
Model
Altronic
#DI-1401P
Rosemount #1151DP-4-S-12-
MI-B1 transducer
Rosemount
#444RL1U11A2NA RTD
Electronic Creations #EB-
010-50-1-0-40/N transducer
Rosemount 0068-F-11-C-30-
A-025-T34 RTD
Specified
Accuracy
+ 1 % of full
scale
+ 1 %
+ 0.25 %
+ 0.25 %
+ 0.25 %
Calibration
Check
Annual
Annual
Annual
Annual
Annual
Operating
Range
45° BTDC
to 45° ATDC
0-100" we
0-125 °F
0-25 PSIG
0-150°F
-------
Figure 2-2. Example PEMS Diagram
Sensor Outputs
for all Monitored
Engine Parameters
No
Outputs from Redundant
Sensors for all Monitored
Engine Parameters
Is the Output for
all Monitored
Parameters Reliable?
PEMS Reports a
Potentially Faulty
Sensor Alarm
Engine Speed and
Torque Settings
PEMS Calculates
Values for all
Monitored Parameters
Comparison of
Calculated and
Monitored Values
PEMS Reporting:
Emissions Values
Emissions Alerts
Out of Limit Alarms
PEMS Determines
Baseline
Emissions
PEMS Adjusts
Baseline Emissions
A PEMS may also use redundant engine monitoring sensors. Redundant sensors can be used for those engine
parameters that the PEMS vendor or engine operator expect to influence emissions the most or are expected to
fail most frequently (including fuel flow, combustion air temperature, and combustion air pressure).
Incorporating sensor redundancy on PEMS applications can facilitate assessments of sensor drift and the
identification of failed or malfunctioning sensors.
Alarms and alerts may be set to give the engine operator knowledge when one or more key operating parameters
is out of specification. These alarms/alerts are set by the PEMS vendor and station operator specific to each
engine. Key parameters that have alarm/alert functions might include efficiency (high and low), ignition timing
deviation from set point, air fuel deviation from set point, and exhaust gas temperature absolute value (high and
low). On the ANR PEMS tested, redundant sensors were used on three key engine monitoring parameters
including air manifold temperature, air manifold pressure, and fuel DP.
-------
-------
3.0 VERIFICATION GUIDELINE
3.1. INTRODUCTION
This section recommends an approach for evaluating the functionality of a PEMS and verifying the accuracy of
its emissions predictions. Specific testing strategies and matrices are presented, and calculations and
instrumental testing methods are identified. Section 4 details the instrumental methods used to verify PEMS
predictions.
The PEMS should be tested over a full range of normal and off-normal engine operating conditions. There are
two classes of verification parameters: emission prediction relative accuracy, and PEMS operational
performance. In the relative accuracy determinations, PEMS emission prediction values are compared to
emissions measurements obtained using EPA Reference Methods for emission rate determinations. PEMS
operational performance evaluations include determination of the PEMS ability to respond to adverse engine
operating conditions and sensor drift or failure. PEMS predictions during these activities are also compared to
Reference Method values. The following specific verification parameters are described individually in the
following sections and should be determined during the PEMS evaluation:
PEMS relative accuracy for emissions of each pollutant predicted
PEMS prediction capabilities during abnormal engine operation
PEMS ability to respond to sensor failure
The parameters listed above should be assessed through observation, collection and analysis of emissions data
generated by the PEMS, comparative instrumental gas measurements collected on-site, use of engine data logs,
and evaluation of data used to characterize engine operations. PEMS emission prediction performance
capabilities should be assessed under normal engine operating conditions, and then challenged by simulating
episodes of substandard engine performance and evaluating PEMS emission predictions during these episodes.
3.2. RELATIVE ACCURACY DETERMINATIONS
Because the PEMS approach to air emissions monitoring is a new technology it is in limited use. As such,
formalized performance demonstration procedures specific to PEMS have not yet been promulgated by EPA
(although EPA has developed a draft performance specification for PEMS, and several states have specific
performance evaluation procedures in place for PEMS). CEMS have been developed to the level that they are a
primary means for monitoring gaseous emissions from industrial processes for regulatory compliance purposes.
This recognition has led to EPA's development of Performance Specification Test procedures to confirm the
precision and accuracy of CEMS by conducting a relative accuracy test audit (RATA). A RATA is a series of
tests during which CEMS outputs are compared to data collected using an independent sampling system and
following EPA's Reference Methods for emission rate determinations.
The EPA Performance Specification Tests can also be used to evaluate PEMS performance. Therefore, the
Performance Specification Tests are the primary bases used in this PEMS verification guideline. After a RATA
is conducted, a statistical comparison is developed on the PEMS emission predictions and the corresponding
Reference Method data collected during the testing. This statistical comparison is defined in Section 4.1.1 and
determines the relative accuracy (RA) of the PEMS for each pollutant.
The Performance Specifications generally require a relative accuracy of 20 percent of the mean reference
method value for a CEMS to be considered functional and able to report accurate emissions for compliance
purposes. A relative accuracy of 20 percent of the mean reference method value is also used to evaluate PEMS.
1-1
-------
EPA's Performance Specification Tests require the use of EPA Reference Test Methods to collect measured
emissions data for comparison with PEMS values. The list below identifies the individual Performance
Specification Tests to be used, and their accompanying Reference Test Method.
Performance Specification Test 2 for NOX Reference Method 7E
Performance Specification Test 3 for CO2 & C>2 Reference Method 3A
Performance Specification Test 4 for CO Reference Method 10
Performance Specification Test 8 for THCs Reference Method 25A
Documentation of these Reference Methods is available in the Code of Federal Regulations, (40CFR60,
Appendices A and B). In general PEMS emission predictions should be compared with the EPA Reference
Method values obtained by an independent gas sampling system. The Reference Method values are obtained
using extractive sampling systems that analyze pollutant concentrations in the exhaust gas using instrumentation
housed in a mobile laboratory. These comparisons should be made after the predicted PEMS and measured
Reference Method values are placed on a common basis (e.g., common moisture and temperature), and after
each have been carefully time-matched. To facilitate time-matching, synchronization of the PEMS and EPA
Reference Method data acquisition clocks should be done daily, and sampling system lags associated with the
Reference Method Sampling Train response time should be measured and integrated into the time-matching.
The Reference Method values are also corrected for sampling system bias and instrument drift before being
compared to PEMS predictions. More detail regarding the methods is provided in Section 4.
The first step in conducting a RATA is to determine the engine operating conditions at which the testing should
occur. Collection of the emissions and other data needed to perform a RATA should occur while the engine
operates under normal speed and torque conditions, and when it is in a well-tuned state. Engine operators at the
site should determine when these conditions are met, and thus, when relative accuracy testing can begin. For the
ANR PEMS verification, engine speed and torque were the primary determinants used by PEMS to predict
engine emissions, and therefore the RATA was conducted while operating the engine at a minimum of four
speed and torque regimes within the normal operating range of the engine. For other PEMS or engine types,
other engine parameters may be the primary factors for PEMS function. The primary engine parameters for a
specific PEMS must be identified prior to designing a verification strategy and evaluating the system.
For example, the test engine used in the ANR PEMS verification test normally operated at torque and speed
values that ranged between 75 to 100 percent of the maximum values for each parameter. Although the
engine/compressor was capable of operating with loads and speeds as low as 50 percent, operation at loads
and/or speeds of less than 70 percent occurred only during start-up or severe process interruption. This engine
operated at loads/speeds of 85 to 100 percent approximately 90 percent of its operating time. The other 10
percent of the time it operated at 70 to 85 percent of rated maximum load and speed.
