University of Florida Thesis Or Dissertation Formatting

VERIFICATION AND VALIDATION OF ATMOSPHERIC TRANSPORT MODELS USING THE UNIVERSITY OF FLORIDA TRAINING REACTOR

GABRIEL ALFREDO SANDLER

A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY

UNIVERSITY OF FLORIDA

2019

To my partner, family, and friends

ACKNOWLEDGMENTS

To begin, I want to thank my adviser Dr. James Baciak for guiding me for the past four and a half years. As a graduate student under Dr. Baciak, I truly learned how to work independently at a high level. I would also like to thank Dr. Andreas Enqvist who was my first research adviser as an undergraduate student and has been an amazing source of help throughout my time as a graduate student. I would also like to thank

Brian Shea, Dan Cronin, and Matt Berglund from the University of Florida Training

Reactor for helping me accomplish tasks essential for my research.

I have also furthered my knowledge and abilities outside the University of Florida.

I would like to thank Dr. Scott Kiff from Sandia National Laboratory and Dr. Micah

Lowenthal from the National Academies of Science for helping me develop new skillsets which I will carry on as I continue my career. Additionally, I would like to thank the

National Nuclear Security Administration for providing funding throughout my graduate career as part of the Consortium for Verification Technology.

My educational path would not have been the same without my mom, dad, and brother. Their support and love throughout the entirety of my life has allowed me to follow my passions and become the person I am today. Also, I would like to thank all the friends I have made in high school, undergrad, and graduate school. My time as a student would not have been the same without you all. Lastly, I would like to thank my partner Hannah Kaufman for providing constant support and pushing me to always be the best version of myself.

TABLE OF CONTENTS

page

ACKNOWLEDGMENTS ...... 4

LIST OF TABLES ...... 7

LIST OF FIGURES ...... 11

LIST OF ABBREVIATIONS ...... 14

ABSTRACT ...... 16

CHAPTER

1 INTRODUCTION AND MOTIVATION...... 18

Introduction to Atmospheric Transport Models ...... 18 Impact of Atmospheric Transport Models in the Nuclear Field ...... 21 Utilizing the University of Florida Training Reactor ...... 26 Objective of Research...... 30

2 THEORY ...... 32

Atmospheric Dispersion Theory ...... 32 Atmospheric Transport Models ...... 34 The Gaussian Dispersion Model ...... 37 The Lagrangian Model ...... 40 The Puff Model ...... 41 The Eulerian Model ...... 42 Computational Fluid Dynamics Modeling ...... 43 Comparison of Models ...... 43 Radiation Detection ...... 45 Gas-filled Detectors ...... 46 Scintillators ...... 47 Semiconductors ...... 48 Selection of Detector for Measurements ...... 49

3 VERIFICATION AND VALIDATION PROCESS ...... 51

Experimental Measurements ...... 51 Instrumentation ...... 51 Measurement Setups ...... 53 Proving the Detectability of the 41Ar Plume ...... 58 Coupling ATMs with MCNP ...... 59 UF Developed MATLAB Gaussian Model ...... 62 AERMOD ...... 64

FLEXPART ...... 68 Summary of Weather Data Sources ...... 71

4 HIGH VELOCITY PLUME STACK ...... 73

Measurement Results for May 2018 and March 2019 Trials ...... 73 Simulation Results for May 2018 and March 2019 Trials ...... 84 Discussion and Analysis of Results ...... 94

5 LOW VELOCITY PLUME STACK ...... 100

Measurement Results for November 2018 and January 2019 Trials ...... 100 Simulation Results for November 2018 and January 2019 Trials ...... 111 Discussion and Analysis of Results ...... 125

6 SENSITIVITY ANALYSIS OF COUPLED MODELS ...... 130

Overview of Proposed Sensitivity Analyses ...... 130 One-factor-at-a-time Sensitivity Analysis ...... 131 Wind Speed ...... 132 Wind Orientation ...... 136 Atmospheric Stability ...... 141 Plume Length and Resolution ...... 141

7 CONCLUSION AND FUTURE WORK ...... 145

APPENDIX: 10 MINUTE AVERAGED MEASUREMENT AND SIMULATION DATA .. 150

LIST OF REFERENCES ...... 185

BIOGRAPHICAL SKETCH ...... 193

LIST OF TABLES

Table page

1-1 August 2017 measurement and low velocity plume stack info ...... 28

1-2 Air sampling information #1 ...... 28

1-3 Air sampling information #2...... 29

2-1 Stability classifications for Gaussian model based on wind speed and solar irradiation...... 39

2-2 Stability classifications for Gaussian model based on atmospheric lapse rate ... 39

2-3 Summary of ATM code selection for various applications and dispersion distances...... 45

3-1 Proposed detectors surrounding UFTR ...... 54

3-2 Detector location coordinates...... 54

3-3 Elevations of selected locations...... 56

3-4 Modified Pasquill stability scheme in the daytime ...... 63

3-5 Parameters used to solve vertical dispersion coefficient (σz)...... 64

3-6 Parameters used to solve horizontal dispersion coefficient (σy)...... 64

4-1 May 8th, 2018 measurement 41Ar count rates and count rate ratios...... 80

4-2 March 20th, 2019 measurement 41Ar count rates and count rate ratios...... 81

4-3 March 22nd, 2019 measurement 41Ar count rates and count rate ratios...... 82

4-4 May 8th, 2018 wind information (averaged hourly) ...... 86

4-5 March 20th and 22nd, 2019 wind information (averaged hourly)...... 87

4-6 Airport weather in-house Gaussian model May 8th, 2018 simulations ...... 87

4-7 UF weather in-house Gaussian model May 8th, 2018 simulations ...... 88

4-8 FLEXPART May 8th, 2018 simulations...... 89

4-9 AERMOD May 8th, 2018 simulations...... 89

4-10 UFTR weather in-house Gaussian model March 20th, 2019 simulations ...... 90

4-11 UF weather in-house Gaussian model March 20th, 2019 simulations...... 91

4-12 FLEXPART March 20th, 2019 simulations...... 92

4-13 UFTR in-house Gaussian model March 22nd, 2019 simulations ...... 92

4-14 UF weather in-house Gaussian model March 22nd, 2019 simulations ...... 93

4-15 FLEXPART March 22nd, 2019 simulations...... 93

4-16 Average percent difference for all models simulating the 41Ar plume emitted by the high velocity plume stack...... 95

4-17 Average percent difference for all models simulating the 41Ar plume emitted by the high velocity plume stack (all results which simulated stations receiving count rates lower than three cps removed)...... 97

5-1 Dose estimation calculations at Weimer Hall on January 18th from 15:00 to 15:30 ...... 102

5-2 November 7th, 2018 measurement 41Ar count rates and count rate ratios ...... 107

5-3 January 16th, 2019 measurement 41Ar count rates and count rate ratios...... 107

5-4 January 17th, 2019 measurement 41Ar count rates and count rate ratios...... 108

5-5 January 18th, 2019 measurement 41Ar count rates and count rate ratios...... 109

5-6 November 7th, 2017 and January 16th-18th, 2019 wind information (averaged hourly)...... 112

5-7 UFTR weather in-house Gaussian model November 7th, 2018 simulations. .... 113

5-8 UF weather in-house Gaussian model November 7th, 2018 simulations ...... 113

5-9 Airport weather in-house Gaussian model November 7th, 2018 simulations. ... 114

5-10 FLEXPART November 7th, 2018 simulations...... 114

5-11 AERMOD November 7th, 2018 simulations ...... 115

5-12 UF weather in-house Gaussian model January 16th, 2019 simulations ...... 115

5-13 Airport weather in-house Gaussian model January 16th, 2019 simulations. .... 116

5-14 FLEXPART January 16th, 2019 simulations...... 116

5-15 AERMOD January 16th, 2019 simulations...... 117

5-16 UFTR weather in-house Gaussian model January 17th, 2019 simulations ...... 117

5-17 UF weather in-house Gaussian model January 17th, 2019 simulations...... 118

5-18 Airport weather in-house Gaussian model January 17th, 2019 simulations...... 119

5-19 FLEXPART January 17th, 2019 simulations ...... 120

5-20 AERMOD January 17th, 2019 simulations...... 120

5-21 UFTR weather in-house Gaussian model January 18th, 2019 simulations...... 121

5-22 UF Weather in-house Gaussian model January 18th, 2019 simulations ...... 122

5-23 Airport weather in-house Gaussian model January 18th, 2019 simulations...... 123

5-24 FLEXPART January 18th, 2019 simulations...... 123

5-25 AERMOD January 18th, 2019 simulations ...... 124

5-26 Average percent difference for all models simulating the 41Ar plume emitted by the low velocity plume stack ...... 126

5-27 Average percent difference for all models simulating the 41Ar plume emitted by the low velocity plume stack (all model results which simulated stations receiving count rates lower than three cps removed) ...... 128

6-1 Maximum % change in count rate ratio as atmospheric stability is altered ...... 141

6-2 Percent difference between March 20th, 2019 12:00 1-hour measurements and UFTR in-house model simulations using 75 cm, 200 cm, and 300 cm resolutions...... 144

A-1 May 8th, 2018 10 minute averaged measurement 41Ar count rates and count rate ratios...... 150

A-2 March 20th, 2019 10 minute averaged measurement 41Ar count rates and count rate ratios ...... 152

A-3 March 22nd, 2019 10 minute averaged measurement 41Ar count rates and count rate ratios ...... 154

A-4 UF 10 min averaged weather in-house Gaussian model May 8th, 2018 simulations...... 156

A-5 UFTR 10 min averaged weather in-house Gaussian model March 20th, 2019 simulations...... 159

A-6 UF 10 min averaged weather in-house Gaussian model March 20th, 2019 simulations...... 161

A-7 UFTR 10 min averaged weather in-house Gaussian model March 22nd, 2019 simulations...... 163

A-8 UF 10 min averaged weather in-house Gaussian model March 22nd, 2019 simulations...... 163

A-9 November 7th, 2018 10 minute averaged measurement 41Ar count rates and count rate ratios ...... 164

A-10 January 16th, 2019 10 minute averaged measurement 41Ar count rates and count rate ratios...... 165

A-11 January 17th, 2019 10 minute averaged measurement 41Ar count rates and count rate ratios...... 167

A-12 January 18th, 2019 10 minute averaged measurement 41Ar count rates and count rate ratios ...... 169

A-13 UFTR 10 min averaged weather in-house Gaussian model November 7th, 2018 simulations ...... 171

A-14 UF 10 min averaged weather in-house Gaussian model November 7th, 2018. 173

A-15 UF 10 min averaged weather in-house Gaussian model January 16th, 2019 simulations...... 174

A-16 UFTR 10 min averaged weather in-house Gaussian model January 17th, 2019 simulations ...... 176

A-17 UF 10 min averaged weather in-house Gaussian model January 17th, 2019 simulations...... 178

A-18 UFTR 10 min averaged weather in-house Gaussian model January 18th, 2019 simulations...... 181

A-19 UF 10 min averaged weather in-house Gaussian model January 18th, 2019 simulations...... 183

LIST OF FIGURES

Figure page

1-1 Potential pathways in pollutant release scenario ...... 20

1-2 Inverse transport modeling utilized to localize third DPRK nuclear test...... 22

1-3 Total deposition of 137Cs and 131I in Japan after Fukushima explosion...... 23

1-4 Wind information taken 10 min before PREX 140La release ...... 25

1-5 Ground-based vehicle results for PREX experiments along with witness plate results...... 25

1-6 UFTR top down rendering of the reactor core...... 27

1-7 Decay diagram of 41Ar ...... 29

2-1 Turbulence, advection, and deposition effects on dispersion ...... 33

2-2 Atmospheric stability effects on plume dispersion...... 33

2-3 Effect of building downwash on atmospheric dispersion ...... 36

2-4 Example of Gaussian atmospheric dispersion ...... 38

2-5 Pasquill’s vertical and horizontal dispersion coefficient graphs...... 39

2-6 Comparing the Lagrangian and Eulerian models...... 44

2-7 Gaussian plume downwind movement vs Puff model trajectory ...... 45

2-8 Voltage operating regions for gas-filled detectors...... 47

2-9 Comparison of pulse height spectra between NaI(Tl) and Ge(Li) detectors...... 49

3-1 RSX-1 detector ...... 51

3-2 Example setup for stand-alone NaI detectors ...... 52

3-3 Weather station placed on top of Rhines Hall...... 53

3-4 Originally proposed detector locations ...... 55

3-5 Finalized detector locations with respect to the high and low velocity plume stacks...... 56

3-6 Detector setups on Weimer Hall, Rhines Hall, Reitz Union, Rhines Hall #2, and Ben Hill Griffin Stadium...... 57

3-7 Google Earth display of low velocity plume stack and RSX-1 location ...... 58

3-8 Reactor emissions spectrum for preliminary 41Ar plume measurement after background subtraction ...... 59

3-9 MCNP visual of buildings surrounding high and low velocity plume stacks...... 61

3-10 AERMOD plume imposed on Google Earth using AERPLOT ...... 68

3-11 Program flow required to run AERMOD ...... 68

3-12 Program flow for the execution of WPS and WRF...... 70

3-13 UF station owned by Alachua County WeatherSTEM ...... 72

4-1 Early morning spectra vs afternoon spectra at Rhines before and after thermal shift normalization ...... 74

4-2 Maximum 30 minute spectra at Rhines, Weimer, Stadium, and Reitz on May 8th, 2018 ...... 77

4-3 Maximum 30 minute spectra at Rhines, Weimer, Rhines 2, and Reitz on March 20th, 2019...... 78

4-4 Maximum 30 minute spectra at Rhines, Weimer, Rhines 2, and Reitz on March 22nd, 2019 ...... 79

4-5 FMESH Tally of 41Ar plume at 12:00 on May 8th, 2018 for in-house model and AERMOD ...... 85

5-1 Decrease in 41Ar count rate after UFTR shutdown...... 101

5-2 Maximum 30 minute spectra at Rhines, Weimer, Rhines 2, and Reitz on November 7th, 2018...... 103

5-3 Maximum 30 minute spectra at Rhines, Weimer, Rhines 2, and Reitz on January 16th, 2019 ...... 104

5-4 Maximum 30 minute spectra at Rhines, Weimer, Rhines 2, and Reitz on January 17th, 2019 ...... 105

5-5 Maximum 30 minute spectra at Rhines, Weimer, Rhines 2, and Reitz on January 18th, 2019...... 106

6-1 Percent change in tally ratio as the wind velocity is altered in the in-house Gaussian MATLAB model ...... 133

6-2 Maximum % change in tally ratios as the wind velocity is altered in the in- house Gaussian MATLAB model ...... 133

6-3 Percent change in tally ratio as the wind velocity is altered in the AERMOD code...... 134

6-4 Maximum % change in tally ratios as the wind velocity is altered in the AERMOD code ...... 134

6-5 Change in plume rise with varying wind velocity (a) full view (b) zoomed in view ...... 135

6-6 Percent change in tally ratio as the wind orientation is altered by 10° in the in- house Gaussian MATLAB model ...... 137

6-7 Maximum % change in tally ratio as the wind orientation is altered by 10° in the in-house Gaussian MATLAB model ...... 137

6-8 Percent change in tally ratio as the wind orientation is altered by 10° in AERMOD...... 138

6-9 Maximum % change in tally ratio as the wind orientation is altered by 10° in AERMOD ...... 138

6-10 Plume direction change near the UFTR from a wind orientation of 80° to 90°. . 139

6-11 Detector grid for secondary set of wind orientation sensitivity analysis simulations...... 140

6-12 Maximum % change in tally ratio as the wind orientation is altered by 20° for initial and secondary detector grids ...... 140

6-13 Percent change in tally ratio as the plume resolution is altered by 7.5 cm in the in-house model...... 142

6-14 Maximum % change in tally ratio as the plume resolution is altered by 7.5 cm in the in-house model ...... 143

LIST OF ABBREVIATIONS

ASOS Automated Surface Observing System

ATM Atmospheric Transport Model

CFD Computational Fluid Dynamics

CPS Counts Per Second

CTBT Comprehensive Test Ban Treaty

CTBTO Comprehensive Test Ban Treaty Organization

DPRK Democratic People’s Republic of Korea

ECMWF European Centre for Medium-Range Weather Forecasts

EMAC ECHAM/MESSy Atmospheric Chemistry

EPA Environmental Protection Agency

GFS Global Forecast System

GM Geiger-Mueller

IDC International Data Centre

IMS International Monitoring System

NCEP National Center for Environmental Prediction

NRC Nuclear Regulatory Commission

NWP Numerical Weather Prediction

NWS National Weather Service

ODE Ordinary Differential Equation

OFAT One-factor-at-a-time

OSI On-site Inspection

PDE Partial Differential Equation

PNNL Pacific Northwest National Laboratory

PREX Particle Release Experiment

RSL Remote Sensing Laboratory

UFTR University of Florida Training Reactor

USGS United States Geological Survey

WPS WRF Preprocessing System

WRF Weather Research Forecast

Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy

VERIFICATION AND VALIDATION OF ATMOSPHERIC TRANSPORT MODELS USING THE UNIVERSITY OF FLORIDA TRAINING REACTOR

Gabriel A. Sandler

August 2019

Chair: James Baciak Major: Nuclear Engineering Sciences

The University of Florida Training Reactor (UFTR) is a 100-kW ARGONAUT type reactor with a unique design such that a large volume of air passes through the core, producing and releasing significant quantities of 41Ar. Once released, the radioargon is dispersed throughout the atmosphere and decays by a 1294 keV gamma ray emission.

This quantified, validated, and controlled 41Ar plume can be utilized to verify and validate atmospheric transport models (ATMs). In this work, we developed a new verification and validation technique by coupling an ATM with MCNP and comparing the results to radiation measurements taken near the UFTR. An in-house developed

Gaussian dispersion model, the EPA approved Gaussian model AERMOD, and the

Lagrangian code FLEXPART were coupled with MCNP to simulate the dispersion of the

41Ar measured on seven different days. These models utilized meteorological data retrieved by weather stations installed by the UFTR, UF athletics program, GNV airport, and National Center for Environmental Prediction Global Forecast System. To collect measurement data, a grid of NaI detectors were placed on five different rooftop locations near the UFTR. The radioactive plume was released by a high velocity plume stack on three measurement days while a low velocity plume stack was used on four

16 measurement days. The simulations predicted some values and trends displayed in the measurement data but failed to consistently produce accurate results. The in-house

Gaussian model using UFTR and UF measured meteorological data provided the most accurate results for the low velocity stack while AERMOD best predicted the 41Ar dispersion for the high velocity stack. Furthermore, the measurements and simulations produced more closely correlated results when the high velocity plume stack was utilized and when lower wind speeds were present. Finally, the sensitivity analysis of several model inputs proved that the MCNP output was most sensitive to changes in the wind orientation. While the three ATMs utilized during this work did not provide consistently accurate results, we proved that the UFTR’s capability to easily emit a measurable 41Ar plume can be used to benchmark other types of ATMs such as computational fluid dynamics codes and short range Lagrangian models.

CHAPTER 1 INTRODUCTION AND MOTIVATION

Introduction to Atmospheric Transport Models

Atmospheric transport models (ATMs), otherwise referred to as atmospheric dispersion models, are utilized to calculate the movement of pollutants as they disperse in the atmosphere. Research in air dispersion modelling began in the 1920s when

British scientists began investigating the dispersal of toxic chemicals in the battlefield under differing types of atmospheric and wind conditions [1]. This research was furthered in the 1930s through work observing the emission and dispersion of effluents through chimneys, otherwise referred to as stacks [2]. From the 1920s to the 1960s, research focused on the dispersion of materials emitted by biological, chemical, and nuclear weapons. While research on biological and chemical weapons looked at short- range dispersion, work in the nuclear field also included long-range transport of radionuclides emitted by nuclear detonations. After the 1960s, research shifted to the study of effluents released from industrial stacks. This occurred at a time when environmental agencies were created and began to regulate the release of industrial pollutants.

Experimental field studies have allowed scientists to gain crucial knowledge on the physics of effluent dispersion in the atmosphere. The methods and techniques utilized for these field experiments vary greatly and depend on the following conditions

[2]:

• Purpose of research • Type of pollutant being released • Timing of pollutant release • Measurement distance • Health effects of pollutant

• Stack height and velocity • Surrounding terrain • Meteorological conditions • Effects of wet and dry deposition, chemical reactions, and radioactivity

Historically, scientists have utilized three distinct methods to better understand the underlying physics occurring during atmospheric dispersion. The first is a technique which allows researchers to visibly outline the dispersion of pollutants. This can be accomplished with tools such as cameras. The second method involves researchers marking particles to follow their trajectory through the atmosphere. The last and most commonly used type of field experiment involves the injection of tracers into the atmosphere so that their concentration can be measured as they disperse downwind.

However, one of the most crucial tools in the development of atmospheric dispersion modeling has been the continuous advancement in computational power and data acquisition systems. Field experiments during the first half of the 20th century collected and analyzed data which was archived through hard copies. Currently, researchers can collect and analyze extremely large datasets in the ranges of gigabytes and terabytes

[2].

There are wide varied applications for ATMs. For example, models have been utilized to better understand the effects of severe air pollution (such as “photochemical smog”) in highly polluted cities and to simulate the release of chemicals from railcars and tanks [3,4]. Furthermore, transport models have simulated the release and transport of pesticides to calculate the unwanted deposition on crops not targeted by the pesticide along with their effect on communities near the source of the pesticide [5]. Yet another application of ATMs includes the modeling of volcanic ash to help develop advisory systems for areas near volcanoes [6]. For a majority of these applications,

19 analyzing the health effects of the dispersing material is the last step in the transport model. Their ability to provide accurate pollutant concentration information allows them to provide regulatory support at institutions like the Environmental Protection Agency

(EPA) [7]. Figure 1-1 displays some of the health hazards and ecological effects associated with the release of a pollutant in the atmosphere.

Figure 1-1. Potential pathways in pollutant release scenario [7]

The ranges of ATMs can be split up into three groups: macroscale (lengths over

1,000 km), mesoscale (lengths between 1 to 1,000 km), and microscale (lengths lower than 1 km) [8]. These scales can also be defined as local (lengths smaller than 10 km), regional (lengths between 20 km to 2,000 km), and global (lengths larger than 2,000 km) [4,9]. However, there are inconsistencies in the definition of these ranges. For example, some reports have listed the regional scale with a range of 200 km to a few thousand kilometers [10].

Impact of Atmospheric Transport Models in the Nuclear Field

In terms of the nuclear field, ATMs can be utilized to track the concentration of radioactive particles and noble gases after nuclear power plant accidents, weapon detonations, and other radioactive releases. For example, the International Monitoring

System (IMS), a network of 321 monitoring stations and 16 laboratories supporting compliance with the Comprehensive Test Ban Treaty (CTBT), has relied on these dispersion models [11]. To stop the creation of new nuclear weapon states and halt any further advancements in nuclear weapon designs, the CTBT was created to ban all countries from detonating nuclear weapons [12]. It was adopted by the United Nations

General Assembly on September 10th, 1996 and has been signed and ratified by 168 states while another 16 states have only signed the treaty (US has signed but not ratified). The IMS is governed by the CTBT Organization (CTBTO) and maintains four types of nuclear weapon monitoring stations; hydroacoustic, infrasound, seismic, and radionuclide. At radionuclide stations, data are obtained through the routine collection and measurement of air samples which are analyzed afterwards by the International

Data Centre (IDC). These samples are tested for the presence of nuclear explosion signatures, mainly the following radioxenon isotopes: 131mXe, 133mXe, 133Xe, and 135Xe

[13,14]. When radionuclide stations detect and measure radioactive traces from a nuclear explosion, the IMS relies on ATMs to analyze the measurement data.

ATMs can be operated in “backwards” mode after obtaining radionuclide data to help localize the source of a nuclear explosion and provide source term estimates for the detonation [15]. Work by De Meutter and Camps observed data obtained by the IMS after the Democratic People’s Republic of Korea (DPRK) announced their third nuclear

21 test [16]. They used this data to inversely run the atmospheric transport code

FLEXPART which allowed them to localize the source of the DPRK nuclear test. The results showed that the DPRK nuclear test site is the most likely location of the nuclear explosion while a second location in East Asia could have also been the source of the test. The authors theorized that this secondary location was predicted by the ATM because of background radioxenon originating from surrounding civilian facilities. Figure

1-2 displays the outputs produced by the model to estimate the possible source locations of the nuclear detonation. Inverse atmospheric transport modeling has also been used for non-nuclear events such as the 2010 volcano eruption of Eyjafallajökull in

Iceland which released large quantities of ash into the atmosphere [17].

Figure 1-2. Inverse transport modeling utilized to localize third DPRK nuclear test [16]

ATMs have also been instrumental in handling nuclear emergency response scenarios such as the Fukushima Dai-ichi nuclear power plant accident. The models can be operated in “forwards” mode to estimate the concentration of radioactive particles as the plume moves downwind along with ground-level dose rates [18]. A

22 study by Christoudias and Lelieveld simulated the Fukushima release through the dispersion of 131I, 137Cs, and 133Xe [19]. For their transport calculations, the

ECHAM/MESSy Atmospheric Chemistry (EMAC) model was utilized in conjunction with source term inputs estimated from previous literature. Surface concentration results from the simulations were compared to measurements taken by a selected number of

IMS stations. The simulations were consistent with the station measurements for 133Xe but not so much for the 137Cs values. The study concluded that 80% of the radioactivity emitted into the atmosphere after the Fukushima explosion was deposited in the Pacific

Ocean. Additionally, it estimated that an area of 34,000 km2 was contaminated by more than 40 kBqm−2, affecting approximately 9.4 million people. When the surface area was expanded to 60,000 km2, it was discovered that the contamination reached an estimated 10 kBqm−2, affecting 46 million people. Figure 1-3 displays the total deposition of 137Cs and 131I in Japan according to EMAC where the black dot represents the location of the Fukushima nuclear plants.

Figure 1-3. Total deposition of 137Cs and 131I in Japan after Fukushima explosion [19]

Moreover, research in the atmospheric dispersion field possesses the ability to support on-site inspection (OSI) capabilities. An OSI supports the CTBT through nuclear weapon test verification techniques such as ground and aerial radiation surveying along with environmental sampling and analysis [20]. However, due to limitations on the number of personnel and time allowed during an OSI, it is essential to have as much knowledge as possible on the localized dispersion of a radioactive plume. Research aimed to improve OSI techniques has included experiments such as the 2013 Particle

Release Experiment (PREX) performed at the Nevada National Security Site and conducted by Pacific Northwest National Laboratory (PNNL) with the aid of the Remote

Sensing Laboratory (RSL) [21]. For this measurement, an underground nuclear explosion was mimicked by releasing 3.7 x 107 kBq of 140La with an air cannon to better understand the localized deposition of radionuclides after an underground nuclear test.

To measure the radioactive plume, witness plates and air samplers were setup near the source location in an array determined by meteorological wind records. Additionally, wind data were measured approximately 10 minutes before the release of the 140La to better understand the plume dispersion (displayed in Figure 1-4). As seen in Figure 1-

4, there is a high variability in wind orientation values due to the specific terrain at the

PREX site. After its release, an aerial survey, vehicle-based survey, in situ measurements, handheld and backpack surveys, and soil sampling were utilized to help characterize the radioactive plume. Once released, the radioactive plume was dispersed into the atmosphere and approximately 14% was deposited within the test site. It was found that the most efficient technique utilized to characterize a radioactive

24 plume was ground vehicle-based surveying with large NaI(Tl) detectors (results displayed in Figure 1-5).

Figure 1-4. Wind information taken 10 min before PREX 140La release [21]

Figure 1-5. Ground-based vehicle measurements for the 140La 1596 keV emitted photons along with witness plate results

After analyzing the data, researchers found large differences in ground deposition activities at small distances. It was discovered that the activity could increase or decrease by as much as six times when moving three meters away from a specific location. This reinforced the idea that soil samples taken at very few locations may cause inspectors to miss evidence of an underground nuclear test. Thus, the ability to characterize the dispersion and deposition of a localized plume with an ATM may serve as a beneficial tool when performing an OSI.

Utilizing the University of Florida Training Reactor

The University of Florida Training Reactor (UFTR) is a nuclear research reactor commissioned in 1959 which is utilized to further research, education, and training [22].

It is a light water and graphite moderated, graphite reflected, light water-cooled reactor licensed to operate at a maximum power of 100 kW [23]. The UFTR is also an

ARGONAUT, named after the ARGOnne Nuclear Assembly for University Training reactor design which first went critical at Argonne National Laboratory in 1957 [24]. One of the most unique features of the UFTR design is the large air gap located in the core.

A top down view of the UFTR core is seen in Figure 1-6. Because a large volume of air passes through the core, a significant quantity of 40Ar undergoes neutron activation and is converted into radioactive 41Ar gas. The radioargon produced in the core of the reactor is released and dispersed into the atmosphere, exposing the public to very small amounts of radiation. Due to this radiation exposure, the amount of 41Ar produced per year is regulated by the Nuclear Regulatory Commission (NRC), making it a limiting constraint on the UFTR’s operation time [26]. However, the creation of a measurable

41Ar plume allows the university to create an easy to use radioactive plume for atmospheric dispersion measurements.

Figure 1-6. UFTR top down rendering of the reactor core [25]

Once the 41Ar is created in the UFTR core, it can be released from either a high or low velocity plume stack. While the UFTR has historically utilized the low velocity plume stack, the measurements presented in this work made use of the high velocity plume stack (which became operational for the first time in May 2018 for these measurements) along with the low velocity plume stack. The high velocity stack was primarily installed to disperse the 41Ar to higher altitudes, reducing the ground-level dose and allowing the UFTR to run at full power for extended periods of time. The

UFTR’s 41Ar emission rate is calculated by taking air samples from the bottom of the stack and measuring their radioactivity. These measurements are performed semiannually by the UFTR staff and have only been completed for the low velocity plume stack. Low velocity plume stack information along with air sampling

27 measurement data taken on August 2nd, 2017 is shown in Table 1-1. The air sampling results obtained from radiation detection measurements are shown in Tables 1-2 and 1-

3. As seen from the tables, six air samples were taken from low velocity plume stack but only the three highest values were utilized to calculate the final value. This is done to account for any potential errors arising from failures in the pumping mechanism which removes the air samples from the stack. By multiplying the 41Ar release point concentration (2.061E-05 µCi m-3) with the true normal chimney flow (13969 cfm), it was concluded that the UFTR releases approximately 1.35E-04 Ci s-1 of 41Ar when operating at full power. To this date, there have been no air sampling measurements taken for the high velocity plume stack. The stack area is 8.836 ft2, true normal flow is 50947 ft3 min-1, and velocity is 29.29 m s-1. This means that the stack velocity increases by 262% when shifting the emission of 41Ar from the low velocity plume stack to the high velocity plume stack.

Table 1-1. August 2017 measurement and low velocity plume stack info Temperature 78 °F Stack Area 6.354 ft2 True Normal Velocity 2162 ft min-1 True Normal Dilution Flow 13737 ft3 min-1 Core Vent Flow 232 ft3 min-1 True Normal Stack Flow 13969 ft3 min-1 Low Plume Stack Velocity 11.168 m s-1 Elevation of Low Plume Stack 50 m

Table 1-2. Air sampling information #1 Delay Count Uncorrected Sample Time Duration Count Rate Number (mins) (min) (cpm) 1 10.65 5 18920 2 16.55 5 16020 3 23.07 5 11200 4 26.75 5 19460 5 32.62 5 17440 6 38.60 5 17560

Table 1-3. Air sampling information #2 Decay Sample Sample Activity in Sample Sample Sample Corrected Concentration DPM Activity Concentration Number Count Rate at Release (cpm efficiency-1) (µCi) (µCi ml-1) (cpm) (µCi ml-1) 1 20233.3 3.127E+06 1.408 1.127E-03 1.871E-05 2 17780.9 2.748E+06 1.238 9.902E-04 1.645E-05 3 12952.2 2.002E+06 0.902 7.213E-04 1.198E-05 4 23032.9 3.559E+06 1.603 1.283E-03 2.130E-05 5 21419.4 3.310E+06 1.491 1.193E-03 1.981E-05 6 22395.4 3.461E+06 1.559 1.247E-03 2.071E-05 Average 1.0935E-03 1.816E-05 Average (high three) 1.2409E-03 2.0609E-05

It takes approximately 15 to 30 minutes for the reactor to reach full power after startup and an estimated 30 to 90 minutes for the 41Ar emission rate to reach equilibrium. Once the 41Ar is released into the atmosphere, it undergoes a beta decay and releases a 1293.6 keV gamma ray with a branching ratio of 99.16% and a 1.83 hour half-life as seen in Figure 1-7 [27,28].

Figure 1-7. Decay diagram of 41Ar [28]

Objective of Research

The formulation of ATMs and the verification and validation work which has accompanied their creation has been accomplished through field measurements. As previously discussed, plumes simulated with these models have been tested through optical techniques, marking and following the trajectories of specific particles, and measuring the concentration of air tracers. Additionally, research in the nuclear field has utilized radiation measurement techniques to map out the movement of plumes downwind. However, no extensive research has attempted to test these dispersion models for radioactive plumes through the comparison of experimental radiation measurements and radiation transport simulations.

In this work, the UFTR’s ability to easily provide a quantified, validated, and controlled 41Ar plume was used to gather radiation measurement data. To collect this measurement data, detector grids were placed near the reactor to provide count rates coming from the 41Ar emitted photons. The experimental datasets were then compared with ATM simulations by coupling the ATM results with MCNP6. Through this coupling, we were able to compare simulation results with radiation measurements, a technique which can help benchmark atmospheric transport models. To fully test ATMs with this technique, sensitivity analysis was performed to provide potential sources of error in the coupled model output.

Due to the UFTR’s close proximity with nearby buildings, this research focused on testing this verification and validation technique for short-range radioactive plumes in an urban-like terrain. Because the half-life of 41Ar is relatively similar to that of nuclear explosion signatures such as 133Xe (5.27 days), this research could aid the

30 effectiveness of ATMs in the compliance of the CTBT [29]. Moreover, the UFTR could also benefit from this work to eventually expand its dose prediction toolset once a model has been fully verified and validated. Currently, the UFTR utilizes the regulatory code

“COMPLY” which calculates the estimated ground-level dose concentration of 41Ar semiannually. However, this model is extremely conservative, does not account for the effects of nearby buildings, and does not output any raw 41Ar concentration data. In summary, the overarching goals of this work were to establish the UFTR as a tool to test different types of ATMs and to attempt a coupled ATM-MCNP technique for the verification and validation of dispersion models at short ranges with urban-like conditions.

CHAPTER 2 THEORY

Atmospheric Dispersion Theory

Atmospheric dispersion theory is the study of pollutant concentration estimation as it moves throughout the atmosphere in a plume. The dispersion of a pollutant depends heavily on two factors, local wind conditions (advection) and turbulence

(diffusion) [30]. The local wind condition refers mainly to the local wind speed and direction. On the other hand, turbulence can be separated into two parts, mechanical and thermal turbulence [31]. Mechanical turbulence is caused by the wind shear created when air passes over large obstacles such as buildings, mountains, and hills. Thermal turbulence on the other hand is caused by buoyancy and depends on atmospheric stability, defined as the degree in which the atmosphere promotes or reduces vertical mixing. Atmospheric stability can be determined by observing the adiabatic lapse rate, defined as the decrease in temperature as altitude increases [32]. To define atmospheric stability, the adiabatic lapse rate of dry air close to the earth’s surface (9.77

°C km-1) is compared with the actual environmental lapse rate. If the actual lapse rate is larger than the dry adiabatic lapse rate, air will tend to move vertically, promoting the diffusion of radionuclides. In this situation, the atmosphere is considered to be in unstable equilibrium. If the actual lapse rate is smaller than the adiabatic lapse rate, upward motion is reduced, thus the atmosphere is in stable equilibrium. A stable atmosphere will reduce the dilution of pollutants in the atmosphere and can lead to larger ground concentrations near the source of the pollutant. Additionally, the concentration of a pollutant in the atmosphere will decrease through wet and dry deposition. While dry deposition is a continuously occurring process in the atmosphere,

32 wet deposition may only take place when precipitation is present. Figure 2-1 displays the effects of turbulence, advection, and deposition on a plume while Figure 2-2 shows the differences in plume dispersion with varying atmospheric stabilities.

Figure 2-1. Turbulence, advection, and deposition effects on dispersion [33]

Figure 2-2. Atmospheric stability effects on plume dispersion (a) Looping from unstable lapse rate (b) Coning from neutral lapse rate (c) Fanning from strongly stable conditions (d) Lofting from conditions that are stable below and neutral above (e) Fumigation from unstable conditions below with stable above [32]

Furthermore, temperature tends to decrease at higher altitudes in the atmosphere. An area in the atmosphere in which the temperature increases at higher elevations is termed an inversion layer [34]. These layers create a stable atmosphere which forces pollutants down to the ground. Three types of inversions can be formed through varying mechanisms: frontal, advective, and radiative. A frontal inversion occurs when hot or cold air collides with a front of the opposing temperature (hot to cold or cold to hot). Since the air mass with the higher temperature is more buoyant, the total air mass will possess a top layer with hot air and a bottom layer with cold air. While this type of inversion reduces vertical mixing, it also creates strong winds and rain which leads to further dispersion of pollutants. Advective inversion occurs when a mass of hot air moves over cold ground or air. This tends to occur when cities are surrounded by mountains, creating higher levels of pollution. Lastly, radiative inversions occur when the ground cools down too quickly, causing the air near the ground to rapidly cool down.

If low wind speeds are present, mixing does not occur and an inversion is created above the ground.

Atmospheric Transport Models

Atmospheric transport models utilize mathematical equations and physical assumptions to solve for the dispersion of pollutants in the atmosphere. Each type of model utilizes a distinct method to solve for the transport equation of a volume of fluid, which is derived through the law of conservation of mass and is presented in Equation

(2-1) as,

푑 ∭ 푐푑푉 = − ∯ 푐푣̅푑퐴̅ + ∭ 푆푐푑푉 − ∯(−퐷푐훻푐), 푑푡 (2-1) 푉1 휕푉1 푉1 푉1

34 where 푣̅ is the wind vector, 푆푐 the source parameter, 퐷푐 the diffusion coefficient, 푉1 the fluid volume, and 푐 the concentration of the fluid [35]. ATMs can utilize either meteorological or numerical weather prediction (NWP) model data along with information on wet and dry deposition, chemical reactions, and radiological decay to calculate the concentration of a pollutant. Wet and dry deposition, chemical reactions, and radioactive decay are accounted for in the source term of Equation (2-1). The transport equation can be solved into its differential form which produces the three- dimensional advection-diffusion equation shown below [33]:

휕퐶 + 훻 ∙ (퐶푢⃑ ) = 훻 ∙ (푲훻퐶) + 푆 . 휕푡 푐 (2-2)

The first term on the left side of the equation represents the change of concentration over time while the second represents the wind advection term. On the right side of the equation, the first term represents pollutant diffusion while the second is the source term. Since turbulent diffusion, otherwise referred to as eddy diffusivity, serves as the dominant mode of mixing in the atmosphere, molecular diffusion can be ignored.

Molecular diffusion is only considered in the dispersion equation at distances extremely close to the ground (approximately 0.1 to 3 cm). Equation (2-2) can be expanded to represent the time-averaged dispersion Equation (2-3) by continuing the assumption of negligible molecular diffusion along with an assumption of isotropic horizontal turbulence and incompressibility,

휕푐̅ 휕 휕푐̅ + 푢̅훻푐̅ = 훻 (퐾 훻 푐̅) + 퐾 + 푆 , 휕푡 ℎ ℎ ℎ 휕푧 푧 휕푧 푐 (2-3) where 훻ℎ represents the horizontal divergence, 퐾ℎ the horizontal eddy diffusivity, and 퐾푧 the vertical eddy diffusivity [35].

Several types of ATMs also utilize terrain and building information to more accurately calculate pollutant dispersion. The techniques and algorithms which account for these obstacles can be crucial for simulations in urban-like settings. A study by

Hyojoon Jeong researched the effects of both terrain and buildings on the transport of radioactive material at the Wolsong nuclear site in South Korea [36]. After testing various ATMs, he concluded that the maximum predicted concentration of radioactive material decreased sevenfold when terrain and building information was not included.

Buildings affect the trajectory of a plume through building downwash, displayed in

Figure 2-3. During this process, turbulent wake zones (shown in Figure 2-3 as blue and white arrows) are formed around the building, pulling the effluent down and hindering the plume from rising higher up into the atmosphere. Additionally, building downwash enhances the horizontal dispersion of the plume.

Figure 2-3. Effect of building downwash on atmospheric dispersion [37]

The most popular types of ATMs are the Gaussian, Lagrangian, Puff, Eulerian, and Computational Fluids Dynamics (CFD) models. The next sections will discuss each of these models in depth.

The Gaussian Dispersion Model

The Gaussian dispersion model uses the mechanism of diffusion along with

Gaussian distributions to estimate the radionuclide concentrations inside a plume.

Regulatory agencies such as the EPA use Gaussian models because of their tendency to over-predict pollutant ground-level concentrations [38]. This has made Gaussian models the most commonly utilized type of ATM. To derive the Gaussian model equation, the following assumptions are made [39]:

• Continuous emission from a point source • Constant wind speed and direction • No downwind diffusion • No inversion layers • Inclusion of upward reflection from the ground • Dispersion is a function of downwind distance

With these assumptions, the turbulent diffusion equation can be solved analytically, producing the Gaussian dispersion model equation [35],

푄 푦2 −(푧 − 퐻)2 −(푧 + 퐻)2 퐶(푥, 푦, 푧) = [푒푥푝 − ( 2)] {푒푥푝 [ 2 ] + 푒푥푝 [ 2 ]}, 2휋푈휎푦휎푧 휎푦 2휎푧 2휎푧 (2-4) where 퐶 is the concentration of the radionuclide at point (푥, 푦, 푧), 푄 is the emission rate of the radionuclide, 푈 is the wind speed, 퐻 is the effective stack height, 휎푦 is the horizontal dispersion coefficient, and 휎푧 is the vertical dispersion coefficient. The effective stack height, otherwise referred to as the height of the virtual point source, is described by

퐻 = ℎ + ∆ℎ, (2-5) where ℎ is the physical height of the source and ∆ℎ is the vertical distance the plume rises before it begins to disperse in the atmosphere. As the radionuclide flows downwind, the vertical and horizontal dispersion is modeled through a normal distribution. This spread moves outward from the centerline of the plume and is

37 dependent on downwind distance and atmospheric stability. Figure 2-4 displays a visual example of dispersion represented by the Gaussian model.

Figure 2-4. Example of Gaussian atmospheric dispersion [39]

The vertical and horizontal dispersion coefficients are also known as Pasquill’s diffusion parameters, named after the English meteorologist Frank Pasquill. These values were empirically derived in the 1950s and 1960s through Pasquill’s smoke- plume measurements [40]. The results for both coefficients can be seen in Figure 2-5.

Each graph in Figure 2-5 contains six distinct lines which represent the change in the dispersion coefficient value at increasing downwind distances for a specific atmospheric stability classification. Pasquill’s atmospheric stability groups are divided into the following groups:

• Extremely Unstable Conditions (Group A) • Moderately Unstable Conditions (Group B) • Slightly Unstable Conditions (Group C) • Neutral Conditions (Group D) • Slightly Stable Conditions (Group E) • Moderately Stable Conditions (Group F)

To select the correct atmospheric stability class, one can utilize surface wind speed and solar irradiation data (displayed in Table 2-1) or through atmospheric lapse rate information (shown in Table 2-2).

(a) (b) Figure 2-5. Pasquill’s vertical (a) and horizontal (b) dispersion coefficient graphs [32]

Table 2-1. Stability classifications for Gaussian model based on wind speed and solar irradiation [32] Daytime Insolation Nighttime Conditions Surface Wind ≥ 4/8 ≤ 3/8 Speed (m s-1) Strong Moderate Slight Cloudiness Cloudiness < 2 A A-B B - - 2 A-B B C E F 4 B B-C C D E 6 C C-D D D D > 6 C D D D D

Table 2-2. Stability classifications for Gaussian model based on atmospheric lapse rate [32] Pasquill’s Temperature change with height Categories (°C per 100m) A < -1.9 B -1.9 to -1.7 C -1.7 to -1.5 D -0.5 to 1.5 E 2.5 to 4.0 F > 4.0

The Lagrangian Model

For Lagrangian models, an ‘air parcel’ (otherwise referred to as an “air particle”) is modeled through a random walk process which uses wind field data, turbulence information, and buoyancy effects [35,41]. The concentration at different positions is estimated stochastically by simulating the trajectory of a large quantity of air parcels.

This trajectory is calculated by using the following equation:

푑푟⃗ = 푣⃗ + 푣⃗ + 푣⃗ , 푑푡 푡 푚 (2-6) where 푟 is the position of the air particle, 푣⃗ is the grid scale velocity accounting for advection, buoyancy, and settling, 푣⃗푡 is the velocity variable accounting for turbulence, and 푣⃗푚 is the mesoscale wind velocity fluctuation [35]. To estimate the wind turbulence variable, a random walk process is utilized in conjunction with the Langevin equation:

2 푤푡 2휎푤 푑푤푡 = − 푑푡 + √ 푑푊, 푇푙 푇푙 (2-7) where 푇푙 is a Lagrangian integration time step, 푤푡 is the vertical turbulent wind parameter, 휎푤 is the standard deviation of the vertical turbulent wind velocity, and 푑푊 represents a Weiner process (otherwise referred to as Brownian motion) with a mean of zero and variance 푑푡. Both the horizontal and vertical wind turbulence are calculated through the Langevin equation. The Lagrangian time step can be inserted directly in a

Lagrangian model or calculated by using velocity fluxes. To calculate these fluxes,

Lagrangian models tend to utilize either Monin-Obukhov theory or eddy diffusivities. The

Langevin equation must be solved several times for different wind components when turbulence is anisotropic due to the model’s assumption of Gaussian turbulence.

Furthermore, the Langevin equation has been modified to account for mesoscale

40 horizontal wind shear, buoyancy, and convective boundary layer turbulence while radioactive decay and deposition are accounted for through the reduction of the air parcel’s mass.

The Puff Model

The Puff model was developed as a fusion between Gaussian and Lagrangian dispersion models. It was created due to the assumption that while a plume tends to disperse in a Gaussian-like manner for horizontal and vertical directions, it does not usually move in a straight line in the downwind direction [35]. Instead of following a straight path, a plume tends to move in a Lagrangian-like trajectory. This allows the Puff model to account for time, a quality the Gaussian model does not possess. The model operates by releasing the pollutant into a small number of “puffs” which are dispersed in the atmosphere in a Lagrangian-like manner. However, the distribution inside each puff is calculated with Gaussian distributions. The final concentration distribution of the pollutant is calculated by utilizing the following equation:

푁 2 2 2 푄훥푡 1 (푥푘 − 푥) (푦푘 − 푦) (푧푘 − 푧) 푐 (푥, 푦, 푧) = 1.5 ∑ 푒푥푝 (− 2 − 2 − 2 ), (2휋) 휎푥푘휎푦푘휎푧푘 2휎푥푘 2휎푦푘 2휎푧푘 (2-8) 푘=1 where 푄훥푡 is the source term, N is the number of puffs, (xk,yk,zk) is the position of the k- th puff, 휎푥푘 is the Gaussian distribution dispersion coefficient inside the k-th puff in the x- direction, 휎푦푘 is the Gaussian distribution dispersion coefficient inside the k-th puff in the y-direction, and 휎푧푘 is the Gaussian distribution dispersion coefficient inside the k-th puff in the z-direction [35]. Like the Gaussian dispersion model equation, the puff model equation can account for buoyancy effects through plume rise equations and can be modified to include effects of ground reflection.

The Eulerian Model

The Eulerian model utilizes a stationary frame of reference to estimate the dispersion of a pollutant [42]. This is accomplished by solving the atmospheric dispersion equation with the correct initial and boundary conditions [35]. There are two popular techniques that are used to solve the equation. The first and most commonly used technique is the “method of lines” [35,43]. It divides the atmospheric dispersion equation, a partial differential equation (PDE), into a series of ordinary differential equations (ODE) through numerical discretization. This is done by replacing the spatial derivates in Equation (2-3) with approximations, referred to as spatial discretization

[35,44]. To accomplish this spatial discretization, techniques such as the finite difference, finite volume, finite element, spectral, and pseudo-spectral methods can be used. Once discretized, the PDE can be divided up into a group of ODEs where the only remaining independent variable is time. This system of ODEs can then be solved through numerical integration, otherwise referred to as temporal or time integration.

Integration techniques such as the explicit, implicit, and Crank-Nicolson method can be used to solve these ODEs.

The Eulerian model possesses the ability to calculate many parameters over time. This includes wind speed and direction, temperature, pressure, chemical concentrations, and radioactivity information. When utilized for large scale dispersion simulations, the Eulerian model requires large computational power due to the extensive amount of numerical integration required. Operational splitting is one technique that has been utilized to speed up this process [35,45]. It allows the atmospheric transport equation to be divided up into subset equations which are solved

42 at the same time but for different aspects of the plume dispersion. For example, this could mean that the transport equation is divided up into horizontal advection, horizontal diffusion, deposition, and radioactivity equations.

Computational Fluid Dynamics Modeling

As computational power has increased, the possibility of CFD codes being used to simulate atmospheric dispersion have risen. CFD models are most appropriate when trying to calculate the concentration of a pollutant in local dispersion simulations. This is especially true for simulations involving concentration grids equal to or smaller than one kilometer in urban areas [35]. For the purpose of dispersion modeling, CFD codes solve the Navier-Stokes-equation for turbulent incompressible fluids, seen below:

휕푣⃗ 1 + (푣⃗훻)푣⃗ = − 훻푝 − 푔⃗ + 푣 훻2푣⃗, 휕푡 휌 푇 (2-9) where 푣⃗ is the wind field component, 휌 is density, 푝 is pressure, 푣푇 is the eddy viscosity and 푔 accounts for gravity [35]. These models possess four distinct capabilities which allow users to model fluid flow. This includes the ability to create a mesh, solve a PDE version of the Navier-Stokes equation, incorporate turbulence effects, and generate 2D and 3D plots of the fluid flow. For atmospheric dispersion cases, the PDE solvers tend to utilize finite volume solvers to deal with the Navier-Stokes-equation for turbulent incompressible fluids [35].

Comparison of Models

When attempting to simulate an atmospheric dispersion problem, the appropriate selection of ATM depends on the specific scenario. For example, the Eulerian model utilizes a stationary frame of reference for concentration calculations while the

Lagrangian model calculates the trajectory of the plume [42]. Thus, for small dispersion

43 distances, the Lagrangian model is more desirable than the Eulerian model since the

Eulerian model’s fixed grid would necessitate a small resolution to account for large gradients. However, the Eulerian model is more efficient for long distance simulations since the Lagrangian model would require a large quantity of particles to be simulated.

Figure 2-6 helps to display these differences.

Figure 2-6. Comparing the Lagrangian and Eulerian models [46]

Because of their similarity to Gaussian models and their ability to account for temporal and spatial changes in source emission and wind data, puff models were the first type of ATM to simulate long range atmospheric transport problems. Figure 2-7 displays the basic differences between the Gaussian and puff models. However, as mentioned earlier, CFD models are ideally utilized when small range simulations are required. A summary of appropriate model selection depending on different applications and dispersion grid ranges is shown in Table 2-3.

Figure 2-7. Gaussian plume downwind movement vs Puff model trajectory [35]

Table 2-3. Summary of ATM code selection for various applications and dispersion distances [35] < 1 1-10 10 – 100 100 – 1000 Application km km km km Online risk management - Gaussian Puff Eulerian Complex Terrain CFD Lagrangian Lagrangian Eulerian Reactive materials CFD Eulerian Eulerian Eulerian Source-receptor sensitivity CFD Lagrangian Lagrangian Lagrangian Long-term average loads - Gaussian Gaussian Eulerian Volcanoes - Lagrangian Lagrangian Lagrangian Convective boundary layer CFD Lagrangian Eulerian Eulerian Stable boundary layer CFD Lagrangian Eulerian Eulerian Urban areas CFD CFD Eulerian Eulerian

Radiation Detection

For this work, our ability to verify and validate ATMs depends on radiation detectors measuring the photons emitted by the UFTR released 41Ar particles. Thus, it is imperative to discuss the theory behind radiation detection. Gamma-ray detectors are commonly divided up into the following groups: Gas detectors, scintillators, and semiconductors.

Gas-filled Detectors

Gas-filled detectors are some of the oldest and most commonly used type of radiation detectors [47]. The most prominent types are ionization chambers, proportional counters, and Geiger-Mueller Counters. For all gas-filled detectors, a charged particle is counted after interacting with the gas, creating the ion-pair necessary to produce an electronic signal. When a charged particle enters an ionization chamber, it directly ionizes the gas, creating the ion pairs which produce a pulse in the presence of an electric field. For these detectors, the voltage is kept within the “ion saturation” region, a voltage zone where ion pairs do not undergo recombination. In this region, increasing the applied voltage does not change the amplitude of the pulse. If the applied voltage is increased past the ion saturation region, the pulse amplitude will begin increasing linearly along with the voltage. This is termed as operating the gas-detector in the “proportional region”, which as the name implies, is the voltage region utilized by proportional counters. At these higher voltages, the ion pairs formed in a gas-detector can undergo multiplication through the creation of avalanches, leading to higher pulse amplitudes. All avalanches are roughly the same, explaining why the charge collected in proportional detectors correlates linearly with the number of initially ionized electrons.

Due to these features, proportional detectors can be utilized for spectroscopy. When the voltage is increased even further, a gas-detector will arrive at the Geiger-Mueller (GM) region and is considered a GM counter. The physics inside these detectors can be explained through the “Geiger discharge”, where avalanches are created at an exponential rate, ending the proportionality between incoming radiation energy and voltage. Due to this large increase in avalanche creation, GM counters do not require

46 any external amplification equipment, making them the most economic choice in photon detection when radiation spectroscopy is not required. Figure 2-8 displays the different regions of operation for all three types of gas-filled detectors.

Figure 2-8. Voltage operating regions for gas-filled detectors [47]

Scintillators

Scintillation detectors utilize scintillation light to measure radioactivity through a four-step process. First, incident radiation deposits some or all of its energy in the scintillating material which in turn becomes excited. The detector material will deexcite by isotropically emitting scintillation photons which scatter and reflect inside of the detector until they escape or are absorbed. If a scintillation photon reaches either a photomultiplier or photodiode, they are converted into an electric pulse. For an idealized scintillation detector, all incoming radiation would interact with the scintillator material

(detection efficiency) and possess the ability to convert the kinetic energy of radiation into light at a high rate (scintillation efficiency). Additionally, it would maintain a linear correlation between the energy deposited and the amount of light created, possess a

47 short decay time, be transparent to the radiation it emits, have a refractive index of approximately 1.5, and be cheap and easy to manufacture [47]. The scintillator material must possess a refractive index of approximately 1.5 to match the optical properties of the glass end window of the photomultiplier tube. This helps minimize the effects of internal reflection and optimizes the collection of scintillation light [47].

Since it is difficult to find materials with all these qualities, researchers have been continuously testing different types of scintillation material. These detectors are divided up into two categories, inorganic and organic. Inorganic detectors tend to possess high

Z-values, high scintillation efficiencies, and a relatively linear correlation between light and deposited energy. However, they tend to possess large decay times on the order of microseconds. Organic detectors on the other hand have smaller decay times (order of nanoseconds) but are made up of lower Z material, possess lower scintillation efficiencies, and tend to struggle with linearity of light output. Due to its excellent light yield and relative ease to manufacture, the inorganic NaI(Tl) detector is the most commonly used type of scintillation detector.

Semiconductors

Semiconductors utilize the creation of electron-hole pairs when hit by incident radiation to create pulses. While the physics behind them is fairly similar to gas-filled ionization chambers (electron-hole pairs vs ion pairs), semiconductors are 2000 to 5000 times denser than gases. Due to this large increase in information carriers, semiconductors possess an improved energy resolution when compared to gas-filled detectors and scintillators. Silicon (Si) and germanium (Ge) are generally the most used materials for semiconductor detectors while others such as cadmium telluride (CdTe)

48 and cadmium zinc telluride (CZT) have increased in popularity. Figure 2-9 displays the difference in spectra between NaI(Tl) and Ge(Li) detectors.

Figure 2-9. Comparison of pulse height spectra between NaI(Tl) and Ge(Li) detectors [48]

Selection of Detector for Measurements

While semiconductors are the ideal choice when trying to differentiate between photon peaks of similar energies (due to their excellent energy resolution), scintillators tend to possess higher detection efficiencies due to their higher atomic number. Some semiconductors such as germanium detectors have acceptable detection efficiencies but are harder to manufacture in large sizes when compared to scintillators.

Additionally, many germanium detectors require continuous cooling with liquid nitrogen, making them more difficult to use in the field. The measurements performed for this

49 work required the utilization of mobile detectors which could discern the 1294 keV peak emitted by the 41Ar. Due to their ability to perform spectroscopy, high detection efficiencies, and ease of transportation, NaI scintillation detectors were chosen to carry out the measurements.

CHAPTER 3 VERIFICATION AND VALIDATION PROCESS

Experimental Measurements

Instrumentation

Two types of large volume NaI(Tl) detectors were chosen to measure the radiation emitted by the UFTR. The first type was the RSX-1, a 4 x 4 x 16 in3 (4 L) NaI detector coupled to a PMT in a carbon fiber package which connects to a RS-701 integrated console, seen in Figure 3-1 [49].

Figure 3-1. RSX-1 detector [25]

This detection system has been developed by Radiation Solutions Inc. and contains an advanced digital spectrometer which processes incoming photon pulses and generates a fully linearized 1024 channel spectrum used in conjunction with its accompanying software (RadAssist). Once turned on, the detector automatically stabilizes itself with natural background and adjusts its gain. This diminishes any fluctuations in the spectrum which could arise from temperature changes or drift effects due to aging. Additionally, eight stand-alone 2 x 4 x 16 in3 (2 L) Saint-Gobain crystal NaI detectors were utilized throughout the measurements in addition to the RSX-1. These

51 detectors were each equipped with either an Ortec Model 266 or a Saint-Gobain P-1410

14-pin PMT base and were connected to a Struck SIS3316 16-channel digitizer for data collection. Each detector was powered by either a CAEN DT14xxET, CAEN NDT1470, or an Ortec 556 high voltage power supply. All stand-alone NaI detectors were calibrated before the first set of measurements with a 60Co source to select the appropriate operating voltage on each detector. This source was selected because the

41Ar emitted photon energy (1294 keV) falls between the 1172.2 keV and 1332.5 keV gamma rays released by 60Co. An example setup for the stand-alone detectors is displayed in Figure 3-2. To maximize the detection of the 1294 keV photons with the standalone NaI detectors, either of the two sides with the larger surface area was oriented towards the atmosphere.

Figure 3-2. Example setup for stand-alone NaI detectors (Photo courtesy of author.)

Furthermore, a weather station was installed on the Rhines Hall rooftop (shown in Figure 3-3) to acquire localized meteorological data. The main component of the weather station is Campbell Scientific’s CR1000X, a measurement and control datalogger. Attached to the CR1000X is a temperature and relative humidity probe

(CS215), 6-plate solar radiation shield (RAD06) manufactured by METSPEC, Vaisala

PTB110 barometer (CS106), Gill 2-D sonic wind sensor (WINDOSNIC4-L10-PW), digital thermopile pyranometer (CS320-W5), and a GARMIN GPS receiver with an integrated antenna (GPS16X-HVS-PW). For the purpose of this thesis, this weather station is referred to as the UFTR weather station. It was programmed to record averaged meteorological data every 1, 10, 30, and 60 minutes.

Figure 3-3. Weather station placed on top of Rhines Hall (Photo courtesy of Kelsey Stadnikia, University of Florida.)

