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Optical Remote Sensing for Emission Characterization 

from Non-point Sources

1.0 Scope and Application

1.1 Introduction. This protocol provides the user with methodologies for 

characterizing gaseous emissions from non-point pollutant sources. These methodologies

use an open-path, Path-Integrated Optical Remote Sensing (PI-ORS) system in multiple 

beam configurations to directly identify “hot spots” and measure emission fluxes. Basic 

knowledge of a PI-ORS system and the ability to obtain quality path-integrated 

concentration (PIC) data is assumed. The user must be capable of using commercial 

software to utilize the procedures and algorithms explained in this protocol. The

methodologies in this protocol have been well developed, evaluated, demonstrated,

validated, and peer-reviewed.1-12

NOTE 1 — Any mention of a “PI-ORS system” in this protocol refers to the open-path 

PI-ORS instrument itself, as well as any associated components used, such as mirrors, scanners, 

and software.

This protocol does not discuss specific applications (e.g., hog farms, landfills), but 

provides general guidelines or procedures that can be applied. Detailed protocols for 

specific applications may be added at a future date.

1.1.1 Scope. This protocol currently describes three methodologies, each for a 

specific use. The Horizontal Radial Plume Mapping (HRPM) methodology was designed 

to map pollutant concentrations in a horizontal plane. The Vertical Radial Plume Mapping 

(VRPM) methodology was designed to measure mass flux of pollutants through a vertical 

plane, downwind from an emission source. The one-dimensional Radial Plume Mapping

methodology (1D-RPM) was designed to profile pollutant concentrations along a line-ofsight (e.g., along an industrial site fenceline). In future revisions to this protocol, additional 

PI-ORS emission monitoring methodologies (other than the methodologies described in 

this protocol) that address non-point sources can be added as validation data are generated.

1.1.2 Choice of Instrumentation. The choice of PI-ORS system to be used for the 

collection of measurement data (and subsequent calculation of PIC) is left to the discretion 

of the user, and should be dependent on the compounds of interest and the purpose of the 

study. The methodologies are independent of the particular PI-ORS system used to 

generate the PIC data. It is recommended for the HRPM, VRPM, and 1D-RPM

methodologies that the typical expected concentration over the longer beams should be 

about 10 times the minimum detection limit of the instrument. When this is not the case, 

the user should replace nondetects with values of half the minimum detection limit (see 

Table A.3 in the Appendix A).
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1.1.3 Developmental Basis. Several methodologies have been developed and applied to 

estimate emission rates from non-point fugitive sources — such as landfills, coal mines, and 

wastewater treatment plants — using PI-ORS technologies.3, 13-18The methodologies explained 

in this protocol were developed from studies that concentrated on developing, evaluating, and 

demonstrating the various configurations of the radial plume mapping (RPM) based

methodologies.

1,2,4-7,9-11

The RPM-based methodologies (configurations, procedures, and 

algorithms) were patented as a technology for mapping air contaminants using a PI-ORS 

system with a non-overlapping, variable pathlength, radial beam geometry.8 The RPM 

methodologies are the intellectual property of the University of Washington; if you plan 

to employ the RPM-based methodologies, please contact the Office of Intellectual 

Property and Technology Transfer at The University of Washington (UW TechTransfer; 

techtran@u.washington.edu) for potential licensing.

1.1.4 Applicability. The methodologies described in this protocol are appropriate for 

characterizing ground level area sources and non-point fugitive emission sources such as 

landfills, lagoons, and industrial complexes. The limitations of these methodologies can be 

based on the instrument or beam geometry.

1.1.4.1 Instrument-Specific Limitations. The PI-ORS system chosen will determine 

the maximum pathlength, the compounds that can be detected, and the detection limits of

these compounds and can influence accuracy and precision as well.

1.1.4.2 Beam Geometry Limitations. Plume emissions are assumed to originate near 

ground level (within three meters from the ground). If some or all of the emissions are 

above the three-meter criteria, then the beam geometries explained in this protocol may 

need to be modified. Complex topography and obstructions may require some variations 

from the standard configurations described in this protocol.

1.2 Compound List. Any fugitive gaseous compound is a potential candidate for 

application of these methodologies. These methodologies are restricted only by the 

limitations of the PI-ORS system chosen.

1.2.1 Sensitivity. Table 1 shows some typical sensitivity ranges for several PI-ORS 

systems. Prior to field deployment, the expected sensitivity of the PI-ORS system should be 

evaluated against project goals.

1.2.2 Data Quality. The level of acceptable uncertainty is dependent on the 

application of the reported data – whether for hot spot determination (HRPM), 

measurement of emissions flux (VRPM), or line-of-sight profile concentrations (1D-RPM). 

The user must tailor their choice of PI-ORS system, configuration, and tolerance 

parameters to meet their end needs.
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Table 1. Typical Sensitivity Ranges for Several PI-ORS Systems

PI-ORS 

System*

Formaldehyde1,3-

Butadiene

Acrolein Benzene Ammonia Total 

VOC

Scanning OP-FTIR 

(for > 100 m pathlength)

2 – 10 

ppb

2 – 10 ppb 8 – 30 

ppb

15 – 50 

ppb

0.5 – 4 ppb 1 – 5 ppb

UV-DOAS

(for > 250 m pathlength)

0.5 ppb NA NA 0.1 ppb 1 ppb NA

TDLAS 

(for > 250 m pathlength)

NA NA NA NA 20 – 50 

ppb

NA

PI-DIAL

(1000 m pathlength)

**   10

μg/m

3

**  **

* See Section 6 for full instrument names.

NA This compound cannot currently be measured with this instrument.

** Typically a custom-built instrument. Sensitivity ranges are instrument-specific.

2.0 Summary of Methodologies

2.1 Principle. This protocol describes the application of the HRPM, VRPM, and 

1D-RPM methodologies designed specifically for the use of PI-ORS systems. The HRPM 

methodology utilizes multiple non-intersecting beam paths in a horizontal plane and 

optimizing algorithms to give a time-averaged surface concentration field across plumes of

contaminants. This methodology is used to locate hot spots close to the ground. The VRPM

methodology utilizes multiple non-intersecting beam paths in a vertical plane downwind 

from the emission source to obtain a mass-equivalent plume map. This map, in conjunction 

with wind speed and direction, is used to obtain the flux of pollutants through the vertical 

plane. The measured flux is then used to estimate the emission rate of the upwind source

being characterized. The 1D-RPM methodology utilizes multiple beam paths along a lineof-sight to obtain concentration profiles downwind of a source (e.g., along an industrial site 

fenceline). The peak concentration position along the line-of-sight can be incorporated with 

wind direction to estimate the location of an upwind fugitive emission source.

2.1.1 The user-selected PI-ORS system collects spectral data; there are no true 

“samples” that require preservation, storage, transport, extraction, digestion, or 

concentration. The chemical concentration of each gas species of interest along each beam 

path is obtained following the measurement and analysis procedures for the instruments 

being used.

2.1.2 The physical range and sensitivity of the methodologies are determined by the 

limitations of the PI-ORS system selected to acquire the PIC data. The accuracy of the

results from the methodologies depends on the instrument accuracy as well as: 1) the 

quality control (QC) criteria defined for the methodology-specific algorithms, and 2) the 

accuracy and representativeness of the wind data (for VRPM and 1D-RPM 

methodologies).
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2.2 HRPM Methodology – Hot Spot Source Location. The HRPM methodology is 

used to locate the source of fugitive emissions or hot spots. A rectangular area (which may 

be a square) is defined around the ground location where the suspected gaseous emissions

are originating. Ideally, the HRPM configuration will cover the entire suspected source 

area; however, this may be prevented by equipment limitations or site conditions. Larger 

areas may need to be divided into smaller sections and studied separately. 

2.2.1 Once the HRPM configuration area has been defined, it is divided into smaller 

rectangular areas called pixels. The total number of pixels required is less than or equal to 

the total number of beam paths. Each pixel will have at least one optical beam path that 

terminates within its boundaries by a pathlength-defining component (PDC).

NOTE 2 — The methodologies here are not instrument specific. For ease of presentation, 

pathlength-defining component (PDC) is used to denote the component on the other end of the 

optical path from the PI-ORS instrument. Depending on the instrument selected, this could be a 

source, detector, mirror, or other reflecting object.

2.2.2 The scanning PI-ORS instrument is typically placed on a corner of the 

rectangular sampling area. The reconstruction algorithm for obtaining concentration 

contour maps consists of two stages (detailed in Section 12.2).

NOTE 3 — Although the PI-ORS instrument is typically placed on a corner of the 

rectangular sampling area, in some cases it may be necessary to place the PI-ORS instrument 

along a boundary of the survey area. This protocol does not address alternate placement of the PIORS instrument.

2.2.2.1 An iterative inversion algorithm is used to determine average concentrations 

in each pixel.

2.2.2.2 An interpolation procedure is then applied to these concentration values to 

calculate concentrations in higher spatial resolution.

2.2.3 HRPM calculations are performed and the locations of concentration maxima 

qualitatively indicate the locations of gaseous emission hot spots. Wind speed and direction 

measurements may be recorded while collecting HRPM methodology data to aid in 

interpreting the concentration contour maps produced.

2.3 VRPM Methodology - Estimation of Emission Rate. The VRPM methodology is 

used to estimate the rate of gaseous emissions from an area fugitive source. A vertical 

scanning plane, downwind of the source, is used to directly measure the gaseous flux 

(detailed in Section 12.3).

2.3.1 The total length of the measurement area required depends on the size of the 

emission source, as well as the limitations of the selected PI-ORS system.

2.3.2 The height of the scanning area is dependent on the PI-ORS system limitations, 

the distance to the upwind boundary of the source, and the limitations of the infrastructure
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used for mounting the PI-ORS system components (e.g., mirrors and/or meteorological

station).

2.3.3 Wind speed and direction measurements must be recorded for flux calculations 

and preferably should be monitored in at least two heights (usually at 2 and 10 meters) for a 

more accurate interpolation and extrapolation through the height of the vertical plane. In

special cases when two wind monitors are not available, one wind monitor can be used at 

mid-height (3-5 m) to represent the average wind of the entire vertical plane. The VRPM 

method was validated with two wind monitors11; however, because a linear interpolation is 

applied between the two wind monitor heights, one wind monitor at mid-height should 

provide similar results.

2.3.4 The PIC measurements along the elevated beam paths (achieved by elevated 

PDC) provide vertical concentration gradient information of the emitted plume. The 

beam paths on the ground (ground level PDC) indicate the approximate ground level

concentration profile along the length of the VRPM setup. Ground-level refers to the area

as close to horizontal as possible, relative to the surface of the measurement area.

2.3.5 A bivariate Gaussian function (or superposition of two) is assumed for the 

plume mass across the VRPM plane, and the parameters of the mass-equivalent bivariate 

Gaussian function(s) are reconstructed from the measured PIC. These reconstructed 

parameters are then used to calculate the concentration values across the VRPM plane at 

high resolution.

2.3.6 The concentration values (in ppm) are converted to mass concentrations using

the molecular weight of the monitored gas species. The products of the mass 

concentration and the wind speed normal to the measurement plane are integrated across 

the plane to calculate the mass flux through the plane. Because the estimation of the 

emission rate is dependent on the wind data, stable and measurable wind conditions are 

desired so that the source remains upwind of the VRPM plane.