Using historical operational data for the engine to be tested, a series of normal operating conditions should be
specified for the RATA. The normal operating conditions established for the ANR verification test are shown in
the matrix presented in Table 3-1. The individual speed/load values in the matrix were considered to be the
nominal values that should be attempted in the field. As a practical matter, varying demand on the engine under
test and other conditions can cause slight variations in these normal test conditions to occur.
-------
Table 3-1. Example Relative Accuracy Test Matrix
Nominal Engine Speed (%)
50-75
75-90
90 - 100
Nominal Engine Load (%)
50-75
Not normal
Not normal
Not normal
75-90
Not normal
3 runs
3 runs
90 - 100
Not normal
3 runs
3 runs
Once the engine operating conditions at which the testing will be conducted are identified, the RATA can be
initiated. A minimum of 12 individual test runs should be conducted to constitute a complete RATA. In this
example, a series of 3 runs were conducted at each of four operating conditions. The Performance
Specifications for CEMS allow for 3 test results to be discarded, and relative accuracy to be determined on the
best 9 results obtained. This practice is not recommended for PEMS because the verification is not intended for
compliance or enforcement purposes. More than 12 runs can be conducted and used to determine relative
accuracy, but repetitions (single test runs) should be evenly distributed over the number of engine operating
conditions selected (e.g., if 5 operating regimes are tested, 3 replicates should be conducted at each for a total of
15 individual runs). Each run should be 21 to 30 minutes in duration after stable emissions readings have been
observed using the Reference Method monitors. A more rigorous RATA can be conducted by conducting 12
individual test runs at each of the engine operating points. The draft EPA performance specification requires
this level of testing for PEMS that will be used for compliance monitoring.
At the completion of the series of test runs, emission data from the Reference Methods and the PEMS should be
compiled for each pollutant predicted by the PEMS. Results should be presented in the reporting units
predicted by the PEMS; typically on a concentration basis (ppm or percent), and on an emission factor basis
(usually gram/brake horsepower-hour (g/Bhp-hr)). This should result in two sets of results with at least 12
replicates each. The relative accuracy for each PEMS pollutant should be determined for each set of reporting
units. The procedures and instrumentation associated with the execution of specific Reference Methods, other
sampling tasks, and relative accuracy calculations are described in Section 4. Data should be summarized in
tabular form similar to the example provided in Table 3-2.
Table 3-2. Example Relative Accuracy Test Results
Parameter
NOX
CO2
CO
THCs
Emission Rates as g/BHp-hr
Mean Diff.
0.60
10.9
-0.07
-0.06
Std. Dev.
0.14
7.41
0.05
0.02
RA (%)
11.1
3.90
6.78
3.42
Concentrations as ppmvd (% for CO2)
Mean Diff.
71.4
-0.36
-12.9
-22.0
Std. Dev.
26.9
0.08
9.61
9.20
RA (%)
11.2
8.18
6.38
3.36
It can also be useful to summarize the RATA results graphically as in the example provided in Figures 3-la and
Figure 3-lb. The figures present results as a function of percent difference between PEMS and Reference
-------
Method values, and as absolute values. The figures also show the engine operating conditions during the runs as
percent speed and torque using the right vertical axes.
Figure 3-la. Example RATA Results as Percent Difference (g/BHp-hr)
RATA Results- NQx (grams/BHp-hr)
40
30
9n
10
0
-10
-20
-30
-50
1
1 1
1
1
r~ii ii~~ir~i
i i i
i=
i
-
| |
13 %Diff
Toque
RPM
-
90
80
70
60
50
40
30
20
0
19 20 21 22 23 24 25 26 27
Run Number
29 30
Figure 3-lb. Example RATA Results as Absolute Values (g/BHp-hr)
RATA Results- NQx (grams/BHp-hr)
14
12
10
.n
Q_
m 8
6
4
2
--- _ ____ ,_
~
-
-
"
, -
1
-
-
.
Tonque (%)
RPM (%)
' ' RM
1 ' PEMS
0
-
m
-
~
~
~
100
90
80
70
60
50
40
30
20
10
0
19 20 21 22 23 24 25 26 27
Run Number
28 29 30
-------
Figure 3-2 presents an example graphic representation of each Reference Method and corresponding PEMS
prediction data point collected during the RATA conducted on the ANR PEMS. This plot allows a reader to
evaluate the PEMS ability to track large and small emission rate changes and trends in the emissions over all of
the engine operating conditions tested. The different engine speed settings observed during the tests are also
plotted.
Figure 3-2. Predicted and Measured NOX Concentrations During RATA Testing
iuuu
1400
-i onn -
Q. -innn .
in
c
onn
in ouu
in
E
LJJ
finn .
0
/inn
onn .
n -
V^A.r/-
Reference Method
i Data 1
VnJ/^JL
/
PEMS Predictions
j"U/\ . A/
wW
fcw
PEM,
Ref f
^ Engir
-WJ/
v-r
3
Method
ie Speed
t»sv^fr\i*\ ..
N^PA^^,,
ouu
340
. ^on
. ^nn
. ofin
o/in
. oon
. onn
Q.
V)
-------
The first step needed to evaluate the effects of abnormal conditions is to select the engine parameters that are
most likely to have an effect on true emissions, and determine the methods for forcing these changes to occur.
Typically, engine operating features affecting emissions are pollutant specific. From a general perspective, the
most significant parameters include (in approximate order): (la) air manifold pressure, (Ib) exhaust manifold
pressure, (2) ignition timing, (3) engine efficiency, (4) air manifold temperature, (5) exhaust manifold
temperature, and (6) relative humidity. The operating parameters that should be used for perturbation include
those parameters that can be physically perturbed on the engine. This excludes ambient humidity, where
perturbations can not be easily simulated, and exhaust gas pressure and temperature, which generally can not be
altered in a predictable manner. The parameters that were varied in ANR PEMS verification are summarized
below along with the physical methods used to vary them, and the measurements used for each condition. Note
that other procedures may be better suited for the test conditions of a given PEMS verification. Consultation
with the operators and vendors involved is recommended to determine the best way to perturb the engine in a
representative and safe manner.
Combustion air manifold temperature and pressure - Air manifold temperatures can be
varied by manually changing the temperature setting, causing the engine to increase or
decrease air flow through the heat exchanger. Both high and low temperatures that are
close to the upper and lower air temperature alarm levels should be established prior to
testing. Manifold pressure changes should be accomplished by increasing and decreasing
combustion air flow.
Engine efficiency - Engine efficiency is generally determined as calculated fuel
consumption/actual measured fuel consumption. Where an engine computer is available,
overriding it and manually changing the engine horsepower value should vary this operating
parameter. This should cause the engine to change fuel flow without a true need for a fuel
change (e.g., when actual demand on the engine is changed). On carbureted engines,
manual adjustments can be made. With the engine consuming non-optimal fuel, efficiency
should be changed. By increasing and decreasing the horsepower setting (or the gas
supplied by the carburetor), efficiency can be raised to an optimum level, and then reduced
to a point where the engine efficiency or some other related engine alarm occurs.
Ignition timing - Ignition timing can be manually adjusted. As above, values just short of
upper and lower alarm values should be established.
After the engine parameters and methods of perturbing operations are identified, tests should be conducted by
changing each of the engine operating parameters both above and below normal operation. After reaching each
of the desired abnormal conditions, emissions should be allowed to stabilize by observing real-time Reference
Method data, and then test runs of approximately 15 to 30 minutes should be conducted. Depending on the
engine torque and speed, emission changes occurring as a result of changes in operating parameters may vary in
significance. Thus, the evaluations should be conducted at two or three different torque and speed conditions.