Measurement Setups

In order to maximize the 41Ar signal, it was decided that all detectors be placed on different rooftops near the UFTR. A large list of possible detector locations was created before measurements began (shown in Table 3-1). The coordinates for each site are specified in Table 3-2 (Universal Transverse Mercator coordinate system units) while Figure 3-4 displays their location through the placemark feature on Google Earth.

A total of 24 locations were originally selected for measurement due to their proximity to the UFTR. Ideally, detectors would be simultaneously located at each spot, creating a 53 large detection grid. This scenario would require the possession of at least 24 detectors and their associated electronics and data acquisition systems.

Table 3-1. Proposed detectors surrounding UFTR # of Proposed Building Name Building # Detectors Ben Hill Griffin Stadium 0155/0157 3 Weil Hall 0024 4 Rhines Hall 0184 3 Reed Hall 0131 1 Weil Cooling Towers 0048 1 Nuclear Sciences (NSC) 0634 3 Nuclear Reactor Building (NRB) 0557 1 Weimer Hall 0030 4 Materials Engineering (MAE) 0719 1 Reitz Union 0686 3

Table 3-2. Detector location coordinates Easting Northing Elevation Placemark (m E) (m N) (m above sea level) Stadium #1 369372 3280683 87 Stadium #2 369461 3280651 64 Stadium #3 369532 3280682 66 Weil #1 369427 3280580 55 Weil #2 369468 3280576 55 Weil #3 369537 3280578 55 Weil #4 369514 3280556 56 Rhines #1 369409 3280520 52 Rhines #2 369438 3280513 52 Rhines #3 369432 3280441 49 Reed 369511 3280526 52 NSC #1 369504 3280477 47 NSC #2 369520 3280452 46 NSC #3 369547 3280465 58 NRB 369513 3280504 48 Weimer #1 369550 3280525 57 Weimer #2 369564 3280487 53 Weimer #3 369588 3280546 57 Weimer #4 369637 3280494 57 MAE 369398 3280402 50 Reitz #1 369474 3280353 60 Reitz #2 369569 3280379 58 Reitz #3 369675 3280322 53 Cooling Tower 369474 3280512 47

Figure 3-4. Originally proposed detector locations

Due to the lack of available detectors, associated equipment, and manpower to place radiation detectors on all 24 sites, five detector sites were chosen to best represent the four cardinal directions with respect to the two UFTR plume stacks. It would have been possible to place the detectors on more than five locations by changing detector site locations on each plume measurement day, but it was decided that consistency in detector locations would be beneficial when testing the ATM-MCNP coupled model with various types of atmospheric and wind conditions. As seen in Figure

3-5, two detector sites were placed on Rhines Hall and one on Weimer Hall, Reitz

Union, and Ben Hill Griffin Stadium. For clarity, the lower Rhines Hall rooftop detector location is referred to as Rhines #2 while the high and low velocity plume stacks are also labeled. The elevations of the five selected rooftops and plume stacks are displayed in Table 3-3. Furthermore, the ground-level elevation above sea level near the UFTR is approximately 38 to 41 meters.

Figure 3-5. Finalized detector locations with respect to the high and low velocity plume stacks

Table 3-3. Elevations of selected locations Rooftop Elevation (m above sea level) High Plume Stack 58 Low Plume Stack 50 Rhines Hall 52 Rhines Hall #2 49 Weimer Hall 57 Ben Hill Griffin Stadium 64 Reitz Union 58

While five sites were chosen, only four at a time were utilized for each measurement due to the availability of only three digitizers to use with the standalone NaI detectors in addition to the RSX-1. Additionally, constraints on our access to the Ben Hill

Griffin Stadium rooftop along with the manpower necessary to place detectors on this location did not allow this location to be used for more than one measurement (results presented in Chapter 4). Figure 3-6 displays the detector setups at each of the five locations.

(a) (b)

(e) Figure 3-6. Detector setups on (a) Weimer Hall (b) Rhines Hall (c) Reitz Union (d) Rhines Hall #2 (e) Ben Hill Griffin Stadium (Photo courtesy of author and Kelsey Stadnikia, University of Florida.)

Proving the Detectability of the 41Ar Plume

To assure the UFTR could be used to verify and validate ATMs, a measurement was conducted in 2016 with the low velocity plume stack to test the detectability of the photons emitted by the 41Ar plume [25]. For this test, the RSX-1 detector was placed 20 meters away from the low velocity plume stack as seen in Figure 3-7, where the top circle represents the RSX-1 location and the bottom circle displays the plume stack.

RSX-1

Low Plume Stack

Figure 3-7. Google Earth display of low velocity plume stack and RSX-1 location

A background radiation survey was taken for approximately 78 minutes with the reactor off. Once the background survey was completed, the reactor was operated and the plume built up for 30 minutes while the reactor reached full power. Data were then collected for approximately 26 minutes. As expected, the 1294 keV 41Ar peak was detected after subtracting background counts and is visible when observing the background subtracted spectra (seen in Figure 3-8). The background-subtracted count rate for this measurement was calculated at 70.78 ± 1.19 CPS of 41Ar, demonstrating the ability to detect the UFTR’s 41Ar emission with a large-volume NaI detector.

Figure 3-8: Reactor emissions spectrum for preliminary 41Ar plume measurement after background subtraction [25]

Coupling ATMs with MCNP

To model a plume in MCNP, an ATM of choice is used to predict the concentration profile of the 41Ar plume by inputting the appropriate meteorological conditions. These conditions will vary depending on the atmospheric and wind data recorded during the experimental measurements. Additional information regarding the plume stack, terrain, and buildings surrounding the UFTR may be added to the ATM.

The concentration profile results are then coupled with MCNP by defining the plume as a 3-dimensional grid of point sources. Each point source holds information on its position and probability of occurrence, defined by the concentration calculated in the

ATM at that location. Additionally, all ATMs ignored any aging the plume might experience due to radioactive decay because it would have small effects on the concentration results. This effect was predicted by utilizing Equation 3-1 [50]:

푥 퐷 = 푒푥푝 (−ѱ ), 푢푠 (3-1)

59 where 퐷 is the decay term for the plume concentration, ѱ is the decay coefficient for

41 Ar, 푥 the downwind distance, and 푢푠 the wind speed. For the ATM simulations, the maximum downwind distance was 500 m while the wind speeds were usually larger than 0.5 m s-1. For this scenario, the maximum value for the decay term was only 90%, thus it was assumed that the effects of radioactive decay on the 41Ar plume were negligible.

While the source information for each simulation changes depending on atmospheric and wind conditions along with the appropriate plume stack information

(low vs high velocity plume stack), most of the MCNP file remains the same. This is referred to as the MCNP base input file. It contains dimensional information on the buildings surrounding the two UFTR plume stacks. This includes the Weil cooling towers, Weil Hall, Rhines Hall, Weimer Hall, Reed Hall, Weimer Hall, Nuclear Sciences

(NSC), Nuclear Reactor Building (NRB), Materials Engineering (MAE), the Reitz Union, and a portion of the Ben Hill Griffin Stadium. Each building is defined by cuboids fully made of concrete. Figure 3-9 displays the building representations created in MCNP for the base input file. The entire stadium was not modeled due to the assumption that the tallest structure on the stadium rooftop would be an adequate representation of the shielding material affecting photons moving in a southerly direction towards the radiation detectors. The NaI detectors utilized for the measurements were modeled at each of the five chosen measurement locations with a density of 3.67 g cm-3 [51].

Furthermore, a 39 m thick block of earth (represented by U.S. averaged soil information) was placed beneath all buildings to represent the terrain above sea level.

The F8 tally, which is normalized to one source particle and is commonly used to

60 simulate detector response was utilized to calculate the number of pulses recorded at each detector. For the 41Ar plume simulations, these tally results depend on the ability of the photons to interact and deposit energy inside of the simulated NaI detector volume.

Figure 3-9. MCNP visual of buildings surrounding the high and low velocity plume stacks To accelerate the run time of the simulations, the CUT card was utilized to kill photons with energies lower than 1280 keV. Additionally, a DXTRAN sphere was placed around each detector to force photons towards them [52]. While the CUT card and

DXTRAN spheres were able to significantly improve the efficiency of the simulations, most runs were performed on HiPerGator (University of Florida’s high performance supercomputer) because of the large number of simulations required to test various 41Ar plumes [53].

Three ATMs were selected for verification and validation with the UFTR emitted

41Ar. This included an in-house developed MATLAB model (Gaussian), AERMOD

(Gaussian), and FLEXPART (Lagrangian). Two Gaussian models were chosen due to

61 their popularity amongst regulatory agencies and industry. Additionally, the Lagrangian model FLEXPART was selected due to its heavy involvement in several nuclear security and emergency response studies. As research progresses in this project, more intricate models could be coupled with MCNP (discussed in Chapter 7). For each of the three

ATM codes, MATLAB scripts were developed to process their output concentration files and input the appropriate source information into a MCNP input file. Moreover, only the

AERMOD code accounts for building downwash, but even this code does not fully eliminate 41Ar concentrations inside of buildings. Thus, an algorithm was implemented in each processing code to lower the concentration of the 41Ar to zero when the ATM simulates the plume in a position where a building is located. While this algorithm assures that a source particle does not originate inside of a building, it leads to an underestimation of plume concentrations near ground-level. The next few sections will describe each of these ATMs in more detail.

UF Developed MATLAB Gaussian Model

An UF Gaussian model, otherwise referred to as the in-house model, was developed on MATLAB by using Equation 2-4 where the emission rate of the radionuclide is a constant determined from UFTR calculations (1.36 x 10-4 Ci s-1) and the wind speed is directly inserted from meteorological data. As stated earlier, the effective stack height is determined through the sum of the physical stack height and the plume rise. Calculating the rise of the plume can be done by using one of several plume rise equations [50]. For this model, the plume rise equation was chosen from previous UFTR documentation and is displayed in Equation 3-2 [54,55]:

푣 1.4 훥ℎ = 푑 ( 푠) , 푢 (3-2) where 푑 is the diameter of the stack, 푣푠 is total stack velocity, and 푢 is wind speed. As previously discussed, the horizontal and vertical dispersion coefficients depend on the atmospheric stability classification which is determined by solar irradiance and wind speed. Table 3-4 displays the modified Pasquill stability scheme used to determine these classifications for the in-house model. Since no measurements were taken at night, only daytime stability classifications are included.

Table 3-4. Modified Pasquill stability scheme in the daytime [56] Wind Day time incoming solar radiation (W m-2) Speed Strong Moderate Slight Overcast (m s-1) > 600 300 – 600 < 300 ≤ 2 A A-B B C 2-3 A-B B C C 3-5 B B-C C C 5-6 C C-D D D >6 C D D D

Once the atmospheric stability is classified, the horizontal and vertical dispersion coefficients can be calculated by using Equations 3-3 through 3-5 [50]:

휎푦 = 465.11628(푥) tan(푇퐻), (3-3)

푇퐻 = 0.017453293[푐 − 푑푙푛(푥)], (3-4)

푏 휎푧 = 푎푥 , (3-5) where 푥 is the downwind distance in kilometers and the coefficients 푎, 푏, 푐, and 푑 are determined by looking at the appropriate parameters in Tables 3-5 and 3-6. While these coefficients can be solved for downwind distances larger than 1 km, the values are not displayed because the plumes simulated for this work never exceeded a downwind distance of 1 km. Furthermore, the in-house model allows the user to determine the resolution and length of the plume in the x, y, and z directions.

Table 3-5. Parameters used to solve vertical dispersion coefficient (휎푧) [50] Stability x (km) 푎 푏 Classification < 0.10 122.800 0.94470 0.10-0.15 158.080 1.05420 0.16-0.20 170.220 1.09320 0.21-0.25 179.520 1.12620 A 0.26-0.30 217.410 1.26440 0.31-0.40 258.890 1.40940 0.41-0.50 346.750 1.72830 0.51-1.00 453.850 2.11660 0.21-0.40 90.673 0.93198 B < 0.40 98.483 0.98332 > 0.40 109.300 1.09710 C All 61.141 0.91465 < 0.30 34.459 0.86974 D 0.31-1.00 32.093 0.81066

Table 3-6. Parameters used to solve horizontal dispersion coefficient (휎푦) [50] Stability 푐 푑 Classification A 24.167 2.5334 B 18.333 1.8096 C 12.5 1.0857 D 8.333 0.72382

This model does not include any algorithms that account for building and terrain effects on plume dispersion. This was done to compare a simple Gaussian model with a fully developed Gaussian code. For this comparison, the EPA approved Gaussian model

AERMOD was selected.

AERMOD

The American Meteorological Society/U.S. EPA Regulatory Model Improvement

Committee began working on the development of AERMOD in 1991 [57]. By 2000, the model was approved to be the EPA’s preferred dispersion model for simple and complex terrain, replacing the Industrial Source Complex code. Five years later, the

EPA announced that AERMOD would be the preferred model for all dispersion analysis.

The AERMOD code is a steady-state ATM which uses a Gaussian model in the horizontal and vertical directions. However, it uses a bi-Gaussian probability density function in the vertical direction at altitudes near the convective boundary layer.

AERMOD uses several preprocessors for improved accuracy in dispersion analysis [58]. This includes AERSURFACE, AERMINUTE, AERMET, BPIPPRM,

AERGRID, and AERMAP. The preprocessor AERMET was designed to prepare and process meteorological data and can only be utilized once the user has run both the

AERSURFACE and AERMINUTE preprocessors [59]. AERSURFACE processes specific location data taken from the U.S. Geological Survey (USGS) National Land

Cover Data archives to account for any type of surface effects [60]. For the purposes of this project, USGS data for Gainesville, Florida was downloaded and utilized in all

AERMOD simulations. To run AERSURFACE, the user must enter the center of the site which measures meteorological data. Since AERMOD takes data from US Air Force weather stations, the GNV airport was chosen as the source of meteorological data and the location was inserted as 376955.42 E and 3285118.27 N (Universal Transverse

Mercator coordinates which are utilized by AERMOD on the concentration output files).

To calculate the effective surface roughness length, the user must input a distance from the center of the site location which the user guide recommends being 1 km.

Additionally, the seasonal temporal resolution without any snow cover option was selected along with the definition of the Gainesville region as not arid. The AERMINUTE code processes 1-minute Automated Surface Observing System (ASOS) wind data and averages it hourly [61]. Approximately 900 ASOS sites which measure meteorological data and assist weather forecasts exist in the US [62]. They are primarily stationed at

65 airports and owned by the National Weather Service (NWS) and/or the Federal Aviation

Administration. Once collected, this data is saved in the Global Surface Hourly database. The outputs created from AERMINUTE and AERSURFACE are utilized alongside upper air (collected by NWS) and hourly surface meteorological data

(collected by ASOS stations) to run AERMET. For this project, the 1-min ASOS data and hourly surface meteorological data were collected from the Gainesville Regional

Airport while the upper air datasets were taken from the Jacksonville airport. While the

Jacksonville airport weather station is approximately 65 miles away from the UFTR, it is the closest source of upper air meteorological data. Information regarding both meteorological stations were entered into the first of AERMET’s three input files. Each input file represents one of the three stages required to successfully run AERMET. The first extracts meteorological data from the surface and upper air data files, the second fuses all data (divided into 24-hour sections) to a temporary file, and the third processes the temporary file and calculates boundary layer parameters to create the meteorological files necessary to run AERMOD. Two output files are created by

AERMET which include meteorological information such as wind direction, wind speed, temperature, relative humidity, sensible heat flux, and the associated standard deviations of these parameters. An option labeled “STABLEBL” was utilized in the third stage of AERMET to accurately change surface friction velocity when low wind velocities and a stable atmosphere were present [59]. After running AERMET, the only other preprocessors required to run AERMOD are AERGRID and AERMAP (must be run after AERGRID). AERGRID allows the user to easily create a receptor network by inputting the center, width, length, and spacing of the grid. This grid directs where the

66 concentrations of the pollutant will be calculated. Due to the small grid distances required for this work, the resolution of the grid was chosen to be two meters. Since

AERGRID did not allow the receptor grid to have more than 99 values in the x and y direction, the width and length of the grid were both selected to be 198 m. While the minimum allowable spacing on AERGRID is one meter, a two meter grid was selected because it was desired to keep the grid length and width greater than the maximum distance between the plume stack and all detector locations (approximately 150 meter distance between high plume stack and the Reitz Union). The effects of plume length and resolution on the MCNP output are discussed in more detail in Chapter 6. After running AERGRID, AERMAP is utilized to analyze the terrain information acquired from

AERSURFACE along with AERGRID’s receptor information to finalize the receptor grid

[63]. However, a MATLAB post-processing code was created to add receptor elevation information to the finalized receptor grid file. This was necessary because AERMAP output files only create ground-level receptor grids. To maximize the resolution in the z direction while assuring that the receptor grid file and AERMOD output would not grow too large, the resolution was determined to be 2 m throughout all simulations.

Furthermore, the user has the option to add the preprocessor BPIPPRM to the final simulation. This preprocessor processes the information of nearby buildings to account for the physical effects of building downwash [64]. This includes building elevation data along with the location of building edges in terms of UTM coordinates.

After running all preprocessors, the AERMOD simulation can be performed. The output concentrations produced by AERMOD can be plotted on Google Earth through the postprocessor AERPLOT (small concentration grid example displayed in Figure 3-

10). The full flow schematic of the AERMOD modeling system is also shown in Figure 3-

11.

Figure 3-10. AERMOD plume imposed on Google Earth using AERPLOT

Figure 3-11. Program flow required to run AERMOD [65]

FLEXPART

FLEXPART is a Lagrangian particle dispersion model coded on Fortran 95 which can be compiled on gfortran, Absoft, and Portland Group on Linux, Solaris, and Mac OS

X [41]. It simulates long-range and mesoscale pollutant transport from point, line, area, or volume sources. While the main version of FLEXPART utilizes meteorological data from the European Centre for Medium-Range Weather Forecasts (ECMWF), other versions have been developed to pair FLEXPART with numerical weather simulation codes designed to solve dispersion problems with smaller grid resolutions. One of these versions is called the FLEXPART-WRF code, and as the name implies, it utilizes the

Weather Research Forecast (WRF) model which is a mesoscale weather simulation code [66]. Since this study requires ATMs to formulate plumes with small grid resolutions, FLEXPART-WRF was utilized.

The WRF model requires the installation of the WRF Preprocessing System

(WPS) to solve for the appropriate meteorological field conditions. There are three separate executables which are required to run the WPS: geogrid, ungrib, and metgrid.

Geogrid obtains terrain information by analyzing global data sets which include information such as terrain height, soil temperature, and monthly albedo to create a simulation domain. The data required to run geogrid is acquired online from the WPS geographical input database. The executable ungrib is used to extract meteorological data from GRIB (General Regularly-distributed Information in Binary) data files. This type of meteorological data file has been standardized by the World Meteorological

Organization’s Commission for Basic Systems due to its ability to efficiently transfer large quantities of gridded information [67]. Lastly, the metgrid program takes the meteorological data extracted by ungrib along with the area created by geogrid and interpolates accordingly. The WRF model, which is split up into an initialization (real) program and a numerical integration of pollutant dispersion (wrf) program, can be

69 utilized after running metgrid. Figure 3-12 displays the program flow necessary to run

WPS and WRF.

Figure 3-12. Program flow for the execution of WPS and WRF

One input file is utilized to run all three WPS executables while a second input file runs both the real and wrf programs. The user has the option to specify a domain or nested domains along with latitudinal and longitudinal information regarding the domain.

For the purpose of this work, no nested domains were created for the receptor grid.

Additionally, the user has the option to decide on the time interval for the simulations, which for this work was kept constant at one hour.

After obtaining the WRF outputs, FLEXPART can be used to simulate the plume.

On FLEXPART’s input file, the turbulence option was turned on in order to use Hanna’s turbulence parametrization scheme which tends to be utilized in the main FLEXPART-

ECMWF version [41]. Additionally, the CBL switch was used on the FLEXPART simulations to model the turbulence with a skewed distribution rather than a Gaussian one when the 41Ar disperse in the convective boundary layer. In terms of the wind fields, time-averaged winds were utilized due to recommendations on the FLEXPART-WRF

70 manual. The geographical longitude and latitude of the lower left corner of the receptor grid were kept constant at -82.353°N and 29.643°W (FLEXPART utilizes degree units for latitude and longitude) while the upper right hand corner of the grid was defined with a longitude and latitude of -82.343°N and 29.653°W. For all simulations, the number of grid points in the x and y directions were held constant at 1000, meaning that the resolution of the grid was approximately 1.11 meters due to the 0.01° length of the grid in the x and y directions. Lastly, the grid spacing interval in the z direction cannot exceed 14, thus the resolution of the grid height was defined as 5 meters and extended up to 70 meters above ground level to appropriately calculate the concentrations of the plume at higher levels of the atmosphere.

Summary of Weather Data Sources

There are four sources of weather data used for this work. As already mentioned, the UFTR weather station and the GNV airport weather stations recorded the meteorological data necessary to run the Gaussian models. A third weather station located on top of the Ben Hill Griffin Stadium was added to our toolbox to simulate the

41Ar dispersion (seen in Figure 3-13). This station is operated by the Alachua County

WeatherSTEM for the University of Florida athletics program [68]. The company maintains an online database of historical data which was utilized to simulate the 41Ar dispersion. For the purpose of this work, the results associated with this station will be referred to as UF station results. Lastly, the Lagrangian code FLEXPART utilized data taken from the Global Data Assimilation System. This source of data comes from surface observations, balloon data, wind profiler data, aircraft reports, buoy observations, radar observations, and satellite observations and is mainly utilized by the

National Center for Environmental Prediction (NCEP) Global Forecast System (GFS)

[69]. This data is directly extracted by metgrid and processed by WRF to successfully run FLEXPART.

Figure 3-13. UF station owned by Alachua County WeatherSTEM [68]

CHAPTER 4 HIGH VELOCITY PLUME STACK

Measurement Results for May 2018 and March 2019 Trials

The first extended 41Ar plume measurement utilizing the high velocity plume stack was performed on May 8th, 2018 [70]. These measurements were performed in conjunction with a set of aerial measurements led by PNNL and RSL which required the use of the high velocity stack to release the 41Ar plume at higher altitudes to test their low activity algorithms. Seven NaI detectors were placed on the Ben Hill Griffin Stadium,

Weimer Hall, Rhines Hall, and the Reitz Union rooftops. The RSX-1 was placed on the

Reitz rooftop while each of the other three locations was equipped with two stand-alone

NaI detectors. Background data were collected for 30 minutes before the reactor was turned on at 8:30. The UFTR reached 100 kW at 9:04 and 41Ar equilibrium at approximately 9:40 (timing information on UFTR startup and 41Ar equilibrium was obtained from UFTR operator log sheets). The detectors collected data continuously until 16:30 when the reactor was shut down. Furthermore, calibration runs were performed with 137Cs and 22Na sources after background data collection and reactor shutdown.

Due to the extended period of time each detector was exposed to sunlight exposure generating significant temperature increases, there was a significant thermal shift in a majority of the spectra. To fix this, spectra were stabilized by using the maxima of the natural 40K photon peak (see Figure 4-1). As previously mentioned, the RSX-1 detector automatically solves issues due to thermal shift, so no further stabilization was required. The thermal shift algorithm was utilized for all future plume measurement data processing.

40K 41Ar Morning Spectrum Morning Spectrum Afternoon Spectrum Afternoon Spectrum -1 10 -1

Counts Counts

-2 10 -2 10 800 1000 1200 1400 1600 1800 2000 2200 800 1000 1200 1400 1600 1800 2000 2200 Energy (keV) Energy (keV) (a) (b) Figure 4-1. Early morning spectra vs afternoon spectra at Rhines (a) before and (b) after thermal shift normalization

The measurement data were divided into 10 minute intervals beginning at 9:40

(after 41Ar equilibrium) and ending at 16:30 (after reactor shutdown). For all three stations with two or three standalone detectors, the measured count rates were averaged between all the detectors. The 30 minute averaged spectra with the largest

41Ar count rates at each location on May 8th are displayed in Figure 4-2 to show the presence of the 1294 keV 41Ar peak in the data. When comparing the spectra at each location, there is a noticeable spectral shift occurring at higher energies, indicating that the NaI detectors are not correctly calibrated at these energies. However, the 41Ar peaks on all spectra were correctly calibrated, thus the spectral shift at higher energies can be ignored for this work. After performing background subtraction, the total 41Ar count rate for each detector was calculated and averaged every 10, 30, and 60 minutes.

Count rates between detectors were averaged and background subtraction was performed using Equation 4-1:

∑푁 푠 − 푏 퐷푒푡푒푐푡표푟 푆푡푎푡𝑖표푛 퐶표푢푛푡 푅푎푡푒 = 푛=1 푛 푛, 푁 ∗ 푡 (4-1)

74 where 푠푛 are the counts when the UFTR is running, 푏푛 are the background counts, 푡 is the averaging time, and 푁 is the number of detectors on the station. The standard deviation of the detector station count rate was calculated using Equation 4-2:

√∑푁 푠 + 푏 휎 = 푛=1 푛 푛. 퐷푒푡푒푐푡표푟 푆푡푎푡𝑖표푛 퐶표푢푛푡 푅푎푡푒 푁 ∗ 푡 (4-2)

Table 4-1 displays the data in counts per second (cps) for 30 and 60 minute averaged data while Table A-1 in the Appendix presents the 10 minute averaged results. The considerable difference in 41Ar counts between the detectors located at

Rhines Hall and the rest of the stations stems from the domination of easterly winds during the morning and early afternoon. For all the data, six count rate ratios were calculated to create a normalized value which was used to better compare the experimental measurements with the simulation results. To calculate these count rate ratios, Equation 4-3 was used:

퐷푒푡푒푐푡표푟 푆푡푎푡𝑖표푛 퐶표푢푛푡 푅푎푡푒 #1 퐶표푢푛푡 푅푎푡푒 푅푎푡𝑖표 = . 퐷푒푡푒푐푡표푟 푆푡푎푡𝑖표푛 퐶표푢푛푡 푅푎푡푒 #2 (4-3)

Tables 4-1 and A-1 display the count rate ratios alongside the count rates. To calculate the error propagation for the count rate ratios, Equation 4-4 was used:

휎 2 휎 2 휎 = 퐶표푢푛푡 푅푎푡푒 푅푎푡𝑖표 ∗ √( 퐶표푢푛푡 푅푎푡푒 #1 ) + ( 퐶표푢푛푡 푅푎푡푒 #2 ) . 퐶표푢푛푡 푅푎푡푒 푅푎푡𝑖표 퐶표푢푛푡 푅푎푡푒 #1 퐶표푢푛푡 푅푎푡푒 #2 (4-4)

To expand our dataset for the high velocity plume stack, two new measurements were taken on March 20th and 22nd of 2019. Three standalone NaI detectors were placed on the lower Rhines Hall rooftop (Rhines #2), three on the Reitz Union, and two at Weimer Hall, while the RSX-1 was stationed on the taller Rhines Hall rooftop.

Background data was collected for 20 minutes and the reactor was turned off at 16:30

75 on both days. During the March 20th measurements, the UFTR was turned on at 9:20 and reached full power at 9:42, while 41Ar production stabilized at 10:45. From 10:50 to

11:20, the Weimer Hall measurement station’s data collection batch file malfunctioned.

This occurred at the Rhines Hall #2 station as well from 13:20 to 14:30. During the

March 22nd experiments, the UFTR was turned on at 9:00, reached 100 kW at 9:18, and reached equilibrium at 10:30. The maximum 30 minute spectra for both days at each of the four stations is displayed in Figure 4-3 (March 20th) and Figure 4-4 (March 22nd).

The background subtracted 41Ar count rates averaged every 30 and 60 minutes are displayed in Tables 4-2 and 4-3 (Tables A-2 and A-3 display the 10 minute averaged data). Data with count rates and count rate ratios equaling zero represent times were either a malfunction took place in the software or a negligible 41Ar background subtracted count rate (< 0.01 cps) was recorded. The variable wind speeds recorded on

March 20th led to a wide dispersion of the 41Ar plume, providing an expansive dataset which was utilized along with the May 2018 measurement data to attempt to verify and validate the three ATMs. However, the March 22nd measurements provided a relatively poor dataset for comparison with simulation data. This was due to the constant domination of westerly winds throughout the entirety of the measurements, leading to extremely low 41Ar count rates on the Rhines Hall and Reitz Union rooftops. The only usable data on March 22nd comes from measurements between 10:30 to 11:30 because afterwards there is a negligible number of counts detected in three of the four stations.

(a)

(b)

(c)

(d)

Figure 4-2. Maximum 30 minute spectra at (a) Rhines (b) Weimer (c) Stadium (d) Reitz on May 8th, 2018

(a)

(b)

(c)

(d)

Figure 4-3. Maximum 30 minute spectra at (a) Rhines (b) Weimer (c) Rhines #2 (d) Reitz on March 20th, 2019

(a)

(b)

(c)

(d)

Figure 4-4. Maximum 30 minute spectra at (a) Rhines (b) Weimer (c) Rhines #2 (d) Reitz on March 22nd, 2019

Table 4-1. May 8th, 2018 measurement 41Ar count rates and count rate ratios Average Start Rhines Stadium Weimer Reitz 푆푡푎푑𝑖푢푚 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푆푡푎푑𝑖푢푚 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (cps) (cps) (cps) (cps) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푆푡푎푑𝑖푢푚 29.27 ± 5.89 ± 4.69 ± 0.41 ± 20.10% ± 16.00% ± 1.40% ± 125.40% 8.80% ± 7.00% ± 10:00 0.12 0.09 0.09 0.08 0.31% 0.32% 0.27% ± 3.05% 1.68% 1.33% 37.27 ± 3.72 ± 3.89 ± 0.45 ± 10.00% ± 10.40% ± 1.20% ± 95.70% ± 11.50% ± 12.00% ± 10:30 0.13 0.08 0.09 0.08 0.23% 0.24% 0.21% 3.08% 2.04% 2.13% 43.91 ± 4.50 ± 4.85 ± 0.14 ± 10.20% ± 11.10% ± 0.30% ± 92.70% ± 3.00% ± 3.20% ± 11:00 0.14 0.09 0.09 0.08 0.20% 0.21% 0.16% 2.47% 1.63% 1.74% 44.10 ± 4.78 ± 5.76 ± 0.36 ± 10.80% ± 13.10% ± 0.80% ± 82.90% ± 6.20% ± 7.50% ± 11:30 0.14 0.09 0.09 0.08 0.20% 0.21% 0.17% 1.99% 1.35% 1.64% 42.47 ± 2.27 ± 5.91 ± 0.45 ± 5.30% ± 13.90% ± 1.10% ± 38.40% ± 7.60% ± 19.70% ± 12:00 0.14 0.08 0.09 0.08 0.19% 0.22% 0.19% 1.50% 1.34% 3.54% 46.93 ± 4.32 ± 7.69 ± 0.44 ± 9.20% ± 16.40% ± 0.90% ± 56.10% ± 5.70% ± 10.10% ± 12:30 0.14 0.08 0.09 0.08 0.18% 0.21% 0.16% 1.30% 1.03% 1.82% 26.51 ± 1.55 ± 7.98 ± 2.54 ± 5.80% ± 30.10% ± 9.60% ± 19.40% ± 31.90% ± 164.20% 30 13:00 0.12 0.08 0.10 0.08 0.30% 0.38% 0.31% 1.03% 1.10% ± 10.04% 43.57 ± 1.28 ± 9.58 ± 3.46 ± 2.90% ± 22.00% ± 8.00% ± 13.40% ± 36.20% ± 270.30% 13:30 0.14 0.08 0.10 0.08 0.18% 0.23% 0.20% 0.85% 0.95% ± 18.06% 25.16 ± 1.71 ± 15.08 ± 8.02 ± 6.80% ± 59.90% ± 31.90% ± 11.30% ± 53.10% ± 468.60% 14:00 0.12 0.08 0.11 0.09 0.32% 0.50% 0.39% 0.54% 0.71% ± 22.71% 51.28 ± 1.29 ± 6.86 ± 1.39 ± 2.50% ± 13.40% ± 2.70% ± 18.80% ± 20.30% ± 108.10% 14:30 0.15 0.08 0.09 0.08 0.16% 0.19% 0.16% 1.19% 1.20% ± 9.14% 11.81 ± 0.77 ± 20.81 ± 11.93 ± 6.50% ± 176.20% 101.00% 3.70% ± 57.30% ± 1546.80% 15:00 0.10 0.08 0.11 0.10 0.67% ± 1.79% ± 1.19% 0.38% 0.56% ± 158.8% 7.62 ± 0.42 ± 20.18 ± 12.80 ± 5.50% ± 265.00% 168.00% 2.10% ± 63.40% ± 3030.40% 15:30 0.10 0.08 0.11 0.10 1.02% ± 3.64% ± 2.47% 0.39% 0.60% ± 562.6% 28.10 ± 1.26 ± 10.07 ± 0.25 ± 4.50% ± 35.80% ± 0.90% ± 12.50% ± 2.50% ± 20.20% ± 16:00 0.12 0.08 0.10 0.08 0.29% 0.38% 0.28% 0.80% 0.77% 6.34% 33.27 4.81 4.29 0.43 14.40% ± 12.90% ± 1.30% ± 112.00% 10.00% ± 9.00% ± 10:00 ±0.09 ±0.06 ±0.06 ±0.06 0.19% 0.19% 0.17% ± 2.18% 1.30% 1.17% 44.00 4.64 5.31 0.25 10.50% ± 12.10% ± 0.60% ± 87.40% ± 4.70% ± 5.40% ± 11:00 ±0.10 ±0.06 ±0.06 ±0.06 0.14% 0.15% 0.13% 1.56% 1.03% 1.19% 60 44.70 3.29 6.80 0.44 7.40% ± 15.20% ± 1.00% ± 48.40% ± 6.50% ± 13.40% ± 12:00 ±0.10 ±0.06 ±0.07 ±0.06 0.13% 0.15% 0.13% 0.99% 0.82% 1.70% 35.04 1.41 8.78 3.00 4.00% ± 25.00% ± 8.60% ± 16.10% ± 34.20% ± 212.30% 13:00 ±0.09 ±0.06 ±0.07 ±0.06 0.16% 0.20% 0.17% 0.66% 0.72% ± 9.46%

Table 4-1. Continued Average Start Rhines Stadium Weimer Reitz 푆푡푎푑𝑖푢푚 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푆푡푎푑𝑖푢푚 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (cps) (cps) (cps) (cps) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푆푡푎푑𝑖푢푚 38.22 1.50 10.97 4.70 3.90% ± 28.70% ± 12.30% ± 13.70% ± 42.90% ± 313.60% 14:00 ±0.09 ±0.06 ±0.07 ±0.06 0.15% 0.20% 0.16% 0.53% 0.62% ± 12.53% 60 9.71 0.60 20.49 12.36 6.10% ± 211.00% 127.30% 2.90% ± 60.30% ± 2071.60% 15:00 ±0.07 ±0.06 ±0.08 ±0.07 0.57% ± 1.72% ± 1.16% 0.27% 0.41% ± 193.3%

Table 4-2. March 20th, 2019 measurement 41Ar count rates and count rate ratios Average Start Rhines Rhines Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (cps) 2 (cps) (cps) (cps) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 12.69 37.35 0.00 0.74 294.00% 0.00% ± 6.00% ± 0.00% ± 0.00% ± 2.00% ± 11:00 ±0.10 ±0.12 ±0.00 ±0.08 ± 2.54% 0.00% 0.65% 0.00% 0.00% 0.22% 12.01 34.03 5.35 0.98 283.00% 45.00% ± 8.00% ± 636.50% 18.30% ± 2.90% ± 11:30 ±0.10 ±0.13 ±0.09 ±0.08 ± 2.63% 0.84% 0.65% ± 10.79% 1.52% 0.24% 20.23 42.25 5.38 0.89 209.00% 27.00% ± 4.00% ± 786.10% 16.60% ± 2.10% ± 12:00 ±0.11 ±0.13 ±0.09 ±0.08 ± 1.26% 0.48% 0.36% ± 13.62% 1.51% 0.19% 10.51 26.36 12.20 6.98 251.00% 116.00% 66.00% ± 216.10% 57.20% ± 26.50% ± 12:30 ±0.11 ±0.13 ±0.09 ±0.09 ± 2.93% ± 1.50% 1.09% ± 1.96% 0.85% 0.36% 10.27 0.00 11.42 6.55 0.00% ± 111.00% 64.00% ± 0.00% ± 57.30% ± 0.00% ± 13:00 ±0.10 ±0.00 ±0.11 ±0.09 0.00% ± 1.47% 1.06% 0.00% 0.94% 0.00% 13.16 0.00 9.18 6.35 0.00% ± 70.00% ± 48.00% ± 0.00% ± 69.20% ± 0.00% ± 30 13:30 ±0.10 ±0.00 ±0.10 ±0.09 0.00% 0.92% 0.76% 0.00% 1.21% 0.00% 11.74 0.00 15.07 6.25 0.00% ± 128.00% 53.00% ± 0.00% ± 41.50% ± 0.00% ± 14:00 ±0.10 ±0.00 ±0.10 ±0.09 0.00% ± 1.39% 0.88% 0.00% 0.64% 0.00% 12.35 28.27 0.22 4.46 229.00% 2.00% ± 36.00% ± 12780.0% 2016.90% 15.80% ± 14:30 ±0.10 ±0.09 ±0.10 ±0.09 ± 2.02% 0.91% 0.75% ± 5789% ± 914.5% 0.31% 6.82 14.65 26.44 10.85 215.00% 387.00% 159.00% 55.40% ± 41.00% ± 74.00% ± 15:00 ±0.10 ±0.12 ±0.09 ±0.10 ± 3.62% ± 5.89% ± 2.74% 0.48% 0.38% 0.88% 14.28 22.90 28.49 6.92 160.00% 200.00% 48.00% ± 80.40% ± 24.30% ± 30.20% ± 15:30 ±0.10 ±0.11 ±0.12 ±0.09 ± 1.37% ± 1.67% 0.71% 0.51% 0.33% 0.41% 5.71 4.28 34.31 14.49 75.00% ± 601.00% 254.00% 12.50% ± 42.20% ± 338.40% 16:00 ±0.09 ±0.10 ±0.13 ±0.10 2.12% ± 10.23% ± 4.56% 0.29% 0.33% ± 8.08% 12.35 35.69 0.00 0.86 289.00% 0.00% ± 6.90% ± 0.00% ± 0.00% ± 2.40% ± 11:00 ±0.07 ±0.09 ±0.06 ±0.06 ± 1.83% 0.00% 0.45% 0.00% 0.00% 0.16% 60 15.37 34.31 8.79 3.94 223.30% 57.20% ± 25.60% ± 390.40% 44.80% ± 11.50% ± 12:00 ±0.08 ±0.09 ±0.07 ±0.06 ± 1.26% 0.51% 0.41% ± 3.07% 0.76% 0.18%

Table 4-2. Continued Average Start Rhines Rhines Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (cps) 2 (cps) (cps) (cps) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 11.72 0.00 10.30 6.45 0.00% ± 87.90% ± 55.10% ± 0.00% ± 62.60% ± 0.00% ± 13:00 ±0.07 ±0.00 ±0.07 ±0.06 0.00% 0.81% 0.63% 0.00% 0.75% 0.00% 12.05 0.00 7.65 5.36 0.00% ± 63.50% ± 44.50% ± 0.00% ± 70.00% ± 0.00% ± 60 14:00 ±0.07 ±0.00 ±0.07 ±0.06 0.00% 0.69% 0.58% 0.00% 1.03% 0.00% 10.55 18.78 27.46 8.88 178.00% 260.30% 84.20% ± 68.40% ± 32.30% ± 47.30% ± 15:00 ±0.07 ±0.08 ±0.07 ±0.07 ± 1.43% ± 1.91% 0.85% 0.34% 0.25% 0.40%

Table 4-3. March 22nd, 2019 measurement 41Ar count rates and count rate ratios Average Start Rhines Rhines Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (cps) 2 (cps) (cps) (cps) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 2.49 3.98 46.90 16.46 160.05% 1884.17% 661.18% 8.49% ± 35.09% ± 413.10% 10:30 ±0.09 ±0.09 ±0.14 ±0.10 ± 6.58% ± 66.15% ± 23.49% 0.19% 0.24% ± 9.29% 0.45 1.04 62.03 5.12 228.30% 13682.3% 1128.8% 1.67% ± 8.25% ± 494.46% 11:00 ±0.08 ±0.08 ±0.15 ±0.09 ± 45.98% ± 2523% ± 209.6% 0.13% 0.14% ± 40.35% 0.00 0.00 56.67 0.75 0.00% ± 0.00% ± 0.00% ± 0.00% ± 1.31% ± 0.00% ± 11:30 ±0.00 ±0.00 ±0.15 ±0.08 0.00% 0.00% 0.00% 0.00% 0.14% 0.00% 0.00 0.00 44.67 0.75 0.00% ± 0.00% ± 0.00% ± 0.00% ± 1.69% ± 0.00% ± 12:00 ±0.00 ±0.00 ±0.14 ±0.08 0.00% 0.00% 0.00% 0.00% 0.18% 0.00% 0.00 0.00 39.41 0.00 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 12:30 ±0.00 ±0.00 ±0.13 ±0.08 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00 0.00 41.16 0.00 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 13:00 ±0.00 ±0.00 ±0.13 ±0.00 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 30 0.00 0.13 44.67 0.77 0.00% ± 0.00% ± 0.00% ± 0.29% ± 1.73% ± 592.63% 13:30 ±0.00 ±0.03 ±0.14 ±0.08 0.00% 0.00% 0.00% 0.01% 0.18% ± 125.2% 0.00 0.00 26.16 0.00 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 14:00 ±0.00 ±0.00 ±0.12 ±0.00 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00 0.00 45.01 0.21 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.46% ± 0.00% ± 14:30 ±0.00 ±0.00 ±0.14 ±0.08 0.00% 0.00% 0.00% 0.00% 0.17% 0.00% 0.00 0.00 32.34 0.02 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.08% ± 0.00% ± 15:00 ±0.00 ±0.00 ±0.12 ±0.08 0.00% 0.00% 0.00% 0.00% 0.26% 0.00% 0.00 0.00 34.93 0.43 0.00% ± 0.00% ± 0.00% ± 0.00% ± 1.23% ± 0.00% ± 15:30 ±0.00 ±0.00 ±0.13 ±0.08 0.00% 0.00% 0.00% 0.00% 0.22% 0.00% 0.00 0.00 34.81 0.62 0.00% ± 0.00% ± 0.00% ± 0.00% ± 1.77% ± 0.00% ± 16:00 ±0.00 ±0.00 ±0.13 ±0.08 0.00% 0.00% 0.00% 0.00% 0.23% 0.00%

Table 4-3. Continued Average Start Rhines Rhines Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (cps) 2 (cps) (cps) (cps) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 0.23 ± 0.52 ± 59.35 ± 2.93 ± 228.30% 26183.6% 1293.10% 0.90% ± 4.90% ± 566.40% 11:00 0.06 0.07 0.11 0.06 ± 67.27% ± 6801% ± 336.8% 0.13% 0.10% ± 79.61% 0.00 ± 0.00 ± 42.04 ± 0.38 ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.90% ± 0.00% ± 12:00 0.00 0.00 0.10 0.06 0.00% 0.00% 0.00% 0.00% 0.13% 0.00% 0.00 ± 0.07 ± 42.92 ± 0.39 ± 0.00% ± 0.00% ± 0.00% ± 0.20% ± 0.90% ± 592.60% 60 13:00 0.00 0.01 0.10 0.06 0.00% 0.00% 0.00% 0.08% 0.13% ± 251.2% 0.00 ± 0.00 ± 35.58 ± 0.10 ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.30% ± 0.00% ± 14:00 0.00 0.00 0.09 0.06 0.00% 0.00% 0.00% 0.00% 0.16% 0.00% 0.00 ± 0.00 ± 33.63 ± 0.23 ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.70% ± 0.00% ± 15:00 0.00 0.00 0.09 0.06 0.00% 0.00% 0.00% 0.00% 0.17% 0.00%

Simulation Results for May 2018 and March 2019 Trials

After obtaining the high velocity plume stack data, the in-house MATLAB

Gaussian model, AERMOD, and FLEXPART codes were utilized to simulate the dispersion of the 41Ar plume emitted by the UFTR on the May 2018 and March 2019 measurement days. To run both Gaussian models, specific information regarding the high velocity stack was required. This included inputting the stack diameter (1.022 m), the physical stack height (58 m above sea level), and the stack height velocity (29.2 m s-1). For the in-house model simulations of the May 8th plume, the resolution of the plume grid was 50 cm and the 41Ar concentration was calculated to a maximum distance of 150 m in the x, y, and z directions. As previously discussed, the meteorological conditions used to run simulations on the in-house Gaussian model were taken from the UFTR, UF, and the GNV regional airport weather stations. During the

May 8th, 2018 measurements, the UFTR weather station’s anemometer malfunctioned, thus no wind information was measured. The hourly wind information measured by the

UF and GNV weather stations is displayed in Table 4-4. For the AERMOD code, the meteorological dataset was taken from the GNV and JAX airport databases and processed through AERMET. For the FLEXPART simulations, the WRF/WPS coupled model extracted data from the NCEP GFS to provide the meteorological inputs needed to run the model. The radiation transport simulation of the photons emitted by the 41Ar plume using the in-house Gaussian model and AERMOD at 12:00 is displayed by using the FMESH tally function of MCNP at elevations of 40 m and 80 m (see Figure 4-5).

(a) (b)

(c) (d) Figure 4-5. FMESH Tally simulation of the 41Ar emitted photons at 12:00 on May 8th, 2018 (a) In-house model at 40 m elevation (b) In-house model at 80 m elevation (c) AERMOD model at 40 m elevation (d) AERMOD model at 80 m elevation

For the simulation inputs on March 20th and 22nd, the meteorological dataset was changed and the detector locations were switched in the MCNP input (from the Ben Hill

Griffin Stadium to the lower Rhines Hall rooftop). The wind information for these two days is displayed in Table 4-5. Additionally, the plume resolution for the in-house model was changed to 75 cm with maximum distances of 225 m in the x, y, and z directions.

This was done to simulate a longer plume which would better reach all detector stations.

The effects of changing the resolution and plume distance on the output is discussed

85 further in Chapter 6. Additionally, the AERMOD and airport data in-house codes were not simulated due to server and system problems at the National Centers for

Environmental Information which analyzes the 1-min ASOS data observed at the GNV airport.

After running each model with the appropriate meteorological inputs, the results were coupled with MCNP and simulated. To compare the measurement count rate ratios with the simulation outputs, tally ratios were calculated using Equation 4-5:

퐷푒푡푒푐푡표푟 푆푡푎푡𝑖표푛 퐹8 푇푎푙푙푦 #1 푇푎푙푙푦 푅푎푡𝑖표 = . 퐷푒푡푒푐푡표푟 푆푡푎푡𝑖표푛 퐹8 푇푎푙푙푦 #2 (4-5)

The relative error on each detector station tally was taken directly from the MCNP output file and the error for the tally ratio was calculated using Equation 4-6:

2 2 휎푇푎푙푙푦 #1 휎푇푎푙푙푦 #2 휎 = 푇푎푙푙푦 푅푎푡𝑖표 ∗ √( ) + ( ) . 푇푎푙푙푦 푅푎푡𝑖표 푇푎푙푙푦 #1 푇푎푙푙푦 #2 (4-6)

The tallies and tally ratio outputs from the ATM-MCNP coupled models are shown in

Tables 4-6 to 4-9 for the May 8th plume, Tables 4-10 to 4-12 for the March 20th plume, and Tables 4-13 to 4-15 for the March 22nd plume. Furthermore, Tables A-4 to A-8 display the results of the 10 minute averaged UFTR and UF simulations for the three days of measurement.

Table 4-4. May 8th, 2018 wind information (averaged hourly) UF Weather Station GNV Airport Wind Wind Wind Wind Start Start Speed Orientation Speed Orientation Time Time (m s-1) (°) (m s-1) (°) 10:00 3.06 117.43 10:00 3.85 79.0 11:00 2.56 131.25 11:00 3.79 93.0 12:00 2.47 142.68 12:00 3.59 63.0 13:00 2.57 125.92 13:00 3.03 33.0 14:00 2.53 146.25 14:00 2.83 4.0 15:00 2.63 193.47 15:00 4.25 57.0

Table 4-5. March 20th and 22nd, 2019 wind information (averaged hourly) March 20th March 22nd Weather Start Wind Speed Wind Wind Speed Wind Station Time (m s-1) Orientation (°) (m s-1) Orientation (°) 11:00 3.490 46.55 1.448 268.7 12:00 2.654 35.25 2.056 256.6 UFTR 13:00 2.390 35.38 - - 14:00 2.413 26.21 - - 15:00 1.717 6.581 - - 11:00 4.754 1.4 2.441 345.5 12:00 3.558 356.1 3.308 309.3 UF 13:00 2.730 348.7 - - 14:00 3.409 356.7 - - 15:00 2.445 345.0 - -

Table 4-6. Airport weather in-house Gaussian model May 8th, 2018 simulations Average Start Rhines Stadium Weimer Reitz 푆푡푎푑𝑖푢푚 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푆푡푎푑𝑖푢푚 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (F8 Tally) (F8 Tally) (F8 Tally) (F8 Tally) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푆푡푎푑𝑖푢푚 4.38E-07 ± 4.13E-08 ± 3.78E-08 ± 1.03E-08 ± 9.43% ± 8.63% ± 2.35% ± 109.26% 27.25% 24.94% 10:00 1.81E-09 1.47E-10 1.65E-09 8.52E-11 0.38% 0.05% 0.02% ± 4.01% ± 0.22% ± 1.21% 8.13E-07 ± 2.46E-08 ± 3.74E-08 ± 1.35E-08 ± 3.03% ± 4.60% ± 1.66% ± 65.78% 36.10% 54.88% 11:00 2.56E-09 2.56E-10 1.75E-09 9.02E-11 0.22% 0.03% 0.01% ± 7.30% ± 0.68% ± 1.71% 6.37E-07 ± 3.53E-08 ± 3.58E-08 ± 1.10E-08 ± 5.54% ± 5.62% ± 1.73% ± 98.60% 30.73% 31.16% 12:00 2.47E-08 2.38E-10 1.51E-09 7.35E-11 0.32% 0.22% 0.07% ± 4.34% ± 0.30% ± 1.31% 60 3.57E-07 ± 1.79E-08 ± 4.64E-08 ± 1.83E-08 ± 5.01% ± 13.00% 5.13% ± 38.6% ± 39.44% 102.23% 13:00 1.70E-09 1.15E-10 1.98E-09 1.36E-10 0.56% ± 0.04% 0.05% 11.17% ± 1.00% ± 1.71% 9.90E-08 ± 1.16E-08 ± 7.91E-08 ± 4.60E-08 ± 11.72% 79.90% 46.46% 14.66% 58.15% 396.55% 14:00 4.90E-10 6.03E-11 3.13E-09 3.80E-10 ± 3.18% ± 0.08% ± 0.45% ± 27.2% ± 3.87% ± 2.35% 4.49E-08 ± 8.96E-09 ± 1.55E-07 ± 2.22E-07 ± 19.96% 345.21% 494.43% 5.78% ± 143.23% 2477.7% 15:00 1.45E-10 7.40E-11 7.41E-09 1.81E-09 ± 16.5% ± 0.18% ± 4.34% 83.93% ± 28.8% ± 6.95%

Table 4-7. UF weather in-house Gaussian model May 8th, 2018 simulations Average Start Rhines Stadium Weimer Reitz 푆푡푎푑𝑖푢푚 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푆푡푎푑𝑖푢푚 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (F8 Tally) (F8 Tally) (F8 Tally) (F8 Tally) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푆푡푎푑𝑖푢푚 2.99E-07 ± 5.21E-08 ± 2.60E-08 ± 8.80E-09 ± 17.50% 8.70% ± 2.90% ± 200.20% 33.80% 16.90% 10:00 5.98E-10 8.34E-11 4.68E-11 1.85E-11 ± 0.04% 0.02% 0.01% ± 0.48% ± 0.09% ± 0.04% 4.77E-07 ± 7.35E-08 ± 2.50E-08 ± 9.53E-09 ± 15.40% 5.20% ± 2.00% ± 294.30% 38.20% 13.00% 10:30 1.24E-09 1.10E-10 5.25E-11 1.72E-11 ± 0.05% 0.02% 0.01% ± 0.76% ± 0.11% ± 0.03% 5.05E-07 ± 7.68E-08 ± 2.48E-08 ± 9.64E-09 ± 15.20% 4.90% ± 1.90% ± 309.60% 38.90% 12.60% 11:00 1.36E-09 1.23E-10 4.46E-11 1.74E-11 ± 0.05% 0.02% 0.01% ± 0.75% ± 0.10% ± 0.03% 8.75E-08 ± 2.72E-08 ± 4.21E-08 ± 7.61E-09 ± 31.10% 48.10% 8.70% ± 64.50% 18.10% 28.00% 11:30 1.23E-10 4.08E-11 6.74E-11 1.45E-11 ± 0.06% ± 0.10% 0.02% ± 0.14% ± 0.04% ± 0.07% 1.20E-07 ± 3.19E-08 ± 3.52E-08 ± 7.82E-09 ± 26.60% 29.30% 6.50% ± 90.80% 22.20% 24.50% 12:00 1.80E-10 7.02E-11 5.63E-11 1.64E-11 ± 0.07% ± 0.06% 0.02% ± 0.25% ± 0.06% ± 0.07% 1.10E-07 ± 3.18E-08 ± 3.83E-08 ± 7.83E-09 ± 28.80% 34.70% 7.10% ± 83.00% 20.40% 24.60% 12:30 1.87E-10 5.72E-11 6.13E-11 1.49E-11 ± 0.07% ± 0.08% 0.02% ± 0.20% ± 0.05% ± 0.06% 2.79E-07 ± 5.56E-08 ± 2.96E-08 ± 8.90E-09 ± 19.90% 10.60% 3.20% ± 187.90% 30.10% 16.00% 30 13:00 5.02E-10 8.34E-11 5.03E-11 1.69E-11 ± 0.05% ± 0.03% 0.01% ± 0.43% ± 0.08% ± 0.04% 1.75E-07 ± 4.05E-08 ± 3.28E-08 ± 8.23E-09 ± 23.20% 18.80% 4.70% ± 123.40% 25.10% 20.30% 13:30 2.80E-10 6.08E-11 5.25E-11 1.65E-11 ± 0.05% ± 0.04% 0.01% ± 0.27% ± 0.06% ± 0.05% 7.36E-08 ± 2.44E-08 ± 4.63E-08 ± 7.55E-09 ± 33.10% 62.90% 10.30% 52.60% 16.30% 31.00% 14:00 1.03E-10 4.15E-11 7.41E-11 1.43E-11 ± 0.07% ± 0.13% ± 0.02% ± 0.12% ± 0.04% ± 0.08% 1.59E-07 ± 3.79E-08 ± 3.33E-08 ± 8.12E-09 ± 23.90% 21.00% 5.10% ± 114.00% 24.40% 21.40% 14:30 2.54E-10 5.69E-11 5.33E-11 1.54E-11 ± 0.05% ± 0.05% 0.01% ± 0.25% ± 0.06% ± 0.05% 3.72E-08 ± 1.64E-08 ± 6.57E-08 ± 7.30E-09 ± 44.00% 176.50% 19.60% 25.00% 11.10% 44.60% 15:00 5.21E-11 2.62E-11 9.86E-11 1.39E-11 ± 0.09% ± 0.36% ± 0.05% ± 0.05% ± 0.03% ± 0.11% 1.98E-08 ± 1.18E-08 ± 1.21E-07 ± 8.17E-09 ± 59.70% 607.90% 41.20% 9.80% ± 6.80% ± 69.00% 15:30 2.57E-11 2.01E-11 1.94E-10 1.55E-11 ± 0.13% ± 1.26% ± 0.09% 0.02% 0.02% ± 0.18% 3.56E-07 ± 5.85E-08 ± 2.57E-08 ± 9.00E-09 ± 16.40% 7.20% ± 2.50% ± 227.80% 35.10% 15.40% 16:00 7.48E-10 9.36E-11 1.21E-10 1.80E-11 ± 0.04% 0.04% 0.01% ± 1.13% ± 0.18% ± 0.04% 3.85E-07 ± 6.16E-08 ± 2.53E-08 ± 9.14E-09 ± 16.00% 6.60% ± 2.40% ± 243.20% 36.10% 14.80% 10:00 8.86E-10 9.86E-11 5.06E-11 3.56E-11 ± 0.04% 0.02% 0.01% ± 0.62% ± 0.16% ± 0.06% 2.05E-07 ± 4.47E-08 ± 3.28E-08 ± 8.54E-09 ± 21.80% 16.00% 4.20% ± 136.40% 26.10% 19.10% 11:00 3.69E-10 6.71E-11 5.58E-11 1.54E-11 ± 0.05% ± 0.04% 0.01% ± 0.31% ± 0.06% ± 0.04% 1.27E-07 ± 3.35E-08 ± 3.78E-08 ± 8.01E-09 ± 26.40% 29.80% 6.30% ± 88.60% 21.20% 23.90% 60 12:00 2.03E-10 5.03E-11 6.05E-11 1.52E-11 ± 0.06% ± 0.07% 0.02% ± 0.19% ± 0.05% ± 0.06% 2.21E-07 ± 4.73E-08 ± 3.08E-08 ± 8.52E-09 ± 21.40% 13.90% 3.80% ± 153.30% 27.60% 18.00% 13:00 5.30E-10 8.51E-11 5.24E-11 1.62E-11 ± 0.06% ± 0.04% 0.01% ± 0.38% ± 0.07% ± 0.05% 9.86E-08 ± 2.88E-08 ± 3.94E-08 ± 7.64E-09 ± 29.20% 39.90% 7.70% ± 73.20% 19.40% 26.50% 14:00 1.38E-10 4.90E-11 5.91E-11 1.45E-11 ± 0.06% ± 0.08% 0.02% ± 0.17% ± 0.05% ± 0.07%

Table 4-7. Continued Average Start Rhines Stadium Weimer Reitz 푆푡푎푑𝑖푢푚 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푆푡푎푑𝑖푢푚 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (F8 Tally) (F8 Tally) (F8 Tally) (F8 Tally) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푆푡푎푑𝑖푢푚 2.65E-08 ± 1.37E-08 ± 8.74E-08 ± 7.60E-09 ± 51.70% 329.50% 28.70% 15.70% 8.70% ± 55.40% 60 15:00 3.45E-11 3.29E-11 1.40E-10 1.44E-11 ± 0.14% ± 0.68% ± 0.07% ± 0.05% 0.02% ± 0.17%

Table 4-8. FLEXPART May 8th, 2018 simulations Average Start Rhines Stadium Weimer Reitz 푆푡푎푑𝑖푢푚 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푆푡푎푑𝑖푢푚 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (F8 Tally) (F8 Tally) (F8 Tally) (F8 Tally) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푆푡푎푑𝑖푢푚 1.49E-07 ± 1.32E-07 ± 8.21E-08 ± 1.54E-08 ± 88.30% 54.90% 10.30% 160.90% 18.70% 11.60% 10:00 6.85E-10 6.01E-09 2.87E-10 1.20E-10 ± 4.05% ± 0.32% ± 0.09% ± 7.34% ± 0.16% ± 0.54% 1.30E-07 ± 8.20E-08 ± 7.48E-08 ± 1.86E-08 ± 63.30% 57.70% 14.30% 109.60% 24.80% 22.60% 11:00 4.55E-10 4.00E-09 7.63E-10 1.17E-10 ± 3.09% ± 0.62% ± 0.10% ± 5.47% ± 0.30% ± 1.12% 2.60E-07 ± 7.73E-08 ± 8.27E-08 ± 2.32E-08 ± 29.70% 31.80% 8.90% ± 93.40% 28.00% 30.00% 12:00 1.12E-08 3.40E-09 5.46E-10 1.46E-10 ± 1.83% ± 1.39% 0.39% ± 4.16% ± 0.26% ± 1.33% 60 6.71E-08 ± 6.60E-08 ± 8.51E-08 ± 2.22E-08 ± 98.40% 126.90% 33.00% 77.50% 26.00% 33.60% 13:00 3.56E-10 2.93E-09 5.36E-10 1.55E-10 ± 4.40% ± 1.04% ± 0.29% ± 3.48% ± 0.25% ± 1.51% 5.31E-08 ± 8.00E-08 ± 7.73E-08 ± 1.87E-08 ± 150.70% 145.70% 35.20% 103.50% 24.20% 23.40% 14:00 2.92E-10 3.30E-09 3.94E-10 1.46E-10 ± 6.26% ± 1.09% ± 0.34% ± 4.30% ± 0.23% ± 0.98% 6.76E-08 ± 8.30E-08 ± 3.90E-08 ± 1.81E-08 ± 122.80% 57.70% 26.80% 212.80% 46.40% 21.80% 15:00 2.43E-10 4.13E-09 3.16E-10 1.39E-10 ± 6.13% ± 0.51% ± 0.23% ± 10.7% ± 0.52% ± 1.10%

