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Electronic Theses and Dissertations, 2004-2019

2012

Monitoring And Modeling To Estimate Hydrogen Sulfide Monitoring And Modeling To Estimate Hydrogen Sulfide

Emissions And Dispersion From Florida Construction And Emissions And Dispersion From Florida Construction And

Demolition Landfills To Construct Odor Buffering Distances Demolition Landfills To Construct Odor Buffering Distances

Steven Jeffrey Bolyard University of Central Florida

Part of the Environmental Engineering Commons

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STARS Citation STARS Citation Bolyard, Steven Jeffrey, "Monitoring And Modeling To Estimate Hydrogen Sulfide Emissions And Dispersion From Florida Construction And Demolition Landfills To Construct Odor Buffering Distances" (2012). Electronic Theses and Dissertations, 2004-2019. 2099. https://stars.library.ucf.edu/etd/2099

MONITORING AND MODELING TO ESTIMATE HYDROGEN

SULFIDE EMISSIONS AND DISPERSION FROM FLORIDA

CONSTRUCTION AND DEMOLITION LANDFILLS TO CONSTRUCT

ODOR BUFFERING DISTANCES

by

STEVEN JEFFREY BOLYARD, E.I.

B.S.C.E. University of Central Florida, 2008

B.S.Env.E. University of Central Florida, 2008

A thesis submitted in partial fulfillment of the requirements

for the degree of Master of Science in Environmental Engineering

in the Department of Civil, Environmental, and Construction Engineering

in the College of Engineering and Computer Science

at the University of Central Florida

Orlando, Florida

Spring Term

2012

ii

© 2012 Steven J. Bolyard, E.I.

iii

ABSTRACT

Emissions of hydrogen sulfide (H2S) from construction and demolition (C & D) landfills can

result in odors that are a significant nuisance to nearby neighborhoods and businesses. As

Florida’s population continues to grow and create development pressures, housing is built closer

to existing landfills. Additionally, new landfills will be created in the future. This research

project was undertaken to develop a detailed modeling methodology for use by counties and

other landfill owners to provide them with an objective and scientifically defensible means to

establish odor buffer zones around C & D landfills.

A technique for estimating methane (and odorous gas) emissions from municipal solid waste

(MSW) landfills was recently developed by researchers at the University of Central Florida. This

technique was based on measuring hundreds of ambient methane concentrations near the surface

of the landfill, and combining that data with matrix inversion mathematics to back-solve the

dispersion equations. The technique was fully documented in two peer-reviewed journal articles.

This project extends that methodology. In this work the author measured ambient H2S

concentrations at various locations in a C & D landfill, and applied those same matrix inversion

techniques to determine the H2S emission rates from the landfill. The emission rates were then

input into the AERMOD dispersion model to determine H2S odor buffer distances around the

landfill.

Three sampling trips to one C & D landfill were undertaken, data were taken, and the modeling

techniques were applied. One problem encountered was that H2S emissions from C & D landfills

are typically about 1000 times smaller than methane emissions (from MSW landfills). Thus, H2S

iv

ambient concentrations often are near the detection limits of the instruments, and the data may

not be as reliable. However, this approach could be used for any particular C & D landfill if the

appropriate amount of data were available to characterize its emissions with some certainty.

The graphical tool developed in this work shows isopleths of “H2S” concentrations at various

distances, and color codes the isopleths into a “green-yellow-red” scheme (analogous to a traffic

signal) that depicts zones where private landowners likely will not detect odors, where they may

experience some odors, or where they likely will experience odors. The “likelihood” can be

quantified by selecting the Nth

highest hourly concentrations in one year to form the plot. In this

study, N was conservatively selected as 8. Requiring that concentrations be at or below the 8th

highest concentration in a year corresponds to a 99.9% probability of not exceeding that

concentration at that distance in any future year.

The graphical tool can be applied to any C & D landfill but each landfill is different. So this

technique depends on having a fairly good estimate of the rate of emissions of H2S from the

landfill in question, and at least one year’s worth of hourly meteorological data (wind speed,

direction, and stability class) that is representative of the landfill location. The meteorological

data can be obtained with relative ease for most locations in Florida; however, the emission data

must be obtained from on-site measurements for any given landfill.

v

For my parents; their continuing emotional and financial support throughout the past eight years

has been imperative to my successes during my collegiate career.

vi

ACKNOWLEDGMENTS

The author would like to acknowledge both The Hinkley Center for Solid and Hazardous Waste

Management for their financial support of this research; and my advisor, Dr. C. David Cooper

for his persistent support and enduring patience during the past three years. Additionally, I would

like to acknowledge my wife’s unrelenting fervent support for my accomplished and ongoing

goals; both academic and professional.

vii

TABLE OF CONTENTS

LIST OF FIGURES ..................................................................................................................... viii

LIST OF TABLES ......................................................................................................................... ix

INTRODUCTION .......................................................................................................................... 1

BACKGROUND ............................................................................................................................ 4

METHODS ................................................................................................................................... 16

Step One: Obtain H2S Concentrations and Atmospheric Data ................................................ 16

Step Two: Estimate H2S Emissions ......................................................................................... 19

Step Three: Determine H2S Concentration Limits ................................................................... 21

Step Four: Perform Air Dispersion Modeling (AERMOD) ..................................................... 22

Step Five: Establish Odor Buffering Distances (Florida C & D landfills) .............................. 24

RESULTS ..................................................................................................................................... 25

Sensitivity Analysis .................................................................................................................. 33

CONCLUSIONS........................................................................................................................... 38

RECOMMENDATIONS .............................................................................................................. 43

APPENDIX A: FIELD DATA – MEASURED H2S CONCENTRATIONS AND THEIR

LOCATIONS ................................................................................................................................ 44

APPENDIX B: CALCULATED EMISSIONS AND SOURCE LOCATIONS (FROM

MATLAB) .................................................................................................................................... 50

APPENDIX C: PREDICTED OFF-SITE CONCENTRATIONS (FROM AERMOD) .............. 54

REFERENCES ............................................................................................................................. 76

viii

LIST OF FIGURES

Figure 1: Weather Profile for Site Visit #1 ................................................................................... 17

Figure 2: Weather Profile for Site Visit #2 ................................................................................... 18

Figure 3: MATLAB Receptor and Source Locations (Entire Landfill) Site Visit #1 ................... 25

Figure 4: MATLAB Receptor and Source Locations (Active Face) Site Visit #1 ....................... 26

Figure 5: MATLAB Receptor and Source Locations (Entire Landfill) Site Visit #2 ................... 26

Figure 6: MATLAB Receptor and Source Locations (Active Face) Site Visit #2 ....................... 27

Figure 7: MATLAB Receptor and Source Locations (Entire Landfill) Site Visit #3 ................... 27

Figure 8: MATLAB Receptor and Source Locations (Active Face) Site Visit #3 ....................... 28

Figure 9: AERMOD Receptor Grid Spacing Example ................................................................. 29

Figure 10: Plot of H2S Concentrations around the active landfill face for Site Visit #1 .............. 31

Figure 11: Plot of H2S Concentrations around the active landfill face for Site Visit #2 .............. 32

Figure 12: Plot of H2S Concentrations around the active landfill face for Site Visit #3 .............. 33

Figure 13: Minimum Odor Buffer Distances based on the First Site Visit .................................. 40

Figure 14: Minimum Odor Buffer Distances based on the Second Site Visit .............................. 41

Figure 15: Minimum Odor Buffer Distances based on the Third Site Visit. ................................ 42

ix

LIST OF TABLES

Table 1: List of Contacted Landfills ............................................................................................. 15

Table 2: Pertinent Site Visit Data and Calculated Emissions ....................................................... 21

Table 3: Base Case Data – Site Visit #1 ....................................................................................... 34

Table 4: Percent Change in Estimated Emissions from Base Case for Site Visit #1 (at base

Stability Class D) .......................................................................................................................... 35

Table 5: Base Case Data – Site Visit #2 ....................................................................................... 35

Table 6: Percent Change in Estimated Emissions from Base Case for Site Visit #2 (at base

Stability Class B) .......................................................................................................................... 36

Table 7: Base Case Data – Site Visit #3 ....................................................................................... 36

Table 8: Percent Change in Estimated Emissions from Base Case for Site Visit #3 (at base

Stability Class D) .......................................................................................................................... 37

Table 9: Emissions Sensitivity to Stability Class ......................................................................... 37

Table 10: Minimum Odor Buffering Distance for Landfill .......................................................... 38

1

INTRODUCTION

Current population trends for both the United States and the State of Florida demonstrate

continuing significant increases in population, and thus significant pressures to develop

previously undeveloped land. Thus, undeveloped, sparsely-populated land is quickly becoming

converted into suburban neighborhoods. The urbanization of America presents many issues;

however, the increased interaction between constituents living in residential neighborhoods, and

solid waste disposal facilities is the relevant issue concerning this thesis. As such, the most

widely attributable conflict between landfills and citizens centers around the fugitive odors that

are emitted by the waste disposed at the landfill site.

The research methods presented in this work will aid in determining an area, or boundary,

outside of which the landfill operators can be 99.9% certain that future odors will not exceed a

predetermined level. In order to establish such odor buffering distances, this author utilized

several techniques that were recently developed in previous research conducted at UCF, which

resulted in two published journal articles.1,2

The first project helped determine the main research

methods, mathematical techniques, and computer programs to be used in determining odorous

source emissions. The second project applied these practices to Municipal Solid Waste (MSW)

landfills. The main program used in air dispersion modeling (leading to the recommended odor

buffering distances), is AERMOD (American Meteorological Society/Environmental Protection

Agency Regulatory Model). AERMOD was chosen over other potential models because of its

ease of use and user familiarity.

2

Odor concerns from C & D landfills are not entirely new issues. The buffer distance chart

developed by this thesis would be a useful tool in determining the area that a particular landfill

authority should acquire in advance of the placement of a new landfill, should acquire around a

current landfill, or to recommend the re-zoning of non-residential development before such

development encroaches upon it. Landfill operators would no longer need to field substantial

complaints before action was taken in regards to odor complaints. The complaints themselves

would not be as likely, since buffer distances could be created in advance, thus reducing the

incidence of off-site fugitive odors.

The differences in the utilization of area surrounding the landfill, and the time of day that these

areas are occupied by individuals are a primary factor in fielding community odor complaints.

Complaints vary by the land use type with which they are associated. Residential, Commercial,

Industrial, and Agricultural lands all have varying uses; as such, the complaints, and type of

complaints will vary greatly from one location type to another. Industrial and Agricultural zones

will have fewer complaints considering their current usage of the inhabited area; an individual is

less likely to be present for long periods of time at one location, and activities at such sites

could/will be producing their own emissions that could overpower fugitive odors. Conversely,

residential and commercial sources are locations that have protracted periods of human

occupation and involvement. Residential zones are especially sensitive areas for two reasons.

First, most residents have a valued personal stake in that specific property location, and second,

the amount of time that an individual spends at their residence could vary from a few hours per

day, up to and including the whole day. This represents significantly more time than they would

have experienced at any commercial, industrial, or agricultural location. It is for this reason that

3

most of the complaints fielded by landfill officials tend to be from residential communities; in

particular, new communities that have recently been constructed near previously undeveloped

and sparsely populated land.

4

BACKGROUND

Odors present serious challenges for air quality officials as they are exceptionally variable in

their location, duration, and intensity. Such odors can be present at any or all hours of the day, or

be absent altogether. Daily, weekly, monthly, seasonal, and even yearly variations exist, and

further contribute to the unpredictability. Relevant topics when considering the history of odor

modeling include: the creation of odors, composition and detection of odors; the foundation of

the mathematical techniques and concepts utilized in modeling; the pros and cons of AERMOD

(the primary air dispersion model utilized); and previous attempts at defining odor buffer

distances.

The first steps in determining an odor buffer distance method is to determine what factors

contribute to an odor, its creation, emission, detection, and dispersion. Although this thesis

centers upon detecting hydrogen sulfide (H2S), there are a myriad of odor causing compounds

present in landfill gas emissions. Such volatile organic odor categories include mono-aromatics,

halogenated compounds, aldehydes, esters, ketones, organo-sulfur/nitrogen compounds, and

volatile fatty acids.3 However, for C & D landfills, H2S is the primary constituent of concern

because household wastes are excluded from C & D landfills. To better understand the emissions

of H2S, one must first determine the origin and composition of the sulfur containing materials

that leads to the creation of H2S. The primary constituent of C & D landfills that supplies the

element sulfur is drywall, or gypsum board. Gypsum board contains a high percentage of

calcium sulfate (CaSO4), which anaerobic bacteria metabolize to create H2S. Sulfate reducing

bacteria (SRB) can utilize this compound as their electron acceptor producing hydrogen sulfide

as an end product.4 The H2S gas then diffuses through the waste layers and is ultimately released

5

into the atmosphere from many locations along the soil surface of the landfill. The quantity of

gas released is dependent upon numerous factors, including the age of waste, closure status,

supply of gypsum board, top cover thickness and composition, and landfill moisture, among

others. Once the odorous emissions are released into the atmosphere, their dispersion (and

resulting concentrations downwind), is dependent upon factors such as wind speed, wind

direction, atmospheric stability class, temperature, terrain profiles, elevation, and others.

Several methods have been developed to detect and quantify odors once they are emitted. Some

of those methods include portable field instruments, lab-based gas chromatograph-mass

spectrometers, electronic noses, odor indexes, and human panels utilizing dilution

olfactometry3,5,6

all of which will be discussed in further detail later in this section. Individuals

react to odors differently depending upon their concentration and duration. Some individuals can

detect hydrogen sulfide concentrations as low as 0.5 part per billion by volume (ppbv), but a

more realistic detection level in the field would be around 5 ppbv.7 Coincidentally, the Jerome

Meter (one of the most sensitive field instruments on the market) has a lower detection limit of

about 1 ppbv. However, detection does not equal annoyance, and it is unrealistic to use the

minimum detectable level of an odor to set a buffering distance. Therefore in this project, the

recommended buffer distance was based on annoyance levels of 15, 30, and 100 ppbv.

Human panels (dilution olfactometry) represent one method of odor determination. A human

odor panel consists of several willing participants to essentially “smell out” odor thresholds. The

panelists are given fresh, uncontaminated air, mixed with a known concentration of the specified

odor, in this instance hydrogen sulfide. The samples are repeatedly diluted, and the panelists use

6

their sense of smell repeatedly, until half of them can no longer detect the presence of odors in

the samples they are given. One positive aspect is that the type of odor being examined is kept

constant. That is, since there are multiple odorous compounds in a landfill, when the panelists are

given a controlled sample; there is no bias as to which odor they smell. Conversely, the human

nose is not a definitive scientific instrument. The panelists’ abilities may vary considerably.

Therefore, one would need to utilize a large number of panelists to minimize the human error.

Additionally, since an odor buffer distance is unique to each specific landfill, one might consider

using local citizens who reside near the selected landfill as panelists. Lastly, dilution

olfactometry is limited when considering large variability in odors. Therefore, when numerous

odors are present, odor can be expressed in a definitive term of odor units, based upon the odor

threshold of the panelists. Since these odor units will be based upon human detectors, their

significance should be limited to the specified landfill; which will have varying quantities and

compositions of pollutants at varying times.8

One possible method for quantification of odors is the Odor Unit (OU/m3). The standard

European Odor Unit (OUE) is based upon the amount of odor that is diffused into one cubic

meter of standard air at standard pressure and temperature that can be detected by 50% of a

human test panel.9 For hydrogen sulfide, a previous study has concluded that 1 OU is equal to

approximately 9 ppbv.10

For comparison, during the first site visit to the landfill utilized in this

project, the majority of readings were between 0 and 3 ppbv. None of the researchers recording

data, or the landfill representatives were able to detect any presence of odor on that day.

