mapping fugitive sulfur emissions from texas oil and
TRANSCRIPT
MAPPING FUGITIVE SULFUR EMISSIONS FROM TEXAS
OIL AND NATURAL GAS PRODUCTION FIELDS
by
GARY A. TARVER, B.S.
A DISSERTATION
IN
CHEMISTRY
Submitted to the Graduate Faculty
of Texas Tech University in Partial Fulfillment of the Requirements for
the Degree of
DOCTOR OF PHILOSOPHY
Approved
Accepted
•adiMte Dean of the Gradiiafe School
August, 1995
©1995, GaryA. Tarver
ACKNOWLEDGEMENTS
The author wishes to thank first and foremost Horn Professor Purnendu
K. Dasgupta without whose guidance, insight, support, patience and trust this
study could not have been satisfactorily completed. Dr. Dasgupta has always
maintained a well organized laboratory with a large inventory of both materials
and tools that were essential to the projects undertaken.
Professional advice and assistance from Dr. Jerry Mills, Dr. Dominick
Casadonte, Jr., Dr. Dennis Shelly, and Dr. Richard Took were instrumental in the
completion of this work. Financial support from the Texas Advanced Research
Program for hardware, operations, and salaries was also crucial to the fulfillment
of this project. Assistance in the implementation and interpretation of field
studies was rendered by Jon Hageman and Mahesh Rege.
An important loan of tools and equipment by Bill and Joyce Tarver during
various portions of the study was instrumental to the satisfactory outcome of this
project. And finally the author wishes to thank Pamela Tarver and Dr. David
Harwell for their assistance in final preparation of this manuscript.
TABLE OF CONTENTS
ACKNOWLEDGEMENTS ii
ABSTRACT vii
LIST OF TABLES ix
LIST OF FIGURES x
LIST OF ABBREVIATIONS xii
CHAPTER
1. INTRODUCTION 1
1.1 Introduction 1
1.2 Biogeochemical Cycles 2
1.2.1 The Sulfur Cycle 4
1.3 Transformation of Sulfur Compounds in the Atmosphere 5
1.4 The Global Sulfur Budget 8
1.5 Oil Production and Sulfur Content 11
1.6 Global, Regional, and Local Impact 13
1.7 References 15
2. INSTRUMENTATION DEVELOPMENT AND DEPLOYMENT 23
2.1 Introduction 23
2.2 A Mobile Atmospheric Research Laboratory 23
2.3 An Instrument to Detect Acidic Sulfur Gases 26
2.3.1 Initial Techniques 26
2.3.2 Gas Chromatograph 26
2.3.3 Search for Solid Absorbents 27
2.3.4 Gas Chromatograph/Scrubber/Desorber System 29
iii
2.3.4.1 Introduction 29
2.3.4.2 Scrubber 30
2.3.4.3 Desorber 32
2.3.4.4 Final Configuration of Analytical System 33
2.3.5 Analytical System Performance 35
2.3.6 Analytical System Calibration 36
2.4 Meteorological Data Acquisition 40
2.5 Miscellaneous Data Acquisition 41
2.6 References 43
3. MODELING FUGITIVE EMISSIONS 53
3.1 Introduction 53
3.2 Description of Plume Models 56
3.3 Assumptions of Plume Models 59
3.4 Model Usage 60
3.5 References 61
4. AMBIENT AIR MAPPING 67
4.1 Introduction 67
4.2 Experimental Design 67
4.3 Atmospheric Trends of Reduced Sulfur Gases 68
4.4 Diurnal Pattern 70
4.4.1 Photolytic Decomposition 71
4.4.1.1 Direct Photolytic Decomposition 72
4.4.1.2 Indirect Photolytic Decomposition 73
4.5 Hydrogen Sulfide Rainout 75
iv
4.6 Model Validation Specific for Hydrogen Sulfide 76
4.6.1 Safety 76
4.6.2 Point Source Release of Hydrogen Sulfide 77
4.6.3 Fugitive Emissions of Hydrogen Sulfide from Crude Oil Storage Tank Vents 79
4.7 Conclusions from Atmospheric Studies 84
4.8 References 86
5. SOIL MAPPING 95
5.1 Introduction 95
5.2 Soil Interactions with Atmospheric Sulfur Gases 95
5.2.1 Soil as a Source 97
5.2.2 Soil as a Sink 97
5.2.2.1 Surface Adsorption 97
5.2.2.2 Deposition Accrual 98
5.3 References 104
6. CONCLUSIONS 110
6.1 Summary 110
6.2 Viability of Models 110
6.3 Diurnal Pattern of Hydrogen Sulfide 111
6.4 Fate of Fugitive Sulfur Emissions 111
6.5 References 113
APPENDIX
A. PASCAL COMPUTER SOFTWARE FOR USE WITH DIGITAR PCW COMPUTER WEATHER STATION 114
B. BASIC COMPUTER SOFTWARE FOR USE WITH APPLIED TECHNOLOGIES SONIC ANEMOMETER 120
C. BASIC COMPUTER SOFTWARE FOR CALIBRATION OF APPLIED TECHNOLOGIES SONIC ANEMOMETER 127
D. BASIC COMPUTER SOFTWARE FOR INTERFACE OF METONE PARTICLE COUNTER 131
VI
ABSTRACT
Hydrogen sulfide and other reduced sulfur gases are released into the