Table 4-9. AERMOD May 8th, 2018 simulations Average Start Rhines Stadium Weimer Reitz 푆푡푎푑𝑖푢푚 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푆푡푎푑𝑖푢푚 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (F8 Tally) (F8 Tally) (F8 Tally) (F8 Tally) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푆푡푎푑𝑖푢푚 6.97E-07 ± 6.63E-08 ± 7.42E-08 ± 1.23E-08 ± 9.51% ± 10.64% 1.76% ± 89.37% 16.58% 18.55% 10:00 2.89E-09 2.11E-10 2.90E-09 9.79E-11 0.42% ± 0.05% 0.02% ± 4.39% ± 0.16% ± 0.66% 1.59E-06 ± 3.82E-08 ± 7.73E-08 ± 1.63E-08 ± 2.40% ± 4.87% ± 1.03% ± 49.37% 21.09% 42.71% 11:00 5.01E-09 3.55E-10 3.24E-09 1.05E-10 0.20% 0.02% 0.01% ± 8.70% ± 0.48% ± 0.90% 9.05E-07 ± 5.87E-08 ± 1.18E-07 ± 1.44E-08 ± 6.49% ± 13.05% 1.59% ± 49.75% 12.20% 24.53% 60 12:00 3.51E-08 3.53E-10 4.47E-09 9.25E-11 0.71% ± 0.25% 0.06% ± 7.70% ± 0.22% ± 0.47% 9.73E-07 ± 2.63E-08 ± 8.88E-08 ± 2.17E-08 ± 2.70% ± 9.12% ± 2.23% ± 29.65% 24.44% 82.41% 13:00 4.64E-09 1.51E-10 3.39E-09 1.55E-10 0.35% 0.02% 0.02% ± 13.0% ± 0.76% ± 0.95% 3.05E-07 ± 2.13E-08 ± 1.45E-07 ± 3.49E-08 ± 6.99% ± 47.57% 11.45% 14.70% 24.07% 163.73% 14:00 1.51E-09 9.89E-11 5.14E-09 2.78E-10 1.70% ± 0.05% ± 0.11% ± 24.3% ± 1.51% ± 0.87%

Table 4-9. Continued Average Start Rhines Stadium Weimer Reitz 푆푡푎푑𝑖푢푚 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푆푡푎푑𝑖푢푚 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (F8 Tally) (F8 Tally) (F8 Tally) (F8 Tally) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푆푡푎푑𝑖푢푚 1.28E-07 ± 2.23E-08 ± 2.82E-07 ± 5.41E-08 ± 17.42% 220.31% 42.27% 7.91% ± 19.18% 242.60% 60 15:00 4.15E-10 1.64E-10 1.21E-08 4.25E-10 ± 9.46% ± 0.14% ± 0.36% 54.96% ± 2.61% ± 0.84%

Table 4-10. UFTR weather in-house Gaussian model March 20th, 2019 simulations Average Start Rhines Rhines 2 Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (F8 Tally) (F8 Tally) (F8 Tally) (F8 Tally) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 2.92E-07 ± 6.89E-07 ± 4.36E-08 ± 2.22E-08 ± 235.90% 14.90% 7.60% ± 1581.1% 51.00% 3.20% ± 11:00 5.26E-10 1.86E-09 6.10E-11 3.11E-11 ± 0.77% ± 0.03% 0.02% ± 4.81% ± 0.10% 0.01% 2.41E-07 ± 5.31E-07 ± 4.81E-08 ± 2.57E-08 ± 220.20% 20.00% 10.70% 1103.4% 53.40% 4.80% ± 11:30 4.34E-10 1.01E-09 7.22E-11 3.08E-11 ± 0.58% ± 0.05% ± 0.02% ± 2.67% ± 0.10% 0.01% 2.14E-07 ± 4.71E-07 ± 5.31E-08 ± 2.87E-08 ± 220.40% 24.90% 13.40% 886.60% 54.00% 6.10% ± 12:00 3.85E-10 1.13E-09 6.90E-11 3.44E-11 ± 0.66% ± 0.06% ± 0.03% ± 2.42% ± 0.10% 0.02% 6.28E-08 ± 5.52E-08 ± 1.06E-07 ± 2.23E-07 ± 87.80% 168.40% 355.00% 52.20% 210.70% 404.10% 12:30 1.38E-10 5.52E-11 1.91E-10 4.91E-10 ± 0.21% ± 0.48% ± 1.10% ± 0.11% ± 0.60% ± 0.98% 1.53E-07 ± 2.18E-07 ± 5.86E-08 ± 3.79E-08 ± 142.80% 38.40% 24.80% 372.20% 64.60% 17.40% 13:00 2.75E-10 3.05E-10 8.20E-11 4.55E-11 ± 0.32% ± 0.09% ± 0.05% ± 0.74% ± 0.12% ± 0.03% 1.64E-07 ± 2.67E-07 ± 6.09E-08 ± 3.78E-08 ± 162.30% 37.00% 23.00% 438.10% 62.10% 14.20% 30 13:30 3.12E-10 4.27E-10 7.92E-11 4.91E-11 ± 0.40% ± 0.09% ± 0.05% ± 0.90% ± 0.11% ± 0.03% 9.02E-08 ± 9.91E-08 ± 9.18E-08 ± 1.16E-07 ± 109.80% 101.70% 128.40% 108.00% 126.20% 116.90% 14:00 1.71E-10 1.19E-10 1.19E-10 1.97E-10 ± 0.25% ± 0.23% ± 0.33% ± 0.19% ± 0.27% ± 0.24% 1.02E-07 ± 1.22E-07 ± 7.87E-08 ± 7.96E-08 ± 119.70% 77.00% 77.80% 155.50% 101.10% 65.00% 14:30 1.94E-10 1.59E-10 1.02E-10 1.11E-10 ± 0.28% ± 0.18% ± 0.18% ± 0.28% ± 0.19% ± 0.12% 6.64E-08 ± 6.17E-08 ± 9.16E-08 ± 1.67E-07 ± 92.80% 137.90% 251.20% 67.30% 182.20% 270.60% 15:00 1.26E-10 6.79E-11 1.56E-10 3.01E-10 ± 0.20% ± 0.35% ± 0.66% ± 0.14% ± 0.45% ± 0.57% 3.62E-08 ± 2.58E-08 ± 1.06E-07 ± 1.70E-07 ± 71.30% 294.40% 471.50% 24.20% 160.20% 661.60% 15:30 9.05E-11 7.22E-11 1.48E-10 3.40E-10 ± 0.27% ± 0.84% ± 1.50% ± 0.08% ± 0.39% ± 2.27% 5.59E-08 ± 4.88E-08 ± 8.41E-08 ± 1.67E-07 ± 87.30% 150.60% 299.50% 57.90% 198.80% 343.20% 16:00 1.12E-10 5.37E-11 1.18E-10 2.84E-10 ± 0.20% ± 0.37% ± 0.78% ± 0.10% ± 0.44% ± 0.69% 2.64E-07 ± 6.15E-07 ± 4.60E-08 ± 2.39E-08 ± 232.70% 17.40% 9.00% ± 1337.7% 51.90% 3.90% ± 11:00 4.75E-10 1.41E-09 5.98E-11 3.59E-11 ± 0.68% ± 0.04% 0.02% ± 3.53% ± 0.10% 0.01% 1.36E-07 ± 2.18E-07 ± 5.64E-08 ± 4.06E-08 ± 160.20% 41.50% 29.90% 385.80% 72.00% 18.70% 60 12:00 2.45E-10 2.62E-10 7.90E-11 4.87E-11 ± 0.35% ± 0.09% ± 0.06% ± 0.71% ± 0.13% ± 0.03% 1.60E-07 ± 2.44E-07 ± 6.02E-08 ± 3.80E-08 ± 152.70% 37.70% 23.70% 405.50% 63.00% 15.50% 13:00 3.84E-10 3.66E-10 7.83E-11 4.56E-11 ± 0.43% ± 0.10% ± 0.06% ± 0.80% ± 0.11% ± 0.03%

Table 4-10. Continued Average Start Rhines Stadium Weimer Reitz 푆푡푎푑𝑖푢푚 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푆푡푎푑𝑖푢푚 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (F8 Tally) (F8 Tally) (F8 Tally) (F8 Tally) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푆푡푎푑𝑖푢푚 9.64E-08 ± 1.11E-07 ± 8.51E-08 ± 9.51E-08 ± 115.00% 88.30% 98.70% 130.20% 111.70% 85.80% 14:00 1.83E-10 1.33E-10 1.19E-10 1.43E-10 ± 0.26% ± 0.21% ± 0.24% ± 0.24% ± 0.23% ± 0.16% 60 4.89E-08 ± 3.89E-08 ± 1.03E-07 ± 2.33E-07 ± 79.50% 209.60% 476.20% 37.90% 227.30% 599.00% 15:00 1.76E-10 4.28E-11 1.44E-10 5.36E-10 ± 0.30% ± 0.81% ± 2.04% ± 0.07% ± 0.61% ± 1.53%

Table 4-11. UF weather in-house Gaussian model March 20th, 2019 simulations Average Start Rhines Rhines 2 Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (F8 Tally) (F8 Tally) (F8 Tally) (F8 Tally) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 6.66E-08 ± 5.94E-08 ± 1.07E-07 ± 2.28E-07 ± 89.20% 160.70% 342.90% 55.50% 213.40% 384.40% 11:00 1.67E-10 5.94E-11 1.39E-10 3.65E-10 ± 0.24% ± 0.45% ± 1.02% ± 0.09% ± 0.44% ± 0.72% 5.52E-08 ± 4.24E-08 ± 1.55E-07 ± 7.83E-07 ± 76.70% 280.70% 1418.0% 27.30% 505.10% 1847.8% 11:30 1.16E-10 4.24E-11 2.02E-10 1.07E-08 ± 0.18% ± 0.69% ± 19.7% ± 0.04% ± 6.95% ± 25.4% 7.02E-08 ± 6.30E-08 ± 1.18E-07 ± 2.43E-07 ± 89.70% 167.90% 345.50% 53.40% 205.80% 385.00% 12:00 1.47E-10 6.93E-11 1.53E-10 5.83E-10 ± 0.21% ± 0.42% ± 1.10% ± 0.09% ± 0.56% ± 1.02% 4.06E-08 ± 2.72E-08 ± 2.42E-07 ± 4.42E-07 ± 67.00% 596.70% 1087.3% 11.20% 182.20% 1623.0% 12:30 9.34E-11 3.81E-11 3.63E-10 1.11E-09 ± 0.18% ± 1.64% ± 3.70% ± 0.02% ± 0.53% ± 4.66% 4.00E-08 ± 2.67E-08 ± 2.47E-07 ± 4.02E-07 ± 66.70% 617.00% 1004.4% 10.80% 162.80% 1506.8% 13:00 9.20E-11 6.14E-11 3.71E-10 9.25E-10 ± 0.22% ± 1.70% ± 3.27% ± 0.03% ± 0.45% ± 4.90% 5.00E-08 ± 3.75E-08 ± 1.59E-07 ± 4.96E-07 ± 75.00% 317.90% 992.20% 23.60% 312.10% 1323.0% 30 13:30 1.05E-10 1.46E-10 4.93E-10 2.68E-09 ± 0.33% ± 1.19% ± 5.75% ± 0.12% ± 1.94% ± 8.81% 3.77E-08 ± 2.45E-08 ± 3.24E-07 ± 3.09E-07 ± 65.00% 859.9% 818.40% 7.60% ± 95.20% 1258.9% 14:00 9.05E-11 2.70E-11 1.35E-08 5.56E-10 ± 0.17% ± 35.8% ± 2.46% 0.31% ± 3.97% ± 2.66% 8.07E-08 ± 8.05E-08 ± 1.04E-07 ± 1.56E-07 ± 99.80% 129.00% 193.20% 77.30% 149.70% 193.50% 14:30 1.61E-10 8.86E-11 2.60E-10 2.50E-10 ± 0.23% ± 0.41% ± 0.50% ± 0.21% ± 0.45% ± 0.38% 4.00E-08 ± 2.68E-08 ± 2.16E-07 ± 3.33E-07 ± 67.10% 540.60% 832.20% 12.40% 153.90% 1240.0% 15:00 9.20E-11 2.95E-11 3.24E-10 6.66E-10 ± 0.17% ± 1.48% ± 2.54% ± 0.02% ± 0.39% ± 2.84% 4.34E-08 ± 3.04E-08 ± 1.87E-07 ± 4.65E-07 ± 70.00% 431.80% 1072.1% 16.20% 248.30% 1531.2% 15:30 1.17E-10 3.04E-11 2.81E-10 3.81E-09 ± 0.20% ± 1.33% ± 9.25% ± 0.03% ± 2.07% ± 12.6% 3.81E-08 ± 2.54E-08 ± 2.02E-07 ± 2.46E-07 ± 66.70% 531.30% 645.30% 12.60% 121.50% 967.00% 16:00 8.76E-11 2.79E-11 2.83E-10 3.94E-10 ± 0.17% ± 1.43% ± 1.81% ± 0.02% ± 0.26% ± 1.88% 6.02E-08 ± 4.96E-08 ± 1.27E-07 ± 4.13E-07 ± 82.40% 211.60% 685.20% 38.90% 323.80% 831.60% 11:00 1.26E-10 4.96E-11 1.65E-10 1.61E-09 ± 0.19% ± 0.52% ± 3.04% ± 0.06% ± 1.34% ± 3.35% 60 5.36E-08 ± 3.99E-08 ± 2.08E-07 ± 7.11E-07 ± 74.50% 388.4% 1327.3% 19.20% 341.7% 1781.0% 12:00 1.18E-10 4.39E-11 8.94E-09 6.75E-09 ± 0.18% ± 16.7% ± 12.9% ± 0.83% ± 15.1% ± 17.0%

Table 4-11. Continued Average Start Rhines Stadium Weimer Reitz 푆푡푎푑𝑖푢푚 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푆푡푎푑𝑖푢푚 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (F8 Tally) (F8 Tally) (F8 Tally) (F8 Tally) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푆푡푎푑𝑖푢푚 4.51E-08 ± 3.17E-08 ± 1.99E-07 ± 5.99E-07 ± 70.30% 441.00% 1328.6% 15.90% 301.30% 1889.4% 13:00 9.92E-11 4.12E-11 2.79E-10 6.11E-09 ± 0.18% ± 1.15% ± 13.9% ± 0.03% ± 3.10% ± 19.4% 60 5.44E-08 ± 4.09E-08 ± 1.74E-07 ± 6.82E-07 ± 75.20% 318.70% 1252.5% 23.60% 393.00% 1665.9% 14:00 1.14E-10 4.09E-11 2.26E-10 9.00E-09 ± 0.17% ± 0.79% ± 16.8% ± 0.04% ± 5.20% ± 22.1% 4.15E-08 ± 2.84E-08 ± 2.01E-07 ± 3.93E-07 ± 68.50% 485.50% 946.50% 14.10% 194.90% 1381.6% 15:00 9.13E-11 2.84E-11 3.02E-10 1.18E-09 ± 0.17% ± 1.29% ± 3.52% ± 0.03% ± 0.66% ± 4.38%

Table 4-12. FLEXPART March 20th, 2019 simulations Average Start Rhines Rhines 2 Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (F8 Tally) (F8 Tally) (F8 Tally) (F8 Tally) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 1.33E-07 ± 1.97E-07 ± 7.53E-08 ± 6.74E-08 ± 148.20% 56.50% 50.60% 262.40% 89.60% 34.10% 11:00 6.05E-09 4.73E-10 2.94E-10 4.79E-10 ± 6.75% ± 2.59% ± 2.33% ± 1.20% ± 0.73% ± 0.26% 5.33E-08 ± 1.17E-07 ± 6.53E-08 ± 6.78E-08 ± 219.70% 122.70% 127.40% 179.10% 103.80% 58.00% 12:00 1.87E-10 2.11E-10 2.87E-10 4.81E-10 ± 0.86% ± 0.69% ± 1.01% ± 0.85% ± 0.87% ± 0.42% 60 6.45E-08 ± 1.42E-07 ± 5.98E-08 ± 6.95E-08 ± 219.7% 92.80% 107.80% 236.70% 116.10% 49.10% 13:00 3.01E-09 3.41E-10 2.33E-10 3.75E-10 ± 10.3% ± 4.34% ± 5.05% ± 1.09% ± 0.77% ± 0.29% 1.29E-07 ± 1.82E-07 ± 6.19E-08 ± 6.24E-08 ± 140.80% 48.00% 48.40% 293.50% 100.90% 34.40% 14:00 6.22E-09 4.73E-10 2.91E-10 3.99E-10 ± 6.81% ± 2.32% ± 2.35% ± 1.58% ± 0.80% ± 0.24% 1.32E-07 ± 2.25E-07 ± 4.97E-08 ± 5.00E-08 ± 171.00% 37.70% 38.00% 453.60% 100.70% 22.20% 15:00 5.86E-09 5.85E-10 1.89E-10 3.35E-10 ± 7.58% ± 1.68% ± 1.70% ± 2.08% ± 0.77% ± 0.16%

Table 4-13. UFTR in-house Gaussian model March 22nd, 2019 simulations Average Start Rhines Rhines 2 Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (F8 Tally) (F8 Tally) (F8 Tally) (F8 Tally) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 1.99E-08 ± 1.08E-08 ± 1.55E-07 ± 2.96E-08 ± 54.00% 777.2% 148.40% 6.90% ± 19.10% 274.9% 10:30 5.37E-11 1.51E-11 7.19E-09 1.46E-09 ± 0.17% ± 36.2% ± 7.36% 0.32% ± 1.29% ± 13.6% 30 2.24E-08 ± 9.81E-09 ± 1.90E-07 ± 1.25E-08 ± 43.80% 849.10% 55.70% 5.20% ± 6.60% ± 127.10% 11:00 9.41E-11 1.57E-11 3.04E-10 1.75E-11 ± 0.20% ± 3.81% ± 0.25% 0.01% 0.01% ± 0.27% 2.24E-08 ± 1.33E-08 ± 1.32E-07 ± 1.33E-08 ± 59.20% 590.80% 59.40% 10.00% 10.10% 100.30% 10:00 5.60E-11 1.73E-11 1.85E-10 7.18E-11 ± 0.17% ± 1.69% ± 0.35% ± 0.02% ± 0.06% ± 0.56% 60 2.31E-08 ± 9.69E-09 ± 1.80E-07 ± 1.13E-08 ± 42.00% 778.90% 49.00% 5.40% ± 6.30% ± 116.80% 11:00 5.78E-11 1.74E-11 2.70E-10 1.70E-11 ± 0.13% ± 2.27% ± 0.14% 0.01% 0.01% ± 0.27%

Table 4-14. UF weather in-house Gaussian model March 22nd, 2019 simulations Average Start Rhines Rhines 2 Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (F8 Tally) (F8 Tally) (F8 Tally) (F8 Tally) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 4.27E-08 ± 3.00E-08 ± 1.65E-07 ± 3.48E-07 ± 70.20% 387.20% 814.90% 18.10% 210.50% 1160.2% 10:30 8.97E-11 3.30E-11 2.97E-10 2.96E-09 ± 0.17% ± 1.07% ± 7.14% ± 0.04% ± 1.83% ± 9.94% 30 2.72E-08 ± 1.59E-08 ± 3.01E-07 ± 5.80E-08 ± 58.60% 1106.4% 213.40% 5.30% ± 19.30% 364.20% 11:00 6.80E-11 2.07E-11 4.82E-10 1.39E-10 ± 0.16% ± 3.28% ± 0.74% 0.01% ± 0.06% ± 1.00% 4.20E-08 ± 2.87E-08 ± 2.11E-07 ± 4.49E-07 ± 68.40% 501.90% 1070.3% 13.60% 213.30% 1565.3% 10:00 9.24E-11 2.87E-11 3.38E-10 2.33E-09 ± 0.17% ± 1.37% ± 6.04% ± 0.03% ± 1.16% ± 8.28% 60 2.39E-08 ± 1.34E-08 ± 4.64E-07 ± 3.58E-08 ± 55.90% 1937.7% 149.70% 2.90% ± 7.70% ± 267.80% 11:00 7.41E-11 2.95E-11 8.35E-10 7.16E-11 ± 0.21% ± 6.96% ± 0.55% 0.01% 0.02% ± 0.79%

Table 4-15. FLEXPART March 22nd, 2019 simulations Average Start Rhines Rhines 2 Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (F8 Tally) (F8 Tally) (F8 Tally) (F8 Tally) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 6.52E-09 ± 5.91E-09 ± 1.85E-07 ± 9.98E-09 ± 90.70% 2835.3% 153.00% 3.20% ± 5.40% ± 168.70% 10:30 3.52E-11 2.54E-11 4.81E-10 4.69E-11 ± 0.63% ± 17.0% ± 1.10% 0.02% 0.03% ± 1.08% 30 8.21E-09 ± 6.80E-09 ± 1.37E-07 ± 1.37E-08 ± 82.80% 1669.7% 166.90% 5.00% ± 10.00% 201.40% 11:00 6.57E-11 3.13E-11 3.56E-10 1.07E-10 ± 0.76% ± 14.0% ± 1.86% 0.03% ± 0.08% ± 1.82%

Discussion and Analysis of Results

Several trends in the count rate ratios observed on the three experimental measurement days were correctly simulated by some of the models but were not exact.

For example, there was a large increase in counts measured by the detectors on

Weimer and Reitz on May 8th from 15:00 to 16:00. The UF in-house model, airport in- house model, and AERMOD were all able to model this increase at the correct time. For the AERMOD simulations, the Weimer ratio increased at 14:00 to 15:00 from 47.57% ± Rhines

0.05% to 220.31% ± 0.14% while the measurement ratio increased from 28.7% ± 0.20% to 211.0% ± 1.72%. On the other hand, the Reitz value at this time increased from Rhines

12.3% ± 0.16% to 127.3% ± 1.16% for the measurements and only 11.45% ± 0.11% to

42.27% ± 0.36% in the AERMOD simulations. While this trend is consistent with the measurements, the values did not change with the same intensity and in the case of the

Reitz ratio, the values were far from equal. Rhines

To better compare the models on the three measurement days, the percent difference between the measured count rate ratios and simulation tally ratios was calculated for each model along with its standard deviation using Equations 4-7 and 4-8:

|푚푒푎푠푢푟푒푑 푐표푢푛푡 푟푎푡푒 푟푎푡𝑖표 − 푠𝑖푚푢푙푎푡𝑖표푛 푡푎푙푙푦 푟푎푡𝑖표| 푃푒푟푐푒푛푡 퐷𝑖푓푓푒푟푒푛푐푒 = , (4-7) 푚푒푎푠푢푟푒푚푒푛푡 푐표푢푛푡 푟푎푡푒 푟푎푡𝑖표

2 2 휎 휎푇푎푙푙푦 푅푎푡𝑖표 휎 = 푃푒푟푐푒푛푡 퐷𝑖푓푓푒푟푒푛푐푒 ∗ √( 퐶표푢푛푡 푅푎푡푒 푅푎푡𝑖표 ) + ( ) . (4-8) 푃푒푟푐푒푛푡 퐷𝑖푓푓푒푟푒푛푐푒 퐶표푢푛푡 푅푎푡푒 푅푎푡𝑖표 푇푎푙푙푦 푅푎푡𝑖표 These percent differences were then averaged and categorized depending on the date, specific ratio, and plume model utilized. The total results are displayed in Table 4-16 along with the total averaged percent difference for all models on each measurement date. The simulation code which best predicted the measured count rate ratios on May

8th was by far the AERMOD code. On two out of the six measurement hours (10:00 and

12:00), the AERMOD code produced several tally ratio results which were extremely similar to ones produced by the measurements, particularly the ones involving the

Rhines, Stadium, and Weimer count rates. For instance, the 12:00 41Ar plume simulation produced differences of 12.3% ± 0.71%, 14.2% ± 0.58%, and 2.8% ± 0.12% for the Stadium, Weimer, and Stadium ratios respectively. The airport in-house model was Rhines Rhines Weimer able to recreate some of the successes of the AERMOD code, but not as effectively.

This most likely occurred because it utilized the same meteorological input data but did not include the same preprocessing capabilities of the AERMOD code. For the May 8th simulations, the UF in-house modeling simulations produced improved results when the meteorological data were averaged every 60 minutes. In terms of the FLEXPART simulations, the results were very poor estimators of the trends in the measurement data.

Table 4-16. Average percent difference for all models simulating the 41Ar plume emitted by the high velocity plume stack 푆푡푎푑𝑖푢푚 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푆푡푎푑𝑖푢푚 푅푒𝑖푡푧 푅푒𝑖푡푧 May 8th Average 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푆푡푎푑𝑖푢푚 1625.1% 652.00% 916.20% 2382.3% 489.5% ± 171.40% 1039.40% UF-10m ± 279.4% ± 6.28% ± 62.18% ± 299.1% 100.1% ± 31.53% ± 71.18% 379.20% 76.40% ± 268.10% 456.00% 303.90% 112.10% 266.00% UF-30m ± 15.89% 0.44% ± 30.52% ± 12.53% ± 59.10% ± 13.48% ± 11.80% 367.80% 52.80% ± 229.50% 330.70% 183.50% 112.90% 212.90% UF-60m ± 12.71% 0.24% ± 24.49% ± 9.42% ± 18.20% ± 9.72% ± 5.95% 97.30% ± 74.70% ± 156.20% 62.80% ± 233.60% 220.60% 140.90% Airport 4.44% 0.58% ± 6.96% 2.38% ± 26.02% ± 34.73% ± 7.37% 1558.80% 283.20% 720.30% 1406.3% 156.40% 124.90% 708.30% FLEXPART ± 54.66% ± 1.90% ± 86.78% ± 128.1% ± 17.33% ± 12.54% ± 27.58% 70.10% ± 37.50% ± 52.30% ± 55.10% ± 107.10% 179.60% 83.60% ± AERMOD 3.33% 0.25% 3.02% 3.09% ± 13.01% ± 26.00% 4.93% 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 March 20th Average 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 41.00% ± 252.60% 617.10% 375.30% 257.70% 1929.30% 578.80% UFTR-10m 0.53% ± 2.97% ± 7.80% ± 4.93% ± 6.78% ± 35.37% ± 6.22%

Table 4-16. Continued 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 March 20th Average 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 65.50% ± 640.70% 4006.8% 162.20% 427.60% 17695.2% 3833.0% UF-10m 0.46% ± 13.03% ± 212.8% ± 7.16% ± 23.32% ± 1348% ± 227.5% 36.10% ± 418.6% ± 187.30% 102.40% 228.30% 550.50% 253.90% UFTR-30m 0.18% 141.49% ± 2.41% ± 5.42% ± 4.54% ± 5.10% ± 23.63% 58.20% ± 935.3% ± 3760.9% 77.30% ± 616.50% 14353.4% 3300.3% UF-30m 0.37% 265.41% ± 159.8% 12.50% ± 27.77% ± 1174% ± 202.4% 34.30% ± 35.70% ± 138.50% 22.90% ± 180.40% 430.10% 140.30% UFTR-60m 0.54% 0.19% ± 1.15% 0.12% ± 2.58% ± 3.71% ± 0.78% 66.60% ± 367.50% 4195.3% 87.20% ± 502.30% 2825.60% 1340.80% UF-60m 0.81% ± 6.53% ± 131.6% 2.09% ± 16.71% ± 25.26% ± 22.54% 18.20% ± 57.40% ± 238.10% 308.00% 118.20% 594.20% 222.40% FLEXPART 2.25% 1.06% ± 10.33% ± 1.94% ± 1.85% ± 29.22% ± 5.20% 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 March 22nd Average 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 72.50% ± 69.30% ± 528.50% 120.20% 68.30% ± 57.20% ± 152.70% UFTR-10m 7.08% 6.65% ± 39.44% ± 5.95% 1.11% 2.49% ± 6.86% 64.40% ± 63.40% ± 2902.2% 01.60% ± 429.90% 204.60% 661.00% UF-10m 6.48% 6.47% ± 164.6% 19.39% ± 4.80% ± 5.06% ± 27.69% 73.50% ± 76.20% ± 86.30% ± 113.60% 32.90% ± 53.90% ± 72.70% ± UFTR-30m 8.26% 8.84% 9.14% ± 8.41% 1.56% 3.18% 2.95% 65.20% ± 85.70% ± 52.20% ± 165.20% 317.30% 103.50% 131.50% UF-30m 7.59% 8.61% 7.54% ± 8.78% ± 3.02% ± 2.44% ± 2.79% 53.50% ± 69.20% ± 81.00% ± 129.80% 52.90% ± 59.20% ± 74.30% ± FLEXPART 6.49% 8.18% 8.05% ± 7.96% 0.42% 2.54% 2.60%

For the March 20th and 22nd simulations, the Rhines 2 count rate and tally ratios are Rhines relatively close, especially when compared to all the other ratios. This could arise from the increased number of counts detected on these stations throughout the two days of simulations (only the first hour of measurements on March 22nd) and their proximity to each other. The simulations run on FLEXPART with the March 20th and 22nd meteorological conditions showed improved alignment with the measurements, but the trends were still relatively poor. Furthermore, the addition of the UFTR in-house modeling simulations provided 10, 30, and 60 minute averaged results which were more accurate than those obtained by the UF in-house code. While the results for all the

March 2019 UFTR simulations were overall poorer than the May 8th AERMOD simulations, there were several 10 minute averaged runs which produced accurate tally

96 ratios for three out of the four modeled detector stations. For example, the 10 minute simulations at 11:00, 12:00, 15:30, and 15:50 all produced percent differences lower than 30% for three detector stations.

After observing all the simulation and measurement data, it became clear that there were many instances when three tally ratios representing three of the four detector stations were far more accurate than the other three ratios. This would occur because of errors in one detector station which affected the three poor count rate ratios.

We found that this frequently occurred when one or more of the detector stations detected very small 41Ar count rates. To fix this issue, the average percent differences were recalculated by removing all simulation tally ratios where one or more of the stations detected less than three counts per second of the 41Ar 1294 keV emitted photons. The results are displayed on Table 4-17.

Table 4-17. Average percent difference for all models simulating the 41Ar plume emitted by the high velocity plume stack (all results which simulated stations receiving count rates lower than three cps removed) 푆푡푎푑𝑖푢푚 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푆푡푎푑𝑖푢푚 푅푒𝑖푡푧 푅푒𝑖푡푧 May 8th Average 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푆푡푎푑𝑖푢푚 403.20% 652.00% 58.40% ± 251.30% 57.60% ± 0.00% ± 284.50% UF-10m ± 11.54% ± 6.28% 0.57% ± 9.14% 0.35% 0.00% ± 3.20% 153.40% 76.40% ± 89.20% ± 117.90% 265.10% 0.00% ± 140.40% UF-30m ± 2.60% 0.44% 9.31% ± 1.79% ± 66.66% 0.00% ± 13.48% 125.10% 52.80% ± 56.50% ± 85.50% ± 53.20% ± 0.00% ± 74.60% ± UF-60m ± 3.96% 0.58% 1.13% 2.46% 0.87% 0.00% 0.98% 43.60% ± 74.70% ± 202.20% 43.60% ± 62.80% ± 0.00% ± 85.40% ± Airport 1.37% 0.58% ± 1.96% 1.69% 0.66% 0.00% 0.61% 439.20% 283.20% 183.30% 54.00% ± 30.10% ± 0.00% ± 198.00% FLEXPART ± 13.41% ± 1.90% ± 2.31% 1.74% 0.32% 0.00% ± 2.77% 41.10% ± 37.50% ± 49.30% ± 22.20% ± 46.90% ± 0.00% ± 39.40% ± AERMOD 1.25% 0.25% 0.60% 0.74% 0.44% 0.00% 0.33% 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 March 20th Average 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 46.60% ± 121.60% 302.10% 184.50% 200.50% 249.40% 184.10% UFTR-10m 2.29% ± 0.45% ± 3.32% ± 4.68% ± 6.67% ± 10.29% ± 1.95% 70.80% ± 468.10% 1050.30% 149.80% 435.80% 13054.7% 2538.2% UF-10m 0.46% ± 5.96% ± 29.22% ± 3.21% ± 29.09% ± 1052% ± 175.5% 36.10% ± 47.50% ± 220.60% 102.40% 233.20% 817.20% 242.80% UFTR-30m 0.18% 0.26% ± 1.74% ± 12.65% ± 4.66% ± 7.23% ± 2.57%

Table 4-17. Continued 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 March 20th Average 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 58.20% ± 935.30% 1197.50% 77.30% ± 295.60% 2777.80% 890.30% UF-30m 0.37% ± 265.4% ± 8.34% 12.50% ± 4.91% ± 23.81% ± 44.49% 34.30% ± 35.70% ± 165.30% 22.90% ± 180.40% 614.10% 175.40% UFTR-60m 0.54% 0.19% ± 1.34% 0.12% ± 2.58% ± 5.17% ± 0.99% 66.60% ± 367.50% 2783.50% 87.20% ± 502.30% 2825.60% 1105.40% UF-60m 0.81% ± 6.53% ± 28.49% 2.09% ± 16.71% ± 25.26% ± 7.03% 18.20% ± 57.40% ± 139.00% 308.00% 118.20% 228.50% 144.90% FLEXPART 2.25% 1.06% ± 2.21% ± 1.94% ± 1.85% ± 3.46% ± 0.92% 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 March 22nd Average 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 64.10% ± 57.40% ± 231.50% 100.20% 64.50% ± 42.10% ± 93.30% ± UFTR-10m 2.53% 2.00% ± 10.47% ± 2.80% 0.48% 1.13% 1.89% 55.20% ± 32.50% ± 2972.9% 20.20% ± 471.90% 455.10% 668.00% UF-10m 2.16% 1.13% ± 107.2% 0.44% ± 4.84% ± 12.06% ± 18.00% 66.10% ± 58.70% ± 86.30% ± 113.60% 32.90% ± 53.90% ± 68.60% ± UFTR-30m 2.73% 3.42% 9.14% ± 8.41% 1.56% 3.18% 2.27% 56.10% ± 79.50% ± 52.20% ± 165.20% 317.30% 103.50% 129.00% UF-30m 2.32% 2.80% 7.54% ± 8.78% ± 3.02% ± 2.44% ± 2.12% 43.40% ± 50.60% ± 81.00% ± 129.80% 52.90% ± 59.20% ± 69.50% ± FLEXPART 1.81% 1.80% 8.05% ± 7.96% 0.42% 2.54% 1.98%

There is a clear improvement in most of the simulation results and their associated errors after deleting all measurement data points with low count rates. For example, the average difference between the May 8th measurements and the AERMOD simulations was originally 83.6% ± 4.93% However, there were many times throughout the day where the Stadium and Reitz count rates fell below 3 cps. After deleting this data, the average difference for the AERMOD simulations dropped down to 39.4% ±

0.33%. While the percent difference between simulation models and measurement results tends to be a good indicator of the model’s accuracy, this is not always true, especially in terms of predicting the correct trends. For instance, the FLEXPART simulations on March 20th after deleting the low count measurement results have the smallest total averaged percentage difference out of all models. However, it does not simulate the more accurate ratio trends that the other models are able to do. From

14:00 to 15:00, the Weimer measurement value increases from 63.5% ± 0.69% to Rhines

260.3% ± 1.91% while the FLEXPART results decrease from 48.4% ± 2.35% to 38.0% ±

1.7%. However, the UF in-house model output increases from 318.7% ± 0.79% to

485.5% ± 1.29% while the UFTR in-house model value increases from 88.3% ± 0.21% to 209.6% ± 0.81%. Through the analysis of these trends along with the percentage differences outputted by the UFTR in-house Gaussian model, the UF in-house

Gaussian model, AERMOD, and FLEXPART, we concluded that the most effective model for simulating the 41Ar plume emitted from the high velocity plume stack is

AERMOD while the second best is the in-house Gaussian model with UFTR data.

CHAPTER 5 LOW VELOCITY PLUME STACK

Measurements Results for November 2018 and January 2019 Trials

The first set of low velocity plume stack data was measured on November 7th,

2018. During this measurement, two standalone NaI detectors were placed on the higher Rhines Hall rooftop, two were positioned on the lower Rhines Hall rooftop, two were positioned on top of Weimer Hall, and the RSX-1 detector was situated on the

Reitz Union. Before turning on the reactor at 10:20, background data were collected for

20 minutes. The UFTR reached 100 kW at 10:44 and began emitting the 41Ar plume at equilibrium at 12:30. The reactor was shut down at 16:30 along with the data collection.

A larger low velocity plume stack experimental dataset was collected on January

16th, 17th, and 18th of 2019. For all days of measurement, the RSX-1 detector was placed on the taller Rhines Hall rooftop while two standalone NaI detectors were stationed at the Reitz Union, Weimer Hall, and the lower Rhines Hall rooftops. On

January 16th, the reactor was turned on at 9:30, reached full power at 9:49, and reached

41Ar equilibrium at 10:45. The detectors on Rhines Hall stopped recording plume data at

16:30 when the reactor was turned off, while the Weimer and Reitz Union detectors kept accumulating data until 17:30. This was done to calculate the drop in 41Ar counts after reactor shutdown. The Rhines Hall detectors did not measure plume data after 16:30 due to our inability to access the rooftop after 17:00. Figure 5-1 displays the ten-minute averaged count rates recorded on the Weimer detectors from 16:30 to 17:30. While the counts are negligible approximately 50 to 60 minutes after reactor shutdown, the gradual drop-off of photon counts proves that there is a sustained presence of 41Ar particles in the first hour after shutdown. Since there is no continued release of the

100 radioactive plume after the reactor is turned off due to a negligible buildup of 41Ar in the reactor cell, it is theorized that this occurs because of wake effects caused by nearby buildings.

Figure 5-1. Decrease in 41Ar count rate after UFTR shutdown

During the measurements taken on January 17th, the reactor was turned on at

9:00, reached 100 kW at 9:14, and 41Ar production hit equilibrium at 10:22. Data collection ended at 16:00 when the UFTR was shut down. For the measurements recorded on January 18th, the reactor was started approximately at 9:30, achieved full power by 9:44, and arrived at equilibrium 41Ar production at 10:30. However, the reactor was shut down at 13:42, leading to loss in measurement data. The reactor was restarted at 14:00 hit equilibrium at 15:00, and shutdown at 16:00.

As previously discussed, the UFTR is required to abide by the NRC’s as low as reasonably achievable (ALARA) policy. It states that the total effective dose equivalent to the maximally-exposed member of the public should not surpass 10 mrem yr-1 [26]. On

January 18th from 15:00 to 15:30, the largest 30 minute averaged count rate was recorded at 109.77 ± 0.19 cps on the Weimer detector station. This value was utilized to approximate the maximum dose observed on one of the detector station locations during

UFTR operation. To estimate this dose, a ratio was calculated by dividing the total UFTR plume count rate at that time by the total background count rate, seen in Equation 5-1:

101

Background subtracted total UFTR plume count rate 푈퐹푇푅 푃푙푢푚푒 푅푎푡𝑖표 = . (5-1) Total background count rate This UFTR plume ratio was multiplied by the average annual natural background dose to calculate the estimated average annual dose coming from the UFTR plume at the Weimer rooftop if the meteorological conditions observed on January 18th from 15:00 to 15:30 were constant and the UFTR operated constantly throughout the year. Finally, this value was utilized to estimate the average number of allowable full-power hours of operation when taking into consideration the 10 mrem yr-1 limit. The results are displayed on Table

5-1.

Table 5-1. Dose estimation calculations at Weimer Hall on January 18th from 15:00 to 15:30 Average 41Ar background subtracted count rate (1294 keV peak) 109.77 ± 0.19 cps Total background count rate 235.71 ± 0.36 cps Background subtracted total UFTR plume count rate 333.56 ± 0.43 cps UFTR Plume Ratio 1.415 Average annual natural background dose 322.4 mRem Estimated annual dose on Weimer Hall 456.2 mRem Average # of allowable full-power hour operations 192 hours

In 2018, the UFTR was operated at full-power for 63 hours, which reinforces the

UFTR’s case for abiding by ALARA policies. Furthermore, this dose calculation is significantly conservative since it assumes that all natural background radiation comes from photons and that the meteorological conditions which provided the highest count rate during our measurements on all detector locations are constant.

Thermal shift calibrations were performed on the November and January datasets.

The largest 30 minute averaged 41Ar peaks for the November experiment and the three days of measurement in January are displayed in Figures 5-2 through 5-5. The background subtracted 41Ar count rates averaged every 30, and 60 minutes for the

November and January measurements are displayed in Tables 5-2 through 5-5 along

102 with their respective count rate ratios (10 minute averaged results shown in Tables A-9 through A-12).

(a)

(b)

(c)

(d)

Figure 5-2. Maximum 30 minute spectra at (a) Rhines (b) Weimer (c) Rhines 2 (d) Reitz on November 7th, 2018 103

(a)

(b)

(c)

(d)

Figure 5-3. Maximum 30 minute spectra at (a) Rhines (b) Weimer (c) Rhines 2 (d) Reitz on January 16th, 2019

104

(a)

(b)

(c)

(d)

Figure 5-4. Maximum 30 minute spectra at (a) Rhines (b) Weimer (c) Rhines 2 (d) Reitz on January 17th, 2019

105

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(b)

(c)

(d)

Figure 5-5. Maximum 30 minute spectra at (a) Rhines (b) Weimer (c) Rhines 2 (d) Reitz on January 18th, 2019 106

Table 5-2. November 7th, 2018 measurement 41Ar count rates and count rate ratios Average Start Rhines Rhines Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (cps) 2 (cps) (cps) (cps) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 15.33 2.47 16.96 0.61 16.10% ± 110.60% 4.00% ± 14.50% ± 3.60% ± 24.80% ± 12:30 ±0.10 ±0.08 ±0.10 ±0.08 0.55% ± 1.00% 0.52% 0.49% 0.46% 3.30% 29.40 5.17 18.11 1.04 17.60% ± 61.60% ± 3.50% ± 28.50% ± 5.70% ± 20.10% ± 13:00 ±0.12 ±0.09 ±0.11 ±0.08 0.30% 0.44% 0.27% 0.51% 0.44% 1.57% 23.11 3.69 17.66 0.76 16.00% ± 76.40% ± 3.30% ± 20.90% ± 4.30% ± 20.70% ± 13:30 ±0.11 ±0.08 ±0.11 ±0.08 0.37% 0.59% 0.34% 0.49% 0.45% 2.20% 28.27 4.73 25.22 0.99 16.70% ± 89.20% ± 3.50% ± 18.80% ± 3.90% ± 20.90% ± 14:00 ±0.12 ±0.09 ±0.12 ±0.08 0.31% 0.56% 0.28% 0.35% 0.31% 1.72% 30 23.54 4.12 13.45 1.01 17.50% ± 57.10% ± 4.30% ± 30.70% ± 7.50% ± 24.40% ± 14:30 ±0.11 ±0.08 ±0.10 ±0.08 0.37% 0.50% 0.34% 0.67% 0.60% 1.99% 30.74 4.26 7.98 0.97 13.90% ± 26.00% ± 3.20% ± 53.40% ± 12.20% ± 22.80% ± 15:00 ±0.12 ±0.09 ±0.09 ±0.08 0.28% 0.30% 0.26% 1.22% 1.01% 1.92% 69.66 8.46 8.66 1.38 12.10% ± 12.40% ± 2.00% ± 97.70% ± 15.90% ± 16.30% ± 15:30 ±0.16 ±0.09 ±0.09 ±0.08 0.13% 0.13% 0.12% 1.46% 0.94% 0.96% 106.78 11.39 11.59 1.59 10.70% ± 10.90% ± 1.50% ± 98.30% ± 13.70% ± 13.90% ± 16:00 ±0.19 ±0.10 ±0.09 ±0.08 0.09% 0.09% 0.08% 1.14% 0.70% 0.71% 26.26 4.43 17.88 0.90 16.90% ± 68.10% ± 3.40% ± 24.80% ± 5.00% ± 20.40% ± 13:00 ±0.08 ±0.06 ±0.07 ±0.06 0.24% 0.36% 0.21% 0.35% 0.31% 1.30% 25.90 4.43 19.34 1.00 17.10% ± 74.60% ± 3.90% ± 22.90% ± 5.20% ± 22.50% ± 60 14:00 ±0.08 ±0.06 ±0.08 ±0.06 0.24% 0.38% 0.22% 0.33% 0.29% 1.30% 50.20 6.36 8.32 1.18 12.70% ± 16.60% ± 2.30% ± 76.50% ± 14.10% ± 18.50% ± 15:00 ±0.10 ±0.06 ±0.06 ±0.06 0.13% 0.13% 0.11% 0.95% 0.69% 0.91%

Table 5-3. January 16th, 2019 measurement 41Ar count rates and count rate ratios Average Start Rhines Rhines Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (cps) 2 (cps) (cps) (cps) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 5.88 6.64 80.62 13.93 113.00% 1371.80% 237.00% 8.20% ± 17.30% ± 209.80% 11:00 ±0.09 ±0.09 ±0.17 ±0.10 ± 2.34% ± 21.75% ± 4.09% 0.11% 0.13% ± 3.21% 10.48 21.90 35.32 15.75 209.00% 337.10% 150.30% 62.00% ± 44.60% ± 71.90% ± 11:30 ±0.10 ±0.11 ±0.13 ±0.10 ± 2.23% ± 3.42% ± 1.84% 0.39% 0.39% 0.67% 30 10.17 16.15 47.74 27.04 158.70% 469.40% 265.90% 33.80% ± 56.60% ± 167.50% 12:00 ±0.10 ±0.10 ±0.14 ±0.12 ± 1.84% ± 4.76% ± 3.55% 0.24% 0.55% ± 1.87% 15.65 40.34 26.59 20.68 257.80% 169.90% 132.20% 151.70% 77.80% ± 51.30% ± 12:30 ±0.11 ±0.13 ±0.12 ±0.11 ± 1.94% ± 1.40% ± 1.28% ± 0.86% 0.65% 0.39%

107

Table 5-3. Continued Average Start Rhines Rhines Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (cps) 2 (cps) (cps) (cps) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 7.18 12.10 37.91 15.87 168.60% 528.20% 221.20% 31.90% ± 41.90% ± 131.10% 13:00 ±0.09 ±0.10 ±0.13 ±0.10 ± 2.59% ± 7.18% ± 3.10% 0.28% 0.25% ± 1.22% 9.41 16.16 48.79 13.24 171.70% 518.50% 140.70% 33.10% ± 27.10% ± 81.90% ± 13:30 ±0.10 ±0.10 ±0.14 ±0.10 ± 2.09% ± 5.59% ± 1.59% 0.23% 0.15% 0.64% 18.33 41.56 18.49 14.86 226.70% 100.90% 81.00% ± 224.80% 80.30% ± 35.70% ± 14:00 ±0.11 ±0.13 ±0.12 ±0.10 ± 1.53% ± 0.87% 0.57% ± 1.57% 0.58% 0.18% 12.15 26.46 33.60 13.16 217.80% 276.50% 108.30% 78.80% ± 39.20% ± 49.70% ± 30 14:30 ±0.10 ±0.12 ±0.13 ±0.10 ± 2.05% ± 2.54% ± 0.97% 0.46% 0.20% 0.27% 15.87 26.05 68.89 15.10 164.20% 434.00% 95.20% ± 37.80% ± 21.90% ± 58.00% ± 15:00 ±0.11 ±0.12 ±0.16 ±0.10 ± 1.32% ± 3.08% 0.73% 0.19% 0.10% 0.34% 10.97 24.70 37.33 16.07 225.20% 340.30% 146.50% 66.20% ± 43.00% ± 65.10% ± 15:30 ±0.10 ±0.11 ±0.13 ±0.10 ± 2.29% ± 3.33% ± 1.52% 0.38% 0.26% 0.44% 14.73 38.03 36.57 13.94 258.10% 248.20% 94.60% ± 104.00% 38.10% ± 36.70% ± 16:00 ±0.10 ±0.13 ±0.13 ±0.12 ± 2.03% ± 1.98% 1.05% ± 0.52% 0.35% 0.34% 8.18 14.27 57.97 14.84 174.50% 708.90% 181.50% 24.60% ± 25.60% ± 104.00% 11:00 ±0.07 ±0.07 ±0.11 ±0.07 ± 1.68% ± 6.02% ± 1.71% 0.13% 0.12% ± 0.69% 12.91 28.24 37.17 23.86 218.80% 287.90% 184.80% 76.00% ± 64.20% ± 84.50% ± 12:00 ±0.07 ±0.08 ±0.09 ±0.08 ± 1.39% ± 1.77% ± 1.46% 0.30% 0.39% 0.53% 8.29 14.13 43.35 14.56 170.40% 522.70% 175.50% 32.60% ± 33.60% ± 103.00% 60 13:00 ±0.07 ±0.07 ±0.10 ±0.07 ± 1.63% ± 4.43% ± 1.70% 0.18% 0.19% ± 0.74% 15.24 34.01 26.04 14.01 223.10% 170.90% 91.90% ± 130.60% 53.80% ± 41.20% ± 14:00 ±0.07 ±0.09 ±0.09 ±0.07 ± 1.23% ± 1.01% 0.66% ± 0.55% 0.34% 0.24% 13.42 25.38 53.11 15.59 189.10% 395.70% 116.20% 47.80% ± 29.40% ± 61.40% ± 15:00 ±0.07 ±0.08 ±0.11 ±0.07 ± 1.19% ± 2.29% ± 0.85% 0.18% 0.15% 0.36%

Table 5-4. January 17th, 2019 measurement 41Ar count rates and count rate ratios Average Start Rhines Rhines Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (cps) 2 (cps) (cps) (cps) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 65.23 75.23 9.85 1.16 115.30% 15.10% ± 1.80% ± 763.50% 11.70% ± 1.50% ± 10:30 ±0.16 ±0.16 ±0.09 ±0.08 ± 0.38% 0.15% 0.12% ± 7.29% 0.82% 0.10% 45.64 61.15 14.66 1.66 134.00% 32.10% ± 3.60% ± 417.30% 11.40% ± 2.70% ± 30 11:00 ±0.14 ±0.15 ±0.10 ±0.08 ± 0.53% 0.24% 0.17% ± 3.03% 0.56% 0.13% 41.78 31.18 26.41 4.46 74.60% ± 63.20% ± 10.70% ± 118.10% 16.90% ± 14.30% ± 11:30 ±0.14 ±0.12 ±0.12 ±0.09 0.38% 0.35% 0.21% ± 0.69% 0.33% 0.28%

108

Table 5-4. Continued Average Start Rhines Rhines Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (cps) 2 (cps) (cps) (cps) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 49.40 27.55 0.00 2.02 55.80% ± 0.00% ± 4.10% ± 0.00% ± 0.00% ± 7.30% ± 12:00 ±0.14 ±0.12 ±0.00 ±0.08 0.29% 0.00% 0.17% 0.00% 0.00% 0.30% 65.00 31.76 0.00 2.48 48.90% ± 0.00% ± 3.80% ± 0.00% ± 0.00% ± 7.80% ± 12:30 ±0.16 ±0.12 ±0.00 ±0.08 0.22% 0.00% 0.13% 0.00% 0.00% 0.26% 24.78 12.44 0.00 2.33 50.20% ± 0.00% ± 9.40% ± 0.00% ± 0.00% ± 18.70% ± 13:00 ±0.12 ±0.09 ±0.00 ±0.08 0.45% 0.00% 0.33% 0.00% 0.00% 0.67% 54.62 12.79 8.39 1.78 23.40% ± 15.40% ± 3.30% ± 152.50% 21.20% ± 13.90% ± 13:30 ±0.15 ±0.10 ±0.09 ±0.08 0.19% 0.18% 0.15% ± 2.05% 0.99% 0.64% 30 5.26 5.57 72.66 2.85 105.90% 1382.20% 54.30% ± 7.70% ± 3.90% ± 51.20% ± 14:00 ±0.09 ±0.08 ±0.16 ±0.08 ± 2.40% ± 24.22% 1.84% 0.11% 0.11% 1.66% 30.07 4.53 23.71 0.89 15.10% ± 78.80% ± 3.00% ± 19.10% ± 3.80% ± 19.70% ± 14:30 ±0.12 ±0.08 ±0.12 ±0.08 0.27% 0.52% 0.27% 0.35% 0.34% 1.79% 38.85 5.75 21.25 0.88 14.80% ± 54.70% ± 2.30% ± 27.10% ± 4.10% ± 15.30% ± 15:00 ±0.13 ±0.08 ±0.11 ±0.08 0.22% 0.33% 0.21% 0.41% 0.37% 1.40% 62.26 6.45 18.67 0.37 10.40% ± 30.00% ± 0.60% ± 34.50% ± 2.00% ± 5.70% ± 15:30 ±0.16 ±0.08 ±0.11 ±0.08 0.14% 0.19% 0.13% 0.50% 0.42% 1.21% 43.71 46.17 20.53 3.06 105.60% 47.00% ± 7.00% ± 224.90% 14.90% ± 6.60% ± 11:00 ±0.10 ±0.10 ±0.08 ±0.06 ± 0.32% 0.21% 0.14% ± 0.97% 0.29% 0.13% 57.20 29.65 0.00 2.25 51.80% ± 0.00% ± 3.90% ± 0.00% ± 0.00% ± 7.60% ± 12:00 ±0.11 ±0.08 ±0.00 ±0.06 0.18% 0.00% 0.10% 0.00% 0.00% 0.20% 39.70 12.61 4.20 2.05 31.80% ± 10.60% ± 5.20% ± 300.60% 48.90% ± 16.30% ± 60 13:00 ±0.09 ±0.07 ±0.06 ±0.06 0.19% 0.16% 0.15% ± 4.67% 1.54% 0.47% 17.66 5.05 48.18 1.87 28.60% ± 272.80% 10.60% ± 10.50% ± 3.90% ± 37.10% ± 14:00 ±0.08 ±0.06 ±0.10 ±0.06 0.34% ± 1.32% 0.33% 0.12% 0.12% 1.21% 50.56 6.10 19.96 0.63 12.10% ± 39.50% ± 1.20% ± 30.60% ± 3.10% ± 10.20% ± 15:00 ±0.10 ±0.06 ±0.08 ±0.06 0.12% 0.17% 0.11% 0.32% 0.28% 0.92%

Table 5-5. January 18th, 2019 measurement 41Ar count rates and count rate ratios Average Start Rhines Rhines Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (cps) 2 (cps) (cps) (cps) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 34.89 44.50 83.17 32.10 127.50% 238.40% 92.00% ± 53.50% ± 38.60% ± 72.10% ± 10:30 ±0.13 ±0.14 ±0.17 ±0.12 ± 0.61% ± 1.01% 0.49% 0.20% 0.17% 0.35% 30 40.36 9.31 42.43 2.35 23.10% ± 105.10% 5.80% ± 21.90% ± 5.50% ± 25.20% ± 11:00 ±0.13 ±0.09 ±0.14 ±0.08 0.24% ± 0.49% 0.20% 0.23% 0.19% 0.92%

109

Table 5-5. Continued Average Start Rhines Rhines Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (cps) 2 (cps) (cps) (cps) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 33.90 11.09 35.22 0.12 32.70% ± 103.90% 0.40% ± 31.50% ± 0.30% ± 1.10% ± 11:30 ±0.13 ±0.10 ±0.13 ±0.08 0.31% ± 0.55% 0.26% 0.29% 0.20% 0.72% 5.76 5.19 74.54 3.74 90.00% ± 1294.00% 65.00% ± 7.00% ± 5.00% ± 72.20% ± 12:00 ±0.09 ±0.09 ±0.16 ±0.08 2.10% ± 20.89% 1.79% 0.12% 0.11% 2.03% 3.55 2.12 102.77 1.31 62.10% ± 3011.10% 38.40% ± 2.10% ± 1.30% ± 61.90% ± 12:30 ±0.09 ±0.08 ±0.18 ±0.08 2.83% ± 75.22% 2.53% 0.08% 0.08% 4.46% 3.29 1.23 61.66 0.20 37.50% ± 1874.70% 6.10% ± 2.00% ± 0.30% ± 16.20% ± 13:00 ±0.09 ±0.08 ±0.15 ±0.08 2.77% ± 50.56% 2.39% 0.14% 0.12% 6.43% 2.36 0.35 42.14 5.09 14.80% ± 1783.50% 215.50% 0.80% ± 12.10% ± 1451.7% 30 13:30 ±0.09 ±0.12 ±0.14 ±0.09 4.95% ± 65.81% ± 8.73% 0.27% 0.21% ± 483.2% 7.07 0.02 20.03 0.00 0.30% ± 283.40% 0.00% ± 0.10% ± 0.00% ± 0.00% ± 14:00 ±0.09 ±0.00 ±0.11 ±0.00 0.00% ± 4.11% 0.00% 0.01% 0.00% 0.00% 12.85 0.00 47.28 0.00 0.00% ± 368.00% 0.00% ± 0.00% ± 0.00% ± 0.00% ± 14:30 ±0.10 ±0.00 ±0.14 ±0.00 0.00% ± 3.12% 0.00% 0.00% 0.00% 0.00% 0.00 0.00 109.77 0.11 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.10% ± 0.00% ± 15:00 ±0.00 ±0.00 ±0.19 ±0.08 0.00% 0.00% 0.00% 0.00% 0.07% 0.00% 1.85 0.00 23.06 0.00 0.00% ± 1249.50% 0.00% ± 0.00% ± 0.00% ± 0.00% ± 15:30 ±0.09 ±0.00 ±0.12 ±0.00 0.00% ± 58.59% 0.00% 0.00% 0.00% 0.00% 37.13 10.20 38.83 1.23 27.50% ± 104.60% 3.30% ± 26.30% ± 3.20% ± 12.10% ± 11:00 ±0.09 ±0.07 ±0.09 ±0.06 0.19% ± 0.36% 0.15% 0.18% 0.15% 0.56% 4.66 3.65 88.66 2.53 79.60% ± 1932.80% 55.10% ± 4.10% ± 2.80% ± 69.20% ± 12:00 ±0.06 ±0.06 ±0.12 ±0.06 1.70% ± 26.65% 1.48% 0.07% 0.06% 1.96% 2.83 0.79 51.90 2.65 28.00% ± 1836.60% 93.60% ± 1.50% ± 5.10% ± 334.40% 60 13:00 ±0.06 ±0.06 ±0.10 ±0.06 2.31% ± 40.42% 2.91% 0.12% 0.11% ± 27.59% 9.96 0.01 33.65 0.01 0.10% ± 337.90% 0.00% ± 0.03% ± 0.00% ± 0.00% ± 14:00 ±0.07 ±0.00 ±0.09 ±0.06 0.004% ± 2.53% 0.00% 0.002% 0.00% 0.00% 0.92 0.00 66.42 0.06 0.00% ± 7197.0% 6.10% ± 0.00% ± 0.10% ± 0.00% ± 15:00 ±0.06 ±0.00 ±0.11 ±0.06 0.00% ± 466.2% 6.01% 0.00% 0.10% 0.00%

110

Simulation Results for November 2018 and January 2019 Trials

The in-house Gaussian, AERMOD, and FLEXPART codes were utilized to simulate the dispersion of the 41Ar plume with the meteorological conditions measured on November 7th, 2018 and January 16th-18th, 2019. As mentioned in earlier chapters, the necessary ATM inputs for the low velocity plume stack simulations differ from the high velocity stack. The input changes which affect the dispersion of the 41Ar plume include the stack velocity (11.168 m s-1), stack diameter (0.876 m), and physical stack height (50 m above sea level). For all four simulation days, the resolution of the plume grid in the in-house Gaussian code was 75 cm with maximum distance of 225 m in the x, y, and z directions (equal to the March 2019 simulations). The FLEXPART and

AERMOD plume grids remained the same when compared to the high velocity plume stack simulations. Wind information measured by the UFTR, UF, and GNV Regional

Airport weather stations averaged hourly is displayed in Table 5-6. These data were utilized to run the in-house Gaussian code. Due to a malfunction in the UFTR weather station for the January 16th measurements, the meteorological data was not recorded on that day. As previously discussed in Chapter 4, the AERMOD code used meteorological data preprocessed by AERMET while FLEXPART simulations were completed by using the WRF-WPS coupled code. After coupling the ATMs to MCNP, the pulse tallies were calculated for each detector location along with the tally ratios.