7

Odor indices are an emerging possibility for the detection, quantification, and ultimately the

determination of odor buffering distances around landfills. Odor indexes essentially detect odors

by utilizing a known constituent present in the atmosphere around a landfill, and estimate a

sensible ratio between it and the odor of choice.8 One such possibility in determining the

dispersion of a relatively non-reactive odor species such as hydrogen sulfide is methane. Recent

studies have shown that using known methane concentration, emission, and dispersion data for a

specified MSW landfill can be used to estimate odorous emissions when coupled with an

appropriate gas ratio.11

Possible gas ratios between hydrogen sulfide and methane, (H2S ppmv /

CH4 ppmv) from ordinary MSW landfills have been shown to be in the range of 0.00004, to

0.02222.11

This range varies by over 555 times. A more representative range of ratios once the

outliers have been removed is between 0.00004 and 0.00087, for an effective range of

approximately 22.11

Once the dispersion model is developed for methane, using H2S

concentration measurements and appropriate modeling tools, the selected ratio can be applied

and the odor levels can be estimated for any specified landfill. It should be noted that in this

method, certain factors were excluded, such as constituent reactivity, molecular weight, and wet

or dry removal as they all relate to dispersion.8

Once researchers have sound methods of detection, one must quantify just how significant the

odor issue can be. The average content of drywall (by mass) in a typical Florida C & D waste

stream in 1998 was 11%.12,13

The total amount of C & D waste generated in Florida for the year

2000 was between 4.2 and 5.9 million tons (average of 5.05 million tons).12,13

Nationwide, the

estimates are assumed to be nearly 128 million metric tons of debris.13

Based upon this data, the

annual amount in 2000 of sulfur-containing gypsum board in Florida C & D landfills is about

8

555,000 tons. Such a large mass of drywall can lead to considerable hydrogen sulfide emissions,

depending upon the conversion efficiency of the landfills where the waste is deposited. Florida’s

total C & D contribution is considerably less on a national scale when considering that Florida

represents about 6% of the US population, but Florida generated only about 3% of the national C

& D debris total.13

It should be noted that these figures do not account for the most recent housing

bubble, which was disproportionately distributed in Florida, along with several other states.

Therefore, the amounts of C & D debris received by local landfills may be substantially higher

than previous figures for the past several years. Although the recent housing bubble has since

collapsed, and C & D debris levels will have been reduced accordingly.

The current mathematical methods and techniques utilized in our odor buffering distance

calculations include Voronoi Diagrams, importance sampling, solving the Gaussian Dispersion

Equations for sources, and AERMOD modeling. All of these techniques and the corresponding

MATLAB programs were developed and applied to Municipal Solid Waste (MSW) Landfills in

previous research conducted at UCF.1,2,11,14

The primary basis for most atmospheric dispersion

modeling programs is centered upon the Gaussian Dispersion Equation:

(

)( (

( )

) (

( )

)) (1)

Equation (1) is the general form of the Gaussian Dispersion Equation, where C is the steady-state

concentration in (μg/m3) at a specific point (x,y,z), Q is the emission rate in (μg/s), σz and σy are

the vertical and horizontal spread parameters, that are themselves functions of the distance (X)

9

from emission, and atmospheric stability class, u is the average wind speed measured at the stack

height in (m/s), z is the vertical distance above the ground in (m), y is the horizontal distance

from the centerline of the plume in (m), H is the effective height of the stack in (m). Considering

that the hydrogen sulfide emissions from the landfill are at ground level, Z = 0, and H=0 in the

preceding equation, reducing equation (1) to the following equation:

(

) (2)

Equation 2 can then be rearranged and solved for Q; yielding the sources for a single receptor-

source pair at a given emission level. Equations 3 and 4 represent the dispersion spread

parameters.

(3)

(4)

The variables a, b, c, d and f are curve-fitted constants that are dependent on downwind distance

and atmospheric stability classification. After the source emissions are quantified, the location of

these sources must be determined using the Voronoi Diagrams.

Voronoi Diagrams, with some modifications considering importance sampling, form the basis of

geographic source location from given receptor locations (locations where air was sampled and

10

concentration readings were recorded using a Jerome meter). The first step in the source location

process involves defining the receptor locations for the given data set within a defined landfill

boundary. Each receptor has an X and Y coordinate accompanying its concentration data. These

locations are utilized to construct a Voronoi Diagram composed of Delaunay Tessellations (a

Voronoi Diagram composed of only three sides)1. A Voronoi Diagram is a specific type of

spatial decomposition. Each given point (receptor) has an associated polygon drawn around it.

The interior space of this polygon around the specified point consists of all points that are closer

to one receptor rather than another. Therefore, the perimeters that form the polygons are made up

of points that lie at equidistant lengths between neighboring receptor points. Any points that are

constructed outside of the defined landfill boundary are not included in source estimation. Once

the Voronoi polygons have been formed, the actual source locations are determined by drawing a

perpendicular line at the midpoint of each line that forms the various triangulations (perimeter

lines of their respective polygons). The location at which three of these perpendicularly drawn

lines intersect is the physical location of the source.11

Further information pertaining to the

mathematical techniques utilized in this thesis can be found in the two previous UCF research

projects, and published papers regarding their work.1,2,11,14

Once all of the determinations have been made regarding source location and emissions, then

dispersion modeling can be done. First, the researchers obtained site specific meteorological and

geographic data, and then ran AERMOD. It is a model based upon planetary boundary layer

turbulence structure and scaling concepts, including treatment of both surface and elevated

sources, considering both simple and complex terrain profiles.15

AERMOD has replaced the ISC

model for short range, steady state Gaussian plume modeling. The main benefits of AERMOD

11

over ISC are that surface roughness can be specified precisely in AERMOD versus only

choosing “rural” or “urban” in ISC. The mixing heights are determined automatically from the

meteorological preprocessor AERMET, versus arbitrarily by the user in ISC. Lastly, since wind

speeds were very low during both monitoring events, AERMOD accounts for the meandering of

the plume at small wind speeds, and ISC does not. Lateral plume meander is the slow lateral

back-and-forth shifting of the plume in response to lateral eddies that are larger than the

plume.16,17

The methods utilized in this research project have some advantages over other traditional

techniques; such as a flux chamber. Issues with flux chambers are the extensive time and labor

associated with them, bias caused by pressure build up, and/or chamber-surface interactions. As

a result of these drawbacks, flux chamber studies do not typically have large sample populations,

and this can lead to highly variable results which will potentially result in large errors in final

calculations.2 Small sample populations also make determining odor buffering distances difficult

because the concentration contour lines on the map will tend to “jump about.” This “jumping

about” leads to very jagged, non-smooth, and highly irregular contour concentration lines around

the landfill.

However, the methods used in thesis research project could have some potential drawbacks,

including instrument sensitivity and sensitivity of results to determination of the correct

meteorological conditions. The important meteorological parameters are wind speed, wind

direction, and atmospheric stability class; the predicted results depend heavily on the accurate

measurement of these meteorological variables over the time span of a sampling event. Other

12

parameters such as waste height, presently managed status, characteristics of the waste, and post-

closure management all affect the emission of gases from a landfill.18

Atmospheric stability influences how emissions disperse, and the selection of the stability class

for input into the MATLAB program greatly influences the modeling predictions. The main

equations that are utilized by a wide variety of dispersion models are the standard Gaussian

dispersion equations. These equations assume that the stability class, wind speed, and wind

direction remain constant throughout the duration of the field data collection. Inputting a

different stability class into the emissions model and holding all other parameters constant can

potentially change the predicted emissions by as much as 84%.11

Other parameters that greatly

affect the predicted results are wind speed and wind direction. Using incorrect values for these

parameters will have similar effects on the final results as with stability class. It is therefore

important to accurately and consistently determine all the meteorological parameters during the

field measurements of H2S concentrations. Since this is a complex issue, and since these

parameters may change during the sampling event, it is better to try to do the sampling during

conditions that remain as constant as possible. Small errors in measuring wind speed and/or

slight differences among observers in judging the cloud cover or solar insolation, as well as site

specific variables relating to local geography and weather, can often result in the stability class

being one class different between two different observers when using the Pasquill-Gifford

method (P-G). The P-G method was the first easily applicable and identifiable method for

estimating atmospheric stability classes based upon solar insolation, wind speed, and cloud

cover. In contrast, the AERMOD program incorporates the Monin-Obukhov Length method

(MO). Although the two methods determine stability classes differently, one study revealed that

13

the variations between the two methods were not nearly as significant as with the many other

stability class determination techniques. The two different methods P-G and M-O correctly

predicted stability class B 85% of the time during a comparison analysis.19

Past attempts at establishing odor buffering distances around area sources have generally

concentrated on agricultural contributors such as pig (porcine), chicken (poultry), and cattle

farms; or wastewater treatment plants.20

However, some previous research does allude to

possible odor buffering distances from landfills. Additionally, some of the determinations from

agricultural area sources may also be applicable (and transferrable) to landfills. Current

regulations regarding odors in California and Massachusetts, as well as prior research into the

matter of odor thresholds concerning landfills were examined. A level of 30 ppbv H2S is

currently the maximum one-hour standard in both California and Massachusetts. Additionally,

Massachusetts has an eight-hour concentration standard of approximately 15 ppbv.21

One of several previous research projects described methods for odor buffering distances from

livestock buildings. The buildings studied were located in Europe, and the model utilized was the

Austrian Odour Dispersion Model (AODM). The odor threshold levels selected for study were 1,

3, and 5 odor units. These were selected based upon available information regarding odor

standards in local European countries. Most of these regulations revolved around 1, 2, 5, and 10

OUs.22

From a Singapore study done regarding wastewater treatment facilities, the average 1, 3,

and 5 OU thresholds for the pumping station and the treatment plant would most nearly be 9, 26,

and 49 ppbv (H2S).10

14

The landfill selected for this research project was chosen after an extensive search. First, several

databases on C & D landfills were located via the internet which returned multiple possibilities.

The majority of the located landfill databases were procured form Florida Department of

Environmental Protection (FDEP) websites. Second, the lists of landfills had to be condensed to

lists of open and active C & D landfills. Once currently operating C & D landfills were located,

the researcher attempted to contact the located landfills in order of their proximity to the UCF

campus. Landfills in Orange and Seminole county were contacted first, followed by Volusia,

Brevard, Osceola, Lake, Polk, and finally Marion counties. A table of the contacted landfills and

their participation status is listed in

Table 1. Although several landfills showed promise, only one was particularly well suited for

this study. The selection criteria were the distance from UCF, ease of access, local residence

odor annoyance complaints, and equipment accessibility. Since no complaints could be located

for any of the participating landfills, and the location of the landfills willing to participate was

not excessively far from UCF, the main criterion became the equipment and instrument

availability. As this researcher did not have access to any field monitoring equipment, it was

very helpful that the selected landfill and their resident engineering firm both had all of the

necessary field equipment already available. The two main pieces of equipment were an on-site

weather station and a Jerome Hydrogen Sulfide Meter.

Although numerous landfills were contacted, few were willing to participate in this research

project. Landfill representatives seemed to be concerned with the political, social, and monetary

repercussions of participating in such a research project. This was by far the greatest hurdle in

executing this research; finding willing participants. The problem was exacerbated by the fact

15

that the majority of C & D landfills are privately owned. The author believes that negotiating

with government owned and/or operated facilities would have been considerably easier.

Table 1: List of Contacted Landfills

Name County Address Distance to

UCF (mi)

Clyde Morris Volusia 925 South Clyde Morris Blvd, Daytona Beach, Fl 32114 55.4

Samsula Volusia 363 South SR 415, New Smyrna Beach, Fl 32168 38.3

Pine Ridge Orange 5400 Rex Dr, Winter Garden, Fl 34787 35.0

Bass Road Osceola 750 South Bass Road, Kissimmee, Fl 34746 38.7

West Orange

Environmental Orange 7902 County Rd 545, Winter Garden, Fl 34787 35.3

Four Jays Recycling Volusia 425 South SR 415, New Smyrna Beach, Fl 32168 38.1

Mid Florida Materials Orange 3602 Golden Gem Rd, Apopka, Fl 32712 42.0

Flagler County C & D Flagler 1700 Old Kings Rd South, Flagler Beach, Fl 32136 75.5

Flagler CDS Flagler 2190 County Rd 13, Bunnell, Fl 32110 79.4

SR 545 Orange 8050 SR 545, Winter Garden, FL 34787 35.4

Northeast Landfill

Southeast Landfill Polk 7399 Decastro Rd, Winter Haven, Fl 33880 69.1

Lake County Landfill Lake 13130 County Landfill Road, Tavares, Fl 32778 51.8

Indian River County

Landfill

Indian

River 1325 74th Ave SW, Vero Beach, FL 32968 95.8

Kirton-Self C & D Volusia 1630 Tomoka Farms Road, Port Orange, Fl 32128 53.5

Cape Canaveral AFS

C & D Brevard 1224 Jupiter Street MS 9125, Patrick AFB, Fl 32925 54.1

16

METHODS

Step One: Obtain H2S Concentrations and Atmospheric Data

A determination was made that 50 to 100 points would be the desired quantity of data points for

this project. Too few data points could potentially skew the data due to inadequate

representation, and too many data points could cause a significant increase in time requirements.

This issue is further compounded by the initial underlying concept that one is attempting to

estimate an area source by using point source emissions. This concept reinforces the author’s

previous comments concerning the potentially unreliable nature of flux chambers. Additionally,

the points should be spaced as evenly as possible throughout the landfill’s interior surface

portions to obtain the best representation of the area source. Concerning this project, the number

of data points utilized was below the initial target of at least 50. Continued data acquisition was

infeasible due to time and equipment restrictions.

Three field monitoring site visits to the selected landfill were carried out. In all instances, the

monitoring was undertaken early in the morning to satisfy several requirements: higher odor

concentrations were generally more prevalent in the morning, the wind speed, wind direction and

cloud cover have a higher probability of remaining constant during the morning hours

(producing a constant stability class), and the landfill administration requested early start times

due to staffing levels. For the first and last site visits, the cloud cover was nearly 100%, the wind

was blowing at a steady pace, the temperatures were cool, and the sun was low on the horizon.

All of these factors led the researcher to conclude that the stability class was not likely to change

from the perceived stability class of D. Figure 1 is from a local weather station that was recorded

and posted to the online site Weather Underground (www.wunderground.com). This website has

17

an extensive amount of easily accessible weather data, and could be used if site specific data is

not available. For this research the Weather Underground data was simply used to verify the on-

site data that was recorded. All of the data was recorded between 7:30 am and 10:30 am for each

of the three landfill site visits.

Figure 1: Weather Profile for Site Visit #1

For the second site visit, there were almost no clouds present, the temperatures were warm, the

wind was barely noticeable (close to 0 m/s), and the sun stayed low on the horizon as well. These

meteorological determinations led the researcher to assess the stability classification as B. Figure

18

2 is another example of the confirmed weather data from a locally based weather station with

data again sourced from the website Weather Underground.