atmosphere during oil recovery operations; however, little is quantitatively known
concerning total sulfur flux due to these fugitive emissions. A mobile
atmospheric research laboratory (MARL) was constructed to furnish facile, self-
contained access to oil field sources of reduced sulfur gases. An instrument
able to continuously detect pptv levels of hydrogen sulfide at near real time rates
was developed and subsequently deployed on the mobile platform.
Instrumentation to collect data on other gas and aerosol species along with
information on meteorological conditions was also installed on the MARL.
The MARL was used to collect and log quantitative data in the vicinity of
various oil field operations. Atmospheric sulfur data was collected in the oil
producing regions of several Texas counties including, Lubbock, Hockley, Terry,
and Garza counties. The fugitive emission of hydrogen sulfide was found to be
the major source of atmospheric sulfur, and a strong diurnal pattern was
observed in the ambient hydrogen sulfide concentration. Work was done in the
named regions to classify hydrogen sulfide in terms of source, quantity, and fate.
Crude oil storage tanks and natural gas processing plants were found to be the
major sources of sulfur gas emissions. Estimations of the atmospheric flux of
hydrogen sulfide based upon the atmospheric concentrations recorded indicate
VII
that fugitive emissions of sulfur into the atmosphere are 10 to 30 times higher
than that reported by the oil field operators to the Texas Railroad Commission.
To elucidate the local fate of the fugitive emissions, soil sulfate levels in
the proximity of crude oil storage tanks were determined. Soil sulfate levels
upwind from crude oil tank farms were discovered to be 20 to 200 times higher
than in non-oil producing regions, and the soil sulfate levels directly downwind
from storage tank vents were observed to exceed the upwind levels by a factor
of > 100.
VIM
LIST OF TABLES
1.1 Overview of reactions involved in the oxidation of H2S in the
atmosphere 18
1.2 Ambient atmospheric concentrations of selected species 19
1.3 Estimated atmospheric lifetimes of selected sulfur species 19
1.4 Fluxes (Tg 8 yr' ) of the global atmospheric sulfur cycle 20 1.5 Texas oil production for 1991 tabulated by Railroad Commission
District and month 21
3.1: Meteorological categories A-F, as defined by wind speed, sunlight, and cloudiness 63
3.2 Equations and constants used to calculate the Pasquill-Gifford dispersion coefficients for stability classes A through F as a function of distance, x, from the source 64
IX
LIST OF FIGURES
1.1 Railroad Commission of Texas; Oil and Gas Division; Districts 8 and 8A... 22
2.1. Topdown view of the Mobile Atmospheric Research Laboratory 46
2.2. Center out view of right MARL instrument bay 47
2.3. Diffusion scrubber detail 48
2.4. Diffusion desorber detail 48
2.5 Reduced sulfur gas analytical instrument 49
2.6. Chromatogram indicating response of the reduced sulfur gas analytical
system near the limit of detection for hydrogen sulfide 50
2.7. Sulfur gas calibration system 50
2.8. Typical chromatogram from reduced sulfur gas analytical instrument
using calibrant gases 51
2.9. Calibration of the reduced sulfur gas analytical instrument 52
3.1. Schematic representation of plume dispersion from a point source 65
3.2 Horizontal dispersion coefficient as a function of downwind distance from the source 66
3.3 Vertical dispersion coefficient as a function of downwind distance from the source 66
4.1 Instantaneous (black band) and 10 minute running average (embedded white line) values for wind speed and direction observed on a typical West Texas early morning January 27, 1994 87
4.2 Chromatogram near a natural gas processing plant 88
4.3 Diurnal pattern observed for atmospheric H2S concentrations 88
4.4 Test for effects of atmospheric oxidants on hydrogen sulfide 89
4.5 Effect of rain intensity on atmospheric hydrogen sulfide concentration 89
4.6 Comparison of hydrogen sulfide concentrations calculated from release rate versus that measured from the sampled atmosphere. Results shown for data collected on 9/26/92 90
