U.S. patent application number 13/939413 was filed with the patent office on 2014-01-16 for method and system for measuring emission and quantifying emission source.
This patent application is currently assigned to AIRDAR INC.. The applicant listed for this patent is AIRDAR INC.. Invention is credited to DENNIS SCOTT PRINCE.
Application Number | 20140019066 13/939413 |
Document ID | / |
Family ID | 42981653 |
Filed Date | 2014-01-16 |
United States Patent
Application |
20140019066 |
Kind Code |
A1 |
PRINCE; DENNIS SCOTT |
January 16, 2014 |
METHOD AND SYSTEM FOR MEASURING EMISSION AND QUANTIFYING EMISSION
SOURCE
Abstract
A system and method for quantifying an emission source is
provided. The system and method obtain a plurality of emission
concentration measurements at one or more sampling points and wind
data over the time the emission concentrations are measured. For
each sampling point, a virtual sampling arc can be constructed
using the emission concentration measurements taken at the sampling
point, the wind data for when the emission concentration
measurement were taken and an approximate distance to the emission
source. The virtual sampling arcs can then be used to construct one
or more virtual sampling grids and the amount of emissions
emanating from the emissions source approximated from the virtual
sampling grids.
Inventors: |
PRINCE; DENNIS SCOTT;
(Edmonton, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
AIRDAR INC. |
EDMONTON |
|
CA |
|
|
Assignee: |
AIRDAR INC.
Edmonton
CA
|
Family ID: |
42981653 |
Appl. No.: |
13/939413 |
Filed: |
July 11, 2013 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
12759857 |
Apr 14, 2010 |
8510059 |
|
|
13939413 |
|
|
|
|
61168965 |
Apr 14, 2009 |
|
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Current U.S.
Class: |
702/24 |
Current CPC
Class: |
G01N 1/26 20130101; G01N
1/2273 20130101; G01N 33/0062 20130101 |
Class at
Publication: |
702/24 |
International
Class: |
G01N 33/00 20060101
G01N033/00 |
Claims
1. A method for quantifying an emission source comprising:
obtaining a plurality of emission concentrations measurements at a
plurality of sampling points; obtaining wind speed measurements and
wind direction measurements when the plurality of emission
concentration measurements are taken; for each sampling point,
constructing a virtual sampling arc made up of a plurality of
points, each point based on: an emission concentration measurement
taken at the sampling point; a wind direction when the emission
concentration measurement was taken; and an approximate distance to
the emission source, wherein all of the emission concentration
measurements used to construct one of the virtual sampling arcs
were taken at substantially the same wind speed; grouping virtual
sampling arcs made of emission concentrations measurements at
substantially the same wind speed into a virtual sampling grid; and
approximating the amount of emissions passing through the virtual
sampling grid.
2. The method of claim 1 wherein the sampling points are vertically
spaced.
3. The method of claim 2 wherein the sampling points are vertically
aligned.
4. The method of claim 1 wherein the wind speed measurements and
the wind direction measurements are taken at the plurality of
sampling points.
5. The method of claim 1 wherein the approximate distance to the
emission source from the sampling point is an estimated
distance.
6. The method of claim 1 further comprising: providing an
additional sampling point spaced laterally apart from the plurality
of sampling points; using emission concentration measurements taken
at the additional sampling point to determine a first trajectory of
emissions from the emission source; determining a second trajectory
of emissions from the emission source using emission concentration
measurements taken at the plurality of sampling points; and using
the first trajectory and second trajectory to approximate the
distance to the emission source.
7. The method of claim 6 wherein the amount of emissions passing
through the virtual sampling grid and the distance to the emission
source are iteratively approximated.
8. The method of claim 1 wherein the amount of emissions passing
through the virtual sampling grid is determined by dividing the
virtual sampling grid into sections; approximating the flowrate of
emissions through each section; and determining an approximate
total flowrate of an emissions plume through the virtual sampling
grid.
9. The method of claim 8 further comprising determining whether
each section falls within an emission plume originating from the
emission source.
10. The method of claim 8 further comprising approximating a shape
of an emission plume originating from the emission source.
11. The method of claim 10 further comprising interpolating
additional points in the virtual sampling grid where no points are
present.
12. The method of claim 10 further comprising extrapolating
additional points beyond the virtual sampling grid.
13. The method of claim 1 wherein the emission concentration
measurements are taken with at least one open-path gas
detector.
14. A method for quantifying an emission source comprising:
obtaining a plurality of emission concentrations measurements at a
single sampling point; obtaining wind speed measurements and wind
direction measurements when the plurality of emission concentration
measurements are taken; constructing a virtual sampling arc made up
of a plurality of points, each point based on: an emission
concentration measurement taken at the single sampling point; a
wind direction when the emission concentration measurement was
taken; and an approximate distance to the emission source, wherein
all of the emission concentration measurements used to construct
the virtual sampling arcs were taken at substantially the same wind
speed; estimating an emissions plume shape with the virtual
sampling arc passing through it; extrapolating points in the
emission plume shape using points from the virtual sampling arc;
and approximating the amount of emissions passing through the
emission plume shape.
Description
CROSS REFERENCE TO RELATED APPLICATIONS
[0001] This application is a continuation application of U.S.
application Ser. No. 12/759,857 filed Apr. 14, 2010, which is
presently pending. U.S. application Ser. No. 12/759,857 and the
present application claim priority under 35 U.S.C. .sctn.119(e) to
U.S. provisional patent application No. 61/168,965 filed Apr. 14,
2009,
FIELD OF THE INVENTION
[0002] The present invention relates to air monitoring and more
specifically to a method and system for quantifying an emission
source.
BACKGROUND OF THE INVENTION
[0003] The reduction of contaminant emission into the air is
important to decreasing our environmental impact on the
environment. Air quality monitoring can be an inexact science. Air
contaminants are often visually imperceptible and even when they
may be visible, they are often hard to discern and/or quantify by
visualizations alone. Often, the methods used to monitor the rate
of emission into the air, such as contaminants, are simple and
often inaccurate or alternatively, very complex, requiring skilled
experienced professionals and often error prone. Even in cases
where the methods are successfully performed, the resulting
observations may be too vague or inaccurate to provide a meaningful
quantification of the emissions.
SUMMARY OF THE INVENTION
[0004] In one aspect, a method for quantifying an emission source
is provided. The method comprises: obtaining a plurality of
emission concentrations measurements at a plurality of sampling
points; obtaining wind speed measurements and wind direction
measurements when the plurality of emission concentration
measurements are taken; for each sampling point, constructing a
virtual sampling arc made up of a plurality of points, each point
based on: an emission concentration measurement taken at the
sampling point; a wind direction when the emission concentration
measurement was taken; and an approximate distance to the emission
source, wherein all of the emission concentration measurements used
to construct one of the virtual sampling arcs were taken at
substantially the same wind speed; grouping virtual sampling arcs
made of emission concentrations measurements at substantially the
same wind speed into a virtual sampling grid; and approximating the
amount of emissions passing through the virtual sampling grid.
[0005] In another aspect, a method for quantifying an emission
source is provided. The method comprises obtaining a plurality of
emission concentrations measurements at a single sampling point;
obtaining wind speed measurements and wind direction measurements
when the plurality of emission concentration measurements are
taken; constructing a virtual sampling arc made up of a plurality
of points, each point based on: an emission concentration
measurement taken at the single sampling point; a wind direction
when the emission concentration measurement was taken; and an
approximate distance to the emission source, wherein all of the
emission concentration measurements used to construct the virtual
sampling arcs were taken at substantially the same wind speed;
estimating an emissions plume shape with the virtual sampling arc
passing through it; extrapolating points in the emission plume
shape using points from the virtual sampling arc; and approximating
the amount of emissions passing through the emission plume
shape.