2.4 1D-RPM Methodology – Line-of-Sight Profile Concentrations and Upwind 

Source Location Estimation. The 1D-RPM methodology is used to profile pollutant 

concentrations along a line-of-sight downwind of a fugitive emission source. This 

pollutant concentration profile can be combined with wind data to estimate the location 

of an upwind source, when applicable. The scanning PI-ORS instrument and three or 

more PDC are placed in a crosswind direction along a line, such as an industrial site 

fenceline.

2.4.1 A Gaussian function (or superposition of two) is assumed for the plume 

concentration profile along the line-of-sight of the instrument and the parameters of the 

Gaussian function(s) are reconstructed from the measured PIC.

2.4.2 Multiple peak locations are reconstructed over time along the 1D-RPM lineof-sight. These peak positions are incorporated with corresponding wind directions to 
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create back-projected vectors for each measurement period. When the back-projected 

vectors converge in an area, this indicates the probable location of an upwind hot spot.

3.0 Definitions

1D-RPM: One-dimensional Radial Plume Mapping. The 1D-RPM methodology is one of 

the three methodologies described in this protocol, and is used for reconstructing line-ofsight profile concentrations.

CCF: Concordance Correlation Factor. CCF is used to represent the quality of fit for the 

reconstruction in the path-integrated domain. CCF is similar to the Pearson correlation 

coefficient, but is adjusted to account for shifts in location and scale.

Cycle: Cycle is defined as one complete sequential data collection through all PDCs in 

the setup.

Gaussian function: A normal distribution curve with a specified mean and standard 

deviation.

HRPM: Horizontal Radial Plume Mapping. The HRPM methodology is one of the three 

methodologies described in this protocol, and is used for locating “hot spot” sources.

Kernel matrix: A matrix detailing the length of each beam path in each pixel of the 

HRPM plane.

NNLS: Non-negative least squares. NNLS is similar to a classical least square 

optimization algorithm, but is constrained to provide the best fit of non-negative 

concentration values used in the HRPM methodology.

PDC: Pathlength-defining components. PDC is used to denote the component on the 

other end of the optical path from the PI-ORS instrument. Depending on the instrument 

selected, this could be a source, detector, mirror, or other reflecting object.

PIC: Path Integrated Concentration. Given in the units of parts per million-meter (ppmm), PIC is the integrated concentration of a gaseous pollutant measured along the beam

pathlength.

PI-ORS: Path-Integrated Optical Remote Sensing. An instrument system used to acquire 

gaseous PIC data along an open optical beam path.

ppm: Parts per million. Typical units of gas concentration for PI-ORS instruments, 

ratioed by volume.

SBFM: Smooth Basis Functions Minimization. An algorithm used in the VRPM and

1D-RPM methodologies to fit the parameters of the Gaussian basis function(s) to the 

measured PIC data.
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SSE: Sum of Squared Errors. The SSE is the sum of the squared differences between the 

measured and predicted PIC at each step of the iterative algorithm used in the VRPM and

1D-RPM methodologies.

Tolerance parameter: A threshold value used to terminate iterative search algorithms of 

the methodologies described in this protocol.

VRPM: Vertical Radial Plume Mapping. The VRPM methodology is one of the three 

methodologies described in this protocol, and is used for estimation of the emission rate

from an area source.

4.0 Interferences

4.1 General Interferences

4.1.1 Field-based interferences may result in the need to deviate from the setups 

specified for the PI-ORS system (see Section 11). Some examples of potential field-based 

interferences are vehicular or pedestrian traffic through the beam path and physical site

obstructions (e.g., buildings, trees, and complex topography).

4.1.2 The methodologies described in this protocol are based on concentration 

analysis of the chosen PI-ORS system, and different instruments may have unique

interferences. For example, concentration determination may be affected by the presence of 

water vapor and carbon dioxide in the infrared, or oxygen and ozone in the UV. Detection 

levels for several compounds may increase with the presence of the interfering species.

4.2 Weather Interferences

4.2.1 General. Certain weather conditions such as rain, fog, or snow can obscure the 

light beam and affect the ability of the PI-ORS instrument to continuously measure gaseous 

concentrations. Transient, but significant, obscuration can occur during heavy precipitation 

events, particularly with longer path measurements. This could limit the sensitivity of the 

PIC measurements or the ability to collect data. All meteorological conditions are recorded

in the field log so that the data collected during adverse conditions can be reviewed. The 

data collected during these events may be filtered out before inclusion in the methodologies 

calculations.

4.2.2 Winds. Wind conditions can greatly affect the results of field measurements and 

should be taken into account when interpreting data collected using the methodologies 

described in this protocol.

4.2.2.1 Calm wind conditions do not affect the HRPM methodology algorithm for hot 

spot source location. However, very low wind speeds are not ideal for the VRPM 

methodology for emission rate estimation, as the source plume may not be carried through 

the vertical plane in the absence of measurable wind.
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4.2.2.2 Very high wind speed conditions are not ideal for the HRPM, VRPM, or 

1D-RPM methodologies. High winds may displace or vibrate the optical alignment of the 

components of the PI-ORS system used in the setup, and affect the quality of the PIC 

values acquired in multiple beam paths. They may also cause displacement of the hot spot 

in HRPM. High winds are also not ideal for obvious safety reasons, as scissors jacks and 

other vertical towers can become unstable.

4.2.2.3 Based on controlled studies performed in the past, the following wind speed 

ranges are recommended for optimal results:

HRPM methodology: Near 0 to 5 m/s

VRPM methodology: 1 to 8 m/s

1D-RPM methodology: 1 to 8 m/s

4.2.2.4 For wind speeds between 8 and 11 m/s, data acquisition for VRPM and 1DRPM may take place, but should be carefully checked for reliability. When sustained winds 

are observed above 11 m/s, field measurements are not recommended, as data quality will 

most likely be compromised. General field safety protocols should be followed for the 

well-being of field personnel and for the safe operation of the PI-ORS system.

5.0 Safety

The hazards of performing the methodologies described in this protocol are those 

associated with any field event. Safety procedures should be established and implemented 

before using this protocol. Many of the potential target compounds are hazardous air 

pollutants (HAP), which may be suspected carcinogens or present other serious health 

risks. Exposure to these compounds should be avoided. PI-ORS system-specific safety 

protocols (e.g., eye exposure to lasers) should be followed.

6.0 Equipment and Supplies

6.1 Instrumentation. Any scanning PI-ORS system that can provide PIC data may be 

considered for the purposes of the methodologies described in this protocol, and may 

include the following: 

Open-Path Fourier Transform Infrared (OP-FTIR) Spectroscopy

Ultra-Violet Differential Optical Absorption Spectroscopy (UV-DOAS)

Open-Path Tunable Diode Laser Absorption Spectroscopy (TDLAS)

Path-Integrated Differential Absorption LIDAR* (PI-DIAL)

* LIDAR – Light Detection and Ranging
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6.1.1 The choice of instrument must be made based on its performance relative to the 

data quality objectives of the study.

6.1.2 The OP-FTIR and UV-DOAS technologies are widely used, due to their

capability of simultaneous chemical detection for a large number of gas species of 

environmental interest. However, when only a few gas species are of interest, it may be 

more beneficial to employ other PI-ORS instrumentation, such as the TDLAS or PI-DIAL.

NOTE 4 — A U.S. Environmental Protection Agency (EPA) compendium method (TO16) for making quality PIC measurements is available for OP-FTIR19

, and a set of companion

methodologies to this protocol are anticipated for development.

6.2 Vertical Structure. A stable, vertical structure is necessary for the VRPM 

configuration, and may include scissor jacks, towers, and buildings. The particular 

elevation device is unimportant, as long as the required, stable elevation is achieved. The 

criterion for stability of the vertical structure is reliable PIC data.

6.3 Computer Software. Specific computer software may be required by particular 

PI-ORS systems for obtaining PIC data. Various versions of commercial software are

available for post-analysis of the acquired PIC and wind data for all three methodologies in 

this protocol.

6.4 Meteorological Measurements. There are a number of commercially available 

meteorological stations that can be used. The QC checks described in Section 9.3.1 can be 

used to assess the accuracy and precision of your instruments.

6.5 Survey Measurements. There are a number of commercially available survey

instruments (e.g., rangefinder or theodolite) to measure pathlength, azimuth, and elevation 

angle. The QC checks described in Section 9.2 can be used to assess the accuracy and 

precision of your instruments.

7.0 Reagents and Standards

Use verification gases as a QC check for the methodologies described in this 

protocol (refer to Section 10). 

NOTE 5 —Suggested verification gases for OP-FTIR QC purposes are acetylene, ethylene, 

propane, propylene, and sulfur hexafluoride.

8.0 Sample Collection, Preservation and Storage.

The user will have no actual samples collected by the PI-ORS system or by the 

application of the methodologies described in this protocol. Therefore, a discussion of 

sample collection, preservation, and storage procedures is not necessary. Section 11 

describes the procedures the user will employ to acquire data by this protocol.
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9.0 Quality Control

It is assumed that the user of this protocol can acquire quality PIC data for use in 

the methodologies described in Section 12. Refer to the appropriate PI-ORS system

manuals and EPA methods for instrument-specific QC checks.

9.1 Internal QC. Traditional QC samples are not applicable to PI-ORS experiments. 

The QC procedures detailed in the appropriate instrument manual should be followed and 

must be in agreement with EPA methods, when available. For OP-FTIR measurements, 

currently available documents are Compendium Method TO-16 (1999)19; American 

Society for Testing and Materials (ASTM) Standard Practices E1982-98 (1999)20 and 

ASTM User Guide E1865-97 (Reapproved 2002) (1997)

21; and the German standard for 

OP-FTIR.22 It should be noted that calibration cells are not required in TO-16 or in the 

ASTM documents. For TDLAS, internal calibration cells are used.

9.2 Data Quality Indicator Goals for Critical Measurements. Data quality indicator 

(DQI) goals are established to assess the quality of critical measurements and are presented 

in Table 2. For the PI-ORS systems, they will be dependent on the specific components 

selected for use. Example DQIs for the OP-FTIR instrument are provided in Appendix A. 

Regardless of the PI-ORS system selected, the following QC checks will assess the 

accuracy and precision of the meteorological station and survey instrument, as well as the 

quality of the plume reconstruction for the chosen methodology.

NOTE 6 — Care should be taken when collecting meteorological and survey data, as the 

quality of this data will have a direct impact on the quality of the calculations.

9.2.1 Meteorological Measurements. The quality of the wind speed data can be 

assessed by placing the two wind monitors side-by-side and collecting data for 10 minutes. 

The average wind speed for both heads during this time should be at least 1 m/s. The 

difference of the average wind speed measurements between the two heads should be 

within 20% of the highest average value. 

The quality of the wind direction measurements can be assessed by manually setting 

the vane on the meteorological heads to magnetic north using a hand-held compass. For 

wind monitors with no vane, an artificial wind source can be used to establish a northerly 

wind. The measured wind direction during this check should be within 10o as compared to 

360o/0o. 

In addition to the DQI tests detailed above, there is an additional reasonableness check 

that can be conducted periodically to assess the performance of meteorological instruments 

in the field. Specifically, the measured wind direction should compare closely to the 

observed wind direction. 
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Table 2. Recommended DQIs for the Methodologies Described in this Protocol

Measurement Parameter Analysis Method DQI

PI-ORS Instrument Instrument specific a

Wind speed Side-by-side comparison of two 

wind monitors Within 20%

Wind direction Comparison to magnetic north Within 10o 

Optical path-length Measure and compare to known 

path Within 2%

Beam angle Measure and compare known 

angle Within 2o

HRPM, VRPM, and 

1D-RPM CCF •0.8

b

VRPM Flux Measurement Wind Direction -10o to +25o from 

perpendicularc

1D-RPM Peak Location Variability Reconstructed peak 

locationsd

a

Each PI-ORS instrument will have its own specific DQI goals. For instance, if an OP-FTIR is used, measured nitrous oxide and 

methane concentrations are compared to ambient levels to assess the quality of the data collected (when measurement occurs away 

from sources of these compounds).