Evaluation of off-normal operations should focus on specific speed and torque operating ranges that occur most
often for the engine. As an example, the matrix summarizing the tests used for the ANR verification is
presented as Table 3-3.
Table 3-3. Example Off-Normal Engine Operating Conditions to be Tested
-------
Operational Parameter/Alarm Condition
Efficiency
Ignition Timing
Air Manifold Temperature
Air Manifold Pressure
High
Low
High
Low
High
Low
High
Low
Nominal Engine Speed/Torque (% capacity)
100/100
X
X
X
X
X
X
X
X
75/100
X
X
X
X
X
X
X
X
100/75
X
X
X
X
X
X
X
X
X indicates one test run of 15 to 30 minutes.
The adequacy of the PEMS response to off-normal conditions should be evaluated by comparing the emission
rates obtained from the Reference Method with the emission rates predicted by the PEMS during each of the
tests. The absolute difference and percent difference between these two values should be summarized and
reported. Figure 3-3 is an example of data collected during off-normal engine operation tests. Interpretation of
results of these tests can expose conditions where PEMS predictions of one or more pollutants can become
inaccurate as operating conditions change. These tests can also be used to determine if PEMS predictions are
conservative, or higher than actual, for certain pollutants when abnormal operations are evident. During the
ANR PEMS verification, NOX emission predictions were most affected by abnormal engine operation, primarily
due to changes to engine efficiency.
Figure 3-3. Example Off-Normal Engine Operating Test Results
20
I -15
E 10
Torque
RPM (%)
RM
PEMS
Off Normal Operation Results - NOx
o o
35 36 43 44 49 50 39 40 47 48 55 56 33 34 41 42 53 54 37 38 45 46 51 52
Run Number
1-7
-------
3.3.2. PEMS Response to Sensor Failure
Engine sensor signals are the primary basis of PEMS functions. Therefore a series of tests should be conducted
to demonstrate the performance of PEMS when engine sensor drift or failure occurs, and to document PEMS
ability to identify potentially failed engine sensors. As a first step in doing this evaluation, the vendor-designed,
failure-mode operational procedures should be determined (for example, use of redundant sensors). The failure
mode operation should be reviewed first for its thoroughness (are enough contingencies provided for) and for
applicability (are the procedures appropriate for the application).
As an example of this, the ANR PEMS that was tested was designed to provide conservative NOX emission
predictions when sensor drift or failure occurred. When failure occurred, and redundant sensors were used to
monitor the engine parameter, the ANR PEMS defaulted to the sensor input that resulted in the highest predicted
NOX emission. If the predicted emissions were higher than a pre-set maximum emission level, usually the
maximum permitted emissions for the operating engine, the PEMS alarmed. When sensor failure occurred, the
operators used the PEMS alarm to diagnose and resolve failed sensors. For engine parameters that do not have
redundant sensors (e.g., energy efficiency and ignition timing), erroneous readings from failed sensors can also
result in high emissions indications and alarms at some point within the failure period.
To evaluate PEMS performance during sensor failure, the PEMS emission predictions should be compared to
Reference Method data while simulating engine sensor outputs that correspond to a failed or drifting sensor.
The process should start by collecting and reviewing sensor calibration data for the test engine prior to testing to
document sensor accuracy. Then the sensor inputs to be tested should be identified along with a method of
electronically inhibiting sensor signals. These typically include ignition timing, exhaust manifold pressure,
engine efficiency (fuel flow related sensors), air manifold temperature, and air manifold pressure. Other PEMS
applications may use additional engine monitoring sensors in determining emission bias factors and in these
cases, those sensors should also be perturbed and the PEMS tested. During the ANR test, control software
included the ability to put sensor signals in a control inhibit mode that allowed the operator to simulate sensor
failure.
Testing should be conducted by establishing steady state engine operation at torque and speed levels that are
within 75 to 100 percent of engine capacity. Steady-state Reference Method and PEMS emission rates should
be reached to establish comparability prior to sensor perturbations. Next, sensor perturbation should be
simulated by manually adjusting sensor output signals for each PEMS sensor. Sensors should be perturbed one
at a time, and each should be changed by slowly adjusting the sensor output signal until the transmitter alarm
level is reached. Up to three levels of sensor drift should be simulated whenever possible by periodically
incrementing perturbations to the sensor. In some cases, engine alarms or upsets can be reached quickly and test
runs should be aborted to avoid stalling or damaging the engine. Test durations should be 15 to 30 minutes, or
as needed to achieve stable PEMS concentrations at multiple sensor settings (up to 3 sensor settings when
possible). Throughout each perturbation period, the data below should be recorded.
PEMS concentrations and emission rates for all pollutants,
Reference Method concentrations and emission rates for all pollutants,
Perturbed sensor signal values,
All other sensor values, and
Alarm/alert conditions reported by the PEMS and engine computer.
The data should be used to verify how PEMS predictions change as sensors drift toward the alarm level, and, if
appropriate information is available for operators to identify if a sensor has failed. The simultaneous reference
method data should allow a direct comparison of actual emissions with PEMS predictions, and should
demonstrate how the two values diverge as sensor failure approaches. The entire procedure should be repeated
-------
for low- and high-level alarm regimes, and with all of the sensors that are used by a specific PEMS to predict
emissions.
The difference and percent difference between these two values should be summarized and reported. Figures 3-
4a and b provide examples of data presentation. During the ANR PEMS verification, perturbations to certain
sensor signals did have a significant affect on the accuracy of PEMS predictions, especially cases where
redundant sensors are in use. As shown in these figures, perturbations to the air manifold pressure and
temperature sensors had a large impact on NOX emission predictions.
1-Q
-------
Figure 3-4a. Example Single Sensor Perturbation Test Results as Percent Difference
Single Sensor Perturbation - NOx
50 "
40 "
o 30'
O
E 20 "
^
Q^
(f) 10 "
E
^ ° .
E
£ -10 .
0)
1 -20 "
it
2 -30 .
0)
e -40
0)
D_
-50 "
-60 '
^^ ^^ \
1. .
1 1 , ,1 1
r nnn
n n
llflllllL nn
Q. Q. Q Q
§§§§§§§§JJJJ
llllllllllll
| |
Q. Q.
1 1
1 1
[
1 1 1 1
-70
1234
«,
1
1
|
5
-
s
£
1
S
£
1
^
1
nf
n
n DDnJ 1
y>
£
1
«,
1
1
Q Q Q Q Q Q
"OS "ai "ai "ai "ai 1
*^.
n
II
Q Q
15 15
1 ' % Difference
^^^^ Sensor Readina
i
678
' 110
' 100
' 90
c
g
' 80 ^
c
8
70 ra
c1 *£
60 '-a g_
S O
'50 | |
£ o
'40 ro 2
o
E
30 g
oj
D_
20
' 10
0
Run Number
Figure 3-4b. Example Single Sensor Perturbation Test Results as Absolute Values
Single Sensor Perturbation - NOx
12 "
11
10 "
90 o o o
:= := := :=
8,8,8,8,
1-1
^ '
s7: ii
36" I
w
c
i 5"
w
E
m 4
3
2 _ ^^
1 I
II I II I II
0
~--\___ " \ ' ---
= = = = EEEEEE SSS ii
Q Q Q Q Q Q
IIIIllllll 111 11 | | | | | |
1 n
-I
r
Sensor Reading (%)
3 RM
] PEMS
-i
"I r
n
i
i
r
r
-, - '
" 110
" 100
" 90
Q Q c
1 1 " 80 i
T C
O
n 70 o
D)
p §
60~2
ro Q.