[0006] In another aspect, a system for quantifying an emission
source is provided. The system comprises: a plurality of sampling
points operative to obtain emission concentration measurements; at
least one emission monitor operative take emission concentration
measurements at the plurality of sampling points; a data processing
device operatively connected to the at least one emission monitor
to obtain emission concentration measurements from the at least one
monitor, the data processing device operative to: obtain a
plurality of emission concentrations measurements from the at least
one emission monitor; obtain wind speed measurements and wind
direction measurements when the plurality of emission concentration
measurements were taken; for each sampling point, construct a
virtual sampling arc made up of a plurality of points, each point
based on: an emission concentration measurement taken at the
sampling point; a wind direction measurement when the emission
concentration measurement was taken; and an approximate distance to
the emission source, wherein all of the emission concentration
measurements used to construct one of the virtual sampling arcs
were taken at substantially the same wind speed; group virtual
sampling arcs made of emission concentrations measurements at
substantially the same wind speed into a virtual sampling grid; and
approximate the amount of emissions passing through the virtual
sampling grid.
[0007] In another aspect, a method for quantifying an area emission
source is provided. The method comprises: obtaining a plurality of
emission concentrations measurements at a plurality of sampling
points; obtaining wind speed measurements and wind direction
measurements when the plurality of emission concentration
measurements are taken; for each sampling point, constructing a
virtual sampling array made up of a plurality of points, each point
based on: an emission concentration measurement taken at the
sampling point; a wind direction measurement when the emission
concentration measurement was taken; and a representative distance
to a representative center of a catchment area of the area emission
source being measured by the emission concentration measurement,
wherein all of the emission concentration measurements used to
construct one of the virtual sampling arrays were taken at
substantially the same wind speed; grouping virtual sampling arrays
made of emission concentrations measurements taken at substantially
the same wind speed into a virtual sampling grid; and approximating
the amount of emissions passing through the virtual sampling
grid.
BRIEF DESCRIPTION OF THE DRAWINGS
[0008] Referring to the drawings wherein like reference numerals
indicate similar parts throughout the several views, several
aspects of the present invention are illustrated by way of example,
and not by way of limitation, in detail in the figures,
wherein:
[0009] FIG. 1 is a schematic illustration of a sampling system;
[0010] FIG. 2 is a flowchart illustrating a method for quantifying
an emission source;
[0011] FIG. 3 is a schematic illustration of an emission plume;
[0012] FIG. 4 is a schematic illustration of an emission source and
a measuring point plotted on a polar coordinate system;
[0013] FIG. 5 is a schematic illustration of the emission source
and the measuring point of FIG. 4 with a different direction of
bulk air flow;
[0014] FIG. 6 is a schematic illustration of the emission source
and the measuring point of FIG. 4 with a number of virtual
measuring points indicated;
[0015] FIG. 7 is a schematic illustration of a virtual sampling
grid;
[0016] FIG. 8 is a flowchart illustrating a method of quantifying
an emission source using one or more virtual sampling grids;
[0017] FIG. 9 is a schematic illustration of a testing apparatus
for conducting exemplary testing of a known emission source;
[0018] FIG. 10 is a schematic illustration of an emission source
used for the testing apparatus of FIG. 9;
[0019] FIG. 11 is a plot of emission concentrations measured over
time;
[0020] FIG. 12 is a plot of wind speed data collected over the same
time period shown in FIG. 11;
[0021] FIG. 13 is a plot of wind direction collected over the same
time period shown in FIG. 11;
[0022] FIG. 14 is a plot of flow rate of emission from an emission
source over the same time period shown in FIG. 11;
[0023] FIG. 15 is a set of plots of emission concentrations in
relation to wind speed and wind direction;
[0024] FIG. 16 is a set of plots of average emission concentrations
in relation to wind speed and wind direction;
[0025] FIGS. 17A, 17B and 17C are tables of obtained data across a
virtual sampling grid;
[0026] FIGS. 18A, 18B, 18C, 18D, 18E, 19A, 19B, 19C, 19D, 19E, 20A,
20B, 20C, 20D and 20E are sets of plots of increased emission
concentrations plotted against vertical and horizontal distances
for different emission rates;
[0027] FIG. 21 is a set of plots representing the average flux of
the emission in relation to wind speed and direction at different
sample inlets;
[0028] FIGS. 22A, 22B, 22C, 22D, 22E, 23A, 23B, 23C, 23D, 23E, 24A,
24B, 24C, 24D and 24E are sets of plots representing plume flux
distributions at different wind speeds and observation heights for
different emission rates;
[0029] FIG. 25 is a plot of estimated emission rates based on the
emission plume characteristic at different wind speeds;
[0030] FIG. 26 is a plot of the average emission estimates versus
the known emission rate;
[0031] FIG. 27 is a plot of emission rates estimates based on
emission plume characteristics at different wind speeds;
[0032] FIG. 28 is a plot of emission rates versus actual emission
rates;
[0033] FIG. 29 is a plot of emission rates estimates based on
emission plume characteristics at different wind speeds;
[0034] FIGS. 30A and 30B are flowcharts of a method for quantifying
an emission source when the distance between the emission source
and the measurement position is not known;
[0035] FIG. 31 is a schematic illustration of an area emission
source and a catchment area;
[0036] FIG. 32 is a schematic illustration of the area emission
source in FIG. 31 and a second catchment area;
[0037] FIG. 33 is a schematic illustration of the area emission
source in FIG. 31 and a third catchment area;
[0038] FIG. 34 is a schematic illustration of the area emission
source in FIG. 31 divided in catchment area;
[0039] FIG. 35 is a schematic illustration of a distorted area
emission source;
[0040] FIG. 36 is a schematic illustration of a measurement
position inside an area emissions source; and
[0041] FIG. 37 is a schematic illustration of a distorted area
emission source.
DESCRIPTION OF VARIOUS EMBODIMENTS
[0042] The detailed description set forth below in connection with
the appended drawings is intended as a description of various
embodiments of the present invention and is not intended to
represent the only embodiments contemplated by the inventor. The
detailed description includes specific details for the purpose of
providing a comprehensive understanding of the present invention.
However, it will be apparent to those skilled in the art that the
present invention may be practiced without these specific
details.
[0043] FIG. 1 illustrates a sampling system 10 for obtaining air
samples, measure emission concentrations in the air and quantifying
an emission source. The sampling system 10 can have a tower 12
containing a number of sampling points 20. Each sampling point 20
can be at a different vertical height and in one aspect, all of the
sampling points 20 are vertically aligned on the tower 12. Each
sampling point 20 can have a sampling tube with an inlet of the
sampling tube 1 at the sampling point 20. The sampling tubes 22 can
be routed to a sample router device 30 that selectively supplies
the air samples taken at the sample points 20 to an emission
monitor 40, such as a THC monitor, for measuring a concentration of
one or more emission in the air, such as an air contaminant, etc.
The emission monitor 40 can be operatively connected to a data
processing system 50, such as a personal computer, to receive
information collected/recorded by the emission monitor 40 from the
sampling points 20 on the tower 12. Although FIG. 1 illustrates the
sampling points 20 being vertically aligned, in some aspects the
sampling points 20 may vary in horizontal positioning so that they
are not necessarily vertically aligned.
[0044] In operation, the sampling system 10 can be installed with
the tower 12 and the sampling points 20 positioned at a desired
location for a period of time. During this period of time air can
be drawn in through the sampling points 20 routed through the
sampling tubes 22 and directed to the emission monitor 40 by the
sampler router device 30. The measurement of the emission in the
sample can then be taken by the emission monitor 40 and provided to
the data processing system 50 where the emission reader can be
logged and associated with the sampling point 20 it was taken from
and the time it was taken. In one aspect, the travel time of the
air as it is routed through the tubing 22 can be taken into account
to determine the time the air was taken at the sampling point 20.
In a further aspect, the distance to the source and the approximate
travel time of the air from the source to the sampling point 20 can
also be taken into account. Over the period of time, numerous data
can be collected indicating concentration levels of emission at the
various sampling points 20 at various times.