The results for the November 2018 simulations are displayed in Tables 5-7 to 5-11 while

Tables 5-12 through 5-25 present the simulation data for all the January runs. The 10 minute averaged UFTR and UF in-house Gaussian model simulations for all four measurement days can be seen in Tables A-9 to A-19.

111

Table 5-6: November 7th, 2018 and January 16th-18th, 2019 wind information (averaged hourly) November 7th January 16th January 17th January 18th Wind Wind Wind Wind Wind Wind Wind Wind Weather Time Speed Orientation Speed Orientation Speed Orientation Speed Orientation Source (m s-1) (°) (m s-1) (°) (m s-1) (°) (m s-1) (°) UFTR 11:00 - - - - 1.286 68.1 0.974 158.5 Weather 12:00 - - - - 1.198 123.3 0.986 232.7 Station 13:00 1.488 177.1 - - 1.184 173.6 1.055 231.4 14:00 1.525 185.2 - - 1.157 212.2 1.312 181.7 15:00 1.453 171.5 - - 1.477 174.3 1.307 227.5 UF 11:00 - - 0.969 354.7 1.216 180.6 0.618 167.6 Weather 12:00 - - 1.184 1.6 0.915 146.7 0.726 249.2 Station 13:00 1.775 183.7 1.284 349.4 1.065 168.6 0.797 224.2 14:00 1.892 181.9 1.510 349.3 1.591 226.8 1.043 195.2 15:00 1.393 141.5 1.123 350.3 2.004 183.5 1.632 229.1 Airport 11:00 - - 2.38 317.0 1.79 116.0 1.74 137.0 Weather 12:00 - - 2.22 326.0 1.77 156.0 1.35 110.0 Station 13:00 2.88 170.0 2.36 335.0 1.99 171.0 2.36 137.0 14:00 2.45 185.0 2.08 307.0 1.98 139.0 2.59 201.0 15:00 1.71 125.0 2.28 315.0 2.93 192.0 2.39 206.0

112

Table 5-7. UFTR weather in-house Gaussian model November 7th, 2018 simulations Average Start Rhines Rhines 2 Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (F8 Tally) (F8 Tally) (F8 Tally) (F8 Tally) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 1.16E-08 ± 1.23E-08 ± 4.36E-08 ± 6.84E-09 ± 105.70% 377.20% 59.20% 28.10% 15.70% 55.80% 12:30 4.52E-11 4.90E-11 8.72E-11 1.64E-11 ± 0.59% ± 1.65% ± 0.27% ± 0.13% ± 0.05% ± 0.26% 1.20E-08 ± 9.66E-09 ± 6.40E-08 ± 9.77E-09 ± 80.40% 532.80% 81.30% 15.10% 15.30% 101.20% 13:00 3.48E-11 2.61E-11 1.15E-10 1.66E-11 ± 0.32% ± 1.82% ± 0.27% ± 0.05% ± 0.04% ± 0.32% 1.39E-08 ± 1.14E-08 ± 4.38E-08 ± 9.14E-09 ± 81.80% 314.20% 65.60% 26.00% 20.90% 79.90% 13:30 5.70E-11 3.31E-11 8.32E-11 1.37E-11 ± 0.41% ± 1.42% ± 0.29% ± 0.09% ± 0.05% ± 0.26% 1.37E-08 ± 9.71E-09 ± 4.67E-08 ± 7.79E-09 ± 70.90% 340.90% 56.90% 20.80% 16.70% 80.20% 14:00 3.15E-11 1.94E-11 8.87E-11 1.25E-11 ± 0.22% ± 1.02% ± 0.16% ± 0.06% ± 0.04% ± 0.21% 30 1.21E-08 ± 1.12E-08 ± 4.63E-08 ± 9.34E-09 ± 92.70% 383.20% 77.30% 24.20% 20.20% 83.20% 14:30 2.42E-11 2.13E-11 8.80E-11 1.49E-11 ± 0.26% ± 1.06% ± 0.20% ± 0.06% ± 0.05% ± 0.21% 1.35E-08 ± 1.18E-08 ± 4.36E-08 ± 9.34E-09 ± 87.10% 321.90% 68.90% 27.10% 21.40% 79.30% 15:00 6.48E-11 2.24E-11 7.85E-11 1.31E-11 ± 0.45% ± 1.66% ± 0.35% ± 0.07% ± 0.05% ± 0.19% 1.34E-08 ± 1.25E-08 ± 4.77E-08 ± 9.95E-09 ± 93.30% 356.00% 74.30% 26.20% 20.90% 79.70% 15:30 3.75E-11 2.13E-11 8.59E-11 2.99E-11 ± 0.31% ± 1.18% ± 0.30% ± 0.06% ± 0.07% ± 0.27% 1.53E-08 ± 1.44E-08 ± 4.44E-08 ± 1.00E-08 ± 93.90% 289.60% 65.20% 32.40% 22.50% 69.90% 16:00 3.37E-11 2.30E-11 7.55E-11 1.20E-11 ± 0.26% ± 0.81% ± 0.16% ± 0.08% ± 0.05% ± 0.14% 1.29E-08 ± 1.18E-08 ± 4.44E-08 ± 9.46E-09 ± 91.70% 344.80% 73.40% 26.60% 21.30% 87.20% 13:00 3.87E-11 2.24E-11 8.44E-11 1.51E-11 ± 0.32% ± 1.22% ± 0.25% ± 0.07% ± 0.05% ± 0.20% 1.15E-08 ± 1.09E-08 ± 4.22E-08 ± 9.48E-09 ± 94.00% 365.50% 82.20% 25.70% 22.50% 83.80% 60 14:00 3.68E-11 2.18E-11 8.02E-11 1.99E-11 ± 0.36% ± 1.37% ± 0.32% ± 0.07% ± 0.06% ± 0.25% 1.40E-08 ± 1.27E-08 ± 4.21E-08 ± 9.56E-09 ± 90.30% 299.80% 68.10% 30.10% 22.70% 79.90% 15:00 4.20E-11 2.41E-11 8.00E-11 1.43E-11 ± 0.32% ± 1.07% ± 0.23% ± 0.08% ± 0.05% ± 0.18%

Table 5-8. UF weather in-house Gaussian model November 7th, 2018 simulations Average Start Rhines Rhines 2 Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (F8 Tally) (F8 Tally) (F8 Tally) (F8 Tally) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 1.31E-08 ± 9.04E-09 ± 5.06E-08 ± 1.27E-09 ± 69.00% 386.30% 9.70% ± 17.90% 2.50% ± 14.00% 12:30 4.72E-11 1.99E-11 1.01E-10 2.16E-12 ± 0.29% ± 1.59% 0.04% ± 0.05% 0.01% ± 0.04% 2.13E-08 ± 1.29E-08 ± 4.53E-08 ± 1.97E-09 ± 60.60% 212.70% 9.20% ± 28.50% 4.30% ± 15.30% 13:00 6.60E-11 2.71E-11 8.61E-11 3.74E-12 ± 0.23% ± 0.77% 0.03% ± 0.08% 0.01% ± 0.04% 30 2.81E-08 ± 1.52E-08 ± 3.71E-08 ± 1.96E-09 ± 54.10% 132.00% 7.00% ± 41.00% 5.30% ± 12.90% 13:30 1.15E-10 2.89E-11 8.90E-11 2.94E-12 ± 0.24% ± 0.63% 0.03% ± 0.13% 0.01% ± 0.03% 1.74E-08 ± 1.14E-08 ± 5.20E-08 ± 1.83E-09 ± 65.50% 298.90% 10.50% 21.90% 3.50% ± 16.10% 14:00 5.57E-11 2.39E-11 9.88E-11 2.75E-12 ± 0.25% ± 1.11% ± 0.04% ± 0.06% 0.01% ± 0.04%

113

Table 5-8. Continued Average Start Rhines Rhines 2 Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (F8 Tally) (F8 Tally) (F8 Tally) (F8 Tally) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 1.93E-08 ± 1.18E-08 ± 4.39E-08 ± 1.62E-09 ± 61.10% 227.50% 8.40% ± 26.90% 3.70% ± 13.70% 14:30 6.18E-11 2.24E-11 8.34E-11 2.92E-12 ± 0.23% ± 0.85% 0.03% ± 0.07% 0.01% ± 0.04% 3.44E-08 ± 1.59E-08 ± 3.13E-08 ± 1.59E-09 ± 46.20% 91.00% 4.60% ± 50.80% 5.10% ± 10.00% 15:00 1.10E-10 4.13E-11 6.26E-11 2.39E-12 ± 0.19% ± 0.34% 0.02% ± 0.17% 0.01% ± 0.03% 2.40E-07 ± 3.48E-08 ± 1.57E-08 ± 4.40E-09 ± 14.50% 6.50% ± 1.80% ± 221.70% 28.00% 12.60% 15:30 7.44E-10 4.87E-11 2.83E-11 6.16E-12 ± 0.05% 0.02% 0.01% ± 0.51% ± 0.06% ± 0.03% 9.06E-07 ± 7.56E-08 ± 1.56E-08 ± 9.48E-09 ± 8.30% ± 1.70% ± 1.00% ± 484.60% 60.80% 12.50% 16:00 1.72E-09 9.83E-11 2.81E-11 1.14E-11 0.02% 0.03% 0.01% ± 1.08% ± 0.13% ± 0.02% 1.25E-08 ± 1.16E-08 ± 4.71E-08 ± 9.32E-09 ± 92.40% 376.10% 74.40% 24.60% 19.80% 80.50% 13:00 4.25E-11 2.20E-11 8.95E-11 2.98E-11 ± 0.36% ± 1.47% ± 0.35% ± 0.07% ± 0.07% ± 0.30% 1.26E-08 ± 1.16E-08 ± 4.52E-08 ± 8.91E-09 ± 92.40% 359.60% 70.90% 25.70% 19.70% 76.70% 60 14:00 3.91E-11 2.20E-11 8.59E-11 1.51E-11 ± 0.33% ± 1.30% ± 0.25% ± 0.07% ± 0.05% ± 0.20% 2.66E-08 ± 2.07E-08 ± 3.26E-08 ± 1.08E-08 ± 77.60% 122.60% 40.40% 63.30% 33.00% 52.10% 15:00 8.78E-11 3.31E-11 6.19E-11 1.73E-11 ± 0.29% ± 0.47% ± 0.15% ± 0.16% ± 0.08% ± 0.12%

Table 5-9. Airport weather in-house Gaussian model November 7th, 2018 simulations Average Start Rhines Rhines 2 Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (F8 Tally) (F8 Tally) (F8 Tally) (F8 Tally) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 9.95E-09 ± 9.04E-09 ± 3.21E-08 ± 3.19E-09 ± 90.80% 322.80% 32.00% 28.10% 9.90% ± 35.30% 13:00 3.59E-11 1.82E-11 6.46E-11 1.08E-11 ± 0.38% ± 1.33% ± 0.16% ± 0.08% 0.04% ± 0.14% 9.76E-09 ± 9.32E-09 ± 4.29E-08 ± 5.73E-09 ± 95.50% 439.60% 58.70% 21.70% 13.40% 61.50% 60 14:00 3.21E-11 1.88E-11 8.64E-11 1.03E-11 ± 0.37% ± 1.69% ± 0.22% ± 0.06% ± 0.04% ± 0.17% 4.72E-08 ± 2.72E-08 ± 2.68E-08 ± 1.14E-08 ± 57.60% 56.90% 24.20% 101.30% 42.50% 42.00% 15:00 1.65E-10 4.61E-11 5.40E-11 1.93E-11 ± 0.22% ± 0.23% ± 0.09% ± 0.27% ± 0.11% ± 0.10%

Table 5-10. FLEXPART November 7th, 2018 simulations Average Start Rhines Rhines 2 Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (min) Time (F8 Tally) (F8 Tally) (F8 Tally) (F8 Tally) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 1.04E-07 ± 1.84E-08 ± 8.61E-09 ± 2.71E-09 ± 17.70% 8.30% ± 2.60% ± 213.20% 31.50% 14.80% 13:00 7.38E-10 1.07E-10 5.94E-11 5.96E-11 ± 0.16% 0.08% 0.06% ± 1.93% ± 0.73% ± 0.34% 5.57E-08 ± 1.12E-08 ± 4.93E-09 ± 1.78E-09 ± 20.20% 8.80% ± 3.20% ± 228.00% 36.10% 15.80% 60 14:00 5.40E-10 5.04E-11 6.06E-11 4.17E-11 ± 0.22% 0.14% 0.08% ± 2.98% ± 0.95% ± 0.38% 2.70E-08 ± 5.23E-09 ± 4.03E-09 ± 1.13E-09 ± 19.30% 14.90% 4.20% ± 129.80% 28.00% 21.60% 15:00 6.21E-10 5.70E-11 1.41E-10 4.88E-11 ± 0.49% ± 0.63% 0.20% ± 4.77% ± 1.56% ± 0.96% 114

Table 5-11. AERMOD November 7th, 2018 simulations Average Start Rhines Rhines 2 Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (F8 Tally) (F8 Tally) (F8 Tally) (F8 Tally) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 4.17E-08 ± 3.54E-08 ± 4.44E-07 ± 3.97E-08 ± 84.90% 1063.0% 95.00% 8.00% ± 8.90% ± 112.00% 13:00 4.59E-11 4.96E-11 2.09E-09 3.18E-11 ± 0.15% ± 5.14% ± 0.13% 0.04% 0.04% ± 0.18% 6.10E-08 ± 4.67E-08 ± 3.07E-07 ± 3.83E-08 ± 76.50% 502.8% 62.70% 15.20% 12.50% 82.00% 60 14:00 6.10E-11 9.81E-11 8.69E-09 5.75E-11 ± 0.18% ± 14.3% ± 0.11% ± 0.43% ± 0.35% ± 0.21% 6.13E-08 ± 4.68E-08 ± 3.72E-07 ± 4.22E-08 ± 76.30% 606.6% 68.80% 12.60% 11.30% 90.20% 15:00 6.13E-11 4.68E-11 1.78E-08 2.08E-09 ± 0.11% ± 29.0% ± 3.40% ± 0.60% ± 0.78% ± 4.46%

Table 5-12. UF weather in-house Gaussian model January 16th, 2019 simulations Average Start Rhines Rhines 2 Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (F8 Tally) (F8 Tally) (F8 Tally) (F8 Tally) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 4.24E-08 ± 2.99E-08 ± 1.79E-07 ± 8.82E-07 ± 70.60% 421.60% 2080.1% 16.70% 493.4% 2947.2% 11:00 1.10E-10 3.29E-11 2.69E-10 1.91E-08 ± 0.20% ± 1.27% ± 45.5% ± 0.03% ± 10.7% ± 64.1% 3.37E-08 ± 2.22E-08 ± 2.92E-07 ± 2.97E-07 ± 66.00% 867.00% 881.50% 7.60% ± 101.70% 1334.7% 11:30 8.76E-11 2.66E-11 4.67E-10 5.94E-10 ± 0.19% ± 2.65% ± 2.89% 0.02% ± 0.26% ± 3.12% 1.02E-07 ± 1.34E-07 ± 7.11E-08 ± 6.84E-08 ± 131.80% 69.70% 67.10% 189.10% 96.20% 50.90% 12:00 2.04E-10 1.61E-10 9.95E-11 9.58E-11 ± 0.31% ± 0.17% ± 0.16% ± 0.35% ± 0.19% ± 0.09% 5.66E-08 ± 4.56E-08 ± 1.40E-07 ± 4.37E-07 ± 80.50% 246.60% 771.9% 32.70% 313.10% 958.7% 12:30 1.25E-10 5.02E-11 2.10E-10 6.38E-09 ± 0.20% ± 0.66% ± 11.4% ± 0.06% ± 4.58% ± 14.0% 2.79E-08 ± 1.74E-08 ± 5.05E-07 ± 1.17E-07 ± 62.30% 1811.7% 421.00% 3.40% ± 23.20% 676.10% 13:00 7.81E-11 3.48E-11 1.67E-09 1.87E-10 ± 0.21% ± 7.83% ± 1.35% 0.01% ± 0.08% ± 1.72% 4.11E-08 ± 2.88E-08 ± 1.72E-07 ± 8.99E-07 ± 70.10% 419.30% 2189.3% 16.70% 522.2% 3121.7% 30 13:30 1.03E-10 3.46E-11 3.27E-10 2.20E-08 ± 0.19% ± 1.31% ± 53.9% ± 0.04% ± 12.8% ± 76.6% 3.60E-08 ± 2.39E-08 ± 2.88E-07 ± 4.73E-07 ± 66.40% 797.70% 1311.0% 8.30% ± 164.30% 1974.8% 14:00 9.36E-11 3.11E-11 5.18E-10 8.47E-09 ± 0.19% ± 2.53% ± 23.8% 0.02% ± 2.95% ± 35.5% 2.46E-08 ± 1.48E-08 ± 7.04E-07 ± 6.23E-08 ± 60.10% 2858.0% 252.80% 2.10% ± 8.80% ± 420.60% 14:30 7.38E-11 2.07E-11 8.45E-09 8.10E-11 ± 0.20% ± 35.4% ± 0.83% 0.03% 0.11% ± 0.80% 7.02E-08 ± 6.59E-08 ± 1.04E-07 ± 2.16E-07 ± 93.90% 147.40% 307.10% 63.70% 208.30% 327.10% 15:00 1.47E-10 5.27E-10 1.56E-10 2.53E-09 ± 0.78% ± 0.38% ± 3.66% ± 0.52% ± 2.45% ± 4.65% 3.30E-08 ± 2.18E-08 ± 2.43E-07 ± 4.22E-07 ± 66.10% 735.90% 1277.9% 9.00% ± 173.60% 1934.2% 15:30 9.57E-11 2.83E-11 4.13E-10 1.31E-09 ± 0.21% ± 2.48% ± 5.43% 0.02% ± 0.61% ± 6.51% 7.57E-09 ± 8.14E-09 ± 4.54E-07 ± 1.13E-08 ± 107.40% 5991.5% 148.80% 1.80% ± 2.50% ± 138.50% 16:00 1.89E-11 3.79E-11 7.26E-10 8.36E-11 ± 0.57% ± 17.8% ± 1.17% 0.01% 0.02% ± 1.21% 5.05E-08 ± 3.71E-08 ± 1.83E-07 ± 7.43E-07 ± 73.40% 362.00% 1470.1% 20.30% 406.10% 2002.6% 60 11:00 1.16E-10 4.08E-11 4.21E-10 7.88E-09 ± 0.19% ± 1.18% ± 15.9% ± 0.05% ± 4.40% ± 21.3%

115

Table 5-12. Continued Average Start Rhines Rhines 2 Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (F8 Tally) (F8 Tally) (F8 Tally) (F8 Tally) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 5.69E-08 ± 4.51E-08 ± 1.40E-07 ± 5.21E-07 ± 79.20% 246.90% 915.70% 32.10% 370.90% 1155.6% 12:00 1.25E-10 4.51E-11 1.96E-10 5.94E-09 ± 0.19% ± 0.64% ± 10.6% ± 0.06% ± 4.27% ± 13.2% 3.91E-08 ± 2.67E-08 ± 2.59E-07 ± 6.32E-07 ± 68.20% 662.4% 1616.6% 10.30% 244.00% 2369.4% 13:00 9.78E-11 3.20E-11 7.49E-09 1.46E-08 ± 0.19% ± 19.2% ± 37.6% ± 0.30% ± 9.03% ± 54.8% 60 3.94E-08 ± 2.72E-08 ± 2.02E-07 ± 9.45E-07 ± 69.00% 513.40% 2397.7% 13.40% 467.0% 3476.5% 14:00 9.85E-11 3.26E-11 3.23E-10 2.74E-08 ± 0.19% ± 1.52% ± 69.8% ± 0.03% ± 13.6% ± 100% 4.43E-08 ± 3.10E-08 ± 1.05E-06 ± 9.13E-07 ± 69.90% 2370.6% 2058.9% 2.90% ± 86.90% 2946.5% 15:00 1.02E-10 3.41E-11 4.10E-08 2.90E-08 ± 0.18% ± 92.6% ± 65.7% 0.12% ± 4.38% ± 93.7%

Table 5-13. Airport weather in-house Gaussian model January 16th, 2019 simulations Average Start Rhines Rhines 2 Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (F8 Tally) (F8 Tally) (F8 Tally) (F8 Tally) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 4.79E-09 ± 5.12E-09 ± 1.99E-07 ± 5.21E-08 ± 106.80% 4156.6% 1087.0% 2.60% ± 26.20% 1017.5% 11:00 1.20E-11 1.54E-11 4.18E-10 9.90E-11 ± 0.42% ± 13.6% ± 3.42% 0.01% ± 0.07% ± 3.61% 6.23E-09 ± 6.57E-09 ± 1.70E-07 ± 7.43E-08 ± 105.40% 2724.5% 1192.1% 3.90% ± 43.80% 1131.5% 12:00 1.43E-11 1.38E-11 3.57E-10 1.49E-10 ± 0.33% ± 8.50% ± 3.64% 0.01% ± 0.13% ± 3.28% 8.79E-09 ± 9.69E-09 ± 1.31E-07 ± 1.71E-07 ± 110.30% 1486.6% 1950.5% 7.40% ± 131.20% 1768.8% 60 13:00 1.67E-11 1.84E-11 2.49E-10 3.93E-10 ± 0.30% ± 4.00% ± 5.80% 0.02% ± 0.39% ± 5.26% 5.54E-09 ± 4.02E-09 ± 3.73E-07 ± 3.19E-08 ± 72.50% 6725.1% 575.20% 1.10% ± 8.60% ± 793.20% 14:00 1.39E-11 1.21E-11 9.70E-10 6.06E-11 ± 0.28% ± 24.3% ± 1.81% 0.01% 0.03% ± 2.82% 1.30E-08 ± 1.01E-08 ± 9.67E-08 ± 4.91E-09 ± 77.20% 742.00% 37.60% 10.40% 5.10% ± 48.70% 15:00 2.21E-11 2.12E-11 1.84E-10 1.18E-11 ± 0.21% ± 1.90% ± 0.11% ± 0.03% 0.02% ± 0.16%

Table 5-14. FLEXPART January 16th, 2019 simulations Average Start Rhines Rhines 2 Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (F8 Tally) (F8 Tally) (F8 Tally) (F8 Tally) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 8.40E-10 ± 2.77E-09 ± 7.78E-09 ± 3.14E-09 ± 329.90% 925.9% 373.70% 35.60% 40.40% 113.30% 11:00 3.78E-12 3.13E-11 1.71E-10 3.99E-11 ± 4.01% ± 20.8% ± 5.04% ± 0.88% ± 1.03% ± 1.93% 2.41E-09 ± 4.30E-09 ± 6.08E-09 ± 3.49E-09 ± 178.60% 252.60% 144.90% 70.70% 57.40% 81.20% 60 12:00 1.21E-11 4.60E-11 3.77E-11 5.76E-11 ± 2.11% ± 2.01% ± 2.50% ± 0.87% ± 1.01% ± 1.60% 4.46E-09 ± 6.19E-09 ± 3.39E-09 ± 5.75E-09 ± 138.80% 76.00% 128.80% 182.70% 169.60% 92.80% 13:00 4.82E-11 1.48E-10 5.90E-11 1.66E-10 ± 3.64% ± 1.56% ± 3.98% ± 5.40% ± 5.72% ± 3.48%

116

Table 5-14. Continued Average Start Rhines Rhines 2 Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (F8 Tally) (F8 Tally) (F8 Tally) (F8 Tally) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 2.00E-09 ± 4.15E-09 ± 5.87E-09 ± 6.64E-09 ± 207.80% 294.10% 332.80% 70.60% 113.20% 160.20% 14:00 1.38E-11 8.01E-11 4.81E-11 1.66E-10 ± 4.25% ± 3.15% ± 8.61% ± 1.48% ± 2.98% ± 5.05% 60 8.38E-10 ± 1.90E-09 ± 4.15E-08 ± 3.81E-09 ± 226.80% 4947.1% 454.40% 4.60% ± 9.20% ± 200.40% 15:00 3.02E-12 1.14E-11 1.33E-10 5.30E-11 ± 1.59% ± 23.9% ± 6.53% 0.03% 0.13% ± 3.04%

Table 5-15. AERMOD January 16th, 2019 simulations Average Start Rhines Rhines 2 Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (F8 Tally) (F8 Tally) (F8 Tally) (F8 Tally) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 3.29E-08 ± 2.83E-08 ± 3.58E-07 ± 9.20E-08 ± 85.80% 1085.8% 279.40% 7.90% ± 25.70% 325.40% 11:00 4.11E-10 2.69E-10 7.88E-10 1.10E-10 ± 1.35% ± 13.8% ± 3.51% 0.08% ± 0.06% ± 3.11% 3.97E-08 ± 3.38E-08 ± 2.76E-07 ± 9.97E-08 ± 85.30% 695.0% 251.40% 12.30% 36.20% 294.90% 12:00 6.39E-10 6.39E-10 1.46E-09 1.69E-10 ± 2.11% ± 11.8% ± 4.07% ± 0.24% ± 0.20% ± 5.60% 5.59E-08 ± 4.85E-08 ± 2.49E-07 ± 9.32E-08 ± 86.60% 444.4% 166.60% 19.50% 37.50% 192.30% 60 13:00 2.77E-09 1.38E-09 1.97E-09 1.96E-10 ± 4.95% ± 22.3% ± 8.26% ± 0.57% ± 0.31% ± 5.47% 4.81E-08 ± 3.43E-08 ± 6.98E-07 ± 6.20E-08 ± 71.20% 1450.0% 128.90% 4.90% ± 8.90% ± 180.90% 14:00 1.97E-09 7.51E-10 6.00E-09 1.30E-10 ± 3.31% ± 60.7% ± 5.29% 0.12% 0.08% ± 3.98% 4.50E-08 ± 3.69E-08 ± 4.88E-07 ± 7.85E-08 ± 81.90% 1083.4% 174.20% 7.60% ± 16.10% 212.70% 15:00 1.56E-09 8.34E-10 2.29E-09 1.49E-10 ± 3.40% ± 37.9% ± 6.06% 0.17% ± 0.08% ± 4.82%

Table 5-16. UFTR weather in-house Gaussian model January 17th, 2019 simulations Average Start Rhines Rhines 2 Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (F8 Tally) (F8 Tally) (F8 Tally) (F8 Tally) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 6.36E-07 ± 6.30E-07 ± 3.71E-08 ± 1.43E-08 ± 99.00% 5.80% ± 2.20% ± 1696.6% 38.60% 2.30% ± 10:30 2.04E-09 1.38E-08 1.77E-09 2.29E-11 ± 2.19% 0.28% 0.01% ± 88.9% ± 1.84% 0.05% 2.54E-06 ± 1.99E-07 ± 2.49E-08 ± 1.12E-08 ± 7.80% ± 1.00% ± 0.40% ± 800.40% 45.00% 5.60% ± 11:00 5.31E-08 4.38E-10 4.48E-11 6.38E-11 0.16% 0.02% 0.01% ± 2.27% ± 0.27% 0.03% 3.39E-07 ± 7.00E-07 ± 5.06E-08 ± 2.26E-08 ± 206.60% 14.90% 6.70% ± 1384.4% 44.70% 3.20% ± 30 11:30 1.02E-10 8.54E-09 2.13E-09 9.22E-10 ± 2.52% ± 0.63% 0.27% ± 60.5% ± 2.62% 0.14% 2.79E-07 ± 3.11E-08 ± 2.95E-08 ± 6.40E-09 ± 11.20% 10.60% 2.30% ± 105.60% 21.70% 20.60% 12:00 4.46E-10 5.29E-11 7.08E-11 1.09E-11 ± 0.03% ± 0.03% 0.01% ± 0.31% ± 0.06% ± 0.05% 2.88E-07 ± 3.36E-08 ± 3.07E-08 ± 6.60E-09 ± 11.60% 10.60% 2.30% ± 109.60% 21.50% 19.60% 12:30 4.61E-10 5.04E-11 5.22E-11 1.12E-11 ± 0.03% ± 0.02% 0.01% ± 0.25% ± 0.05% ± 0.04%

117

Table 5-16. Continued Average Start Rhines Rhines 2 Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (F8 Tally) (F8 Tally) (F8 Tally) (F8 Tally) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 4.48E-08 ± 1.08E-08 ± 5.95E-08 ± 5.38E-09 ± 24.20% 132.80% 12.00% 18.20% 9.00% ± 49.70% 13:00 9.41E-11 2.38E-11 1.01E-10 1.29E-11 ± 0.07% ± 0.36% ± 0.04% ± 0.05% 0.03% ± 0.16% 1.04E-07 ± 1.72E-08 ± 3.73E-08 ± 5.35E-09 ± 16.60% 36.00% 5.20% ± 46.10% 14.40% 31.20% 13:30 1.77E-10 2.92E-11 6.71E-11 1.12E-11 ± 0.04% ± 0.09% 0.01% ± 0.11% ± 0.04% ± 0.08% 3.09E-08 ± 9.46E-09 ± 9.75E-08 ± 6.47E-09 ± 30.60% 315.30% 20.90% 9.70% ± 6.60% ± 68.40% 14:00 7.11E-11 1.61E-11 1.66E-10 1.16E-11 ± 0.09% ± 0.90% ± 0.06% 0.02% 0.02% ± 0.17% 3.92E-08 ± 1.01E-08 ± 7.38E-08 ± 5.50E-09 ± 25.90% 188.20% 14.00% 13.70% 7.50% ± 54.30% 30 14:30 8.62E-11 1.92E-11 3.62E-09 9.90E-12 ± 0.07% ± 9.25% ± 0.04% ± 0.67% 0.37% ± 0.14% 5.76E-08 ± 1.18E-08 ± 4.48E-08 ± 4.87E-09 ± 20.40% 77.70% 8.50% ± 26.30% 10.90% 41.40% 15:00 1.32E-10 2.24E-11 8.51E-11 9.25E-12 ± 0.06% ± 0.23% 0.03% ± 0.07% ± 0.03% ± 0.11% 6.62E-08 ± 1.28E-08 ± 4.29E-08 ± 5.05E-09 ± 19.40% 64.80% 7.60% ± 29.90% 11.80% 39.30% 15:30 1.26E-10 2.30E-11 8.15E-11 3.48E-11 ± 0.05% ± 0.17% 0.05% ± 0.08% ± 0.08% ± 0.28% 4.04E-08 ± 9.71E-09 ± 5.53E-08 ± 4.97E-09 ± 24.00% 136.90% 12.30% 17.60% 9.00% ± 51.10% 16:00 8.48E-11 1.94E-11 9.95E-11 8.95E-12 ± 0.07% ± 0.38% ± 0.03% ± 0.05% 0.02% ± 0.14% 8.17E-07 ± 4.31E-07 ± 3.02E-08 ± 1.38E-08 ± 52.80% 3.70% ± 1.70% ± 1426.4% 45.70% 3.20% ± 11:00 2.21E-09 3.40E-09 5.13E-11 2.21E-11 ± 0.44% 0.01% 0.01% ± 11.5% ± 0.11% 0.03% 2.51E-07 ± 3.03E-08 ± 2.88E-08 ± 6.23E-09 ± 12.10% 11.50% 2.50% ± 105.00% 21.60% 20.60% 12:00 3.77E-10 4.85E-11 5.47E-11 1.06E-11 ± 0.03% ± 0.03% 0.01% ± 0.26% ± 0.06% ± 0.05% 6.59E-08 ± 1.32E-08 ± 4.52E-08 ± 5.16E-09 ± 20.00% 68.60% 7.80% ± 29.10% 11.40% 39.20% 60 13:00 3.43E-10 2.24E-11 7.68E-11 9.80E-12 ± 0.11% ± 0.38% 0.04% ± 0.07% ± 0.03% ± 0.10% 3.48E-08 ± 9.70E-09 ± 7.84E-08 ± 5.88E-09 ± 27.90% 225.50% 16.90% 12.40% 7.50% ± 60.60% 14:00 7.66E-11 1.75E-11 1.57E-10 1.06E-11 ± 0.08% ± 0.67% ± 0.05% ± 0.03% 0.02% ± 0.15% 6.20E-08 ± 1.23E-08 ± 4.34E-08 ± 4.93E-09 ± 19.80% 70.10% 7.90% ± 28.20% 11.30% 40.20% 15:00 1.24E-10 2.21E-11 8.25E-11 1.04E-11 ± 0.05% ± 0.19% 0.02% ± 0.07% ± 0.03% ± 0.11%

Table 5-17. UF weather in-house Gaussian model January 17th, 2019 simulations Average Start Rhines Rhines 2 Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (F8 Tally) (F8 Tally) (F8 Tally) (F8 Tally) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 1.97E-08 ± 1.23E-08 ± 4.78E-08 ± 1.97E-09 ± 62.60% 242.7% 10.00% 25.80% 4.10% ± 16.00% 10:30 6.93E-11 2.96E-10 2.50E-09 3.47E-12 ± 1.52% ± 12.7% ± 0.04% ± 1.48% 0.22% ± 0.39% 3.11E-08 ± 1.60E-08 ± 3.63E-08 ± 2.24E-09 ± 51.50% 116.70% 7.20% ± 44.10% 6.20% ± 14.00% 30 11:00 7.15E-10 3.87E-11 7.19E-11 1.40E-11 ± 1.19% ± 2.69% 0.17% ± 0.14% 0.04% ± 0.09% 1.99E-08 ± 1.25E-08 ± 6.63E-08 ± 6.02E-09 ± 62.60% 332.5% 30.20% 18.80% 9.10% ± 48.30% 11:30 6.57E-12 1.68E-10 3.06E-09 2.70E-10 ± 0.84% ± 15.4% ± 1.36% ± 0.91% 0.58% ± 2.26%

118

Table 5-17. Continued Average Start Rhines Rhines 2 Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (F8 Tally) (F8 Tally) (F8 Tally) (F8 Tally) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 3.13E-08 ± 1.57E-08 ± 4.47E-08 ± 5.98E-09 ± 50.20% 142.90% 19.10% 35.20% 13.40% 38.00% 12:00 5.51E-11 2.94E-11 1.18E-10 1.12E-11 ± 0.13% ± 0.45% ± 0.05% ± 0.11% ± 0.04% ± 0.10% 4.72E-07 ± 5.06E-08 ± 2.54E-08 ± 7.56E-09 ± 10.70% 5.40% ± 1.60% ± 198.70% 29.70% 14.90% 12:30 8.31E-10 8.35E-11 4.75E-11 1.41E-11 ± 0.03% 0.01% 0.01% ± 0.50% ± 0.08% ± 0.04% 2.16E-08 ± 1.30E-08 ± 5.66E-08 ± 4.46E-09 ± 60.30% 261.70% 20.60% 23.00% 7.90% ± 34.20% 13:00 4.99E-11 3.15E-11 1.06E-10 1.18E-11 ± 0.20% ± 0.78% ± 0.07% ± 0.07% 0.03% ± 0.12% 7.08E-08 ± 2.24E-08 ± 2.68E-08 ± 4.59E-09 ± 31.60% 37.90% 6.50% ± 83.50% 17.10% 20.50% 13:30 1.32E-10 4.19E-11 5.31E-11 1.06E-11 ± 0.08% ± 0.10% 0.02% ± 0.23% ± 0.05% ± 0.06% 7.59E-09 ± 8.71E-09 ± 2.41E-07 ± 6.05E-09 ± 114.80% 3179.8% 79.70% 3.60% ± 2.50% ± 69.40% 30 14:00 1.92E-11 1.63E-11 4.51E-10 1.20E-11 ± 0.36% ± 9.99% ± 0.26% 0.01% 0.01% ± 0.19% 8.65E-09 ± 8.55E-09 ± 1.18E-07 ± 2.59E-09 ± 98.90% 1362.0% 29.90% 7.30% ± 2.20% ± 30.30% 14:30 2.09E-11 1.79E-11 5.85E-09 5.13E-12 ± 0.32% ± 67.7% ± 0.09% 0.36% 0.11% ± 0.09% 1.55E-08 ± 1.01E-08 ± 4.16E-08 ± 1.17E-09 ± 65.10% 267.70% 7.50% ± 24.30% 2.80% ± 11.60% 15:00 3.92E-11 2.11E-11 8.69E-11 2.45E-12 ± 0.21% ± 0.88% 0.02% ± 0.07% 0.01% ± 0.03% 1.57E-08 ± 1.03E-08 ± 5.52E-08 ± 1.84E-09 ± 65.80% 352.30% 11.80% 18.70% 3.30% ± 17.90% 15:30 3.28E-11 2.04E-11 1.15E-10 1.40E-11 ± 0.19% ± 1.04% ± 0.09% ± 0.05% 0.03% ± 0.14% 6.38E-09 ± 6.19E-09 ± 9.87E-08 ± 1.53E-09 ± 97.10% 1547.5% 24.00% 6.30% ± 1.50% ± 24.70% 16:00 1.47E-11 1.36E-11 1.95E-10 3.03E-12 ± 0.31% ± 4.71% ± 0.07% 0.02% 0.01% ± 0.07% 2.45E-08 ± 1.40E-08 ± 4.77E-08 ± 3.30E-09 ± 57.20% 194.50% 13.50% 29.40% 6.90% ± 23.50% 11:00 7.28E-11 1.22E-10 8.92E-11 5.81E-12 ± 0.52% ± 0.68% ± 0.05% ± 0.26% 0.02% ± 0.21% 8.81E-08 ± 2.46E-08 ± 2.48E-08 ± 6.21E-09 ± 27.90% 28.10% 7.00% ± 99.30% 25.00% 25.20% 12:00 1.45E-10 4.33E-11 5.18E-11 1.16E-11 ± 0.07% ± 0.07% 0.02% ± 0.27% ± 0.07% ± 0.06% 7.31E-08 ± 1.42E-08 ± 4.33E-08 ± 9.96E-09 ± 19.40% 59.20% 13.60% 32.70% 23.00% 70.30% 60 13:00 4.18E-10 2.66E-11 8.10E-11 2.08E-11 ± 0.12% ± 0.36% ± 0.08% ± 0.09% ± 0.06% ± 0.20% 2.72E-08 ± 8.48E-09 ± 9.64E-08 ± 1.18E-08 ± 31.20% 354.30% 43.40% 8.80% ± 12.30% 139.30% 14:00 6.58E-11 1.68E-11 2.12E-10 2.34E-11 ± 0.10% ± 1.16% ± 0.14% 0.03% ± 0.04% ± 0.39% 4.62E-08 ± 1.02E-08 ± 4.45E-08 ± 8.24E-09 ± 22.00% 96.30% 17.80% 22.80% 18.50% 81.10% 15:00 1.02E-10 2.02E-11 9.30E-11 1.90E-11 ± 0.07% ± 0.29% ± 0.06% ± 0.07% ± 0.06% ± 0.25%

Table 5-18. Airport weather in-house Gaussian model January 17th, 2019 simulations Average Start Rhines Rhines 2 Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (F8 Tally) (F8 Tally) (F8 Tally) (F8 Tally) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 5.67E-07 ± 5.76E-08 ± 1.54E-08 ± 8.59E-09 ± 10.20% 2.70% ± 1.50% ± 372.90% 55.60% 14.90% 60 11:00 7.03E-09 1.04E-10 3.23E-11 1.80E-11 ± 0.13% 0.03% 0.02% ± 1.03% ± 0.17% ± 0.04%

119

Table 5-18. Continued Average Start Rhines Rhines 2 Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (F8 Tally) (F8 Tally) (F8 Tally) (F8 Tally) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 6.24E-08 ± 2.17E-08 ± 3.17E-08 ± 6.80E-09 ± 34.70% 50.80% 10.90% 68.30% 21.40% 31.40% 12:00 1.06E-10 3.91E-11 6.02E-11 1.43E-11 ± 0.09% ± 0.13% ± 0.03% ± 0.18% ± 0.06% ± 0.09% 6.00E-08 ± 1.16E-08 ± 3.82E-08 ± 8.15E-09 ± 19.30% 63.60% 13.60% 30.30% 21.30% 70.40% 13:00 1.02E-10 2.09E-11 6.88E-11 1.79E-11 ± 0.05% ± 0.16% ± 0.04% ± 0.08% ± 0.06% ± 0.20% 60 1.50E-07 ± 3.19E-08 ± 2.15E-08 ± 6.81E-09 ± 21.30% 14.30% 4.50% ± 148.60% 31.70% 21.30% 14:00 3.60E-10 5.74E-11 3.87E-11 1.50E-11 ± 0.06% ± 0.04% 0.01% ± 0.38% ± 0.09% ± 0.06% 2.80E-08 ± 7.02E-09 ± 4.53E-08 ± 3.70E-09 ± 25.10% 162.10% 13.20% 15.50% 8.20% ± 52.70% 15:00 5.04E-11 3.23E-11 8.15E-11 9.99E-12 ± 0.12% ± 0.41% ± 0.04% ± 0.08% 0.03% ± 0.28%

Table 5-19. FLEXPART January 17th, 2019 simulations Average Start Rhines Rhines 2 Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (F8 Tally) (F8 Tally) (F8 Tally) (F8 Tally) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 7.29E-08 ± 4.14E-07 ± 1.54E-08 ± 1.01E-08 ± 567.4% 21.20% 13.90% 2681.4% 65.70% 2.50% ± 11:00 7.07E-10 1.24E-08 3.37E-10 1.48E-10 ± 17.9% ± 0.51% ± 0.24% ± 99.6% ± 1.73% 0.08% 3.25E-08 ± 1.62E-07 ± 1.89E-08 ± 1.50E-08 ± 500.0% 58.10% 46.30% 860.6% 79.70% 9.30% ± 12:00 1.46E-10 7.89E-09 7.73E-10 3.33E-10 ± 24.4% ± 2.39% ± 1.05% ± 54.5 % ± 3.69% 0.50% 60 2.12E-08 ± 7.77E-08 ± 1.56E-08 ± 2.54E-08 ± 367.00% 73.70% 120.00% 498.20% 162.90% 32.70% 13:00 8.06E-11 7.15E-10 1.08E-10 1.26E-09 ± 3.65% ± 0.58% ± 5.96% ± 5.73% ± 8.15% ± 1.65% 2.31E-08 ± 2.35E-07 ± 1.13E-08 ± 1.89E-08 ± 1016.4% 48.80% 81.90% 2083.6% 167.80% 8.10% ± 14:00 7.85E-11 1.04E-08 7.23E-11 3.89E-10 ± 45.0 % ± 0.35% ± 1.71% ± 92.7% ± 3.61% 0.39% 1.49E-07 ± 1.62E-07 ± 1.18E-08 ± 1.23E-08 ± 108.80% 7.90% ± 8.30% ± 1368.9% 103.90% 7.60% ± 15:00 5.08E-09 3.52E-09 1.01E-10 2.05E-10 ± 4.39% 0.28% 0.31% ± 32.1% ± 1.96% 0.21%

Table 5-20. AERMOD January 17th, 2019 simulations Average Start Rhines Rhines 2 Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (F8 Tally) (F8 Tally) (F8 Tally) (F8 Tally) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 8.06E-07 ± 8.43E-08 ± 1.18E-07 ± 1.53E-08 ± 10.50% 14.70% 1.90% ± 71.20% 12.90% 18.20% 11:00 3.94E-08 6.07E-10 1.18E-09 3.37E-11 ± 0.52% ± 0.73% 0.09% ± 0.88% ± 0.13% ± 0.14% 2.28E-07 ± 7.16E-08 ± 2.08E-07 ± 1.86E-08 ± 31.40% 91.30% 8.20% ± 34.40% 8.90% ± 26.00% 60 12:00 1.11E-08 5.51E-10 1.71E-09 4.65E-11 ± 1.54% ± 4.49% 0.40% ± 0.39% 0.08% ± 0.21% 2.21E-07 ± 7.40E-08 ± 2.46E-07 ± 1.89E-08 ± 33.40% 111.40% 8.50% ± 30.00% 7.70% ± 25.50% 13:00 1.05E-08 8.51E-10 1.77E-09 4.73E-11 ± 1.64% ± 5.37% 0.41% ± 0.41% 0.06% ± 0.30%

120

Table 5-20. Continued Average Start Rhines Rhines 2 Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (F8 Tally) (F8 Tally) (F8 Tally) (F8 Tally) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 3.13E-07 ± 8.31E-08 ± 2.07E-07 ± 1.90E-08 ± 26.50% 66.20% 6.10% ± 40.10% 9.20% ± 22.80% 14:00 1.28E-08 6.32E-10 2.26E-09 4.75E-11 ± 1.11% ± 2.81% 0.25% ± 0.53% 0.10% ± 0.18% 60 1.23E-07 ± 5.15E-08 ± 2.54E-07 ± 1.21E-08 ± 41.80% 205.9% 9.80% ± 20.30% 4.80% ± 23.50% 15:00 6.13E-09 5.67E-10 1.93E-09 3.75E-11 ± 2.14% ± 10.4% 0.49% ± 0.27% 0.04% ± 0.27%

Table 5-21 UFTR weather in-house Gaussian model January 18th, 2019 simulations Average Start Rhines Rhines 2 Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (F8 Tally) (F8 Tally) (F8 Tally) (F8 Tally) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 3.73E-08 ± 2.46E-08 ± 2.88E-07 ± 3.31E-07 ± 65.80% 771.00% 887.80% 8.50% ± 115.10% 1349.5% 10:30 9.70E-11 2.95E-11 4.61E-10 9.60E-10 ± 0.19% ± 2.36% ± 3.46% 0.02% ± 0.38% ± 4.22% 9.46E-08 ± 1.72E-08 ± 4.12E-08 ± 5.51E-09 ± 18.20% 43.50% 5.80% ± 41.90% 13.40% 32.00% 11:00 1.51E-10 4.64E-11 7.00E-11 9.92E-12 ± 0.06% ± 0.10% 0.01% ± 0.13% ± 0.03% ± 0.10% 1.02E-07 ± 1.74E-08 ± 3.86E-08 ± 5.42E-09 ± 17.10% 38.00% 5.30% ± 45.10% 14.00% 31.10% 11:30 1.63E-10 3.65E-11 6.95E-11 1.03E-11 ± 0.05% ± 0.09% 0.01% ± 0.12% ± 0.04% ± 0.09% 2.59E-08 ± 9.16E-09 ± 1.43E-07 ± 8.05E-09 ± 35.30% 553.00% 31.10% 6.40% ± 5.60% ± 87.90% 12:00 6.48E-11 1.56E-11 2.29E-10 1.61E-12 ± 0.11% ± 1.64% ± 0.08% 0.01% 0.01% ± 0.15% 2.87E-08 ± 9.14E-09 ± 1.10E-07 ± 6.80E-09 ± 31.80% 384.10% 23.70% 8.30% ± 6.20% ± 74.40% 12:30 6.89E-11 1.65E-11 1.87E-10 1.77E-11 ± 0.10% ± 1.13% ± 0.08% 0.02% 0.02% ± 0.24% 2.97E-08 ± 9.20E-09 ± 9.93E-08 ± 6.42E-09 ± 31.00% 334.90% 21.60% 9.30% ± 6.50% ± 69.80% 13:00 7.13E-11 1.66E-11 1.69E-10 1.16E-11 ± 0.09% ± 0.98% ± 0.06% 0.02% 0.02% ± 0.18% 30 2.71E-08 ± 9.30E-09 ± 1.36E-07 ± 7.76E-09 ± 34.40% 502.00% 28.70% 6.80% ± 5.70% ± 83.50% 13:30 6.50E-11 1.77E-11 2.31E-10 1.24E-11 ± 0.11% ± 1.48% ± 0.08% 0.02% 0.01% ± 0.21% 4.56E-08 ± 1.09E-08 ± 5.86E-08 ± 5.35E-09 ± 24.00% 128.50% 11.70% 18.60% 9.10% ± 49.00% 14:00 9.58E-11 2.40E-11 9.96E-11 1.02E-11 ± 0.07% ± 0.35% ± 0.03% ± 0.05% 0.02% ± 0.14% 6.56E-08 ± 1.27E-08 ± 4.23E-08 ± 4.93E-09 ± 19.30% 64.50% 7.50% ± 30.00% 11.70% 38.90% 14:30 1.25E-10 2.67E-11 8.04E-11 9.37E-12 ± 0.05% ± 0.17% 0.02% ± 0.09% ± 0.03% ± 0.11% 2.46E-08 ± 8.67E-09 ± 1.49E-07 ± 7.69E-09 ± 35.20% 605.90% 31.20% 5.80% ± 5.20% ± 88.70% 15:00 6.64E-11 1.65E-11 2.53E-10 1.38E-11 ± 0.12% ± 1.93% ± 0.10% 0.01% 0.01% ± 0.23% 3.33E-08 ± 9.29E-09 ± 7.56E-08 ± 5.70E-09 ± 27.90% 227.40% 17.10% 12.30% 7.50% ± 61.30% 15:30 7.33E-11 2.14E-11 1.74E-10 9.69E-12 ± 0.09% ± 0.72% ± 0.05% ± 0.04% 0.02% ± 0.18% 3.12E-08 ± 8.96E-09 ± 8.02E-08 ± 5.79E-09 ± 28.70% 256.80% 18.50% 11.20% 7.20% ± 64.60% 16:00 7.49E-11 1.61E-11 1.36E-10 1.04E-11 ± 0.09% ± 0.76% ± 0.06% ± 0.03% 0.02% ± 0.16% 9.28E-08 ± 1.67E-08 ± 4.41E-08 ± 5.40E-09 ± 18.00% 47.50% 5.80% ± 37.80% 12.20% 32.40% 60 11:00 1.58E-10 2.67E-11 1.94E-09 1.13E-11 ± 0.04% ± 2.10% 0.02% ± 1.67% ± 0.54% ± 0.09%

121

Table 5-21. Continued Average Start Rhines Rhines 2 Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (F8 Tally) (F8 Tally) (F8 Tally) (F8 Tally) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 2.81E-08 ± 9.17E-09 ± 1.26E-07 ± 7.11E-09 ± 32.70% 449.7% 25.30% 7.30% ± 5.60% ± 77.60% 12:00 6.74E-11 1.74E-11 3.99E-09 1.28E-11 ± 0.10% ± 14.3% ± 0.08% 0.23% 0.18% ± 0.20% 2.83E-08 ± 9.14E-09 ± 1.17E-07 ± 6.97E-09 ± 32.30% 414.20% 24.60% 7.80% ± 5.90% ± 76.20% 13:00 6.79E-11 1.65E-11 2.00E-09 1.18E-11 ± 0.10% ± 7.14% ± 0.07% 0.13% 0.10% ± 0.19% 60 5.50E-08 ± 1.18E-08 ± 5.30E-08 ± 5.10E-09 ± 21.40% 96.40% 9.30% ± 22.20% 9.60% ± 43.30% 14:00 1.16E-10 2.12E-11 2.35E-09 1.02E-11 ± 0.06% ± 4.27% 0.03% ± 0.99% 0.43% ± 0.12% 2.69E-08 ± 8.61E-09 ± 1.18E-07 ± 6.61E-09 ± 31.90% 439.3% 24.50% 7.30% ± 5.60% ± 76.80% 15:00 6.46E-11 1.55E-11 4.46E-09 1.19E-11 ± 0.10% ± 16.6% ± 0.07% 0.28% 0.21% ± 0.20%

Table 5-22. UF Weather in-house Gaussian model January 18th, 2019 simulations Average Start Rhines Rhines 2 Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (F8 Tally) (F8 Tally) (F8 Tally) (F8 Tally) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 2.77E-09 ± 1.47E-09 ± 4.30E-09 ± 9.61E-10 ± 52.90% 155.20% 34.70% 34.10% 22.30% 65.50% 10:30 7.02E-12 1.74E-12 6.71E-12 2.75E-12 ± 0.15% ± 0.46% ± 0.13% ± 0.07% ± 0.07% ± 0.20% 3.61E-08 ± 1.57E-08 ± 3.36E-08 ± 6.38E-09 ± 43.50% 93.00% 17.70% 46.80% 19.00% 40.60% 11:00 5.63E-11 4.18E-11 5.57E-11 1.13E-11 ± 0.13% ± 0.21% ± 0.04% ± 0.15% ± 0.05% ± 0.13% 5.72E-08 ± 2.08E-08 ± 5.10E-08 ± 7.33E-09 ± 36.40% 89.10% 12.80% 40.90% 14.40% 35.20% 11:30 8.92E-11 4.30E-11 8.95E-11 1.37E-11 ± 0.09% ± 0.21% ± 0.03% ± 0.11% ± 0.04% ± 0.10% 7.26E-09 ± 5.77E-09 ± 2.90E-08 ± 8.21E-09 ± 79.50% 399.10% 113.10% 19.90% 28.30% 142.20% 12:00 1.77E-11 9.66E-12 4.52E-11 1.62E-12 ± 0.24% ± 1.16% ± 0.28% ± 0.05% ± 0.04% ± 0.24% 1.07E-08 ± 9.31E-09 ± 2.87E-07 ± 1.03E-08 ± 86.80% 2678.9% 96.20% 3.20% ± 3.60% ± 110.80% 12:30 2.50E-11 1.65E-11 4.76E-10 2.64E-11 ± 0.26% ± 7.69% ± 0.33% 0.01% 0.01% ± 0.34% 1.00E-08 ± 9.10E-09 ± 3.64E-07 ± 1.11E-08 ± 90.80% 3629.0% 111.20% 2.50% ± 3.10% ± 122.50% 30 13:00 2.34E-11 1.61E-11 6.03E-10 1.97E-11 ± 0.27% ± 10.4% ± 0.33% 0.01% 0.01% ± 0.31% 2.17E-08 ± 1.16E-08 ± 6.96E-08 ± 7.38E-09 ± 53.40% 320.60% 34.00% 16.70% 10.60% 63.50% 13:30 5.08E-11 2.17E-11 1.15E-10 1.16E-11 ± 0.16% ± 0.92% ± 0.10% ± 0.04% ± 0.02% ± 0.16% 2.27E-08 ± 1.28E-08 ± 1.01E-07 ± 7.87E-09 ± 56.30% 444.40% 34.60% 12.70% 7.80% ± 61.50% 14:00 4.65E-11 2.77E-11 1.67E-10 1.47E-11 ± 0.17% ± 1.17% ± 0.10% ± 0.03% 0.02% ± 0.18% 2.73E-08 ± 1.42E-08 ± 7.12E-08 ± 7.34E-09 ± 52.10% 261.20% 26.90% 19.90% 10.30% 51.70% 14:30 5.06E-11 2.94E-11 1.32E-10 1.37E-11 ± 0.14% ± 0.68% ± 0.07% ± 0.06% ± 0.03% ± 0.14% 8.85E-09 ± 8.89E-09 ± 2.69E-07 ± 9.68E-09 ± 100.40% 3038.4% 109.30% 3.30% ± 3.60% ± 108.90% 15:00 2.33E-11 1.66E-11 4.46E-10 1.72E-11 ± 0.32% ± 9.46% ± 0.35% 0.01% 0.01% ± 0.28% 1.20E-08 ± 9.90E-09 ± 1.61E-07 ± 8.54E-09 ± 82.40% 1336.7% 71.10% 6.20% ± 5.30% ± 86.30% 15:30 2.57E-11 2.24E-11 3.61E-10 1.43E-11 ± 0.26% ± 4.16% ± 0.19% 0.02% 0.01% ± 0.24%

122

Table 5-22. Continued Average Start Rhines Rhines 2 Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (F8 Tally) (F8 Tally) (F8 Tally) (F8 Tally) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 1.05E-08 ± 9.52E-09 ± 1.61E-07 ± 7.92E-09 ± 90.70% 1537.3% 75.40% 5.90% ± 4.90% ± 83.20% 30 16:00 2.46E-11 1.69E-11 2.67E-10 1.40E-11 ± 0.27% ± 4.40% ± 0.22% 0.01% 0.01% ± 0.21% 5.20E-08 ± 1.97E-08 ± 4.88E-08 ± 7.14E-09 ± 37.80% 93.90% 13.70% 40.30% 14.60% 36.30% 11:00 9.02E-11 3.28E-11 2.17E-09 1.53E-11 ± 0.09% ± 4.18% ± 0.04% ± 1.80% ± 0.65% ± 0.10% 1.22E-08 ± 9.51E-09 ± 2.76E-07 ± 1.18E-08 ± 77.90% 2259.5% 96.50% 3.40% ± 4.30% ± 123.80% 12:00 2.99E-11 1.88E-11 8.84E-09 2.17E-11 ± 0.25% ± 72.6% ± 0.30% 0.11% 0.14% ± 0.33% 1.62E-08 ± 1.07E-08 ± 1.61E-07 ± 8.95E-09 ± 66.00% 993.5% 55.10% 6.60% ± 5.50% ± 83.40% 60 13:00 3.97E-11 2.00E-11 2.78E-09 1.55E-11 ± 0.20% ± 17.3% ± 0.17% 0.12% 0.10% ± 0.21% 2.38E-08 ± 1.32E-08 ± 8.83E-08 ± 7.61E-09 ± 55.30% 370.9% 32.00% 14.90% 8.60% ± 57.80% 14:00 5.10E-11 2.47E-11 3.95E-09 1.55E-11 ± 0.16% ± 16.6% ± 0.09% ± 0.67% 0.39% ± 0.16% 1.03E-08 ± 9.42E-09 ± 2.05E-07 ± 9.09E-09 ± 91.80% 1997.0% 88.60% 4.60% ± 4.40% ± 96.60% 15:00 2.52E-11 1.76E-11 7.83E-09 1.67E-11 ± 0.28% ± 76.1% ± 0.27% 0.18% 0.17% ± 0.25%

Table 5-23. Airport weather in-house Gaussian model January 18th, 2019 simulations Average Start Rhines Rhines 2 Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (F8 Tally) (F8 Tally) (F8 Tally) (F8 Tally) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 1.42E-07 ± 3.14E-08 ± 2.15E-08 ± 7.26E-09 ± 22.10% 15.10% 5.10% ± 146.00% 33.80% 23.20% 11:00 2.70E-10 6.59E-11 4.09E-11 1.52E-11 ± 0.06% ± 0.04% 0.01% ± 0.41% ± 0.10% ± 0.07% 8.06E-07 ± 7.80E-08 ± 1.76E-08 ± 9.63E-09 ± 9.70% ± 2.20% ± 1.20% ± 443.90% 54.80% 12.30% 12:00 7.98E-09 1.25E-10 3.17E-11 1.73E-11 0.10% 0.02% 0.01% ± 1.07% ± 0.14% ± 0.03% 1.14E-07 ± 2.51E-08 ± 2.01E-08 ± 4.62E-09 ± 22.00% 17.60% 4.10% ± 125.00% 23.00% 18.40% 60 13:00 2.05E-10 6.78E-11 4.02E-11 1.06E-11 ± 0.07% ± 0.05% 0.01% ± 0.42% ± 0.07% ± 0.07% 1.40E-08 ± 1.03E-08 ± 9.61E-08 ± 3.96E-09 ± 73.60% 685.2% 28.20% 10.70% 4.10% ± 38.40% 14:00 2.52E-11 2.16E-11 4.77E-09 9.90E-12 ± 0.20% ± 34.1% ± 0.09% ± 0.53% 0.20% ± 0.13% 1.30E-08 ± 1.01E-08 ± 9.67E-08 ± 4.91E-09 ± 77.20% 742.00% 37.60% 10.40% 5.10% ± 48.70% 15:00 2.21E-11 2.12E-11 1.84E-10 1.18E-11 ± 0.21% ± 1.90% ± 0.11% ± 0.03% 0.02% ± 0.16%

Table 5-24. FLEXPART January 18th, 2019 simulations Average Start Rhines Rhines 2 Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (F8 Tally) (F8 Tally) (F8 Tally) (F8 Tally) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 9.11E-10 ± 1.36E-09 ± 3.24E-09 ± 2.61E-09 ± 149.40% 355.40% 286.10% 42.00% 80.50% 191.50% 60 11:00 2.28E-12 3.13E-12 2.98E-11 5.48E-12 ± 0.51% ± 3.39% ± 0.94% ± 0.40% ± 0.76% ± 0.60%

123

Table 5-24. Continued Average Start Rhines Rhines 2 Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (F8 Tally) (F8 Tally) (F8 Tally) (F8 Tally) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 6.73E-10 ± 1.24E-09 ± 2.23E-08 ± 2.03E-09 ± 184.90% 3321.1% 302.10% 5.60% ± 9.10% ± 163.40% 12:00 1.82E-12 8.43E-12 9.81E-11 9.54E-12 ± 1.35% ± 17.1% ± 1.63% 0.05% 0.06% ± 1.35% 6.00E-09 ± 4.35E-09 ± 5.32E-08 ± 5.66E-09 ± 72.40% 886.2% 94.40% 8.20% ± 10.60% 130.30% 13:00 9.54E-11 1.09E-10 3.56E-10 2.72E-10 ± 2.15% ± 15.3% ± 4.77% 0.21% ± 0.52% ± 7.05% 60 5.20E-09 ± 3.50E-09 ± 4.01E-08 ± 3.62E-09 ± 67.30% 771.5% 69.70% 8.70% ± 9.00% ± 103.60% 14:00 7.18E-11 5.64E-11 2.69E-10 7.60E-11 ± 1.43% ± 11.8% ± 1.75% 0.15% 0.20% ± 2.74% 2.66E-09 ± 2.44E-09 ± 2.61E-08 ± 3.34E-09 ± 91.50% 978.4% 125.20% 9.40% ± 12.80% 136.80% 15:00 2.55E-11 3.37E-11 1.51E-10 4.88E-11 ± 1.54% ± 11.0% ± 2.19% 0.14% ± 0.20% ± 2.75%

Table 5-25. AERMOD January 18th, 2019 simulations Average Start Rhines Rhines 2 Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧 Time Time (F8 Tally) (F8 Tally) (F8 Tally) (F8 Tally) (min) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 1.56E-07 ± 5.64E-08 ± 1.13E-07 ± 1.33E-08 ± 36.30% 72.90% 8.50% ± 49.70% 11.70% 23.50% 11:00 5.62E-09 3.44E-10 9.38E-10 5.85E-11 ± 1.32% ± 2.68% 0.31% ± 0.51% ± 0.11% ± 0.18% 3.39E-07 ± 9.55E-08 ± 1.77E-07 ± 1.99E-08 ± 28.10% 52.00% 5.90% ± 54.10% 11.30% 20.80% 12:00 1.63E-08 1.59E-09 4.28E-09 6.77E-11 ± 1.43% ± 2.81% 0.28% ± 1.58% ± 0.27% ± 0.35% 1.41E-07 ± 5.39E-08 ± 1.08E-07 ± 1.06E-08 ± 38.30% 76.90% 7.50% ± 49.90% 9.80% ± 19.70% 60 13:00 1.28E-09 8.95E-10 1.76E-09 3.82E-11 ± 0.72% ± 1.43% 0.07% ± 1.16% 0.16% ± 0.33% 5.09E-08 ± 4.16E-08 ± 2.18E-07 ± 1.08E-08 ± 81.80% 429.2% 21.20% 19.10% 4.90% ± 25.90% 14:00 2.39E-09 1.69E-09 3.42E-09 8.32E-11 ± 5.08% ± 21.2% ± 1.01% ± 0.83% 0.09% ± 1.07% 4.89E-08 ± 4.66E-08 ± 2.50E-07 ± 1.20E-08 ± 95.20% 511.8% 24.50% 18.60% 4.80% ± 25.70% 15:00 1.74E-09 1.90E-09 6.60E-09 1.10E-10 ± 5.16% ± 22.7% ± 0.90% ± 0.91% 0.13% ± 1.08%

124

Discussion and Analysis of Results

The similarity in trends displayed by the high velocity plume stack measurement and simulation results remain apparent for only some of the low velocity plume stack results. For example, the measurements taken on January 17th present a large rise in the 푊푒𝑖푚푒푟 value from 13:50 to 14:00, increasing from 37.8% ± 0.34% to 2426.3% ± 푅ℎ𝑖푛푒푠

115.2%. For the UFTR and UF in-house modeling simulations, this value increases from

60.8% ± 2.8% to 725.1% ± 2.3% (UFTR) and 30.9% ± 1.5% to 4065.3% ± 13.3% (UF).