1 " 50 ? ro
S §
40 co J
'o
"c
30 g
OJ
Q_
20
10
0
12345678
Run Number
-------
4.0
FIELD TESTING AND CALCULATION PROCEDURES
4.1. OVERVIEW
The procedures described in this section provide a framework for testing a PEMS during both normal and off-
normal engine operation. They are based on EPA Performance Specification Test guidelines for CEMS (40
CFR 60, Appendix B), EPA Reference Methods for determination of emission rates (40 CFR 60, Appendix A),
and the document "Example Specifications and Test Procedures for Predictive Emission Monitoring Systems"
provided by EPA's Emission Measurement Center (Emission Measurement Center, 1999).
4.1.1. Determination of Relative Accuracy
For each of the gases for which concentrations and/or emission rates are predicted by a PEMS, the parameter
that should be used to represent the result of the PEMS/Reference Method comparison is Relative Accuracy.
Relative Accuracy should be calculated in accordance with the four-step process outlined below.
First, calculate the arithmetic mean of the difference, d, for all runs conducted as in Equation 1 below:
1 n
~d~ X d i
n i = l (Eqn. 1)
Where:
n = number of runs
d; = difference between Reference Method and PEMS output for a run
Second, calculate the standard deviation associated with all runs, Sd, as shown in Equation 2 below:
S d
7
<
I
n
n - i
(Eqn. 2)
Third, calculate the 2.5 percent error confidence coefficient (one-tailed), cc, as shown in Equation 3 below:
S
cc - t
0 .975
(Eqn. 3)
Where:
to 975 = t-value (see Table 4-1).
4- 1
-------
Table 4-1. t- Values
n*
2
3
4
5
6
tfl.975
12.706
4.303
3.182
2.776
2.571
n*
7
8
9
10
11
tfl.975
2.447
2.365
2.306
2.262
2.228
n*
12
13
14
15
16
Tfl.975
2.201
2.179
2.160
2.145
2.131
* The values in this table are already corrected for n-1 degrees of freedom. Use n equal to the number of
individual runs.
Fourth, calculate the Relative Accuracy, RA, for all runs as shown in Equation 4
below:
Where:
RA = d
+
cc
100
~RM~
d\ = Absolute value of the mean differences (from Eqn. 1)
cc\ = Absolute value of the confidence coefficient (from Eqn. 1)
RM= Average Reference Method value
(Eqn. 4)
The test procedures suggested for utilization in this guideline are Federal Reference Methods. Reference
Methods are well documented in the Code of Federal Regulations, include detailed procedures, and generally
address the elements listed below (40CFR60, Appendices A and B).
Applicability and principle
Range and sensitivity
Definitions
Measurement system performance specifications
Apparatus and reagents
Measurement system performance test procedures
Emission test procedure
Quality control procedures
Emission calculations
Bibliography
-------
Each of the selected testing methods utilizing an instrument measurement technique includes performance-based
specifications for the gas analyzer used. These performance specifications cover span, calibration error,
sampling system bias, zero drift, response time, interference response, and calibration drift requirements. An
overview of each test method suggested for use is presented in this section, with emphasis on the type of
monitors to be used, the monitor range, the sampling system configuration, and general calibration plans. The
entire method reference will not be repeated here, but should be available to site personnel during testing, and
can be viewed in Appendix A of 40CFR60 (www.epa.gov/cfr40.htm). Field log forms that can be used to
conduct calibrations and other field activities are presented in Appendix A. Sample Reference Method output
formats and summaries are also presented in Appendix A.
4.2. SAMPLE HANDLING AND TESTING METHODS
4.2.1. Sample Conditioning and Handling
A schematic of the sampling system used for the ANR test is presented as Figure 4-1. In order for some of the
instruments used to operate properly and reliably, the flue gas must be conditioned prior to introduction into the
analyzer if conditions are outside acceptable instrument parameters. The gas conditioning system shown in this
figure is designed to remove water vapor and/or particulate from the sample. All interior surfaces of the gas
conditioning system are made of stainless steel, Teflon, or glass to avoid or minimize any reactions with the
sample gas components. Gas is extracted from the gas stream through a heated stainless steel probe, filter, and
sample line and transported to two ice bath condensers on each side of the sample pump. The condensers
remove moisture from the gas stream. The clean, dry sample is then transported to a flow distribution manifold
where sample flow to each analyzer is controlled. Calibration gases can be routed through this manifold to the
sample probe by way of a Teflon line. This allows calibration and bias checks to include all components of
the sampling system. The distribution manifold also routes calibration gases directly to the analyzer when
linearity checks are made on each of the analyzers (other than the THC analyzer).
-------
Figure 4-1. Gas Sampling and Analysis System
Sample line and
calibration gases
B^S^B^E^S*
The time required for sample gas to travel from the probe tip to the analyzers and obtain a stable response (i.e.,
the system response time) must be determined to ensure that time-matched comparisons of PEMS and Reference
Method outputs are made. The sampling system response time should be measured at the beginning of field
testing. The procedure should include the following stepwise process for each analyzer used:
1. Initiate a flow of zero concentration calibration gas at the probe and wait for stable readings to occur,
2. Introduce a high concentration calibration gas at the probe while simultaneously recording the start time,
3. Record the time at which the gas concentrations due to the step increase are at 95 percent of their
expected level, and
4. Repeat the procedure going from high range gas to zero gas, record that time, and record the system
response time for that pollutant as the longer of the two.
The final system response time is the longest response time recorded for an individual test parameter over the
whole range of analyzers in use.
In addition to the system response time test, a flue gas stratification test should be conducted prior to the start of
testing to determine the most representative location to position the reference method sampling probe. The
4-4
-------
procedures specified in Reference Method 20 for determination of NOX emissions from gas turbines should be
followed. Since most engine exhaust ducts are less than 16 square feet in diameter, 8 traverse points are
sufficient to check for stratification. Using a calibrated sampling system, measure the O2 or CO2 concentration
in the exhaust gas stream at each of the 8 traverse points selected. If the concentrations are consistent at each of
the 8 points, position the probe tip near the GHG Center of the duct for sampling. If the concentrations vary by
5 percent or more at one or more of the points, position the probe at the point where the value nearest to the
average O2 or CO2 concentration was measured.
4.2.2. Calibrations
Calibrations should be conducted on all monitors using Protocol No. 1 calibration gases. Protocol No. 1 gases
comply with requirements for traceability to the National Institute of Standards and Technology.
Each monitor should be calibrated with a zero concentration gas. In addition, each should be calibrated with a
suite of gases, selected to cover the monitor operating ranges specified later in Section 4. The NOX, CO2, and O2
monitors should be calibrated with two additional gas concentrations each. One concentration should be 40 to 60
percent of span and one should be 80 to 100 percent of span. Maximum and actual pollutant concentrations
anticipated for the test engine should be determined prior to the test to aid in selecting appropriate calibration
gases and setting instrument ranges. The CO and THC monitors should be calibrated with three additional gas
concentrations. For CO, the concentrations should include one each at approximately 30 , 60 , and 90 percent of
span. For THCs, methane should be used if this is consistent with the basis that PEMS uses to report THCs (i.e.,
THC concentrations quantified as methane). The calibration concentration ranges for THCs includes the
following: 25 to 35 percent, 45 to 55 percent, and 80 to 90 percent of span.