Figure 2: Weather Profile for Site Visit #2

During each visit the data were collected as quickly as possible, since variations in the angle of

the sun, cloud cover, temperature, wind speed, and wind direction needed to be minimized. In

both instances the data were completely recorded between 2 and 3 hours after the start times.

Weather data obtained from the meteorological tower located at the landfill included the wind

speed, wind direction, and temperature; while the sun angle and cloud cover were measured

19

manually. Atmospheric stability classifications were estimated from considering the data

together using the Pasquill-Gifford method.

Prior to using the Jerome Meter (model 631-X), the instrument was calibrated by the landfill

authority. The H2S concentrations were recorded by holding the Jerome Meter still

approximately three feet above the landfills surface. The resulting receptor concentration data

were manually and independently collected by two individuals to minimize any errors in data

recording.

Step Two: Estimate H2S Emissions

In order to estimate hydrogen sulfide emissions, the ambient H2S concentration and meteorologic

data collected from each landfill site visit must be processed through a MATLAB application

developed by previous UCF researchers. The specific code was written by Dr. Kevin Mackie.

Each recorded data point taken at the landfill contains the GPS coordinates and the H2S

concentration. These points are utilized by the MATLAB model to determine the source

emission rates and source locations. The MATLAB code consists of the mathematical techniques

described previously in the background section of this paper. Initially, the landfill shape and

boundary locations were left unchanged. However, the landfill had two distinct parts, an older

closed portion and a newer active portion. After further analysis of the results determined by the

MATLAB model, the author decided that analyzing only the open/active portion of the landfill

would be appropriate. This determination was made after noting that the source emissions

calculated by the model were higher when modeling the entire landfill versus modeling just the

active portion for the first site visit. Considering that the only appreciable readings were recorded

20

in the active working face of the landfill, the researchers believe that the amount of H2S gas

contributed by the closed landfill cells was negligible. Adding to this decision was the

knowledge that the waste buried in the closed portion was also of sufficient age and buried depth

(several feet of final soil cover placed on top of the refuse) that it was contributing essentially

nothing.

Table 2 illustrates the differences between the total H2S emissions derived for the entire landfill

from the MATLAB program, and the total H2S emissions from considering only the open/active

portion of the landfill (Appendix B). Note that the total emissions differ widely for the two

different scenarios. This could potentially be explained as merely an artifact produced from the

mathematical techniques employed by the MATLAB model, especially when one considers that

the measured concentrations during this first visit were close to the instrument detection limit.

When applying a similar analysis to the second site visit, the total amount of emissions remained

almost unchanged. This illustrates that careful consideration must be given in regards to the

validity of data at or near instrumentation detection thresholds. Since the first visit’s hydrogen

sulfide concentrations measured between 0 – 4 ppb (Appendix A), and the instrument is typically

only calibrated to a low of 3 ppb (although it can still detect lower), the data were still utilized,

but with the open/active boundary modification.

Additionally, the wind speed for the second site visit was recorded between 0 and 2 mph. This

corresponds to between 0 and 0.90 m/s. However, the Gaussian dispersion equations are

generally recommended to be used with at least a 1.0 m/s wind speed. Therefore, the wind

speeds were ultimately artificially increased to this required 1.0 m/s scenario. Both of the

21

aforementioned scenarios further help to illustrate the difficulties that can be faced in field

measurements and dispersion modeling. Lastly, the third site visit further reinforces these

scenarios. The total estimated H2S emissions based on active face analysis verses analyzing the

entire landfill are close to one another; the relative percent difference between the two is only

1%. The data collected for this site visit were well above the lower detection threshold of the

instrument, while not causing significant readings as were witnessed in the second site visit.

Table 2: Pertinent Site Visit Data and Calculated Emissions

Visit #1 Visit #2 Visit #3

Entire

Landfill

Active

Face

Entire

Landfill

Active

Face

Entire

Landfill

Active

Face

Wind Angle (Ɵ) 11.25 11.25 303.75

Wind Speed (m/s) 2.68 1.00* 2.45

Stability Class D B D

Total Emissions (g/s) 0.051 0.017 0.396 0.401 0.196 0.198

Relative Percent

Difference (%) 95.77 1.25 1.02

* Original wind speed was reported as 0.45 -0.90 m/s.

Step Three: Determine H2S Concentration Limits

The annoyance levels utilized in this study were determined after considerable deliberation.

Several possibilities had to be accounted for, but ultimately there were six considerations that

weighed most heavily upon the final decision:

Studies reported minimum H2S odor detection thresholds between 0.5 and 5 ppbv.7

The AODM study determined 1, 3, and 5 Odor Unit levels were acceptable annoyance

intervals;22

which can then be equated to this projects green, yellow, and red

concentration isopleths, respectively.

Existing regulations in North America and Europe , such as those in Massachusetts that

limit 1-hour H2S exposure to 30 ppbv, and an 8-hour exposure to 15 ppbv.21

22

H2S Concentration to Odor Unit relationships from a Singapore wastewater treatment

facility that determined 9, 26, and 49 ppbv H2S concentrations correlated to the 1, 3, and

5 OU levels.10

Although, these threshold quantities could have been adversely affected by

additional odors present at the wastewater treatment plant.

Previously established odor buffering distance research conducted at the University of

Central Florida, suggested that 15 and 30 ppbv H2S were acceptable odor thresholds.11

Orange County, Florida’s maximum allowable standard for H2S of 100 ppbv before

reporting and notification is required.

The author believes that odor buffer distances based upon odor concentration ranges of <15 ppb,

15-30 ppb, 30-100 ppb, and >100 ppb are justified. These ranges will be represented by light

green (0-7.5 ppb), dark green (7.5 – 15.0 ppb), light yellow (15-22.5 ppb), dark yellow (22.5-

30.0), light red (30.0-65.0 ppb), dark red (65.0-100.0 ppb), and blue (>100.0 ppb) concentration

isopleths for easy visualization purposes.

Step Four: Perform Air Dispersion Modeling (AERMOD)

In setting the odor buffer distances with AERMOD, the one year’s worth of hourly

meteorological data utilized were acquired from the website (www.webmet.com). Since there

was not a full scale weather station present at the exact location, or in the general town vicinity,

local weather data from Tampa International Airport (TIA) was input into AERMOD. Such data

consisted of an AERMET Upper Air File, and a SAMSON Surface Air file; both of which

contained an entire year’s worth of hourly readings from January 1, 1989 to December 31, 1989.

23

This year was chosen because the data were available in both file formats for Tampa, FL.

Additionally, the author concluded that the weather patterns from 1989 closely reflected current

2009 - 2010 weather phenomena, particularly considering the winter months. Central Florida

experienced below average temperatures in the late 1980s, resulting in a cooler than average

winter; and a similar pattern was observed in the winter months of 2009 – 2010. Since two out of

the three landfill site visits were undertaken in cold weather, the author decided that the

meteorological conditions present during the winter months more aptly approximated current

weather conditions.

Once the air data are processed and loaded, the source data must be uploaded. The source

locations and emission rates were previously determined from the MATLAB program. Next,

numerous receptor locations outside the landfill must be chosen. This project has both discrete

Cartesian and polar receptors. This selection process can be a trial and error process; as the exact

amount needed depends upon the specificity of H2S concentrations desired. For all cases, the

receptors in question were selected based upon the researcher’s judgment, and the ability to

establish minimum buffer distances about the landfill. The elevation heights of the surrounding

topography were determined from 7.5 min DEM files obtained from the website

(www.webgis.com).

The author then decided what type of outputs that AERMOD should produce. In this instance the

99.9% probability of non-exceedance relates to the 8th

highest hourly concentration values in one

year. This represents the 24 hours/day*365 days/year = 8760 hours per year*0.1% probability =

8.76 hours (~8) of exceedance. This output level could be chosen differently by a specific landfill

24

authority. It was set very conservatively for this thesis. Since the AERMOD input files can be

tedious and cumbersome, especially for novice users, a commercialized graphical user interface

was utilized. The interface used by the researcher was a program developed by the company

Lakes Environmental (www.weblakes.com).

Step Five: Establish Odor Buffering Distances (Florida C & D landfills)

After the AERMOD model has finished running, and the user has selected his/her desired

maximum exceedance level, the data must then be imported into a mapping and graphing

program. For this research the program Surfer 8 was used, since it was already available at UCF.

However, any program with extensive mapping/graphing capabilities would be acceptable.

Kriging was selected as the interpolation method since it had been used previously in the

MATLAB program during the selection of source locations. In the final graphical printouts, the

interior portion of the landfill is filled in black to denote the landfill boundaries and interior

areas. Since we are concerned with buffering distances, the interior landfill concentrations of

H2S are not important.

The limits determined in step three were applied next, with some judgments made by the

researcher. The surrounding hydrogen sulfide concentration gradients were distributed into four

different zones; green, yellow, red, and blue for ease of visual recognition. Within each of these

zones there are two divisions, an upper and lower level each denoted by a darker and lighter

shade of that color, respectively.

25

RESULTS

The MATLAB model produces a schematic of the relationship between established receptor

locations, and estimated emissions sources. The source points established by using the entire

landfill are illustrated in Figure 3, Figure 5, and Figure 7. The source points established by using

just the active landfill area are shown in Figure 4, Figure 6, and Figure 8. All of the source

locations that lie outside of the landfill boundaries have been excluded from the figures.

Additionally, the sources that are identified within the landfill boundary contain two source

types; “contributors”, and “non-contributors.” Non-contributor sources are those which the

MATLAB program has identified and excluded since they do not significantly contribute to the

overall emissions totals.

Figure 3: MATLAB Receptor and Source Locations (Entire Landfill) Site Visit #1

-600 -500 -400 -300 -200 -100 0 100 200

-200

-100

0

100

200

300

400

500

600

X (m)

Y (

m)

Receptor

Source Wind

N

26

Figure 4: MATLAB Receptor and Source Locations (Active Face) Site Visit #1

Figure 5: MATLAB Receptor and Source Locations (Entire Landfill) Site Visit #2

-200 -150 -100 -50 0 50 100 150 200

-200

-150

-100

-50

0

50

100

150

200

X (m)

Y (

m)

Receptor

Source Wind

N

-600 -500 -400 -300 -200 -100 0 100 200

-200

-100

0

100

200

300

400

500

600

X (m)

Y (

m)

Receptor

Source

N

Wind

27

Figure 6: MATLAB Receptor and Source Locations (Active Face) Site Visit #2

Figure 7: MATLAB Receptor and Source Locations (Entire Landfill) Site Visit #3

-200 -150 -100 -50 0 50 100 150 200

-200

-150

-100

-50

0

50

100

150

200

X (m)

Y (

m)

Receptor

Source

Wind

N

-600 -500 -400 -300 -200 -100 0 100 200

-200

-100

0

100

200

300

400

500

600

X (m)

Y (

m)

Receptor

Source

Wind

N

28

Figure 8: MATLAB Receptor and Source Locations (Active Face) Site Visit #3

The receptors in AERMOD that recorded the odor concentrations are separated into two different

grids, fence line receptors, and uniformly spaced polar receptors. The fence line receptors were

placed approximately 100 meters apart on the landfill boundary lines. The polar receptors were

placed approximately 10 degrees apart from one another, and concentric polar rings were set to

100 meter intervals. The AERMOD receptor locations were selected based on a few basic

criteria. The first was that spacing them more closely to one another did not significantly

increase the details of the concentration plots. Specifically, a test analysis was undertaken, and

the difference between 50 meter and 100 meter polar ring spacing yielded no appreciable

changes in the final odor isopleths in terms of either line roughness, or concentration gradient.

-200 -150 -100 -50 0 50 100 150 200

-200

-150

-100

-50

0

50

100

150

200

X (m)

Y (

m)

Receptor

Source

N

Wind

29

The second criterion concerns the ability of the computer model to process the changes. Even

with newer computers, the run times for large receptor grids varied between 20 and 30 minutes

per run for the 100 meter spacing, and 45 minutes for the 50 meter spacing. The polar grid was

spaced out at 100 meter intervals until a distance which illustrated probable yellow and red

isopleths areas. Specifically, once the researcher was satisfied that the “may likely experience,”

and “highly likely experience” isopleths were observed in the AERMOD results, the

concentration plots were developed. A sample graph of the AERMOD receptor locations for the

landfill is included in Figure 9.

Figure 9: AERMOD Receptor Grid Spacing Example

Figure 10, Figure 11, and Figure 12 display the zones from Surfer from which odor buffer

distances can be determined. The graphing program attempts to establish its best approximation

30

of the areas, however, the majority of receptors were polar, and therefore required additional

mathematical manipulation to depict their concentrations on a Cartesian plot.

Figure 10 illustrates the concentrations of H2S about the landfill based on the first site visit. In

the southeast corner of the landfill, there is a prime illustration of the potential issues related to

contour lines. The concentrations proceed to decrease from 200 ppb to 0 in less than 75 meters.

Then, after reaching 0 ppb, the concentrations suddenly increase to, and maintain a 0 – 15 ppb

range. This “island” of no Hydrogen Sulfide amongst a sea of odor is most likely a gridding and

interpolating error, especially since it did not show up on the graphical readout in the AERMOD

view program. Considering that the landfill authority owns land that extends several hundred

meters to the north, that there is an existing landfill to the southwest, that there is a road and open

land to the east, and numerous known agricultural sources, the predicted odors are unlikely to

affect anyone in the surrounding areas when considering the first site visit. Additionally, it

should be re-iterated that these AERMOD readings and concentration plots are the 8th

highest

hourly concentrations. This 8th

highest hour for the year represents a 99.9% probability of non-

exceedance, which translates to only 8 hourly instances per year when the odor concentration

thresholds will be exceeded.

31

Figure 10: Plot of H2S Concentrations around the active landfill face for Site Visit #1

Figure 11 illustrates the Hydrogen Sulfide concentrations for the second site visit. These results

are considerably higher than the first. Although the author concurs with the program regarding

concentrations to the north, the other three landfill boundaries seem considerably higher than

first hypothesized given the meteorological conditions present. One possible qualifier that must

be addressed for this specific landfill site visit was the intense (over four inches) rainfall event

that occurred before the visit. Large rainfall events can increase the presence of H2S because of

the increase in Sulfate Reducing Bacteria Another possible reason might be that other local and

-800 -600 -400 -200 0 200 400 600 800

X, (m)

-800

-600

-400

-200

0

200

400

600

800Y

, (m

)

0.0

7.5

15.0

22.5

30.0

65.0

100.0

200.0

400.0

H2

S,

(pp

bv)

-3000 -2500 -2000 -1500 -1000 -500 0 500 1000 1500 2000 2500 3000

X, (m)

-3000

-2500

-2000

-1500

-1000

-500

0

500

1000

1500

2000

2500

3000

Y, (m

)

0.0

7.5

15.0

22.5

30.0

65.0

100.0

200.0

400.0

800.0

H2

S,

(pp

bv)

Ɵ

N Wind

32

adjacent odor sources were affecting the readings. Landfill personal reiterated the point

concerning the high initial Jerome Meter readings that they were some of the highest they had

ever witnessed. Therefore, more credibility should be given to the first and third site visits over

the second.