[0045] In another aspect, open-path gas detectors could be provided
at each of the sampling points 20 to obtain emission concentration
measurements at the sampling points 20. Open-path gas detectors
typically use a laser source to direct a laser beam through a path
to a receptor (in some cases they may use a mirror to reflect the
laser back to the receptor). Based on the absorption of the laser
by gas in the path of the laser, the open-path gas detector can be
used to detect the presence of and the concentration of specific
emissions.
[0046] In some cases, the gap the open-path gas detector is
monitoring may be 6 feet or greater resulting in the sampling point
where the emission concentration measurements being measured to be
a relatively large sampling point.
[0047] FIG. 2 illustrates is a flowchart illustrating a method for
quantifying an emission source using samples obtained of the
emission in the air, such as by using the sampling system 10 shown
in FIG. 1. The method 100 starts and at step 102 emission
concentration data regarding emissions in the air is obtained by
the sampling system 100 and is combined with wind speed and
direction data related to the emission concentration data. The
combined data is used to approximate dimensionless plume data for
each sample points 20 on the tower 12 in the sampling system 10 at
step 104. Each sampling point 20 on the tower 15 can be converted
to a virtual sampling arc at step 108. Typically, a virtual
sampling arc is determined for each sampling point 20 for a
specific wind speed or relatively narrow range of wind speeds. At
step 110, the virtual sampling arcs determined for the different
sampling points 20 can be grouped into a number of virtual sampling
grids. Typically, each virtual sampling grid will be associated
with a specific wind speed or relatively narrow range of wind
speeds. Using the virtual sampling grids, at step 112, the overall
plume shape can be completed. At step 114, a source emission rate
for the emission source can be determined.
[0048] After the method 100 starts, measured emission
concentrations in the air are combined with representative wind
speed and direction data in a mathematical manipulation at steps
102 and 104 that produces dimensionless plumes viewed from the
perspective of each measurement position. In the context of the
present description, an emission plume means or refers to a column
or aggregation of the emitted material which moves through the air.
Plume may also refer more generally to a column of a fluid moving
through another fluid. Several effects control the motion of the
fluid, including momentum, buoyancy, density difference, etc. A log
of wind speeds and directions are kept, from which a previous wind
speed measurement and a corresponding wind direction measurement
may be selected based on the air sample propagation time delay down
a corresponding sampling tube 22, sampler routing device 30, and
possibly the emission monitor 40. The emission concentration
measurements can be averaged during an interval of sampling time to
reduce signal noise and possibly analog to digital conversion
errors. For example, measurements can be made at a frequency of 500
readings per second collected and averaged over the 10 second
period. Emission concentration can be measured in parts-per-million
(ppm).
[0049] In tracking emission sources an accurate characterization
may be needed of air movement (wind driven) driving emission plumes
from emitting sources to the sample points 20. In accordance with
an embodiment of the invention, wind speed and wind direction are
not necessarily assumed to be constant. Wind speed and wind
direction can be measured at each air sample inlet 20, a reduced
number of locations or even at a single representative location.
Following the measurement of wind velocity characteristics such as,
but not limited to, wind speed and wind direction, the wind
characteristics can be correlated with the corresponding emission
concentration measurements performed by the emission monitor 40 and
provided to the data processing system 50. Correlating wind
characteristics can take into account air sample travel time along
the sampling tubes 22 from the sample points 20, and time of travel
over the area of interest.
[0050] The wind speed and direction is not stable over time and can
vary second to second moving a volume of air along a nonlinear path
from the emission source to the sample tower 12. Obstructions such
as land topography and buildings can cause wind to be non-linear,
and knowledge of the geometry of such obstructions can improve the
tracking of the trajectory of the air. Accordingly, wind speed and
wind direction estimates are related to individual readings from
the emission monitor 40.
[0051] A higher level process may be used to account for the wind
variability by back tracking the nonlinear path of a volume of air
from the sampling points 20 back to the emission source, by
stepping backward in time and outward in space away from the
sampling point 20 adjusting the path and concentration with each
step for the changing wind conditions (note concentrations would be
adjusted to reflect the dispersion that occurs as the plume travels
down wind). Each emission concentration measured by the emission
monitor 40 can take into account the degree to which changes in
wind velocity have affected the air sample traversing a path
outward and up-wind from the sampling point 20.
[0052] Alternatively, a representative wind velocity can be used
wherein the non-linear path of air from an emission source to the
sampling tower 12 can be replaced with a linear vector which
estimates the average wind (velocity) speed and wind direction
during the time of travel of the air from the emission source to
the sampling point 20 measuring the emission concentration in the
air. A measure of the standard deviation of wind speed and wind
direction can also be calculated to provide an estimate of the
accuracy of the assumption of linearity of the non-linear flow
path. The linearity assumption can have more error at low wind
speed because of longer averaging times and possibly due to a more
unstable direction of flow of the wind (i.e. low speed wind may be
subject to more radical changes in direction than high speed wind.
In addition the travel time, which is calculated as the distance
over wind speed, increases dramatically as a function of reciprocal
wind speed and at low speeds (i.e. air moving at low speed takes
much longer to get to the sampling point 20 and results in a longer
averaging time substantially equal to the traveling time). The
result of standard deviation calculation is used to filter out
readings of the analysis that occur when the wind direction shifts
too much for an accurate prediction of the flow path. This
technique identifies wind data that accurately predicts wind
effects and eliminates data that does not. Accurate low wind data
may be very valuable in locating emission sources at great
distances if the wind direction is stable. With knowledge of the
geometry of the topography, buildings and other obstacles, the
trajectory of the emission plume can be assumed linear and
corrected for movement around obstacles.
[0053] An adjustment can be made for the time of travel of the air
sample from the sampling point 20 down the corresponding sampling
tube 22 through sample router 30 and to the emission monitor
40.
[0054] The measured emission concentrations at each sampling point
20 can be combined with the determined representative wind speed
and wind direction associated with when that measurement of the
emission concentration was taken. In one aspect, there is
preferably a number of measured emission concentrations for a
representative wind speed and wind direction and these measured
emission concentrations can be averaged (or a median taken) to
determine an emission concentration associated with the
representative wind speed and wind direction. By grouping these
emission concentrations with their associated representative wind
speed and wind direction a dimensionless plume can be
constructed.
[0055] At step 108 of the method 100, the data obtained from each
sampling points 20 can be converted into one or more virtual
sampling arcs using the distance of the sampling points 20 to the
emission source. Typically, each generated virtual sampling arc
will be for a specific wind speed or a relatively narrow range of
wind speeds.
[0056] A single sampling point 20 on the tower 15 of the sampling
system 10 can be represented as a virtual arc of measurement
positions that will provide concentration measures at a constant
elevation. The emission concentration measurement obtained at a
virtual measurement position can be an average of the emission
concentration measurements taken at that virtual measurement
position. This virtual arc will intercept a plume in a horizontal
line for a given wind speed. This line can be at a different
location on the plume if the plume elevation changes as a result of
different wind speeds (due to buoyancy or momentum. etc.). FIG. 3
illustrates an emission plume 130 with three horizontal lines A, B
and C, passing through different portions of the emission plume
130. Each line A, B, C represents a virtual arc taken from a single
sampling point 20 at a specific vertical position on the tower 15
of the sampling system 10. Each line A, B, C was taken at a
different wind speed; line A represents a virtual arc taken by the
sampling point 20 at a first wind speed, line B represents a
virtual arc taken by the same sampling point 20 at a second wind
speed and line C represents a virtual arc taken by the same
sampling point 20 at a third wind speed. As can be seen in FIG. 3,
the portion of the emission plume 130 that is measured by a
sampling point 20 can vary depending on the wind speed.