4.7 Comparison of hydrogen sulfide concentrations calculated from release rate versus that measured from the sampled atmosphere. Results shown for data collected on 10/9/92 91
4.8 Comparison of hydrogen sulfide concentrations calculated from release rate versus that measured from the sampled atmosphere. Calculations are based on revised dispersion coefficients 92
4.9 Measured ambient concentration of hydrogen sulfide near a tank vent and estimated sulfur flux from the vent. Data set is for the Mallet lease in Hockley County as collected on September 5, 1992 93
4.10 Measured ambient concentration of hydrogen sulfide near a tank vent and estimated sulfur flux from the vent. Data set is for the Mallet lease in Hockley County as collected on July 24, 1993 94
5.1 Test chamber to examine H2S interaction with local soil 105
5.2 Contour plot indicating sulfur deposition onto the soil around an oil tank vent 106
5.3 Hydrogen sulfide concentration at ground level along a plume centerline 107
5.4 Depth profile of core samples obtained downwind along radii of 50° and 70° 108
5.5 Depth profile of core samples obtained crosswind along radius of 110°... 109
XI
LIST OF ABBREVIATIONS
CIM
COS
CS2
DMDS
DMS
EMT
FPD
GC
GC-FPD
H2S
i.d.
I/O
kVA
LOD
LPDE
LS-GC-FPD
MARL
MeSH
PBL
PFA
pptv
computer interface module
carbonyl sulfide
carbon disulfide
dimethyl disulfide
dimethyl sulfide
electrical metallic tubing
flame photometric detector
gas chromatograph
gas chromatograph with flame photometric detector
hydrogen sulfide
internal diameter
input/output, inlet/outlet
kilovolt amps (1000 watts)
limit of detection
low density polyethylene
custom liquid-scrubber/gas chromatographic/flame [ analytical system for reduced sulfur gases as de section 2.2
Mobile Atmosphere Research Laboratory
methyl mercaptan
planetary boundary layer
polyfluoroacetate
parts per trillion by volume
XII
PTFE polytetrafluoroethylene
RSD% percent relative standard deviation
RTV room temperature vulcanizing
SLPM standard liter per minute
UPS uninterruptible power supply
VAC volts (alternating current)
VDC volts (direct current)
XIII
CHAPTER 1
INTRODUCTION
1.1 Introduction
The distinct possibility of major changes in the earth's climate system
and/or biosystems as a result of processes that alter concentrations of
atmospheric gases has attracted intense interest in both the scientific world and
the general press. Global warming due to greenhouse gases, acid rain, and
ozone depletion head a list of well-known adverse environmental effects that can
arise from man's activities. The air near the earth's surface contributes not only
the necessary oxygen for life, its constant turbulent motion also allows the
efficient exchange of heat, water vapor, etc., around the global surface.
Atmospheric turbulence also provides expedient dispersion of pollutants and
thereby precludes catastrophic poisoning of life by diluting the byproducts of
geologic, biogenic, and anthropogenic actions. There is the suspicion that
certain human practices are changing the long stable atmospheric conditions of
the earth, and as a result, these actions may affect the environment on a global
scale.
It is at the earth's surface that most gases and particles are introduced
into the atmosphere and, usually following chemical transformation, are removed
from it. The majority of volatile materials and aerosols released near the ground
are quickly mixed throughout the planetary boundary layer (PBL) and the lower
troposphere, and although the PBL comprises only a small portion of the
atmosphere, the processes occurring within it are essential to the survival of life
on earth. Measuring the fluxes of material at the atmosphere-surface interface
and understanding the manifold processes that give rise to these fluxes is a
significant problem in atmospheric chemistry. Understanding the sources, sinks,
and chemical processes of atmospheric gases and particles, as well as their
impact on the local, regional, and global environment is a basic prerequisite to
the development of programs aimed at reducing the negative consequences of
human activities.