19

b There are no true accuracy and precision parameters associated with the CCF. The calculated CCF value associated with the RPM 

algorithm must be •0.8 for the reconstruction to be considered valid. See Sections 12.2.3.2 (and following Note 10) and 12.3.3.2.

c This DQI is for each reconstruction/flux determination. Emission rate estimates — based on the Duke Forest validation study11 are 

typically considered valid when the wind direction is -10° to +25o from perpendicular (to the optical plane) (refer to Section 

11.3.4).

d Reconstructed peak locations should appear in at least two different segments to determine the source location using the 1D-RPM 

methodology (refer to Section 12.4.4). [A segment is defined as the distance between two consecutive PDCs or the closest PDC and 

the PI-ORS instrument location.] 

9.2.2 Survey Measurements. Perform a range calibration test by comparing a 

measured distance to a set distance. The measured distance should be within 2% of the set 

distance.

A possible angle measurement calibration test can be performed by placing the 

survey instrument between and in-line with two observable targets. Measure the 

horizontal angle, first from one object, then the other. The difference of the two 

measurements should be within 2o of 180°.

9.2.3 Plume Reconstruction. The plume reconstructions in the methodologies 

described in this protocol are assessed for quality using a statistical parameter, 

Concordance Correlation Factor (CCF), that indicates the goodness of fit between 

measured and predicted PIC. A CCF value of >0.8 indicates a valid reconstruction. See 

Section 12.2.3.2 (and following Note 10) and Section 12.3.3.2 for a discussion of CCF. For 

emission rate estimations using the VRPM methodology, maximal plume capture is 

desired. Therefore, emission flux measurements are typically considered valid when the 
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wind direction is close to perpendicular to the vertical plane (-10° to +25° for the Duke 

Forest validation study). Source locations using the 1D-RPM methodology are typically 

considered valid when the wind direction is within ±45o from perpendicular (to the line-ofsight). Reconstructed peak locations should appear in at least two different segments to 

determine the source location using the 1D-RPM methodology (refer to Section 12.4.4). A 

segment is defined as the distance between two consecutive PDCs or the closest PDC and 

the PI-ORS instrument location.

10.0 Calibration and Standardization

10.1 Instrument Calibration. The methodologies described in this protocol rely on 

accurate PIC data provided by a PI-ORS instrument. Calibration of these instruments is

instrument-specific and the user should refer to the instrument manual and EPA procedures 

for proper instrument calibration procedures.

10.2 Methodology Verification. The verification of the methodologies described in this 

protocol is a procedure to test the ability of each methodology to meet its objectives as 

described in Section 2.

10.2.1 Conduct a verification procedure involving a controlled gas release prior to 

using any new instrument/setup combination, and repeat the procedure when a significant 

change is made to any part of the PI-ORS instrument or setup. If only the methodology

software is changed, a previously verified data set can be used for verification purposes. 

Detailed explanations of these peer-reviewed procedures using verification gases have been 

published for the HRPM,6 VRPM,7,9,11and 1D-RPM 2,10 methodologies.

10.2.2 The verification procedure can be performed while data is collected in the field

as long as the following three criteria are met: 1) the PI-ORS system is able to monitor 

more than one gas simultaneously; 2) the verification gas is one of these monitored gases; 

and 3) the verification gas is not emitted by the source under study. If these criteria are not 

met, this verification procedure must be performed in a separate location using the same 

setup geometry. Table 3 presents the DQI goals for the verification procedures.

10.3 HRPM Methodology – Verification Procedure. The verification procedure 

involves releasing gas from a defined area, simulating a hot spot.

10.3.1 A suggestion for simulating a hot spot is to release the verification gas through 

a soaker hose arranged in a star-shaped pattern. This simulated source should be situated in 

an arbitrary location within the measurement area and comparable in size to the dimensions 

of one pixel.

10.3.2 A set of twelve (12) cycles can be considered a complete verification procedure. 

A cycle is defined as one complete sequential data collection through all PDCs in the setup. 

Data acquisition (see Section 11.2.9) and analysis parameters for the verification procedure 

should be similar to those used for field measurements.
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Table 3. DQIs for Verification Procedures

Measurement 

Parameter Analysis Method Accuracy Precision % Completea

HRPM hot spot location Verification gas release 10% b NA 100%

VRPM emission rate 

estimation

Verification gas release 25%c NA 100%

1D-RPM upwind source 

location

Verification gas release 20%d NA 100%

a % Complete is the number of “valid” measurements (those that meet DQI goals for accuracy and precision) compared to 

the total number of measurements taken.

b The distance between the reconstructed peak concentration and the center of the simulated hot spot should be within 10 

percent of the diagonal distance of the HRPM measurement area (see Section 10.2.3.3).

c The estimated release rate should be within ±25 percent of the measured (known) release rate to demonstrate an 

acceptable verification (see Section 10.2.4.5).

d The distance between the determined upwind source and the center of the simulated hot spot should be within 20 percent 

of the length of the 1D-RPM line-of-sight (see Section 10.2.5.3).

10.3.3 The software will reconstruct a surface concentration contour map for the 

HRPM configuration. The maximum concentration value of this map is considered the 

reconstructed peak concentration. The distance between the reconstructed peak 

concentration and the center of the simulated hot spot should be within 10 percent of the 

diagonal distance of the HRPM measurement area. This 10 percent criterion applies when 8 

to 16 beams are used in the setup.

NOTE 7 - Fewer than 8 beams can be used in the HRPM configuration; however, a verification 

procedure is not needed due to the qualitative (low resolution) nature of the results.

10.4 VRPM Methodology - Verification Procedure. The verification procedure 

involves releasing gas from a defined area, simulating an area source.

10.4.1 A suggestion for simulating an area source is to release the verification gas 

through a soaker hose arranged in an “H”-shaped pattern. This simulated source should be 

situated almost immediately upwind from the VRPM plane. The distance between the 

VRPM plane and the nearest boundary of the simulated area source should be 

approximately five times the average height of the ground-level beam(s) (refer to Section 

11.3). The dimensions of the simulated area source should be approximately one-third to 

one-half the length of the VRPM setup, and the “H” pattern should be centered with respect 

to the measurement plane.
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14

10.4.2 For the VRPM methodology verification procedure, the quantity of 

verification gas released over time should be measured. The precise starting and ending 

time of the release should be recorded.

10.4.3 The mass of the gas released can be determined in several ways. Two 

approaches are given below.

a) Weigh the gas cylinder prior to and after the release of the gas. Calculate the 

average actual emission rate of the gas. For example, if one kilogram (kg) of 

gas [1,000 grams (g)] is released over one hour [3,600 seconds (s)], the flux is 

calculated to be 1,000 g/3,600 s = 0.28 g/s.

b) Use a calibrated mass flowmeter to maintain a constant emission rate. The 

output emission rate from the mass flowmeter should be converted to units of 

g/s if necessary.

10.4.4 The software will calculate the flux of the verification gas through the VRPM 

plane. Fluxes should be averaged for all time periods when the measured wind direction 

is within -10° to + 25° from perpendicular to the vertical plane. These averaged values 

are considered valid as estimated emission rates for the verification procedure. A set of 

12 cycles can be considered a complete verification procedure, as long as at least half of 

these cycles satisfy the -10° to + 25° from perpendicular wind criteria. Data acquisition 

(see Section 11.3.5) and analysis parameters for the verification procedure should be 

similar to those used for field measurements. It is recommended that at least 1 kg be 

released to minimize errors in weighing the cylinders.

10.4.5 Compare the measured emission rate value (Section 10.4.3) with the 

estimated emission rate from the VRPM methodology (Section 10.4.4). The calculated 

release should be ±25 percent of the measured release rate (known) to demonstrate an 

acceptable verification.

10.5 1D-RPM Methodology - Verification Procedure. The verification procedure 

involves releasing gas from a defined area, simulating a hot spot.

10.5.1 A suggestion for simulating a hot spot is to release the verification gas 

through a soaker hose arranged in a star-shaped pattern. This simulated source should be 

situated upwind from the 1D-RPM line-of-sight at a distance approximately equal to onequarter of the length of the setup. This source should be centered with respect to the full 

length of the line-of-sight.

10.5.2 The software will determine the location of the upwind simulated source. The 

location should be determined using data collected during time periods when the measured 

wind direction is within ±45° from perpendicular to the 1D-RPM line-of-sight. A set of 12 

cycles can be considered a complete verification procedure, as long as at least half of these 

cycles satisfy the ±45° from perpendicular wind criteria. Data acquisition (see Section 
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15

11.4.4) and analysis parameters for the verification procedure should be similar to those 

used for field measurements.

10.5.3 The distance between the determined upwind source and the center of the 

simulated hot spot should be within 20 percent of the length of the 1D-RPM line-of-sight.

11.0 Procedure for Setup and Data Acquisition

11.1 Overview. High-quality PIC data are needed for input to the methodologies 

described in this protocol. A pre-study geographical site assessment should be conducted 

and an appropriate PI-ORS system must be selected. In addition, the user must choose the 

appropriate methodology – HRPM, VRPM, or 1D-RPM – depending on the purpose of the 

study.

11.1.1 The site assessment should collect information on the size, layout, and 

topography of the site, any physical barriers that may affect data collection, and the 

location of any possible off-site emission sources. This could include photographs and a 

detailed geographical site survey, which may be performed using a rangefinder, a 

theodolite, Geographical Positioning System (GPS), or similar instrument.

11.1.2 During the planning process, the seasonal prevailing wind direction expected 

during the time of the field campaign should be researched. This wind data, in conjunction 

with the suspected source location and site specific details, is used to design possible 

measurement setups.

11.2 HRPM Configuration. The HRPM configuration works best in an area without 

many topographical features, so that the PI-ORS beam paths are close to the ground. This 

enhances the ability to detect minor constituents emitted from the ground, since the emitted 

plumes may dilute significantly as they rise above ground level. Also, if the beam paths are 

elevated from the ground, the plume may drift underneath the nearest beam and be detected 

by a beam further away. This would result in a misrepresentation of the actual source 

location.

11.2.1 The PI-ORS instrument is typically placed at the origin (in the first quadrant of 

the Cartesian convention) of the rectangular area to be measured (see Figure 1). Special 

cases do arise when the scanner and the PI-ORS instruments are placed on the x-axis away

from the origin (see Note 3). For convenience, irregularly sized areas may be assumed to be 

rectangular. The maximum dimensions of the setup are limited only by the instrumentspecific capabilities (i.e., maximum path length) and the user-required peak location 

resolution.

11.2.2 A survey instrument should be used to determine the length and width of the 

study area and the angle of the x-axis from magnetic north. The size of the sampling area 

and desired peak location resolution can be used to determine the optimal number of PDCs 

and their positions inside the area to be scanned.
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11.2.3 Once the HRPM measurement area and the number of PDCs have been 

determined, the area is divided into smaller rectangular areas called pixels. The total 

number of pixels required is smaller or equal to the total number of beam paths. The pixels 

are typically numbered in the order shown in Figure 1.