[0057] FIG. 4 illustrates an emission source 150 in relation to a
measurement position 155 with an emission plume 140 originating
from the emission source 150. The emission plume 140 is carried
along with the bulk airflow (i.e. the wind). The measurement
position 155 can be the tower 15 of the sampling system 10 shown in
FIG. 1. A polar coordinate axis (.theta., r) in plan view can be
used with the origin at the emission source 150 and the zero (0)
degree axis aligned with a direction of the bulk air flow (i.e. the
wind), which is also pointed directly at the measurement position
155. The measurement position 155 is shown positioned in the
emission plume 140 originating from the emission source 150 because
the emission plume 140 will be carried along by the bulk
airflow.
[0058] FIG. 5 illustrates the emission source 150 and the
measurement position 155 when the direction of the bulk air flow
has shifted (i.e. the wind has changed direction). By keeping the
zero (0) degree axis aligned with the direction of the bulk air
flow in FIG. 5, the relative position of the measurement position
155 of air concentrations sifts relative to the upwind emission
source 150. FIG. 5 shows the measurement position 155 being at a
slight negative angle relative to the zero (0) axis line. While
neither the emission source 150 nor the measurement position 155
have physically moved, their positions have changed relative to the
bulk air flow (which carries the emission plume 140). The magnitude
of the relative position shift is directly related to the angle of
the bulk airflow (i.e. the wind) direction shift and the distance
between the emission source 150 and measurement positions 155. The
virtual measurement position 158 indicates where the measurement
position 155 was relative to the bulk airflow in FIG. 4. The
measurement position 155 is now measuring the concentration of
emission in the emission plume 140 at a different point in the
emission plume 140.
[0059] With continued changes in the direction of the bulk airflow,
a single measurement position 155 can be used as a series of
virtual measurement positions 158 through the emission plume 140 in
a radial arc with the center of the arc at the emission source 150,
as shown in FIG. 6. With enough changes in wind direction and
measurements of emission concentrations at the measurement point
155 a virtual sampling arc 160 can be determined. This virtual
sampling arc 160 can have measured emission concentrations of the
emission plume 140 along the virtual sampling arc 160 for a
specific wind speed or relatively narrow range of wind speeds. In
one aspect, the measured emission concentrations along the virtual
sampling arc 160 can be an average of measured emission
concentrations at each virtual measurement positions 158.
[0060] The positions of the virtual measurement positions 158 in
the virtual sampling arc 160 can be determined using the angular
shift in the direction of the bulk airflow. The conversion of an
angular shift in the direction of bulk airflow to a scalar length
along the arc between virtual measurement positions 158 is the arc
length along a curve of a circle centered at the emission source
150 for a point emission source:
Length LARC = AngularWidth 360 .degree. .times. cirumference =
AngularWidth 360 .degree. .times. 2 .times. .pi. .times. r [ 1 ]
##EQU00001##
wherein Length.sub.LARC is the scalar length along the arc, the
angular width is the change in the angle of the direction of the
wind and r is the distance between the emission source 150 and the
measurement position 158.
[0061] In this manner, a virtual sampling arc 160 can be determined
where an emission concentration has been measured for each of the
virtual measurement positions 158 (or points) making up the virtual
sampling arc 160.
[0062] Referring again to FIG. 1, one or more virtual sampling arcs
160 can be determined for each of the sampling points 20 on the
tower 15 in this manner. Typically, each virtual sampling arc 160
is associated with a specific wind speed or relatively narrow range
of wind speeds.
[0063] Referring again to FIG. 2, once the virtual sampling arcs
have been generated at step 108, the method 100 can move on to step
110 and the generated virtual sampling arcs determined at step 108
can be grouped together to form one or more virtual sampling grids.
FIG. 7 illustrates a virtual sampling grid 170. Typically, each
virtual sampling grid 170 will be made up of measured emission
concentrations at a specific wind speed or relatively narrow range
of wind speed. The multiple sampling points 20 of the sampling
system 100 shown in FIG. 1 can be used to form the virtual sampling
grid 170 of emission concentration measurements using the
measurement position 155. The virtual sampling grid 170 can follow
an arc that is centered on the emission source 150 location.
[0064] The virtual sampling grid 170 can be determined using the
virtual sampling arcs 160 determined for each sampling point 20 for
a specific wind speed or range of wind speeds at step 108 of method
100 shown in FIG. 2. Each virtual sampling arc 160 is associated
with its corresponding sampling point 20 on the tower 15 and can be
placed in the virtual sampling grid 170 at the vertical level of
the sampling point 20. By applying the determined virtual sampling
arc 160 for each sampling point 20 at a specific wind speed or
range of wind speeds, the virtual sampling grid 170 for the
specific wind speed or range of wind speeds, can be created, with
each point on the virtual sampling grid 170 having an emission
concentration that has been measured at that position.
[0065] Referring again to FIG. 2, in this manner, set of virtual
sampling grids 170 can be constructed at step 110, with each
virtual sampling grid 170 associated with a wind speed or range of
wind speeds and each point in the virtual sampling grid 170 has an
emission concentrations associated with it that has been measured
at that point.
[0066] Optionally, at step 112 the overall emission plume shape and
the concentration profile of the emission plumes can be
approximated by combining information from different sampling
points 20 and virtual measurement positions 158 for the same
emission plume. If the different sampling points 20 do not provide
enough desired points on the virtual sampling grid 170 as shown in
FIG. 7, emission concentrations measurements for point on the quasi
radial virtual sampling grid 170 can be used to extrapolate and/or
interpolate to approximate emissions concentrations at the desired
points where there are no emission concentrations measurement or
insufficient emission concentration measurements. In one
embodiment, the emission plume shape and concentration profile can
be interpolated and/or extrapolated from locations having measured
emissions concentrations during the sampling period. Emission
concentrations can be approximated for locations in the virtual
sampling grid 170 where no emission concentration measurements were
taken or not enough emissions concentrations were taking to provide
a useful average. By interpolation/extrapolation using adjacent
virtual measurement positions 158 having measured emission
concentrations, emission concentrations for other points in the
virtual sampling grid 170 can be approximated. For example, if
there is measurement positions at two different elevations then the
shape of the plume can be interpolated between the measurement
positions. Additionally, if the highest or lowest sampling points
20 do reach the top/bottom of the emission plume, points above or
below the sampling points 20 could be extrapolated from adjacent
sampling points 20 using the measured emission concentrations at
the adjacent sampling point 20.
[0067] In one embodiment, the emission plume shape and
concentration profile can be extrapolated from a single sampling
point 20 (and its associated virtual sampling arc 160). The
emission plume can be broken down to concentric circle rings or
some other assumed shape and the area or each ring calculated and
the flux across each piece determined in order to integrate them to
the total number.
[0068] Assuming a circular shape to the plume is just a method to
extrapolate the measured concentration profile across one line of
the emission plume to other areas of the plume and any known and
appropriate shape can be assumed. This method can be effective even
if the ground impinges on the lower part of the emission plume so
that it cannot develop the actual circular shape. Basically,
characterizing the top portion of an emission plume and assuming
the bottom portion is the same can provide effective estimates of
emission rate,
[0069] Referring again to FIG. 2, at step 114, the emission rate of
the emission source can be quantified. The emission plume as
measured by the sampling points 20 can be broken down to smaller
manageable pieces and the flux per unit emission plume area
analyzed across the pieces. An evaluation to determine which pieces
belong to the overall plume or sub plumes can be done to total the
overall emission rate of an emission source and the emission rate
of sub sources within the overall plume.
[0070] FIG. 8 is a flow chart illustrating a method 200 of
quantifying an emission source in one aspect and can be used to
perform step 114 of method 100 in FIG. 2. The method 200 starts and
at step 210 a virtual sampling grid, determined at step 112 of the
method 100 shown in FIG. 2, is divided into subsections. At step
220, the flux rate of the increased compound concentrations through
each of the subsections is determined for different wind speeds.