Figure 11: Plot of H2S Concentrations around the active landfill face for Site Visit #2

Lastly, the third landfill site visit was perhaps the most important site visit. The odor readings

were not excessively high; there was no preceding rainfall event, and the stability class was more

definitively stable then in the first two events. However, due to time, geographic, and weather

constraints, the third site visit had the least amount of recorded data points. The weather was

-3000 -2500 -2000 -1500 -1000 -500 0 500 1000 1500 2000 2500 3000

X, (m)

-3000

-2500

-2000

-1500

-1000

-500

0

500

1000

1500

2000

2500

3000

Y, (m

)

0.0

7.5

15.0

22.5

30.0

65.0

100.0

200.0

400.0

800.0

H2

S,

(pp

bv)

Ɵ

N Wind

33

quite cold, and the landfill staff was busy; therefore, the desired amount of data were not

obtained. Too few data points could potentially contribute to either overestimated or

underestimated final H2S emissions. The final analysis for the third site visit can be seen in

Figure 12.

Figure 12: Plot of H2S Concentrations around the active landfill face for Site Visit #3

Sensitivity Analysis

These results rely heavily upon computer modeling and mathematical techniques using matrix

inversion solving methods. It is important to understand that there will be sources of variability

in any simulation. The Gaussian dispersion equations require that the sample data be steady state

-2000 -1500 -1000 -500 0 500 1000 1500 2000

X, (m)

-2000

-1500

-1000

-500

0

500

1000

1500

2000

Y,

(m)

0

7.5

15

22.5

30

65

100

200

400

800

H2S

, (p

pb

v)

Ɵ

N Wind

34

with respect to the many meteorological parameters. However, the wind angle, wind speed and

general atmospheric stability class are only constant for brief periods in time, and it would be

prohibitively expensive to take scores of measurements simultaneously all over the landfill.

To better understand potential variability, a sensitivity analysis was conducted. In the sensitivity

analysis, the input parameters (wind speed, wind angle, and stability class) were altered in the

MATLAB model for each visit. The model was run numerous times, each run yielding a

different estimate of the total emissions. The sensitivity analysis demonstrated the potential

variability in the simulation. Table 3 displays the base case data for the open/active face

measurements for the first site visit.

Table 3: Base Case Data – Site Visit #1

Wind Angle (deg) 191.25

Wind Speed (m/s) 2.70

Stability Class D

Total Emissions

(g/s) 0.017

Table 4 contains the results from the sensitivity analysis for the first site visit. Since the

sensitivity analysis required the researcher to, in this instance, run the MATLAB model over 400

times, including all the results here would be excessive. Therefore, the results are arranged such

that the total calculated landfill emission was obtained for each different combination of wind

speed, wind direction, and stability class. Then, the total emission rates from each run were

compared to base cases. The percent change between two cases was compared for each of the

site visits. Equation (6) illustrates how to calculate the percent change between the two values;

where X1 is the base case and X2 represents the test case.

35

(

)

(6)

Table 4: Percent Change in Estimated Emissions from Base Case for Site Visit #1 (at base

Stability Class D)

Site Visit #1

Wind Angle, Θ (deg)

176.25 181.25 186.25 191.25 196.25 201.25 202.2

5 206.25

Wind

Speed,

u (m/s)

1.70 -27.9 -71.4 -45.7 -37.0 -32.7 -56.3 -10.9 -51.6

1.95 -17.3 -67.2 -37.7 -27.8 -22.7 -49.9 2.2 -44.4

2.20 -6.7 -63.0 -29.7 -18.5 -12.8 -43.5 15.3 -37.3

2.45 3.9 -58.8 -21.7 -9.3 -2.9 -37.0 28.4 -30.2

2.70 14.5 -54.5 -13.7 0.0* 7.0 -30.6 41.5 -23.1

2.95 25.1 -50.3 -5.7 9.3 16.9 -24.2 54.6 -16.0

3.20 35.7 -46.1 2.2 18.5 26.8 -17.8 67.7 -8.8

3.45 46.3 -41.9 10.2 27.8 36.7 -11.3 80.8 -1.7

3.70 56.9 -37.7 18.2 37.0 46.6 -4.9 93.9 5.4

* Base Case = 0.017 g/s H2S emissions

The base case data and emissions for the second site visit are listed in Table 5. It should be noted

that the wind speeds for this case were arbitrarily increased to 1.0 m/s to satisfy the requirements

pertaining to the Gaussian dispersion equations. Additionally, Table 6 contains the sensitivity

data for the second site visit.

Table 5: Base Case Data – Site Visit #2

Wind Angle (deg) 191.25

Wind Speed (m/s) 1.00*

Stability Class B

Total Emissions

(g/s) 0.401

* Measured wind speed was 0.5-0.9 m/s

36

Table 6: Percent Change in Estimated Emissions from Base Case for Site Visit #2 (at base

Stability Class B)

Site Visit #2

Wind Angle, Θ (deg)

176.25 181.25 186.25 191.25 196.25 201.25 202.25 206.25

Wind

Speed,

u (m/s)

0.50 -50.1 -39.8 -46.3 -50.0 -56.5 -74.2 -74.6 -73.0

0.75 -25.1 -9.7 -19.4 -25.0 -34.7 -61.3 -62.0 -59.5

1.00 -0.2 20.4 7.4 0.0* -13.0 -48.3 -49.3 -46.0

1.25 24.8 50.5 34.3 25.0 8.8 -35.4 -36.6 -32.4

1.50 49.8 80.6 61.1 50.0 30.5 -22.5 -23.9 -18.9

1.75 74.7 110.7 88.0 75.0 52.3 -9.6 -11.2 -5.4

2.00 99.7 140.8 114.8 100.0 74.0 3.3 1.5 8.1

* Base Case = 0.401 g/s H2S Emissions

Lastly, the base case data for the third landfill site visit is contained within Table 7. The results

of the third analysis are listed in Table 8. It should be noted that some of the data may tend to

fluctuate greatly from trial to trial. This phenomenon is both attributable to the variability in

input data, but also due to the author’s removal of data that were considered outliers. Outliers

were considered to be any source emission points that the MATLAB code returned which were

two orders of magnitude higher than the average value for that trial run. Any such values were

excluded from the final sensitivity analysis. This deviation occurred in only 4% of the total cases

that were run. Because of this low occurrence of outliers, the author still believes that the

MATLAB code is both robust and dependable.

Table 7: Base Case Data – Site Visit #3

Wind Angle (deg) 123.75

Wind Speed (m/s) 2.45

Stability Class D

Total Emissions

(g/s) 0.197

37

Table 8: Percent Change in Estimated Emissions from Base Case for Site Visit #3 (at base

Stability Class D)

Site Visit #3

Wind Angle, Θ (deg)

108.75 113.75 118.75 123.75 128.75 133.75 134.75 138.75

Wind

Speed,

u (m/s)

1.45 -26.6 -79.8 -80.8 -40.8 -38.5 -29.9 -28.3 -36.9

1.70 -14.0 -76.3 -77.5 -30.6 -27.9 -17.8 -15.9 -26.0

1.95 -1.3 -72.9 -74.2 -20.4 -17.3 -5.8 -3.6 -15.2

2.20 11.4 -69.4 -70.8 -10.2 -6.7 6.3 8.8 -4.3

2.45 24.0 -65.9 -67.5 0.0* 3.9 18.4 21.2 6.6

2.70 36.7 -62.4 -64.2 10.2 14.5 30.5 33.5 17.5

2.95 49.3 -58.9 -60.9 20.4 25.1 42.6 45.9 28.3

3.20 62.0 -55.5 -57.6 30.6 35.7 54.7 58.2 39.2

3.45 74.6 -52.0 -54.3 40.8 46.3 66.7 70.6 50.1

* Base Case = 0.198 g/s H2S Emissions

Table 9 displays the sensitivity of the results to the presumed stability class. The model was run

at the base case wind speed and direction, but with the stability class changed by one class up or

down from the base case. The results are highly sensitive to stability class.

Table 9: Emissions Sensitivity to Stability Class

Site Visit #1 Site Visit #2 Site Visit #3

Stability

Class % Change

Stability

Class % Change

Stability

Class % Change

C 41.2% A 32.1% C 28.8%

D 0.0%* B 0.0%* D 0.0%*

E 72.2% C 14.3% E 69.5%

*Base Cases: Visit #1 = 0.017 g/s H2S Emissions (December 16, 2009)

Visit #2 = 0.401 g/s H2S Emissions (September 14, 2010) Visit #3 = 0.198 g/s H2S Emissions (December 9, 2010)

38

CONCLUSIONS

Table 10 below lists the odor buffer distances derived in this study based on the data collected

from the three landfill site visits. It can be seen from Figure 10, Figure 11, and Figure 12, that the

dispersion of odor from a landfill is not uniform around its exterior. Therefore, the researcher

decided to disproportionately weight the odor affected areas compared to the unaffected areas.

That is to say, although the northern and eastern portions of the surrounding lands were affected

less by the odors, the buffer distances were extended further into them, for visual purposes. The

final visual odor buffer distances are easier to comprehend if they are easy to recognize and

apply to the surrounding lands by any individual.

Table 10: Minimum Odor Buffering Distance for Landfill

H2S

Concentration

(ppbv)

Site Visit #1:

Buffer Distance

(meters)

Site Visit #2:

Buffer Distance

(meters)

Site Visit #3:

Buffer Distance

(meters)

0.0 – 15.0 600 2800 2400

15.0 – 30.0 400 2400 2000

30.0 – 100.0 200 2000 1600

> 100.0 100 1600 1000

*Distances are from the edge of the landfill

Figure 13, Figure 14, and Figure 15 show easily identifiable areas in which the proposed odor

buffer distances can be applied. The colored rings represent their respective odor buffer

concentrations of >100 ppb (blue), 30 – 100 ppb (red), 15 – 30 ppb (yellow), and 0 – 15 ppb

(green). These color coded rings represent the easy, straightforward, visually appealing odor

buffer distances that this research initially intended to achieve.

The landfills size and odor buffers were centered and superimposed over a map of The

University of Central Florida. The primary reason for this was to respect the desires of the

39

landfill’s administration that their facility remain anonymous. The final odor buffering distances

are based upon one specific landfill, derived from data acquired during three specific site visits.

Ultimately odor buffer distances depend upon a large number of variables. The study eventually

noted that operating and weather conditions during field data collection appeared to have the

greatest impact upon the calculated odor buffer distances. Odors continue to be highly variable in

nature, and more consistent monitoring is certainly required to develop more accurate and

reliable odor buffering distances. Such distances will increasingly play a pivotal role in the

planning and development of future comprehensive land use plans by developers, operators, and

local governmental organizations.

40

Figure 13: Minimum Odor Buffer Distances based on the First Site Visit

© Google Maps

41

Figure 14: Minimum Odor Buffer Distances based on the Second Site Visit

© Google Maps

42

Figure 15: Minimum Odor Buffer Distances based on the Third Site Visit.

3 cm = 1 km

© Google Maps

43

RECOMMENDATIONS

Some potential future research recommendations that could improve upon the accuracy and

precision of this research include:

Conduct more site visits to obtain additional data sets to better estimate emission levels.

Obtain greater quantities of data points for each additional data set.

Evaluate this methodology at other locations to compare data and results.

Identify new methods for more accurately determining atmospheric stability

classification.

Obtain more accurate upper-air and surface data files for use in AERMOD from site

specific locations.

Perform non-steady state modeling, while paying particular attention to meteorological

parameters such as stability class, wind direction, wind speed, solar insolation, and cloud

cover.

Research specific peak-to-mean ratios for odors in general and specifically for Hydrogen

Sulfide odors coming from area sources such as landfills.

Substantiate current Odor Unit-to-H2S concentration ratios.

44

APPENDIX A: FIELD DATA – MEASURED H2S CONCENTRATIONS

AND THEIR LOCATIONS

45

Site Visit #1

Entire Landfill Open Face Portion

No. xr yr Ctotal

(μg/m3)

No. xr yr Ctotal

(μg/m3)

1 379 -79 2.14 1 176 122 2.14

2 379 198 0.71 2 -204 62 1.43

3 165 384 1.43 3 -150 -153 2.14

4 -107 386 1.43 4 148 -186 0.71

5 -351 356 1.43 5 122 -1 0.71

6 -378 233 1.43 6 40 31 0.71

7 -379 17 1.43 7 -14 31 0.71

8 -109 16 0.71 8 -69 31 0.71

9 -1 -139 1.43 9 -149 62 1.43

10 53 -354 2.14 10 -150 -30 1.43

11 351 -387 0.71 11 -123 -61 2.86

12 325 -202 0.71 12 -69 -92 1.43

13 243 -170 0.71 13 -14 -62 2.14

14 189 -170 0.71 14 40 154 1.43

15 134 -170 0.71 15 -41 154 1.43

16 54 -139 1.43 16 -94 186 2.14

17 53 -231 1.43 17 -177 -61 2.14

18 80 -262 2.86 18 -205 -91 2.14

19 134 -293 1.43 19 -205 -153 2.14

20 189 -263 2.14 20 -178 -153 2.14

21 243 -47 1.43 21 -96 -153 2.14

22 162 -47 1.43 22 -56 -123 2.86

23 109 -15 2.14 23 -15 -123 2.86

24 54 15 1.43 24 13 -92 2.86

25 82 77 2.14 25 13 -62 1.43

26 136 76 2.14 26 67 -62 1.43

27 218 76 0.71

28 271 76 1.43

29 26 -262 2.14

30 -2 -292 2.14

31 -2 -354 2.14

32 25 -354 2.14

33 107 -354 2.14

34 147 -324 2.86

46

35 188 -324 2.86

36 216 -293 2.86

37 216 -263 1.43

38 270 -263 1.43

47

Site Visit #2

Entire Landfill Open Face Portion

No. xr yr Ctotal

(μg/m3)

No. xr yr Ctotal

(μg/m3)

1 379 -79 0.00 1 176 122 0.00

2 379 198 0.00 2 -176 62 2.80

3 165 384 0.00 3 -150 -153 237.71

4 -107 386 1.40 4 148 -185 2.80

5 -351 356 1.40 5 19 50 6.99

6 -378 233 0.00 6 -31 50 2.80

7 -379 17 1.40 7 -81 50 2.80

8 -109 16 1.40 8 -81 20 5.59

9 27 -139 2.80 9 -31 20 5.59

10 53 -354 237.71 10 19 20 5.59

11 351 -387 2.80 11 69 20 223.72

12 222 -151 6.99 12 69 -10 44.75

13 172 -151 2.80 13 -31 -10 9.79

14 122 -151 2.80 14 -81 -10 5.59

15 122 -181 5.59 15 -81 -40 15.38

16 172 -181 5.59 16 -31 -40 5.59

17 222 -181 5.59 17 19 -40 125.85

18 272 -181 223.72 18 69 -40 181.78

19 272 -211 44.75 19 49 -90 4.20

20 172 -211 9.79 20 59 -70 72.71

21 122 -211 5.59 21 -1 -80 33.56

22 122 -241 15.38 22 -51 -90 65.72

23 172 -241 5.59 23 -91 -100 68.52

24 222 -241 125.85 24 -121 -110 153.81

25 272 -241 181.78 25 -141 -115 433.47

26 252 -291 4.20 26 -161 -120 146.82

27 262 -271 72.71 27 -121 -156 11.19

28 202 -281 33.56 28 -91 -166 144.02

29 152 -291 65.72 29 -61 -166 25.17

30 112 -301 68.52 30 -31 -176 34.96

31 82 -311 153.81 31 19 -176 47.54

32 62 -316 433.47 32 69 -176 33.56

33 42 -321 146.82 33 109 -166 5.59

34 82 -357 11.19

48

35 112 -367 144.02

36 142 -367 25.17

37 172 -377 34.96

38 222 -377 47.54

39 272 -377 33.56

40 312 -367 5.59

41 339 57 2.80

42 314 32 4.20

43 344 107 4.20

44 364 82 2.80

49

Site Visit #3

Entire Landfill Open Face Portion

No. xr yr Ctotal

(μg/m3)