PI-ORS

Instrument

Flags

PDCs

PI-ORS

Instrument

Flags

PDCs

Figure 1. Example of an HRPM Configuration Setup

11.2.4 In Figure 1, the survey area is divided into nine pixels of equal size. It should be 

noted that the survey area may be irregular in size, so that the resulting pixel grid is 

asymmetric (e.g., 2 by 4 pixels, 3 by 5 pixels, etc.). The total length of each axis should be 

divided by the number of pixels on that axis. This calculates the length of each pixel along 

each axis. Flags should be placed on each axis where each pixel boundary intersects (the 

location of the flags are indicated by the circles in Figure 1). These flags will be used as 

reference points for PDC placement.

NOTE 8 – Due to cost considerations associated with the PDCs, this protocol addresses 

HRPM setups utilizing a maximum of 16 PDCs. However, the use of a larger number of PDCs 

will increase the resolution of the peak location.

11.2.5 Figure 1 shows an example HRPM configuration setup. Each pixel will have at 

least one optical beam path that terminates within its boundaries at a PDC. This geometry 

maximizes the spread of the optical beams inside the area of emissions by passing one 

optical beam through the center of each pixel. The approximate location (in polar 

coordinates) of each PDC within each pixel is determined using trigonometric calculations.

11.2.6 Each PDC should be placed as close as possible to its calculated distance and 

angle from north. After all PDCs had been placed, a visual inspection should be made to 

ensure a clean line-of-sight to each PDC, and that each PDC is located within the 

appropriate pixel.
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11.2.6.1 A clean line-of-sight is ensured by looking at each PDC from the 

PI-ORS instrument. The PDC may need to be moved (within the appropriate pixel) to 

obtain a clear optical path.

11.2.6.2 The flags mentioned in Section 11.2.4 and illustrated in Figure 1 can be used 

as reference points for ensuring that each PDC is located within the boundaries of the 

appropriate pixel.

11.2.7 The optical beam is defined by the instrument and each PDC. Measure the 

actual pathlength and angle from magnetic north of each optical beam using a survey 

instrument.

11.2.8 It is recommended that a meteorological station is set up as part of the HRPM 

configuration. Although this data is not required for reconstructing the hot spot source 

location, wind speed and direction data may be helpful in interpreting the results.

11.2.9 Data Acquisition Parameters. Data acquisition parameters include total time 

of data collection and dwelling time per PDC. Data should be collected for a minimum of 

one hour during times when the wind meets the criteria defined in Section 4.2.2.3. 

Dwelling time per PDC is determined by 1) the specific project goals, and 2) the PI-ORS 

instrument-specific detection limits of the expected target gases. A recommended range 

for dwelling time per PDC is 10 to 60 seconds.

11.3 VRPM Configuration. The VRPM plane should be placed immediately 

downwind from the suspected emission source. The prevailing wind direction should be 

as perpendicular as possible to the vertical plane of measurement. The dimensions of the 

VRPM plane (length and height) should be maximized to capture as much of the plume

as possible.

11.3.1 The primary purpose of the VRPM methodology is to calculate the flux 

through the vertical plane. A minimum of two PDCs are necessary for this 

measurement – one of which should be on the ground defining the full length of the 

setup, and one on the vertical structure. The recommended setup for flux calculation is 

three PDCs, with one on the ground defining the full length of the setup, one at the top of 

the vertical structure, and one at approximately half of the height of the vertical structure.

NOTE 9 - Ground-level PDCs refer to those defining optical beams as close to horizontal as 

possible, given the topography of the site and the particular PI-ORS system characteristics.

11.3.2 In addition to measuring the flux, spatial information pertaining to the source 

homogeneity of the emitted plume can be obtained through the use of additional PDCs 

placed at intermediate lengths along the ground. This spatial information can be used to 

assess source homogeneity, and similar to the 1D-RPM methodology, can be used to 

determine the location of the upwind source (see Section 2.4.2). A minimum of four 

PDCs are necessary for the measurement of flux and plume spatial information, with

three placed at ground level (one defining the full length of the setup) and one on the 
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18

vertical structure. The recommended setup utilizes five to seven PDCs, with three to five

PDCs along the ground, one at the top of the vertical structure, and one at approximately 

half the height of the vertical structure. Figure 2 illustrates a typical VRPM setup using 

six PDCs, placed as follows:

a. At 1/4 of the distance of the length of the VRPM setup.

b. At 1/2 of the distance of the length of the VRPM setup.

c. At 3/4 of the distance of the length of the VRPM setup.

d. At the full length of the VRPM setup.

e. Positioned on the vertical structure at half height.

f. Positioned at the top of the vertical structure.

X

Y

Z

PI-ORS

Instrument

Fugitive Source/

Area of Interest

Mean Wind Direction

PDCs

a

b

c

d

e

f

X

Y

Z

PI-ORS

Instrument

Fugitive Source/

Area of Interest

Mean Wind Direction

PDCs

a

b

c

d

e

f

Figure 2. Example of a VRPM Configuration Setup
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19

11.3.3 The vertical structure should be located between the midpoint and far end of

the VRPM setup, as referenced from the PI-ORS instrument (see Figure 2). Instrumentspecific limitations and topography will dictate the specific placement of the vertical 

structure. For example, when collecting data under moderate to high wind conditions, it 

may be necessary to locate the vertical structure near the midpoint of the VRPM setup to 

optimize the PI-ORS instrument signal quality.

11.3.4 Prevailing Wind Direction Criteria. Ideally, the prevailing wind direction 

should be as close as possible to perpendicular to the VRPM measurement plane. This 

needs to be determined for each field study measurement configuration. For the Duke 

Forest validation study,

11 the prevailing wind direction criteria was determined to be -10o to 

+25o, where 0o is perpendicular to the vertical plane. The procedure for determining the

prevailing wind direction criteria is described in Appendix A (see Section A.2.3.2.4). 

11.3.5 Data Acquisition Parameters. Data acquisition parameters include total time of 

data collection and dwelling time per PDC. Data collection should proceed regardless of 

the wind conditions (if safety permits) until a minimum of one hour of total data is 

collected during times when the wind meets the criteria defined in Sections 4.2.2.3 and 

11.3.4. Dwelling time per PDC is determined by 1) the specific project goals, and 2) the 

PI-ORS instrument-specific detection limits of the expected target gases. A recommended 

range for dwelling time per PDC is 10 to 60 seconds. 

11.3.6 Wind Measurements. The wind data should preferably be measured at two 

heights — near the base and near the top of the vertical plane (e.g., at 2 and 10 meters). 

Temporal resolution of the wind data should not be longer than the dwelling time on each 

PDC. The dual-height measurement of wind conditions allows for interpolation and 

extrapolation of this data through the vertical plane and is important in determining if the 

wind criteria have been met. In special cases when two wind monitors are not available, 

one wind monitor can be used at mid-height (3-5 m) to represent the average wind of the 

entire vertical plane.

11.3.7 When Data Acquisition and Wind Criteria Are Not Met. Data collection may 

proceed even when the one-hour data acquisition criterion is not met. Prior knowledge on 

source location and size, and actual wind direction, should be used to assess how much of 

the plume is captured by the setup. If the assessment of plume capture is valid (see 

Appendix A for a suggested method for plume capture assessment), the data can be used 

to estimate the emission rate. Without prior knowledge of source location and size, the 

data may be insufficient to estimate the emission rate.

11.4 1D-RPM Configuration. The 1D-RPM configuration is used to profile pollutant 

concentrations along a line-of-sight downwind of a fugitive emission source. This pollutant 

concentration profile can be combined with wind data to estimate the location of an upwind 

source, when applicable. The scanning PI-ORS instrument and three or more PDCs are 

placed along a crosswind direction and PIC measurements are made.
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20

11.4.1 The 1D-RPM configuration setup is shown in Figure 3. It is necessary to 

deploy PDCs slightly off of a direct line-of-sight orientation to avoid overlap of the beam 

paths, as depicted in the figure. A minimum of three PDCs are needed, but four to six are 

recommended for this configuration. The additional PDCs provide a more detailed 

concentration profile. PDCs should be placed on the line-of-sight, with an equal distance 

between each subsequent PDC, if possible (see Figure 3).

11.4.2 Extending the 1D-RPM configuration. To extend the range of the 1D-RPM 

configuration, the PI-ORS instrument may be placed at an intermediate location in the 

setup. The PDCs should be placed in a line-of-sight extending in two opposite directions. 

For this special setup, the same recommendation and criteria detailed in Section 11.4.1 

should be followed. If there is an even number of PDCs, the PI-ORS instrument should 

be placed at approximately the center of the setup, with an equal number of PDCs on 

either side. If there is an odd number of PDCs, the PI-ORS instrument should be as close 

to the center of the setup as possible, while maintaining an equal distance between each 

PDC.

Concentration Profile

PI-ORS Instrument PI-ORS 

Instrument

100 m 200 m 300 m 400 m 500 m

Y

Conc.

Concentration Profile

PI-ORS Instrument PI-ORS 

Instrument

100 m 200 m 300 m 400 m 500 m

Y

Conc.

Figure 3. Example of a 1D-RPM Configuration Setup

11.4.3 Data Collection Criteria. Ideally, the prevailing wind direction should be 

within 45o from perpendicular to the 1D-RPM setup, where 0o is perpendicular to the 

line-of-sight.

11.4.4 Data Acquisition Parameters. Data acquisition parameters include total time 

of data collection and dwelling time per PDC. Data collection should proceed regardless 

of the wind conditions until a minimum of one hour of total data is collected during times 
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21

when the wind meets the criteria defined in Section 4.2.2.3 and 11.4.3. Dwelling time per 

PDC is determined by 1) the specific project goals, and 2) the PI-ORS instrumentspecific detection limits of the expected target gases. A recommended range for dwelling 

time per PDC is 10 to 60 seconds.

11.4.5 Wind Measurements. The wind data should be measured in at least one location 

along the line-of-sight, with additional locations providing a better representation of the 

overall site wind field. Temporal resolution of the wind data should not be longer than the 

dwelling time on each PDC.

11.4.6 When Data Acquisition and Wind Criteria Are Not Met. Data collection may 

proceed even when the one-hour data acquisition criterion (within 45o from

perpendicular) is not met. In this case, data should be collected for a total of two hours 

when the prevailing wind direction is within 70o from perpendicular to the 1D-RPM lineof-sight before reassessing the setup.

12.0 Data Analysis and Calculations

12.1 Overview. Prior to analysis, determine the moving averaging scheme for 

generation of the plume maps for any methodologies used in this protocol. Because data is 

acquired sequentially, a moving average is required to reduce errors that originate from 

temporal variability (see Appendix A, Section A2.3.2.2). Typically, a moving average with 

a grouping of three cycles is sufficient to provide stable results with a CCF larger than 0.8. 

12.2 HRPM Methodology

12.2.1 HRPM Theory. Once the PIC for all beam paths are averaged with the 

predetermined grouping of cycles for the gas species of interest, the HRPM calculations

make use of the information to reconstruct a plume map over the area of interest.

An example emission source location map is shown in Figure 4. The cross shows 

the location of the plume center from a study where propane gas was released at the 

location shown by the open circle.

12.2.2 HRPM Algorithm. Average concentrations for each pixel are obtained by 

applying an iterative algebraic deconvolution algorithm. The measured PIC, as a function 

of the field of concentration, is given by:

=∑m

k km m PIC K c (12-1)
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Figure 4. An Example Emission Source Location Map

Where:

K = a kernel matrix that incorporates the specific beam geometry with the 

pixel dimensions; 

k = the number index for the beam paths; 

m = the number index for the pixels; and 

c = the average concentration in the m

th pixel. 