The increased compound concentration is the measured concentration
less the concentration of that compound that normally occurs in
that location. Using the flux rates determined for the subsections
at step 220, the subsections that are within the emission plume
boundaries are determined for the different wind speeds at step
230. At step 240, for each subsection, the flux rates determined
for the subsection at step 220 are multiplied by the area of the
subsections to determine a flow rate. At step 245, the flow rates
determined for each of the subsections at step 240 are totaled to
approximate the source emission rate. In this manner, the
quantification of the emission rate can be approximated by
calculating the flux of increased emission crossing the virtual
sampling grid after dividing the virtual sampling grid into
subsections. Because the measured emission concentrations in each
virtual sampling grid which will vary depending on the wind speed,
the method 200 can be performed for each virtual sampling grid that
has be determined and is associated with a wind speed or range of
wind speeds, allowing a separate quantification of a flow rate to
be determined for each of the virtual sampling grids that were
determined for a specific wind speed or relatively narrow range of
wind speeds.
[0071] At step 210 the virtual sampling grids can be divided into
subsections. If the sampling system 10 shown in FIG. 1 was used to
sample the air and measure the emission concentrations, the
vertical spacing of the subsections can be set by the vertical
spacing of the sampling points 20 on the tower 15. The horizontal
spacing of the subsections is set by the size of increments of wind
direction on which the data is aggregated. The increments need to
be small enough to accurately characterize the emission plume. The
boarders of each subsection can be defined by half the distance to
the adjacent subsection center. If there are no adjacent
subsection, such as along the bottom of the virtual sampling grid,
then the ground can be used as the border (or something just above
the ground to take into account that there is little air flow along
the ground). The top boundary of the subsections along the top of
the virtual sampling grid positions is assumed as the same distance
to the center of the subsections as the bottom boundary (this upper
boundary can also be assumed based on an extrapolated emission
plume concentration profile if the plume boundary extends above the
virtual radial sampling grid).
[0072] The area of the each subsection can be calculated by height
*width if the elements are rectangular as follows:
Area.sub.subsection=HEIGHT.times.WIDTH [2]
[0073] At step 220, a flux value can be approximated for each of
the subsections. The flux value can be approximated by multiplying
the increased emission concentration (i.e. if the emission being
measured is THC, the THC concentration less the background level of
THC could be used for the increased emission concentration) by the
wind speed as follows:
FluxValue=IncreasedEmissionConcentration.times.windspeed [3]
The units of this flux value is the amount of compound that is
passing a unit area of the grid of virtual measurement positions
during a unit of time, for example
L ( min .times. m 2 ) , or L ( hr .times. m 2 ) . ##EQU00002##
The area (m.sup.2) in these formulas refers to the radial
cross-sectional area of the emission plume.
[0074] At step 230, the boundary of the emission plume can be
approximated. The boundary of the emission plume can be taken to be
the point where the modeled flux breaks below some minimum flux
level on either side of the emission plume peak. This allows the
emission plume boundaries that exist within the background noise to
be accurately predicted. A model is not fitted and the emission
plume is considered not definable when the plume shape is not
dominant above the background flux values.
[0075] After the boundaries of the emission plume are determined at
step 230, the flow rate through each of the subsections can be
approximated at step 240. The flow rate through each subsection can
be determined by multiplying the flux value determined for the
subsection at step 220 by the area of the subsection determined at
step 210, as follows:
FlowRate=FluxValue.sub.SUBSECTION.times.Area.sub.SUBSECTION [4]
At the completion of step 230, the flow rates of the emission
through each of the subsections should be approximated.
[0076] At step 245, the flow rates approximated for each of the
subsections at step 240 can be totaled to determine the source
emission rate. Using the emission plume boundary determined at step
330, the approximated flow rates through each of the subsections
can be totaled across the emission plume boundary. The total flow
rate through the emission plume boundary can provide an
approximation of the emission rate for the emission source.
[0077] Referring again to FIG. 2, after step 114, with the emission
source having been quantified, the method 100 ends.
[0078] Testing was conducted with a sampling device to quantify a
known emission source with sampling positions at different heights
used to construct a virtual sampling grid of virtual measurement
positions. Natural gas was released at controlled flow rates and
the resulting emission plume was characterized and the emission
rate determined using the system and method outlined above.
[0079] In a ten acre hay field an emission source 250, a wind
monitor 255, and a sampling tower 12 were erected as shown in FIGS.
9 and 10. This study was set in southwestern Alberta which has
predominant wind from the southwest. The sampling tower 12 was 15.2
m high with sampling points 20 positioned at the ten different
heights shown. The sampling tower 12 was positioned 60 m away in
the predominant downwind direction from the emission source 250 and
the wind monitor 255. The emission source 250 is shown in more
detail in FIG. 10 and consisted of a 2.5 m aluminum heating duct
that was 150 mm in diameter with the end pointing upward at a
height of 1.52 m off the ground. Two duct fans 257A, 257B were used
to maintain a constant flow upward and entrain the natural gas
released from a line 258 running from a gas supply (not shown) that
is metered with a flow sensor 259 that has been calibrated with a
bubble flow meter made by Gillian. This setup allowed the
controlled emission plume to have a roughly constant exit velocity
for different natural gas emission rates. Small diameter (1/4 inch
OD) polyethylene sample lines 22 connected the sample points 20 on
the sampling tower 15 to a sample router 30 (200 m away) that
constantly draws a sample from all of the sample points 20 and
selectively channels one of the samples to an emission detector 40,
in this case a flame ionization detector (Photovac microFID)
providing a measure of total hydrocarbons (THC). In this way, one
instrument was used to provide concentration measures from multiple
locations. The data processing system 50 shown in FIG. 9 was used
to control the sample router 30 and store data at a one second
frequency from the emission detector 40, the wind monitor 255, and
the flow meter 259 connected to the line 258.
[0080] FIGS. 11 through 14 shows plots of the data collected during
the study rolled up to a ten second average. There are periods of
time when data was not available due to equipment malfunction. FIG.
11 shows the THC levels measured by the emission detector 40
through the study. FIGS. 12 and 13 show wind speed and direction
measurements taken during the study. FIG. 14 shows a plot of output
from the flow meter 259 measuring the flow rate of the controlled
emission source 250 of natural gas released.
[0081] Referring again to FIG. 2, with the data shown in FIGS. 11
through 14 steps 102 and 104 of the method 100 were performed to
obtain dimensionless emission plumes for each of the measurement
positions. Drawing samples from different elevations results in a
different Plume THC concentration profile at different levels. FIG.
15 shows the THC concentrations plotted against wind speed and wind
direction at the different heights for the period of November 1 to
December 17 when the controlled emission rate was 20.4 lpm. As the
figures show, the predominant wind direction during the study was
from southwest. The surfaces in FIG. 15 shows the average THC
concentration over that period compared to wind speed and
direction. FIG. 16 shows the same surfaces without the data points
focused in on wind directions from 200 to 300 degrees and wind
speeds of 0 to 25 kph. FIGS. 15 and 16 illustrate results obtained
after the completion of steps 102 and 104 of the method 100 in FIG.
2. FIGS. 15 and 16 show evidence of the emission plume in a
dimension of wind speed and direction at the different heights
(i.e. dimensionless). On there own, the plots in FIGS. 15 and 16 do
not indicate the physical size of the emission plume in measures of
meters but indicate the emission plume characteristics in terms of
wind angles and speeds. As expected, the plots show the highest
concentrations occur when the wind direction aligns with the
emission source 250 and the sampling tower 15 at low wind
speeds.
[0082] Changes in wind direction results in a shift in the sample
points 20 along a arc of a circle centered at the emission source
250 with the radius of the arc equaling the distance between the
emission source 250 and the sampling tower 15. The magnitude of the
shift is equal the number of degrees of wind change divided by 360
times the circumference (2*PI*r). For a one degree shift in wind
direction this would results in a 1.047 m shift in the sample inlet
20 position along the arc of the circle.