Even in just a 10 minute span, the in-house model’s shift in meteorological conditions created a plume which when coupled with MCNP was able to model the extremely large increase in photon counts arriving at the Weimer station. Although this trend is correctly modeled, the original and final ratios are quite different between the simulations and the measurements.

As performed in Chapter 4, the percent differences between all simulations and measurements were calculated for all four days of data and averaged for each model to better display and compare the results. Once the six averaged tally ratios were calculated for each model, an average percent difference was calculated from those six values. The results (displayed in Table 5-26) show that the simulation code which best models the 41Ar plume on November 7th is FLEXPART, on January 16th is AERMOD, and on January 17th and 18th is the UFTR in-house Gaussian model. However, the results display that most values are inconsistent and many of the trends in tally ratio values do not align with the measurements, even for the best modeling results during each measurement day.

125

Table 5-26. Average percent difference for all models simulating the 41Ar plume emitted by the low velocity plume stack November 푹풉풊풏풆풔ퟐ 푾풆풊풎풆풓 푹풆풊풕풛 푹풉풊풏풆풔ퟐ 푹풆풊풕풛 푹풆풊풕풛 Average 7th 푹풉풊풏풆풔 푹풉풊풏풆풔 푹풉풊풏풆풔 푾풆풊풎풆풓 푾풆풊풎풆풓 푹풉풊풏풆풔ퟐ 2926.30% 1308.00% 17714.70% 666.10% 1364.6% 1110.3% 4181.7% UFTR-10m ± 64.47% ± 13.88% ± 1582.8% ± 15.87% ± 137.1% ± 159.3% ± 266.4% 1224.90% 803.90% 1486.30% 162.30% 207.40% 194.30% 679.80% UF-10m ± 40.83% ± 20.30% ± 72.31% ± 6.52% ± 7.98% ± 7.89% ± 14.41% 507.40% 1080.70% 2330.60% 48.30% ± 194.60% 297.00% 743.10% UFTR-30m ± 3.65% ± 5.19% ± 62.75% 0.48% ± 8.45% ± 8.41% ± 10.70% 430.50% 465.20% 1683.50% 25.10% ± 236.90% 229.10% 511.70% UF-30m ± 3.59% ± 1.99% ± 57.73% 0.22% ± 8.38% ± 7.71% ± 9.83% 503.30% 836.30% 2313.20% 26.80% ± 239.70% 295.50% 702.50% UFTR-60m ± 3.75% ± 5.02% ± 73.46% 0.27% ± 9.29% ± 9.73% ± 12.49% 466.70% 490.80% 1823.80% 9.90% ± 236.60% 239.10% 544.50% UF-60m ± 3.54% ± 2.23% ± 60.50% 0.09% ± 8.39% ± 8.35% ± 10.30% 416.60% 368.30% 1066.10% 17.10% ± 152.40% 124.30% 357.50% Airport ± 3.33% ± 1.50% ± 35.28% 0.15% ± 4.87% ± 4.24% ± 6.01% 24.90% ± 62.00% ± 41.10% ± 574.50% 407.60% 24.70% ± 189.10% FLEXPART 0.49% 0.60% 1.98% ± 7.22% ± 17.22% 0.95% ± 3.14% 417.10% 1864.60% 2367.70% 61.70% ± 79.40% ± 367.20% 859.60% AERMOD ± 3.03% ± 57.78% ± 91.51% 1.46% 3.42% ± 14.08% ± 18.21% January 푹풉풊풏풆풔ퟐ 푾풆풊풎풆풓 푹풆풊풕풛 푹풉풊풏풆풔ퟐ 푹풆풊풕풛 푹풆풊풕풛 Average 16th 푹풉풊풏풆풔 푹풉풊풏풆풔 푹풉풊풏풆풔 푾풆풊풎풆풓 푾풆풊풎풆풓 푹풉풊풏풆풔ퟐ 57.60% ± 796.20% 539.60% ± 263.40% 510.10% 1680.70% 641.30% UF-10m 0.31% ± 8.05% 4.20% ± 3.79% ± 4.51% ± 10.92% ± 2.56% 57.20% ± 431.40% 552.40% ± 119.30% 595.30% 1712.40% 578.00% UF-30m 0.20% ± 2.33% 5.18% ± 0.38% ± 7.27% ± 14.02% ± 2.80% 62.70% ± 157.80% 1222.10% 65.40% ± 711.40% 3664.00% 980.60% UF-60m 0.22% ± 3.95% ± 19.18% 0.84% ± 7.80% ± 59.11% ± 10.46% 50.40% ± 1089.30% 529.40% ± 87.80% ± 97.90% ± 1115.40% 495.10% Airport 0.18% ± 5.53% 2.52% 0.22% 0.39% ± 3.94% ± 1.21% 30.60% ± 270.30% 141.30% ± 129.60% 130.40% 107.50% 135.00% FLEXPART 0.30% ± 1.79% 1.73% ± 2.79% ± 2.85% ± 1.99% ± 0.85% 57.10% ± 226.60% 37.10% ± 74.50% ± 36.90% ± 226.70% 109.80% AERMOD 1.04% ± 6.47% 0.53% 0.75% 0.20% ± 2.27% ± 1.17% January 푹풉풊풏풆풔ퟐ 푾풆풊풎풆풓 푹풆풊풕풛 푹풉풊풏풆풔ퟐ 푹풆풊풕풛 푹풆풊풕풛 Average 17th 푹풉풊풏풆풔 푹풉풊풏풆풔 푹풉풊풏풆풔 푾풆풊풎풆풓 푾풆풊풎풆풓 푹풉풊풏풆풔ퟐ 74.70% ± 89.40% ± 590.20% ± 96.80% ± 525.7% ± 560.6% ± 322.9% ± UFTR-10m 0.44% 0.52% 604.60% 3.28% 115.1% 356.54% 118.55% 134.00% 4570.50% 2362.60% 69.00% ± 425.7% ± 1983.0% 1590.8% UF-10m ± 1.15% ± 42.83% ± 1847.2% 0.50% 590.13% ± 426.8% ± 331.0% 71.70% ± 92.70% ± 198.70% ± 178.20% 192.60% 166.60% 150.10% UFTR-30m 0.37% 1.39% 22.90% ± 5.97% ± 4.61% ± 11.69% ± 4.47% 154.60% 695.90% 400.40% ± 60.80% ± 44.00% ± 235.90% 265.30% UF-30m ± 1.23% ± 14.60% 36.69% 0.98% 2.08% ± 8.13% ± 6.73% 46.00% ± 183.50% 157.00% ± 162.50% 160.50% 143.60% 142.20% UFTR-60m 0.13% ± 2.22% 0.60% ± 1.31% ± 1.42% ± 1.30% ± 0.55% 44.50% ± 236.70% 406.10% ± 54.30% ± 204.40% 357.30% 217.20% UF-60m 0.21% ± 1.89% 24.87% 0.42% ± 11.25% ± 12.81% ± 5.04% 59.10% ± 249.80% 295.50% ± 379.70% 301.60% 245.70% 255.20% Airport 0.34% ± 1.94% 17.95% ± 3.85% ± 6.75% ± 7.92% ± 3.53%

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Table 5-26. Continued January 푹풉풊풏풆풔ퟐ 푾풆풊풎풆풓 푹풆풊풕풛 푹풉풊풏풆풔ퟐ 푹풆풊풕풛 푹풆풊풕풛 Average 17th 푹풉풊풏풆풔 푹풉풊풏풆풔 푹풉풊풏풆풔 푾풆풊풎풆풓 푾풆풊풎풆풓 푹풉풊풏풆풔ퟐ 1321.60% 202.80% 929.00% 6313.4% 2006.10% 57.90% ± 1805.10% FLEXPART ± 33.66% ± 2.61% ± 29.08% ± 228.5% ± 84.31% 1.65% ± 41.27% 77.60% ± 379.40% 201.80% 118.60% 71.60% ± 128.40% 162.90% AERMOD 2.74% ± 13.17% ± 14.82% ± 1.35% 1.77% ± 2.83% ± 3.39% January 푹풉풊풏풆풔ퟐ 푾풆풊풎풆풓 푹풆풊풕풛 푹풉풊풏풆풔ퟐ 푹풆풊풕풛 푹풆풊풕풛 Average 18th 푹풉풊풏풆풔 푹풉풊풏풆풔 푹풉풊풏풆풔 푾풆풊풎풆풓 푾풆풊풎풆풓 푹풉풊풏풆풔ퟐ 84.10% ± 84.40% ± 515.2% ± 669.10% 1504.5% 198.90% 509.40% UFTR-10m 0.94% 1.78% 132.87% ± 20.19% ± 215.6% ± 20.83% ± 42.48% 127.50% 68.60% ± 734.00% 388.10% 1336.0% 347.10% 500.20% UF-10m ± 7.35% 4.76% ± 88.36% ± 23.46% ± 157.9% ± 77.80% ± 33.10% 40.70% ± 93.50% ± 406.4% ± 147.50% 1775.1% 816.30% 546.6% ± UFTR-30m 0.50% 0.74% 134.14% ± 4.58% ± 514.0% ± 296.8% 101.43% 58.70% ± 34.60% ± 885.8% ± 73.80% ± 1433.6% 667.20% 525.6% ± UF-30m 1.79% 0.41% 354.53% 0.73% ± 511.8% ± 339.1% 118.15% 46.80% ± 75.10% ± 144.40% 60.70% ± 192.10% 89.60% ± 101.50% UFTR-60m 0.65% 2.64% ± 1.90% 1.70% ± 9.22% 3.88% ± 1.78% 58.60% ± 31.10% ± 444.8% ± 137.50% 139.60% 117.90% 154.90% UF-60m 3.74% 1.13% 331.90% ± 9.35% ± 7.65% ± 3.79% ± 55.36% 53.70% ± 91.70% ± 224.0% ± 5582.30% 2595.60% 86.60% ± 1439.00% Airport 1.04% 2.02% 170.59% ± 89.18% ± 30.74% 2.41% ± 32.49% 287.20% 132.60% 3662.5% 47.60% ± 5113.10% 811.30% 1675.7% FLEXPART ± 2.27% ± 2.09% ± 656.9% 0.48% ± 56.73% ± 34.55% ± 110.1% 48.00% ± 73.60% ± 183.30% 652.90% 1756.40% 82.40% ± 466.10% AERMOD 1.88% 3.05% ± 99.46% ± 20.47% ± 8.07% 2.51% ± 16.99%

As done with the high plume stack data, the average percent differences were recalculated by removing all simulation tally ratios for stations which detected less than three counts per second during the measurements (results displayed in Table 5-27).

Since the simulation data trends observed on January 17th and 18th correlate more closely than the results on November 7th and January 16th, it is theorized that the true dominant codes which best represent all of the measurement results are the UFTR and

UF in-house model. This is most likely due to the need for localized meteorological information when the low plume stack is used. Since the low stack releases the 41Ar at lower atmospheric heights, wind speed and orientation become more dependent on localized effects.

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Table 5-27. Average percent difference for all models simulating the 41Ar plume emitted by the low velocity plume stack (all model results which simulated stations receiving count rates lower than three cps removed) November 푹풉풊풏풆풔ퟐ 푾풆풊풎풆풓 푹풆풊풕풛 푹풉풊풏풆풔ퟐ 푹풆풊풕풛 푹풆풊풕풛 Average 7th 푹풉풊풏풆풔 푹풉풊풏풆풔 푹풉풊풏풆풔 푾풆풊풎풆풓 푾풆풊풎풆풓 푹풉풊풏풆풔ퟐ 3296.30% 1308.00% 0.00% ± 697.00% 0.00% ± 0.00% ± 1767.10% UFTR-10m ± 85.92% ± 13.88% 0.00% ± 20.67% 0.00% 0.00% ± 29.82% 1342.00% 803.90% 0.00% ± 168.80% 0.00% ± 0.00% ± 771.60% UF-10m ± 54.36% ± 20.30% 0.00% ± 8.65% 0.00% 0.00% ± 19.56% 500.40% 1080.70% 0.00% ± 41.80% ± 0.00% ± 0.00% ± 541.00% UFTR-30m ± 3.17% ± 5.19% 0.00% 0.30% 0.00% 0.00% ± 2.03% 421.90% 465.20% 0.00% ± 25.10% ± 0.00% ± 0.00% ± 304.10% UF-30m ± 3.33% ± 1.99% 0.00% 0.19% 0.00% 0.00% ± 1.29% 503.30% 836.30% 0.00% ± 26.80% ± 0.00% ± 0.00% ± 455.50% UFTR-60m ± 3.75% ± 5.02% 0.00% 0.27% 0.00% 0.00% ± 2.09% 466.70% 490.80% 0.00% ± 9.90% ± 0.00% ± 0.00% ± 322.50% UF-60m ± 3.54% ± 2.23% 0.00% 0.09% 0.00% 0.00% ± 1.40% 416.60% 368.30% 0.00% ± 17.10% ± 0.00% ± 0.00% ± 267.30% Airport ± 3.33% ± 1.50% 0.00% 0.15% 0.00% 0.00% ± 1.22% 24.90% ± 62.00% ± 0.00% ± 574.50% 0.00% ± 0.00% ± 220.50% FLEXPART 0.49% 0.60% 0.00% ± 7.22% 0.00% 0.00% ± 2.42% 417.10% 1864.60% 0.00% ± 61.70% ± 0.00% ± 0.00% ± 781.10% AERMOD ± 3.03% ± 57.78% 0.00% 1.46% 0.00% 0.00% ± 19.29% January 푹풉풊풏풆풔ퟐ 푾풆풊풎풆풓 푹풆풊풕풛 푹풉풊풏풆풔ퟐ 푹풆풊풕풛 푹풆풊풕풛 Average 16th 푹풉풊풏풆풔 푹풉풊풏풆풔 푹풉풊풏풆풔 푾풆풊풎풆풓 푾풆풊풎풆풓 푹풉풊풏풆풔ퟐ 57.60% ± 796.20% 539.60% 263.40% 510.10% 1680.70% 641.30% UF-10m 0.31% ± 8.05% ± 4.20% ± 3.79% ± 4.51% ± 10.92% ± 2.56% 57.20% ± 431.40% 552.40% 119.30% 595.30% 1712.40% 578.00% UF-30m 0.20% ± 2.33% ± 5.18% ± 0.38% ± 7.27% ± 14.02% ± 2.80% 62.70% ± 157.80% 1222.10% 65.40% ± 711.40% 3664.00% 980.60% UF-60m 0.22% ± 3.95% ± 19.18% 0.84% ± 7.80% ± 59.11% ± 10.46% 50.40% ± 1089.30% 529.40% 87.80% ± 97.90% ± 1115.40% 495.10% Airport 0.18% ± 5.53% ± 2.52% 0.22% 0.39% ± 3.94% ± 1.21% 30.60% ± 270.30% 141.30% 129.60% 130.40% 107.50% 135.00% FLEXPART 0.30% ± 1.79% ± 1.73% ± 2.79% ± 2.85% ± 1.99% ± 0.85% 57.10% ± 226.60% 37.10% ± 74.50% ± 36.90% ± 226.70% 109.80% AERMOD 1.04% ± 6.47% 0.53% 0.75% 0.20% ± 2.27% ± 1.17% January 푹풉풊풏풆풔ퟐ 푾풆풊풎풆풓 푹풆풊풕풛 푹풉풊풏풆풔ퟐ 푹풆풊풕풛 푹풆풊풕풛 Average 17th 푹풉풊풏풆풔 푹풉풊풏풆풔 푹풉풊풏풆풔 푾풆풊풎풆풓 푾풆풊풎풆풓 푹풉풊풏풆풔ퟐ 74.70% ± 89.40% ± 523.70% 96.80% ± 563.20% 901.80% 374.90% UFTR-10m 0.44% 0.73% ± 15.65% 0.81% ± 27.36% ± 26.66% ± 6.88% 134.00% 4570.50% 285.10% 69.00% ± 43.80% ± 388.80% 915.20% UF-10m ± 1.15% ± 42.83% ± 12.78% 0.50% 0.94% ± 17.28% ± 7.99% 71.70% ± 92.70% ± 37.70% ± 178.20% 164.30% 77.40% ± 103.70% UFTR-30m 0.37% 1.09% 1.70% ± 5.97% ± 10.15% 3.63% ± 2.08% 154.60% 695.90% 182.70% 60.80% ± 46.30% ± 236.80% 229.50% UF-30m ± 1.23% ± 14.60% ± 8.94% 0.98% 3.12% ± 12.02% ± 3.53% 46.00% ± 183.50% 75.90% ± 162.50% 206.70% 51.50% ± 121.00% UFTR-60m 0.13% ± 2.22% 1.49% ± 1.31% ± 4.07% 1.08% ± 0.86% 44.50% ± 236.70% 92.40% ± 54.30% ± 53.60% ± 257.10% 123.10% UF-60m 0.21% ± 1.89% 1.81% 0.42% 1.06% ± 5.46% ± 1.03%

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Table 5-27. Continued January 푹풉풊풏풆풔ퟐ 푾풆풊풎풆풓 푹풆풊풕풛 푹풉풊풏풆풔ퟐ 푹풆풊풕풛 푹풆풊풕풛 Average 17th 푹풉풊풏풆풔 푹풉풊풏풆풔 푹풉풊풏풆풔 푾풆풊풎풆풓 푾풆풊풎풆풓 푹풉풊풏풆풔ퟐ 59.10% ± 249.80% 78.40% ± 379.70% 274.40% 126.00% 194.50% Airport 0.34% ± 1.94% 1.81% ± 3.85% ± 5.43% ± 2.46% ± 1.26% 1321.60% 202.80% 97.90% ± 6313.4% 340.20% 63.00% ± 1389.80% FLEXPART ± 33.66% ± 2.61% 2.56% ± 228.5% ± 11.17% 2.43% ± 38.55% 77.60% ± 379.40% 72.90% ± 118.60% 13.00% ± 175.00% 139.40% AERMOD 2.74% ± 13.17% 3.84% ± 1.35% 0.29% ± 3.63% ± 2.42% January 푹풉풊풏풆풔ퟐ 푾풆풊풎풆풓 푹풆풊풕풛 푹풉풊풏풆풔ퟐ 푹풆풊풕풛 푹풆풊풕풛 Average 18th 푹풉풊풏풆풔 푹풉풊풏풆풔 푹풉풊풏풆풔 푾풆풊풎풆풓 푾풆풊풎풆풓 푹풉풊풏풆풔ퟐ 83.30% ± 84.80% ± 87.20% ± 521.20% 272.80% 187.60% 206.10% UFTR-10m 0.52% 1.30% 0.74% ± 6.22% ± 4.45% ± 1.54% ± 1.33% 90.10% ± 72.20% ± 86.50% ± 198.10% 101.40% 93.20% ± 106.90% UF-10m 3.41% 0.63% 1.30% ± 2.75% ± 2.64% 1.02% ± 0.90% 44.50% ± 88.70% ± 458.40% 56.60% ± 87.70% ± 894.00% 271.60% UFTR-30m 0.39% 0.46% ± 2.94% 0.29% 0.56% ± 5.13% ± 1.00% 42.40% ± 40.10% ± 68.10% ± 90.80% ± 173.60% 53.20% ± 78.00% ± UF-30m 0.27% 0.37% 1.05% 0.86% ± 5.28% 1.37% 0.94% 46.80% ± 75.10% ± 0.00% ± 60.70% ± 0.00% ± 0.00% ± 60.90% ± UFTR-60m 0.65% 2.64% 0.00% 1.70% 0.00% 0.00% 1.07% 19.90% ± 27.40% ± 0.00% ± 34.70% ± 0.00% ± 0.00% ± 27.30% ± UF-60m 0.14% 1.84% 0.00% 1.24% 0.00% 0.00% 0.74% 53.70% ± 91.70% ± 0.00% ± 5582.30% 0.00% ± 0.00% ± 1909.20% Airport 1.04% 2.02% 0.00% ± 89.18% 0.00% 0.00% ± 29.74% 287.20% 132.60% 0.00% ± 47.60% ± 0.00% ± 0.00% ± 155.80% FLEXPART ± 2.27% ± 2.09% 0.00% 0.48% 0.00% 0.00% ± 1.04% 48.00% ± 73.60% ± 0.00% ± 652.90% 0.00% ± 0.00% ± 258.20% AERMOD 1.88% 3.05% 0.00% ± 20.47% 0.00% 0.00% ± 6.93%

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CHAPTER 6 SENSITIVITY ANALYSIS OF COUPLED MODELS

Overview of Proposed Sensitivity Analyses

Uncertainty quantification techniques can be utilized to measure the validity of computational models [71]. Sensitivity analysis is a type of uncertainty quantification technique which quantifies the contribution of selected input parameters to the output, allowing it to become a tool in parameter selection. During parameter selection, the inputs which have the largest effect on the output results are selected for further statistical analyses. On the other hand, model inputs which are found to be extremely insensitive can be assumed to be “constant”.

One of the simplest techniques in performing sensitivity analysis is termed

“changing one-factor-at-a-time (OFAT)”. As the name implies, this technique allows one model parameter to be changed while all other values remain the same. The change in output results will be indicative of the sensitivity of the model to that input. Regression analysis can also be performed on the change in output to better quantify the sensitivity.

However, since this technique only allows one parameter to be changed at a time, there is no way of measuring interactions between inputs [72]. This type of sensitivity analysis technique is referred to as “local”. On the other hand, “global” sensitivity analysis techniques allow the utilization of all the parameter space [73]. For example, variance- based sensitivity analysis is a global technique where the variance of the model output can be formulated from inputs or sets of inputs. With this technique, it is possible to study the interaction between two or more inputs in a model. This is accomplished by calculating the main effect sensitivity indices, seen in Equation 6-1 [73, 74]:

130

푣푎푟(퐸[푌|푋 ]) 푆 = 𝑖 , (6-1) 𝑖 푣푎푟(푌) where Y is the model output, Xi is a random variable representing an input parameter, and E[Y|Xi ] is the portion of the variance in Y that will remain when Xi is held constant.

The sensitivity index of the model output concerning a specific input variable refers to the fraction of the output variance which can be attributed to the input variable, whether it is on its own or combined with other input parameters [75,76]. To calculate the sensitivity indices, techniques such as the Fourier Amplitude Sensitivity Test method or the Sobol’ method can be used. The FAST method utilizes Fourier transforms while the

Sobol’ method uses the Monte Carlo method. After finalizing parameter selection, sensitivity analysis tends to move towards model calibration, where selected parameters are molded so that the output of the model is equal to the experimental value. This can be obtained through the use of parameter distributions or confidence intervals [77].

Due to the large variations between the measurement and simulation results, it was decided to perform an OFAT technique for this research to select which ATM input parameters have the largest effect on the MCNP outputs. Sensitivity analysis could technically be performed on two outputs for this research: The ATM concentration profile results and the 41Ar tally ratios. Since the ATMs were coupled with MCNP for all analyses, it was imperative that the final output (41Ar tally ratios) be used for all sensitivity analysis.

One-factor-at-a-time Sensitivity Analysis

The next few sections describe the simulation results attained after varying the wind speed, wind orientation, atmospheric stability, plume resolution, and plume length

131 for the two Gaussian models (in-house and AERMOD). For the FLEXPART-WRF model, changing the meteorological conditions is a more intricate process due to the large gridded meteorological data processed and outputted by the WPS and WRF models. The possibility of performing sensitivity analysis on this model is mentioned in the next chapter under the future work section. Furthermore, the simulations performed for the wind speed, wind orientation, and atmospheric stability tests utilized low velocity plume stack data while plume resolution and plume length tests used high velocity plume stack information.

Wind Speed

The wind speed profile near the release of a pollutant will directly affect its dispersion by not only defining the speed in which a pollutant moves downwind, but also the atmospheric stability and rise of the plume. Thus, inputting the correct wind speed in an ATM will decrease the likelihood of output errors. Since this work coupled ATMs with

MCNP, the effect wind speed has on the tally ratios was analyzed. For the in-house model, this was accomplished by directly changing the input of the wind speed in the

MATLAB script. To change the wind speeds for AERMOD, the output files produced by

AERMET were altered.

The base case for the in-house model sensitivity analysis was defined with a wind speed of 1.51 m s-1, wind orientation of 212°, Pasquill class A, plume resolution of

75 cm, and plume length of 225 m. The wind speed was decreased to 0.151 m s-1 and increased to 3.02 m s-1 by using 2% interval differences between 2% and 20% and 5% intervals for wind speed values changing by more than 20%. The results obtained from the in-house Gaussian model are displayed in Figure 6-1. Additionally, the maximum

132 change in tally ratio for each interval was calculated and displayed in Figure 6-2. The results show that fluctuations in wind velocity do not tend to result in large tally ratio changes. However, the model begins displaying increased variations in simulation outputs when decreasing the wind speed to very low values (approximately 0.4 to 0.5 m s-1).

Figure 6-1. Percent change in tally ratio as the wind velocity is altered in the in-house Gaussian MATLAB model

Figure 6-2. Maximum % change in tally ratios as the wind velocity is altered in the in- house Gaussian MATLAB model

The effect of wind speed on the AERMOD-MCNP outputs was also analyzed.

The base input utilized meteorological data taken on January 18th at 15:00. This

133 included a wind speed of 2.59 m s-1 and orientation of 206°. The wind speed was decreased to 0.13 m s-1 and increased to 5.18 m s-1 with the same interval pattern as the in-house model. The total and maximum changes in the tally ratios with varying wind speeds are displayed in Figures 6-3 and 6-4.

Figure 6-3. Percent change in tally ratio as the wind velocity is altered in the AERMOD code

Figure 6-4. Maximum % change in tally ratios as the wind velocity is altered in the AERMOD code

The maximum changes in tally ratios for AERMOD are similar to the in-house model where they tend to change relatively proportionally with changes in wind speed.

However, for very low wind speed values, the in-house Gaussian model displays a larger sensitivity than AERMOD. The output’s heightened sensitivity when low wind

134 speeds are present can be explained by the increase in plume rise at these conditions.

The plume rise equation utilized with the in-house Gaussian model (Equation 3-2) was used to display the change in plume rise at varying wind speeds (seen in Figure 6-5).

As seen from the figure, the exponential increase in plume rise at low wind speeds leads to large surges in the total elevation of the 41Ar plume which directly affects the

MCNP tallies on each detector.

(a)

(b) Figure 6-5. Change in plume rise with varying wind velocity (a) full view (b) zoomed in view

135

It is also worth noting that Gaussian models such as AERMOD have historically struggled at accurately approximating pollutant concentrations at low wind speed conditions. At wind speeds lower than 2 m s-1, the model struggles to remain a valid estimator of plume dispersion due to the domination of diffusion over advection [78].

This has led to modeling evaluations where dispersion and plume rise algorithms are altered. This includes models such as AERMOD which as previously discussed, incorporates the STABLEBL function to accurately modify concentration values during times of low wind speeds and a stable atmosphere [79].

Wind Orientation

Inputting accurate wind orientation information on ATMs is crucial when trying to replicate radiation measurements. Since we placed detectors on four locations during each measurement, the direction in which the wind carried the 41Ar plume was crucial in defining the number of counts recorded at each station. Due to variabilities in wind direction, the count rates at specific stations were seen to rise or drop significantly even for 10 minute intervals. For example, during the May 8th measurements, the count rate recorded from 13:50 to 14:00 at the Rhines Hall station was 79.05 ± 0.29 cps and dropped to 10.53 ± 0.17 cps from 14:00 to 14:10. Meanwhile, the count rate recorded at the Reitz Union rose from 0.67 ± 0.14 cps to 16.39 ± 0.18 cps. This large difference in values could only arise from fast variations in wind direction.

To calculate the effect of wind orientation on the in-house Gaussian model, a base input case was created with the same wind speed (1.51 m s-1), Pasquill class (A), plume resolution (75 cm), and plume length (225 m) as simulated on the wind speed section while the wind orientation was varied from 10° to 360° in 10° intervals. To

136 observe the effects of small variations in wind speed, the tally ratio percent differences were calculated between degrees spaced 10° from each other. For example, the percent difference for a simulation utilizing a wind orientation of 200° would be calculated by comparing it with the results of a 190° wind orientation simulation.

Additionally, this analysis was performed using the AERMOD code with the same meteorological inputs as the wind speed sensitivity analysis. The results for both models along with the maximum differences for each of them are displayed in Figures 6-6 through 6-9.

Figure 6-6. Percent change in tally ratio as the wind orientation is altered by 10° in the in-house Gaussian MATLAB model

Figure 6-7. Maximum % change in tally ratio as the wind orientation is altered by 10° in the in-house Gaussian MATLAB model

137

Figure 6-8. Percent change in tally ratio as the wind orientation is altered by 10° in AERMOD

Figure 6-9. Maximum % change in tally ratio as the wind orientation is altered by 10° in AERMOD

The results for both models prove that small changes in wind orientation can lead to large variations in count rate ratios. This is true in a larger sense for the in-house model where the fluctuations in the output are consistently larger than the AERMOD code. It is theorized this difference stems from AERMOD’s ability to create a wider plume than the in-house Gaussian model. Moreover, the in-house Gaussian model shows a heightened sensitivity with northerly and easterly winds (0° to 100°) while the

AERMOD code displays this with northerly and northeasterly winds (0° to 40°). These

138 large changes tend to occur when a change in the downwind direction removes or places the plume in the direct field of view of one or more specific stations. For example, for the in-house Gaussian model simulations, there is a large drop in the

Rhines 2 value from 80° to 90°, decreasing from 222.3% ± 3.2% to 54.1% ± 0.3%. This Rhines small change in wind orientation moves the plume away from the direction of the Rhines

#2 station and directly above the Rhines station (seen in Figure 6-10). Due to this large sensitivity, the ability for a dispersion model to accurately estimate the count rate ratios of the 41Ar plume depends heavily on the accuracy of the wind orientation information utilized in the simulation.

(a) (b) Figure 6-10. Plume direction change near the UFTR from a wind orientation of (a) 90° to (b) 80°

A secondary set of simulations were performed to fully test the sensitivity of the

MCNP output to variations in wind sensitivity. This was done by adding two detectors on the Reitz Union, one in Weimer Hall, and three on Weil Hall (seen in Figure 6-11). The maximum change in tally ratio as the wind orientation was altered by 20° was calculated and compared with the results obtained from the first set of simulations. The results are displayed on Figure 6-12. As expected, the large dip in sensitivity displayed by the first

139 set of simulations near 100° to 220° becomes less apparent when new detectors are introduced near the UFTR. Additionally, since detectors were placed at shorter distances for these simulations, the total sensitivity of the MCNP output to changes in wind orientation rose, thus solidifying the conclusion that the accuracy of the coupled

ATM-MCNP model depends heavily on the user’s ability to utilize accurate meteorological data.

Figure 6-11. Detector grid for secondary set of wind orientation sensitivity analysis simulations

Figure 6-12. Maximum % change in tally ratio as the wind orientation is altered by 20° for initial and secondary detector grids

140

Atmospheric Stability

Simulation errors stemming from the incorrect selection of the atmospheric stability classification for a Gaussian model was analyzed. Due to the large meteorological differences between each classification, it was assumed that a user would not input an atmospheric stability classification which is two classifications away from the correct class. For instance, if a user selected the Pasquill classification B, it’s likely that the true atmospheric stability could be either A or C, but not D. With this assumption, the base input case utilized in the previous sections for the in-house

Gaussian model was simulated with stability classifications: A, B, C, and D and the results can be seen in Table 6-1. Due to these small variations, it was assumed that an incorrect stability class definition was not a source of large error on the model results with respect to the measurements. Therefore, sensitivity analysis was not performed with the AERMOD code at this time.

Table 6-1. Maximum % change in tally ratio as atmospheric stability is altered Change in stability Maximum % change in class tally ratio A to B 15.13% ± 0.05% B to C 14.84% ± 0.05% C to D 9.69% ± 0.04%

Plume Length and Resolution

The effect of the plume’s geometrical definition in the Gaussian models on the

MCNP output was studied by performing a sensitivity analysis on plume resolution and plume length. For the in-house Gaussian model, the base input case utilized meteorological data taken on March 20th at 11:00 to 12:00 which included a wind speed of 3.49 m s-1 and 46.55° orientation. The resolution, which for the majority of the in- house simulations was held constant at 75 cm, was varied between 22.5 cm to 127.5

141 cm with 7.5 cm intervals. Additionally, the plume length was held constant at 300 steps in the x, y, and z directions, meaning that the total plume length changed accordingly.

For example, if the resolution was 45 cm, the total plume length in one direction would equal 0.135 km. The total and maximum percent differences in tally ratios obtained through the simulations are displayed in Figures 6-13 and 6-14.

(a)

(b) Figure 6-13. Percent change in tally ratio as the plume resolution is altered by 7.5 cm in the in-house model (a) full graph (b) zoomed in view

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Figure 6-14. Maximum % change in tally ratio as the plume resolution is altered by 7.5 cm in the in-house model

The results display that at approximately 45 cm resolutions or lower (plume length of 0.135 km), the model begins displaying large variations in MCNP outputs. As the resolution is increased to 127.5 cm and the plume length to 0.383 km, the results remain almost identical to the original value of 75 cm resolution and 0.225 km plume length. To test the variability with larger resolutions, two simulations were performed with 200 cm (0.5 km plume length) and 300 cm (0.6 km plume length) resolutions. The maximum percent changes for each of these two simulations were 21.6% ± 0.1% (200 cm) and 32.8% ± 0.1% (300 cm). Due to these increases, simulations performed with the UFTR in-house model meteorological data on March 20th at 12:00 were performed to analyze if the larger resolutions would improve or worsen the simulation data with respect to the measurements. The results of these two simulations when compared to the original simulation (resolution of 75 cm) displayed that the percent differences did not undergo large changes (seen in Table 6-2). This proves that large inaccuracies in our simulation results do not stem from plume length and resolution inputs as long as the length is sufficiently long (approximately 0.135 km) and resolution remains relatively

143 small ( < ~300 cm). For the time being, it is assumed that the geometrical definition of the plume was not a large source of error in the AERMOD simulations since the resolution was defined at 200 cm and plume length at 0.198 km for all simulation data.

Table 6-2. Percent difference between March 20th, 2019 12:00 1-hour measurements and UFTR in-house model simulations using 75 cm, 200 cm, and 300 cm resolutions 푹풉풊풏풆풔ퟐ 푾풆풊풎풆풓 푹풆풊풕풛 푹풉풊풏풆풔ퟐ 푹풆풊풕풛 푹풆풊풕풛 Resolution Average 푹풉풊풏풆풔 푹풉풊풏풆풔 푹풉풊풏풆풔 푾풆풊풎풆풓 푾풆풊풎풆풓 푹풉풊풏풆풔ퟐ 42.2% ± 17.7% ± 134.0% ± 50.9% ± 98.4% ± 303.5% ± 107.8% ± 75 cm 0.29% 0.17% 2.14% 1.47% 1.67% 4.68% 5.38% 40.1% ± 12.1% ± 166.5% ± 46.6% ± 137.5% ± 343.4% ± 124.3% ± 200 cm 0.28% 0.11% 2.66% 1.34% 2.33% 5.30% 5.78% 39.1% ± 10.2% ± 176.3% ± 44.8% ± 150.5% ± 352.7% ± 128.9% ± 300 cm 0.27% 0.10% 2.82% 1.28% 2.55% 5.44% 5.88%

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CHAPTER 7 CONCLUSION AND FUTURE WORK

There are many applications of ATMs in the nuclear realm, mainly in nuclear security and emergency response. To assure these models can accurately predict the release and dispersion of radionuclides, it is imperative that they are verified and validated. While different types of techniques have been developed for this purpose, this research studied a new technique in which radiation detection measurements taken from a radioactive plume are compared with simulation results created through the coupling of ATMs and MCNP.

For this research, the UFTR’s unique ability to easily emit a measurable 41Ar plume was used to obtain radiation measurements. Extended measurements were taken on May 8th (2018), March 20th (2019), and March 22nd (2019) with the high velocity plume stack while the low velocity plume stack was utilized for measurements taken on November 7th (2018), January 16th (2019), January 17th (2019), and January

18th (2019). The data recorded during these measurements were used to test three

ATMs:

1. An in-house developed Gaussian code written on MATLAB 2. AERMOD (Gaussian model) 3. FLEXPART (Lagrangian model)

Each of these models required meteorological data to simulate the dispersion of the 41Ar plume. For the in-house Gaussian code, data was taken from weather stations at the

GNV Regional Airport, the Ben Hill Griffin Stadium (UF WeatherSTEM data), and

Rhines Hall (UFTR weather data). The AERMOD simulations utilized data measured by the GNV regional airport while FLEXPART used NCEP GFS data. Due to the close

145 proximity of buildings near the UFTR, the new verification and validation technique focused on short-range urban terrain dispersion modeling.

While these models were able to replicate some of the measurement data, the results were imprecise. The in-house Gaussian model using meteorological data acquired by the UFTR and UF weather stations and the AERMOD code tended to be the most accurate models. The UFTR and UF weather station in-house Gaussian model replicated both the trends and results more accurately when the low velocity plume stack was used while the AERMOD code was most effective when using the high velocity plume stack measurements. Meanwhile, the FLEXPART model was constantly the poorest code when attempting to simulate the 41Ar plume measurement results. Due to its development as a long-range atmospheric dispersion code, FLEXPART utilizes meteorological data with very high resolutions, thus it was not able to accurately simulate the dispersion of the 41Ar plume at short ranges. Additionally, the 30 and 60 minute averaged in-house Gaussian simulations were consistently more accurate than the 10 minute runs. The results also showed a slight improvement in accuracy when using the high plume stack and on days with lower wind speeds. This improvement in accuracy is potentially a result of the increase in plume rise when these two conditions are true. With a higher plume rise, the atmospheric dispersion of the 41Ar plume becomes less dependent on the localized effects of nearby buildings, thus the dispersion tends to be better represented by the simplistic Gaussian models.

Due to the high variability in simulation results and the inability to accurately predict the count rate ratios throughout the simulations, this work was not able to verify and validate the three models through this new technique. This work supported the

146 conclusion of previous studies which determined that simplified dispersion models such as the Gaussian model may output concentration predictions which are fairly different than experimentally measured values [80]. While previous studies have calculated plume concentrations at flat terrains that are two to four factors different than the experimentally measured values, this study attempted to measure the dispersion of a radionuclide in an urban-like terrain, making it even more difficult to accurately predict the dispersion of the plume. As shown in the sensitivity analysis, there are many possible sources of error which could have affected the MCNP outputs. The concentration outputs were most sensitive to changes in wind orientation, which explains some of the errors observed between the measurements and simulations since the three weather stations tended to exhibit large differences in wind orientation. For example, on January 17th between 11:00 and 12:00, the average wind orientation was

68.1° for the UFTR station, 180.6° for the UF station, and 116.0° for the GNV station.

These large variations in wind orientation prove that improved accuracy in meteorological data inputs is necessary when trying to verify and validate ATMs through radiation measurements. Additionally, studies testing Lagrangian based dispersion models have found that the largest source of uncertainty in dispersion model outputs is meteorological data and differences in ATM results usually arise from changes in meteorological data, not the ATMs themselves [81,82,83]. The ATM-MCNP coupling technique developed for this study is able to support these results. However, this work has also proven that the ability of the UFTR to easily emit a measurable 41Ar plume allows the University of Florida to keep working towards the benchmarking of other types of ATMs.

147

Several steps can be taken to continue and improve the results obtained in this work. First of all, the sensitivity analysis work displayed in Chapter 6 should be completed by calculating the effects of plume length, plume resolution, and atmospheric stability on the AERMOD code. Additionally, testing the in-house Gaussian model with different plume rise formula would display its effect on the MCNP output. Plume dimension and meteorology inputs should also be altered for the FLEXPART-WRF model to calculate their effects on the MCNP outputs. To improve the Gaussian simulation models, the Gaussian dispersion equation should be modified to better represent ground reflection when the plume is dispersing directly above a building. This would allow the model to better represent the obstacles surrounding both the high and low velocity plume stacks. In terms of the measurements, it would be beneficial to add more radiation detectors to expand the detector grid. Whether new detectors are available or not, measurement results can be improved by placing all detectors in the path of the forecasted downwind direction. While this might lead to measurement times when no counts are detected, it would allow for better plume characterization when it is flowing in the forecasted direction. This setup would be very similar to the one presented by Martin Drews et al, where the 41Ar plume produced and emitted by the

BR1 reactor in Mol, Belgium, was measured [84]. For this experiment, radiation detection data was accompanied with Lidar scanning of a visible tracer which was injected into the reactor’s plume stack. It would be beneficial for this work to add this capability for better comparisons between the simulation data and the experimental results. Furthermore, due to the strong sensitivity of the coupled model to wind orientation, it is recommended that several smaller mobile weather stations be installed

148 around the UFTR. These weather stations would be placed next to each of the two plume stacks and each of the detector stations to provide more accurate measurements of localized meteorological data.

Lastly, due to the inability to verify and validate the three models tested in this work, it is recommended that a CFD code be tested along with a new Lagrangian model since these are the ideal ATMs for short-range dispersion simulations. The CFD model

OpenFoam, an open source code which has been gaining popularity in local scale atmospheric dispersion situations can be utilized and coupled with MCNP [85].

Additionally, it would be beneficial to attempt to build an in-house Lagrangian model so that inputs could be more easily modified. It would also provide the ability to add building information to the dispersion model, a capability which the FLEXPART code does not possess.

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APPENDIX 10 MINUTE AVERAGED MEASUREMENT AND SIMULATION DATA

Table A-1. May 8th, 2018 10 minute averaged measurement 41Ar count rates and count rate ratios Start Rhines Stadium Weimer Reitz 푆푡푎푑𝑖푢푚 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푆푡푎푑𝑖푢푚 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (cps) (cps) (cps) (cps) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푆푡푎푑𝑖푢푚 41.97 9.86 5.10 0.18 23.50% ± 12.20% ± 0.40% ± 193.30% ± 3.50% ± 1.80% ± 09:40 ±0.24 ±0.16 ±0.16 ±0.14 0.41% 0.38% 0.30% 6.76% 2.66% 1.37% 62.58 3.68 4.03 0.20 5.90% ± 6.40% ± 0.30% ± 91.10% ± 5.10% ± 5.60% ± 09:50 ±0.27 ±0.15 ±0.15 ±0.14 0.23% 0.25% 0.20% 5.02% 3.39% 3.72% 31.69 6.69 4.20 0.30 21.10% ± 13.30% ± 1.00% ± 159.30% ± 7.20% ± 4.50% ± 10:00 ±0.22 ±0.15 ±0.16 ±0.14 0.51% 0.50% 0.45% 6.93% 3.26% 2.03% 21.73 6.99 5.57 0.49 32.20% ± 25.60% ± 2.30% ± 125.40% ± 8.80% ± 7.00% ± 10:10 ±0.20 ±0.15 ±0.16 ±0.14 0.77% 0.77% 0.64% 4.52% 2.45% 1.95% 34.39 3.98 4.31 0.45 11.60% ± 12.50% ± 1.30% ± 92.40% ± 10.50% ± 11.30% ± 10:20 ±0.22 ±0.15 ±0.16 ±0.14 0.43% 0.46% 0.39% 4.75% 3.19% 3.44% 34.71 4.61 3.59 0.46 13.30% ± 10.30% ± 1.30% ± 128.60% ± 12.90% ± 10.00% ± 10:30 ±0.22 ±0.15 ±0.15 ±0.14 0.44% 0.45% 0.38% 6.88% 3.85% 2.97% 30.37 5.17 3.61 0.46 17.00% ± 11.90% ± 1.50% ± 143.30% ± 12.90% ± 9.00% ± 10:40 ±0.22 ±0.15 ±0.15 ±0.14 0.51% 0.51% 0.44% 7.38% 3.83% 2.65% 46.74 1.39 4.48 0.42 3.00% ± 9.60% ± 0.90% ± 31.00% ± 9.30% ± 29.90% ± 10:50 ±0.25 ±0.14 ±0.16 ±0.14 0.30% 0.34% 0.29% 3.27% 3.06% 10.22% 35.28 4.69 4.14 0.14 13.30% ± 11.70% ± 0.40% ± 113.20% ± 3.40% ± 3.00% ± 11:00 ±0.22 ±0.15 ±0.16 ±0.14 0.43% 0.44% 0.39% 5.55% 3.31% 2.92% 51.63 3.06 4.65 0.01 5.90% ± 9.00% ± 0.00% ± 65.80% ± 0.00% ± 0.00% ± 11:10 ±0.25 ±0.14 ±0.16 ±0.13 0.28% 0.31% 0.00% 3.80% 0.00% 0.00% 44.81 5.74 5.77 0.29 12.80% ± 12.90% ± 0.70% ± 99.60% ± 5.10% ± 5.10% ± 11:20 ±0.24 ±0.15 ±0.16 ±0.14 0.34% 0.36% 0.32% 3.80% 2.37% 2.36% 45.21 9.07 6.04 0.26 20.10% ± 13.40% ± 0.60% ± 150.20% ± 4.20% ± 2.80% ± 11:30 ±0.24 ±0.16 ±0.16 ±0.14 0.37% 0.36% 0.32% 4.78% 2.23% 1.48% 50.15 1.59 5.91 0.38 3.20% ± 11.80% ± 0.80% ± 26.80% ± 6.50% ± 24.10% ± 11:40 ±0.25 ±0.14 ±0.16 ±0.14 0.28% 0.32% 0.28% 2.46% 2.31% 8.81% 36.94 3.67 5.33 0.44 9.90% ± 14.40% ± 1.20% ± 68.80% ± 8.30% ± 12.00% ± 11:50 ±0.23 ±0.15 ±0.16 ±0.14 0.40% 0.44% 0.37% 3.41% 2.57% 3.73% 37.30 1.69 6.53 0.69 4.50% ± 17.50% ± 1.90% ± 25.80% ± 10.60% ± 41.00% ± 12:00 ±0.23 ±0.14 ±0.16 ±0.14 0.37% 0.45% 0.38% 2.23% 2.12% 8.80% 46.77 2.18 5.60 0.34 4.70% ± 12.00% ± 0.70% ± 39.00% ± 6.10% ± 15.70% ± 12:10 ±0.25 ±0.14 ±0.16 ±0.14 0.30% 0.35% 0.28% 2.75% 2.42% 6.30%

150

Table A-1. Continued Start Rhines Stadium Weimer Reitz 푆푡푎푑𝑖푢푚 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푆푡푎푑𝑖푢푚 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (cps) (cps) (cps) (cps) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푆푡푎푑𝑖푢푚 43.35 2.94 5.60 0.31 6.80% ± 12.90% ± 0.70% ± 52.50% ± 5.50% ± 10.40% ± 12:20 ±0.24 ±0.14 ±0.16 ±0.14 0.33% 0.37% 0.31% 2.96% 2.44% 4.64% 47.69 3.66 4.68 0.05 7.70% ± 9.80% ± 0.10% ± 78.10% ± 1.10% ± 1.40% ± 12:30 ±0.25 ±0.15 ±0.16 ±0.13 0.31% 0.33% 0.26% 4.05% 2.91% 3.70% 40.83 1.95 6.52 0.36 4.80% ± 16.00% ± 0.90% ± 29.90% ± 5.60% ± 18.60% ± 12:40 ±0.23 ±0.14 ±0.16 ±0.14 0.35% 0.41% 0.34% 2.27% 2.10% 7.09% 52.27 7.34 11.87 0.90 14.00% ± 22.70% ± 1.70% ± 61.80% ± 7.60% ± 12.30% ± 12:50 ±0.25 ±0.16 ±0.17 ±0.14 0.30% 0.35% 0.26% 1.59% 1.17% 1.90% 27.75 2.70 7.40 1.08 9.70% ± 26.70% ± 3.90% ± 36.40% ± 14.70% ± 40.20% ± 13:00 ±0.21 ±0.14 ±0.16 ±0.14 0.52% 0.62% 0.50% 2.09% 1.90% 5.54% 26.89 0.94 7.62 1.76 3.50% ± 28.30% ± 6.50% ± 12.30% ± 23.00% ± 187.00% ± 13:10 ±0.21 ±0.14 ±0.16 ±0.14 0.51% 0.65% 0.52% 1.82% 1.90% 31.14% 24.90 1.01 8.90 4.78 4.00% ± 35.80% ± 19.20% ± 11.30% ± 53.70% ± 475.50% ± 13:20 ±0.20 ±0.14 ±0.17 ±0.15 0.55% 0.73% 0.62% 1.56% 1.95% 66.64% 29.90 0.95 14.54 3.72 3.20% ± 48.60% ± 12.40% ± 6.50% ± 25.60% ± 391.50% ± 13:30 ±0.21 ±0.14 ±0.18 ±0.15 0.46% 0.70% 0.49% 0.94% 1.05% 58.62% 21.76 0.35 7.28 6.01 1.60% ± 33.40% ± 27.60% ± 4.70% ± 82.50% ± 1738.10% ± 13:40 ±0.20 ±0.14 ±0.16 ±0.15 0.63% 0.81% 0.74% 1.84% 2.79% 681.83% 79.05 2.55 6.91 0.67 3.20% ± 8.70% ± 0.80% ± 36.90% ± 9.70% ± 26.20% ± 13:50 ±0.29 ±0.14 ±0.16 ±0.14 0.18% 0.21% 0.16% 2.23% 2.00% 5.56% 10.53 1.15 15.95 16.39 11.00% ± 151.50% ± 155.70% ± 7.20% ± 102.70% ± 1421.70% ± 14:00 ±0.17 ±0.14 ±0.18 ±0.18 1.33% 3.04% 3.07% 0.87% 1.63% 170.75% 29.41 2.77 23.41 6.72 9.40% ± 79.60% ± 22.90% ± 11.80% ± 28.70% ± 242.50% ± 14:10 ±0.21 ±0.14 ±0.20 ±0.15 0.49% 0.89% 0.55% 0.62% 0.70% 13.67% 35.55 1.21 5.89 0.93 3.40% ± 16.60% ± 2.60% ± 20.50% ± 15.80% ± 77.20% ± 14:20 ±0.23 ±0.14 ±0.16 ±0.14 0.39% 0.46% 0.38% 2.41% 2.37% 14.43% 65.87 1.03 5.47 0.34 1.60% ± 8.30% ± 0.50% ± 18.80% ± 6.20% ± 32.90% ± 14:30 ±0.28 ±0.14 ±0.16 ±0.14 0.21% 0.24% 0.20% 2.58% 2.50% 13.93% 31.70 1.60 6.97 1.95 5.00% ± 22.00% ± 6.20% ± 23.00% ± 28.00% ± 122.00% ± 14:40 ±0.22 ±0.14 ±0.16 ±0.14 0.44% 0.53% 0.45% 2.07% 2.12% 13.79% 56.27 1.24 8.15 1.89 2.20% ± 14.50% ± 3.40% ± 15.20% ± 23.20% ± 152.30% ± 14:50 ±0.26 ±0.14 ±0.17 ±0.14 0.25% 0.30% 0.25% 1.72% 1.79% 20.39% 7.17 0.62 16.79 19.50 8.60% ± 234.10% ± 271.80% ± 3.70% ± 116.10% ± 3167.5% ± 15:00 ±0.16 ±0.14 ±0.19 ±0.19 1.91% 5.97% 6.75% 0.82% 1.69% 701% 14.74 1.28 40.32 15.19 8.70% ± 273.50% ± 103.00% ± 3.20% ± 37.70% ± 1184.10% ± 15:10 ±0.18 ±0.14 ±0.23 ±0.18 0.94% 3.74% 1.75% 0.35% 0.49% 128.37%

151

Table A-1. Continued Start Rhines Stadium Weimer Reitz 푆푡푎푑𝑖푢푚 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푆푡푎푑𝑖푢푚 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (cps) (cps) (cps) (cps) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푆푡푎푑𝑖푢푚 13.51 0.42 5.30 1.11 3.10% ± 39.20% ± 8.20% ± 7.80% ± 20.90% ± 266.20% ± 15:20 ±0.18 ±0.14 ±0.16 ±0.14 1.01% 1.28% 1.03% 2.55% 2.68% 92.96% 11.16 0.51 7.64 2.19 4.50% ± 68.40% ± 19.60% ± 6.60% ± 28.60% ± 433.10% ± 15:30 ±0.17 ±0.14 ±0.16 ±0.14 1.21% 1.82% 1.30% 1.78% 1.95% 119.90% 6.40 0.34 30.24 17.48 5.40% ± 472.80% ± 273.20% ± 1.10% ± 57.80% ± 5094.30% ± 15:40 ±0.16 ±0.14 ±0.21 ±0.18 2.14% 12.48% 7.50% 0.43% 0.72% 2012.26% 5.29 0.42 22.66 18.72 7.90% ± 428.50% ± 354.00% ± 1.80% ± 82.60% ± 4469.60% ± 15:50 ±0.16 ±0.14 ±0.20 ±0.18 2.57% 13.48% 11.25% 0.58% 1.09% 1447.93% 29.97 0.93 5.98 0.62 3.10% ± 20.00% ± 2.10% ± 15.50% ± 10.40% ± 67.20% ± 16:00 ±0.21 ±0.14 ±0.16 ±0.14 0.46% 0.55% 0.46% 2.33% 2.30% 17.78% 38.09 2.15 4.60 0.01 5.60% ± 12.10% ± 0.00% ± 46.80% ± 0.00% ± 0.00% ± 16:10 ±0.23 ±0.14 ±0.16 ±0.13 0.37% 0.42% 0.00% 3.45% 0.00% 0.00% 16.24 0.71 19.63 0.14 4.40% ± 120.90% ± 0.90% ± 3.60% ± 0.70% ± 19.90% ± 16:20 ±0.19 ±0.14 ±0.19 ±0.14 0.85% 1.82% 0.86% 0.69% 0.67% 19.46%

Table A-2. March 20th, 2019 10 minute averaged measurement 41Ar count rates and count rate ratios