12.2.2.1 Each value in the kernel matrix K is the length of the k

th beam within the mth

pixel; therefore, the matrix is specific to the beam geometry. The HRPM procedure solves 

for the average concentrations (one for each pixel) by applying non-negative least squares 

(NNLS).

23

12.2.2.2 The HRPM procedure multiplies the resulting vertical vector of averaged 

concentration by the matrix K to yield the end vector of predicted PIC data. 

12.2.2.3 The second stage of the plume reconstruction involves interpolation among 

the reconstructed pixel’s average concentration, providing a peak concentration not limited 

to the center of the pixels. A triangle-based cubic interpolation procedure (in Cartesian 

coordinates) is currently used in the HRPM procedure.

24

12.2.3 Check for Reasonableness of Surface Concentration Plot Results. Evaluate the 

data for reasonableness with the following qualitative (12.2.3.1) and quantitative (12.2.3.2) 

checks.
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12.2.3.1 If the order in which the beam paths were scanned (and the corresponding 

pixel numbering convention inside the HRPM program) are different than the order of 

PIC data input, the reconstructed plume center could fall in an incorrect pixel. Verify that 

the generated result is reasonable based on the raw PIC data.

12.2.3.2 To determine the quality of the reconstructed plume maps against the 

measured PIC data, the Concordance Correlation Factor (CCF) is used to represent the 

level of fit between measured PIC and predicted PIC. A CCF greater than 0.8 verifies that 

the surface concentration plot is a reasonable fit with the raw data (Table 2, Section 

9.2).25If the CCF is less than 0.8, the Check for Reasonableness procedures should be 

performed a second time to confirm the input data. The analysis may repeated with a 

longer average scheme, which typically increases the CCF value.

NOTE 10 — The CCF is similar to the Pearson correlation coefficient, but is adjusted to 

account for shifts in location and scale. Like the Pearson correlation (correlation coefficient, ‘R’), 

CCF values are bounded between -1 and 1, yet the CCF can never exceed the absolute value of 

the Pearson correlation factor. For example, the CCF will be equal to the Pearson correlation 

when the linear regression line intercepts the ordinate at 0, its slope equals 1. Its value will be 

lower than the Pearson correlation when the above conditions are not met.14,26 A detailed 

description of the procedure for calculating the CCF is included in Section 12.3.3.3.

12.2.4 Hot spot location determination The HRPM procedure provides a plume map 

and calculates the location of the peak concentrations. It is for the user to interpret this 

information and site constraints, such as obstructions or terrain complexities, for the 

determination of the actual location of the hot spot. 

12.3 VRPM Methodology

12.3.1 VRPM Theory and Algorithms. Once the PIC for all beam paths are averaged 

with the predetermined grouping of cycles for the gas species of interest, the VRPM 

calculations make use of the information to reconstruct a plume map in the vertical

downwind plane. Two different beam configurations of the VRPM methodology are 

recommended: the five-beam (or more) and the three-beam VRPM configuration. Figure 2

illustrates the setup for these two VRPM beam configurations. In the five-beam (or more) 

configuration, the ORS instrument sequentially scans over five PDCs. Three PDCs are 

along the ground-level crosswind direction (beams a, b, and c in Figure 2), and the other 

two are elevated on a vertical structure (beams e and f in Figure 2). The additional beam (d) 

in Figure 2 is for 6-beam configuration, which provides better spatial definition of the 

plume in the crosswind direction. In the three-beam configuration, the ORS instrument 

sequentially scans over three PDCs. Only one beam is along the ground level (beam c or d 

in Figure 2) and the other two are elevated on a vertical structure (beams e and f in Figure 

2). PIC data are collected over time, completing many cycles through the defined beams of 

each configuration.

12.3.1.1 A two-phase smooth basis function minimization (SBFM) approach is applied 

where there are three or more beams along the ground level (5-beam or more 
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24

configuration). In the two-phase SBFM approach, a one-dimensional SBFM reconstruction 

procedure is first applied in order to reconstruct the smoothed ground level and crosswind 

concentration profile. The reconstructed parameters are then substituted into the bivariate 

Gaussian function when applying a two-dimensional SBFM procedure.

12.3.1.1.1 A one-dimensional SBFM reconstruction is applied to the ground level 

segmented beam paths (Figure 2) of the same beam geometry to find the cross wind 

concentration profile. A univariate Gaussian function is fitted to measured PIC groundlevel values. 

12.3.1.1.2 The error function for the minimization procedure is the Sum of Squared 

Errors (SSE) function and is defined in the one-dimensional SBFM approach as follows: 

2

0

2

2

1

exp

2

( , , ) ∑ ∑ ∫























































 −

= − −

i j

r

j

y

j

y

j

y

j

i

j

y jj y

i

dr

B m r

SSE B m PIC

πσ σ

σ (12-2)

Where:

B = equal to the area under the one-dimensional Gaussian distribution 

(integrated concentration);

ri = the pathlength of the i

th beam;

my = the mean (peak location);

σy = the standard deviation of the j

th Gaussian function; and

PICi = the measured PIC value of the i

th path.

12.3.1.1.3 The SSE function is minimized using the Simplex minimization procedure 

to solve for the unknown parameters (i.e., B, my, σy) .

27

12.3.1.1.4 When there are more than three beams at the ground level, two Gaussian 

functions are fitted to retrieve skewed and sometimes bi-modal concentration profiles. This 

is the reason for the index j in Equation 12-2.

12.3.1.1.5 Once the one-dimensional phase is completed, the two-dimensional phase 

of the two-phase process is applied. To derive the bivariate Gaussian function used in the 

second phase, it is convenient to express the generic bivariate function G in polar 

coordinates r and θ:

( )

( )( ) ( ) G r

A r m r m r m r m

y z

y

y

y z

y z

z

z

( , ) exp

( cos ) cos sin sin

θ

πσ σ ρ ρ

θ

σ

ρ θ θ

σ σ

θ

σ

=

−

−

−

⋅ −

−

⋅ − ⋅ −

+

⋅ −



































2 1 

1

2 1

2

12

2

12

2

2

2

12

2

2

(12-3)
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25

12.3.1.1.6 The bivariate Gaussian has six unknown independent parameters:

A = normalizing coefficient which adjusts for the peak value of the 

bivariate surface;

ρ12 = correlation coefficient which defines the direction of the

distribution-independent variations in relation to the Cartesian 

directions y and z (ρ12=0 means that the distribution variations 

overlap the Cartesian coordinates);

my and mz = peak locations in Cartesian coordinates; and

σy and σz = standard deviations in Cartesian coordinates. 

12.3.1.1.7 Six independent beam paths are sufficient to determine one bivariate 

Gaussian that has six independent unknown parameters.

12.3.1.1.8 Some reasonable assumptions are made when applying the VRPM 

methodology to this problem, to reduce the number of unknown parameters. The first is 

setting the correlation parameter ρ12 equal to zero. This assumes that the reconstructed 

bivariate Gaussian is limited only to changes in the vertical and crosswind directions. 

Secondly, when ground level emissions are known to exist, the ground level PIC is 

expected to be the largest of the vertical beams. Therefore, the peak location in the vertical 

direction can be fixed to the ground level. 

In the above ground-level scenario, Equation 12-3 reduces into Equation 12-4:

( )































 ⋅

+

⋅ −

= − 2

2

2

2

( cos ) sin

2

1

exp

2

( , )

y z

y

y z

A r m r

G r

σ

θ

σ

θ

πσ σ

θ (12-4)

12.3.1.1.9 The standard deviation and peak location retrieved in the one-dimensional 

SBFM procedure are substituted in Equation 12-4 to yield:

( )































 ⋅

+

⋅ −

= −

−

−

−

2

2

2

1

2

1

1

( cos ) sin

2

1

exp

2

( , )

y D z

y D

y D z

z

A r m r

G A

σ

θ

σ

θ

πσ σ

σ (12-5)

Where:

σy-1D = standard deviation along the crosswind direction (found in the onedimensional SBFM procedure);

my-1D = peak location along the crosswind direction (found in the onedimensional SBFM procedure);
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26

12.3.1.1.10 A and σz are unknown parameters to be retrieved in the second phase of 

the fitting procedure.

12.3.1.1.11 An error function (SSE) for minimization is defined for this phase in a 

similar manner. The SSE function for the second phase is defined as:

( ) ∑ ∫ 















= −

i

r

z i i i z

i

SSE A PIC G r A dr

2

0

,σ ( ,θ , ,σ ) (12-6)

Where:

PICi = the measured path-integrated concentration value of the ith path.

12.3.1.1.12 The SSE function is minimized using the Simplex method to solve for 

the two unknown parameters. 

12.3.1.2 When the VRPM configuration consists only of three beam paths—one at 

the ground level and the other two elevated—the one-dimensional phase can be skipped, 

assuming that the plume is very wide. In this scenario, peak location can be arbitrarily 

assigned to be in the middle of the configuration. Therefore, the three-beam VRPM 

configuration is most suitable for area sources (where no localized hot spot is expected) 

or for sources with a series of point and fugitive sources that are known to be distributed 

across the upwind area. In this case, the bivariate Gaussian has the same two unknown 

parameters as in the second phase (Equations 12-5 and 12-6), but information about the 

plume width or location is not known. The standard deviation in the crosswind direction 

is typically assumed to be about 10 times that of the ground level beam path (length of 

vertical plane). If r1 represents the length of the vertical plane, the bivariate Gaussian 

would be as follows:

( )

( )



























 ⋅

+

⋅ −

= − 2

2

2

1

2

2 1

1

1

sin

10

( cos )

2

1

exp

2 (10 )

( , )

z z

z

r

r

r r

r

A

G A

σ

θ θ

π σ

σ (12-7)

This process is for determining the vertical gradient in concentration. It allows an 

accurate integration of concentrations across the vertical plane as the long-beam groundlevel PIC provides a direct integration of concentration at the lowest level.

12.3.2 Once the parameters of the function are found for a specific run, the VRPM 

procedure calculates the concentration values for every square elementary unit in a vertical 

plane. Then, the VRPM procedure integrates the values, incorporating wind speed data at 

each height level to compute the flux. The concentration values are converted from parts 

per million by volume (ppmv) to grams per cubic meter (g/m3), taking into consideration 

the molecular weight of the target gas. This enables the direct calculation of the flux in 

grams per second (g/s), using wind speed data in meters per second (m/s).
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27

12.3.3 Check for Reasonableness of the Calculated Flux. Evaluate the data for 

reasonableness with the following qualitative (12.3.2.1) and quantitative (12.3.2.2) checks.

12.3.3.1 Verify that the generated result is reasonable based on the raw PIC data.

12.3.3.2 To determine the quality of the reconstructed plume maps against the 

measured PIC data, the CCF is used to represent the level of fit between measured PIC 

and predicted PIC (see Note 10). 

12.3.3.3 As described in earlier studies,

7

the Concordance Correlation Factor (CCF) 

was used to represent the level of fit for the reconstruction in the path-integrated domain 

(predicted versus measured PIC).

CCF is defined as the product of two components:

CCF = rA (12-8)

Where: 

r = the Pearson correlation coefficient;

A = a correction factor for the shift in population and location.

12.3.3.4 This shift is a function of the relationship between the averages and standard 

deviations of the measured and predicted PIC vectors:

1

2

2

1

−























































 −

= + +

P P M

M

M

P

PIC PIC

P M

PIC

PIC

PIC

PIC PIC PIC A

σ σ σ

σ

σ

σ

(12-9)

Where: 

PICP

σ = standard deviation of the predicted PIC vector;

PICM

σ = standard deviation of the measured PIC vector;

PICP = the mean of the predicted PIC vector; and 

PICM =the mean of the measured PIC vector.