[0083] Referring again to FIG. 2, step 108 was performed and a set
of virtual sampling arcs were constructed using the obtained data.
Digitizing the surface in FIG. 16 into one degree increments of
wind direction and one kph of wind speed allows the emulation of an
array of virtual sample inlets that are 1.047 m apart forming a
virtual sampling arc at the height of the sample inlet 20 as
discussed earlier (note smoothing was used here by averaging the
adjacent readings with equal weight). There is a similar virtual
sampling arc for each sample inlet 20 at the different heights.
[0084] With the virtual sampling arcs constructed, step 110 was
performed and the constructed virtual sampling arcs were combined
into virtual sampling grids. Combining the virtual sampling arcs
for each of the sample inlets 20 resulted in the creation of a
virtual sampling grid of virtual measurement positions emulated by
the sampling inlets 20 at the different heights located 60 meters
away from the emission source 250 similar to earlier FIG. 7 except
the horizontal space will be much closer. The numbers populating
the table in FIG. 17 reflect the actual THC measurements taken
across this virtual sampling grid less the background level of 1.75
ppm (i.e. these are the THC levels above background levels) over
the time period November 1 and December 17 (20.4 lpm emission rate)
for the wind speed of 11 kph. Additional tables (not shown) could
also be generated for other wind speeds. The numbers in FIG. 17
show the increased THC level resulting from the emission plume.
These numbers change at different wind speeds for which another
similar table could be calculated.
[0085] The emission plume shape and concentration profile were then
determined based on the data. The resulting emission plume
boundaries and concentration contours are shown graphically for the
data in FIG. 18 and the other wind speeds of 3, 7, 15, and 19 kph
as well when the emission rate from the emission source 250 was
20.4 lpm. The numbers on the short axis represent the vertical
height in meters and the numbers on the long axis represent the
horizontal length along the grid of virtual measurement positions
(note zero represents the center of the emission plume). It is
important to realize that the surface in FIG. 18 is not flat as
represented but curves along the arc of the virtual sampling grid.
The contour images and 3D surfaces in the figures were generated in
mapping software call Surfer.TM. which converts the values measured
on the virtual sampling grid of virtual measurement positions into
the images using a kriging interpolation method. Similarly, FIGS.
19 and 20 show emission plume images for the time periods of
December 18 to January 17 (6.9 lpm emission rate) and October 10 to
30 (14.8 lpm emission rate).
[0086] The emission plumes images in FIGS. 18 to 20 represent the
average shape of the emission plume over the sampling period. The
uneven levels outside the plume reflect the "background noise" in
the method. The higher noise evident at low wind speeds in FIGS. 18
to 20 likely reflects errors at predicting the direction of the
bulk flow of air as it moves from the emission source 250 and the
sample points 20 based on a single measure of wind direction
located at the emission source 250. At higher wind speeds, the time
of travel from the emission source 250 to the sample points 20 is
less and likely reduces the error of predicting the direction of
the direction of the bulk flow of air. Some of the noise in FIGS.
18 to 20 is also due to errors in the THC measurement. In spite of
the background noise, the emission plumes are easily
distinguishable.
[0087] Referring again to FIG. 2, once the emission plume shape and
concentration profile was completed at step 112 of the method 100,
the emission rate from the emission source 250 was quantified using
step 114. Referring to FIG. 8, the method 200 was performed to
approximate emission rates for the emission source 250. The
quantification of the emission rate was accomplished by calculating
the flux of increased THC compounds crossing the virtual sampling
grid after dividing the virtual sampling grid into subsections,
[0088] Step 210 of the method was performed and the obtained
virtual sampling grid is divided into subsections. The vertical
spacing of the subsections is set by the vertical spacing of the
sample inlets 20 on the tower 12. The horizontal spacing of the
subsections can be set by the size of increments of wind direction
on which the data is aggregated. The increments can be small enough
to accurately characterize the emission plume (1 degrees was used
in the test). In FIG. 17 one degree was used to aggregate the data
which is associated with 1.047 m separation along the virtual
sampling arc. The boarders of each subsection are defined by half
the distance to the adjacent subsection center. If there is no
adjacent subsection as along the bottom of the virtual sampling
grid then the border is the ground (or something just above to
reflect there is little air flow along the ground). The top
boundary of the subsections along the top of the virtual sampling
grid is assumed as the same distance to the center of the
subsection as the bottom boundary (this upper boundary can also be
assume base on an extrapolated emission plume concentration profile
if the emission plume boundary extends above the virtual radial
sampling grid). The area of the subsections are calculated by
height *width if the elements are rectangular. FIG. 17 shows the
virtual sampling grid with the heights and widths the subsections
for a one degree wind direction aggregation.
[0089] With the virtual sampling grid separated into subsections,
step 220 of the method 200 shown in FIG. 8 was performed and a flux
value across each subsection was determined. The flux values were
obtained by multiplying the increased THC concentration (i.e. the
THC concentration less the background level of 1.75 ppm) by the
wind speed.
[0090] The THC concentrations shown in FIG. 16 were converted to
flux values and plotted with wind speed and direction in FIG. 21.
The plots show the THC flux of the emission plume for different
wind speeds and directions in a time period where there was a
single controlled emission rate.
[0091] Referring again to FIG. 8, step 230 was performed and the
subsections that were within the emission plume boundary were
determined for the different wind speeds. The increased THC
concentration flux plots like those in FIG. 21 were isolated for
some individual wind speeds and plotted against wind direction for
the three different controlled emission rates in FIGS. 22 to 24.
The modeled emission plume shape in the dashed line is a Gaussian
distribution fitted to the upper portion of the emission plume
shape by a linear regression of a natural log transformation of the
flux values. The boundary of the emission plume was taken to be the
point where the modeled flux breaks below some minimum flux level
(we are using 0.0067 L/(hr*m2)) on either side of the emission
plume peak. This allows the emission plume boundaries that exist
within the background noise to be approximated. A model is not
fitted and the emission plume is considered not definable when the
emission plume shape is not dominant above the background flux
values.
[0092] Referring again to FIG. 8, step 240 was performed to
determine the flowrate of the emission being measured through each
of the subsections. The compound flow rate through each subsection
was determined by multiplying the rate of flux of increased THC
determined for an area by the area of the subsection. Step 245 was
then performed and the flow rates throughout the emission plume
were totaled to approximate an emission rate of the emission source
250 shown in FIGS. 9 and 10.
[0093] Using method 100 shown in FIG. 2 and method 200 shown in
FIG. 8, emission flow rates were calculated for the three different
emission conditions and the for wind speeds from 1 to 19 kph. The
results are presented in FIG. 25 which shows the estimated emission
rate versus wind speed for the three controlled emission rates
during the study. There are three lines in the plots in FIG. 25
that show the expected controlled emission rates of 6.9, 14.8, and
20.4 lpm. The plots show fairly good agreement between the
estimated emission rates and the actual emission rates for wind
speeds above 7 kph (note the points for 6.9 lpm are lower at higher
wind speeds). The lack of agreement at lower wind speeds may be due
to the emission plume not being completely characterized because of
the inaccuracy in the directional estimates of the bulk air flow at
low wind speeds (i.e. lack of efficiency in capturing the emission
plume). The average estimated emission rate between 7 and 15 kph
was plotted against the expected controlled emission rate.
[0094] The background noise in the concentration profile across the
virtual sampling grid shown in FIGS. 23 to 25 can have an important
impact on quantifying the emission rate from the emission plume
concentration profile. An important affect is due to the value
selected for the background level.
[0095] The background level of emission has an important impact of
the estimates of the emission rate particularly at high wind speeds
because it acts across the entire emission plume area. The
sensitivity analysis of the background level of THC used levels of
1.72, 1.75, and 1.78 ppm and calculated the resulting estimated
emission rates. FIG. 26 shows the results of the analysis and shows
that estimated emission rates vary significantly with background
levels and the best agreement with expected emission rates uses a
background level of 1.75 ppm.
