Modified Area-Source Technique

The area-source technique is a versatile method for accurately estimating emissions from ground-level sources.  It is applicable to all area-type sources, i.e., homogeneous sources (uniformly emitting) and non-homogeneous sources (having "hot spots").  The technique involves identification of a source "attribution" based on a series of near-ground upwind and downwind measurements, and the subsequent back-calculation of emission rates based on Gaussian dispersion relationships inherent in most USEPA Guideline models (e.g., ISCST).  In addition to the source-attribution information, on-site coincident measurements of wind speed, wind direction, and atmospheric stability are required.

Source attribution is represented as a path-integrated concentration, and is obtained by subtracting the upwind path-integrated concentration from the downwind path-integrated concentration.  Mathematically, a path-integrated concentration (units of mg/m2) can be derived by integrating a concentration at a point (mg/m3) across the width (crosswind) of the plume (m).  The benefit of working with path-integrated (or cross-plume) concentration representations lies in the inherent spatial representativeness of the data.

Ideally, path-integrated measurements are generated via some type of optical remote sensing technology -- such as open-path Fourier-transform infrared (FTIR) or ultraviolet (UV) spectroscopy --  which yields such data directly.  However, for the few compounds which are poor IR or UV absorbers, associated minimum detection levels (MDLs) may not be sufficient to meet the required measurement quality objectives (MQOs).  In such cases, a source-attribution approach based on use of rapid-response point monitors is typically employed.

This is exactly the situation for H2S, as it is a notoriously poor IR and UV absorber.  For our work at municipal wastewater treatment plants (WTPs), we have employed Jerome meters to measure this compound.  The Jerome meter can measure H2S in real time (a response time on the order of about 30 seconds) to levels as low as 1 part per billion (ppb).

The area-source technique has been accepted in regulatory applications by USEPA and is consistent with guidance provided in the USEPA's "Air/Superfund National Technical Guidance Study Series - Volume II, Estimation of Baseline Air Emissions at Superfund Sites, EPA-450/1-89-002a." 

The area-source technique, as modified for use with point monitors, is summarized in the following three-step approach:

1.         Identify Source Attribution

This step consists of a series of 15-minute-averaged "monitoring events" in which concurrent, near-ground-level measurements are made upwind (or off-wind) and immediately downwind of the source (separate instruments) to identify source attribution.  Downwind measurements are made at pre-designated locations equispaced along each downwind source perimeter (i.e., downwind pathlength).  Wind speed, wind direction, and atmospheric stability class are averaged over each monitoring event.

A minor variation on this step is employed whenever possible, in which the accuracy of the downwind path-averaged concentration is improved through the simultaneous use of two instruments in the downwind configuration.  Measurements begin at opposite ends of the downwind pathlength, and the results are averaged to reduce error caused by plume meander (i.e., the inability to collect instantaneous data at all downwind locations).

The most important meteorological criterion is wind direction, as pre-defined "windows" (defined as the range of acceptable directions from which the wind can blow) are typically established on a source-specific basis.  Factors considered in defining these windows include source orientation, relationship to other sources, and logistics. 

2.         Predict Relative Path-Integrated Concentration Along Measurement Path

This step consists of using an appropriate dispersion model (typically the ISCST3 Model in screen mode) to predict the relative path-integrated concentration along the downwind measurement path defined in Step 1.  This is accomplished by: (a) predicting the point concentration (mg/m3) at every meter along the measurement path based on a unity emission rate, e.g., 1 mg/m3, and actual meteorology and source configuration; (b) determining the arithmetic average of the point concentrations (mg/m3); and (c) multiplying the average point concentration by the downwind pathlength (m).

"Hot spots" are represented in the unity modeling by assigning a scalar multiplier to the appropriate subarea of the source.  This scalar multiplier is generally based on results of "hot-spot" monitoring immediately before or after the source-attribution monitoring.  Surface "hot-spot" measurements are made across the source in an amount sufficient to provide reasonable spatial representation of the wastewate fate within the source. 

3. Scale Unity Modeling Results to Estimate Emission Rate
This step involves estimating the actual emission rate, QA, in accordance with the following ratio:



CM = measured path-integrated concentration of compound of concern (attribution) (mg/m2)

QA = actual compound emission rate (mg/m2-s)

CP = predicted relative path-integrated concentration (mg/m2)

QU = unity-based emission rate (mg/m2-s)

A more sophisticated means of generating a path-integrated representation of the measured point concentrations is generally required, owing to the larger spacing necessitated by the monitoring instrument response time. An appropriate numerical technique for this data is the parabolic assumption (also known as Simpson's Three-Point Rule) in which the line representing the value of the function is replaced by a second-order equation (y = ax2 + bx + c) with unique values of a, b, and c determined for each subregion. The integral,

(a) Break the interval into n equal parts of width Δx each, where n is an even number.

(b) Compute yk = f(xk), k = 0, 1, 2, . . . , n; x0 = a, xn = ß.

(c) Then:       f(x) dx = 1/3x (y0 + 4y1+ 2y2 + . . . + 2yn-2 + 4yn-1 + yn)

where Δx is calculated by dividing the downwind pathlength (m) by the total number of downwind measurements and y0 is the compound concentration at the first downwind location, y1 is the compound concentration at the next downwind location, etc. 

An important component of this technique concerns collection of the actual meteorological data during Step 1 above.  Ideally, one or more on-site meteorological systems are equipped to monitor a variety of parameters, including wind speed and direction at heights of 1 and 10 meters, all in 15-minute-averaged blocks of time coincident with each monitoring event.  The information is used as input, together with the requisite atmospheric stability data, into the appropriate algorithm to support all emission-rate back-calculations.

The 1-meter wind data is best provided by a portable meteorological system at an on-site location judged representative of the microscale meteorology in the region between the sources and the respective measurements.  The 10-meter wind data is best provided by a second meteorological system installed at a location representative of the local meteorology as influenced by the facility and its immediate environs.

Atmospheric stability is one of the parameters required for the back-calculation of emission rates.  Identification of the proper atmospheric stability class (A through F) is necessary so that the appropriate vertical dispersion coefficient can be assigned by the model in the back-calculation process.  The resultant emission rate is a strong function of the vertical dispersion coefficient.

A variety of methods exist for estimating the atmospheric stability class.  The solar radiation method involves consideration of insolation intensity and surface wind speed and is applicable during both daytime and nighttime.  The delta-temperature method involves consideration of the vertical temperature gradient and surface wind speed and is applicable only during nighttime.  The sigma-theta method involves consideration of the standard deviation of the wind direction and surface wind speed and is applicable during both daytime and nighttime.

The greatest single source of error in the application of the area-source technique involves the treatment of atmospheric stability as a discrete function (for a given downwind distance) when, in reality, atmospheric stability (and the resultant vertical dispersion coefficients) is a continuous function.  Optical remote sensing can be employed to define site-specific vertical dispersion coefficients which can be substituted into the back-calculation algorithm to eliminate this source of error.

Click onto site-specific vertical dispersion coefficient development for more information about atmospheric stability and how site-specific vertical dispersion coefficients are developed.


© 2002 Minnich and Scotto, Inc.