All monitor calibrations should be conducted daily, before sampling begins. Calibrations should start by routing
calibration gases directly to each monitor using the sample gas manifold, and then adjusting the monitors to read
the appropriate calibration gas values. Note that the THC monitor calibrations are conducted through the entire
system only, not directly to the analyzer. After adjustments are made to the analyzers, a final linearity test
should be conducted by introducing each gas to the analyzers and recording responses while making no
adjustments. In accordance with Reference Method Criteria, an analyzer response within two percent of the
span (range) of the analyzer is acceptable. Following this and after each test run, zero concentration and mid-
span gases should be passed through the entire sampling system, and the values that are measured should be
recorded. Differences between the initial calibration and these system calibrations should be used to determine
system bias and drift values for each run and analyzer drift over the duration of each run. After field operations
are complete, these bias and drift values should be used to adjust measured Reference Method concentrations
before comparing the values to PEMS predictions. Details regarding the equations used to calculate these
corrections are provided in the corresponding Reference Method.
Regarding engine sensor calibrations, the testing entity should obtain copies of the most recent calibration
records for all of these sensors. If PEMS predictions do not agree well with Reference Method values during the
testing, these records may help in determining if the problem is related to sensor accuracy, or PEMS algorithm
problems.
4.2.3. Reference Method 3A - Determination of Oxygen & Carbon Dioxide Concentrations
For CO2 and O2, a continuous sample should be extracted from the emission source and passed through
instrumental analyzers. For determination of CO2 a non-dispersive infrared (NDIR) analyzer or equivalent
should be used. This type of instrument measures the amount infrared light that passes through the sample gas
versus a reference cell. As CO2 absorbs light in the infrared region, the light attenuation is proportional to the
CO2 concentration in the sample. The CO2 monitor range should be set at 0 to 20 percent CO2.
-------
Oxygen should be analyzed using a fuel cell, electrochemical cell, or paramagnetic analyzer or equivalent. The
fuel cell and electrochemical cell analyzers use electrolytic concentration cells that contain a solid electrolyte to
enhance electron flow to the O2 as it permeates through the cell. The technology used by this type of instrument
determines levels of O2 based on partial pressures. The electrode is porous (zirconium oxide) and serves as an
electrolyte and as a catalyst. The sample side of the reaction has a lower partial pressure than the partial
pressure in the reference side. The current produced by the flow of electrons is directly proportional to the O2
concentration in the sample. The paramagnetic technology used by this instrument determines levels of O2
based on the level of physical deflection of a diamagnetic material caused by exposure to the stack gas. The
higher the O2 concentrations, the greater the material is deflected. An optical system with an amplifier detects
the level of deflection, which is linearly proportional to the O2 level in the gas. The O2 monitor range should be
set at 0 to 25 percent O2.
4.2.4. Reference Method 7E - Determination of Nitrogen Oxides Concentration
Nitrogen oxides should be determined on a continuous basis, utilizing a chemiluminescence analyzer. This type
of analyzer catalytically reduces nitrogen oxides in the sample gas to NO. The gas is then converted to excited
NO2 molecules by oxidation with O3 (normally generated by ultraviolet light irradiation of air or oxygen). The
resulting NO2 luminesces in the infrared region. This emitted light is measured by an infrared detector and
reported as NOX. The intensity of the emitted energy from the excited NO2 is proportional to the concentration
of NO2 in the sample. The efficiency of the catalytic converter in making the changes in chemical state for the
various nitrogen oxides is checked as an element of instrument set up and checkout. The appropriate NOX
monitor range should be set based on preliminary site-specific data collected before starting the test. More than
one range may be needed if measured NOX concentrations vary widely between different engine load and speed
operations. In any case, measured NOX concentrations should be greater than 30 percent of the analytical range
selected, and no readings should be higher than the selected range.
4.2.5. Reference Method 10 - Determination of Carbon Monoxide Concentration
For Reference Method 10, a gas filter correlation analyzer utilizing an optical filter arrangement and NDIR
detection or equivalent should be used. The method chosen should provide high specificity for CO.
In the instrument suggested gas filter correlation utilizes a constantly rotating filter with two separate 180-
degree sections (much like a pinwheel.) One section of the filter contains a known concentration of CO, and the
other section contains an inert gas without CO. The sample gas is passed through the sample chamber containing
a light beam in the region absorbed by CO. The sample is then measured for CO absorption with and without
the CO filter in the light path. Based upon the known concentrations of CO in the filter, these two values are
correlated to determine the concentration of CO in the sample gas. An appropriate CO analyzer operating range
should be selected as described in Section 4.2.4.
4.2.6. Reference Method 25A - Determination of Total Gaseous Organic Concentration
Total hydrocarbon vapors in the exhaust gas should be measured using a flame ionization (FID) analyzer. The
method used by the FID passes the sample through a hydrogen flame. The intensity of the resulting ionization is
amplified, measured, and then converted to a signal proportional to the concentration of hydrocarbons in the
sample. Unlike the other reference methods, the sample stream going to the FID analyzer does not pass through
the condenser system, so it can be kept heated until it is analyzed. This is necessary to avoid loss of the less
volatile hydrocarbons in the gas sample. Because all combustible hydrocarbons are being analyzed and reported,
the emission value must be calculated to some base (methane or propane). The calibration gas for THCs should
be either methane or propane; which ever is consistent with the basis on which the PEMS reports THC values.
An appropriate THC analyzer operating range should be selected as described in Section 4.2.4.
-------
4.2.7. Determination of Emission Rates
If the PEMS predicts emissions in units of mass per unit time, use Reference Method 19 to convert measured
concentration values of the exhaust gases to emission rate values. This is accomplished by determining the
volumetric flow rate of the exhaust gas and then calculating the emission rate from the concentration and
volume data. The fundamental principle of this method is based upon F-factors, which are the ratio of
combustion gas volume to the heat content of the fuel. F-factors are calculated as a volume/heat input value,
(e.g., standard cubic feet per million Btu). This method applies only to combustion sources for which the
heating value for the fuel can be determined. The F-factor can be calculated from measured CO2 or O2
concentrations. This method includes all calculations required to compute the F-factors and guidelines on their
use. The F-factor for natural gas should be calculated from gas compositional measurements (elemental
analyses and lower heat content). Many facilities can provide these analyses using pipeline gas chromatograph
(GC) data. If not, gas samples can be collected and submitted to a laboratory for analysis, or the F-factors
published in Reference Method 19 can be used.
Other parameters needed to complete the Method 19 conversions to mass rate include fuel flow rate measured
by a fuel flow monitoring system (pressure and temperature based), and calculated engine brake horsepower
(can be calculated from engine speed and torque readings per operator based methods). The step-by-step
calculations involved are listed below.
Step 1. Normalize measure pollutant concentrations to heat input.
Concentration (Ib/MBtu) = measured concentration (Ib/scf) x F-factor (scf/MBtu)
Step 2. Calculate the engine heat consumption rate in million Btu per hour.
Heat consumption (MBtu/hr) = measured fuel flow (scfh) x fuel heating value (MBtu/ft3)
Step 3. Calculate emission rate as pounds per hour of pollutant.
Emission rate (Ib/hr) = concentration (Ib/Mbtu) x engine heat consumption (Mbtu/hr)
Step 4. Normalize emission rates to engine output as grams per brake horsepower hour (g/BHp-hr).
Emission rate (g/BHp-hr = (emission rate (Ib/hr) x 453.59 gms/lb) / engine output (BHp-hr)
As an alternative to Method 19 for determination of emission rates, exhaust gas volumetric flow rate can be
determined using actual stack gas measurements. This testing is done in accordance with EPA Reference
Methods 1 through 4 and involves determining exhaust gas velocity and molecular weight, and using these
measurements along with the measured stack cross-sectional area to calculate gas volumetric flow rate. This
procedure is fully documented in the Reference Methods and not repeated here. However, this procedure can
only be conducted on engine exhaust stacks that have sufficient straight run of pipe, acceptable test ports with
safe access, and laminar flow characteristics.