12.3.3.5 The Pearson correlation coefficient is a good indicator of the quality of fit to 

the Gaussian mathematical function. In this procedure, typically an r close to 1 will be 

followed by an A very close to 1. This means that the averages and standard deviations in 

the two concentration vectors are very similar and the mass is conserved (good flux 

value). However, when a poor CCF is reported (CCF<0.80) at the end of the fitting 
FINAL ORS Protocol

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28

procedure it does not directly mean that the mass is not conserved. It could be a case 

where only a poor fit to the Gaussian function occurred if the correction factor A was still 

very close to 1 (A>0.90). However, when both r and A are low one can assume that the 

flux calculation is inaccurate.

12.3.3.6 A CCF greater than 0.80 indicates that the surface concentration plot is a 

reasonable fit with the measured PIC (Table 2, Section 9.2).25If the CCF is less than 0.80,

but A>0.90, this is still a reasonable indication of a good mass equivalent surface 

concentration plot. If the CCF is less than 0.80, but A<0.90, then the Check for 

reasonableness procedures (Section 12.3.3) should be performed a second time to 

confirm the input data. The analysis may be repeated with a longer average scheme,

which typically increases the CCF value. 

12.4 1D-RPM Methodology

12.4.1 1D-RPM Theory and Algorithms. Once the PIC for all beam paths are 

averaged with the predetermined grouping of cycles for the gas species of interest, the

1D-RPM calculations make use of the information to reconstruct a plume concentration 

profile along the measurement line-of-sight. Similar to the case of VRPM (which 

assumes a bivariate Gaussian plume mass in two dimensions), the 1D-RPM calculations

utilize the one-dimensional (1D) SBFM to reconstruct a mass-equivalent plume 

concentration profile along the line-of-sight measurement. The plume crosswind peak 

location, coupled with the average wind direction data, can provide an idea of the 

emission source location and configuration.

12.4.2 The 1D-RPM procedure fits a univariate Gaussian function to measured PIC 

ground-level values. The error function for the minimization procedure is the SSE 

function, and is defined in the 1D-SBFM approach as follows:

2

0

2

2

1

exp

2

( , , ) ∑ ∑ ∫



















































 −

= − −

i

r

y

y

j y

j

j y y i

i

j

j

j

j j

dr

B m r

SSE B m PIC

πσ σ

σ (12-10)

12.4.3 The unknown independent parameters for the 1D-SPFM Gaussian are:

B = the area under the Gaussian distribution;

ri = the path length of the ith beam;

my = the mean (peak location);

σy = standard deviation of the jth Gaussian function; and

PICi = the measured path-integrated concentration value of the ith path.
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29

12.4.4 Check for Reasonableness of the Concentration Profile. Evaluate the data for 

reasonableness with the following qualitative (12.4.4.1) and quantitative (12.4.4.2) checks.

12.4.4.1 Verify that the generated result is reasonable based on the raw PIC data.

12.4.4.2 To determine the quality of the reconstructed plume maps against the 

measured PIC data, the CCF is used to represent the level of fit between measured PIC 

and predicted PIC (see Note 10). A CCF greater than 0.8 verifies that the surface 

concentration plot is a reasonable fit with the raw data (Table 2, Section 9.2).25If the CCF 

is less than 0.8, the Check for Reasonableness procedures should be performed a second

time to confirm the input data. The analysis may be repeated with a longer average 

scheme, which typically increases the CCF value. 

NOTE 11 • The 1D-RPM methodology above explains a single Gaussian massequivalent plume. It is possible to fit multiple Gaussian plume profiles when more than three 

PDC are used [e.g., a combination of two Gaussian profiles with four or more PDC as explained 

in Hashmonay and Yost (1999)2]. This multiple Gaussian approach can provide multiple mode or 

skewed concentration profiles. Also this can be extended for VRPM configurations where four or 

more ground-level PDC are used to fit bi-modal or skewed bivariate Gaussian profiles. This may 

improve the accuracy of flux measurements, as it always provides higher CCF values.

12.4.5 The 1D-RPM procedure reconstructs the plume profile along the measurement 

line-of-site and notes the peak location. Over time, as the wind direction fluctuates, 

different peak locations are reconstructed from the PIC measurements as illustrated in 

Figure 5. Each time a peak location is noted, a source projection line is drawn for each 

peak location. This is done by calculating a line equation through the peak location, with 

the same orientation as the averaged wind direction for the same measurement time 

interval. Ideally, for a stationary point source, all source projection lines drawn over time 

should intersect at a point upwind of the measurement line in the vicinity of the real 

emission source location. Calculating the density of lines per unit area upwind from the 

measurement plane, the most likely location of the source can be estimated as the region 

of the maximal line density.

13.0 Methodology Performance

13.1 Data Quality Objectives. A verification gas release may be conducted during a 

field study to verify that the instrument is performing well, as long as the PI-ORS 

instrument is capable of detecting multiple compounds. Note the beginning and end of the 

release and the amount released.

13.1.1 For a verification gas release using the HRPM methodology, a plume center 

location error of ±10 percent of the diagonal distance of the entire area scanned is 

considered a good indicator of quality.
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30

13.1.2 For the weight of the verification gas release retrieved using the VRPM 

methodology, an error of ±25 percent of the total actual release for the duration of the 

experiment is considered a good indicator of quality.

13.1.3 For the location of the verification gas release using the 1D-RPM 

methodology, an error of ±20 percent of the longest beam path along the line-of-sight is 

considered a good indicator of quality.

Figure 5. An Example of a 1D-RPM Fenceline Monitoring Setup

14.0 Pollution Prevention

A discussion of pollution prevention issues is not necessary, as they are 

instrument specific and not directly associated with application of the methodologies

described in this protocol.

Source Location

Reflectors

PI-ORS

Instrument

Met Station

Wind

Direction

Industrial Complex

1 2 3

PDC
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31

15.0 Waste Management

Because no actual samples are collected with PI-ORS instrumentation, there are 

no waste management issues.

16.0 References

1 Hashmonay, R. A.; Yost, M. G. Innovative Approach for Estimating Gaseous 

Fugitive Fluxes Using Computed Tomography and Remote Optical Sensing 

Techniques. J. Air & Waste Manage. Assoc. 1999, 49, 966.

2 Hashmonay, Ram A.; Yost, Michael G. Localizing Gaseous Fugitive Emission 

Sources by Combining Real-Time Remote Optical Sensing and Wind Data. J. Air 

& Waste Manage. Assoc. 1999, 49, 1374-1379.

3 Hashmonay, R. A.; Yost, M. G.; Mamane, Y.; Benayahu, Y. Emission Rate 

Apportionment from Fugitive Sources Using Open-Path FTIR and Mathematical 

Inversion. Atmos. Environ. 1999, 33, 735-743.

4 Hashmonay, R. A.; Yost, M. G.; Wu, C. F. Computed Tomography of Air Pollutants 

Using Radial Scanning Path-Integrated Optical Remote Sensing. Atmos. Environ. 

1999, 33(2), 267.

5

Price, P. N. Pollutant Tomography Using Integrated Concentration Data from NonIntersecting Optical Paths. Atmos. Environ. 1999, 33(2), 275-280.

6 Wu, C. F.; Yost, M. G.; Hashmonay, R. A.; Park, D. Y. Experimental Evaluation of a 

Radial Beam Geometry for Mapping Air Pollutants Using Optical Remote 

Sensing and Computed Tomography. Atmos. Environ. 1999, 33(28), 4709-4716.

7 Hashmonay, R.A.; Natschke, D. F.; Wagoner, K.; Harris, D. B.; Thompson, E. L.; 

Yost, M. G. Field Evaluation of a Method for Estimating Gaseous Fluxes from 

Area Sources Using Open-Path Fourier Transform Infrared. Environ. Sci. 

Technol. 2001, 35, 2309-2313.

8 Yost, M. G.; Hashmonay, R. Mapping Air Contaminants Using Path-Integrated 

Optical Remote Sensing with a Non-Overlapping Variable Path Length Beam 

Geometry. U.S. Patent 6,542,242 B1, 2003.

9 Modrak, M. T.; Hashmonay, R. A.; Keagan [Kagann], R. Measurement of Fugitive 

Emissions at a Region I Landfill; U.S. Environmental Protection Agency, 

Research and Development, EPA-600/R-04-001, January 2004.

10

Thoma, E. D.; Shores, R. C.; Thompson, E. L.; Harris, D. B.; Thornloe, S. A.; Varma,

R. M.; Hashmonay, R. A.; Modrak, M. T.; Natschke, D. F.; Gamble, H.A. Open 
FINAL ORS Protocol

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32

Path Tunable Diode Laser Absorption Spectroscopy for Acquisition of Fugitive 

Emission Flux Data. J. Air & Waste Manage. Assoc. 2005, 55, 658-668.

11 Hashmonay, Ram A.; Varma, Ravi M.; Modrak, Mark T.; Kagann, Robert H.; Egler,

Kim; Sullivan, Patrick D.; Segall, Robin R. Validation of Vertical Radial Plume 

Mapping Methodology for Estimating Gaseous Emission Rates from Area 

Sources. J. Air & Waste Manage. Assoc. Submitted in 2006.

12 Huang, Zhonghua; Wang, Junde; Li, Yan. Mapping Spacial Tracer Gases 

Concentration Profiles on a Two-Dimensional Plane by OP-FTIR Remote 

Sensing. Instrumentation Sci. & Technol. 2003, 31(1), 23-32.

13

Scotto, R. L.; Minnich, T. R.; Leo, M.R. A Method for Estimating VOC Emission 

Rates from Area Sources Using Remote Optical Sensing. In Proceedings of the 

EPA/A&WMA International Symposium on the Measurement of Toxic and 

Related Air Pollution, Raleigh, NC, 1991, 698.

14

Piccot, S. D.; Masemore, S. S.; Lewis-Bevan, W.; Ringler, E. S.; Harris, D. B. Field 

Assessment of a New Method for Estimating Emission Rates from Volume 

Sources Using Open-Path FTIR. J. Air & Waste Management Assoc. 1996, 46, 

159.

15

Simpson, O. A.; Kagann, R. H. Measurements of Emissions at a Chemical Waste 

Water Site with an Open Path Remote Fourier Transform Interferometer. In 

Proceedings of the EPA/ A&WMA International Symposium on the Measurement 

of Toxic and Related Air Pollution, Raleigh, NC, 1990, 937.

16 Weber, Konradin; Lamp, Torsten; Schulte, Klaus;Weidemann, Johannes; van Haren,

Günther; Gärtner, Andrea; Bröker, Günter. Open-Path FTIR-Measurements of 

Methane as a Tracer Gas for Waste Site Emissions at a Waste Site in Germany. 

Proceedings of the A&WMA 89th Annual Meeting & Exhibition, Pittsburgh, PA, 

1996, 11p.

17 Heise,Michael; Müller, Uwe; Gärtner, Andrea; Hölscher; Norbert. Improved 

Chemometric Strategies for Quantitative FTIR Spectral Analysis and Applications 

in Atmospheric Open-Path Monitoring. Field Anal. Chem. & Technol. 2001, 

5(1-2), 13-28.