Start Rhines Rhines Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (cps) 2 (cps) (cps) (cps) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 13.46 46.34 0.00 1.30 344.00% ± 0.00% ± 10.00% ± 0.00% ± 0.00% ± 2.80% ± 10:50 ±0.18 ±0.24 ±0.00 ±0.14 4.89% 0.00% 1.08% 0.00% 0.00% 0.30% 13.17 39.75 0.00 1.36 302.00% ± 0.00% ± 10.00% ± 0.00% ± 0.00% ± 3.40% ± 11:00 ±0.18 ±0.23 ±0.00 ±0.14 4.45% 0.00% 1.04% 0.00% 0.00% 0.35% 9.31 29.12 0.00 0.96 313.00% ± 0.00% ± 10.00% ± 0.00% ± 0.00% ± 3.30% ± 11:10 ±0.17 ±0.20 ±0.00 ±0.14 6.12% 0.00% 1.45% 0.00% 0.00% 0.47% 11.62 37.71 0.00 0.89 325.00% ± 0.00% ± 8.00% ± 0.00% ± 0.00% ± 2.40% ± 11:20 ±0.18 ±0.22 ±0.00 ±0.14 5.27% 0.00% 1.24% 0.00% 0.00% 0.37% 15.24 39.22 0.00 0.62 257.00% ± 0.00% ± 4.00% ± 0.00% ± 0.00% ± 1.60% ± 11:30 ±0.18 ±0.22 ±0.00 ±0.14 3.43% 0.00% 0.88% 0.00% 0.00% 0.35% 11.21 35.11 5.20 0.70 313.00% ± 46.00% ± 6.00% ± 675.40% ± 13.40% ± 2.00% ± 11:40 ±0.17 ±0.22 ±0.16 ±0.14 5.24% 1.57% 1.18% 20.92% 2.67% 0.39% 10.71 34.24 5.21 0.89 320.00% ± 49.00% ± 8.00% ± 657.30% ± 17.10% ± 2.60% ± 11:50 ±0.17 ±0.21 ±0.16 ±0.14 5.55% 1.68% 1.24% 20.34% 2.69% 0.40% 13.97 39.72 5.10 1.03 284.00% ± 36.00% ± 7.00% ± 779.50% ± 20.10% ± 2.60% ± 12:00 ±0.18 ±0.22 ±0.16 ±0.14 4.02% 1.21% 0.94% 24.50% 2.77% 0.35%

152

Table A-2. Continued Start Rhines Rhines Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (cps) 2 (cps) (cps) (cps) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 11.36 28.13 5.73 1.02 248.00% ± 50.00% ± 9.00% ± 490.60% ± 17.70% ± 3.60% ± 12:10 ±0.17 ±0.20 ±0.16 ±0.14 4.22% 1.59% 1.23% 14.08% 2.46% 0.49% 18.34 41.08 5.97 1.31 224.00% ± 33.00% ± 7.00% ± 688.00% ± 21.90% ± 3.20% ± 12:20 ±0.19 ±0.23 ±0.16 ±0.14 2.64% 0.95% 0.75% 18.81% 2.40% 0.34% 18.72 37.53 4.86 0.69 200.00% ± 26.00% ± 4.00% ± 771.90% ± 14.30% ± 1.80% ± 12:30 ±0.19 ±0.22 ±0.16 ±0.14 2.37% 0.88% 0.79% 25.33% 2.86% 0.36% 23.61 48.15 5.29 0.68 204.00% ± 22.00% ± 3.00% ± 910.10% ± 12.80% ± 1.40% ± 12:40 ±0.20 ±0.24 ±0.16 ±0.14 2.02% 0.68% 0.61% 27.57% 2.62% 0.28% 13.74 39.75 7.90 1.77 289.00% ± 57.00% ± 13.00% ± 503.20% ± 22.30% ± 4.40% ± 12:50 ±0.18 ±0.22 ±0.16 ±0.14 4.13% 1.41% 1.05% 10.88% 1.83% 0.35% 11.04 26.46 11.03 8.08 240.00% ± 100.00% ± 73.00% ± 239.90% ± 73.20% ± 30.50% ± 13:00 ±0.17 ±0.20 ±0.17 ±0.16 4.20% 2.22% 1.83% 4.16% 1.83% 0.64% 6.74 12.87 17.67 11.09 191.00% ± 262.00% ± 165.00% ± 72.80% ± 62.80% ± 86.20% ± 13:10 ±0.16 ±0.17 ±0.19 ±0.17 5.27% 6.94% 4.71% 1.23% 1.15% 1.72% 8.17 18.07 16.54 7.15 221.00% ± 202.00% ± 88.00% ± 109.30% ± 43.30% ± 39.60% ± 13:20 ±0.17 ±0.18 ±0.19 ±0.16 5.03% 4.71% 2.62% 1.64% 1.06% 0.95% 11.51 26.68 6.66 4.50 232.00% ± 58.00% ± 39.00% ± 400.40% ± 67.50% ± 16.80% ± 13:30 ±0.18 ±0.20 ±0.16 ±0.15 3.94% 1.66% 1.41% 10.16% 2.76% 0.57% 11.13 0.00 11.06 7.99 0.00% ± 99.00% ± 72.00% ± 0.00% ± 72.20% ± 0.00% ± 13:40 ±0.17 ±0.00 ±0.17 ±0.16 0.00% 2.19% 1.82% 0.00% 1.82% 0.00% 13.35 0.00 10.95 11.13 0.00% ± 82.00% ± 83.00% ± 0.00% ± 101.60% ± 0.00% ± 13:50 ±0.18 ±0.00 ±0.17 ±0.17 0.00% 1.70% 1.67% 0.00% 2.20% 0.00% 12.70 0.00 9.10 5.23 0.00% ± 72.00% ± 41.00% ± 0.00% ± 57.40% ± 0.00% ± 14:00 ±0.18 ±0.00 ±0.17 ±0.15 0.00% 1.67% 1.31% 0.00% 1.96% 0.00% 13.43 0.00 7.49 2.71 0.00% ± 56.00% ± 20.00% ± 0.00% ± 36.20% ± 0.00% ± 14:10 ±0.18 ±0.00 ±0.16 ±0.14 0.00% 1.44% 1.09% 0.00% 2.07% 0.00% 10.51 0.00 11.70 7.34 0.00% ± 111.00% ± 70.00% ± 0.00% ± 62.70% ± 0.00% ± 14:20 ±0.17 ±0.00 ±0.17 ±0.16 0.00% 2.46% 1.88% 0.00% 1.63% 0.00% 17.28 0.00 6.15 0.93 0.00% ± 36.00% ± 5.00% ± 0.00% ± 15.20% ± 0.00% ± 14:30 ±0.19 ±0.00 ±0.16 ±0.14 0.00% 1.02% 0.74% 0.00% 2.28% 0.00% 7.43 0.00 27.36 10.48 0.00% ± 369.00% ± 141.00% ± 0.00% ± 38.30% ± 0.00% ± 14:40 ±0.17 ±0.13 ±0.21 ±0.16 0.00% 8.68% 3.84% 0.00% 0.67% 0.00% 10.17 23.25 0.66 4.90 229.00% ± 7.00% ± 48.00% ± 3503.30% ± 737.70% ± 21.10% ± 14:50 ±0.17 ±0.19 ±0.15 ±0.15 4.31% 1.54% 1.68% 767.47% 163.06% 0.67% 13.21 36.05 0.00 2.22 273.00% ± 0.00% ± 17.00% ± 0.00% ± 0.00% ± 6.20% ± 15:00 ±0.18 ±0.22 ±0.00 ±0.14 4.06% 0.00% 1.11% 0.00% 0.00% 0.40%

153

Table A-2. Continued Start Rhines Rhines Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (cps) 2 (cps) (cps) (cps) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 13.68 25.51 0.00 6.27 186.00% ± 0.00% ± 46.00% ± 0.00% ± 0.00% ± 24.60% ± 15:10 ±0.18 ±0.20 ±0.00 ±0.15 2.84% 0.00% 1.28% 0.00% 0.00% 0.63% 7.97 21.42 7.29 6.01 269.00% ± 91.00% ± 75.00% ± 294.00% ± 82.40% ± 28.00% ± 15:20 ±0.17 ±0.19 ±0.16 ±0.15 6.10% 2.79% 2.47% 7.07% 2.79% 0.75% 2.82 3.52 51.83 15.54 125.00% ± 1836.00% ± 551.00% ± 6.80% ± 30.00% ± 441.60% ± 15:30 ±0.15 ±0.14 ±0.25 ±0.18 8.51% 100.12% 30.58% 0.28% 0.37% 18.83% 9.68 19.02 20.20 10.99 196.00% ± 209.00% ± 114.00% ± 94.20% ± 54.40% ± 57.80% ± 15:40 ±0.17 ±0.18 ±0.19 ±0.17 3.95% 4.20% 2.65% 1.28% 0.97% 1.04% 25.09 33.67 12.83 4.85 134.00% ± 51.00% ± 19.00% ± 262.50% ± 37.80% ± 14.40% ± 15:50 ±0.21 ±0.21 ±0.18 ±0.15 1.39% 0.82% 0.61% 3.99% 1.28% 0.45% 14.01 30.17 21.06 4.23 215.00% ± 150.00% ± 30.00% ± 143.20% ± 20.10% ± 14.00% ± 16:00 ±0.18 ±0.21 ±0.20 ±0.15 3.15% 2.39% 1.12% 1.65% 0.73% 0.50% 3.73 4.86 51.58 11.67 130.00% ± 1385.00% ± 313.00% ± 9.40% ± 22.60% ± 240.10% ± 16:10 ±0.16 ±0.15 ±0.25 ±0.17 6.72% 58.27% 13.83% 0.29% 0.34% 8.09% 3.04 4.14 40.98 14.32 136.00% ± 1350.00% ± 472.00% ± 10.10% ± 34.90% ± 345.70% ± 16:20 ±0.15 ±0.15 ±0.23 ±0.17 8.39% 68.85% 24.60% 0.36% 0.47% 12.87%

Table A-3. March 22nd, 2019 10 minute averaged measurement 41Ar count rates and count rate ratios

Start Rhines Rhines Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (cps) 2 (cps) (cps) (cps) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 3.24 ± 4.65 ± 37.15 ± 16.36 ± 143.53% ± 799.36% ± 44.05% ± 12.51% ± 44.05% ± 352.08% ± 10:30 0.15 0.15 0.22 0.18 8.24% 38.04% 2.13% 0.42% 0.55% 12.12% 3.37 ± 5.55 ± 45.19 ± 23.83 ± 164.69% ± 814.56% ± 52.74% ± 12.28% ± 52.74% ± 429.64% ± 10:40 0.15 0.15 0.24 0.19 8.73% 37.30% 2.44% 0.34% 0.51% 12.20% 0.86 ± 1.76 ± 58.34 ± 9.17 ± 204.09% ± 3324.09% ± 15.72% ± 3.01% ± 15.72% ± 522.45% ± 10:50 0.15 0.15 0.26 0.16 38.86% 565.41% 2.69% 0.26% 0.28% 45.69% 0.91 ± 1.98 ± 60.69 ± 7.39 ± 216.26% ± 3072.48% ± 12.18% ± 3.25% ± 12.18% ± 374.09% ± 11:00 0.15 0.15 0.27 0.16 38.29% 492.80% 1.97% 0.24% 0.26% 29.18% 0.45 ± 1.13 ± 71.57 ± 5.98 ± 252.90% ± 6335.97% ± 8.35% ± 1.58% ± 8.35% ± 529.03% ± 11:10 0.15 0.14 0.28 0.15 87.66% 2056.12% 2.72% 0.19% 0.21% 65.84% 0.00 ± 0.00 ± 53.82 ± 1.99 ± 0.00% ± 0.00% ± 3.69% ± 0.00% ± 3.69% ± 0.00% ± 11:20 0.00 0.00 0.25 0.14 0.00% 0.00% 0.12% 0.00% 0.26% 0.00% 0.00 ± 0.00 ± 64.60 ± 1.11 ± 0.00% ± 0.00% ± 1.71% ± 0.00% ± 1.71% ± 0.00% ± 11:30 0.00 0.00 0.27 0.14 0.00% 0.00% 0.15% 0.00% 0.21% 0.00% 154

Table A-3. Continued Start Rhines Rhines Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (cps) 2 (cps) (cps) (cps) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 0.00 ± 0.00 ± 53.76 ± 0.20 ± 0.00% ± 0.00% ± 0.37% ± 0.00% ± 0.37% ± 0.00% ± 11:40 0.00 0.00 0.25 0.13 0.00% 0.00% 0.00% 0.00% 0.25% 0.00% 0.00 ± 0.00 ± 51.66 ± 0.93 ± 0.00% ± 0.00% ± 1.80% ± 0.00% ± 1.80% ± 0.00% ± 11:50 0.00 0.00 0.25 0.14 0.00% 0.00% 0.00% 0.00% 0.26% 0.00% 0.00 ± 0.00 ± 67.13 ± 2.15 ± 0.00% ± 0.00% ± 3.20% ± 0.00% ± 3.20% ± 0.00% ± 12:00 0.00 0.00 0.28 0.14 0.00% 0.00% 0.00% 0.00% 0.21% 0.00% 0.00 ± 0.00 ± 32.99 ± 0.00 ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 12:10 0.00 0.00 0.22 0.13 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00 ± 0.00 ± 33.89 ± 0.11 ± 0.00% ± 0.00% ± 0.33% ± 0.00% ± 0.33% ± 0.00% ± 12:20 0.00 0.00 0.22 0.13 0.00% 0.00% 0.00% 0.00% 0.40% 0.00% 0.00 ± 0.00 ± 40.70 ± 0.00 ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 12:30 0.00 0.00 0.23 0.00 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00 ± 0.00 ± 47.81 ± 0.00 ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 12:40 0.00 0.00 0.24 0.00 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00 ± 0.00 ± 29.72 ± 0.00 ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 12:50 0.00 0.00 0.21 0.00 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00 ± 0.00 ± 32.39 ± 0.00 ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 13:00 0.00 0.00 0.22 0.00 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00 ± 0.00 ± 52.45 ± 0.00 ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 13:10 0.00 0.00 0.25 0.00 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00 ± 0.00 ± 38.64 ± 0.00 ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 13:20 0.00 0.00 0.23 0.00 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00 ± 0.00 ± 24.40 ± 0.00 ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 13:30 0.00 0.00 0.20 0.00 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00 ± 0.00 ± 62.19 ± 0.50 ± 0.00% ± 0.00% ± 0.81% ± 0.00% ± 0.81% ± 0.00% ± 13:40 0.00 0.00 0.27 0.14 0.00% 0.00% 0.00% 0.00% 0.22% 0.00% 0.00 ± 0.39 ± 47.43 ± 1.82 ± 0.00% ± 12102.93% 3.84% ± 0.83% ± 3.84% ± 464.46% ± 13:50 0.00 0.01 0.24 0.14 0.00% ± 0.00% 0.00% 0.00% 0.30% 0.00% 0.00 ± 0.00 ± 25.90 ± 0.00 ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 14:00 0.00 0.00 0.20 0.00 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00 ± 0.00 ± 39.10 ± 0.00 ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 14:10 0.00 0.00 0.23 0.00 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00 ± 0.00 ± 13.48 ± 0.00 ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 14:20 0.00 0.00 0.17 0.00 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00 ± 0.00 ± 50.59 ± 0.20 ± 0.00% ± 0.00% ± 0.39% ± 0.00% ± 0.39% ± 0.00% ± 14:30 0.00 0.00 0.25 0.13 0.00% 0.00% 0.00% 0.00% 0.27% 0.00%

155

Table A-3. Continued Start Rhines Rhines Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (cps) 2 (cps) (cps) (cps) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 0.00 ± 0.00 ± 54.73 ± 0.43 ± 0.00% ± 0.00% ± 0.78% ± 0.00% ± 0.78% ± 0.00% ± 14:40 0.00 0.00 0.26 0.14 0.00% 0.00% 0.00% 0.00% 0.25% 0.00% 0.00 ± 0.00 ± 29.70 ± 0.00 ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 14:50 0.00 0.00 0.21 0.13 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00 ± 0.00 ± 56.62 ± 0.01 ± 0.00% ± 0.00% ± 0.02% ± 0.00% ± 0.02% ± 0.00% ± 15:00 0.00 0.00 0.26 0.13 0.00% 0.00% 0.00% 0.00% 0.30% 0.00% 0.00 ± 0.00 ± 25.47 ± 0.00 ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 15:10 0.00 0.00 0.20 0.13 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00 ± 0.00 ± 14.93 ± 0.06 ± 0.00% ± 0.00% ± 0.43% ± 0.00% ± 0.43% ± 0.00% ± 15:20 0.00 0.00 0.18 0.13 0.00% 0.00% 0.00% 0.00% 0.91% 0.00% 0.00 ± 0.00 ± 25.59 ± 0.00 ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 15:30 0.00 0.00 0.20 0.00 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00 ± 0.00 ± 40.99 ± 0.41 ± 0.00% ± 0.00% ± 1.01% ± 0.00% ± 1.01% ± 0.00% ± 15:40 0.00 0.00 0.23 0.14 0.00% 0.00% 0.00% 0.00% 0.33% 0.00% 0.00 ± 0.00 ± 38.21 ± 0.88 ± 0.00% ± 0.00% ± 2.30% ± 0.00% ± 2.30% ± 0.00% ± 15:50 0.00 0.00 0.23 0.14 0.00% 0.00% 0.00% 0.00% 0.36% 0.00% 0.00 ± 0.00 ± 24.65 ± 0.00 ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 16:00 0.00 0.00 0.20 0.00 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00 ± 0.00 ± 48.59 ± 1.85 ± 0.00% ± 0.00% ± 3.81% ± 0.00% ± 3.81% ± 0.00% ± 16:10 0.00 0.00 0.25 0.14 0.00% 0.00% 0.00% 0.00% 0.29% 0.00% 0.00 ± 0.00 ± 31.18 ± 0.00 ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 16:20 0.00 0.00 0.21 0.00 0.00% 0.00% 0.00% 0.00% 0.00% 0.00%

Table A-4. UF 10 min averaged weather in-house Gaussian model May 8th, 2018 simulations

Start Rhines Stadium Weimer Reitz (F8 푆푡푎푑𝑖푢푚 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푆푡푎푑𝑖푢푚 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (F8 Tally) (F8 Tally) (F8 Tally) Tally) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푆푡푎푑𝑖푢푚 1.35E-07 ± 3.48E-08 ± 3.57E-08 ± 7.95E-09 ± 25.80% ± 26.40% ± 5.90% ± 97.50% ± 22.20% ± 22.80% ± 09:40 2.03E-10 5.22E-11 8.93E-11 1.43E-11 0.05% 0.08% 0.01% 0.28% 0.07% 0.05% 1.84E-07 ± 4.14E-08 ± 3.20E-08 ± 8.29E-09 ± 22.50% ± 17.40% ± 4.50% ± 129.50% ± 25.90% ± 20.00% ± 09:50 3.13E-10 6.21E-11 5.12E-11 1.66E-11 0.05% 0.04% 0.01% 0.28% 0.07% 0.05% 2.07E-07 ± 4.40E-08 ± 3.05E-08 ± 8.40E-09 ± 21.30% ± 14.70% ± 4.10% ± 144.40% ± 27.60% ± 19.10% ± 10:00 3.52E-10 6.60E-11 5.19E-11 1.51E-11 0.05% 0.04% 0.01% 0.33% 0.07% 0.04% 1.78E-07 ± 4.15E-08 ± 3.30E-08 ± 8.27E-09 ± 23.40% ± 18.60% ± 4.70% ± 125.80% ± 25.10% ± 19.90% ± 10:10 2.85E-10 1.33E-10 5.28E-11 1.57E-11 0.08% 0.04% 0.01% 0.45% 0.06% 0.07%

156

Table A-4. Continued Start Rhines Stadium Weimer Reitz (F8 푆푡푎푑𝑖푢푚 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푆푡푎푑𝑖푢푚 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (F8 Tally) (F8 Tally) (F8 Tally) Tally) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푆푡푎푑𝑖푢푚 7.41E-07 ± 2.74E-07 ± 1.63E-08 ± 9.27E-09 ± 37.00% ± 2.20% ± 1.30% ± 1684.30% 57.10% ± 3.40% ± 10:20 1.11E-08 1.32E-08 3.59E-11 1.67E-11 1.86% 0.03% 0.02% ± 80.77% 0.16% 0.16% 5.30E-07 ± 7.38E-08 ± 2.36E-08 ± 9.57E-09 ± 13.90% ± 4.50% ± 1.80% ± 312.30% ± 40.50% ± 13.00% ± 10:30 1.91E-09 1.11E-10 4.48E-11 1.82E-11 0.05% 0.02% 0.01% 0.76% 0.11% 0.03% 2.02E-07 ± 4.38E-08 ± 3.12E-08 ± 8.39E-09 ± 21.70% ± 15.50% ± 4.20% ± 140.20% ± 26.80% ± 19.10% ± 10:40 4.85E-10 7.01E-11 4.99E-11 1.51E-11 0.06% 0.04% 0.01% 0.32% 0.06% 0.05% 6.35E-07 ± 1.43E-07 ± 2.39E-08 ± 1.13E-08 ± 22.60% ± 3.80% ± 1.80% ± 600.30% ± 47.30% ± 7.90% ± 10:50 3.94E-09 2.29E-10 4.54E-11 2.03E-11 0.14% 0.02% 0.01% 1.49% 0.12% 0.02% 4.75E-07 ± 2.02E-07 ± 2.39E-08 ± 1.23E-08 ± 42.60% ± 5.00% ± 2.60% ± 848.40% ± 51.50% ± 6.10% ± 11:00 1.14E-09 3.64E-10 4.54E-11 7.63E-11 0.13% 0.02% 0.02% 2.21% 0.33% 0.04% 1.91E-07 ± 4.11E-08 ± 2.97E-08 ± 8.30E-09 ± 21.50% ± 15.50% ± 4.30% ± 138.40% ± 28.00% ± 20.20% ± 11:10 3.25E-10 6.17E-11 5.05E-11 1.58E-11 0.05% 0.04% 0.01% 0.31% 0.07% 0.05% 4.14E-07 ± 7.17E-08 ± 2.67E-08 ± 9.52E-09 ± 17.30% ± 6.40% ± 2.30% ± 268.80% ± 35.70% ± 13.30% ± 11:20 8.69E-10 1.15E-10 4.54E-11 3.90E-11 0.05% 0.02% 0.01% 0.63% 0.16% 0.06% 5.07E-08 ± 1.95E-08 ± 5.50E-08 ± 7.36E-09 ± 38.50% ± 108.30% ± 14.50% ± 35.50% ± 13.40% ± 37.70% ± 11:30 7.61E-11 3.90E-11 8.80E-11 1.47E-11 0.10% 0.24% 0.04% 0.09% 0.03% 0.11% 1.76E-07 ± 5.43E-08 ± 3.06E-08 ± 9.05E-09 ± 30.80% ± 17.30% ± 5.10% ± 177.50% ± 29.60% ± 16.70% ± 11:40 2.64E-10 7.60E-11 7.04E-11 1.54E-11 0.06% 0.05% 0.01% 0.48% 0.08% 0.04% 5.99E-08 ± 2.16E-08 ± 5.09E-08 ± 7.46E-09 ± 36.00% ± 85.00% ± 12.50% ± 42.40% ± 14.70% ± 34.60% ± 11:50 8.39E-11 3.46E-11 7.64E-11 1.57E-11 0.08% 0.17% 0.03% 0.09% 0.04% 0.09% 5.35E-07 ± 1.70E-07 ± 2.16E-08 ± 1.15E-08 ± 31.70% ± 4.00% ± 2.10% ± 785.40% ± 53.20% ± 6.80% ± 12:00 1.12E-09 2.72E-10 4.10E-11 1.96E-11 0.08% 0.01% 0.01% 1.95% 0.14% 0.02% 5.33E-08 ± 2.02E-08 ± 4.97E-08 ± 7.40E-09 ± 37.90% ± 93.30% ± 13.90% ± 40.60% ± 14.90% ± 36.60% ± 12:10 7.46E-11 3.43E-11 7.46E-11 3.70E-11 0.08% 0.19% 0.07% 0.09% 0.08% 0.19% 5.06E-08 ± 1.96E-08 ± 5.55E-08 ± 7.38E-09 ± 38.60% ± 109.60% ± 14.60% ± 35.30% ± 13.30% ± 37.70% ± 12:20 8.10E-11 5.10E-11 8.88E-11 1.55E-11 0.12% 0.25% 0.04% 0.11% 0.04% 0.13% 6.64E-08 ± 2.08E-07 ± 4.84E-08 ± 7.52E-09 ± 312.50% ± 72.90% ± 11.30% ± 428.80% ± 15.50% ± 3.60% ± 12:30 9.30E-11 6.24E-10 7.74E-11 1.65E-11 1.04% 0.15% 0.03% 1.46% 0.04% 0.01% 1.85E-07 ± 2.08E-07 ± 3.16E-08 ± 1.46E-08 ± 112.10% ± 17.10% ± 7.90% ± 656.90% ± 46.10% ± 7.00% ± 12:40 4.07E-10 3.54E-10 5.69E-11 2.34E-11 0.31% 0.05% 0.02% 1.63% 0.11% 0.02% 3.15E-08 ± 1.46E-08 ± 6.11E-08 ± 7.18E-09 ± 46.20% ± 193.90% ± 22.80% ± 23.80% ± 11.70% ± 49.20% ± 12:50 4.10E-11 2.34E-11 1.16E-10 1.29E-11 0.10% 0.45% 0.05% 0.06% 0.03% 0.12% 3.76E-07 ± 9.44E-08 ± 2.93E-08 ± 1.05E-08 ± 25.10% ± 7.80% ± 2.80% ± 322.00% ± 35.60% ± 11.10% ± 13:00 9.02E-10 1.42E-10 5.27E-11 1.79E-11 0.07% 0.02% 0.01% 0.75% 0.09% 0.03% 1.43E-08 ± 9.86E-09 ± 1.79E-07 ± 9.63E-09 ± 68.90% ± 1250.60% 67.30% ± 5.50% ± 5.40% ± 97.70% ± 13:10 2.00E-11 1.77E-11 3.04E-10 1.73E-11 0.16% ± 2.76% 0.15% 0.01% 0.01% 0.25%

157

Table A-4. Continued Start Rhines Stadium Weimer Reitz (F8 푆푡푎푑𝑖푢푚 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푆푡푎푑𝑖푢푚 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (F8 Tally) (F8 Tally) (F8 Tally) Tally) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푆푡푎푑𝑖푢푚 6.14E-07 ± 8.38E-08 ± 2.32E-08 ± 9.86E-09 ± 13.60% ± 3.80% ± 1.60% ± 360.70% ± 42.40% ± 11.80% ± 13:20 2.46E-09 1.34E-10 8.12E-11 1.77E-11 0.06% 0.02% 0.01% 1.39% 0.17% 0.03% 8.84E-08 ± 3.18E-08 ± 2.89E-08 ± 7.66E-09 ± 35.90% ± 32.70% ± 8.70% ± 109.70% ± 26.50% ± 24.10% ± 13:30 6.10E-10 4.77E-11 4.62E-11 1.46E-11 0.25% 0.23% 0.06% 0.24% 0.07% 0.06% 7.67E-08 ± 3.58E-07 ± 3.32E-08 ± 2.49E-08 ± 466.40% ± 43.30% ± 32.50% ± 1076.50% 75.10% ± 7.00% ± 13:40 1.15E-10 6.80E-10 5.98E-11 3.98E-11 1.13% 0.10% 0.07% ± 2.82% 0.18% 0.02% 1.89E-08 ± 1.16E-08 ± 1.29E-07 ± 8.35E-09 ± 61.20% ± 684.80% ± 44.20% ± 8.90% ± 6.40% ± 72.10% ± 13:50 4.35E-11 2.09E-11 2.06E-10 1.50E-11 0.18% 1.91% 0.13% 0.02% 0.02% 0.18% 2.07E-08 ± 1.15E-08 ± 7.98E-08 ± 7.72E-09 ± 55.30% ± 385.40% ± 37.30% ± 14.40% ± 9.70% ± 67.40% ± 14:00 3.11E-11 1.96E-11 1.28E-10 1.39E-11 0.13% 0.85% 0.09% 0.03% 0.02% 0.17% 4.24E-08 ± 1.74E-08 ± 5.50E-08 ± 7.16E-09 ± 41.10% ± 129.80% ± 16.90% ± 31.70% ± 13.00% ± 41.10% ± 14:10 5.94E-11 2.78E-11 9.35E-11 1.29E-11 0.09% 0.29% 0.04% 0.07% 0.03% 0.10% 6.18E-07 ± 1.83E-07 ± 1.86E-08 ± 1.16E-08 ± 29.70% ± 3.00% ± 1.90% ± 985.30% ± 62.10% ± 6.30% ± 14:20 1.42E-09 3.11E-10 4.09E-11 2.67E-11 0.08% 0.01% 0.01% 2.74% 0.20% 0.02% 1.57E-07 ± 3.74E-08 ± 3.02E-08 ± 7.89E-09 ± 23.80% ± 19.20% ± 5.00% ± 123.80% ± 26.10% ± 21.10% ± 14:30 2.36E-10 6.36E-11 5.44E-11 1.58E-11 0.05% 0.05% 0.01% 0.31% 0.07% 0.06% 8.82E-08 ± 3.27E-07 ± 3.54E-08 ± 2.36E-08 ± 370.10% ± 40.10% ± 26.80% ± 922.20% ± 66.70% ± 7.20% ± 14:40 1.23E-10 5.23E-10 6.02E-11 4.01E-11 0.79% 0.09% 0.06% 2.16% 0.16% 0.02% 1.65E-08 ± 1.08E-08 ± 1.58E-07 ± 8.91E-09 ± 65.50% ± 952.00% ± 53.80% ± 6.90% ± 5.70% ± 82.20% ± 14:50 2.64E-11 1.94E-11 2.69E-10 1.60E-11 0.16% 2.24% 0.13% 0.02% 0.01% 0.21% 2.00E-08 ± 1.19E-08 ± 1.09E-07 ± 7.85E-09 ± 59.60% ± 543.30% ± 39.20% ± 11.00% ± 7.20% ± 65.80% ± 15:00 3.00E-11 2.38E-11 1.74E-10 1.49E-11 0.15% 1.20% 0.10% 0.03% 0.02% 0.18% 6.82E-08 ± 2.36E-08 ± 4.39E-08 ± 7.37E-09 ± 34.60% ± 64.40% ± 10.80% ± 53.60% ± 16.80% ± 31.30% ± 15:10 9.55E-11 4.72E-11 7.02E-11 1.33E-11 0.08% 0.14% 0.02% 0.14% 0.04% 0.08% 3.75E-08 ± 1.66E-08 ± 6.39E-08 ± 7.35E-09 ± 44.30% ± 170.20% ± 19.60% ± 26.00% ± 11.50% ± 44.20% ± 15:20 5.25E-11 3.65E-11 9.59E-11 1.62E-11 0.12% 0.35% 0.05% 0.07% 0.03% 0.14% 2.41E-07 ± 6.13E-08 ± 3.02E-08 ± 9.19E-09 ± 25.50% ± 12.50% ± 3.80% ± 203.00% ± 30.40% ± 15.00% ± 15:30 3.86E-10 8.58E-11 5.13E-11 1.56E-11 0.05% 0.03% 0.01% 0.45% 0.07% 0.03% 9.97E-09 ± 8.98E-09 ± 5.10E-07 ± 1.69E-08 ± 90.00% ± 5118.60% 169.00% ± 1.80% ± 3.30% ± 187.70% ± 15:40 1.79E-11 1.62E-11 1.12E-09 2.70E-11 0.23% ± 14.54% 0.41% 0.01% 0.01% 0.45% 1.06E-08 ± 9.36E-09 ± 3.21E-07 ± 1.08E-08 ± 88.30% ± 3028.40% 101.80% ± 2.90% ± 3.40% ± 115.40% ± 15:50 1.59E-11 4.12E-11 6.10E-10 1.94E-11 0.41% ± 7.33% 0.24% 0.01% 0.01% 0.55% 7.78E-08 ± 2.51E-08 ± 4.50E-08 ± 7.58E-09 ± 32.30% ± 57.80% ± 9.70% ± 55.80% ± 16.90% ± 30.20% ± 16:00 1.17E-10 3.77E-11 7.20E-11 1.67E-11 0.07% 0.13% 0.03% 0.12% 0.05% 0.08% 3.24E-07 ± 5.64E-08 ± 2.67E-08 ± 8.91E-09 ± 17.40% ± 8.20% ± 2.80% ± 211.70% ± 33.40% ± 15.80% ± 16:10 6.48E-10 1.47E-10 4.54E-11 1.60E-11 0.06% 0.02% 0.01% 0.66% 0.08% 0.05%

158

Table A-4. Continued Start Rhines Stadium Weimer Reitz (F8 푆푡푎푑𝑖푢푚 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푆푡푎푑𝑖푢푚 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (F8 Tally) (F8 Tally) (F8 Tally) Tally) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푆푡푎푑𝑖푢푚 3.66E-07 ± 2.98E-07 ± 1.92E-08 ± 1.27E-08 ± 81.50% ± 5.30% ± 3.50% ± 1550.10% 65.90% ± 4.30% ± 16:20 6.95E-10 5.66E-10 3.84E-11 2.29E-11 0.22% 0.01% 0.01% ± 4.28% 0.18% 0.01%

Table A-5 UFTR 10 min averaged weather in-house Gaussian model March 20th, 2019 simulations

Start Rhines Rhines 2 Weimer Reitz (F8 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (F8 Tally) (F8 Tally) (F8 Tally) Tally) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 2.69E-07 ± 6.42E-07 ± 4.19E-08 ± 1.98E-08 ± 238.90% ± 15.60% ± 7.40% ± 1531.80% 47.30% ± 3.10% ± 11:00 5.11E-10 2.25E-09 5.87E-11 2.57E-11 0.95% 0.04% 0.02% ± 5.78% 0.09% 0.01% 2.83E-07 ± 7.14E-07 ± 4.37E-08 ± 2.26E-08 ± 252.10% ± 15.40% ± 8.00% ± 1633.90% 51.60% ± 3.20% ± 11:10 5.38E-10 1.93E-09 6.12E-11 2.94E-11 0.83% 0.04% 0.02% ± 4.97% 0.10% 0.01% 2.92E-07 ± 7.78E-07 ± 4.26E-08 ± 2.20E-08 ± 266.70% ± 14.60% ± 7.60% ± 1827.80% 51.80% ± 2.80% ± 11:20 5.26E-10 2.72E-09 8.52E-11 2.86E-11 1.05% 0.04% 0.02% ± 7.36% 0.12% 0.01% 2.96E-07 ± 5.70E-07 ± 4.49E-08 ± 2.20E-08 ± 192.40% ± 15.20% ± 7.40% ± 1269.50% 49.10% ± 3.90% ± 11:30 5.33E-10 2.00E-09 8.98E-11 2.86E-11 0.76% 0.04% 0.02% ± 5.12% 0.12% 0.01% 3.74E-07 ± 5.82E-07 ± 4.07E-08 ± 1.91E-08 ± 155.70% ± 10.90% ± 5.10% ± 1430.60% 46.90% ± 3.30% ± 11:40 7.11E-10 1.11E-09 6.51E-11 2.48E-11 0.42% 0.03% 0.01% ± 3.55% 0.10% 0.01% 1.76E-07 ± 3.47E-07 ± 5.45E-08 ± 3.39E-08 ± 196.70% ± 30.90% ± 19.20% ± 637.60% ± 62.20% ± 9.80% ± 11:50 3.17E-10 5.21E-10 7.09E-11 4.41E-11 0.46% 0.07% 0.04% 1.26% 0.11% 0.02% 1.94E-07 ± 3.79E-07 ± 5.63E-08 ± 3.15E-08 ± 195.10% ± 29.00% ± 16.20% ± 672.90% ± 56.00% ± 8.30% ± 12:00 3.49E-10 7.20E-10 7.32E-11 3.78E-11 0.51% 0.06% 0.04% 1.55% 0.10% 0.02% 2.49E-07 ± 7.87E-07 ± 4.67E-08 ± 2.45E-08 ± 316.20% ± 18.80% ± 9.90% ± 1684.20% 52.50% ± 3.10% ± 12:10 4.73E-10 1.39E-08 6.54E-11 3.19E-11 5.63% 0.04% 0.02% ± 29.92% 0.10% 0.06% 2.77E-07 ± 6.55E-07 ± 4.76E-08 ± 2.33E-08 ± 236.40% ± 17.20% ± 8.40% ± 1375.70% 48.90% ± 3.60% ± 12:20 6.93E-10 3.41E-09 6.66E-11 3.26E-11 1.36% 0.05% 0.02% ± 7.41% 0.10% 0.02% 1.40E-07 ± 2.00E-07 ± 6.38E-08 ± 4.46E-08 ± 142.20% ± 45.50% ± 31.80% ± 312.60% ± 69.90% ± 22.40% ± 12:30 2.52E-10 2.80E-10 8.29E-11 4.91E-11 0.33% 0.10% 0.07% 0.60% 0.12% 0.04% 6.85E-08 ± 6.47E-08 ± 8.73E-08 ± 1.51E-07 ± 94.50% ± 127.40% ± 220.00% ± 74.20% ± 172.60% ± 232.80% ± 12:40 1.64E-10 7.12E-11 1.22E-10 2.57E-10 0.25% 0.35% 0.65% 0.13% 0.38% 0.47% 5.77E-08 ± 4.81E-08 ± 1.15E-07 ± 2.74E-07 ± 83.40% ± 199.80% ± 475.40% ± 41.70% ± 237.90% ± 570.10% ± 12:50 1.21E-10 4.81E-11 2.19E-10 1.48E-09 0.19% 0.56% 2.75% 0.09% 1.36% 3.13% 6.21E-08 ± 5.35E-08 ± 1.16E-07 ± 2.69E-07 ± 86.20% ± 187.70% ± 434.20% ± 45.90% ± 231.30% ± 503.70% ± 13:00 1.24E-10 9.63E-11 1.62E-10 1.86E-09 0.23% 0.46% 3.11% 0.11% 1.63% 3.59% 1.85E-07 ± 3.27E-07 ± 5.85E-08 ± 3.30E-08 ± 177.30% ± 31.70% ± 17.90% ± 559.60% ± 56.40% ± 10.10% ± 13:10 3.33E-10 9.81E-10 8.19E-11 3.96E-11 0.62% 0.07% 0.04% 1.85% 0.10% 0.03%

159

Table A-5. Continued Start Rhines Rhines 2 Weimer Reitz (F8 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (F8 Tally) (F8 Tally) (F8 Tally) Tally) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 1.12E-07 ± 1.38E-07 ± 6.48E-08 ± 5.60E-08 ± 122.90% ± 57.80% ± 50.00% ± 212.80% ± 86.50% ± 40.60% ± 13:20 2.02E-10 1.79E-10 9.07E-11 6.72E-11 0.27% 0.13% 0.11% 0.41% 0.16% 0.07% 1.51E-07 ± 1.98E-07 ± 5.38E-08 ± 3.45E-08 ± 131.60% ± 35.70% ± 22.90% ± 368.30% ± 64.20% ± 17.40% ± 13:30 2.87E-10 2.77E-10 7.53E-11 4.14E-11 0.31% 0.08% 0.05% 0.73% 0.12% 0.03% 1.22E-07 ± 1.65E-07 ± 7.23E-08 ± 5.89E-08 ± 135.40% ± 59.20% ± 48.20% ± 228.70% ± 81.50% ± 35.60% ± 13:40 2.32E-10 2.15E-10 9.40E-11 7.66E-11 0.31% 0.14% 0.11% 0.42% 0.15% 0.07% 3.08E-07 ± 4.61E-07 ± 4.82E-08 ± 2.15E-08 ± 149.80% ± 15.70% ± 7.00% ± 957.00% ± 44.60% ± 4.70% ± 13:50 6.16E-10 1.80E-09 6.75E-11 2.80E-11 0.66% 0.04% 0.02% 3.96% 0.09% 0.02% 1.08E-07 ± 1.35E-07 ± 7.91E-08 ± 7.46E-08 ± 125.10% ± 73.30% ± 69.10% ± 170.60% ± 94.30% ± 55.30% ± 14:00 2.05E-10 1.76E-10 1.03E-10 1.04E-10 0.29% 0.17% 0.16% 0.31% 0.18% 0.11% 1.71E-07 ± 3.08E-07 ± 5.97E-08 ± 3.62E-08 ± 180.10% ± 34.90% ± 21.10% ± 516.50% ± 60.70% ± 11.70% ± 14:10 3.08E-10 4.93E-10 7.76E-11 4.34E-11 0.43% 0.08% 0.05% 1.06% 0.11% 0.02% 3.90E-08 ± 2.66E-08 ± 1.74E-07 ± 2.89E-07 ± 68.20% ± 445.20% ± 741.20% ± 15.30% ± 166.50% ± 1086.50% 14:20 9.36E-11 2.93E-11 2.44E-10 9.51E-09 0.18% 1.24% 24.44% 0.03% 5.47% ± 35.76% 1.52E-07 ± 2.44E-07 ± 6.50E-08 ± 4.25E-08 ± 160.30% ± 42.70% ± 27.90% ± 375.50% ± 65.30% ± 17.40% ± 14:30 2.89E-10 3.90E-10 8.45E-11 5.95E-11 0.40% 0.10% 0.07% 0.77% 0.12% 0.04% 3.01E-07 ± 4.80E-07 ± 4.68E-08 ± 2.16E-08 ± 159.80% ± 15.60% ± 7.20% ± 1025.30% 46.10% ± 4.50% ± 14:40 5.72E-10 1.15E-09 6.08E-11 2.81E-11 0.49% 0.04% 0.02% ± 2.80% 0.08% 0.01% 5.50E-08 ± 4.41E-08 ± 1.30E-07 ± 3.40E-07 ± 80.20% ± 235.70% ± 618.30% ± 34.00% ± 262.30% ± 771.00% ± 14:50 1.21E-10 4.85E-11 1.82E-10 4.45E-09 0.20% 0.62% 8.21% 0.06% 3.45% 10.14% 8.89E-08 ± 9.81E-08 ± 7.07E-08 ± 8.02E-08 ± 110.30% ± 79.50% ± 90.20% ± 138.70% ± 113.40% ± 81.80% ± 15:00 1.60E-10 1.18E-10 9.90E-11 1.04E-10 0.24% 0.18% 0.20% 0.26% 0.22% 0.14% 4.54E-08 ± 3.37E-08 ± 1.35E-07 ± 3.25E-07 ± 74.30% ± 296.40% ± 715.40% ± 25.10% ± 241.30% ± 962.70% ± 15:10 9.53E-11 3.37E-11 1.89E-10 4.62E-09 0.17% 0.75% 10.28% 0.04% 3.44% 13.73% 5.23E-08 ± 4.43E-08 ± 8.71E-08 ± 1.82E-07 ± 84.70% ± 166.50% ± 347.20% ± 50.90% ± 208.50% ± 410.10% ± 15:20 1.05E-10 4.87E-11 1.22E-10 3.09E-10 0.19% 0.41% 0.91% 0.09% 0.46% 0.83% 1.42E-07 ± 2.03E-07 ± 6.14E-08 ± 4.22E-08 ± 142.80% ± 43.20% ± 29.70% ± 330.60% ± 68.70% ± 20.80% ± 15:30 2.56E-10 3.25E-10 8.60E-11 5.06E-11 0.34% 0.10% 0.06% 0.70% 0.13% 0.04% 7.07E-08 ± 7.08E-08 ± 6.29E-08 ± 8.58E-08 ± 100.10% ± 89.00% ± 121.30% ± 112.50% ± 136.30% ± 121.20% ± 15:40 1.27E-10 8.50E-11 8.81E-11 1.12E-10 0.22% 0.20% 0.27% 0.21% 0.26% 0.21% 2.28E-08 ± 1.35E-08 ± 1.42E-07 ± 3.93E-08 ± 59.40% ± 623.40% ± 172.50% ± 9.50% ± 27.70% ± 290.60% ± 15:50 6.16E-11 1.76E-11 1.99E-10 4.72E-11 0.18% 1.89% 0.51% 0.02% 0.05% 0.52% 3.53E-08 ± 2.48E-08 ± 1.13E-07 ± 1.67E-07 ± 70.20% ± 319.70% ± 472.10% ± 22.00% ± 147.60% ± 672.50% ± 16:00 7.77E-11 2.98E-11 1.58E-10 3.34E-10 0.18% 0.83% 1.41% 0.04% 0.36% 1.57% 4.08E-08 ± 2.83E-08 ± 1.65E-07 ± 3.19E-07 ± 69.30% ± 404.50% ± 780.90% ± 17.10% ± 193.00% ± 1126.00% 16:10 1.47E-10 2.83E-11 2.31E-10 3.54E-09 0.26% 1.56% 9.12% 0.03% 2.16% ± 12.56%

160

Table A-5. Continued Start Rhines Rhines 2 Weimer Reitz (F8 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (F8 Tally) (F8 Tally) (F8 Tally) Tally) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 6.15E-08 ± 5.75E-08 ± 7.01E-08 ± 1.16E-07 ± 93.60% ± 114.00% ± 188.70% ± 82.10% ± 165.60% ± 201.60% ± 16:20 1.17E-10 6.90E-11 1.05E-10 1.62E-10 0.21% 0.28% 0.45% 0.16% 0.34% 0.37%

Table A-6 UF 10 min averaged weather in-house Gaussian model March 20th, 2019 simulations Start Rhines Rhines 2 Weimer Reitz (F8 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (F8 Tally) (F8 Tally) (F8 Tally) Tally) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 4.98E-08 ± 3.79E-08 ± 1.53E-07 ± 7.42E-07 ± 76.10% ± 306.70% ± 1489.00% 24.80% ± 485.40% ± 1957.60% 10:50 1.19E-10 3.94E-11 2.11E-10 1.36E-08 0.20% 0.85% ± 27.59% 0.04% 8.93% ± 36.00% 5.66E-08 ± 4.41E-08 ± 1.48E-07 ± 7.06E-07 ± 77.80% ± 262.10% ± 1247.90% 29.70% ± 476.20% ± 1603.40% 11:00 1.30E-10 4.41E-11 1.92E-10 1.27E-08 0.20% 0.69% ± 22.63% 0.05% 8.61% ± 28.86% 6.82E-08 ± 6.06E-08 ± 1.06E-07 ± 2.21E-07 ± 88.80% ± 155.50% ± 323.60% ± 57.10% ± 208.10% ± 364.50% ± 11:10 9.21E-10 2.42E-10 1.38E-10 3.54E-10 1.25% 2.11% 4.41% 0.24% 0.43% 1.57% 8.22E-08 ± 8.77E-08 ± 8.39E-08 ± 1.08E-07 ± 106.80% ± 102.10% ± 132.00% ± 104.50% ± 129.20% ± 123.60% ± 11:20 1.81E-10 9.65E-11 1.09E-10 1.40E-10 0.26% 0.26% 0.34% 0.18% 0.24% 0.21% 6.25E-08 ± 5.11E-08 ± 1.37E-07 ± 4.27E-07 ± 81.80% ± 218.90% ± 683.50% ± 37.40% ± 312.30% ± 835.60% ± 11:30 1.56E-10 5.11E-11 1.78E-10 5.55E-09 0.22% 0.62% 9.04% 0.06% 4.07% 10.90% 3.86E-08 ± 2.58E-08 ± 2.43E-07 ± 4.59E-07 ± 66.80% ± 629.60% ± 1188.40% 10.60% ± 188.70% ± 1779.10% 11:40 9.65E-11 2.84E-11 3.40E-10 8.72E-10 0.18% 1.80% ± 3.73% 0.02% 0.45% ± 3.91% 6.33E-08 ± 5.42E-08 ± 1.12E-07 ± 2.75E-07 ± 85.70% ± 177.10% ± 434.20% ± 48.40% ± 245.20% ± 506.80% ± 11:50 1.58E-10 5.42E-11 1.46E-10 5.23E-10 0.23% 0.50% 1.36% 0.08% 0.57% 1.09% 7.77E-08 ± 7.59E-08 ± 1.02E-07 ± 1.56E-07 ± 97.70% ± 131.80% ± 201.20% ± 74.10% ± 152.60% ± 206.00% ± 12:00 1.55E-10 8.35E-11 1.33E-10 2.96E-10 0.22% 0.31% 0.55% 0.13% 0.35% 0.45% 4.64E-07 ± 2.34E-07 ± 1.28E-07 ± 3.71E-07 ± 50.40% ± 27.70% ± 80.00% ± 182.10% ± 289.10% ± 158.70% ± 12:10 2.15E-08 1.14E-08 1.79E-10 1.81E-08 3.40% 1.28% 5.38% 8.94% 14.18% 10.96% 6.85E-08 ± 6.10E-08 ± 1.21E-07 ± 2.66E-07 ± 89.10% ± 176.30% ± 387.90% ± 50.50% ± 220.00% ± 435.50% ± 12:20 1.37E-10 6.10E-11 1.69E-10 5.32E-10 0.20% 0.43% 1.10% 0.09% 0.54% 0.98% 2.94E-08 ± 2.34E-08 ± 4.03E-08 ± 6.47E-08 ± 79.70% ± 137.30% ± 220.10% ± 58.10% ± 160.40% ± 276.20% ± 12:30 7.06E-11 2.81E-11 1.73E-10 8.41E-11 0.21% 0.68% 0.60% 0.26% 0.72% 0.49% 3.50E-08 ± 2.22E-08 ± 3.24E-07 ± 2.03E-07 ± 63.50% ± 925.00% ± 581.40% ± 6.90% ± 62.90% ± 915.90% ± 12:40 8.75E-11 2.66E-11 5.18E-10 3.05E-10 0.18% 2.75% 1.69% 0.01% 0.14% 1.76% 3.17E-08 ± 2.01E-08 ± 3.87E-07 ± 1.65E-07 ± 63.60% ± 1221.10% 521.80% ± 5.20% ± 42.70% ± 820.50% ± 12:50 9.19E-11 2.41E-11 6.58E-10 2.64E-10 0.20% ± 4.10% 1.72% 0.01% 0.10% 1.64% 3.09E-08 ± 1.91E-08 ± 4.11E-07 ± 1.24E-07 ± 62.00% ± 1330.90% 400.90% ± 4.70% ± 30.10% ± 646.60% ± 13:00 8.03E-11 2.29E-11 7.40E-10 1.74E-10 0.18% ± 4.21% 1.19% 0.01% 0.07% 1.20%

161

Table A-6. Continued Start Rhines Rhines 2 Weimer Reitz (F8 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (F8 Tally) (F8 Tally) (F8 Tally) Tally) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 5.26E-08 ± 3.89E-08 ± 3.81E-07 ± 7.18E-07 ± 74.00% ± 724.80% ± 1364.10% 10.20% ± 188.20% ± 1843.70% 13:10 1.10E-10 3.89E-11 1.81E-08 7.47E-09 0.17% 34.44% ± 14.48% 0.49% 9.16% ± 19.28% 3.91E-08 ± 2.63E-08 ± 1.98E-07 ± 2.75E-07 ± 67.20% ± 506.20% ± 703.90% ± 13.30% ± 139.10% ± 1047.40% 13:20 8.99E-11 2.63E-11 2.77E-10 5.23E-10 0.17% 1.36% 2.10% 0.02% 0.33% ± 2.25% 3.17E-08 ± 2.04E-08 ± 1.56E-07 ± 1.10E-07 ± 64.20% ± 493.20% ± 346.70% ± 13.00% ± 70.30% ± 539.70% ± 13:30 7.61E-11 2.65E-11 2.18E-10 1.54E-10 0.18% 1.37% 0.96% 0.02% 0.14% 1.03% 5.12E-08 ± 3.88E-08 ± 1.56E-07 ± 4.96E-07 ± 75.80% ± 303.70% ± 967.70% ± 25.00% ± 318.60% ± 1276.00% 13:40 1.08E-10 3.88E-11 2.18E-10 4.27E-09 0.18% 0.77% 8.58% 0.04% 2.77% ± 11.07% 7.43E-08 ± 7.00E-08 ± 1.12E-07 ± 2.04E-07 ± 94.10% ± 150.70% ± 274.80% ± 62.50% ± 182.30% ± 291.90% ± 13:50 1.49E-10 7.70E-11 1.46E-10 3.67E-10 0.22% 0.36% 0.74% 0.11% 0.40% 0.61% 3.26E-08 ± 2.07E-08 ± 3.73E-07 ± 1.73E-07 ± 63.60% ± 1143.80% 531.10% ± 5.60% ± 46.40% ± 835.00% ± 14:00 8.80E-11 2.69E-11 6.34E-10 2.60E-10 0.19% ± 3.65% 1.64% 0.01% 0.11% 1.66% 6.63E-08 ± 5.68E-08 ± 1.26E-07 ± 3.13E-07 ± 85.70% ± 189.90% ± 472.60% ± 45.10% ± 248.90% ± 551.40% ± 14:10 1.46E-10 5.68E-11 1.64E-10 1.97E-09 0.21% 0.49% 3.15% 0.07% 1.60% 3.52% 2.71E-08 ± 1.60E-08 ± 2.67E-07 ± 5.75E-08 ± 58.90% ± 986.20% ± 212.20% ± 6.00% ± 21.50% ± 360.10% ± 14:20 7.59E-11 2.24E-11 1.15E-08 7.48E-11 0.18% 42.36% 0.66% 0.26% 0.92% 0.69% 9.60E-08 ± 1.13E-07 ± 8.43E-08 ± 8.71E-08 ± 117.50% ± 87.80% ± 90.80% ± 133.80% ± 103.40% ± 77.30% ± 14:30 1.92E-10 1.24E-10 1.10E-10 1.13E-10 0.27% 0.21% 0.22% 0.23% 0.19% 0.13% 5.63E-08 ± 4.28E-08 ± 2.68E-07 ± 6.83E-07 ± 76.10% ± 475.40% ± 1213.60% 16.00% ± 255.30% ± 1594.60% 14:40 1.29E-10 5.14E-11 1.19E-08 1.48E-08 0.20% 21.16% ± 26.35% 0.71% 12.58% ± 34.52% 9.16E-08 ± 1.02E-07 ± 7.10E-08 ± 7.59E-08 ± 110.90% ± 77.60% ± 82.90% ± 142.90% ± 106.80% ± 74.80% ± 14:50 1.65E-10 1.22E-10 9.94E-11 9.87E-11 0.24% 0.18% 0.18% 0.26% 0.20% 0.13% 4.98E-08 ± 3.57E-08 ± 1.96E-07 ± 7.92E-07 ± 71.80% ± 393.00% ± 1591.00% 18.30% ± 404.90% ± 2215.70% 15:00 1.10E-10 3.57E-11 2.55E-10 9.98E-09 0.17% 1.01% ± 20.34% 0.03% 5.12% ± 28.04% 3.20E-08 ± 1.98E-08 ± 2.77E-07 ± 1.16E-07 ± 61.70% ± 866.20% ± 361.90% ± 7.10% ± 41.80% ± 586.40% ± 15:10 8.32E-11 2.18E-11 4.16E-10 1.51E-10 0.17% 2.60% 1.05% 0.01% 0.08% 1.00% 3.63E-08 ± 2.56E-08 ± 1.12E-07 ± 1.70E-07 ± 70.60% ± 308.60% ± 469.00% ± 22.90% ± 152.00% ± 664.60% ± 15:20 7.62E-11 3.07E-11 1.57E-10 3.23E-10 0.17% 0.78% 1.33% 0.04% 0.36% 1.49% 6.69E-08 ± 5.91E-08 ± 1.18E-07 ± 2.61E-07 ± 88.30% ± 175.70% ± 390.60% ± 50.20% ± 222.20% ± 442.30% ± 15:30 1.34E-10 6.50E-11 1.53E-10 4.96E-10 0.20% 0.42% 1.08% 0.09% 0.51% 0.97% 2.97E-08 ± 1.80E-08 ± 4.11E-07 ± 9.60E-08 ± 60.60% ± 1385.20% 323.20% ± 4.40% ± 23.30% ± 533.20% ± 15:40 7.72E-11 2.34E-11 6.99E-10 1.25E-10 0.18% ± 4.30% 0.94% 0.01% 0.05% 0.98% 3.99E-08 ± 2.80E-08 ± 1.27E-07 ± 2.24E-07 ± 70.20% ± 317.70% ± 560.40% ± 22.10% ± 176.40% ± 798.60% ± 15:50 5.15E-10 2.80E-11 1.78E-10 5.15E-10 0.91% 4.13% 7.36% 0.04% 0.47% 2.01% 2.93E-08 ± 1.76E-08 ± 3.25E-07 ± 8.21E-08 ± 60.00% ± 1107.10% 280.10% ± 5.40% ± 25.30% ± 467.00% ± 16:00 8.50E-11 2.29E-11 4.88E-10 1.07E-10 0.19% ± 3.62% 0.89% 0.01% 0.05% 0.86%

162

Table A-6. Continued Start Rhines Rhines 2 Weimer Reitz (F8 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (F8 Tally) (F8 Tally) (F8 Tally) Tally) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 3.03E-08 ± 1.85E-08 ± 3.98E-07 ± 1.05E-07 ± 60.90% ± 1313.70% 346.00% ± 4.60% ± 26.30% ± 567.90% ± 16:10 7.88E-11 2.22E-11 6.77E-10 1.37E-10 0.17% ± 4.08% 1.01% 0.01% 0.06% 1.00% 5.31E-08 ± 4.98E-08 ± 4.53E-08 ± 6.35E-08 ± 93.80% ± 85.30% ± 119.70% ± 109.90% ± 140.40% ± 127.70% ± 16:20 9.56E-11 1.20E-10 5.89E-11 9.53E-11 0.28% 0.19% 0.28% 0.30% 0.28% 0.36%

Table A-7 UFTR 10 min averaged weather in-house Gaussian model March 22nd, 2019 simulations Start Rhines Rhines 2 Weimer Reitz (F8 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (F8 Tally) (F8 Tally) (F8 Tally) Tally) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 2.15E-08 ± 1.51E-08 ± 4.56E-08 ± 5.01E-08 ± 70.30% ± 212.20% ± 232.80% ± 33.10% ± 109.70% ± 331.40% ± 10:30 9.25E-11 1.81E-11 5.47E-11 6.51E-11 0.31% 0.95% 1.05% 0.06% 0.19% 0.59% 2.49E-08 ± 9.39E-09 ± 1.19E-07 ± 8.67E-09 ± 37.70% ± 478.80% ± 34.80% ± 7.90% ± 7.30% ± 92.30% ± 10:40 5.98E-11 1.60E-11 5.36E-10 1.30E-11 0.11% 2.44% 0.10% 0.04% 0.03% 0.21% 2.03E-08 ± 1.08E-08 ± 1.63E-07 ± 1.92E-08 ± 53.30% ± 802.50% ± 94.70% ± 6.60% ± 11.80% ± 177.50% ± 10:50 5.28E-11 2.38E-11 2.28E-10 2.50E-11 0.18% 2.37% 0.27% 0.02% 0.02% 0.45% 2.10E-08 ± 1.05E-08 ± 2.00E-07 ± 1.68E-08 ± 50.20% ± 954.90% ± 80.10% ± 5.30% ± 8.40% ± 159.30% ± 11:00 5.46E-11 1.58E-11 3.00E-10 2.18E-11 0.15% 2.86% 0.23% 0.01% 0.02% 0.32% 2.35E-08 ± 9.68E-09 ± 1.92E-07 ± 1.11E-08 ± 41.10% ± 815.60% ± 47.10% ± 5.00% ± 5.80% ± 114.40% ± 11:10 6.11E-11 1.55E-11 2.88E-10 1.55E-11 0.13% 2.45% 0.14% 0.01% 0.01% 0.24% 2.28E-08 ± 9.57E-09 ± 1.56E-07 ± 1.08E-08 ± 41.90% ± 682.80% ± 47.40% ± 6.10% ± 6.90% ± 113.20% ± 11:20 5.47E-11 1.72E-11 2.34E-10 1.94E-11 0.13% 1.94% 0.14% 0.01% 0.02% 0.29%