No. xr yr Ctotal

(μg/m3)

1 379 -79 5.96 1 176 122 6.00

2 380 167 4.47 2 -177 -30 3.00

3 165 384 5.96 3 -178 -184 6.00

4 -107 386 4.47 4 175 -186 22.40

5 -351 325 5.96 5 39 -92 14.90

6 -378 202 5.96 6 -42 -62 19.40

7 -353 -13 4.47 7 -95 -91 10.40

8 -109 -14 4.47 8 -123 -30 10.40

9 26 -231 2.98 9 -14 61 13.40

10 25 -385 5.96 10 14 92 7.50

11 378 -387 22.37 11 95 92 7.50

12 242 -293 14.91 12 -169 -132 16.40

13 161 -263 19.38 13 -73 -63 10.40

14 108 -292 10.44 14 -23 -12 11.90

15 80 -231 10.44 15 85 34 14.90

16 189 -140 13.42 16 104 44 13.40

17 217 -109 7.46 17 86 118 13.40

18 298 -109 7.46 18 17 162 11.90

19 271 45 17.89 19 108 -130 10.40

20 34 -333 16.40 20 -35 -72 17.90

21 130 -264 10.44 21 58 1 13.40

22 180 -213 11.93 22 -32 20 19.40

23 288 -167 14.91

24 307 -157 13.42

25 289 -83 13.42

26 220 -39 11.93

27 311 -331 10.44

28 168 -273 17.89

29 261 -200 13.42

30 171 -181 19.38

50

APPENDIX B: CALCULATED EMISSIONS AND SOURCE LOCATIONS

(FROM MATLAB)

51

Site Visit #1

Entire Landfill Open Face Portion

No. xr yr Qtotal

(μg/s) No. xr yr

Qtotal

(μg/s)

1 -181 201 25,000 1 159 -90 6,272

2 266 -366 2,354 2 -123 -111 2,361

3 185 -293 220 3 -41 89 821

4 203 -278 1,259 4 -101 115 346

5 102 -86 326 5 63 -165 2,285

6 99 32 2,136 6 77 -144 154

7 67 -27 378 7 -164 -169 2,065

8 39 -370 2,062 8 -70 -30 321

9 243 -220 230 9 0 -77 2,030

10 362 -291 8,009 10 -18 -92 220

11 280 -345 407 11 -33 -92 362

12 170 -293 356

13 216 -108 1,549

14 162 -112 755

15 115 -101 1,207

16 326 -1 16

17 133 -231 339

18 80 -312 2,364

19 27 -185 2,129

Total 51,093 Total 17,237

52

Site Visit #2

Entire Landfill Open Face Portion

No. xr yr Qtotal

(μg/s) No. xr yr

Qtotal

(μg/s)

1 -244 -7 18,037 1 44 -137 3,720

2 247 -226 81,361 2 16 -127 62,191

3 56 -335 31,244 3 78 -127 178,125

4 140 -328 10,083 4 44 -27 89,619

5 197 -332 6,030 5 -6 -127 6,428

6 281 -329 162,972 6 -147 -137 31,248

7 247 -337 4,366 7 -63 -127 10,208

8 219 -328 62,525 8 -126 -137 12,093

9 77 -334 12,086 9 -97 -137 7,700

10 106 -334 7,667

Total 396,371 Total 401,331

53

Site Visit #3

Entire Landfill Open Face Portion

No. xr yr Qtotal

(μg/s) No. xr yr

Qtotal

(μg/s)

1 -230 110 2,902 1 -99 -171 4,918

2 -197 227 1,037 2 -106 -59 5,116

3 97 -260 5,326 3 -57 -80 2,902

4 104 -372 4,909 4 131 119 151,064

5 53 -280 7,843 5 147 77 2,250

6 275 278 45,202 6 55 69 981

7 306 -258 19,090 7 23 -40 1,450

8 344 -243 6,300 8 103 -57 19,100

9 226 -241 1,450 9 141 -42 6,281

10 194 -247 3,694 10 132 -32 3,708

11 146 -281 2,903

12 335 -233 3,665

13 350 -124 2,480

14 258 -132 979

15 208 211 21,478

16 334 -82 43,142

17 331 -12 23,421

Total 195,823 Total 197,769

54

APPENDIX C: PREDICTED OFF-SITE CONCENTRATIONS (FROM

AERMOD)

55

Site Visit #1: Active Face

X (m) Y (m) C (ppb) X (m) Y (m) C (ppb) X (m) Y (m) C (ppb)

295 52 29.1 394 69 24.3 492 87 18.4

282 103 36.0 376 137 25.3 470 171 22.1

260 150 39.0 346 200 24.4 433 250 15.0

230 193 40.5 306 257 21.7 383 321 19.1

193 230 31.1 257 306 24.1 321 383 10.9

150 260 50.3 200 346 22.7 250 433 13.8

103 282 43.1 137 376 33.7 171 470 12.8

52 295 65.0 69 394 20.9 87 492 9.8

0 300 30.7 0 400 19.7 0 500 11.8

-52 295 31.2 -69 394 24.0 -87 492 21.8

-103 282 44.2 -137 376 17.7 -171 470 13.2

-150 260 44.8 -200 346 17.6 -250 433 8.8

-193 230 99.5 -257 306 46.1 -321 383 19.4

-230 193 73.0 -306 257 37.3 -383 321 29.3

-260 150 56.2 -346 200 35.2 -433 250 37.2

-282 103 63.6 -376 137 44.3 -470 171 33.4

-295 52 49.4 -394 69 41.5 -492 87 27.5

-300 0 38.6 -400 0 37.2 -500 0 28.6

-295 -52 49.4 -394 -69 30.6 -492 -87 21.6

-282 -103 54.5 -376 -137 27.6 -470 -171 17.5

-260 -150 34.9 -346 -200 27.7 -433 -250 20.4

-230 -193 77.1 -306 -257 29.3 -383 -321 16.5

-193 -230 64.2 -257 -306 25.5 -321 -383 15.2

-150 -260 64.2 -200 -346 35.1 -250 -433 22.1

-103 -282 46.5 -137 -376 30.1 -171 -470 24.3

-52 -295 49.4 -69 -394 27.4 -87 -492 26.0

0 -300 28.4 0 -400 20.2 0 -500 17.5

52 -295 28.3 69 -394 16.8 87 -492 12.8

103 -282 21.8 137 -376 14.4 171 -470 10.8

150 -260 22.3 200 -346 16.4 250 -433 12.7

193 -230 21.1 257 -306 18.8 321 -383 16.7

230 -193 30.4 306 -257 23.5 383 -321 17.4

260 -150 19.3 346 -200 17.0 433 -250 15.7

282 -103 24.4 376 -137 18.0 470 -171 13.2

295 -52 22.4 394 -69 18.3 492 -87 11.6

300 0 22.6 400 0 12.3 500 0 15.7

56

X (m) Y (m) C (ppb) X (m) Y (m) C (ppb) X (m) Y (m) C (ppb)

591 104 14.5 689 122 11.7 788 139 9.5

564 205 15.6 658 239 9.8 752 274 8.4

520 300 9.8 606 350 8.4 693 400 8.6

460 386 16.4 536 450 11.9 613 514 6.2

386 460 12.8 450 536 7.7 514 613 7.1

300 520 10.3 350 606 12.5 400 693 5.9

205 564 7.0 239 658 5.0 274 752 5.5

104 591 7.0 122 689 7.8 139 788 6.6

0 600 8.0 0 700 7.2 0 800 6.4

-104 591 14.3 -122 689 6.4 -139 788 4.6

-205 564 7.7 -239 658 6.3 -274 752 6.1

-300 520 7.7 -350 606 5.0 -400 693 4.2

-386 460 14.1 -450 536 10.3 -514 613 7.8

-460 386 23.2 -536 450 17.9 -613 514 15.4

-520 300 23.7 -606 350 20.5 -693 400 11.6

-564 205 21.2 -658 239 19.1 -752 274 12.7

-591 104 19.1 -689 122 14.3 -788 139 15.9

-600 0 19.5 -700 0 14.8 -800 0 11.0

-591 -104 18.8 -689 -122 18.2 -788 -139 11.2

-564 -205 19.1 -658 -239 17.3 -752 -274 14.0

-520 -300 20.5 -606 -350 17.4 -693 -400 13.3

-460 -386 16.2 -536 -450 24.7 -613 -514 17.1

-386 -460 15.9 -450 -536 18.1 -514 -613 17.0

-300 -520 16.5 -350 -606 14.8 -400 -693 14.2

-205 -564 19.7 -239 -658 15.3 -274 -752 12.7

-104 -591 17.3 -122 -689 18.3 -139 -788 16.9

0 -600 17.6 0 -700 14.5 0 -800 13.6

104 -591 11.7 122 -689 12.0 139 -788 10.6

205 -564 8.5 239 -658 8.6 274 -752 7.3

300 -520 10.6 350 -606 9.2 400 -693 7.7

386 -460 15.0 450 -536 13.4 514 -613 12.1

460 -386 15.1 536 -450 13.4 613 -514 11.2

520 -300 13.3 606 -350 11.1 693 -400 8.9

564 -205 12.9 658 -239 10.2 752 -274 7.6

591 -104 9.7 689 -122 8.1 788 -139 6.4

600 0 13.4 700 0 9.8 800 0 9.09

57

X (m) Y (m) C (ppb)

178 186 53.9

178 -17 197.3

178 -186 117.3

-14 -186 114.0

-178 -186 393.2

-178 -17 58.4

-178 186 33.4

-14 186 33.2

-144 186 40.2

178 83 97.4

178 -117 622.7

86 -186 166.1

-114 -186 66.7

-178 -117 158.2

-178 83 31.4

-114 186 35.3

86 186 42.9

58

Site Visit #2: Active Face

X (m) Y (m) C (ppb) X (m) Y (m) C (ppb) X (m) Y (m) C (ppb)

295 52 783.1 394 69 662.8 492 87 506.0

282 103 929.3 376 137 512.4 470 171 450.7

260 150 808.5 346 200 709.0 433 250 553.0

230 193 763.5 306 257 609.8 383 321 510.0

193 230 720.4 257 306 379.7 321 383 360.7

150 260 694.0 200 346 438.1 250 433 271.3

103 282 534.3 137 376 309.8 171 470 300.8

52 295 549.8 69 394 237.5 87 492 255.0

0 300 506.5 0 400 349.0 0 500 167.4

-52 295 677.7 -69 394 361.4 -87 492 231.4

-103 282 782.9 -137 376 588.1 -171 470 219.6

-150 260 762.3 -200 346 354.0 -250 433 298.9

-193 230 612.7 -257 306 457.5 -321 383 309.1

-230 193 1,235.7 -306 257 784.0 -383 321 588.3

-260 150 2,306.3 -346 200 1,039.6 -433 250 744.6

-282 103 2,646.9 -376 137 1,680.7 -470 171 975.1

-295 52 2,675.0 -394 69 1,310.6 -492 87 922.7

-300 0 2,693.8 -400 0 1,111.9 -500 0 830.1

-295 -52 2,789.0 -394 -69 1,745.1 -492 -87 934.8

-282 -103 1,351.0 -376 -137 1,122.0 -470 -171 942.2

-260 -150 1,147.9 -346 -200 1,313.7 -433 -250 862.3

-230 -193 907.7 -306 -257 935.3 -383 -321 728.7

-193 -230 952.3 -257 -306 812.8 -321 -383 867.4

-150 -260 1,497.8 -200 -346 817.0 -250 -433 678.9

-103 -282 1,238.6 -137 -376 1,311.4 -171 -470 848.4

-52 -295 1,241.7 -69 -394 1,013.0 -87 -492 953.9

0 -300 1,097.2 0 -400 554.5 0 -500 469.2

52 -295 625.6 69 -394 422.2 87 -492 389.5

103 -282 586.6 137 -376 550.1 171 -470 394.0

150 -260 664.9 200 -346 529.7 250 -433 402.4

193 -230 702.7 257 -306 528.9 321 -383 401.5

230 -193 651.0 306 -257 491.2 383 -321 399.3

260 -150 709.0 346 -200 561.4 433 -250 459.7

282 -103 952.5 376 -137 572.7 470 -171 389.3

295 -52 640.5 394 -69 574.4 492 -87 593.1

300 0 924.6 400 0 642.4 500 0 523.2

59

X (m) Y (m) C (ppb) X (m) Y (m) C (ppb) X (m) Y (m) C (ppb)

591 104 486.4 689 122 398.3 788 139 388.9

564 205 379.1 658 239 361.4 752 274 242.7

520 300 445.8 606 350 386.3 693 400 336.0

460 386 363.9 536 450 238.2 613 514 187.5

386 460 285.3 450 536 302.6 514 613 271.3

300 520 331.0 350 606 211.8 400 693 203.3

205 564 162.6 239 658 144.7 274 752 114.6

104 591 227.9 122 689 189.7 139 788 159.2

0 600 206.9 0 700 111.9 0 800 93.1

-104 591 235.3 -122 689 214.2 -139 788 136.3

-205 564 96.7 -239 658 127.1 -274 752 96.5

-300 520 156.3 -350 606 103.7 -400 693 79.4

-386 460 274.9 -450 536 180.9 -514 613 136.9

-460 386 427.7 -536 450 306.1 -613 514 254.8

-520 300 538.3 -606 350 410.3 -693 400 339.3

-564 205 802.7 -658 239 463.8 -752 274 379.0

-591 104 686.1 -689 122 456.5 -788 139 373.9

-600 0 623.9 -700 0 468.6 -800 0 394.0

-591 -104 562.1 -689 -122 446.4 -788 -139 384.9

-564 -205 552.2 -658 -239 555.1 -752 -274 419.1

-520 -300 622.5 -606 -350 469.4 -693 -400 374.4

-460 -386 792.9 -536 -450 562.6 -613 -514 395.5

-386 -460 697.3 -450 -536 484.5 -514 -613 401.9

-300 -520 443.2 -350 -606 414.2 -400 -693 339.2

-205 -564 456.6 -239 -658 416.3 -274 -752 267.3

-104 -591 672.0 -122 -689 569.7 -139 -788 348.8

0 -600 416.9 0 -700 372.6 0 -800 273.4

104 -591 398.9 122 -689 352.7 139 -788 418.9

205 -564 300.4 239 -658 247.4 274 -752 283.2

300 -520 330.6 350 -606 280.6 400 -693 246.2

386 -460 358.4 450 -536 301.1 514 -613 271.7

460 -386 349.5 536 -450 300.1 613 -514 262.9

520 -300 372.0 606 -350 371.5 693 -400 316.4

564 -205 329.2 658 -239 380.3 752 -274 289.3

591 -104 535.3 689 -122 509.9 788 -139 397.4

600 0 510.6 700 0 443.5 800 0 343.4

60

X (m) Y (m) C (ppb) X (m) Y (m) C (ppb) X (m) Y (m) C (ppb)