18 Schäfer, Klaus; Steinecke, Ina; Emeis, Stefan; Stockhause, Martina; Sussmann, Ralf; 

Trickl, Thomas ; Reitebuch, Oliver; Hoechstetter, Karsten; Sedlmaier, Achim;

Depta, Georg; Gronauer, Andreas; Seedorf, Jens; Hartung, Jörg. Inverse 

Modelling on the Basis of Remote Sensing to Determine Emission Rates. 

Meteorol. Zeitschrift, 1998, N.F. 7, 7-10 (Februar).
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33

19 Compendium Method TO-16: Long-Path Open-Path Fourier Transform Infrared 

Monitoring of Atmospheric Gases; U.S. Environmental Protection Agency,

Center for Environmental Research Information-Office of Research and 

Development: Cincinnati, Ohio, January 1999. 

20

American Society for Testing and Materials (ASTM) Standard Practice E1982-98, 

Standard Practice for Open-Path Fourier Transform Infrared (OP/FT-IR) 

Monitoring of Gases and Vapors in Air; March 1999.

21

American Society for Testing and Materials (ASTM) Standard Guide E1865-97 

(Reapproved 2002), Standard Guide for Open-Path Fourier Transform Infrared 

(OP/FT-IR) Monitoring of Gases and Vapors in Air; July 1997.

22 VDI 4211, Part 1. Remote Sensing, Atmospheric Measurements Near Ground with 

FTIR Spectroscopy, Measurements of Gaseous Emissions and Immissions. Beuth 

Verlag Berlin, 2000.

23

Lawson, Charles L.; Janson, Richard J. Solving Least Squares Problems; Society for 

Industrial and Applied Mathematics: Philadelphia, 1995; Chapter 23, pp 158-165.

24 Barber, C. B., D.P. Dobkin, and H.T. Huhdanpaa, "The Quickhull Algorithm for 

Convex Hulls," ACM Transactions on Mathematical Software, Vol. 22, No. 4, 

Dec. 1996, p. 469-483.

25 Lin, L. I-K. A Concordance Correlation Coefficient to Evaluate Reproducibility.

Biometrics. 1989, 45. 255-68.

26 Byer, R. L.; Shepp, L. A. Two-Dimensional Remote Air-Pollution Monitoring Via 

Tomography. Opt. Lett. 1979, 4(3), 75-77.

27

Press, W. H.; Teukolsky, S. A.; Vetterling, W. T.; Flannery, B.P. Numerical Recipes 

in FORTRAN, 2nd ed.; Cambridge University Press: Cambridge, MA, 1992.
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Appendix A

Example Application of Methodologies Described in this Protocol

using OP-FTIR

The methodologies described in this protocol are independent of the particular 

PI-ORS instrument. This appendix has been included to illustrate the application of the

methodologies described in this protocol during two separate experiments using a 

scanning open-path FTIR (OP-FTIR).A1-4The methodologies described in this protocol

have been utilized for several other environmental monitoring programs.A5-7

A1.0 Examples of DQI Goals and Internal QC.

The Data Quality Indicator (DQI) goals for the OP-FTIR instrument are shown in 

Table A.1 The DQI goals were developed based on analysis of the historical data 

obtained in similar studies and available guidance documents. 

Table A.1 Data Quality Indicators (DQIs) for OP-FTIR

Measurement Parameter Analysis Method Accuracy Precision % Complete

PIC Determination OP-FTIR: Nitrous Oxide Conc. ±25%/15%/10%a± 10% 90%

Mid-IR absorbance OP-FTIR: Spectra Quality Acceptableb NA 100%

a The accuracy acceptance criterion is ±25 percent for pathlengths of less than 50 m, ±15 percent for pathlengths between 

50 and 100 m, and ±10 percent for pathlengths greater than 100 m.

b Spectral quality must meet minimal quality (refer to instrumentation manuals and EPA methods for instrument-specific 

spectral quality criteria).

A1.1 Procedures for Evaluating OP-FTIR DQIs. The development and determination 

of DQIs for open-path measurements is an ongoing process. The following section details

the procedure for assessing the OP-FTIR DQI goals presented in Table A.1.

A1.1.1 PIC Determination. The accuracy and precision of the absorbance data may 

be verified by analyzing measured atmospheric nitrous oxide concentrations over time. 

This test is valid only if the background spectrum is void of nitrous oxide, and nitrous 

oxide is not used in the verification gas release. For the duration of the study, the calculated 

concentration results for nitrous oxide should be comparable to the natural ambient 

atmosphere level of 315 ppb ±25 percent for path lengths less than 50 meters, 315 ppb ±15

percent for path lengths between 50 and 100 meters, and 315 ppb ±10 percent for path

lengths greater than 100.A8 Refer to Section 11.3.1.1 of ASTM Standard Practice E 

1982-98 for more information on this procedure.A2

A1.1.2 Mid-IR Absorbance. The quality of the mid-IR absorbance data can be 

assessed by performing several qualitative and quantitative checks. These checks include 

assessing instrument noise, detector nonlinearity, detector saturation, and instrument 
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35

response. These checks were developed based on ASTM Standard Practice E 1982-98. 

Additional details on how to perform these checks can be found in the EPA document

entitled, ECPB Optical Remote Sensing Facility Manual.

A9

A1.2 Internal Quality Control. Traditional quality control (QC) samples are not 

applicable to OP-FTIR experiments. Instead, the analyses of IR-active ambient gases 

having relatively constant values are included in the quantification process. Examples 

include nitrous oxide and methane, which are found at relatively constant concentrations of 

315 ppb and 1.7 ppm as global backgrounds, respectively. These must be used with 

caution, because a particular measurement area may prove to be a source of these gases. 

Methane, for example, is often emitted from hog waste lagoons and landfills.

A1.2.1 Generation of a Background Spectrum. As described in EPA Compendium 

Method TO-16 (1999),A2, A3 the generation of a background spectrum, more precisely the I0

spectrum, is best accomplished synthetically. The best approach to this depends upon the 

software being used for processing the data. Many commercially available software 

systems are compatible with the data format used by OP-FTIR instruments. However, all of 

the available software options require analyst input; therefore, there is some subjectivity 

involved in the process. 

A1.2.2 Data Integrity. Spectra are analyzed for peaks of common atmospheric 

constituents, such as water vapor, carbon dioxide, and methane. If these peaks are located 

outside of their expected spectral region or exhibit any other abnormal characteristics, a 

spectroscopist should manually examine a select portion of the original data to determine 

the reason for these deviations and/or the usability of the collected data.

A2.0 RPM Example using the HRPM and VRPM Methodologies

A2.1 Introduction. During the Fall of 2002 and Spring of 2003, the methodologies 

described in this protocol was evaluated using the controlled release of verification gases 

and a scanning monostatic OP-FTIR instrument. The experiments were performed at the 

Duke Forest Facility of Duke University, located in Chapel Hill, North Carolina. A nearly 

flat and square area of 14,400 m2 was selected for the study. The verification gases released 

during the experiments included ethylene and acetylene. This example briefly describes the 

preliminary results obtained from this controlled demonstration study using the HRPM and 

VRPM methodologies.

A2.2 Experimental Setup. This study was supported by the Environmental Security 

Technology Certification Program (ESTCP) of the Department of Defense (DoD) and 

audited by the Emissions Monitoring Center (EMC) of the EPA.

In this study, an OP-FTIR mounted on a scanner and an array of mirrors (PDC) 

formed multiple, non-intercepting beam paths. Nine mirrors were used for the HRPM 

experiment, and five were used for the VRPM experiment. The OP-FTIR was scanned 

sequentially from mirror to mirror, acquiring spectra from each beam path. The OP-FTIR 
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36

dwelling time on each mirror was 30 seconds for the HRPM experiment and 60 seconds 

for the VRPM experiment.

A2.3 Results and Discussion. PIC data were derived from the collected spectra, and 

wind data were time-synchronized with the spectral data and averaged for the 

corresponding measurement cycle. Following this, the PIC data were sorted according to 

mirror number, and the expanded data matrix (see Table A.2) was then used as input to the 

software developed by ARCADIS in Research Triangle Park, NC. In the case of the HRPM 

methodology, the software reconstructs the surface concentration contour map. In the case 

of the VRPM methodology, the software provides spatial information on the homogeneity 

of the plume, and calculates the emission flux through the configuration.

A2.3.1 HRPM Results. Several verification gases were released at random locations 

and spectral data were collected by sequentially scanning the OP-FTIR from mirror to 

mirror. This spectral data were used to derive PIC data along each beam path, which were 

then input into the RPM software to construct a surface concentration contour map. The hot 

spot location was determined by the area of highest concentrations in the contour map. This

location was then compared to the actual release location of the verification gas.

For this example, acetylene was released and data were collected for 18 cycles. 

Figure A.1 shows the concentration contour map constructed by averaging PIC data from

all 18 cycles. The open circle indicates the actual release location, and the closed circle 

indicates the hot spot location determined by the software. The dislocation distance 

(distance between the actual and determined release location) is shown with a doubleheaded arrow. In this case, the dislocation distance was 17 meters. Table A.2 presents the 

data matrix used to construct Figure A.1.
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Figure A.1 Actual Versus Determined Source Location for the Acetylene Release

Table A.2 Data Matrix Used to Construct Figure A.1

Pixel no. 1 2 3 4 5 6 7 8 9

Physical Beam 

Path Length (m) 68.4 102.6 148.9 103.1 137.2 169.6 149.1 171.2 178.5

Cycle 1 (ppm-m) 0.0 0.0 0.0 0.0 0.0 0.0 11.6 23.2 0.0

Cycle 2 (ppm-m) 0.0 1.3 0.0 0.0 0.0 0.0 0.0 32.6 0.0

Cycle 3 (ppm-m) 0.0 0.0 0.0 0.0 0.0 0.0 0.0 5.2 0.0

Cycle 4 (ppm-m) 0.0 1.1 0.0 0.0 0.0 0.0 8.5 6.6 0.0

Cycle 5 (ppm-m) 1.0 1.0 0.0 0.0 0.0 2.3 49.6 34.3 0.0

Cycle 6 (ppm-m) 0.0 0.0 0.0 0.0 0.0 2.1 6.5 7.5 0.0

Cycle 7 (ppm-m) 0.0 0.0 0.0 0.0 1.4 0.0 8.0 11.7 0.0

Cycle 8 (ppm-m) 0.0 0.0 0.0 4.0 0.0 0.0 55.6 62.8 1.8

Cycle 9 (ppm-m) 0.0 0.0 0.0 0.0 0.0 0.0 8.2 4.2 0.0

Cycle 10 (ppm-m) 1.1 0.5 0.0 0.0 1.1 0.0 8.0 73.0 0.0

Cycle 11 (ppm-m) 0.0 0.0 0.0 0.0 0.0 0.0 28.3 0.0 0.0

Cycle 12 (ppm-m) 0.0 0.0 0.0 0.0 0.0 0.0 28.8 91.9 0.0

Cycle 13 (ppm-m) 0.0 0.0 0.0 0.0 0.0 2.4 49.1 10.1 3.2

Cycle 14 (ppm-m) 0.0 0.0 0.0 0.0 0.0 4.4 25.5 119.1 2.1

Cycle 15 (ppm-m) 0.8 0.0 1.3 0.0 0.0 1.9 63.0 192.0 2.8

Cycle 16 (ppm-m) 0.0 0.0 0.0 4.1 0.0 2.7 78.0 12.4 0.0

Cycle 17 (ppm-m) 1.1 1.0 0.0 49.6 0.0 0.0 303.0 247.2 0.0

Cycle 18 (ppm-m) 37.9 0.0 0.0 120.7 52.4 13.4 169.1 199.6 98.7

18-Cycle Average 

(ppm-m) 2.33 0.27 0.07 9.91 3.05 1.62 50.04 62.97 6.03
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A2.3.2 VRPM Results. Several verification gases were released in an “H” pattern 

upwind of the VRPM configuration to simulate a small area source in Duke Forest (see 

Figure A.2).A9The verification gas cylinders were weighed before and after each release to 

calculate the actual release rate (in g/s). Spectral data were collected by sequentially 

scanning the OP-FTIR from mirror to mirror. This data were used to derive PIC data along 

each beam path, which were used as input to the VRPM algorithm to determine a planeintegrated concentration. Wind data were simultaneously collected at two heights (2 and 10 

m), and were incorporated with the plane-integrated concentration data to calculate the 

emission flux through the VRPM configuration.