4.3. DATA ACQUISITION
Output from each of the instruments should be transmitted to a data acquisition system, typically a personal
computer-based data acquisition system. The system clock should be synchronized with the PEMS and the
engine control systems. This system should be configured to receive signals from all of the instruments every
4-7
-------
two seconds, and integrate those values over a pre-specified averaging period. During all tests, a 30-second
averaging period should be used for each monitored parameter, and these values should be stored for later
analysis and reporting purposes. Average values should also be determined over the time associated with each
run, and these values should be stored and used to determine run-average emissions for Relative Accuracy and
other determinations. Computer spreadsheets (Excel or other) can be used to calculate calibration results, and
make corrections to the data for calibration, system bias, and drift values.
Data should also be collected on engine performance parameters, and these data should be provided by either the
operator or PEMS data acquisition systems. These data will be needed to calculate some verification
parameters, identify alarm/alert conditions, and interpret verification results. Data should be recorded at 30-
second intervals, and then averaged for each test period.
d-R
-------
5.0 DATA VALIDATION, QUALITY ASSESSMENT, AND REPORTING
5.1. DATA VALIDATION
Quality control checks for the Reference Method measurements were presented in Section 4.2.2. Upon review,
all data collected should be classified as valid, suspect, or invalid. In general, valid results are based on
measurements that meet data quality goals, and that were collected when an instrument was verified as being
properly calibrated.
Often anomalous data are identified in the process of data review. All outlying or unusual values should be
investigated daily in the field using test records, test crew and engine operator interviews, and log forms.
Anomalous data may be considered suspect if no specific operational cause to invalidate the data is found. All
data, whether valid, invalid, or suspect, should be included in the final report. However, report conclusions
should be based on valid data only. The reasons for excluding any data should be justified in the report. Suspect
data may be included in the analyses, but may be given special treatment as specifically indicated.
All engine sensor and Reference Method data should be reviewed in the field by a designated field team leader
on a daily basis including those listed below.
Run average comparison of Reference Method and PEMS data for agreement based on
arithmetic mean, standard deviation, and Relative Accuracy for each measured parameter
Daily Reference Method calibration results and run-specific zero and mid-span calibration
results
5.2. DATA QUALITY
As a consequence of using EPA Reference Methods to verify PEMS performance, measurement methodologies
and data quality determinations are defined. Reference Method procedures ensure that run-specific
quantification of instrument and sampling system drift and bias occurs, and that runs are repeated if specific
performance goals are not met. Furthermore, the Reference Methods require adjustments be made to all
measured concentrations based on run-specific measurements of instrument and sampling system responses to
calibration checks. Normally, measurements of these data quality indicators would be used to quantify the data
quality achieved during testing, but in this case, these data are used to adjust measured values to ensure that the
highest possible representativeness and quality exists in the final results. Therefore, the Relative Accuracy and
other determinations conducted are considered to be of acceptable quality if all Reference Method calibrations,
performance checks, and concentration corrections specified in the Reference Methods have been successfully
conducted. As such, the Data Quality Objective (DQO) for all runs is to ensure that this has occurred. Evidence
of the successful execution of these requirements should be documented in the verification report, along with
run- and pollutant-specific calibration results.
Specific data quality indicators are discussed below including indicators for completeness, precision, and bias.
These apply to all of the verification parameters that should be assessed. A summary of the data quality
indicator goals is shown in Table 5-1.
1. Completeness should be 100 percent for the Relative Accuracy determinations. This means that data must meet
the DQOs (analyzer and system calibration criteria) for all RATA runs conducted. Runs that don't meet the
-------
DQO should be repeated. The completeness goal for the off-normal engine operating tests should be 85
percent. This goal is lower than 100 percent to account for potential difficulties that may occur in (1)
establishing abnormal engine operating conditions planned for this series of tests, and (2) measuring potentially
large and dynamic pollutant concentration profiles in a manner that meets the DQO. Finally, the completeness
goal for the sensor drift tests is 100 percent, which means that all runs should be conducted, as outlined in 3.3.2,
that meet the DQO above, or be repeated. During the verification of the ANR PEMS, all of these completeness
goals were met.
2. System accuracy or bias assessments should be conducted at the beginning of each day using the protocols
defined in each Reference Method. This should be accomplished by routing a suite of calibration gases directly
into each monitor. For each calibration gas concentration examined, a data quality indicator goal of ± 2 percent
of the analyzer span value should be used for O2, CO2, NOx, and CO. A goal of ± 5 percent of the calibration
gas value should be used for THCs. Daily accuracy values determined from these evaluations should be
reported in the final verification report to document the ability of the testing entity to achieve the accuracy
indicator goals specified above. These accuracies should be determined in the field, and if deviations from the
goals are observed, sampling should be halted by the testing entity until corrective action is taken. A corrective
action is the process that occurs when the result of an audit or quality control measurement is shown to be
unsatisfactory, as defined by the data quality objectives or by the measurement objectives for each task. The
corrective action process involves the Field Team Leader, Project Manager, and QA Manager. In cases
involving the analytical process, the correction action will also involve the analyst. A written Corrective Action
Report is required on all corrective actions (Example in Appendix A).
3. System precision or bias should be determined for the combined sampling system and analyzer at the
beginning and end of each run using the protocols defined in each Reference Method. This is accomplished
by routing zero concentration and mid-span gases through the sample collection lines and monitor systems,
and comparing the measured concentrations with the certified calibration values. System bias, determined
in this manner, should be measured before and after each run to determine if the run is acceptable for use. A
drift of greater than ± 3 percent of analyzer span (difference between the before and after system bias)
should be considered unacceptable, and the run should be repeated. If a drift of less than 3 percent occurs,
which is the data quality indicator goal for precision, the average of the before and after system bias values
should be used to correct the measured concentrations in each of the Reference Methods. All system bias
values and calculated drift values should be reported in the final verification report on a run-specific and gas
specific basis as a means of documenting that this data quality indicator goal has been achieved.
Table 5-1. Data Quality Indicator Goals
Data Quality
Indicator
Completeness
Precision
Accuracy
Type of Verification Test
Relative Accuracy
100 %
Drift <± 3% of span
±2% of span3
±5 % of cal. conc.b
Off-Normal Engine
85%
Drift <± 3% of span
±2% of span3
±5 % of cal. conc.b
Sensor-Failure
100 %
Drift <± 3% of span
±2% of span3
±5 % of cal. conc.b
a 02, C02, NOX, and CO
b THCs
In addition to these quality control measures, independent systematic checks to determine the quality of the data
should be performed on the activities of this type of evaluation. Under the ETV Program, these checks consist
-------
of a performance evaluation audit and data audit as described below. In addition, the internal quality control
measurements are used to assess the performance of the analytical methodology. The combination of these
audits and the evaluation of the internal quality control data allow the assessment of the overall quality of the
data for the evaluation.
Under the ETV program, a designated QA Manager is responsible for ensuring the audits are conducted as
required by the site specific Test/QA Plan. Audit reports that describe problems and deviations from the
procedures are prepared and distributed to the Field Team Leader. Any problems or deviations need to be
corrected. The Field Team Leader is responsible for evaluating corrective action reports, taking appropriate and
timely corrective actions, and informing the QA Manager of the action taken. The QA Manager is then
responsible for ensuring that the corrective action was taken. A summary report of the findings and corrective
actions is prepared and distributed to the Project Manager and Center Director.