886 156 314.7 985 174 304.7 1,083 191 225.2

846 308 219.8 940 342 203.8 1,034 376 178.2

779 450 237.9 866 500 228.6 953 550 207.5

689 579 189.6 766 643 186.4 843 707 178.3

579 689 230.0 643 766 141.8 707 843 112.4

450 779 162.7 500 866 132.5 550 953 112.5

308 846 126.6 342 940 95.0 376 1,034 86.5

156 886 123.8 174 985 75.1 191 1,083 55.5

0 900 83.2 0 1000 64.6 0 1,100 54.8

-156 886 85.9 -174 985 59.0 -191 1,083 49.7

-308 846 56.0 -342 940 64.9 -376 1,034 46.5

-450 779 68.7 -500 866 60.1 -550 953 64.5

-579 689 122.8 -643 766 116.4 -707 843 113.5

-689 579 214.9 -766 643 196.8 -843 707 178.6

-779 450 288.0 -866 500 250.6 -953 550 221.1

-846 308 340.1 -940 342 251.6 -1,034 376 218.2

-886 156 312.6 -985 174 255.8 -1,083 191 227.6

-900 0 371.1 -1,000 0 342.2 -1,100 0 260.7

-886 -156 343.2 -985 -174 287.0 -1,083 -191 243.3

-846 -308 326.9 -940 -342 339.2 -1,034 -376 361.3

-779 -450 323.6 -866 -500 351.1 -953 -550 311.5

-689 -579 363.0 -766 -643 283.9 -843 -707 255.2

-579 -689 307.0 -643 -766 251.3 -707 -843 232.5

-450 -779 273.3 -500 -866 328.2 -550 -953 313.2

-308 -846 211.1 -342 -940 182.9 -376 -1,034 165.6

-156 -886 268.4 -174 -985 244.1 -191 -1,083 292.3

0 -900 265.7 0 -1000 247.0 0 -1,100 239.6

156 -886 312.9 174 -985 200.5 191 -1,083 139.8

308 -846 253.8 342 -940 200.7 376 -1,034 144.3

450 -779 240.8 500 -866 209.5 550 -953 157.9

579 -689 240.5 643 -766 212.9 707 -843 204.6

689 -579 250.0 766 -643 260.3 843 -707 236.8

779 -450 277.6 866 -500 253.4 953 -550 223.5

846 -308 199.2 940 -342 170.0 1,034 -376 146.7

886 -156 269.2 985 -174 240.4 1,083 -191 213.3

900 0 273.9 1,000 0 262.9 1,100 0 224.8

61

X (m) Y (m) C (ppb) X (m) Y (m) C (ppb) X (m) Y (m) C (ppb)

1,182 208 200.3 1,280 226 183.4 1,379 243 168.5

1,128 410 188.1 1,222 445 164.0 1,316 479 164.7

1,039 600 198.8 1,126 650 160.4 1,212 700 116.2

919 771 132.0 996 836 98.4 1,072 900 102.4

771 919 104.2 836 996 106.1 900 1,072 105.7

600 1,039 101.3 650 1,126 68.5 700 1,212 56.1

410 1,128 67.4 445 1,222 54.3 479 1,316 50.9

208 1,182 37.4 226 1,280 38.6 243 1,379 39.4

0 1,200 55.6 0 1,300 57.9 0 1,400 54.2

-208 1,182 32.8 -226 1,280 39.9 -243 1,379 32.0

-410 1,128 40.9 -445 1,222 43.0 -479 1,316 38.4

-600 1,039 44.9 -650 1,126 40.4 -700 1,212 36.1

-771 919 105.6 -836 996 96.2 -900 1,072 89.4

-919 771 155.1 -996 836 139.8 -1,072 900 129.4

-1,039 600 198.0 -1,126 650 176.6 -1,212 700 208.2

-1,128 410 180.5 -1,222 445 180.5 -1,316 479 205.4

-1,182 208 221.7 -1,280 226 235.6 -1,379 243 250.5

-1,200 0 228.8 -1,300 0 194.4 -1,400 0 178.6

-1,182 -208 236.2 -1,280 -226 194.3 -1,379 -243 182.4

-1,128 -410 307.1 -1,222 -445 290.3 -1,316 -479 269.2

-1,039 -600 306.8 -1,126 -650 253.5 -1,212 -700 228.1

-919 -771 215.1 -996 -836 229.7 -1,072 -900 226.6

-771 -919 221.8 -836 -996 203.6 -900 -1,072 192.8

-600 -1,039 320.7 -650 -1,126 274.6 -700 -1,212 234.4

-410 -1,128 148.0 -445 -1,222 150.2 -479 -1,316 157.1

-208 -1,182 228.3 -226 -1,280 150.1 -243 -1,379 124.2

0 -1,200 220.2 0 -1,300 207.2 0 -1,400 177.8

208 -1,182 125.2 226 -1,280 124.1 243 -1,379 131.5

410 -1,128 115.6 445 -1,222 105.4 479 -1,316 94.1

600 -1,039 129.0 650 -1,126 111.8 700 -1,212 111.9

771 -919 195.7 836 -996 185.4 900 -1,072 190.6

919 -771 209.8 996 -836 168.0 1,072 -900 147.8

1,039 -600 189.9 1,126 -650 168.7 1,212 -700 154.8

1,128 -410 113.4 1,222 -445 92.8 1,316 -479 85.6

1,182 -208 227.9 1,280 -226 208.9 1,379 -243 167.7

1,200 0 207.1 1,300 0 203.8 1,400 0 181.4

62

X (m) Y (m) C (ppb) X (m) Y (m) C (ppb) X (m) Y (m) C (ppb)

1,477 260 156.8 1,576 278 142.6 1,674 295 125.9

1,410 513 139.6 1,504 547 125.4 1,597 581 110.3

1,299 750 102.1 1,386 800 97.1 1,472 850 83.3

1,149 964 83.4 1,226 1,028 77.2 1,302 1,093 74.1

964 1,149 102.6 1,028 1,226 96.2 1,093 1,302 86.6

750 1,299 46.0 800 1,386 34.8 850 1,472 28.4

513 1,410 52.2 547 1,504 53.7 581 1,597 56.7

260 1,477 41.0 278 1,576 30.5 295 1,674 34.7

0 1,500 51.3 0 1,600 53.7 0 1,700 46.2

-260 1,477 22.1 -278 1,576 18.4 -295 1,674 14.0

-513 1,410 27.7 -547 1,504 23.9 -581 1,597 23.0

-750 1,299 31.8 -800 1,386 28.4 -850 1,472 24.9

-964 1,149 83.7 -1,028 1,226 77.5 -1,093 1,302 63.9

-1,149 964 132.1 -1,226 1,028 128.9 -1,302 1,093 119.7

-1,299 750 196.6 -1,386 800 183.2 -1,472 850 145.1

-1,410 513 185.6 -1,504 547 170.3 -1,597 581 118.8

-1,477 260 228.1 -1,576 278 181.8 -1,674 295 181.7

-1,500 0 173.9 -1,600 0 187.4 -1,700 0 219.1

-1,477 -260 167.5 -1,576 -278 153.5 -1,674 -295 152.0

-1,410 -513 246.4 -1,504 -547 234.7 -1,597 -581 219.4

-1,299 -750 213.4 -1,386 -800 202.5 -1,472 -850 186.4

-1,149 -964 208.7 -1,226 -1,028 214.8 -1,302 -1,093 213.2

-964 -1,149 192.7 -1,028 -1,226 184.1 -1,093 -1,302 188.7

-750 -1,299 190.0 -800 -1,386 153.6 -850 -1,472 139.2

-513 -1,410 167.6 -547 -1,504 148.3 -581 -1,597 115.0

-260 -1,477 110.0 -278 -1,576 104.2 -295 -1,674 91.4

0 -1,500 160.1 0 -1,600 134.1 0 -1,700 141.0

260 -1,477 124.9 278 -1,576 103.0 295 -1,674 102.4

513 -1,410 85.9 547 -1,504 83.1 581 -1,597 90.1

750 -1,299 107.4 800 -1,386 129.9 850 -1,472 122.4

964 -1,149 180.8 1,028 -1,226 157.8 1,093 -1,302 139.0

1,149 -964 126.4 1,226 -1,028 133.4 1,302 -1,093 131.0

1,299 -750 146.6 1,386 -800 141.8 1,472 -850 138.7

1,410 -513 79.3 1,504 -547 74.8 1,597 -581 70.9

1,477 -260 174.0 1,576 -278 157.0 1,674 -295 158.7

1,500 0 167.2 1,600 0 154.3 1,700 0 124.1

63

X (m) Y (m) C (ppb) X (m) Y (m) C (ppb) X (m) Y (m) C (ppb)

1,773 313 118.2 1,871 330 107.2 1,970 347 96.4

1,691 616 95.4 1,785 650 83.2 1,879 684 71.2

1,559 900 77.5 1,645 950 60.5 1,732 1,000 59.8

1,379 1,157 70.7 1,455 1,221 61.3 1,532 1,286 45.5

1,157 1,379 73.6 1,221 1,455 61.0 1,286 1,532 48.0

900 1,559 19.7 950 1,645 14.1 1,000 1,732 10.2

616 1,691 52.2 650 1,785 38.7 684 1,879 36.9

313 1,773 35.3 330 1,871 31.4 347 1,970 27.3

0 1,800 43.9 0 1,900 40.3 0 2,000 36.2

-313 1,773 13.1 -330 1,871 12.1 -347 1,970 11.3

-616 1,691 21.9 -650 1,785 20.6 -684 1,879 19.7

-900 1,559 21.9 -950 1,645 19.8 -1,000 1,732 18.1

-1,157 1,379 57.1 -1,221 1,455 52.4 -1,286 1,532 49.1

-1,379 1,157 99.2 -1,455 1,221 82.8 -1,532 1,286 74.0

-1,559 900 149.6 -1,645 950 144.9 -1,732 1,000 126.2

-1,691 616 104.5 -1,785 650 106.7 -1,879 684 104.4

-1,773 313 180.8 -1,871 330 162.2 -1,970 347 151.1

-1,800 0 214.7 -1,900 0 200.8 -2,000 0 187.8

-1,773 -313 173.4 -1,871 -330 169.8 -1,970 -347 164.4

-1,691 -616 183.0 -1,785 -650 172.9 -1,879 -684 169.7

-1,559 -900 173.4 -1,645 -950 162.7 -1,732 -1,000 145.2

-1,379 -1,157 202.7 -1,455 -1,221 188.0 -1,532 -1,286 167.3

-1,157 -1,379 181.2 -1,221 -1,455 185.9 -1,286 -1,532 176.6

-900 -1,559 152.7 -950 -1,645 162.5 -1,000 -1,732 161.0

-616 -1,691 106.7 -650 -1,785 97.2 -684 -1,879 90.3

-313 -1,773 84.3 -330 -1,871 79.4 -347 -1,970 74.2

0 -1,800 125.5 0 -1,900 121.5 0 -2,000 116.9

313 -1,773 104.5 330 -1,871 114.4 347 -1,970 93.9

616 -1,691 96.3 650 -1,785 93.6 684 -1,879 90.2

900 -1,559 120.3 950 -1,645 114.7 1,000 -1,732 106.8

1,157 -1,379 122.7 1,221 -1,455 112.4 1,286 -1,532 107.2

1,379 -1,157 125.6 1,455 -1,221 117.9 1,532 -1,286 110.7

1,559 -900 135.3 1,645 -950 144.0 1,732 -1,000 135.0

1,691 -616 73.5 1,785 -650 68.6 1,879 -684 64.3

1,773 -313 156.8 1,871 -330 141.2 1,970 -347 127.2

1,800 0 126.2 1,900 0 120.3 2,000 0 102.5

64

X (m) Y (m) C (ppb) X (m) Y (m) C (ppb) X (m) Y (m) C (ppb)

2,068 365 84.3 2,167 382 76.8 2,265 399 69.1

1,973 718 71.9 2,067 752 67.6 2,161 787 63.2

1,819 1,050 57.1 1,905 1,100 52.4 1,992 1,150 51.6

1,609 1,350 42.1 1,685 1,414 40.8 1,762 1,478 39.9

1,350 1,609 37.6 1,414 1,685 29.5 1,478 1,762 26.5

1,050 1,819 9.4 1,100 1,905 9.0 1,150 1,992 8.6

718 1,973 37.6 752 2,067 40.0 787 2,161 39.3

365 2,068 23.6 382 2,167 20.3 399 2,265 18.1

0 2,100 35.9 0 2,200 28.7 0 2,300 26.6

-365 2,068 9.4 -382 2,167 8.1 -399 2,265 8.0

-718 1,973 19.9 -752 2,067 20.3 -787 2,161 19.0

-1,050 1,819 16.8 -1,100 1,905 15.2 -1,150 1,992 14.0

-1,350 1,609 46.1 -1,414 1,685 41.5 -1,478 1,762 39.0

-1,609 1,350 66.6 -1,685 1,414 60.5 -1,762 1,478 58.4

-1,819 1,050 100.5 -1,905 1,100 91.9 -1,992 1,150 89.7

-1,973 718 97.5 -2,067 752 88.3 -2,161 787 78.2

-2,068 365 142.6 -2,167 382 135.5 -2,265 399 106.1

-2,100 0 144.7 -2,200 0 124.6 -2,300 0 115.7

-2,068 -365 155.0 -2,167 -382 146.0 -2,265 -399 134.0

-1,973 -718 166.2 -2,067 -752 175.8 -2,161 -787 158.8

-1,819 -1,050 141.9 -1,905 -1,100 134.9 -1,992 -1,150 132.3

-1,609 -1,350 160.2 -1,685 -1,414 148.2 -1,762 -1,478 134.5

-1,350 -1,609 144.2 -1,414 -1,685 131.9 -1,478 -1,762 119.9

-1,050 -1,819 139.7 -1,100 -1,905 119.6 -1,150 -1,992 90.4

-718 -1,973 85.8 -752 -2,067 88.5 -787 -2,161 83.1

-365 -2,068 79.8 -382 -2,167 78.3 -399 -2,265 71.3

0 -2,100 115.9 0 -2,200 95.6 0 -2,300 76.6

365 -2,068 81.1 382 -2,167 82.3 399 -2,265 90.7

718 -1,973 86.4 752 -2,067 83.2 787 -2,161 75.9

1,050 -1,819 101.5 1,100 -1,905 96.5 1,150 -1,992 92.8

1,350 -1,609 100.9 1,414 -1,685 96.4 1,478 -1,762 93.3

1,609 -1,350 103.9 1,685 -1,414 98.7 1,762 -1,478 93.7

1,819 -1,050 118.9 1,905 -1,100 109.0 1,992 -1,150 111.2

1,973 -718 53.8 2,067 -752 50.5 2,161 -787 47.4

2,068 -365 128.0 2,167 -382 120.5 2,265 -399 114.4

2,100 0 105.6 2,200 0 103.3 2,300 0 99.2

65

X (m) Y (m) C (ppb) X (m) Y (m) C (ppb) X (m) Y (m) C (ppb)