[0096] The background levels of THC measured through the project
showed some instability. The baseline levels were calculated for
the three emission rate periods by averaging the THC readings after
removing the reading corresponding to wind directions of 220 to 280
degrees (i.e. the emission source direction) and wind speeds less
than 7 kph (to avoid sporadic high reading at low wind speeds). The
average reading for the associated time periods are as follows:
[0097] October 10 to 30 (14.8 lpm emission rate) was 1.79 ppm
[0098] November 1 to December 17 (20.4 lpm emission rate) was 1.76
ppm [0099] December 18 to January 17 (6.9 lpm emission rate) 1.89
ppm. The emission rate estimates were calculated using these
different baselines for the different time periods and the results
are presented in FIG. 27. The average estimated emission rate was
calculated for wind speeds between 7 and 11 kph and plotted against
the expected emission rate in FIG. 28. There was some lack of
agreement that can be corrected by using the equation of the
regression line as the correction factors. FIG. 29 shows emission
rate estimates with the correction factors applied with good
agreement to the expected values.
[0100] The reason a correction is needed may be due to the
efficiency in isolating the emission plume or due to the background
noise in the raw data. Lack of efficiency in isolating the emission
plume means that we may only be capturing a portion of the THC
molecules leaving the emission source, which likely changes at
different wind speeds. This is related to the inaccuracies in
predicting the direction of the bulk flow of air. This would
explain the underestimation of the emission rate at lower wind
speeds. Understanding the efficiencies in capturing emission plumes
versus the accuracy of the wind data will allow wind measurements
to be taken a great distance from the emission source and
correction factors used to estimate the actual emission rate.
[0101] This study used many sampling inlets 20 at different heights
to characterize the emission plume exactly. In practice, emission
rate estimates can be made with far fewer and possible only one
measurement position using interpolation and extrapolation of the
vertical emission plume shape.
[0102] The modeled Gaussian distributions used to determine the
plume boundaries (see FIGS. 22 to 24) can also be used to establish
the smoothed average plume characteristic over the sampling period.
Levels of air concentration of THC (or any compound in question)
can be compared to the long term average using the exact wind speed
and direction at the time of collection. Changes in source emission
rate over time can be tracked by assuming deviations from the
long-term average are due to short-term changes in the source
emission rate. In this way one can predict changes in source
emission rates over time by attributing deviation from long term
concentration measures on a virtual sampling grid or virtual
sampling arc to changes in source emission rate.
[0103] Method 100 in FIG. 2 assumes that a distance to an emission
source is known. In some cases, the location of an emission source
may not be known and therefore the distance between a measurement
position and the emission source may also not be known. Knowing the
distance to the emission source allows one to convert the
dimensionless emission plume obtained from measured emission
concentrations to the appropriate scalar dimension. If the emission
source location is known, method 100 shown in FIG. 2 can be used to
quantify the emission source. If the emission source locations are
not known then method 100 may not be usable and quantifying the
emission source(s) may take a number of iterations and comparing
predicted locations and emission source sizes from a number of
measurement positions and looking for agreement.
[0104] FIG. 30 is a flowchart illustrating a method 300 for
quantifying one or more emission sources when the location of the
emission source(s) is not known and therefore the distance between
a measurement position and the emission source is not known. Method
300 is similar to method 100 shown in FIG. 2 but it includes
assuming a distance to the emission source and possible iteration
and comparing of predicted locations and sizes from a number of
measurement positions to look for agreement.
[0105] The method 300 starts and steps 302 and 304 are similar to
steps 102 and 104 in the method 100 shown in FIG. 2 wherein
measured emission concentration data and wind data are combined to
create data about a dimensionless emission plume.
[0106] At step 306 a distance to the emission source(s) is assumed
and then this assumed distance is used in step 308 to determine a
set of virtual sampling arcs. Steps 308, 310, 312 and 314 of method
300 can be performed in a similar manner to steps 108, 110, 112 and
114 of method 100 shown in FIG. 2, with step 314 using the method
200 shown in FIG. 8.
[0107] After step 314 is performed and the emission source is
quantified based on the distance to the emission source that was
assumed at step 306, the method 300 can continue to step 316 and
try to determine the emission source location by triangulating the
trajectory of identified emission plumes from multiple measurement
positions and looking for agreement in source characteristics as
described in PCT/CA2008/000080.
[0108] The location of an emission source can be approximated by
using two or more measurement locations, where each measurement
locations is spaced laterally apart from the other measurement
locations, to measure emission concentrations and combine them with
representative wind speeds and wind directions. The directions or
trajectories to the important sources identified by predominant
peaks in the plots of measured emission concentrations against the
associated representative wind speed and wind direction can be
projected outwards from each of the measurement locations.
Somewhere along the line of each projected trajectory may be an
emission source. These trajectories from the different measurement
locations may cross in the vicinity of an emission source. Because
multiple trajectories can be projected from each measurement
location, some trajectory paths may cross at locations that are not
leaks (ghost leaks). When more than two measurement locations are
employed, confidence in predicting emission source locations
increases if three or four trajectories cross. By computing
emission rates for candidate emission sources located at the
intersection of these trajectories, the existence of an emission
source can be asserted based on a substantial agreement between
candidate emission source emission rates by the different
measurement locations. The location of this asserted emission
source can then be used to approximate a distance to this asserted
emission source.
[0109] With the emission source location approximated at step 316,
the method 300 moves to step 318 and checks whether the assumed
distance to the emission source, used at step 306, agrees with the
distance to the emission source determined at step 316. If the
distance to the emission source assumed at step 306 agrees with the
distance to the emission source approximated at step 316, the
method 300 can move to step 320 and accept the location and
quantification of the emission source. However, if at step 318, the
distance to the emission source assumed at step 306 does not agree
with the distance to the emission source approximate at step 316,
the method 300 can return to step 306 and use the distance to the
emission source calculated at step 316 for the assumed distance to
the emission source. The method 300 can then perform steps 308,
310, 312, 314 and 316 using the calculated emission source to
construct the set of virtual sampling arcs, virtual sampling grids,
quantify the emission source, etc. At step 318, the method 300 will
once again check the distance to the emission source used at step
306 against an approximated distance to the emission source
determined in the subsequent step 316. In this manner, method 300
can iteratively perform the method 300 until the measured distances
to the emission source agree with the assumed distance to the
emission source to within an acceptable tolerance. When the assumed
distance and calculated distance are within an acceptable range,
the characteristics of the emission source can be accepted at step
420 and the method 300 can end.
[0110] In this manner, method 300 can be used to quantify one or
more emission sources when the location(s) of the emission
source(s) are not specifically known.
[0111] Virtual sampling arcs and virtual sampling grids of
measurement positions can be determined by assuming that the
emissions source is acting as a point emission source. However,
this may not always an accurate assumption. The methods described
herein are also applicable to other source configurations like area
emission sources or multiple emission sources of similar size.
Referring again to FIG. 2, the method 100 could also be used for
area emission sources. Steps 102 and 104 are performed with the
emission concentration measurements combined with wind data to
construct a dimensionless emission plume. Step 108 is then
performed and a set of virtual sampling arrays are constructed.
Unlike the virtual sampling arcs, these virtual sampling arrays may
not follow an arc but rather vary as a result of the area emission
course. Because the emission source is not being treated as a point
emission source, but rather an area emission source, the virtual
sampling arcs must be constructed in a slightly different manner
than when a point emission source is being assumed. In one aspect,
quantifying area emission sources can be accomplished by
envisioning that a measurement position gets a concentration
measurement of an emission plume from an area emission source
downwind from a "catchment" area of the area emission source.