Table A-8 UF 10 min averaged weather in-house Gaussian model March 22nd, 2019 simulations Start Rhines Rhines 2 Weimer Reitz (F8 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (F8 Tally) (F8 Tally) (F8 Tally) Tally) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 4.27E-08 ± 2.89E-08 ± 2.71E-07 ± 6.44E-07 ± 67.60% ± 634.20% ± 1507.10% 10.70% ± 237.60% ± 2230.60% 10:30 1.02E-10 3.18E-11 4.07E-10 1.10E-08 0.18% 1.80% ± 26.04% 0.02% 4.08% ± 38.18% 4.50E-08 ± 3.15E-08 ± 2.04E-07 ± 6.46E-07 ± 69.90% ± 453.50% ± 1433.80% 15.40% ± 316.20% ± 2050.80% 10:40 1.04E-10 3.15E-11 2.86E-10 1.10E-08 0.18% 1.22% ± 24.63% 0.03% 5.40% ± 34.92% 3.56E-08 ± 2.67E-08 ± 7.50E-08 ± 1.27E-07 ± 75.00% ± 210.80% ± 358.30% ± 35.60% ± 169.90% ± 478.00% ± 10:50 8.19E-11 2.67E-11 9.75E-11 1.91E-10 0.19% 0.56% 0.98% 0.06% 0.34% 0.86% 3.25E-08 ± 2.07E-08 ± 1.84E-07 ± 1.18E-07 ± 63.70% ± 565.30% ± 362.10% ± 11.30% ± 64.10% ± 568.30% ± 11:00 8.78E-11 5.59E-11 2.58E-10 1.65E-10 0.24% 1.72% 1.10% 0.03% 0.13% 1.73%

163

Table A-8. Continued Start Rhines Rhines 2 Weimer Reitz (F8 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (F8 Tally) (F8 Tally) (F8 Tally) Tally) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 2.38E-08 ± 1.33E-08 ± 3.53E-07 ± 3.41E-08 ± 55.80% ± 1484.90% 143.40% ± 3.80% ± 9.70% ± 256.90% ± 11:10 6.43E-11 2.26E-11 5.65E-10 1.74E-10 0.18% ± 4.65% 0.83% 0.01% 0.05% 1.38% 2.56E-08 ± 1.48E-08 ± 3.92E-07 ± 4.63E-08 ± 57.80% ± 1535.90% 181.20% ± 3.80% ± 11.80% ± 313.60% ± 11:20 6.91E-11 1.11E-10 6.66E-10 5.56E-11 0.46% ± 4.89% 0.53% 0.03% 0.02% 2.38%

Table A-9 November 7th, 2018 10 minute averaged measurement 41Ar count rates and count rate ratios Start Rhines Rhines2 Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (cps) (cps) (cps) (cps) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 13.00 2.22 17.31 0.56 17.10% ± 133.10% ± 4.30% ± 12.80% ± 3.20% ± 25.10% ± 12:30 ±0.17 ±0.14 ±0.18 ±0.14 1.11% 2.24% 1.06% 0.83% 0.79% 6.36% 24.36 3.61 12.24 0.77 14.80% ± 50.30% ± 3.20% ± 29.50% ± 6.30% ± 21.30% ± 12:40 ±0.20 ±0.15 ±0.17 ±0.14 0.61% 0.80% 0.57% 1.26% 1.13% 3.89% 8.64 1.57 21.33 0.51 18.20% ± 246.80% ± 5.90% ± 7.40% ± 2.40% ± 32.60% ± 12:50 ±0.16 ±0.14 ±0.19 ±0.14 1.65% 5.08% 1.57% 0.66% 0.64% 9.13% 56.63 6.97 26.00 1.19 12.30% ± 45.90% ± 2.10% ± 26.80% ± 4.60% ± 17.10% ± 13:00 ±0.26 ±0.15 ±0.20 ±0.14 0.28% 0.41% 0.24% 0.63% 0.54% 2.03% 12.48 4.97 15.14 1.16 39.80% ± 121.30% ± 9.30% ± 32.80% ± 7.60% ± 23.30% ± 13:10 ±0.17 ±0.15 ±0.17 ±0.14 1.32% 2.17% 1.12% 1.06% 0.91% 2.87% 19.10 3.57 13.18 0.78 18.70% ± 69.00% ± 4.10% ± 27.10% ± 5.90% ± 21.80% ± 13:20 ±0.19 ±0.15 ±0.17 ±0.14 0.78% 1.11% 0.72% 1.16% 1.04% 3.94% 12.64 4.19 40.38 1.23 33.10% ± 319.60% ± 9.80% ± 10.40% ± 3.10% ± 29.50% ± 13:30 ±0.17 ±0.15 ±0.23 ±0.14 1.25% 4.71% 1.11% 0.37% 0.35% 3.47% 22.80 3.10 4.51 0.52 13.60% ± 19.80% ± 2.30% ± 68.80% ± 11.40% ± 16.60% ± 13:40 ±0.19 ±0.14 ±0.15 ±0.14 0.64% 0.66% 0.61% 3.89% 3.03% 4.45% 33.89 3.79 8.08 0.54 11.20% ± 23.80% ± 1.60% ± 47.00% ± 6.70% ± 14.30% ± 13:50 ±0.22 ±0.15 ±0.15 ±0.14 0.44% 0.48% 0.40% 2.02% 1.69% 3.65% 7.34 1.89 57.59 1.33 25.70% ± 784.50% ± 18.10% ± 3.30% ± 2.30% ± 70.60% ± 14:00 ±0.16 ±0.14 ±0.26 ±0.14 1.99% 17.14% 1.93% 0.25% 0.24% 9.05% 43.36 7.46 12.84 1.22 17.20% ± 29.60% ± 2.80% ± 58.10% ± 9.50% ± 16.30% ± 14:10 ±0.24 ±0.16 ±0.17 ±0.14 0.37% 0.42% 0.32% 1.43% 1.09% 1.88% 34.10 4.85 5.24 0.42 14.20% ± 15.40% ± 1.20% ± 92.40% ± 8.00% ± 8.60% ± 14:20 ±0.22 ±0.15 ±0.15 ±0.14 0.45% 0.45% 0.39% 3.86% 2.61% 2.81% 28.13 4.23 14.63 0.96 15.00% ± 52.00% ± 3.40% ± 28.90% ± 6.60% ± 22.80% ± 14:30 ±0.21 ±0.15 ±0.17 ±0.14 0.53% 0.72% 0.49% 1.06% 0.95% 3.36% 15.22 3.97 19.03 1.30 26.10% ± 125.00% ± 8.50% ± 20.90% ± 6.80% ± 32.60% ± 14:40 ±0.18 ±0.15 ±0.18 ±0.14 1.01% 1.88% 0.91% 0.80% 0.73% 3.69% 164

Table A-9. Continued Start Rhines Rhines2 Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (cps) (cps) (cps) (cps) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 27.27 4.17 6.68 0.76 15.30% ± 24.50% ± 2.80% ± 62.40% ± 11.40% ± 18.20% ± 14:50 ±0.20 ±0.15 ±0.15 ±0.14 0.55% 0.58% 0.51% 2.61% 2.07% 3.35% 28.39 3.58 6.57 0.95 12.60% ± 23.20% ± 3.30% ± 54.40% ± 14.40% ± 26.40% ± 15:00 ±0.21 ±0.15 ±0.15 ±0.14 0.52% 0.56% 0.48% 2.54% 2.12% 3.99% 39.13 5.17 8.57 1.02 13.20% ± 21.90% ± 2.60% ± 60.20% ± 11.90% ± 19.80% ± 15:10 ±0.23 ±0.15 ±0.15 ±0.14 0.39% 0.41% 0.35% 2.06% 1.62% 2.73% 24.71 4.05 8.80 0.95 16.40% ± 35.60% ± 3.80% ± 46.00% ± 10.80% ± 23.40% ± 15:20 ±0.20 ±0.15 ±0.15 ±0.14 0.61% 0.68% 0.55% 1.85% 1.58% 3.50% 27.79 4.05 5.99 0.99 14.60% ± 21.50% ± 3.60% ± 67.60% ± 16.60% ± 24.60% ± 15:30 ±0.20 ±0.15 ±0.15 ±0.14 0.54% 0.56% 0.50% 2.97% 2.34% 3.53% 51.17 6.49 8.42 1.20 12.70% ± 16.50% ± 2.30% ± 77.10% ± 14.30% ± 18.50% ± 15:40 ±0.25 ±0.15 ±0.15 ±0.14 0.31% 0.31% 0.27% 2.30% 1.67% 2.18% 130.02 14.85 11.56 1.94 11.40% ± 8.90% ± 1.50% ± 128.40% ± 16.80% ± 13.10% ± 15:50 ±0.36 ±0.17 ±0.16 ±0.14 0.14% 0.13% 0.11% 2.34% 1.24% 0.96% 130.78 12.04 8.91 1.33 9.20% ± 6.80% ± 1.00% ± 135.10% ± 14.90% ± 11.00% ± 16:00 ±0.36 ±0.17 ±0.15 ±0.14 0.13% 0.12% 0.10% 2.99% 1.58% 1.16% 132.41 14.52 14.53 1.68 11.00% ± 11.00% ± 1.30% ± 99.90% ± 11.60% ± 11.60% ± 16:10 ±0.36 ±0.17 ±0.17 ±0.14 0.14% 0.13% 0.11% 1.67% 0.97% 0.97% 57.14 7.62 11.33 1.75 13.30% ± 19.80% ± 3.10% ± 67.20% ± 15.50% ± 23.00% ± 16:20 ±0.26 ±0.16 ±0.16 ±0.14 0.28% 0.29% 0.25% 1.68% 1.26% 1.90%

Table A-10. January 16th, 2019 10 minute averaged measurement 41Ar count rates and count rate ratios Start Rhines Rhines Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (cps) 2 (cps) (cps) (cps) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 14.81 29.33 25.48 13.72 198.00% ± 172.10% ± 92.70% ± 115.10% ± 53.90% ± 46.80% ± 10:50 ±0.18 ±0.21 ±0.21 ±0.17 2.80% 2.55% 1.63% 1.25% 0.81% 0.67% 4.81 5.40 106.90 14.89 112.20% ± 2220.70% ± 309.30% ± 5.10% ± 13.90% ± 275.70% ± 11:00 ±0.16 ±0.15 ±0.33 ±0.17 4.85% 72.80% 10.73% 0.15% 0.17% 8.45% 9.50 11.52 65.54 14.78 121.20% ± 689.60% ± 155.50% ± 17.60% ± 22.60% ± 128.30% ± 11:10 ±0.17 ±0.17 ±0.28 ±0.17 2.79% 12.61% 3.32% 0.27% 0.28% 2.40% 3.31 3.00 69.43 12.12 90.60% ± 2095.10% ± 365.70% ± 4.30% ± 17.50% ± 403.80% ± 11:20 ±0.15 ±0.15 ±0.28 ±0.17 6.13% 97.14% 17.64% 0.21% 0.25% 20.75% 8.42 18.43 67.34 12.36 218.90% ± 800.10% ± 146.80% ± 27.40% ± 18.40% ± 67.10% ± 11:30 ±0.17 ±0.18 ±0.28 ±0.17 4.84% 16.16% 3.53% 0.29% 0.26% 1.13%

165

Table A-10. Continued Start Rhines Rhines Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (cps) 2 (cps) (cps) (cps) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 13.12 29.88 16.86 13.59 227.70% ± 128.50% ± 103.60% ± 177.20% ± 80.60% ± 45.50% ± 11:40 ±0.18 ±0.21 ±0.20 ±0.17 3.46% 2.30% 1.92% 2.40% 1.39% 0.66% 9.90 17.39 21.76 21.30 175.70% ± 219.90% ± 215.20% ± 79.90% ± 97.90% ± 122.50% ± 11:50 ±0.17 ±0.18 ±0.20 ±0.19 3.52% 4.31% 4.16% 1.11% 1.27% 1.67% 15.09 26.69 15.95 27.49 176.90% ± 105.70% ± 182.30% ± 167.40% ± 172.40% ± 103.00% ± 12:00 ±0.18 ±0.20 ±0.20 ±0.20 2.52% 1.83% 2.58% 2.43% 2.49% 1.08% 9.45 15.50 61.49 17.53 164.00% ± 650.40% ± 185.50% ± 25.20% ± 28.50% ± 113.10% ± 12:10 ±0.17 ±0.18 ±0.27 ±0.18 3.47% 11.97% 3.83% 0.31% 0.32% 1.74% 5.97 6.24 65.79 36.10 104.50% ± 1101.30% ± 604.20% ± 9.50% ± 54.90% ± 578.40% ± 12:20 ±0.16 ±0.15 ±0.28 ±0.22 3.80% 29.88% 16.61% 0.24% 0.41% 14.68% 10.56 23.73 38.78 37.49 224.60% ± 367.10% ± 354.90% ± 61.20% ± 96.70% ± 158.00% ± 12:30 ±0.17 ±0.19 ±0.23 ±0.22 4.08% 6.37% 6.14% 0.62% 0.82% 1.59% 20.89 69.11 12.79 8.11 330.80% ± 61.20% ± 38.80% ± 540.50% ± 63.50% ± 11.70% ± 12:40 ±0.20 ±0.27 ±0.19 ±0.16 3.36% 1.08% 0.84% 8.42% 1.56% 0.23% 15.48 28.18 28.20 16.42 182.00% ± 182.10% ± 106.10% ± 99.90% ± 58.20% ± 58.30% ± 12:50 ±0.18 ±0.20 ±0.22 ±0.18 2.52% 2.58% 1.70% 1.06% 0.78% 0.76% 10.38 24.09 16.16 17.04 232.00% ± 155.60% ± 164.10% ± 149.00% ± 105.40% ± 70.70% ± 13:00 ±0.17 ±0.19 ±0.19 ±0.18 4.25% 3.18% 3.21% 2.15% 1.69% 0.94% 7.00 8.15 35.71 14.88 116.40% ± 510.30% ± 212.70% ± 22.80% ± 41.70% ± 182.70% ± 13:10 ±0.16 ±0.16 ±0.23 ±0.17 3.56% 12.32% 5.54% 0.47% 0.56% 4.20% 4.15 4.08 61.87 15.69 98.30% ± 1490.50% ± 378.10% ± 6.60% ± 25.40% ± 384.80% ± 13:20 ±0.16 ±0.15 ±0.27 ±0.18 5.17% 56.15% 14.77% 0.25% 0.31% 14.89% 16.24 33.79 13.77 12.16 208.10% ± 84.80% ± 74.90% ± 245.40% ± 88.30% ± 36.00% ± 13:30 ±0.18 ±0.21 ±0.19 ±0.17 2.71% 1.52% 1.34% 3.74% 1.73% 0.55% 3.99 3.83 78.36 13.32 96.00% ± 1961.90% ± 333.60% ± 4.90% ± 17.00% ± 347.60% ± 13:40 ±0.15 ±0.15 ±0.29 ±0.17 5.23% 76.45% 13.63% 0.19% 0.23% 14.04% 8.00 10.85 54.25 14.23 135.70% ± 678.40% ± 178.00% ± 20.00% ± 26.20% ± 131.20% ± 13:50 ±0.17 ±0.16 ±0.26 ±0.17 3.48% 14.39% 4.27% 0.32% 0.34% 2.55% 24.78 55.80 8.46 16.87 225.20% ± 34.10% ± 68.10% ± 659.40% ± 199.30% ± 30.20% ± 14:00 ±0.20 ±0.25 ±0.18 ±0.18 2.11% 0.80% 0.91% 14.71% 4.84% 0.35% 15.61 41.34 28.60 13.31 264.80% ± 183.20% ± 85.20% ± 144.50% ± 46.50% ± 32.20% ± 14:10 ±0.18 ±0.23 ±0.22 ±0.17 3.44% 2.56% 1.48% 1.36% 0.69% 0.45% 14.61 27.53 18.40 14.39 188.50% ± 126.00% ± 98.50% ± 149.60% ± 78.20% ± 52.30% ± 14:20 ±0.18 ±0.20 ±0.20 ±0.17 2.72% 2.09% 1.70% 1.97% 1.27% 0.74% 15.49 39.86 19.88 11.64 257.40% ± 128.40% ± 75.20% ± 200.50% ± 58.50% ± 29.20% ± 14:30 ±0.18 ±0.23 ±0.20 ±0.17 3.38% 2.00% 1.40% 2.33% 1.03% 0.45%

166

Table A-10. Continued Start Rhines Rhines Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (cps) 2 (cps) (cps) (cps) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 13.56 31.18 20.58 20.18 229.80% ± 151.70% ± 148.70% ± 151.50% ± 98.00% ± 64.70% ± 14:40 ±0.18 ±0.21 ±0.20 ±0.19 3.40% 2.50% 2.40% 1.81% 1.33% 0.74% 7.40 8.36 60.32 7.65 113.00% ± 815.50% ± 103.50% ± 13.90% ± 12.70% ± 91.60% ± 14:50 ±0.16 ±0.16 ±0.27 ±0.16 3.31% 18.42% 3.12% 0.27% 0.27% 2.57% 4.32 4.40 119.15 15.11 101.80% ± 2756.70% ± 349.60% ± 3.70% ± 12.70% ± 343.40% ± 15:00 ±0.16 ±0.15 ±0.35 ±0.18 5.05% 99.69% 13.24% 0.13% 0.15% 12.37% 19.91 38.46 18.00 19.86 193.20% ± 90.40% ± 99.70% ± 213.60% ± 110.30% ± 51.60% ± 15:10 ±0.19 ±0.22 ±0.20 ±0.19 2.18% 1.33% 1.35% 2.68% 1.60% 0.57% 23.38 35.30 69.50 10.35 151.00% ± 297.20% ± 44.30% ± 50.80% ± 14.90% ± 29.30% ± 15:20 ±0.20 ±0.22 ±0.29 ±0.16 1.60% 2.82% 0.80% 0.38% 0.24% 0.50% 14.82 38.16 37.89 8.23 116.40% ± 510.30% ± 212.70% ± 22.80% ± 41.70% ± 182.70% ± 15:30 ±0.18 ±0.22 ±0.23 ±0.16 3.56% 12.32% 5.54% 0.47% 0.56% 4.20% 7.38 16.55 53.47 27.80 257.60% ± 255.70% ± 55.50% ± 100.70% ± 21.70% ± 21.60% ± 15:40 ±0.16 ±0.18 ±0.26 ±0.20 3.50% 3.51% 1.27% 0.85% 0.44% 0.43% 10.71 19.39 20.64 12.18 224.10% ± 724.10% ± 376.50% ± 31.00% ± 52.00% ± 168.00% ± 15:50 ±0.17 ±0.18 ±0.20 ±0.17 5.52% 16.44% 8.79% 0.37% 0.46% 2.18% 20.61 52.43 13.24 6.18 181.10% ± 192.80% ± 113.80% ± 93.90% ± 59.00% ± 62.80% ± 16:00 ±0.19 ±0.25 ±0.19 ±0.17 3.38% 3.62% 2.41% 1.28% 1.00% 1.05% 10.94 19.97 75.85 23.02 254.40% ± 64.30% ± 30.00% ± 395.90% ± 46.60% ± 11.80% ± 16:10 ±0.17 ±0.19 ±0.29 ±0.24 2.69% 1.12% 0.87% 6.08% 1.44% 0.33% 12.65 41.70 20.62 12.62 182.60% ± 693.50% ± 210.50% ± 26.30% ± 30.40% ± 115.30% ± 16:20 ±0.18 ±0.23 ±0.20 ±0.20 3.35% 11.26% 3.97% 0.27% 0.34% 1.61%

Table A-11 January 17th, 2019 10 minute averaged measurement 41Ar count rates and count rate ratios

Start Rhines Rhines Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (cps) 2 (cps) (cps) (cps) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 67.98 88.19 7.29 0.54 129.70% ± 10.70% ± 0.80% ± 1209.30% ± 7.40% ± 0.60% ± 10:30 ±0.28 ±0.30 ±0.15 ±0.14 0.69% 0.22% 0.20% 25.25% 1.88% 0.15% 55.78 82.85 12.16 1.92 148.50% ± 21.80% ± 3.40% ± 681.10% ± 15.80% ± 2.30% ± 10:40 ±0.26 ±0.29 ±0.16 ±0.14 0.87% 0.31% 0.25% 9.53% 1.18% 0.17% 71.94 54.64 10.10 1.01 76.00% ± 14.00% ± 1.40% ± 541.00% ± 10.00% ± 1.80% ± 10:50 ±0.28 ±0.25 ±0.16 ±0.14 0.46% 0.23% 0.19% 8.95% 1.38% 0.25% 61.59 96.19 9.45 0.97 156.20% ± 15.30% ± 1.60% ± 1018.00% ± 10.30% ± 1.00% ± 11:00 ±0.27 ±0.31 ±0.16 ±0.14 0.85% 0.26% 0.23% 17.32% 1.47% 0.14%

167

Table A-11. Continued Start Rhines Rhines Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (cps) 2 (cps) (cps) (cps) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 45.00 76.32 17.57 2.95 169.60% ± 39.00% ± 6.60% ± 434.40% ± 16.80% ± 3.90% ± 11:10 ±0.24 ±0.29 ±0.18 ±0.14 1.11% 0.45% 0.32% 4.76% 0.84% 0.19% 30.33 10.95 16.95 1.07 36.10% ± 55.90% ± 3.50% ± 64.60% ± 6.30% ± 9.80% ± 11:20 ±0.21 ±0.16 ±0.18 ±0.14 0.59% 0.71% 0.45% 1.17% 0.81% 1.27% 53.15 10.82 17.20 0.57 20.40% ± 32.40% ± 1.10% ± 62.90% ± 3.30% ± 5.20% ± 11:30 ±0.25 ±0.16 ±0.18 ±0.14 0.32% 0.37% 0.26% 1.15% 0.80% 1.25% 23.21 32.27 43.79 6.90 139.10% ± 188.70% ± 29.70% ± 73.70% ± 15.80% ± 21.40% ± 11:40 ±0.20 ±0.21 ±0.24 ±0.15 1.50% 1.92% 0.71% 0.62% 0.36% 0.50% 48.98 50.46 18.23 5.90 103.00% ± 37.20% ± 12.10% ± 276.90% ± 32.40% ± 11.70% ± 11:50 ±0.25 ±0.24 ±0.18 ±0.15 0.72% 0.42% 0.32% 3.08% 0.89% 0.31% 44.41 11.82 0.00 1.20 26.60% ± 0.00% ± 2.70% ± 0.00% ± 0.00% ± 10.10% ± 12:00 ±0.24 ±0.16 ±0.00 ±0.14 0.40% 0.00% 0.31% 0.00% 0.00% 1.18% 55.05 24.27 0.00 0.68 44.10% ± 0.00% ± 1.20% ± 0.00% ± 0.00% ± 2.80% ± 12:10 ±0.26 ±0.20 ±0.00 ±0.14 0.41% 0.00% 0.24% 0.00% 0.00% 0.57% 48.74 46.54 0.00 4.18 95.50% ± 0.00% ± 8.60% ± 0.00% ± 0.00% ± 9.00% ± 12:20 ±0.25 ±0.24 ±0.00 ±0.15 0.69% 0.00% 0.31% 0.00% 0.00% 0.32% 83.01 46.09 0.00 5.12 55.50% ± 0.00% ± 6.20% ± 0.00% ± 0.00% ± 11.10% ± 12:30 ±0.30 ±0.24 ±0.00 ±0.15 0.35% 0.00% 0.18% 0.00% 0.00% 0.33% 73.13 28.54 0.00 0.62 39.00% ± 0.00% ± 0.80% ± 0.00% ± 0.00% ± 2.20% ± 12:40 ±0.29 ±0.20 ±0.00 ±0.14 0.32% 0.00% 0.18% 0.00% 0.00% 0.49% 38.85 20.65 0.00 1.70 53.10% ± 0.00% ± 4.40% ± 0.00% ± 0.00% ± 8.20% ± 12:50 ±0.23 ±0.19 ±0.00 ±0.14 0.57% 0.00% 0.36% 0.00% 0.00% 0.68% 35.51 10.91 0.00 1.47 30.70% ± 0.00% ± 4.10% ± 0.00% ± 0.00% ± 13.50% ± 13:00 ±0.22 ±0.16 ±0.00 ±0.14 0.49% 0.00% 0.39% 0.00% 0.00% 1.29% 29.16 15.81 0.00 1.43 54.20% ± 0.00% ± 4.90% ± 0.00% ± 0.00% ± 9.10% ± 13:10 ±0.21 ±0.17 ±0.00 ±0.14 0.71% 0.00% 0.48% 0.00% 0.00% 0.89% 9.67 10.58 0.00 4.08 109.50% ± 0.00% ± 42.20% ± 0.00% ± 0.00% ± 38.50% ± 13:20 ±0.17 ±0.16 ±0.00 ±0.15 2.54% 0.00% 1.69% 0.00% 0.00% 1.50% 74.28 23.59 0.00 3.43 31.80% ± 0.00% ± 4.60% ± 0.00% ± 0.00% ± 14.50% ± 13:30 ±0.29 ±0.19 ±0.00 ±0.14 0.29% 0.00% 0.20% 0.00% 0.00% 0.62% 23.06 4.59 0.00 1.09 19.90% ± 0.00% ± 4.70% ± 0.00% ± 0.00% ± 23.80% ± 13:40 ±0.20 ±0.21 ±0.08 ±0.14 0.91% 0.00% 0.60% 0.00% 0.00% 3.20% 66.52 10.20 25.17 0.82 15.30% ± 37.80% ± 1.20% ± 40.50% ± 3.20% ± 8.00% ± 13:50 ±0.28 ±0.16 ±0.20 ±0.14 0.24% 0.34% 0.20% 0.70% 0.54% 1.35% 3.23 4.59 78.32 4.84 142.10% ± 2426.30% ± 149.80% ± 5.90% ± 6.20% ± 105.40% ± 14:00 ±0.15 ±0.14 ±0.29 ±0.15 7.95% 115.23% 8.46% 0.18% 0.19% 4.52%

168

Table A-11. Continued Start Rhines Rhines Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (cps) 2 (cps) (cps) (cps) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 5.72 5.57 69.02 2.09 97.30% ± 1205.80% ± 36.50% ± 8.10% ± 3.00% ± 37.50% ± 14:10 ±0.16 ±0.14 ±0.28 ±0.14 3.66% 33.95% 2.67% 0.21% 0.20% 2.70% 6.82 6.54 70.64 1.63 96.00% ± 1036.10% ± 23.90% ± 9.30% ± 2.30% ± 24.90% ± 14:20 ±0.16 ±0.14 ±0.28 ±0.14 3.10% 25.01% 2.12% 0.21% 0.20% 2.20% 6.72 5.24 25.33 1.13 77.90% ± 376.60% ± 16.80% ± 20.70% ± 4.50% ± 21.60% ± 14:30 ±0.16 ±0.14 ±0.22 ±0.14 2.79% 9.64% 2.09% 0.58% 0.55% 2.70% 30.31 3.71 21.97 0.68 12.20% ± 72.50% ± 2.20% ± 16.90% ± 3.10% ± 18.40% ± 14:40 ±0.21 ±0.13 ±0.20 ±0.14 0.44% 0.85% 0.44% 0.62% 0.62% 3.75% 53.18 4.65 23.83 0.86 8.70% ± 44.80% ± 1.60% ± 19.50% ± 3.60% ± 18.40% ± 14:50 ±0.25 ±0.14 ±0.21 ±0.14 0.26% 0.45% 0.26% 0.60% 0.58% 3.00% 23.23 4.23 37.97 1.07 18.20% ± 163.50% ± 4.60% ± 11.10% ± 2.80% ± 25.30% ± 15:00 ±0.20 ±0.14 ±0.22 ±0.14 0.61% 1.70% 0.59% 0.36% 0.36% 3.36% 48.95 4.77 14.69 0.12 9.70% ± 30.00% ± 0.20% ± 32.50% ± 0.80% ± 2.40% ± 15:10 ±0.25 ±0.14 ±0.16 ±0.14 0.28% 0.37% 0.23% 1.00% 0.92% 2.77% 44.39 8.26 11.09 1.45 18.60% ± 25.00% ± 3.30% ± 74.50% ± 13.10% ± 17.60% ± 15:20 ±0.24 ±0.15 ±0.17 ±0.14 0.36% 0.41% 0.32% 1.80% 1.27% 1.72% 55.05 8.03 16.90 0.34 14.60% ± 30.70% ± 0.60% ± 47.50% ± 2.00% ± 4.20% ± 15:30 ±0.26 ±0.15 ±0.19 ±0.14 0.28% 0.37% 0.24% 1.03% 0.80% 1.67% 48.71 6.21 24.61 0.72 12.80% ± 50.50% ± 1.50% ± 25.20% ± 2.90% ± 11.60% ± 15:40 ±0.25 ±0.15 ±0.20 ±0.14 0.31% 0.49% 0.28% 0.63% 0.55% 2.21% 83.02 5.10 14.49 0.05 6.10% ± 17.50% ± 0.10% ± 35.20% ± 0.30% ± 0.90% ± 15:50 ±0.30 ±0.14 ±0.18 ±0.13 0.17% 0.23% 0.29% 1.07% 0.86% 2.58%

Table A-12 January 18th, 2019 10 minute averaged measurement 41Ar count rates and count rate ratios

Start Rhines Rhines Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (cps) 2 (cps) (cps) (cps) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 2.77 4.28 145.84 38.42 154.60% ± 5262.90% ± 1386.40% ± 2.90% ± 26.30% ± 897.00% ± 10:30 ±0.15 ±0.15 ±0.37 ±0.22 10.05% 288.20% 76.27% 0.10% 0.17% 31.97% 32.89 51.53 64.39 24.29 156.70% ± 195.80% ± 73.80% ± 80.00% ± 37.70% ± 47.10% ± 10:40 ±0.22 ±0.25 ±0.27 ±0.20 1.29% 1.54% 0.77% 0.51% 0.34% 0.44% 69.02 77.68 39.29 33.60 112.50% ± 56.90% ± 48.70% ± 197.70% ± 85.50% ± 43.30% ± 10:50 ±0.28 ±0.29 ±0.23 ±0.21 0.62% 0.41% 0.37% 1.37% 0.74% 0.32% 70.13 21.09 31.38 5.64 30.10% ± 44.70% ± 8.00% ± 67.20% ± 18.00% ± 26.70% ± 11:00 ±0.28 ±0.19 ±0.22 ±0.15 0.30% 0.36% 0.22% 0.77% 0.50% 0.75%

169

Table A-12. Continued Start Rhines Rhines Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (cps) 2 (cps) (cps) (cps) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 38.66 4.64 25.61 1.11 12.00% ± 66.20% ± 2.90% ± 18.10% ± 4.30% ± 23.90% ± 11:10 ±0.23 ±0.15 ±0.22 ±0.14 0.40% 0.69% 0.36% 0.61% 0.54% 3.08% 12.31 2.19 70.30 0.29 17.80% ± 571.30% ± 2.40% ± 3.10% ± 0.40% ± 13.40% ± 11:20 ±0.18 ±0.15 ±0.27 ±0.14 1.23% 8.46% 1.11% 0.21% 0.19% 6.27% 6.30 0.00 32.93 0.00 0.00% ± 522.80% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 11:30 ±0.16 ±0.00 ±0.23 ±0.00 0.00% 13.84% 0.00% 0.00% 0.00% 0.00% 12.91 1.29 38.98 0.00 10.00% ± 302.00% ± 0.00% ± 3.30% ± 0.00% ± 0.00% ± 11:40 ±0.18 ±0.15 ±0.23 ±0.00 1.20% 4.52% 0.00% 0.39% 0.00% 0.00% 82.50 31.98 33.76 0.36 38.80% ± 40.90% ± 0.40% ± 94.70% ± 1.10% ± 1.10% ± 11:50 ±0.30 ±0.21 ±0.22 ±0.14 0.29% 0.31% 0.15% 0.88% 0.42% 0.42% 6.92 5.06 78.49 4.69 73.00% ± 1133.50% ± 67.70% ± 6.40% ± 6.00% ± 92.70% ± 12:00 ±0.16 ±0.15 ±0.29 ±0.15 2.81% 26.94% 2.67% 0.20% 0.19% 4.07% 3.47 1.03 53.78 0.73 29.60% ± 1550.20% ± 20.90% ± 1.90% ± 1.40% ± 70.80% ± 12:10 ±0.15 ±0.17 ±0.25 ±0.14 5.02% 68.97% 4.05% 0.31% 0.26% 17.69% 6.89 9.47 91.35 5.81 137.50% ± 1326.20% ± 84.30% ± 10.40% ± 6.40% ± 61.30% ± 12:20 ±0.16 ±0.16 ±0.30 ±0.15 4.00% 31.60% 2.97% 0.18% 0.17% 1.91% 10.24 6.36 66.25 3.93 62.10% ± 647.00% ± 38.40% ± 9.60% ± 5.90% ± 61.90% ± 12:30 ±0.17 ±0.15 ±0.27 ±0.15 1.81% 11.11% 1.57% 0.23% 0.22% 2.74% 0.00 0.00 73.04 0.00 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 12:40 ±0.00 ±0.00 ±0.28 ±0.00 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00 0.00 169.04 0.00 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 12:50 ±0.00 ±0.00 ±0.39 ±0.00 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00 0.00 66.38 0.00 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 13:00 ±0.00 ±0.00 ±0.27 ±0.00 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00 0.00 73.57 0.00 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 13:10 ±0.00 ±0.00 ±0.28 ±0.00 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 9.87 3.70 45.04 0.60 37.50% ± 456.50% ± 6.10% ± 8.20% ± 1.30% ± 16.20% ± 13:20 ±0.17 ±0.15 ±0.24 ±0.14 1.69% 8.23% 1.39% 0.34% 0.30% 3.75% 4.31 0.57 45.94 0.08 13.20% ± 1066.90% ± 1.80% ± 1.20% ± 0.20% ± 13.30% ± 13:30 ±0.16 ±0.15 ±0.24 ±0.13 3.50% 38.99% 3.20% 0.32% 0.36% 23.88% 0.22 0.48 62.59 15.20 216.60% ± 28093.0% ± 6822.80% ± 0.80% ± 24.30% ± 3150.20% ± 13:40 ±0.14 ±0.00 ±0.27 ±0.18 0.00% 18192.05% 4418.82% 0.00% 0.30% 0.00% 2.56 0.00 17.90 0.00 0.00% ± 699.20% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 13:50 ±0.15 ±0.00 ±0.19 ±0.00 0.00% 41.95% 0.00% 0.00% 0.00% 0.00% 0.00 0.00 22.99 0.00 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 14:00 ±0.00 ±0.00 ±0.20 ±0.00 0.00% 0.00% 0.00% 0.00% 0.00% 0.00%

170

Table A-12. Continued Start Rhines Rhines Weimer Reitz 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (cps) 2 (cps) (cps) (cps) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 2.05 0.00 20.96 0.00 0.00% ± 1024.30% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 14:10 ±0.15 ±0.00 ±0.20 ±0.00 0.00% 75.51% 0.00% 0.00% 0.00% 0.00% 19.15 0.06 16.13 0.00 0.30% ± 84.20% ± 0.00% ± 0.40% ± 0.00% ± 0.00% ± 14:20 ±0.19 ±0.01 ±0.20 ±0.00 0.01% 1.34% 0.00% 0.00% 0.00% 0.00% 10.06 0.00 13.05 0.00 0.00% ± 129.70% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 14:30 ±0.17 ±0.00 ±0.23 ±0.00 0.00% 3.19% 0.00% 0.00% 0.00% 0.00% 17.88 0.00 13.36 0.00 0.00% ± 74.70% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 14:40 ±0.19 ±0.00 ±0.25 ±0.00 0.00% 1.60% 0.00% 0.00% 0.00% 0.00% 10.60 0.00 115.44 0.00 0.00% ± 1088.60% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 14:50 ±0.17 ±0.00 ±0.33 ±0.00 0.00% 17.91% 0.00% 0.00% 0.00% 0.00% 0.00 0.00 110.35 0.14 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.10% ± 0.00% ± 15:00 ±0.00 ±0.00 ±0.33 ±0.14 0.00% 0.00% 0.00% 0.00% 0.10% 0.00% 0.00 0.00 81.22 0.00 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 15:10 ±0.00 ±0.00 ±0.29 ±0.00 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00 0.00 137.75 0.20 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.10% ± 0.00% ± 15:20 ±0.00 ±0.00 ±0.36 ±0.14 0.00% 0.00% 0.00% 0.00% 0.07% 0.00% 4.07 0.00 29.39 0.00 0.00% ± 722.20% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 15:30 ±0.16 ±0.00 ±0.22 ±0.00 0.00% 28.05% 0.00% 0.00% 0.00% 0.00% 1.47 0.00 39.80 0.00 0.00% ± 2711.60% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 15:40 ±0.15 ±0.00 ±0.23 ±0.00 0.00% 273.75% 0.00% 0.00% 0.00% 0.00% 0.00 0.00 0.00 0.00 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 0.00% ± 15:50 ±0.00 ±0.00 ±0.00 ±0.00 0.00% 0.00% 0.00% 0.00% 0.00% 0.00%

Table A-13. UFTR 10 min averaged weather in-house Gaussian model November 7th, 2018 simulations

Start Rhines Rhines 2 Weimer Reitz (F8 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (F8 Tally) (F8 Tally) (F8 Tally) Tally) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 1.45E-08 ± 1.30E-08 ± 3.03E-07 ± 3.75E-07 ± 90.20% ± 2095.60% 2597.10% 4.30% ± 123.90% ± 2878.80% 12:30 3.92E-11 2.47E-11 6.06E-10 4.88E-10 0.30% ± 7.02% ± 7.75% 0.01% 0.30% ± 6.64% 1.37E-08 ± 1.24E-08 ± 4.31E-08 ± 9.17E-09 ± 90.80% ± 314.80% ± 67.00% ± 28.80% ± 21.30% ± 73.80% ± 12:40 4.52E-11 5.08E-10 1.90E-09 4.32E-10 3.72% 13.88% 3.16% 1.73% 1.37% 4.62% 1.53E-08 ± 1.27E-08 ± 5.17E-08 ± 1.02E-08 ± 82.80% ± 337.40% ± 66.70% ± 24.50% ± 19.80% ± 80.60% ± 12:50 5.51E-11 2.41E-11 9.31E-11 2.86E-11 0.34% 1.36% 0.30% 0.06% 0.07% 0.27% 1.27E-08 ± 1.18E-08 ± 4.42E-08 ± 8.79E-09 ± 92.40% ± 347.00% ± 69.10% ± 26.60% ± 19.90% ± 74.70% ± 13:00 5.08E-11 2.71E-11 1.37E-10 1.32E-11 0.43% 1.76% 0.30% 0.10% 0.07% 0.20%

171

Table A-13. Continued Start Rhines Rhines 2 Weimer Reitz (F8 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (F8 Tally) (F8 Tally) (F8 Tally) Tally) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 1.17E-08 ± 1.09E-08 ± 4.86E-08 ± 9.44E-09 ± 93.70% ± 416.20% ± 80.80% ± 22.50% ± 19.40% ± 86.30% ± 13:10 3.28E-11 1.96E-11 8.75E-11 1.23E-11 0.31% 1.38% 0.25% 0.06% 0.04% 0.19% 1.22E-08 ± 1.10E-08 ± 5.99E-08 ± 1.04E-08 ± 90.30% ± 489.90% ± 85.10% ± 18.40% ± 17.40% ± 94.30% ± 13:20 3.78E-11 2.09E-11 2.64E-09 5.08E-10 0.33% 21.66% 4.17% 0.81% 1.14% 4.62% 2.05E-08 ± 3.67E-07 ± 3.71E-08 ± 1.02E-08 ± 1792.60% 181.20% ± 49.90% ± 989.30% ± 27.60% ± 2.80% ± 13:30 6.56E-11 6.97E-10 8.53E-11 1.63E-11 ± 6.66% 0.71% 0.18% 2.95% 0.08% 0.01% 1.38E-08 ± 1.24E-08 ± 3.97E-08 ± 1.92E-07 ± 89.80% ± 287.00% ± 1386.40% 31.30% ± 483.00% ± 1544.00% 13:40 3.59E-11 2.36E-11 7.15E-11 2.50E-10 0.29% 0.91% ± 4.04% 0.08% 1.07% ± 3.56% 9.47E-09 ± 9.28E-09 ± 8.16E-08 ± 1.09E-08 ± 98.00% ± 861.40% ± 115.40% ± 11.40% ± 13.40% ± 117.80% ± 13:50 3.03E-11 1.76E-11 3.98E-09 1.74E-11 0.36% 42.14% 0.41% 0.56% 0.65% 0.29% 1.84E-08 ± 1.55E-08 ± 4.08E-08 ± 1.02E-08 ± 84.50% ± 222.10% ± 55.60% ± 38.00% ± 25.00% ± 65.80% ± 14:00 5.52E-11 2.95E-11 7.34E-11 1.43E-11 0.30% 0.78% 0.18% 0.10% 0.06% 0.16% 1.24E-08 ± 1.14E-08 ± 4.74E-08 ± 9.57E-09 ± 92.40% ± 383.30% ± 77.40% ± 24.10% ± 20.20% ± 83.80% ± 14:10 3.47E-11 2.28E-12 8.06E-11 1.34E-11 0.26% 1.25% 0.24% 0.04% 0.04% 0.12% 1.23E-08 ± 1.14E-08 ± 4.87E-08 ± 9.69E-09 ± 92.60% ± 395.30% ± 78.60% ± 23.40% ± 19.90% ± 84.90% ± 14:20 7.38E-12 5.32E-10 2.14E-09 6.78E-12 4.33% 17.42% 0.07% 1.50% 0.88% 3.97% 1.08E-08 ± 6.32E-07 ± 5.00E-08 ± 6.53E-07 ± 5826.20% 461.00% ± 6021.70% 1263.70% 1306.10% 103.40% ± 14:30 3.46E-11 1.20E-09 9.50E-11 2.76E-08 ± 21.78% 1.72% ± 255.89% ± 3.40% ± 55.17% 4.36% 1.35E-08 ± 1.23E-08 ± 4.34E-08 ± 9.56E-09 ± 90.80% ± 320.80% ± 70.60% ± 28.30% ± 22.00% ± 77.70% ± 14:40 3.92E-11 3.94E-11 1.22E-10 1.24E-11 0.39% 1.30% 0.23% 0.12% 0.07% 0.27% 1.37E-08 ± 3.69E-07 ± 3.17E-07 ± 3.41E-07 ± 2688.00% 2308.10% 2482.40% 116.50% ± 107.60% ± 92.40% ± 14:50 4.25E-11 6.27E-10 5.71E-10 4.77E-10 ± 9.52% ± 8.29% ± 8.47% 0.29% 0.25% 0.20% 1.26E-08 ± 1.16E-08 ± 4.24E-08 ± 9.36E-09 ± 92.20% ± 336.90% ± 74.50% ± 27.40% ± 22.10% ± 80.70% ± 15:00 2.52E-11 2.09E-11 7.63E-11 1.22E-11 0.25% 0.91% 0.18% 0.07% 0.05% 0.18% 1.25E-08 ± 1.17E-08 ± 4.68E-08 ± 9.66E-09 ± 93.10% ± 373.80% ± 77.10% ± 24.90% ± 20.60% ± 82.80% ± 15:10 3.75E-11 2.11E-11 8.42E-11 1.45E-11 0.33% 1.31% 0.26% 0.06% 0.05% 0.19% 1.33E-08 ± 1.20E-08 ± 3.95E-08 ± 9.25E-09 ± 90.50% ± 297.10% ± 69.60% ± 30.50% ± 23.40% ± 76.90% ± 15:20 4.12E-11 4.93E-10 7.11E-11 4.18E-10 3.72% 1.06% 3.15% 1.25% 1.06% 4.71% 4.17E-08 ± 1.79E-08 ± 4.26E-08 ± 6.95E-09 ± 42.90% ± 102.20% ± 16.70% ± 42.00% ± 16.30% ± 38.90% ± 15:30 1.42E-10 3.22E-11 8.09E-11 1.04E-11 0.17% 0.40% 0.06% 0.11% 0.04% 0.09% 3.26E-08 ± 1.59E-08 ± 4.71E-08 ± 6.61E-09 ± 48.80% ± 144.40% ± 20.30% ± 33.80% ± 14.10% ± 41.60% ± 15:40 1.01E-10 7.63E-10 2.29E-09 3.08E-10 2.35% 7.05% 0.95% 2.31% 0.95% 2.78% 6.17E-08 ± 2.18E-08 ± 4.09E-08 ± 7.33E-09 ± 35.40% ± 66.30% ± 11.90% ± 53.40% ± 17.90% ± 33.50% ± 15:50 1.91E-10 4.14E-11 7.77E-11 1.98E-11 0.13% 0.24% 0.05% 0.14% 0.06% 0.11% 6.92E-08 ± 2.33E-08 ± 4.50E-08 ± 7.38E-09 ± 33.60% ± 65.00% ± 10.70% ± 51.70% ± 16.40% ± 31.70% ± 16:00 2.01E-10 4.19E-11 8.10E-11 1.03E-11 0.11% 0.22% 0.03% 0.13% 0.04% 0.07%

172

Table A-13. Continued Start Rhines Rhines 2 Weimer Reitz (F8 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (F8 Tally) (F8 Tally) (F8 Tally) Tally) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 4.12E-08 ± 1.74E-08 ± 5.76E-08 ± 7.25E-09 ± 42.30% ± 139.70% ± 17.60% ± 30.30% ± 12.60% ± 41.60% ± 16:10 1.32E-10 3.13E-11 1.09E-10 1.02E-11 0.16% 0.52% 0.06% 0.08% 0.03% 0.10% 2.47E-08 ± 1.36E-08 ± 7.28E-08 ± 7.30E-09 ± 55.00% ± 294.30% ± 29.50% ± 18.70% ± 10.00% ± 53.70% ± 16:20 8.17E-11 2.51E-11 1.40E-10 1.05E-11 0.21% 1.13% 0.11% 0.05% 0.02% 0.13%

Table A-14. UF 10 min averaged weather in-house Gaussian model November 7th, 2018 Start Rhines Rhines 2 Weimer Reitz (F8 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (F8 Tally) (F8 Tally) (F8 Tally) Tally) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 9.74E-09 ± 9.29E-09 ± 4.26E-08 ± 4.90E-09 ± 95.40% ± 437.80% ± 50.40% ± 21.80% ± 11.50% ± 52.80% ± 12:30 3.21E-11 2.04E-11 8.52E-11 8.82E-12 0.38% 1.69% 0.19% 0.06% 0.03% 0.15% 1.40E-08 ± 1.24E-08 ± 3.67E-08 ± 8.31E-09 ± 88.60% ± 261.50% ± 59.20% ± 33.90% ± 22.70% ± 66.90% ± 12:40 4.76E-11 2.48E-11 6.97E-11 1.25E-11 0.35% 1.02% 0.22% 0.09% 0.05% 0.17% 8.41E-09 ± 8.41E-09 ± 6.13E-08 ± 7.64E-09 ± 99.90% ± 728.90% ± 90.90% ± 13.70% ± 12.50% ± 90.90% ± 12:50 2.69E-11 1.93E-11 1.16E-10 1.22E-11 0.39% 2.71% 0.33% 0.04% 0.03% 0.25% 3.94E-08 ± 2.46E-08 ± 3.40E-08 ± 1.15E-08 ± 62.40% ± 86.20% ± 29.30% ± 72.40% ± 34.00% ± 46.90% ± 13:00 1.30E-10 4.43E-11 5.78E-11 1.50E-11 0.23% 0.32% 0.10% 0.18% 0.07% 0.10% 8.15E-09 ± 8.19E-09 ± 6.71E-08 ± 7.84E-09 ± 100.50% ± 822.60% ± 96.20% ± 12.20% ± 11.70% ± 95.70% ± 13:10 2.53E-11 1.72E-11 1.27E-10 1.25E-11 0.38% 2.99% 0.34% 0.03% 0.03% 0.25% 1.07E-08 ± 1.01E-08 ± 4.60E-08 ± 8.33E-09 ± 94.50% ± 428.40% ± 77.60% ± 22.10% ± 18.10% ± 82.10% ± 13:20 3.42E-11 2.02E-11 8.74E-11 1.25E-11 0.36% 1.60% 0.28% 0.06% 0.04% 0.21% 1.03E-08 ± 9.94E-09 ± 6.57E-08 ± 1.06E-08 ± 96.60% ± 638.30% ± 102.60% ± 15.10% ± 16.10% ± 106.20% ± 13:30 2.88E-11 2.39E-11 1.18E-10 1.48E-11 0.36% 2.12% 0.32% 0.05% 0.04% 0.30% 2.75E-08 ± 5.09E-07 ± 3.38E-08 ± 1.07E-08 ± 1853.30% 123.00% ± 39.00% ± 1507.30% 31.70% ± 2.10% ± 13:40 9.90E-11 2.32E-08 6.08E-11 1.39E-11 ± 84.66% 0.49% 0.15% ± 68.72% 0.07% 0.10% 1.02E-08 ± 9.59E-09 ± 2.17E-07 ± 7.67E-09 ± 94.30% ± 2134.20% 75.40% ± 4.40% ± 3.50% ± 79.90% ± 13:50 1.52E-10 2.01E-11 1.05E-08 1.53E-11 1.41% ± 108.14% 1.13% 0.21% 0.17% 0.23% 7.52E-09 ± 7.86E-09 ± 8.10E-08 ± 6.95E-09 ± 104.50% ± 1077.60% 92.50% ± 9.70% ± 8.60% ± 88.50% ± 14:00 2.41E-11 1.89E-11 1.54E-10 1.18E-11 0.42% ± 4.01% 0.33% 0.03% 0.02% 0.26% 1.53E-08 ± 1.11E-08 ± 3.81E-08 ± 9.40E-09 ± 72.10% ± 248.10% ± 61.30% ± 29.10% ± 24.70% ± 85.00% ± 14:10 4.90E-11 4.44E-12 1.52E-10 2.16E-11 0.23% 1.28% 0.24% 0.12% 0.11% 0.20% 2.05E-08 ± 2.17E-07 ± 3.71E-08 ± 5.28E-09 ± 1059.50% 181.20% ± 25.80% ± 584.70% ± 14.20% ± 2.40% ± 14:20 6.77E-11 9.77E-09 7.79E-11 1.00E-11 ± 47.76% 0.71% 0.10% 26.35% 0.04% 0.11% 1.38E-08 ± 1.25E-08 ± 4.21E-08 ± 9.47E-09 ± 90.30% ± 305.10% ± 68.60% ± 29.60% ± 22.50% ± 76.00% ± 14:30 4.83E-11 2.38E-11 8.00E-11 1.42E-11 0.36% 1.21% 0.26% 0.08% 0.05% 0.18%

173

Table A-14. Continued Start Rhines Rhines 2 Weimer Reitz (F8 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (F8 Tally) (F8 Tally) (F8 Tally) Tally) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 9.99E-09 ± 9.69E-09 ± 5.70E-08 ± 9.49E-09 ± 97.10% ± 570.80% ± 95.00% ± 17.00% ± 16.60% ± 97.90% ± 14:40 3.80E-11 1.94E-11 1.03E-10 1.33E-11 0.42% 2.40% 0.38% 0.05% 0.04% 0.24% 1.44E-08 ± 1.29E-08 ± 3.99E-08 ± 9.42E-09 ± 89.50% ± 277.00% ± 65.40% ± 32.30% ± 23.60% ± 73.10% ± 14:50 4.61E-11 2.45E-11 7.58E-11 2.73E-11 0.33% 1.03% 0.28% 0.09% 0.08% 0.25% 1.48E-08 ± 1.31E-08 ± 3.89E-08 ± 9.35E-09 ± 88.70% ± 263.00% ± 63.30% ± 33.70% ± 24.10% ± 71.30% ± 15:00 4.88E-11 2.36E-11 7.78E-11 2.15E-11 0.33% 1.01% 0.25% 0.09% 0.07% 0.21% 1.32E-08 ± 1.12E-08 ± 3.39E-08 ± 7.76E-09 ± 85.30% ± 257.30% ± 58.90% ± 33.20% ± 22.90% ± 69.00% ± 15:10 4.49E-11 2.24E-11 7.12E-11 1.16E-11 0.33% 1.03% 0.22% 0.10% 0.06% 0.17% 1.87E-08 ± 1.62E-08 ± 3.81E-08 ± 1.01E-08 ± 86.60% ± 203.30% ± 53.80% ± 42.60% ± 26.40% ± 62.10% ± 15:20 5.98E-11 2.59E-11 7.24E-11 4.04E-11 0.31% 0.76% 0.28% 0.11% 0.12% 0.27% 3.61E-08 ± 2.59E-08 ± 3.00E-08 ± 1.14E-08 ± 71.60% ± 82.90% ± 31.50% ± 86.30% ± 38.00% ± 44.00% ± 15:30 1.19E-10 4.40E-11 5.40E-11 1.48E-11 0.27% 0.31% 0.11% 0.21% 0.08% 0.09% 6.28E-08 ± 3.12E-08 ± 3.12E-08 ± 1.20E-08 ± 49.70% ± 49.60% ± 19.20% ± 100.20% ± 38.70% ± 38.60% ± 15:40 2.45E-10 4.37E-11 5.30E-11 1.56E-11 0.21% 0.21% 0.08% 0.22% 0.08% 0.07% 8.04E-08 ± 3.88E-08 ± 2.58E-08 ± 1.31E-08 ± 48.30% ± 32.10% ± 16.30% ± 150.30% ± 50.80% ± 33.80% ± 15:50 2.65E-10 5.82E-11 4.64E-11 1.57E-11 0.17% 0.12% 0.06% 0.35% 0.11% 0.06% 5.39E-08 ± 3.22E-08 ± 2.84E-08 ± 1.22E-08 ± 59.80% ± 52.70% ± 22.70% ± 113.50% ± 43.10% ± 38.00% ± 16:00 1.67E-10 2.35E-10 5.11E-11 1.46E-11 0.47% 0.19% 0.08% 0.85% 0.09% 0.28% 1.97E-07 ± 4.97E-08 ± 3.05E-08 ± 1.41E-08 ± 25.20% ± 15.40% ± 7.10% ± 163.00% ± 46.30% ± 28.40% ± 16:10 3.94E-10 6.46E-11 4.88E-11 1.69E-11 0.06% 0.04% 0.02% 0.34% 0.09% 0.05% 2.20E-07 ± 5.36E-08 ± 3.10E-08 ± 1.46E-08 ± 24.40% ± 14.10% ± 6.60% ± 172.70% ± 47.00% ± 27.20% ± 16:20 3.96E-10 9.11E-11 6.20E-11 1.75E-11 0.06% 0.04% 0.01% 0.45% 0.11% 0.06%

Table A-15. UF 10 min averaged weather in-house Gaussian model January 16th, 2019 simulations Start Rhines Rhines 2 Weimer Reitz (F8 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (F8 Tally) (F8 Tally) (F8 Tally) Tally) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 4.65E-08 ± 3.37E-08 ± 1.69E-07 ± 5.09E-07 ± 72.50% ± 364.20% ± 1094.10% 19.90% ± 300.40% ± 1508.20% 10:50 1.02E-10 3.37E-11 2.37E-10 6.31E-09 0.18% 0.95% ± 13.79% 0.03% 3.76% ± 18.79% 5.01E-08 ± 3.72E-08 ± 1.65E-07 ± 4.60E-07 ± 74.30% ± 329.30% ± 917.20% ± 22.60% ± 278.50% ± 1234.80% 11:00 1.05E-10 4.09E-11 2.81E-10 1.50E-08 0.18% 0.89% 29.99% 0.05% 9.10% ± 40.33% 5.84E-08 ± 4.87E-08 ± 1.15E-07 ± 3.18E-07 ± 83.40% ± 196.50% ± 544.60% ± 42.40% ± 277.10% ± 653.30% ± 11:10 1.34E-10 6.33E-11 4.91E-09 9.03E-09 0.22% 8.42% 15.52% 1.81% 14.18% 18.56% 3.83E-08 ± 2.55E-08 ± 2.63E-07 ± 4.81E-07 ± 66.60% ± 686.20% ± 1256.20% 9.70% ± 183.10% ± 1886.30% 11:20 9.96E-11 3.06E-11 4.21E-10 6.01E-09 0.19% 2.10% ± 16.03% 0.02% 2.30% ± 23.69% 3.37E-08 ± 2.21E-08 ± 2.07E-07 ± 8.40E-07 ± 65.60% ± 613.10% ± 2493.00% 10.70% ± 406.60% ± 3801.10% 11:30 9.44E-11 3.09E-11 3.52E-10 9.66E-09 0.21% 2.01% ± 29.50% 0.02% 4.72% ± 44.03% 174

Table A-15. Continued Start Rhines Rhines 2 Weimer Reitz (F8 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (F8 Tally) (F8 Tally) (F8 Tally) Tally) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 3.10E-08 ± 2.00E-08 ± 3.45E-07 ± 2.25E-07 ± 64.70% ± 1114.10% 726.30% ± 5.80% ± 65.20% ± 1122.60% 11:40 9.61E-11 2.80E-11 8.00E-09 4.28E-10 0.22% ± 26.05% 2.64% 0.13% 1.52% ± 2.66% 3.67E-08 ± 2.40E-08 ± 2.26E-07 ± 2.23E-07 ± 65.60% ± 615.50% ± 607.50% ± 10.70% ± 98.70% ± 926.20% ± 11:50 8.44E-11 2.88E-11 3.39E-10 3.35E-10 0.17% 1.69% 1.67% 0.02% 0.21% 1.78% 3.36E-08 ± 2.22E-08 ± 2.33E-07 ± 4.94E-07 ± 66.10% ± 692.10% ± 1470.60% 9.50% ± 212.50% ± 2226.40% 12:00 9.07E-11 2.89E-11 3.96E-10 2.17E-09 0.20% 2.21% ± 7.59% 0.02% 1.00% ± 10.21% 3.47E-08 ± 2.32E-08 ± 2.42E-07 ± 4.83E-07 ± 67.00% ± 698.30% ± 1391.50% 9.60% ± 199.30% ± 2078.20% 12:10 9.02E-11 2.78E-11 3.87E-10 1.79E-09 0.19% 2.13% ± 6.29% 0.02% 0.80% ± 8.10% 1.28E-07 ± 1.93E-07 ± 7.14E-08 ± 5.48E-08 ± 151.30% ± 55.90% ± 42.90% ± 270.60% ± 76.80% ± 28.40% ± 12:20 4.22E-10 2.70E-10 9.28E-11 7.67E-11 0.54% 0.20% 0.15% 0.52% 0.15% 0.06% 2.59E-07 ± 8.46E-07 ± 4.54E-08 ± 2.37E-08 ± 326.90% ± 17.60% ± 9.10% ± 1861.40% 52.10% ± 2.80% ± 12:30 5.18E-10 2.96E-08 6.36E-11 3.32E-11 11.45% 0.04% 0.02% ± 65.27% 0.10% 0.10% 1.29E-07 ± 1.97E-07 ± 7.15E-08 ± 5.41E-08 ± 152.00% ± 55.30% ± 41.80% ± 274.80% ± 75.60% ± 27.50% ± 12:40 2.45E-10 2.76E-10 9.30E-11 8.66E-11 0.36% 0.13% 0.10% 0.53% 0.16% 0.06% 1.01E-07 ± 2.99E-08 ± 1.92E-07 ± 4.30E-07 ± 29.60% ± 189.80% ± 425.40% ± 15.60% ± 224.20% ± 1438.10% 12:50 4.60E-09 3.29E-11 2.88E-10 5.93E-09 1.35% 8.66% 20.26% 0.03% 3.11% ± 19.91% 3.08E-08 ± 1.95E-08 ± 2.13E-07 ± 4.93E-07 ± 63.20% ± 690.80% ± 1602.30% 9.20% ± 232.00% ± 2534.00% 13:00 9.55E-11 2.73E-11 3.83E-10 3.35E-09 0.22% 2.48% ± 11.96% 0.02% 1.63% ± 17.55% 4.97E-08 ± 3.61E-08 ± 5.56E-07 ± 6.01E-07 ± 72.70% ± 1119.40% 1210.70% 6.50% ± 108.20% ± 1666.30% 13:10 1.19E-10 3.61E-11 2.67E-08 9.98E-09 0.19% ± 53.77% ± 20.28% 0.31% 5.49% ± 27.69% 2.03E-08 ± 9.37E-09 ± 2.31E-06 ± 2.36E-08 ± 46.10% ± 11365.7% 116.00% ± 0.40% ± 1.00% ± 251.70% ± 13:20 6.90E-11 1.78E-11 3.23E-08 3.30E-11 0.18% ± 163.94% 0.43% 0.01% 0.01% 0.59% 3.00E-08 ± 1.90E-08 ± 4.21E-07 ± 1.63E-07 ± 63.30% ± 1401.40% 542.90% ± 4.50% ± 38.70% ± 857.30% ± 13:30 8.10E-11 4.56E-11 1.09E-09 2.93E-10 0.23% ± 5.26% 1.76% 0.02% 0.12% 2.57% 3.63E-08 ± 2.42E-08 ± 1.71E-07 ± 9.23E-07 ± 66.70% ± 471.90% ± 2542.80% 14.10% ± 538.80% ± 3813.30% 13:40 1.09E-10 3.39E-11 2.91E-10 2.51E-08 0.22% 1.62% ± 69.58% 0.03% 14.71% ± 103.88% 5.56E-08 ± 4.60E-08 ± 9.75E-08 ± 3.28E-07 ± 82.80% ± 175.40% ± 589.50% ± 47.20% ± 336.10% ± 712.20% ± 13:50 1.28E-10 5.52E-11 1.56E-10 7.48E-09 0.21% 0.49% 13.52% 0.09% 7.69% 16.28% 3.20E-08 ± 2.03E-08 ± 4.21E-07 ± 1.65E-07 ± 63.40% ± 1316.00% 514.60% ± 4.80% ± 39.10% ± 811.80% ± 14:00 9.60E-11 3.45E-11 5.98E-09 2.97E-10 0.22% ± 19.09% 1.80% 0.07% 0.56% 2.01% 2.60E-08 ± 1.56E-08 ± 3.10E-07 ± 1.62E-07 ± 60.00% ± 1192.30% 621.80% ± 5.00% ± 52.20% ± 1036.40% 14:10 8.06E-11 2.34E-11 5.89E-10 3.24E-10 0.21% ± 4.34% 2.30% 0.01% 0.14% ± 2.60% 9.39E-08 ± 1.07E-07 ± 9.18E-08 ± 1.09E-07 ± 113.70% ± 97.70% ± 116.50% ± 116.40% ± 119.30% ± 102.50% ± 14:20 1.78E-10 1.39E-10 1.19E-10 1.96E-10 0.26% 0.23% 0.30% 0.21% 0.26% 0.23% 2.97E-08 ± 1.81E-08 ± 4.14E-07 ± 9.91E-08 ± 61.00% ± 1391.70% 333.50% ± 4.40% ± 24.00% ± 546.80% ± 14:30 7.72E-11 2.17E-11 7.45E-10 1.49E-10 0.17% ± 4.41% 1.00% 0.01% 0.06% 1.05%