1.2 Biooeochemical Cycles
Chemical processes allow the elements requisite for life to cycle from the
earth's geological reservoirs into the biological inventory. Waste from biotic
processes return used elements to the geological reserve, usually in a
chemically altered form. Fundamental inorganic processes, as determined by
the kinetics and thermodynamics of the repository environment, modify the
elements, often restoring them to an assimilable form, and as a result complete
the biogeochemical cycle. Using the cycle approach to describe biogeochemical
processes has both advantages and disadvantages. One of the major
advantages that this technique contributes is an overview of the fluxes, reservoir
quantities, and turnover times; taken in whole, this approach furnishes a basis
for quantitative modeling (Rodhe, 1992).
Understanding the biogeochemical cycles requires study and elucidation
of the myriad chemical and physical processes that occur in the biosphere. A
considerable body of data and theory has been assembled concerning the
chemical processes of both the relatively stable stratosphere distant from the
earth's surface, and the more turbulent troposphere adjoining the earth's
surface. Insight into the sources, sinks, and chemical processes of atmospheric
gases and particles has increased significantly; however, our present knowledge
is still incomplete.
Of all the elements prevalent in the biosphere, the most essential to life
are carbon, hydrogen, oxygen, nitrogen, phosphorus, sulfur. Four of these
crucial elements (i.e., carbon, nitrogen, oxygen, and sulfur) are doubly mobile, a
characterization based upon their ease of transport in both the atmosphere and
the hydrosphere. The physics and chemistry of these four elements constitute
the most studied biogeochemical cycles, with the carbon, nitrogen, and sulfur
cycles regarded as the ones most affected by human activities (Smil, 1985;
Lovelock, 1987). Of these four, the sulfur cycle is ostensibly the most perturbed
by anthropogenic activities. Some estimates suggest that the contemporary
global flux of sulfur compounds is 100 per cent greater than during the
preindustrial era (Kellogg etaj., 1972; Smil, 1985).
1.2.1 The Sulfur Cycle
The biogeochemistry of sulfur forms one of the most complex cycles.
Sulfur exists in a variety of oxidation states from -2 to +6, and it is incorporated
into numerous organic and inorganic compounds. In the hydrosphere, the
sulfate ion Is ubiquitous, being the second most prevalent ion in both surface
waters and sea water. This large background of sulfate ion has presented
challenges in the quantification of small fluctuations in sulfur concentrations, a
requisite for the determination of sulfur flux at a reservoir boundary. Conversely,
in the atmosphere sulfur concentrations are so small that only recently have
advances in analytical methods provided detection limits sufficient to make
measurements of transfer rate.
The majority of the anthropogenic sulfur emitted into the atmosphere is in
the form of either SO2 or SO/' , and the atmospheric chemistry of these
compounds has been extensively studied. Conversely, the atmospheric
chemistry of reduced sulfur gases is dominated by oxidation, which hampers
collection, concentration, and analysis in the highly oxidative atmosphere. As a
result, the reduced sulfur compounds, which include hydrogen sulfide (H2S),
carbon disulfide (CS2), dimethyl sulfide (DMS), dimethyl disulfide (DMDS),
methyl mercaptan (MeSH), carbonyl sulfide (COS) and others, have not been
studied as thoroughly.
1.3 Transformation of Sulfur Compounds in the Atmosphere
The concentration of hydrogen sulfide in the lower atmosphere is
attenuated by both physical and chemical processes. Physical removal of the
hydrogen sulfide occurs due to rainout, washout, and dry deposition.
Chemically, the ultimate fate of all sulfur compounds released into the
atmosphere is their oxidation to sulfate (Seinfeld, 1986). Table 1.1 presents an
overview of the reactions involved in oxidation of atmospheric hydrogen sulfide,
with accompanying rate coefficients and heats of reaction where known. Table
1.2 gives the average atmospheric concentrations in the unpolluted troposphere
of the oxidants in Table 1.1, as well as hydrogen sulfide. For all of the species
listed, except molecular oxygen and ozone, the reported concentrations are
quite variable depending upon a variety of conditions such as altitude, latitude,
season of year, time of day, local conditions, etc. (Natusch et aj., 1972;
Jaeschke et a!., 1980; Servant and Delpart, 1982; Spedding and Cope, 1984;
Warneck, 1988; Thompson et a]., 1993; Yvon et a]., 1993).