Performance Evaluation Audit
The performance evaluation audit (PEA) is designed to check the operation of the emissions testing analytical
system. The method of performance will be based on internal audits performed by the Field Team Leader. For
an evaluation of this type, a blind audit of one or more of the analyzers can represent the PEA. Calibration
gases can be obtained with known (certified) concentrations of NOX, CO, and/or THCs and be presented to the
Entech analyst in such a manner as to have the concentration of the PEA unknown (blind) to the analyst. Upon
receiving the analytical data from the analyst, the Field Team Leader will evaluate the performance data for
compliance with the requirements of the project. The PEA must occur on-site during the field test.
Audit of Data Quality
The audit of data quality (ADQ) is an evaluation of the measurement, processing, and evaluation steps to
determine if systematic errors have been introduced. During the ADQ, the QA Manager, or designee, will
randomly select approximately 10 percent of the data to be followed through the analysis and processing the
data. The scope of the ADQ is to verify that the data-handling system is correct and to assess the quality of the
data generated.
The ADQ, as part of the system audit, is not an evaluation of the reliability of the data presentation. The review
of the data presentation is the responsibility of the Project Manager and the technical peer reviewer.
5.3. REPORTING
At the completion of the evaluation, a draft verification report and Statement is prepared by the Project
Manager. Under the ETV Program, the final verification report contains a verification statement, which is a 3 to
4 page summary of the PEMS tested, the test strategy used, and the verification results obtained. The
verification report summarizes the results for each verification parameter discussed in this guideline and
contains sufficient raw data to support findings and allow others to assess data trends, completeness, and quality.
Clear statements should be provided which characterize the performance of the verification parameters. An
example outline of the report is shown below.
Example Verification Report Outline
Verification Statement
5-3
-------
Section 1: Verification Test Design and Description
Identification of Participants
PEMS system and site description
Overview of the verification parameters and evaluation strategies
Section 2: Results
Relative Accuracy Determinations
PEMS Prediction Capabilities During Abnormal Engine Operation
PEMS Response to Sensor Failure
SectionS: Data Quality Assessment
Section 4: Additional Technical and Performance Data (optional)
Appendices: Raw Verification and Other Data
-------
6.0 BIBLIOGRAPHY
Buchop, Thomas Robert, et al. "Parametric Emissions Monitoring System Having Operating Condition
Deviation Feedback." United States Patent Number 5,703,777. United States Patent Office. Washington, DC.
December 30, 1997.
Code of Federal Regulations, Title 40, Part 60 (Appendices A and B). United States Environmental Protection
Agency. Washington, DC. 1999.
Code of Federal Regulations, Title 40, Parts 64 (Appendix C) and 75 (Appendix E). United States
Environmental Protection Agency. Washington, DC. 1999.
"Example Specifications and Test Procedures for Predictive Emission Monitoring Systems." Emission
Measurement Center. United States Environmental Protection Agency. Research Triangle Park, NC. 1999.
Document can be obtained from the following Internet location www.epa.gov/ttn/emc/cem.html.
-------
-------
APPENDIX A
Sample
Field Data Log Forms
and
Data Acquisition System Outputs
A-l
-------
SAMPLE
FIELD DATA
LOG FORMS
A-
-------
PEMS INSTALLATION/SET-UP CHECKLIST
Completed by: Date:
Complete
Y/N/na
ACTIVITY/ITEM
REMARKS
(if needed, continue on reverse side by item)
Software installation and
checkout completed
Verify critical sensors - number,
model
Sensor input present on engine
computer, correct range
Procure sensor calibration data
Verify PEMS printouts available
and include identification of
engine, date, time, all emission
values, and alarms
Verify and document engine ID.
NOTES:
A -
-------
TESTING SET-UP/PREPARATION CHECKLIST
Completed by:
Date:
Complete
Y/N/na
ACTIVITY/ITEM
Identify test team participants and
team leader
Identify contact person for PEMS
and engine operation
Identify test team Reference
Method system - model, serial
number, wet or dry basis
Identify operating range and
calibration gases - contents,
concentrations, cylinder s/n
calibration certificate
Verify interference tests
documented or completed
Verify and document results of
NC>2 to NO conversion test
Verify DAS printout is complete
Verify stratification testing and
document results
Verify integrity of the sampling
system, multi-point sampling, and
document location of calibration
gas injection
Document system leak check
REMARKS
(if needed, continue on reverse side by item)
NOTES:
A-4
-------
TESTING SET-UP/PREPARATION CHECKLIST
(continued)
Complete
Y/N/na
ACTIVITY/ITEM
REMARKS
(if needed, continue on reverse side by item)
Document system response times
Synchronize PEMS and Reference
Method Clocks
Manually check DAS calculations
Document any data points
requiring manual data collection
and transfer list to "Test Run
Observation Checklist"
NOTES:
-------
TEST RUN OBSERVATION CHECKLIST
(Note: Complete a checklist for each test run)
Completed by:
Date:
Complete
Y/N/na
ACTIVITY/ITEM
Document planned test conditions
(from test matrix)
Pre-test calibrations on sampling
systems completed? Documented?
Atmospheric conditions
Start time for test run
Document actual test conditions
Verify PEMS and Reference Method
System are collecting required data
points
Verify all manually collected data
are documented
End time for test run
Post-test calibration of sampling
systems completed
Bias determined and applied to data
REMARKS
(if needed, continue on reverse side by item)
Temperature Barometric
Press. RH
Wind speed/direction /
Test Start
Test end
NOTES:
A-fi
-------
TEST RUN OBSERVATION CHECKLIST
(continued)
Complete
Y/N/na
ACTIVITY/ITEM
REMARKS
(if needed, continue on reverse side by item)
Copy of Reference Method test run
data obtained
Verify completeness
Copy of PEMS test run data obtained
Verify completeness
Document all anomalies and
unexpected events/conditions
DAS output obtained?
Obtain gas composition data?