175

Table A-15. Continued Start Rhines Rhines 2 Weimer Reitz (F8 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (F8 Tally) (F8 Tally) (F8 Tally) Tally) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 3.10E-08 ± 1.97E-08 ± 3.76E-07 ± 1.62E-07 ± 63.80% ± 1215.60% 523.50% ± 5.20% ± 43.10% ± 820.70% ± 14:40 9.30E-12 2.56E-11 6.39E-10 2.43E-10 0.08% ± 2.09% 0.80% 0.01% 0.10% 1.63% 3.67E-08 ± 2.40E-08 ± 2.82E-07 ± 3.18E-07 ± 65.40% ± 769.00% ± 865.80% ± 8.50% ± 112.60% ± 1323.20% 14:50 1.10E-11 2.64E-11 4.23E-10 6.68E-10 0.07% 1.18% 1.84% 0.02% 0.29% ± 3.14% 1.44E-07 ± 9.15E-09 ± 4.96E-07 ± 1.55E-08 ± 6.30% ± 343.70% ± 10.70% ± 1.80% ± 3.10% ± 169.20% ± 15:00 7.13E-09 1.74E-11 9.42E-10 2.17E-11 0.31% 17.06% 0.53% 0.01% 0.01% 0.40% 5.10E-08 ± 3.86E-08 ± 1.42E-07 ± 6.35E-07 ± 75.80% ± 277.70% ± 1246.10% 27.30% ± 448.80% ± 1643.20% 15:10 1.17E-10 5.02E-11 2.13E-10 9.97E-09 0.20% 0.76% ± 19.76% 0.05% 7.05% ± 25.92% 1.12E-07 ± 1.42E-07 ± 7.13E-08 ± 6.33E-08 ± 125.80% ± 63.40% ± 56.30% ± 198.40% ± 88.70% ± 44.70% ± 15:20 2.02E-10 1.70E-10 9.27E-11 7.60E-11 0.27% 0.14% 0.12% 0.35% 0.16% 0.08% 5.81E-08 ± 4.73E-08 ± 1.24E-07 ± 4.27E-07 ± 81.50% ± 213.00% ± 734.60% ± 38.30% ± 344.90% ± 901.40% ± 15:30 1.28E-10 6.15E-11 1.74E-10 5.29E-09 0.21% 0.56% 9.26% 0.07% 4.30% 11.26% 2.83E-08 ± 1.81E-08 ± 2.68E-07 ± 4.17E-07 ± 64.10% ± 949.50% ± 1475.50% 6.70% ± 155.40% ± 2303.30% 15:40 8.77E-11 5.25E-11 4.56E-10 2.05E-08 0.27% 3.35% ± 72.64% 0.02% 7.66% ± 113.55% 4.72E-08 ± 3.40E-08 ± 1.73E-07 ± 1.34E-06 ± 72.20% ± 366.10% ± 2840.10% 19.70% ± 775.90% ± 3933.30% 15:50 1.09E-10 3.74E-11 2.42E-10 4.42E-08 0.18% 0.99% ± 93.91% 0.03% 25.58% ± 130.13% 6.49E-09 ± 5.56E-09 ± 5.86E-07 ± 3.11E-08 ± 85.70% ± 9022.60% 478.90% ± 0.90% ± 5.30% ± 559.10% ± 16:00 1.72E-11 1.17E-11 9.08E-10 9.58E-10 0.29% ± 27.72% 14.81% 0.01% 0.16% 17.27% 1.64E-08 ± 1.13E-08 ± 1.12E-07 ± 7.93E-09 ± 68.60% ± 678.70% ± 48.20% ± 10.10% ± 7.10% ± 70.30% ± 16:10 4.43E-11 2.26E-11 1.74E-10 3.26E-10 0.23% 2.13% 1.99% 0.03% 0.29% 2.89% 8.88E-09 ± 8.96E-09 ± 2.59E-07 ± 9.59E-09 ± 100.90% ± 2920.30% 108.10% ± 3.50% ± 3.70% ± 107.10% ± 16:20 2.20E-11 1.43E-11 3.82E-10 3.06E-10 0.30% ± 8.40% 3.46% 0.01% 0.12% 3.42%

Table A-16. UFTR 10 min averaged weather in-house Gaussian model January 17th, 2019 simulations Start Rhines Rhines 2 Weimer Reitz (F8 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (F8 Tally) (F8 Tally) (F8 Tally) Tally) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 9.19E-07 ± 4.41E-07 ± 2.54E-08 ± 1.24E-08 ± 48.00% ± 2.80% ± 1.30% ± 1737.30% 48.60% ± 2.80% ± 10:30 2.85E-09 1.00E-08 4.57E-11 1.98E-11 1.10% 0.01% 0.01% ± 39.54% 0.12% 0.06% 3.32E-07 ± 1.13E-06 ± 3.48E-08 ± 1.85E-08 ± 341.80% ± 10.50% ± 5.60% ± 3256.70% 53.20% ± 1.60% ± 10:40 6.97E-10 1.54E-08 6.26E-11 2.96E-11 4.68% 0.03% 0.01% ± 44.55% 0.13% 0.02% 8.35E-07 ± 4.16E-07 ± 3.25E-08 ± 1.37E-08 ± 49.80% ± 3.90% ± 1.60% ± 1281.30% 42.20% ± 3.30% ± 10:50 2.25E-09 2.87E-09 1.58E-09 2.06E-11 0.37% 0.19% 0.01% ± 62.96% 2.05% 0.02% 3.12E-07 ± 1.29E-06 ± 3.15E-08 ± 1.73E-08 ± 411.70% ± 10.10% ± 5.50% ± 4088.10% 54.90% ± 1.30% ± 11:00 6.86E-10 4.14E-08 7.88E-11 2.60E-11 13.30% 0.03% 0.01% ± 131.86% 0.16% 0.04%

176

Table A-16. Continued Start Rhines Rhines 2 Weimer Reitz (F8 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (F8 Tally) (F8 Tally) (F8 Tally) Tally) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 1.01E-07 ± 1.31E-07 ± 7.27E-08 ± 7.19E-08 ± 129.80% ± 72.00% ± 71.20% ± 180.40% ± 98.90% ± 54.80% ± 11:10 2.02E-10 1.57E-10 1.02E-10 6.26E-10 0.30% 0.18% 0.64% 0.33% 0.87% 0.48% 5.90E-08 ± 1.16E-08 ± 4.03E-08 ± 4.41E-09 ± 19.70% ± 68.30% ± 7.50% ± 28.80% ± 11.00% ± 38.00% ± 11:20 1.24E-10 2.32E-11 7.66E-11 9.70E-12 0.06% 0.19% 0.02% 0.08% 0.03% 0.11% 5.83E-07 ± 5.79E-08 ± 3.01E-08 ± 7.98E-09 ± 9.90% ± 5.20% ± 1.40% ± 192.40% ± 26.50% ± 13.80% ± 11:30 1.22E-09 8.11E-11 5.12E-11 1.28E-11 0.03% 0.01% 0.01% 0.42% 0.06% 0.03% 6.44E-08 ± 5.50E-08 ± 1.34E-07 ± 3.61E-07 ± 85.40% ± 208.20% ± 560.90% ± 41.00% ± 269.40% ± 656.70% ± 11:40 1.29E-10 6.05E-11 1.88E-10 1.65E-08 0.19% 0.51% 25.59% 0.07% 12.29% 29.95% 2.57E-07 ± 8.15E-07 ± 4.50E-08 ± 2.37E-08 ± 317.40% ± 17.50% ± 9.20% ± 1811.90% 52.70% ± 2.90% ± 11:50 6.68E-10 7.01E-09 1.35E-11 3.32E-11 2.85% 0.05% 0.03% ± 15.59% 0.08% 0.03% 2.29E-07 ± 2.71E-08 ± 3.01E-08 ± 6.08E-09 ± 11.80% ± 13.20% ± 2.70% ± 89.80% ± 20.20% ± 22.50% ± 12:00 3.44E-10 4.61E-11 5.42E-11 1.03E-11 0.03% 0.03% 0.01% 0.22% 0.05% 0.05% 4.16E-07 ± 3.88E-08 ± 2.75E-08 ± 6.90E-09 ± 9.30% ± 6.60% ± 1.70% ± 141.00% ± 25.10% ± 17.80% ± 12:10 8.32E-10 6.21E-11 4.95E-11 1.17E-11 0.02% 0.02% 0.01% 0.34% 0.06% 0.04% 2.06E-08 ± 1.10E-08 ± 1.51E-06 ± 3.10E-08 ± 53.60% ± 7323.10% 150.70% ± 0.70% ± 2.10% ± 281.30% ± 12:20 6.39E-11 1.76E-11 8.76E-09 4.65E-11 0.19% ± 48.21% 0.52% 0.01% 0.01% 0.62% 5.59E-07 ± 5.17E-08 ± 2.89E-08 ± 7.63E-09 ± 9.30% ± 5.20% ± 1.40% ± 179.00% ± 26.40% ± 14.80% ± 12:30 1.17E-09 9.31E-11 4.91E-11 1.22E-11 0.03% 0.01% 0.01% 0.44% 0.06% 0.04% 2.16E-06 ± 1.37E-07 ± 2.61E-08 ± 1.03E-08 ± 6.40% ± 1.20% ± 0.50% ± 526.00% ± 39.40% ± 7.50% ± 12:40 4.56E-08 2.82E-09 4.70E-11 1.55E-11 0.19% 0.03% 0.01% 10.85% 0.09% 0.16% 4.97E-08 ± 1.17E-08 ± 6.14E-08 ± 5.52E-09 ± 23.60% ± 123.50% ± 11.10% ± 19.10% ± 9.00% ± 47.00% ± 12:50 5.62E-10 1.99E-11 2.82E-09 1.16E-11 0.27% 5.85% 0.13% 0.88% 0.41% 0.13% 9.68E-08 ± 1.63E-08 ± 3.76E-08 ± 5.25E-09 ± 16.80% ± 38.80% ± 5.40% ± 43.30% ± 14.00% ± 32.30% ± 13:00 1.65E-10 2.77E-11 6.77E-11 9.45E-12 0.04% 0.10% 0.01% 0.11% 0.04% 0.08% 3.53E-08 ± 9.67E-09 ± 7.36E-08 ± 5.70E-09 ± 27.40% ± 208.40% ± 16.10% ± 13.10% ± 7.70% ± 58.90% ± 13:10 8.12E-11 1.74E-11 1.25E-10 1.03E-11 0.08% 0.60% 0.05% 0.03% 0.02% 0.15% 2.65E-08 ± 9.31E-09 ± 1.43E-07 ± 8.08E-09 ± 35.10% ± 537.70% ± 30.50% ± 6.50% ± 5.70% ± 86.70% ± 13:20 6.36E-11 1.58E-11 2.29E-10 1.37E-11 0.10% 1.56% 0.09% 0.02% 0.01% 0.21% 1.71E-07 ± 2.45E-08 ± 3.55E-08 ± 6.09E-09 ± 14.30% ± 20.70% ± 3.60% ± 69.10% ± 17.20% ± 24.90% ± 13:30 2.57E-10 3.68E-11 6.04E-11 3.90E-11 0.03% 0.05% 0.02% 0.16% 0.11% 0.16% 9.05E-08 ± 1.51E-08 ± 3.67E-08 ± 5.03E-09 ± 16.60% ± 40.60% ± 5.60% ± 41.00% ± 13.70% ± 33.40% ± 13:40 1.63E-10 2.72E-11 6.97E-11 1.01E-11 0.04% 0.11% 0.01% 0.11% 0.04% 0.09% 7.66E-08 ± 1.45E-08 ± 4.65E-08 ± 5.24E-09 ± 19.00% ± 60.80% ± 6.80% ± 31.20% ± 11.30% ± 36.10% ± 13:50 1.30E-10 2.47E-11 2.16E-09 1.21E-11 0.05% 2.82% 0.02% 1.45% 0.52% 0.10% 2.39E-08 ± 8.79E-09 ± 1.73E-07 ± 8.38E-09 ± 36.80% ± 725.10% ± 35.10% ± 5.10% ± 4.80% ± 95.40% ± 14:00 6.45E-11 1.85E-11 2.94E-10 1.34E-11 0.13% 2.31% 0.11% 0.01% 0.01% 0.25%

177

Table A-16. Continued Start Rhines Rhines 2 Weimer Reitz (F8 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (F8 Tally) (F8 Tally) (F8 Tally) Tally) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 3.56E-08 ± 1.02E-08 ± 8.06E-08 ± 6.11E-09 ± 28.80% ± 226.50% ± 17.20% ± 12.70% ± 7.60% ± 59.70% ± 14:10 7.83E-11 1.41E-10 1.29E-10 1.04E-11 0.40% 0.62% 0.05% 0.18% 0.02% 0.83% 3.83E-08 ± 1.02E-08 ± 7.13E-08 ± 5.69E-09 ± 26.70% ± 186.00% ± 14.80% ± 14.40% ± 8.00% ± 55.50% ± 14:20 1.90E-09 1.84E-11 2.00E-09 1.25E-11 1.32% 10.62% 0.74% 0.40% 0.22% 0.16% 4.63E-08 ± 1.10E-08 ± 6.20E-08 ± 5.34E-09 ± 23.70% ± 133.80% ± 11.50% ± 17.70% ± 8.60% ± 48.60% ± 14:30 9.26E-11 1.87E-11 2.83E-09 1.28E-11 0.06% 6.11% 0.04% 0.81% 0.39% 0.14% 3.61E-08 ± 9.57E-09 ± 6.60E-08 ± 5.33E-09 ± 26.50% ± 182.90% ± 14.80% ± 14.50% ± 8.10% ± 55.70% ± 14:40 8.66E-11 1.91E-11 1.19E-10 9.59E-12 0.08% 0.55% 0.04% 0.04% 0.02% 0.15% 3.61E-08 ± 9.91E-09 ± 7.54E-08 ± 5.84E-09 ± 27.40% ± 208.60% ± 16.20% ± 13.10% ± 7.70% ± 58.90% ± 14:50 7.94E-11 1.78E-11 1.51E-11 1.11E-11 0.08% 0.46% 0.05% 0.02% 0.01% 0.15% 3.54E-08 ± 9.59E-09 ± 7.16E-08 ± 5.61E-09 ± 27.10% ± 202.50% ± 15.90% ± 13.40% ± 7.80% ± 58.50% ± 15:00 7.79E-11 1.73E-11 1.29E-10 1.07E-11 0.08% 0.57% 0.05% 0.03% 0.02% 0.15% 8.04E-08 ± 1.39E-08 ± 3.73E-08 ± 4.85E-09 ± 17.30% ± 46.40% ± 6.00% ± 37.30% ± 13.00% ± 34.80% ± 15:10 1.45E-10 2.50E-11 7.09E-11 1.02E-11 0.04% 0.12% 0.02% 0.10% 0.04% 0.10% 7.55E-08 ± 1.35E-08 ± 3.86E-08 ± 4.96E-09 ± 17.90% ± 51.10% ± 6.60% ± 35.00% ± 12.80% ± 36.70% ± 15:20 1.36E-10 2.43E-11 7.33E-11 8.53E-11 0.05% 0.13% 0.11% 0.09% 0.22% 0.64% 6.70E-08 ± 1.28E-08 ± 4.17E-08 ± 4.94E-09 ± 19.10% ± 62.30% ± 7.40% ± 30.70% ± 11.80% ± 38.50% ± 15:30 1.27E-10 2.30E-11 7.51E-11 1.09E-11 0.05% 0.16% 0.02% 0.08% 0.03% 0.11% 6.03E-08 ± 1.26E-08 ± 4.78E-08 ± 5.18E-09 ± 20.90% ± 79.30% ± 8.60% ± 26.40% ± 10.80% ± 41.10% ± 15:40 1.09E-10 2.77E-11 1.00E-10 9.84E-12 0.06% 0.22% 0.02% 0.08% 0.03% 0.12% 6.95E-08 ± 1.29E-08 ± 4.39E-08 ± 4.83E-09 ± 18.60% ± 63.20% ± 6.90% ± 29.40% ± 11.00% ± 37.40% ± 15:50 1.32E-10 2.45E-11 1.98E-09 9.66E-12 0.05% 2.85% 0.02% 1.33% 0.50% 0.10% 4.74E-08 ± 1.05E-08 ± 4.83E-08 ± 4.70E-09 ± 22.20% ± 101.80% ± 9.90% ± 21.90% ± 9.70% ± 44.50% ± 16:00 9.95E-11 2.00E-11 8.69E-11 1.18E-11 0.06% 0.28% 0.03% 0.06% 0.03% 0.14% 3.63E-08 ± 9.62E-09 ± 6.71E-08 ± 5.41E-09 ± 26.50% ± 185.10% ± 14.90% ± 14.30% ± 8.10% ± 56.20% ± 16:10 8.35E-11 1.73E-11 1.21E-10 9.74E-12 0.08% 0.54% 0.04% 0.04% 0.02% 0.14% 5.30E-07 ± 2.85E-07 ± 5.14E-08 ± 2.83E-07 ± 53.80% ± 9.70% ± 53.40% ± 554.70% ± 550.70% ± 99.30% ± 16:20 2.57E-08 1.38E-08 9.25E-11 1.23E-08 3.69% 0.47% 3.48% 26.91% 23.92% 6.46%

Table A-17. UF 10 min averaged weather in-house Gaussian model January 17th, 2019 simulations Start Rhines Rhines 2 Weimer Reitz (F8 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (F8 Tally) (F8 Tally) (F8 Tally) Tally) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 5.48E-08 ± 2.06E-08 ± 4.84E-08 ± 7.43E-09 ± 37.50% ± 88.40% ± 13.60% ± 42.40% ± 15.30% ± 36.10% ± 10:30 1.75E-10 4.82E-10 8.97E-11 1.22E-11 0.89% 0.33% 0.05% 1.00% 0.04% 0.85%

178

Table A-17. Continued Start Rhines Rhines 2 Weimer Reitz (F8 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (F8 Tally) (F8 Tally) (F8 Tally) Tally) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 1.09E-08 ± 1.13E-08 ± 2.67E-07 ± 5.80E-08 ± 103.80% ± 2453.50% 532.70% ± 4.20% ± 21.70% ± 513.30% ± 10:40 2.36E-11 1.58E-10 4.95E-10 9.56E-11 1.47% ± 6.98% 1.45% 0.06% 0.05% 7.24% 3.43E-07 ± 2.12E-07 ± 2.83E-08 ± 1.28E-08 ± 61.90% ± 8.30% ± 3.70% ± 749.50% ± 45.30% ± 6.00% ± 10:50 9.54E-10 1.51E-09 1.42E-09 1.98E-11 0.47% 0.41% 0.01% 37.95% 2.27% 0.04% 9.00E-09 ± 8.39E-09 ± 6.56E-07 ± 1.38E-08 ± 93.30% ± 7290.6% ± 153.50% ± 1.30% ± 2.10% ± 164.50% ± 11:00 2.04E-11 2.77E-10 1.69E-09 2.13E-11 3.09% 25.00% 0.42% 0.04% 0.01% 5.44% 7.55E-09 ± 7.37E-09 ± 9.90E-07 ± 1.46E-08 ± 97.60% ± 13109.4% 193.80% ± 0.70% ± 1.50% ± 198.50% ± 11:10 1.56E-11 9.11E-12 1.43E-09 1.31E-10 0.23% ± 32.97% 1.78% 0.01% 0.01% 1.79% 1.12E-07 ± 2.93E-08 ± 2.79E-08 ± 7.56E-09 ± 26.10% ± 24.90% ± 6.70% ± 105.00% ± 27.10% ± 25.80% ± 11:20 2.42E-10 6.04E-11 5.46E-11 1.71E-11 0.08% 0.07% 0.02% 0.30% 0.08% 0.08% 5.48E-08 ± 2.06E-08 ± 4.84E-08 ± 7.43E-09 ± 37.50% ± 88.40% ± 13.60% ± 42.40% ± 15.30% ± 36.10% ± 11:30 1.19E-10 2.97E-11 8.47E-11 1.22E-11 0.10% 0.25% 0.04% 0.10% 0.04% 0.08% 1.09E-08 ± 1.13E-08 ± 2.67E-07 ± 5.80E-08 ± 103.80% ± 2453.50% 532.70% ± 4.20% ± 21.70% ± 513.30% ± 11:40 2.25E-11 1.28E-11 3.85E-10 2.72E-09 0.24% ± 6.16% 25.02% 0.01% 1.02% 24.12% 3.43E-07 ± 2.12E-07 ± 2.83E-08 ± 1.28E-08 ± 61.90% ± 8.30% ± 3.70% ± 749.50% ± 45.30% ± 6.00% ± 11:50 9.19E-10 1.88E-09 8.74E-12 1.85E-11 0.57% 0.02% 0.01% 6.64% 0.07% 0.05% 9.00E-09 ± 8.39E-09 ± 6.56E-07 ± 1.38E-08 ± 93.30% ± 7290.60% 153.50% ± 1.30% ± 2.10% ± 164.50% ± 12:00 1.39E-11 1.47E-11 1.22E-09 2.42E-11 0.22% ± 17.59% 0.36% 0.01% 0.01% 0.41% 6.73E-08 ± 4.48E-08 ± 2.71E-08 ± 8.55E-09 ± 66.50% ± 40.20% ± 12.70% ± 165.20% ± 31.60% ± 19.10% ± 12:10 1.39E-10 7.38E-11 5.02E-11 1.50E-11 0.18% 0.11% 0.03% 0.41% 0.08% 0.05% 1.26E-07 ± 3.67E-08 ± 3.39E-08 ± 7.99E-09 ± 29.20% ± 27.00% ± 6.40% ± 108.30% ± 23.60% ± 21.80% ± 12:20 4.02E-10 6.05E-11 2.03E-10 1.23E-11 0.10% 0.18% 0.02% 0.67% 0.15% 0.05% 2.54E-07 ± 8.72E-08 ± 2.96E-08 ± 1.04E-08 ± 34.30% ± 11.60% ± 4.10% ± 294.90% ± 35.10% ± 11.90% ± 12:30 5.49E-10 1.62E-10 5.18E-11 1.71E-11 0.10% 0.03% 0.01% 0.75% 0.08% 0.03% 2.07E-07 ± 3.77E-08 ± 2.11E-08 ± 7.81E-09 ± 18.20% ± 10.20% ± 3.80% ± 179.00% ± 37.10% ± 20.70% ± 12:40 4.50E-09 8.00E-10 3.91E-11 1.21E-11 0.55% 0.22% 0.08% 3.81% 0.09% 0.44% 1.28E-07 ± 5.17E-08 ± 2.66E-08 ± 8.97E-09 ± 40.30% ± 20.70% ± 7.00% ± 194.60% ± 33.80% ± 17.40% ± 12:50 1.49E-09 9.05E-11 1.26E-09 1.94E-11 0.48% 1.01% 0.08% 9.22% 1.60% 0.05% 2.64E-07 ± 4.01E-08 ± 1.71E-08 ± 7.10E-09 ± 15.20% ± 6.50% ± 2.70% ± 234.10% ± 41.50% ± 17.70% ± 13:00 4.62E-10 7.02E-11 3.17E-11 1.32E-11 0.04% 0.02% 0.01% 0.60% 0.11% 0.05% 3.42E-08 ± 1.55E-08 ± 6.95E-08 ± 7.35E-09 ± 45.30% ± 203.20% ± 21.50% ± 22.30% ± 10.60% ± 47.50% ± 13:10 8.10E-11 2.87E-11 1.22E-10 1.36E-11 0.14% 0.60% 0.06% 0.06% 0.03% 0.12% 1.24E-08 ± 8.76E-09 ± 9.07E-08 ± 1.01E-08 ± 70.50% ± 729.90% ± 81.00% ± 9.70% ± 11.10% ± 115.00% ± 13:20 3.07E-11 1.53E-11 1.49E-10 1.77E-11 0.21% 2.17% 0.25% 0.02% 0.03% 0.29% 4.81E-07 ± 6.02E-08 ± 2.06E-08 ± 9.16E-09 ± 12.50% ± 4.30% ± 1.90% ± 291.70% ± 44.40% ± 15.20% ± 13:30 7.43E-10 9.30E-11 3.61E-11 6.04E-11 0.03% 0.01% 0.01% 0.68% 0.30% 0.10%

179

Table A-17. Continued Start Rhines Rhines 2 Weimer Reitz (F8 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (F8 Tally) (F8 Tally) (F8 Tally) Tally) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 3.50E-08 ± 1.58E-08 ± 6.94E-08 ± 7.33E-09 ± 45.00% ± 197.90% ± 20.90% ± 22.80% ± 10.60% ± 46.50% ± 13:40 6.49E-11 2.93E-11 1.36E-10 1.51E-11 0.12% 0.53% 0.06% 0.06% 0.03% 0.13% 1.11E-07 ± 2.99E-08 ± 3.44E-08 ± 7.82E-09 ± 26.80% ± 30.90% ± 7.00% ± 86.70% ± 22.70% ± 26.20% ± 13:50 1.94E-10 5.24E-11 1.65E-09 1.85E-11 0.07% 1.49% 0.02% 4.17% 1.09% 0.08% 1.01E-08 ± 9.10E-09 ± 4.10E-07 ± 1.16E-08 ± 90.30% ± 4065.30% 115.50% ± 2.20% ± 2.80% ± 127.80% ± 14:00 2.81E-11 1.97E-11 7.18E-10 1.91E-11 0.32% ± 13.34% 0.37% 0.01% 0.01% 0.35% 1.39E-08 ± 1.01E-08 ± 2.15E-07 ± 9.78E-09 ± 72.70% ± 1545.40% 70.40% ± 4.70% ± 4.60% ± 96.80% ± 14:10 3.15E-11 1.44E-10 3.54E-10 1.71E-11 1.05% ± 4.33% 0.20% 0.07% 0.01% 1.39% 9.97E-09 ± 9.25E-09 ± 2.24E-07 ± 9.36E-09 ± 92.80% ± 2245.50% 93.80% ± 4.10% ± 4.20% ± 101.10% ± 14:20 5.10E-10 1.71E-11 6.46E-09 2.12E-11 4.75% ± 132.01% 4.81% 0.12% 0.12% 0.30% 9.29E-09 ± 9.26E-09 ± 1.83E-07 ± 7.41E-09 ± 99.60% ± 1971.00% 79.70% ± 5.10% ± 4.00% ± 80.00% ± 14:30 1.91E-11 1.62E-11 8.60E-09 1.83E-11 0.27% ± 92.61% 0.26% 0.24% 0.19% 0.24% 5.20E-07 ± 1.06E-08 ± 1.02E-07 ± 7.00E-09 ± 2.00% ± 19.50% ± 1.30% ± 10.40% ± 6.90% ± 66.10% ± 14:40 1.29E-09 2.18E-11 1.89E-10 1.30E-11 0.01% 0.06% 0.01% 0.03% 0.02% 0.18% 1.26E-08 ± 1.01E-08 ± 1.15E-07 ± 7.01E-09 ± 80.00% ± 919.20% ± 55.80% ± 8.70% ± 6.10% ± 69.70% ± 14:50 2.86E-11 1.87E-11 2.37E-11 1.37E-11 0.23% 2.08% 0.17% 0.02% 0.01% 0.19% 1.06E-08 ± 9.29E-09 ± 1.43E-07 ± 4.16E-09 ± 87.80% ± 1352.20% 39.30% ± 6.50% ± 2.90% ± 44.70% ± 15:00 2.40E-11 1.72E-11 2.65E-10 8.14E-12 0.26% ± 3.95% 0.12% 0.02% 0.01% 0.12% 5.26E-08 ± 1.99E-08 ± 3.11E-08 ± 4.50E-09 ± 37.90% ± 59.00% ± 8.60% ± 64.20% ± 14.50% ± 22.60% ± 15:10 9.75E-11 3.69E-11 6.09E-11 9.73E-12 0.10% 0.16% 0.02% 0.17% 0.04% 0.06% 3.52E-08 ± 1.68E-08 ± 3.86E-08 ± 4.66E-09 ± 47.60% ± 109.70% ± 13.20% ± 43.40% ± 12.10% ± 27.80% ± 15:20 6.53E-11 3.11E-11 7.55E-11 8.26E-11 0.13% 0.30% 0.24% 0.12% 0.22% 0.49% 3.27E-08 ± 1.58E-08 ± 5.25E-08 ± 7.04E-09 ± 48.20% ± 160.60% ± 21.50% ± 30.00% ± 13.40% ± 44.70% ± 15:30 6.40E-11 2.93E-11 9.73E-11 1.60E-11 0.13% 0.43% 0.06% 0.08% 0.04% 0.13% 1.65E-08 ± 1.13E-08 ± 9.57E-08 ± 7.41E-09 ± 68.60% ± 581.90% ± 45.00% ± 11.80% ± 7.70% ± 65.60% ± 15:40 3.06E-11 2.56E-11 2.07E-10 1.45E-11 0.20% 1.65% 0.12% 0.04% 0.02% 0.20% 3.27E-08 ± 1.59E-08 ± 5.07E-08 ± 6.95E-09 ± 48.50% ± 154.80% ± 21.30% ± 31.30% ± 13.70% ± 43.80% ± 15:50 6.40E-11 3.11E-11 2.36E-09 1.43E-11 0.13% 7.21% 0.06% 1.46% 0.64% 0.12% 1.15E-08 ± 9.67E-09 ± 1.20E-07 ± 6.07E-09 ± 84.30% ± 1045.20% 52.90% ± 8.10% ± 5.10% ± 62.80% ± 16:00 2.49E-11 1.89E-11 2.22E-10 1.56E-11 0.25% ± 2.97% 0.18% 0.02% 0.02% 0.20% 1.29E-08 ± 1.00E-08 ± 9.97E-08 ± 5.30E-09 ± 77.70% ± 771.90% ± 41.00% ± 10.10% ± 5.30% ± 52.80% ± 16:10 3.06E-11 1.85E-11 1.85E-10 9.83E-12 0.23% 2.32% 0.12% 0.03% 0.01% 0.14% 1.40E-08 ± 1.05E-08 ± 9.39E-08 ± 5.94E-09 ± 74.80% ± 671.20% ± 42.50% ± 11.10% ± 6.30% ± 56.80% ± 16:20 6.99E-10 5.25E-10 1.74E-10 2.66E-10 5.30% 33.53% 2.84% 0.56% 0.28% 3.79%

180

Table A-18. UFTR 10 min averaged weather in-house Gaussian model January 18th, 2019 simulations Start Rhines Rhines 2 Weimer Reitz (F8 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (F8 Tally) (F8 Tally) (F8 Tally) Tally) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 3.91E-08 ± 2.59E-08 ± 2.60E-07 ± 3.91E-07 ± 66.30% ± 665.10% ± 999.70% ± 10.00% ± 150.30% ± 1507.50% 10:30 9.78E-11 3.11E-11 4.16E-10 2.93E-09 0.18% 1.97% 7.91% 0.02% 1.15% ± 11.47% 2.85E-08 ± 1.71E-08 ± 2.76E-07 ± 7.57E-08 ± 60.10% ± 970.90% ± 266.00% ± 6.20% ± 27.40% ± 442.50% ± 10:40 7.13E-11 2.39E-11 8.75E-09 9.84E-11 0.17% 30.79% 0.75% 0.20% 0.87% 0.85% 2.58E-07 ± 2.95E-08 ± 3.18E-08 ± 6.30E-09 ± 11.40% ± 12.30% ± 2.40% ± 92.80% ± 19.80% ± 21.40% ± 10:50 4.13E-10 4.43E-11 1.55E-09 1.26E-11 0.03% 0.60% 0.01% 4.53% 0.97% 0.05% 8.03E-08 ± 1.55E-08 ± 7.37E-08 ± 5.42E-09 ± 19.30% ± 91.80% ± 6.80% ± 21.10% ± 7.40% ± 34.90% ± 11:00 1.69E-10 2.48E-11 3.13E-09 9.76E-12 0.05% 3.91% 0.02% 0.89% 0.31% 0.08% 2.31E-07 ± 2.93E-08 ± 3.36E-08 ± 6.42E-09 ± 12.70% ± 14.50% ± 2.80% ± 87.30% ± 19.10% ± 21.90% ± 11:10 3.70E-10 4.40E-11 5.71E-11 1.28E-11 0.03% 0.03% 0.01% 0.20% 0.05% 0.05% 5.39E-08 ± 1.25E-08 ± 5.08E-08 ± 5.41E-09 ± 23.20% ± 94.20% ± 10.00% ± 24.60% ± 10.70% ± 43.30% ± 11:20 9.16E-11 2.13E-11 8.13E-11 9.20E-12 0.06% 0.22% 0.02% 0.06% 0.02% 0.10% 3.81E-08 ± 1.01E-08 ± 6.86E-08 ± 5.59E-09 ± 26.40% ± 180.20% ± 14.70% ± 14.60% ± 8.10% ± 55.70% ± 11:30 8.00E-11 2.02E-11 1.17E-10 1.01E-11 0.08% 0.49% 0.04% 0.04% 0.02% 0.15% 1.16E-07 ± 1.93E-08 ± 3.89E-08 ± 5.66E-09 ± 16.70% ± 33.70% ± 4.90% ± 49.60% ± 14.50% ± 29.30% ± 11:40 1.86E-10 3.09E-11 6.61E-11 1.02E-11 0.04% 0.08% 0.01% 0.12% 0.04% 0.07% 1.91E-07 ± 4.50E-07 ± 5.15E-08 ± 3.02E-08 ± 235.30% ± 27.00% ± 15.80% ± 872.80% ± 58.50% ± 6.70% ± 11:50 3.63E-10 9.00E-10 7.21E-11 5.44E-11 0.65% 0.06% 0.04% 2.13% 0.13% 0.02% 2.15E-08 ± 9.85E-09 ± 2.86E-07 ± 1.45E-08 ± 45.90% ± 1334.10% 67.80% ± 3.40% ± 5.10% ± 147.60% ± 12:00 6.02E-11 1.58E-11 4.58E-10 2.03E-11 0.15% ± 4.29% 0.21% 0.01% 0.01% 0.31% 4.22E-08 ± 1.08E-08 ± 6.65E-08 ± 2.77E-08 ± 25.60% ± 157.70% ± 65.60% ± 16.20% ± 41.60% ± 256.70% ± 12:10 8.44E-11 1.94E-11 1.13E-10 1.38E-09 0.07% 0.41% 3.26% 0.04% 2.07% 12.76% 1.46E-07 ± 2.42E-07 ± 6.62E-08 ± 4.57E-08 ± 165.60% ± 45.40% ± 31.30% ± 365.10% ± 68.90% ± 18.90% ± 12:20 2.77E-10 3.87E-10 8.61E-11 5.94E-11 0.41% 0.10% 0.07% 0.75% 0.13% 0.04% 2.31E-08 ± 8.82E-09 ± 2.00E-07 ± 9.08E-09 ± 38.20% ± 868.80% ± 39.40% ± 4.40% ± 4.50% ± 103.00% ± 12:30 6.24E-11 1.59E-11 3.40E-10 1.45E-11 0.12% 2.76% 0.12% 0.01% 0.01% 0.25% 3.75E-08 ± 1.02E-08 ± 7.33E-08 ± 5.80E-09 ± 27.30% ± 195.60% ± 15.50% ± 13.90% ± 7.90% ± 56.80% ± 12:40 7.88E-11 5.41E-11 1.25E-10 9.86E-12 0.16% 0.53% 0.04% 0.08% 0.02% 0.32% 2.80E-08 ± 9.01E-09 ± 1.13E-07 ± 6.80E-09 ± 32.20% ± 403.70% ± 24.30% ± 8.00% ± 6.00% ± 75.50% ± 12:50 6.72E-11 1.80E-11 1.92E-10 1.16E-11 0.10% 1.19% 0.07% 0.02% 0.01% 0.20% 3.42E-08 ± 9.55E-09 ± 7.68E-08 ± 5.79E-09 ± 27.90% ± 224.30% ± 16.90% ± 12.40% ± 7.50% ± 60.60% ± 13:00 7.87E-11 2.01E-11 1.31E-10 1.10E-11 0.09% 0.64% 0.05% 0.03% 0.02% 0.17% 2.44E-08 ± 8.78E-09 ± 1.64E-07 ± 8.12E-09 ± 36.00% ± 670.80% ± 33.30% ± 5.40% ± 5.00% ± 92.50% ± 13:10 1.27E-10 2.55E-11 2.95E-10 1.38E-11 0.21% 3.70% 0.18% 0.02% 0.01% 0.31% 3.26E-08 ± 9.46E-09 ± 8.54E-08 ± 6.06E-09 ± 29.10% ± 262.30% ± 18.60% ± 11.10% ± 7.10% ± 64.00% ± 13:20 7.82E-11 1.70E-11 1.45E-10 1.09E-11 0.09% 0.77% 0.06% 0.03% 0.02% 0.16%

181

Table A-18. Continued Start Rhines Rhines 2 Weimer Reitz (F8 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (F8 Tally) (F8 Tally) (F8 Tally) Tally) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 2.85E-08 ± 9.31E-09 ± 1.16E-07 ± 7.12E-09 ± 32.60% ± 405.70% ± 25.00% ± 8.00% ± 6.20% ± 76.50% ± 13:30 6.56E-11 2.70E-11 1.97E-10 1.28E-11 0.12% 1.16% 0.07% 0.03% 0.02% 0.26% 1.98E-08 ± 9.91E-09 ± 8.18E-07 ± 2.05E-08 ± 50.10% ± 4139.00% 103.70% ± 1.20% ± 2.50% ± 206.80% ± 13:40 6.14E-11 1.68E-11 1.96E-09 3.28E-11 0.18% ± 16.20% 0.36% 0.01% 0.01% 0.48% 3.61E-08 ± 1.02E-08 ± 7.34E-08 ± 6.03E-09 ± 28.20% ± 203.60% ± 16.70% ± 13.90% ± 8.20% ± 59.20% ± 13:50 7.58E-11 1.73E-11 1.17E-10 1.03E-11 0.08% 0.54% 0.05% 0.03% 0.02% 0.14% 4.30E-08 ± 1.06E-08 ± 6.11E-08 ± 5.40E-09 ± 24.60% ± 142.20% ± 12.60% ± 17.30% ± 8.80% ± 51.10% ± 14:00 8.60E-11 1.91E-11 1.10E-10 1.30E-11 0.07% 0.38% 0.04% 0.04% 0.03% 0.15% 3.42E-08 ± 9.61E-09 ± 7.95E-08 ± 5.90E-09 ± 28.10% ± 232.50% ± 17.30% ± 12.10% ± 7.40% ± 61.40% ± 14:10 7.87E-11 1.73E-11 1.35E-10 1.06E-11 0.08% 0.66% 0.05% 0.03% 0.02% 0.16% 7.03E-08 ± 1.39E-08 ± 4.44E-08 ± 5.21E-09 ± 19.80% ± 63.20% ± 7.40% ± 31.30% ± 11.70% ± 37.50% ± 14:20 1.48E-10 3.89E-11 7.99E-11 9.38E-12 0.07% 0.17% 0.02% 0.10% 0.03% 0.12% 5.94E-08 ± 1.21E-08 ± 4.50E-08 ± 4.97E-09 ± 20.30% ± 75.70% ± 8.40% ± 26.80% ± 11.00% ± 41.10% ± 14:30 1.13E-10 2.18E-11 9.00E-11 1.14E-11 0.05% 0.21% 0.02% 0.07% 0.03% 0.12% 1.13E-07 ± 1.12E-08 ± 4.23E-08 ± 3.05E-08 ± 9.90% ± 37.50% ± 27.00% ± 26.60% ± 72.00% ± 271.10% ± 14:40 4.66E-09 2.24E-11 8.04E-11 1.45E-09 0.41% 1.54% 1.70% 0.07% 3.44% 13.00% 5.42E-07 ± 3.32E-07 ± 4.00E-08 ± 2.33E-07 ± 61.30% ± 7.40% ± 43.10% ± 831.00% ± 583.60% ± 70.20% ± 14:50 2.46E-08 1.60E-08 7.60E-11 9.67E-09 4.05% 0.34% 2.64% 39.95% 24.20% 4.46% 2.34E-08 ± 8.68E-09 ± 1.80E-07 ± 8.46E-09 ± 37.10% ± 767.20% ± 36.10% ± 4.80% ± 4.70% ± 97.40% ± 15:00 7.25E-10 1.74E-11 3.06E-10 1.69E-11 1.15% 23.88% 1.12% 0.01% 0.01% 0.28% 2.46E-08 ± 8.60E-09 ± 1.47E-07 ± 7.60E-09 ± 34.90% ± 595.10% ± 30.90% ± 5.90% ± 5.20% ± 88.40% ± 15:10 8.36E-11 1.63E-11 2.65E-10 2.43E-11 0.14% 2.30% 0.14% 0.02% 0.02% 0.33% 2.57E-08 ± 8.67E-09 ± 1.31E-07 ± 7.19E-09 ± 33.80% ± 509.70% ± 28.00% ± 6.60% ± 5.50% ± 82.90% ± 15:20 6.68E-11 2.51E-11 2.23E-10 1.37E-11 0.13% 1.58% 0.09% 0.02% 0.01% 0.29% 6.09E-08 ± 1.24E-08 ± 4.07E-07 ± 4.61E-07 ± 20.30% ± 668.60% ± 757.60% ± 3.00% ± 113.30% ± 3728.00% 15:30 1.16E-10 2.23E-11 1.80E-08 2.10E-08 0.05% 29.57% 34.47% 0.13% 7.19% ± 169.29% 2.75E-08 ± 9.01E-09 ± 1.21E-07 ± 7.09E-09 ± 32.80% ± 439.50% ± 25.80% ± 7.50% ± 5.90% ± 78.60% ± 15:40 7.15E-11 1.53E-11 2.06E-10 1.21E-11 0.10% 1.37% 0.08% 0.02% 0.01% 0.19% 2.94E-08 ± 8.77E-09 ± 8.55E-08 ± 5.90E-09 ± 29.80% ± 290.20% ± 20.00% ± 10.30% ± 6.90% ± 67.20% ± 15:50 6.76E-11 1.58E-11 1.45E-10 1.18E-11 0.09% 0.83% 0.06% 0.03% 0.02% 0.18% 2.75E-08 ± 8.93E-09 ± 1.17E-07 ± 6.90E-09 ± 32.50% ± 425.20% ± 25.10% ± 7.60% ± 5.90% ± 77.30% ± 16:00 6.88E-11 1.70E-11 2.22E-10 1.79E-11 0.10% 1.34% 0.09% 0.02% 0.02% 0.25% 3.19E-08 ± 8.99E-09 ± 7.57E-08 ± 5.64E-09 ± 28.10% ± 237.10% ± 17.70% ± 11.90% ± 7.50% ± 62.80% ± 16:10 7.34E-11 1.62E-11 1.36E-10 1.02E-11 0.08% 0.69% 0.05% 0.03% 0.02% 0.16% 3.87E-08 ± 9.69E-09 ± 5.95E-08 ± 5.17E-09 ± 25.00% ± 153.80% ± 13.40% ± 16.30% ± 8.70% ± 53.40% ± 16:20 1.04E-10 1.74E-11 1.07E-10 9.82E-12 0.08% 0.50% 0.04% 0.04% 0.02% 0.14%

182

Table A-19. UF 10 min averaged weather in-house Gaussian model January 18th, 2019 simulations Start Rhines Rhines 2 Weimer Reitz (F8 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (F8 Tally) (F8 Tally) (F8 Tally) Tally) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 1.18E-09 ± 1.06E-09 ± 6.62E-09 ± 2.85E-09 ± 89.60% ± 561.70% ± 241.60% ± 16.00% ± 43.00% ± 269.60% ± 10:30 3.03E-12 1.31E-12 1.08E-11 2.17E-11 0.26% 1.70% 1.94% 0.03% 0.34% 2.08% 1.26E-09 ± 1.03E-09 ± 6.57E-09 ± 2.25E-09 ± 82.20% ± 522.50% ± 179.20% ± 15.70% ± 34.30% ± 217.90% ± 10:40 3.23E-12 1.48E-12 2.12E-10 2.97E-12 0.24% 16.85% 0.52% 0.51% 1.10% 0.43% 1.82E-08 ± 2.14E-08 ± 1.03E-08 ± 9.59E-09 ± 117.40% ± 56.60% ± 52.70% ± 207.60% ± 93.10% ± 44.80% ± 10:50 2.99E-11 3.29E-11 5.11E-10 1.95E-11 0.26% 2.81% 0.14% 10.31% 4.62% 0.11% 1.21E-08 ± 8.20E-09 ± 2.64E-09 ± 1.79E-09 ± 67.90% ± 21.90% ± 14.80% ± 310.40% ± 67.70% ± 21.80% ± 11:00 2.61E-11 1.35E-11 1.14E-10 3.27E-12 0.18% 0.94% 0.04% 13.42% 2.93% 0.05% 3.79E-08 ± 1.63E-08 ± 6.00E-08 ± 7.17E-09 ± 43.00% ± 158.30% ± 18.90% ± 27.20% ± 12.00% ± 44.00% ± 11:10 6.22E-11 2.51E-11 1.04E-10 1.46E-11 0.10% 0.38% 0.05% 0.06% 0.03% 0.11% 1.85E-08 ± 1.04E-08 ± 6.03E-08 ± 7.24E-09 ± 56.50% ± 326.30% ± 39.20% ± 17.30% ± 12.00% ± 69.40% ± 11:20 3.23E-11 1.81E-11 9.80E-11 1.25E-11 0.14% 0.78% 0.10% 0.04% 0.03% 0.17% 1.58E-08 ± 1.13E-08 ± 1.09E-07 ± 7.74E-09 ± 71.80% ± 693.70% ± 49.10% ± 10.40% ± 7.10% ± 68.40% ± 11:30 3.40E-11 2.32E-11 1.88E-10 1.42E-11 0.21% 1.91% 0.14% 0.03% 0.02% 0.19% 3.10E-08 ± 1.42E-08 ± 4.86E-08 ± 6.78E-09 ± 46.00% ± 157.00% ± 21.90% ± 29.30% ± 13.90% ± 47.60% ± 11:40 5.09E-11 2.33E-11 8.39E-11 1.24E-11 0.11% 0.37% 0.05% 0.07% 0.04% 0.12% 8.05E-08 ± 3.65E-08 ± 1.71E-08 ± 8.35E-09 ± 45.40% ± 21.30% ± 10.40% ± 213.10% ± 48.70% ± 22.90% ± 11:50 1.57E-10 7.49E-11 2.43E-11 1.53E-11 0.13% 0.05% 0.03% 0.53% 0.11% 0.06% 1.40E-09 ± 1.75E-09 ± 5.81E-09 ± 8.92E-09 ± 125.40% ± 415.40% ± 637.70% ± 30.20% ± 153.50% ± 508.70% ± 12:00 4.02E-12 2.87E-12 9.44E-12 1.27E-11 0.41% 1.37% 2.04% 0.07% 0.33% 1.11% 1.10E-08 ± 9.48E-09 ± 1.85E-07 ± 1.97E-08 ± 86.10% ± 1683.90% 178.70% ± 5.10% ± 10.60% ± 207.70% ± 12:10 2.26E-11 1.75E-11 3.20E-10 9.95E-10 0.24% ± 4.51% 9.05% 0.01% 0.54% 10.50% 4.21E-09 ± 2.15E-09 ± 5.25E-09 ± 1.22E-09 ± 51.00% ± 124.70% ± 28.90% ± 40.90% ± 23.20% ± 56.80% ± 12:20 8.21E-12 3.53E-12 6.93E-12 1.61E-12 0.13% 0.29% 0.07% 0.09% 0.04% 0.12% 1.28E-08 ± 9.38E-09 ± 1.57E-07 ± 1.14E-08 ± 73.00% ± 1223.30% 88.50% ± 6.00% ± 7.20% ± 121.20% ± 12:30 3.55E-11 1.73E-11 2.71E-10 1.85E-11 0.24% ± 4.00% 0.29% 0.02% 0.02% 0.30% 9.97E-09 ± 9.35E-09 ± 2.01E-07 ± 8.88E-09 ± 93.80% ± 2016.70% 89.00% ± 4.60% ± 4.40% ± 94.90% ± 12:40 2.15E-11 5.08E-11 3.47E-10 1.53E-11 0.55% ± 5.57% 0.25% 0.03% 0.01% 0.54% 1.19E-08 ± 9.67E-09 ± 2.23E-07 ± 9.56E-09 ± 81.00% ± 1869.30% 80.10% ± 4.30% ± 4.30% ± 98.80% ± 12:50 2.93E-11 1.98E-11 3.85E-10 1.65E-11 0.26% ± 5.64% 0.24% 0.01% 0.01% 0.27% 9.90E-09 ± 9.22E-09 ± 2.41E-07 ± 9.65E-09 ± 93.20% ± 2438.90% 97.50% ± 3.80% ± 4.00% ± 104.60% ± 13:00 2.34E-11 1.99E-11 4.16E-10 1.86E-11 0.30% ± 7.12% 0.30% 0.01% 0.01% 0.30% 8.43E-09 ± 8.62E-09 ± 3.72E-07 ± 1.08E-08 ± 102.20% ± 4413.10% 128.20% ± 2.30% ± 2.90% ± 125.50% ± 13:10 4.50E-11 2.56E-11 6.80E-10 1.87E-11 0.62% ± 24.89% 0.72% 0.01% 0.01% 0.43% 6.64E-09 ± 5.11E-09 ± 2.05E-08 ± 6.27E-09 ± 77.00% ± 309.20% ± 94.50% ± 24.90% ± 30.50% ± 122.70% ± 13:20 1.64E-11 9.44E-12 3.54E-11 1.15E-11 0.24% 0.93% 0.29% 0.06% 0.08% 0.32%

183

Table A-19. Continued Start Rhines Rhines 2 Weimer Reitz (F8 푅ℎ𝑖푛푒푠2 푊푒𝑖푚푒푟 푅푒𝑖푡푧 푅ℎ𝑖푛푒푠2 푅푒𝑖푡푧 푅푒𝑖푡푧

Time (F8 Tally) (F8 Tally) (F8 Tally) Tally) 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푅ℎ𝑖푛푒푠 푊푒𝑖푚푒푟 푊푒𝑖푚푒푟 푅ℎ𝑖푛푒푠2 1.95E-08 ± 1.09E-08 ± 7.08E-08 ± 7.51E-09 ± 55.80% ± 362.70% ± 38.50% ± 15.40% ± 10.60% ± 68.90% ± 13:30 4.60E-11 3.24E-11 1.22E-10 1.37E-11 0.21% 1.06% 0.11% 0.05% 0.03% 0.24% 1.63E-08 ± 9.77E-09 ± 9.08E-08 ± 7.75E-09 ± 59.90% ± 556.60% ± 47.50% ± 10.80% ± 8.50% ± 79.30% ± 13:40 5.18E-11 1.70E-11 2.21E-10 1.26E-11 0.22% 2.23% 0.17% 0.03% 0.03% 0.19% 3.36E-08 ± 1.51E-08 ± 6.01E-08 ± 7.12E-09 ± 44.90% ± 179.20% ± 21.20% ± 25.10% ± 11.80% ± 47.20% ± 13:50 7.24E-11 2.63E-11 9.77E-11 1.23E-11 0.12% 0.48% 0.06% 0.06% 0.03% 0.12% 1.99E-08 ± 1.24E-08 ± 9.10E-08 ± 7.62E-09 ± 62.00% ± 456.60% ± 38.20% ± 13.60% ± 8.40% ± 61.60% ± 14:00 4.08E-11 2.29E-11 1.66E-10 1.86E-11 0.17% 1.26% 0.12% 0.04% 0.03% 0.19% 1.09E-08 ± 9.22E-09 ± 3.55E-07 ± 1.20E-08 ± 84.50% ± 3258.60% 110.10% ± 2.60% ± 3.40% ± 130.20% ± 14:10 2.57E-11 1.70E-11 6.13E-10 2.19E-11 0.25% ± 9.52% 0.33% 0.01% 0.01% 0.34% 5.66E-08 ± 2.09E-08 ± 4.45E-08 ± 7.13E-09 ± 36.90% ± 78.70% ± 12.60% ± 46.90% ± 16.00% ± 34.20% ± 14:20 1.22E-10 6.00E-11 8.14E-11 1.30E-11 0.13% 0.22% 0.04% 0.16% 0.04% 0.12% 2.83E-08 ± 1.48E-08 ± 5.31E-08 ± 6.69E-09 ± 52.30% ± 187.40% ± 23.60% ± 27.90% ± 12.60% ± 45.10% ± 14:30 5.52E-11 2.73E-11 1.08E-10 1.56E-11 0.14% 0.53% 0.07% 0.08% 0.04% 0.13% 3.74E-08 ± 1.65E-08 ± 6.27E-08 ± 7.29E-09 ± 44.10% ± 167.90% ± 19.50% ± 26.30% ± 11.60% ± 44.20% ± 14:40 1.58E-09 3.39E-11 1.21E-10 3.53E-10 1.87% 7.09% 1.25% 0.07% 0.56% 2.14% 2.15E-08 ± 1.22E-08 ± 1.08E-07 ± 7.89E-09 ± 57.00% ± 500.70% ± 36.80% ± 11.40% ± 7.30% ± 64.50% ± 14:50 1.00E-09 6.02E-10 2.08E-10 3.33E-10 3.85% 23.42% 2.31% 0.56% 0.31% 4.20% 9.85E-09 ± 9.07E-09 ± 3.15E-07 ± 1.06E-08 ± 92.10% ± 3197.80% 107.10% ± 2.90% ± 3.40% ± 116.40% ± 15:00 3.13E-10 1.86E-11 5.44E-10 2.15E-11 2.93% ± 101.86% 3.43% 0.01% 0.01% 0.34% 6.80E-09 ± 7.80E-09 ± 2.72E-07 ± 7.18E-09 ± 114.80% ± 3997.20% 105.60% ± 2.90% ± 2.60% ± 92.00% ± 15:10 2.37E-11 1.52E-11 4.97E-10 2.33E-11 0.46% ± 15.75% 0.50% 0.01% 0.01% 0.35% 9.48E-09 ± 9.13E-09 ± 4.47E-07 ± 9.62E-09 ± 96.30% ± 4717.40% 101.40% ± 2.00% ± 2.20% ± 105.30% ± 15:20 2.53E-11 2.72E-11 7.72E-10 1.86E-11 0.38% ± 14.98% 0.33% 0.01% 0.01% 0.37% 1.62E-08 ± 1.10E-08 ± 1.38E-07 ± 8.40E-09 ± 67.90% ± 852.50% ± 51.70% ± 8.00% ± 6.10% ± 76.20% ± 15:30 3.16E-11 2.03E-11 6.20E-09 3.88E-10 0.18% 38.29% 2.40% 0.36% 0.39% 3.53% 1.09E-08 ± 9.60E-09 ± 1.75E-07 ± 8.66E-09 ± 87.80% ± 1604.40% 79.20% ± 5.50% ± 4.90% ± 90.20% ± 15:40 2.91E-11 1.67E-11 3.02E-10 1.50E-11 0.28% ± 5.10% 0.25% 0.01% 0.01% 0.22% 1.03E-08 ± 9.44E-09 ± 1.76E-07 ± 8.35E-09 ± 91.80% ± 1711.70% 81.20% ± 5.40% ± 4.70% ± 88.40% ± 15:50 2.43E-11 1.74E-11 3.04E-10 1.70E-11 0.27% ± 5.00% 0.25% 0.01% 0.01% 0.24% 7.40E-09 ± 8.09E-09 ± 2.52E-07 ± 1.07E-08 ± 109.20% ± 3403.80% 144.90% ± 3.20% ± 4.30% ± 132.60% ± 16:00 1.90E-11 1.58E-11 4.86E-10 2.83E-11 0.35% ± 10.93% 0.53% 0.01% 0.01% 0.43% 1.32E-08 ± 1.03E-08 ± 1.23E-07 ± 7.70E-09 ± 78.10% ± 932.40% ± 58.50% ± 8.40% ± 6.30% ± 74.90% ± 16:10 3.11E-11 1.90E-11 2.25E-10 1.41E-11 0.23% 2.78% 0.17% 0.02% 0.02% 0.19% 1.09E-08 ± 9.60E-09 ± 5.57E-07 ± 8.07E-09 ± 88.30% ± 5122.80% 74.20% ± 1.70% ± 1.40% ± 84.00% ± 16:20 3.02E-11 1.77E-11 1.02E-09 1.56E-11 0.29% ± 16.96% 0.25% 0.01% 0.01% 0.22%

184

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192

BIOGRAPHICAL SKETCH

Gabriel Sandler was born in Buenos Aires, Argentina and moved to south Florida at the age of seven. He obtained a BS and MS in nuclear engineering and a minor in sales engineering at the University of Florida. As a graduate student, he worked under

Dr. James Baciak as a fellow of the Consortium for Verification Technology. Gabriel began his graduate work on the utilization of X-ray Backscatter Radiography for non- destructive testing of polymer coated steel and shifted his thesis work to radioactive plume tracking analysis for nuclear security purposes. Gabriel has also interned at

Sandia National Laboratory studying detection characterization of a neutron multiplicity counter and at the National Academies of Science working in the Committee on

International Security and Arms Control. He is a member of the American Nuclear

Society and has served as president and vice-president of the UF Institute of Nuclear

Material Management chapter. After completing his PhD, Gabriel will join the National

Nuclear Security Administration's Office of Cost Estimation and Program Evaluation as a NGFP fellow. In his free time, Gabriel enjoys watching and playing sports, and traveling.

193