Figure A.2 Schematic of the VRPM Configuration Used for the Ethylene Release

For this example, ethylene was released and data were collected for 12 cycles. 

Figure A.3 shows the reconstructed mass-equivalent plume map constructed by averaging 

PIC data from all 12 cycles. A total of 1.0 lb of ethylene was released over a period of 68 

minutes, which resulted in an average release rate of 0.11 g/s. The average calculated 

emission flux was 0.10 g/s. Table A.3 presents the data matrix used to construct Figure 

A.3.

X

Y

Z

15 m

30 m

30 m

90 m

40 m

50 m

90 m

140 m

7 m

13 m

Scanning 

OP-FTIR

Mean Wind Direction

Retroreflectors
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Figure A.3 Flux Measurement for Ethylene

Table A.3 Data Matrix Used to Construct Figure A.3

Beam Path no. 1 2 3 4 5

Physical Beam 

Path Length (m) 52.1 90.1 137 141.5 141.9

WS 

(m/s)

WD from 

Normal

(deg)

Cycle 1 (ppm-m) 2.7 13.4 17.8 3.8 5.1 2.7 5

Cycle 2 (ppm-m) 6.4 28.0 19.4 9.0 5.4 2.6 1

Cycle 3 (ppm-m) 4.5 23.4 23.1 8.8 7.9 2.1 0

Cycle 4 (ppm-m) 2.8 28.3 20.4 10.0 7.3 2.1 14

Cycle 5 (ppm-m) 5.0 19.8 34.7 4.2 5.3 2.9 13

Cycle 6 (ppm-m) 2.9 27.9 14.4 11.1 7.8 2.9 3

Cycle 7 (ppm-m) 10.8 14.1 28.5 4.7 7.9 3.0 -11

Cycle 8 (ppm-m) 2.7 10.3 49.1 4.9 5.8 2.3 18

Cycle 9 (ppm-m) 2.7 23.1 25.8 23.3 7.1 1.8 -2

Cycle 10 (ppm-m) 6.7 11.6 18.7 4.5 11.1 1.7 -15

Cycle 11 (ppm-m) 14.4 20.2 36.0 15.7 7.0 2.0 -8

Cycle 12 (ppm-m) 2.6 3.3 30.9 8.3 6.7 2.2 14

12-Cycle Average (ppm-m) 5.4 18.6 26.6 9.0 7.0 2.35 3

BOLD values represent one-half the minimum detection limit.
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A2.3.2.1 Average wind speed and direction data for each measurement cycle is 

shown in Table A.3. Wind measurements were interpolated every 2 meters between the 

2- and 10-meter heights. The average wind data for each cycle at 4 meters above the 

ground are shown. The wind direction is measured clockwise from an axis perpendicular 

to the VRPM configuration. In this convention, 0o is perpendicular to the vertical plane.

A2.3.2.2 A moving average is used in the calculation of average values to show 

temporal variability in the measurements. A moving average involves averaging values 

from several different consecutive cycles. For example, a data set may be reported using 

a moving average with a group size of 4, where values from cycles 1 to 4, and 2 to 5 are 

averaged together to show any variability in the values.

The example in this appendix explores the dependence of the results on the group size 

of the moving average, and is illustrated in Figure A.4. To assess the accuracy of the 

reconstruction for each moving average group, the CCF is computed. It is apparent in 

Figure A.4 that as the group size of the moving averages increase, the standard deviation 

decreases (smaller error bar). The CCF value increases for larger group sizes of moving 

averages (indicating a better fit for the measured data), but levels off at a group size of 

three. A moving average group of three is recommended for the VRPM methodology. In 

some conditions, it may not be advisable to use a larger group size for the moving 

average.

CCF vs grouping size for moving averages 

0.86

0.88

0.9

0.92

0.94

0.96

0.98

1

0 2 4 6

Group size

CCF

Figure A.4 Dependence of CCF vs. Moving Average Group Size

A2.3.2.3 A time plot of the flux calculation for the ethylene verification release, 

using a moving average with a group size of three, is shown in Figure A.5. The dashed

horizontal line corresponds to the actual mass released; the dashed plot indicates the 

measured wind direction from perpendicular to the VRPM configuration; and the solid 
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plot indicates the calculated emission flux values. The corresponding data are listed in 

Table A.4.

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

1 2 3 4 5 6 7 8 9 10

Cycle Number

Flux [g/s]

-80.0

-60.0

-40.0

-20.0

0.0

20.0

40.0

60.0

80.0

Wind Direction from Normal [degrees]

Flux WD

Figure A.5 Time Series of Ethylene Emission Flux Estimation

(• • • Indicates the actual release rate)

Table A.4 Moving Average of Three Ethylene Emission Data Points for 

Figure A.5

Group CCF Flux(g/s) WS(m/s) WD(deg.)

1 0.95 0.08 2.2 2

2 0.96 0.1 2.1 3

3 0.96 0.09 2.2 8

4 0.96 0.11 2.4 8

5 0.96 0.11 2.7 2

6 0.97 0.13 2.5 3

7 0.98 0.16 2.2 2

8 0.96 0.12 1.8 2

9 0.98 0.11 1.7 -7

10 0.94 0.12 1.8 -3

Average 0.96 0.11

Std. Dev. 0.012 0.022
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A2.3.2.4 The example below of flux data from the Duke Forest study provides 

guidance for determining the range of wind directions that will ensure complete capture 

of the plume (in the horizontal direction) by the VRPM configuration. The VRPM flux 

results are representative of the source emission rate only during periods that the 

prevailing wind directions meet the established criterion. 

The determination of the acceptable wind criterion is done by analyzing a data set of 

calculated flux values, with the corresponding wind direction, at the time of the flux 

calculation. The data set should consist of data collected over a wide range of wind 

directions on both sides of the perpendicular direction to the VRPM configuration. A plot 

is create of the calculated flux values as a function of the angle of the prevailing wind 

direction (from perpendicular to the VRPM configuration) of all runs made when the 

wind direction angles were close to the perpendicular direction of the VRPM 

configuration. Because these runs were collected over a period of six months, the flux 

values were normalized to the maximum flux value in each run. 

Figure A.6 presents a plot of this data set. The figure shows the calculated normalized 

flux values and the corresponding wind direction (from the normal to the VRPM 

configuration during the time of the measurements).

The figure shows that the raw flux values steadily increase, up to a certain point, as 

the prevailing wind direction becomes closer to perpendicular to the configuration. 

However, over a certain range of wind directions, there appears to be no relationship 

between calculated flux values and prevailing wind direction. This range is 

approximately between -10° and +25° for the Duke Forest validation study. This is the 

approximate range of acceptable wind directions, as the variations in flux values in this 

range are due to variations in the source strength, and not due to changes in wind 

direction. It is recommended that these flux plots be smoothed out with a moving 

average approach to retrieve a more definite and accurate cutoff of the wind criterion. 

The lined curves in the figure show examples of such moving averages, one with a 

grouping of 10 data values (thin line) and the other with a grouping of 20 data values 

(thicker line). These examples of moving averages clearly define the range of wind 

directions where flux values are independent from the wind direction values. 
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43

Horizontal Plume Capture

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

-20.0 -10.0 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0

Wind Direction [degrees]

Normalized Flux

Raw Data

Moving Average of 10

Moving Average of 20

Figure A.6 Plot of Calculated Flux Values and Corresponding Wind Direction 

During the Time of Measurements 

A3.0 RPM Example using the 1D-RPM Methodology

An example of a 1D-RPM methodology controlled release can be found in Hashmonay 

and Yost (1999).A10

A4.0 References

A1 Varma, R. M.; Hashmonay, R.A.; Kagann, R.H.; Modrak, M. T.; Sullivan, P.D.; 

Segall, R. R. Optical Remote Sensing Method for Flux Measurement from NonPoint Sources. In Proceedings of the 96th Air & Waste Management Association 

Conference, San Diego, CA, June 22-26, 2003.

A2 American Society for Testing and Materials (ASTM) Standard Practice E1982-98, 

Standard Practice for Open-Path Fourier Transform Infrared (OP/FT-IR) 

Monitoring of Gases and Vapors in Air; March 1999.

A3 American Society for Testing and Materials (ASTM)Standard Guide E1865-97 

(Reapproved 2002), Standard Guide for Open-Path Fourier Transform Infrared 

(OP/FT-IR) Monitoring of Gases and Vapors in Air; July 1997.

A4 Russwurm, G. M.; Childers, J. W. FT-IR Open-Path Monitoring Guidance 

Document, 3rd ed.; Submitted by ManTech Environmental Technology, Inc., 
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44

under contract 68-D5-0049 to the U.S. Environmental Protection Agency, Human 

Exposure and Atmospheric Sciences Division, National Exposure Research 

Laboratory: Research Triangle Park, NC, 1999.

A5 Modrak, M. T.; Hashmonay, R. A.; Keagan [Kagann], R. Measurement of Fugitive 

Emissions at a Region I Landfill; U.S. Environmental Protection Agency, 

Research and Development, EPA-600/R-04-001, January 2004.

A6 Hashmonay, R.A.; Natschke, D. F.; Wagoner, K.; Harris, D. B.; Thompson, E. L., 

Yost, M. G. Field Evaluation of a Method for Estimating Gaseous Fluxes from 

Area Sources Using Open-Path Fourier Transform Infrared. Environ. Sci. 

Technol. 2001, 35, 2309-2313.

A7 Modrak, M. T.; Varma, R. M.; Hashmonay, R. A.; Kagann, R. H.; Bolch, M. A.

Demonstration of Optical Remote Sensing Method for Flux Measurement from 

Non-Point Sources. In Proceedings of the 97th Air & Waste Management 

Association Conference, Indianapolis, IN, June 22-25, 2004.

A8 ARCADIS G&M, Inc. ECPB Optical Remote Sensing Facility Manual; U.S. 

Environmental Protection Agency, Emissions Characterization and Prevention 

Branch, Research Triangle Park, NC; Contract No. EP-C-04-023, Work 

Assignment No. 0-33, expected publication 2006.

A9 Hashmonay, Ram A.; Varma, Ravi M.; Modrak, Mark T.; Kagann, Robert H.; Egler, 

Kim; Sullivan, Patrick D.; Segall, Robin R. Validation of Vertical Radial Plume 

Mapping Methodology for Estimating Gaseous Emission Rates from Area 

Sources. J. Air & Waste Manage. Assoc. Submitted in 2006.

A10 Hashmonay, Ram A.; Yost, Michael G. Localizing Gaseous Fugitive Emission 

Sources by Combining Real-Time Remote Optical Sensing and Wind Data. J. Air 

& Waste Manage. Assoc. 1999, 49, 1374-1379.