[0112] FIG. 31 illustrates an area emission source 350 and a
measurement position 355 measuring emission concentrations
originating from a first catchment area 360A of the area emission
source 350. The measurement position 355 could be the sampling
tower 12 containing the sampling inlets 20 in the sampling system
10 shown in FIG. 1. Depending on the direction of the wind relative
to the area emission source 350 and the measurement position 355,
the measurement position 355 obtains measurements of the
concentration of emission from a number of catchment areas of the
area emission source 350. At different wind directions there will
be different catchment areas of the area emission source under
surveillance. FIG. 32 illustrates the area emission source 350 and
the measurement position 355 where the wind direction differs from
FIG. 31 and therefore the measurement position 355 is measuring the
emission concentrations from a second catchment area 360B of the
area emission source 350. FIG. 33 illustrates the area emission
source 350 and the measurement position 355 when the wind has yet
another direction and the measurement position 355 is measuring the
emission concentrations from a third catchment area 360C of the
area emission source 350.
[0113] Area emission sources will have a more complex curve that
will be centered at a representative center 362 of the catchment
areas 360, a representative distance from the measurement position
355. The representative distance is the distance between the
measurement position 355 and the representative center 362 of the
catchment area 360 of the area emission source 350 being measured.
This representative distance may be variable depending on the
catchment area 360 being measured by the measurement position 355.
This representative center of an area emission source or subsection
of an area emission source is the position whose distance to the
measurement position will provide the appropriate emission rate
when used in the quantification steps of this procedure. In one
aspect, the centroid of the catchment area 360 may be used as the
representative center. The scalar width of the emission plume for
each wind direction will be based on the representative distance to
the representative center 362 of the catchment area 360 being
measured and can be calculated as follows:
ScalarWidth = AngulaWidth 360 .times. Circumference = AngularWidth
360 .times. 2 .times. .pi. .times. r [ 5 ] ##EQU00003##
wherein r is the representative distance to the catchment area
slices.
[0114] FIG. 34 shows the area emission source 350 and the
measurement positions 355 wherein the area emission source 350 is
divided into measurement catchment areas 360 related to different
wind directions. FIG. 35 shows how the single measurement position
355 can be represented as a series of virtual measurement positions
358 related to measurement catchment area 360 slices. The distance
between the virtual measurement positions 358 can be determined
using Equation [5] to determine the arc length of a circle with the
radius equal to distance between measurement position and the
representational center. In this way the angular plume horizontal
dimension can be converted into a scalar horizontal dimension to
construct a virtual sampling array. Unlike the earlier described
virtual sampling arcs, the area emission source forms a virtual
sampling array that will necessarily follow the curve of an arc but
may vary in curvature along its length as shown in FIG. 35. The
change of emission plume intensity along the horizontal dimension
can also be used to map out the regions of the area emission source
that have higher (or lower) emission rates particularly if observed
from multiple measurement positions.
[0115] Referring again to FIG. 1, with virtual sampling arrays
created for measured emission concentrations at the measurement
position 355, step 108 has been performed and the method 100 can
continue on to step 110 and use the constructed virtual sampling
arrays to construct one or more virtual sampling grids before
performing steps 112 and 114 and quantifying the area emission
source 355.
[0116] The measurement point for an area emission source do not
need to necessarily be located outside the area emission source,
rather it might be located within the area emission source. FIG. 36
illustrates an aspect where a measurement position 375 is located
inside an area emission source 370. As the wind changes direction,
the emission plume from a different catchment area 380 will arrive
at the measurement position 375. The changing wind direction will
expose the measurement position 375 to a different portion of the
area source emission 370. The catchment areas 380 will be like pie
slices. FIG. 37 shows how the single measurement position 375 can
be represented as a series of virtual measurement positions 385
related to measurement catchment area 380 slices. The distance
between the virtual measurement positions 385 can be obtained using
Equation [5] to determine an arc length of a circle with a radius
equal to the distance between the measurement position 375 and the
representative center 382 of the measurement catchment area 380
slice. In this way, a measurement position 375 inside an area
source emission 370 can be used to stretch out the angular plume
dimensions, convert them to scalar dimensions and construct a
virtual sampling array to be used to approximate the emission rate
of the area emission source 370. Again, areas of higher (or lower)
emission rate can be identified particularly if multiple
measurement positions are used.
[0117] If emission plumes from multiple sources can be
differentiated then they can be quantified separately. Observation
positions from other locations can help to differentiate the
emission plumes. Emission plumes that result from multiple point
sources and cannot be differentiated can be quantified as a group
(i.e. an area emission source). The distance from the measurement
position to the area emission sources can be taken to the centroid
of the group of sources or to an imaginary central focus point
upwind of the group of emission sources.
[0118] An area emission source can be treated as a point source if
the observation position is far enough away from the area emission
source. Quantifying emission rates from area emission sources can
be done by having measurement positions strategically located in
and around the area emission source. If there is no evidence of hot
spots (sub areas of higher emission rate) then the area emission
source can be treated as having a homogenous emission rate and the
emission plume generated will reflect the area of the emission
source in the upwind fetch. If the plume is not homogenous and
higher emission rates are evident from sub-areas of the larger
emitting area, then relating emission plume intensities to sub-area
emission rates from multiple measurement positions and then
quantifying the sub-area emission rates and asserting the locations
and pattern of the sub-area emission rates based on agreement from
multiple measurement positions. The overall emission rate is then
determined by totaling the sub-area emission rates across the
entire area emission source.
[0119] The scalar width of an emission plume originating from an
area emission source can be assumed to be the same width as the
area emission source it self. The increased width due to the
emission plume dispersing at the edges of the emission plume may be
less important than the emission plume width established by the
width of the area emission source. The position of the measurement
position relative to the area emission source can be used to adjust
the plume scalar width for different wind speeds,
[0120] In a further aspect, these techniques can be used with data
collected from mobile monitoring equipment. With knowledge of the
position of the detectors in motion, actual sampling arcs, arrays
and grids (for steps 108 and 110 of method 100 shown in FIG. 2 or
steps 208 and 210 of method 200 shown in FIG. 8) can be developed
to intercept emission plumes, delineate emission plume boundaries
and determine emission plume trajectory. Emission plume
trajectories from multiple sampling positions can be used to
determine the location of the emission sources using triangulation
techniques.
[0121] Many applications for the systems and methods described
herein can be envisioned including: emission from a large area
source like a city could be measured this way; emission from a
large tailing pond could be measured with these techniques;
military applications, measurement from moving vehicles; homeland
security, monitoring for releases of nerve agents in a city;
etc.
[0122] In another aspect, treating the emission source as an area
emission source could be useful in situation where the emission
plumes are so large that you cannot get far enough away to assume
the emission source is a point emission source. For example, this
approach could quantify emission of an entire city to find the
overall emission rate and the location and timing of emission from
sub areas of the city.
[0123] In a further aspect, this approach could be useful to
provide surveillance of attacks with air borne agents being
released in a city,
[0124] Emission plumes can be visualized and characterized with
measures of air concentrations taken down wind. Knowing the shape,
size, and concentration profile of the emission plume at different
wind speeds enables a flux calculation to predict the associated
emission rate of the source causing the plume.
[0125] The previous description of the disclosed embodiments is
provided to enable any person skilled in the art to make or use the
present invention. Various modifications to those embodiments will
be readily apparent to those skilled in the art, and the generic
principles defined herein may be applied to other embodiments
without departing from the spirit or scope of the invention. Thus,
the present invention is not intended to be limited to the
embodiments shown herein, but is to be accorded the full scope
consistent with the claims, wherein reference to an element in the
singular, such as by use of the article "a" or "an" is not intended
to mean "one and only one" unless specifically so stated, but
rather "one or more". All structural and functional equivalents to
the elements of the various embodiments described throughout the
disclosure that are known or later come to be known to those of
ordinary skill in the art are intended to be encompassed by the
elements of the claims. Moreover, nothing disclosed herein is
intended to be dedicated to the public regardless of whether such
disclosure is explicitly recited in the claims.
* * * * *