NOTES:
A-7
-------
Verification
Verification
Description
Corrective Action Report
Title:
Description:
of Problem:
Investigatic
Originator: Date:
>n and Results:
Investigator: Date:
Corrective Action Taken:
Carbon copy
Originator: Date:
Approver: Date:
Project Manager, Center Director, Center QA Manager, Pilot Manager
Pnae> A-R
-------
SAMPLE
REFERENCE METHOD
DATA ACQUISITION SYSTEM
OUTPUTS
Pnae> A-Q
-------
PLANT NAME:
UNIT # :
LOCATION:
DATE:
RUN*
1
2
3
4
5
6
7
8
9
* 10
* 11
* 12
START END
TIME TIME
0:00
12:01
12:47
13:30
14:15
15:00
15:45
16:30
17:30
0:30
12:31
13:17
14:00
14:45
15:30
16:15
17:00
18:00
REFERENCE METHOD
IbNOx/
ppmd NOx %w CO2 mmBffl
268.80 13.28 0.435
274.23 13.34 0.442
279.63 13.21 0.455
275.21 13.35 0.443
272.02 13.27 0.441
272.58 13.27 0.441
268.34 13.25 0.435
271.52 13.28 0.439
268.61 13.28 0.435
CONTINUOUS MONITORING
IbNOx/
ppmd NOx %w CO2 mmBtu
265.05 13.08 0.436
264.45 13.05 0.436
261.90 13.03 0.432
264.50 13.03 0.436
262.85 12.97 0.436
259.75 13.03 0.428
253.40 12.94 0.421
254.50 12.94 0.423
252.75 12.99 0.418
DIFFERENCE
IbNOx/
ppmd NOx %w CO2 mmBtu
3.75 0.20 -0.001
9.78 0.29 0.006
17.73 0.18 0.023
10.71 0.32 0.007
9.17 0.30 0.005
12.83 0.24 0.013
14.94 0.31 0.014
17.02 0.34 0.016
15.86 0.29 0.017
Test Mean: 272.33 13.28 0.441 259.91 13.01 0.430
MEAN DIFFERENCE: 12.42 0.27 0.01
NOx Conversion Factor: 1.194E-07 Ib NOx / SCF - ppm NOx
Fc- Factor: 180° SCF/mmBtu STANDARD DEVIATION: 4.52 0.06 0.01
CONFIDENCE COEFFICIENT: 3.47 0.04 0.01
Bias Adjustment Factor = (1 + d/CEM) RELATIVE ACCURACY (%): 5.84 | 2.39 3.81
WHERE: d = Meanof the Differences BIAS ADJUSTMENT FACTOR: 1.026
GEM = Mean of the Source Monitor's Data Values
T - VALUE: 2.306
Run not included in Relative Accuracy Calculations
-------
Reference Method Values Corrected for Bias & Drift
PLANT NAME:
UNIT*:
RUN #:
START TIME:
END TIME:
DATE:
CAL GAS
0.00
443.00
0.00
463.60
0.00
12.12
0.00
11.50
VALUE
ppm SO2
ppm SO2
ppm NOx
ppm NOx
%02
%02
% CO2
% CO2
INITIAL CAL
4.15
435.41
1.22
437.36
0.18
12.15
0.15
11.38
FINAL CAL
2.69
439.80
0.73
439.80
0.43
12.27
-0.05
11.48
AVERAGE CAL
3.42
437.61
0.98
438.58
0.31
12.21
0.05
11.43
Raw Data: 223.11 ppm SO2
257.27 ppm NOx
6.41 % 02
13.19 % CO2
0.000 % H20
CORRECTED VALUES: 224.15 ppmw SO2
271.52 ppmw NOx
13.28 %w CO2
0.439 IbNOx/mmBtu
6.22 %d O2
13.7.8 Q/.H rm
CONVERSION FACTORS:
NOx = 1.194E-07 IbNOx / SCF - ppm NOx
Fc - FACTOR = 1800 SCF / mmBtu
SAMPLE CALCULATIONS:
CORRECTED VALUES = Cma * (C - Co) / (Cm - Co)
WHERE: C = MEAN REFERENCE MEASUREMENT
Co = MEAN ZERO CALIBRATION RESPONSE
Cm = MEAN MID OR UPSCALE CALIBRATION RESPONSE
Cma = ACTUAL MID OR UPSCALE CAL GAS CONCENTRATE
EMISSION RATE = (ppm)(Conversion Factor)(Fc-Factor)(100 / % CO2)
A-l 1
-------
System Bias & Drift Calculations
PLANT NAME:
UNIT #:
RUN #:
START TIME:
END TIME:
DATE:
ANALYZER SPAN: 1000.00
1000.00
25.00
3 VALUE
ppm SO2
ppm SO2
ppm SO2
ppm NOx
ppm NOx
ppm NOx
% O2
% O2
% O2
% CO2
% CO2
% CO2
CAL ERROR
RESPONSE
1.10
451.53
956.04
0.73
468.13
860.81
-0.18
12.15
20.70
0.05
11.67
17.53
20.00
CAL ERROR
( % OF SPAN )
-0.11
-0.85
0.01
-0.07
-0.45
0.00
0.72
-0.12
-0.24
-0.25
-0.85
-0.15
ppm SO2
ppm NOx
% O2
% CO2
INITIAL
SYSTEM BIAS CHECK
RESPONSE (% BIAS)
4.15 0.31
435.41 -1.61
1.22 0.05
437.36 -3.08
0.18 1.44
12.15 0.00
0.15 0.50
11.38 -1.45
FINAL
SYSTEM BIAS CHECK
RESPONSE
2.69
439.80
0.73
439.80
0.43
12.27
-0.05
11.48
(% BIAS)
0.16
-1.17
0.00
-2.83
2.44
0.48
-0.50
-0.95
DRIFT
(% OF SPAN)
-0.15
0.44
-0.05
0.24
1.00
0.48
-1.00
0.50
IION ERROR = (( R-A ) / S ) * 100
R = CALIBRATION GAS VALUE
A = REFERENCE ANALYZER RESPONSE
S = ANALYZER SPAN VALUE
3IAS = (( C - A) / S) * 100
C = SYSTEM CAL RESPONSE
A = ANALYZER CAL RESPONSE
S = ANALYZER SPAN VALUE
Cf = FINAL SYSTEM CAL RESPONSE
Ci = INITIAL SYSTEM CAL RESPONSE
S = ANALYZER SPAN VALUE
A-17
-------
Volumetric Flow Rate Determination
PLANT NAME:
UNIT #:
RUN #:
START TIME:
END TIME:
DATE:
TEST DATA
Test
Beiat
A-l
A-2
A-3
A-4
A-5
A-6
A-7
A-8
B-l
B-2
B-3
B-4
B-5
B-6
B-7
B-8
MAX.
MTN
Delta P
fin H2O)
0.530
0.520
0.530
0.490
0.530
0.520
0.500
0.450
0.530
0.530
0.520
0.470
0.540
0.520
0.510
0.440
0.540
0 440
Temperature
(Dog. F)
126
126
127
129
128
128
123
125
128
129
128
125
125
125
125
125
129
1 7^
Stack Diameter (D):
Stack Area (A):
Barometric Pressure (Pbar):
Static Pressure (Pg):
Percent O2 (% O2):
Percent CO2 (% CO2):
Percent Nitrogen (% N2):
Pilot Tube Coefficient (Cp):
Meter Box Delta H (dH):
Meter Box Factor (Y):
Average Meter Temp. (Tm):
Gas Meter Volume (Vm):
Impinger (V):
Silica Gel (W):
Root Mean Sq. Delta P (Pavg):
Mean Stack Temperature (Ts):
367.00
105,784
29.70
-0.480
6.22
13.28
80.50
0.84
1.94
0.9800
67.300
23.838
62
3.6
inches
sq. inches
inches Hg
inches H2O
%O2
% CO2
%N2
degrees F
cubic feet
ml
grams
0.5077 inches H2O
126.38 degrees F
CALCULATIONS
Vm(std) = (Vm)(Y)(17.64((Pbar)/(Tm + 460))
Vwc(std) = (V)(.04707) + (W)(.04715)
% H2O = [Vwc(std) / (Vwc(std) + Vm(std))] x 100
Mfd = 1 - (%H2O / 100)
Ps = Pbar + (Pg/ 13.6)
Md = 0.44(% CO2) + 0.32(% O2) + 0.28(% N2)
Ms = (Md)(Mfd) + 0.18(% H2O)
Vs = 85.49 (Cp) x SQRT[(Pavg)(Ts + 460) / (Ps)(Ms)]
Qsd = (60 / 144)(Mfd)(Vs)(A)(Ps / Pstd)(Tstd / (Ts + 460))
Qs = (3600 / 144)(Vs)(A)(Ps / Pstd)(Tstd / (Ts + 460))
Qaw = (60 / 144)(Vs)(A)
Vm(std) =
Vwc(std) =
% H2O =
Mfd =
Ps =
Md =
Ms =
Vs =
23.211 dscf
3.0834 cubic ft.
11.726 %H2O
0.883
29.665 in. Hg
30.374 Ib/lb-mole
28.931 Ib/lb-mole
42.29 ft/sec
Qsd = 1.469E+06 DSCFM
Qs = 9.985E+07 SCFH
Qaw = 1.864E+06 ACFM
1664.1 Kscfm
A-ll
------- |