2,364 417 65.9 2,462 434 55.1 2,561 451 51.1

2,255 821 62.3 2,349 855 53.9 2,443 889 49.4

2,078 1,200 50.2 2,165 1,250 46.9 2,252 1,300 42.0

1,839 1,543 39.8 1,915 1,607 37.5 1,992 1,671 33.9

1,543 1,839 25.4 1,607 1,915 24.5 1,671 1,992 23.6

1,200 2,078 8.2 1,250 2,165 7.8 1,300 2,252 7.5

821 2,255 38.8 855 2,349 35.7 889 2,443 35.1

417 2,364 18.1 434 2,462 17.9 451 2,561 17.6

0 2,400 25.9 0 2,500 26.3 0 2,600 26.1

-417 2,364 7.3 -434 2,462 5.8 -451 2,561 5.5

-821 2,255 17.1 -855 2,349 16.8 -889 2,443 16.5

-1,200 2,078 12.7 -1,250 2,165 11.7 -1,300 2,252 10.7

-1,543 1,839 38.9 -1,607 1,915 37.8 -1,671 1,992 35.4

-1,839 1,543 56.8 -1,915 1,607 55.4 -1,992 1,671 55.2

-2,078 1,200 86.9 -2,165 1,250 102.0 -2,252 1,300 96.4

-2,255 821 75.8 -2,349 855 76.8 -2,443 889 75.6

-2,364 417 83.5 -2,462 434 75.9 -2,561 451 81.5

-2,400 0 109.1 -2,500 0 122.8 -2,600 0 121.2

-2,364 -417 125.5 -2,462 -434 118.9 -2,561 -451 111.1

-2,255 -821 138.4 -2,349 -855 130.1 -2,443 -889 126.6

-2,078 -1,200 126.4 -2,165 -1,250 123.3 -2,252 -1,300 119.1

-1,839 -1,543 114.9 -1,915 -1,607 106.2 -1,992 -1,671 88.9

-1,543 -1,839 114.8 -1,607 -1,915 106.6 -1,671 -1,992 96.7

-1,200 -2,078 81.9 -1,250 -2,165 79.0 -1,300 -2,252 76.4

-821 -2,255 78.4 -855 -2,349 73.5 -889 -2,443 68.9

-417 -2,364 68.8 -434 -2,462 64.2 -451 -2,561 54.5

0 -2,400 66.2 0 -2,500 60.7 0 -2,600 61.2

417 -2,364 91.7 434 -2,462 86.8 451 -2,561 73.7

821 -2,255 71.8 855 -2,349 69.8 889 -2,443 67.8

1,200 -2,078 87.0 1,250 -2,165 83.3 1,300 -2,252 74.5

1,543 -1,839 88.8 1,607 -1,915 85.0 1,671 -1,992 81.0

1,839 -1,543 88.6 1,915 -1,607 83.2 1,992 -1,671 78.6

2,078 -1,200 107.9 2,165 -1,250 102.2 2,252 -1,300 94.1

2,255 -821 45.3 2,349 -855 46.6 2,443 -889 44.9

2,364 -417 109.9 2,462 -434 105.1 2,561 -451 101.6

2,400 0 96.8 2,500 0 95.8 2,600 0 92.4

66

X (m) Y (m) C (ppb) X (m) Y (m) C (ppb) X (m) Y (m) C (ppb)

2,659 469 51.8 2,757 486 56.2 2,856 504 57.2

2,537 923 46.1 2,631 958 43.9 2,725 992 42.6

2,338 1,350 37.9 2,425 1,400 36.7 2,511 1,450 36.4

2,068 1,736 31.5 2,145 1,800 30.8 2,222 1,864 30.7

1,736 2,068 22.8 1,800 2,145 18.2 1,864 2,222 14.6

1,350 2,338 7.2 1,400 2,425 6.9 1,450 2,511 6.6

923 2,537 35.6 958 2,631 34.5 992 2,725 30.9

469 2,659 17.3 486 2,757 17.0 504 2,856 14.6

0 2,700 25.0 0 2,800 25.3 0 2,900 25.0

-469 2,659 5.2 -486 2,757 4.9 -504 2,856 4.7

-923 2,537 15.9 -958 2,631 15.1 -992 2,725 14.0

-1,350 2,338 9.8 -1,400 2,425 9.0 -1,450 2,511 8.0

-1,736 2,068 34.3 -1,800 2,145 32.6 -1,864 2,222 29.1

-2,068 1,736 53.1 -2,145 1,800 50.6 -2,222 1,864 48.0

-2,338 1,350 91.6 -2,425 1,400 85.7 -2,511 1,450 82.4

-2,537 923 72.3 -2,631 958 69.0 -2,725 992 65.5

-2,659 469 73.8 -2,757 486 62.6 -2,856 504 58.0

-2,700 0 111.3 -2,800 0 102.6 -2,900 0 98.3

-2,659 -469 103.0 -2,757 -486 97.7 -2,856 -504 99.0

-2,537 -923 121.4 -2,631 -958 116.2 -2,725 -992 108.8

-2,338 -1,350 116.2 -2,425 -1,400 113.3 -2,511 -1,450 107.1

-2,068 -1,736 77.8 -2,145 -1,800 76.5 -2,222 -1,864 75.3

-1,736 -2,068 88.4 -1,800 -2,145 79.9 -1,864 -2,222 74.4

-1,350 -2,338 72.6 -1,400 -2,425 70.0 -1,450 -2,511 69.2

-923 -2,537 62.5 -958 -2,631 57.0 -992 -2,725 52.2

-469 -2,659 49.9 -486 -2,757 48.0 -504 -2,856 46.1

0 -2,700 60.0 0 -2,800 52.5 0 -2,900 51.1

469 -2,659 68.3 486 -2,757 66.5 504 -2,856 64.7

923 -2,537 67.0 958 -2,631 66.1 992 -2,725 61.6

1,350 -2,338 67.6 1,400 -2,425 69.3 1,450 -2,511 69.8

1,736 -2,068 77.7 1,800 -2,145 74.0 1,864 -2,222 73.9

2,068 -1,736 76.4 2,145 -1,800 72.6 2,222 -1,864 69.7

2,338 -1,350 80.6 2,425 -1,400 77.2 2,511 -1,450 78.8

2,537 -923 40.5 2,631 -958 35.0 2,725 -992 34.9

2,659 -469 97.4 2,757 -486 95.0 2,856 -504 93.1

2,700 0 88.5 2,800 0 90.0 2,900 0 88.0

67

X (m) Y (m) C (ppb) X (m) Y (m) C (ppb)

2,954 521 56.4 178 186 1,036.8

2,819 1,026 39.8 178 -17 2,292.1

2,598 1,500 34.7 178 -186 1,529.2

2,298 1,928 30.3 -14 -186 6,584.5

1,928 2,298 14.5 -178 -186 2,110.5

1,500 2,598 6.4 -178 -17 1,191.1

1,026 2,819 27.9 -178 186 738.1

521 2,954 12.7 -14 186 1,240.6

0 3,000 24.5 186 186 903.0

-521 2,954 4.5 178 83 1,466.4

-1,026 2,819 12.9 178 -117 2,390.0

-1,500 2,598 6.7 86 -186 11,290.5

-1,928 2,298 26.1 -114 -186 2,132.9

-2,298 1,928 45.5 -178 -117 5,151.6

-2,598 1,500 76.6 -178 83 970.6

-2,819 1,026 63.1 -114 186 903.4

-2,954 521 56.1 86 186 1,331.0

-3,000 0 93.4

-2,954 -521 99.6

-2,819 -1,026 103.8

-2,598 -1,500 101.3

-2,298 -1,928 73.2

-1,928 -2,298 69.6

-1,500 -2,598 68.2

-1,026 -2,819 48.4

-521 -2,954 44.2

0 -3,000 53.1

521 -2,954 58.9

1,026 -2,819 59.1

1,500 -2,598 66.7

1,928 -2,298 68.9

2,298 -1,928 63.3

2,598 -1,500 78.8

2,819 -1,026 35.4

2,954 -521 89.9

3,000 0 82.5

68

Site Visit #3: Active Face

X (m) Y (m) C (ppb) X (m) Y (m) C (ppb) X (m) Y (m) C (ppb)

197 35 3,492.0 295 52 1,911.4 394 69 1,174.4

188 68 4,666.2 282 103 2,444.6 376 137 1,505.9

173 100 9,076.9 260 150 2,369.3 346 200 1,502.0

153 129 25,202.3 230 193 1,905.4 306 257 1,235.4

129 153 15,071.3 193 230 1,420.1 257 306 568.1

100 173 4,048.7 150 260 766.1 200 346 519.1

68 188 3,238.3 103 282 423.4 137 376 474.2

35 197 2,975.4 52 295 360.7 69 394 274.8

0 200 2,685.3 0 300 624.7 0 400 150.2

-35 197 2,040.0 -52 295 819.7 -69 394 270.3

-68 188 1,778.0 -103 282 1,448.1 -137 376 412.9

-100 173 1,774.6 -150 260 898.2 -200 346 842.2

-129 153 1,514.3 -193 230 771.7 -257 306 583.3

-153 129 1,517.2 -230 193 682.5 -306 257 540.5

-173 100 1,276.6 -260 150 822.8 -346 200 516.2

-188 68 1,302.3 -282 103 683.0 -376 137 677.3

-197 35 1,076.7 -295 52 753.2 -394 69 721.5

-200 0 1,270.8 -300 0 566.4 -400 0 554.2

-197 -35 1,055.2 -295 -52 675.8 -394 -69 481.2

-188 -68 907.8 -282 -103 635.2 -376 -137 403.1

-173 -100 20,363.3 -260 -150 565.4 -346 -200 369.0

-153 -129 962.6 -230 -193 663.8 -306 -257 339.0

-129 -153 761.0 -193 -230 718.3 -257 -306 476.4

-100 -173 967.0 -150 -260 704.9 -200 -346 485.7

-68 -188 697.8 -103 -282 525.6 -137 -376 400.9

-35 -197 780.0 -52 -295 485.0 -69 -394 235.4

0 -200 495.1 0 -300 407.1 0 -400 239.6

35 -197 557.3 52 -295 376.8 69 -394 280.6

68 -188 608.2 103 -282 509.1 137 -376 379.6

100 -173 827.5 150 -260 606.7 200 -346 359.6

129 -153 868.2 193 -230 573.3 257 -306 666.7

153 -129 1,077.2 230 -193 783.2 306 -257 410.9

173 -100 1,101.1 260 -150 623.7 346 -200 516.2

188 -68 1,673.7 282 -103 851.8 376 -137 819.8

197 -35 1,494.7 295 -52 1,395.8 394 -69 784.9

200 0 2,426.3 300 0 1,353.0 400 0 1,085.0

69

X (m) Y (m) C (ppb) X (m) Y (m) C (ppb) X (m) Y (m) C (ppb)

492 87 818.4 591 104 679.9 689 122 579.0

470 171 882.0 564 205 581.4 658 239 429.1

433 250 1,018.1 520 300 617.6 606 350 300.0

383 321 438.3 460 386 324.8 536 450 178.2

321 383 358.6 386 460 227.4 450 536 145.4

250 433 282.4 300 520 129.1 350 606 109.8

171 470 178.2 205 564 108.5 239 658 87.1

87 492 140.1 104 591 149.2 122 689 175.7

0 500 176.3 0 600 94.3 0 700 77.8

-87 492 123.0 -104 591 64.3 -122 689 37.3

-171 470 158.1 -205 564 147.8 -239 658 126.5

-250 433 320.0 -300 520 170.8 -350 606 143.8

-321 383 358.7 -386 460 273.8 -450 536 233.9

-383 321 458.9 -460 386 315.1 -536 450 229.5

-433 250 404.7 -520 300 358.7 -606 350 232.7

-470 171 441.1 -564 205 275.5 -658 239 293.5

-492 87 354.2 -591 104 343.6 -689 122 337.0

-500 0 515.4 -600 0 381.6 -700 0 321.6

-492 -87 364.0 -591 -104 343.2 -689 -122 300.6

-470 -171 321.6 -564 -205 330.7 -658 -239 357.9

-433 -250 286.4 -520 -300 287.9 -606 -350 244.5

-383 -321 244.2 -460 -386 256.6 -536 -450 286.5

-321 -383 326.7 -386 -460 297.5 -450 -536 297.2

-250 -433 391.4 -300 -520 310.8 -350 -606 250.9

-171 -470 311.4 -205 -564 298.5 -239 -658 295.3

-87 -492 192.4 -104 -591 240.9 -122 -689 161.0

0 -500 194.9 0 -600 188.2 0 -700 137.5

87 -492 294.0 104 -591 178.9 122 -689 199.2

171 -470 308.8 205 -564 242.1 239 -658 148.2

250 -433 286.8 300 -520 171.6 350 -606 314.6

321 -383 309.7 386 -460 184.2 450 -536 219.4

383 -321 481.1 460 -386 334.7 536 -450 284.2

433 -250 611.5 520 -300 543.3 606 -350 386.1

470 -171 448.2 564 -205 491.8 658 -239 358.0

492 -87 681.1 591 -104 434.5 689 -122 306.9

500 0 397.0 600 0 484.1 700 0 335.4

70

X (m) Y (m) C (ppb) X (m) Y (m) C (ppb) X (m) Y (m) C (ppb)

788 139 443.1 886 156 302.9 985 174 349.8

752 274 265.1 846 308 226.3 940 342 181.5

693 400 289.6 779 450 202.5 866 500 143.7

613 514 164.2 689 579 117.9 766 643 104.4

514 613 118.0 579 689 97.6 643 766 76.3

400 693 69.1 450 779 39.2 500 866 28.9

274 752 74.2 308 846 55.9 342 940 47.0

139 788 103.5 156 886 92.5 174 985 55.7

0 800 58.5 0 900 31.6 0 1,000 21.3

-139 788 31.3 -156 886 32.2 -174 985 43.5

-274 752 89.1 -308 846 33.9 -342 940 24.5

-400 693 66.9 -450 779 65.9 -500 866 38.5

-514 613 134.9 -579 689 141.3 -643 766 79.8

-613 514 131.6 -689 579 123.9 -766 643 128.2

-693 400 161.0 -779 450 123.4 -866 500 142.3

-752 274 212.8 -846 308 164.2 -940 342 163.3

-788 139 307.0 -886 156 256.6 -985 174 203.1

-800 0 257.1 -900 0 224.9 -1,000 0 199.6

-788 -139 186.7 -886 -156 148.6 -985 -174 136.0

-752 -274 240.6 -846 -308 214.4 -940 -342 168.4

-693 -400 212.5 -779 -450 202.9 -866 -500 175.2

-613 -514 284.6 -689 -579 227.5 -766 -643 200.9

-514 -613 227.4 -579 -689 202.5 -643 -766 175.4

-400 -693 225.1 -450 -779 176.4 -500 -866 126.3

-274 -752 266.2 -308 -846 188.2 -342 -940 129.6

-139 -788 169.2 -156 -886 144.5 -174 -985 107.3

0 -800 137.5 0 -900 104.9 0 -1,000 83.0

139 -788 240.2 156 -886 149.1 174 -985 122.6

274 -752 176.8 308 -846 162.3 342 -940 114.4

400 -693 186.8 450 -779 128.0 500 -866 142.3

514 -613 161.2 579 -689 151.9 643 -766 186.1

613 -514 303.0 689 -579 264.6 766 -643 202.6

693 -400 240.3 779 -450 160.1 866 -500 137.9

752 -274 246.5 846 -308 211.3 940 -342 179.5

788 -139 255.9 886 -156 144.1 985 -174 103.3

800 0 360.3 900 0 260.8 1,000 0 239.3

71

X (m) Y (m) C (ppb) X (m) Y (m) C (ppb) X (m) Y (m) C (ppb)

