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:
where:
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 = 1/3 x
(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.
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