1,083 191 231.1 1,182 208 197.0 1,280 226 184.4

1,034 376 165.4 1,128 410 128.9 1,222 445 96.3

953 550 113.0 1,039 600 102.7 1,126 650 85.2

843 707 87.4 919 771 76.9 996 836 69.3

707 843 60.9 771 919 56.7 836 996 55.1

550 953 28.3 600 1,039 20.5 650 1,126 15.0

376 1,034 33.6 410 1,128 24.2 445 1,222 23.7

191 1,083 48.4 208 1,182 33.9 226 1,280 28.9

0 1,100 17.6 0 1,200 16.4 0 1,300 13.3

-191 1,083 25.7 -208 1,182 21.6 -226 1,280 17.5

-376 1,034 15.0 -410 1,128 15.8 -445 1,222 16.4

-550 953 49.3 -600 1,039 48.0 -650 1,126 36.2

-707 843 86.2 -771 919 96.5 -836 996 67.4

-843 707 129.8 -919 771 139.9 -996 836 116.5

-953 550 90.5 -1,039 600 89.2 -1,126 650 80.9

-1,034 376 120.1 -1,128 410 120.7 -1,222 445 111.6

-1,083 191 211.8 -1,182 208 150.5 -1,280 226 103.8

-1,100 0 181.4 -1,200 0 182.1 -1,300 0 156.8

-1,083 -191 139.3 -1,182 -208 164.9 -1,280 -226 161.2

-1,034 -376 150.9 -1,128 -410 185.5 -1,222 -445 147.4

-953 -550 175.1 -1,039 -600 157.2 -1,126 -650 145.4

-843 -707 156.9 -919 -771 127.2 -996 -836 109.0

-707 -843 169.9 -771 -919 158.1 -836 -996 143.6

-550 -953 124.7 -600 -1,039 104.0 -650 -1,126 93.5

-376 -1,034 124.8 -410 -1,128 99.6 -445 -1,222 93.8

-191 -1,083 65.3 -208 -1,182 58.2 -226 -1,280 67.3

0 -1,100 70.0 0 -1,200 55.4 0 -1,300 65.7

191 -1,083 97.5 208 -1,182 94.7 226 -1,280 84.3

376 -1,034 95.4 410 -1,128 82.9 445 -1,222 71.3

550 -953 98.2 600 -1,039 82.2 650 -1,126 55.3

707 -843 173.5 771 -919 128.5 836 -996 95.1

843 -707 134.2 919 -771 102.0 996 -836 100.7

953 -550 118.0 1,039 -600 136.7 1,126 -650 95.0

1,034 -376 142.5 1,128 -410 124.9 1,222 -445 94.7

1,083 -191 97.5 1,182 -208 92.1 1,280 -226 96.0

1,100 0 222.8 1,200 0 151.9 1,300 0 125.4

72

X (m) Y (m) C (ppb) X (m) Y (m) C (ppb) X (m) Y (m) C (ppb)

1,379 243 137.2 1,477 260 99.9 1,576 278 94.2

1,316 479 84.8 1,410 513 77.6 1,504 547 70.2

1,212 700 74.6 1,299 750 68.7 1,386 800 61.7

1,072 900 62.5 1,149 964 56.4 1,226 1,028 51.0

900 1,072 49.0 964 1,149 45.7 1,028 1,226 40.4

700 1,212 15.2 750 1,299 13.4 800 1,386 11.5

479 1,316 21.1 513 1,410 21.1 547 1,504 23.4

243 1,379 32.9 260 1,477 30.8 278 1,576 24.4

0 1,400 14.1 0 1,500 14.8 0 1,600 16.6

-243 1,379 12.0 -260 1,477 10.9 -278 1,576 10.4

-479 1,316 15.7 -513 1,410 10.0 -547 1,504 9.4

-700 1,212 33.5 -750 1,299 26.9 -800 1,386 17.5

-900 1,072 60.9 -964 1,149 55.2 -1,028 1,226 48.1

-1,072 900 106.0 -1,149 964 98.8 -1,226 1,028 99.5

-1,212 700 78.7 -1,299 750 81.0 -1,386 800 83.6

-1,316 479 102.7 -1,410 513 109.3 -1,504 547 93.0

-1,379 243 93.9 -1,477 260 106.0 -1,576 278 95.1

-1,400 0 126.6 -1,500 0 93.0 -1,600 0 76.4

-1,379 -243 137.9 -1,477 -260 115.5 -1,576 -278 92.8

-1,316 -479 139.0 -1,410 -513 124.0 -1,504 -547 123.9

-1,212 -700 131.2 -1,299 -750 121.6 -1,386 -800 109.6

-1,072 -900 98.9 -1,149 -964 96.2 -1,226 -1,028 105.0

-900 -1,072 130.5 -964 -1,149 122.2 -1,028 -1,226 103.9

-700 -1,212 86.8 -750 -1,299 85.5 -800 -1,386 82.4

-479 -1,316 96.3 -513 -1,410 83.6 -547 -1,504 73.7

-243 -1,379 55.3 -260 -1,477 45.6 -278 -1,576 51.6

0 -1,400 69.9 0 -1,500 62.1 0 -1,600 58.4

243 -1,379 78.2 260 -1,477 71.5 278 -1,576 64.9

479 -1,316 47.0 513 -1,410 57.4 547 -1,504 53.7

700 -1,212 55.0 750 -1,299 43.6 800 -1,386 47.3

900 -1,072 72.3 964 -1,149 85.6 1,028 -1,226 78.4

1,072 -900 127.5 1,149 -964 104.8 1,226 -1,028 115.0

1,212 -700 104.9 1,299 -750 97.3 1,386 -800 81.5

1,316 -479 71.7 1,410 -513 90.4 1,504 -547 89.8

1,379 -243 94.2 1,477 -260 81.2 1,576 -278 78.2

1,400 0 105.5 1,500 0 94.6 1,600 0 114.9

73

X (m) Y (m) C (ppb) X (m) Y (m) C (ppb) X (m) Y (m) C (ppb)

1,674 295 81.7 1,773 313 83.1 1,871 330 76.3

1,597 581 70.7 1,691 616 75.4 1,785 650 64.7

1,472 850 50.6 1,559 900 47.6 1,645 950 43.5

1,302 1,093 45.9 1,379 1,157 41.3 1,455 1,221 39.2

1,093 1,302 36.8 1,157 1,379 33.3 1,221 1,455 29.3

850 1,472 10.3 900 1,559 9.5 950 1,645 9.1

581 1,597 22.0 616 1,691 21.8 650 1,785 19.6

295 1,674 18.1 313 1,773 17.7 330 1,871 15.8

0 1,700 15.7 0 1,800 16.5 0 1,900 16.4

-295 1,674 8.2 -313 1,773 7.5 -330 1,871 7.0

-581 1,597 8.9 -616 1,691 8.0 -650 1,785 8.5

-850 1,472 17.7 -900 1,559 19.0 -950 1,645 19.8

-1,093 1,302 40.5 -1,157 1,379 40.7 -1,221 1,455 35.6

-1,302 1,093 97.9 -1,379 1,157 90.8 -1,455 1,221 70.8

-1,472 850 82.0 -1,559 900 75.6 -1,645 950 59.3

-1,597 581 77.3 -1,691 616 80.7 -1,785 650 61.9

-1,674 295 82.2 -1,773 313 74.7 -1,871 330 63.5

-1,700 0 67.8 -1,800 0 71.7 -1,900 0 68.3

-1,674 -295 87.4 -1,773 -313 79.6 -1,871 -330 82.5

-1,597 -581 123.7 -1,691 -616 122.0 -1,785 -650 116.4

-1,472 -850 102.1 -1,559 -900 95.3 -1,645 -950 88.6

-1,302 -1,093 105.9 -1,379 -1,157 97.7 -1,455 -1,221 94.6

-1,093 -1,302 102.6 -1,157 -1,379 98.0 -1,221 -1,455 93.0

-850 -1,472 78.2 -900 -1,559 72.8 -950 -1,645 71.3

-581 -1,597 70.0 -616 -1,691 66.2 -650 -1,785 63.8

-295 -1,674 48.0 -313 -1,773 42.2 -330 -1,871 38.2

0 -1,700 57.8 0 -1,800 64.3 0 -1,900 67.1

295 -1,674 80.3 313 -1,773 77.1 330 -1,871 72.4

581 -1,597 44.2 616 -1,691 40.1 650 -1,785 37.0

850 -1,472 44.0 900 -1,559 49.3 950 -1,645 50.6

1,093 -1,302 79.4 1,157 -1,379 63.7 1,221 -1,455 64.6

1,302 -1,093 96.4 1,379 -1,157 84.8 1,455 -1,221 81.7

1,472 -850 82.0 1,559 -900 70.1 1,645 -950 73.5

1,597 -581 75.6 1,691 -616 60.7 1,785 -650 49.2

1,674 -295 70.6 1,773 -313 69.5 1,871 -330 84.9

1,700 0 102.9 1,800 0 80.1 1,900 0 84.2

74

X (m) Y (m) C (ppb) X (m) Y (m) C (ppb) X (m) Y (m) C (ppb)

1,970 347 74.5 2,068 365 75.4 2,167 382 73.2

1,879 684 53.6 1,973 718 47.0 2,067 752 43.9

1,732 1,000 40.4 1,819 1,050 38.6 1,905 1,100 37.5

1,532 1,286 36.5 1,609 1,350 32.4 1,685 1,414 30.9

1,286 1,532 25.3 1,350 1,609 21.7 1,414 1,685 19.0

1,000 1,732 8.8 1,050 1,819 8.4 1,100 1,905 7.3

684 1,879 18.9 718 1,973 18.6 752 2,067 18.2

347 1,970 14.9 365 2,068 14.0 382 2,167 12.9

0 2,000 13.6 0 2,100 12.8 0 2,200 11.4

-347 1,970 5.2 -365 2,068 4.5 -382 2,167 4.0

-684 1,879 5.9 -718 1,973 4.7 -752 2,067 4.3

-1,000 1,732 20.5 -1,050 1,819 18.1 -1,100 1,905 16.6

-1,286 1,532 34.8 -1,350 1,609 24.3 -1,414 1,685 23.5

-1,532 1,286 62.9 -1,609 1,350 55.5 -1,685 1,414 39.9

-1,732 1,000 61.7 -1,819 1,050 59.2 -1,905 1,100 51.2

-1,879 684 55.6 -1,973 718 52.7 -2,067 752 57.0

-1,970 347 47.8 -2,068 365 46.9 -2,167 382 46.0

-2,000 0 55.3 -2,100 0 55.6 -2,200 0 53.4

-1,970 -347 83.3 -2,068 -365 83.2 -2,167 -382 76.6

-1,879 -684 104.1 -1,973 -718 93.0 -2,067 -752 84.2

-1,732 -1,000 82.9 -1,819 -1,050 77.9 -1,905 -1,100 72.8

-1,532 -1,286 89.0 -1,609 -1,350 81.4 -1,685 -1,414 74.2

-1,286 -1,532 87.6 -1,350 -1,609 82.7 -1,414 -1,685 77.6

-1,000 -1,732 69.6 -1,050 -1,819 66.7 -1,100 -1,905 62.9

-684 -1,879 56.8 -718 -1,973 54.2 -752 -2,067 47.1

-347 -1,970 33.0 -365 -2,068 31.7 -382 -2,167 30.0

0 -2,000 52.4 0 -2,100 43.4 0 -2,200 35.5

347 -1,970 65.5 365 -2,068 63.1 382 -2,167 50.6

684 -1,879 34.7 718 -1,973 31.0 752 -2,067 24.9

1,000 -1,732 40.9 1,050 -1,819 37.1 1,100 -1,905 37.1

1,286 -1,532 64.5 1,350 -1,609 44.7 1,414 -1,685 49.8

1,532 -1,286 69.3 1,609 -1,350 74.1 1,685 -1,414 74.3

1,732 -1,000 68.3 1,819 -1,050 63.0 1,905 -1,100 60.2

1,879 -684 46.8 1,973 -718 57.1 2,067 -752 44.0

1,970 -347 81.0 2,068 -365 74.1 2,167 -382 62.5

2,000 0 78.4 2,100 0 68.0 2,200 0 73.4

75

X (m) Y (m) C (ppb) X (m) Y (m) C (ppb) X (m) Y (m) C (ppb)

2,265 399 64.6 2,364 417 52.4 178 186 3,989.5

2,161 787 41.7 2,255 821 38.7 178 -17 2,564.6

1,992 1,150 35.5 2,078 1,200 32.3 178 -186 922.5

1,762 1,478 29.7 1,839 1,543 28.3 -14 -186 1,323.5

1,478 1,762 17.1 1,543 1,839 15.6 -178 -186 775.1

1,150 1,992 6.8 1,200 2,078 6.4 -178 -17 994.0

787 2,161 17.7 821 2,255 17.1 -178 186 760.6

399 2,265 12.5 417 2,364 11.9 -14 186 1,719.4

0 2,300 10.1 0 2,400 10.0 178 83 4,161.7

-399 2,265 3.6 -417 2,364 3.4 178 -117 1,655.0

-787 2,161 4.1 -821 2,255 4.1 86 -186 1,412.0

-1,150 1,992 16.0 -1,200 2,078 17.6 -114 -186 1,270.2

-1,478 1,762 20.2 -1,543 1,839 15.3 -178 -117 781.4

-1,762 1,478 32.8 -1,839 1,543 28.5 -178 83 610.9

-1,992 1,150 39.6 -2,078 1,200 30.7 -114 186 881.0

-2,161 787 49.3 -2,255 821 43.0 86 186 5,883.4

-2,265 399 44.3 -2,364 417 42.6

-2,300 0 51.6 -2,400 0 44.4

-2,265 -399 71.0 -2,364 -417 67.0

-2,161 -787 80.0 -2,255 -821 76.0

-1,992 -1,150 69.2 -2,078 -1,200 67.0

-1,762 -1,478 71.8 -1,839 -1,543 69.4

-1,478 -1,762 71.3 -1,543 -1,839 64.9

-1,150 -1,992 59.2 -1,200 -2,078 54.4

-787 -2,161 44.7 -821 -2,255 41.5

-399 -2,265 27.0 -417 -2,364 25.1

0 -2,300 31.8 0 -2,400 31.4

399 -2,265 43.5 417 -2,364 38.5

787 -2,161 22.4 821 -2,255 23.0

1,150 -1,992 34.3 1,200 -2,078 32.4

1,478 -1,762 46.2 1,543 -1,839 43.9

1,762 -1,478 73.1 1,839 -1,543 70.7

1,992 -1,150 63.7 2,078 -1,200 58.3

2,161 -787 48.9 2,255 -821 49.8

2,265 -399 70.0 2,364 -417 61.4

2,300 0 77.9 2,400 0 72.2

76

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