The primary oxidizing agent for hydrogen sulfide is thought to be the
hydroxyl radical, although ozone (O3), atomic oxygen (O), molecular oxygen
(O2), hydroperoxyl (HO2), hydrogen peroxide (H2O2), and oxides of nitrogen
(NOx) may also play important roles in certain reaction pathways. The oxidation
of hydrogen sulfide begins with abstraction of hydrogen, with the most probable
mechanism being Reaction 4 (Table 1.1). In addition, this reaction is also widely
considered to be the rate limiting step In the oxidation of H2S. This scheme is
also substantiated by the fractional kinetic orders, autocatalytic behavior, and
chemiluminescence; all of which imply a radical induced chain mechanism.
Laboratory studies report a pseudo second order rate constant between
3.1 X 10' ^ and 5.9 x 10' ^ cm^ molecule' s" (Jaeschke et a]., 1980; Servant and
Delpart, 1982; Spedding and Cope, 1984; Barnes etaj., 1986; Toon et aj., 1987;
Thompson et aj., 1993; Yvon et a]., 1993) for this reaction, with
5.9x10"^^exp(-65/T) cm^ molecule' s' being the most widely accepted value.
For T=298 K, calculations from this equation give a rate constant of 4.74 x 10" ^
cm^ molecule' s'\
The abstraction of hydrogen by ozone (Reaction 1, Table 1.1) has been
suggested as an important reaction in the atmospheric oxidation of hydrogen
sulfide (Becker etaj., 1975). Concentration and kinetic data indicate a rate
constant greater than 3 x 10' ^ cm^ molecule" s' would be required for O3 to
become a significant competitor of OH (Warneck, 1988). With a reported rate
constant of less than 2 x 10' ° cm^ molecule" s' (Becker etaj., 1975), it is
apparent that hydrogen abstraction by O3 is negligible as gauged against
abstraction by OH. Atomic oxygen reacts with H2S quickly on an absolute scale
(Reaction 2, Table 1.1). However, tropospheric concentrations of atomic oxygen
are generally an order of magnitude lower than that of OH. In addition, the
reaction rate is two orders of magnitude slower than that with OH. Calculations
from this data indicate atomic oxygen is an insignificant competitor in the
oxidation of hydrogen sulfide.
The Initial formation of the sulfhydryl radical is followed by several
reactions that lead ultimately to the production of SO2. Many of these
transformations, however, can only be identified as "multistep" processes
because the detailed chemistry is not currently well characterized (Charlson et
aJ., 1992). The rates at which most of the transformations occur are also poorly
understood and have for the most part been estimated only semi-quantitatively.
Present understanding suggests rapid oxidation of the HS radical by either
molecular oxygen or ozone (Table 1.1, Reactions 5 and 6). Although SO is
proposed as a transitional moiety in some cases, sulfur dioxide is the key result
from gas phase oxidation of reduced sulfur compounds.
As with the oxidation of reduced sulfur species, pathways for the oxidation
of atmospheric SO2 are complex and have not yet been fully characterized.
Elucidation of the many reaction pathways is hampered in part due to the
multifaceted nature of the oxidation. The reactions occur in the gas phase, in
fog or cloud droplets, as well as on the surface of aerosol particles. The most
likely gas phase oxidants of sulfur dioxide are the radicals OH, HO2, RO2, and
Criegee intermediates, whereas reactions with O3, NO3, CH3O, and O2 are
considered insignificant in the atmosphere (Warneck, 1988).
In addition to gas phase reactions, aqueous phase oxidation occurs
where SO2 has dissolved into the water of clouds or fogs, this must also be
considered. Sulfur dioxide dissolves to some extent In liquid water, the quantity
of which can be determined based on its partial pressure and a Henry's law
constant of 1.24 M/atm (Stumm and Morgan, 1981). In the aqueous phase, SO2
forms HSO3' and SOs^'which are subject to oxidation by dissolved oxygen,
ozone, and hydrogen peroxide. The chemistry of the aqueous phase is
complicated by a multitude of equilibrium relations between aqueous species
and partitioning of reactants and products between the aqueous and gaseous
phases. There is also interplay between the cloud condensation nuclei upon
which the droplets form. These nuclei often contain metals capable of catalyzing
the reactions between sulfur dioxide and the oxidants (Warneck, 1988), and
their effect on rates of reaction must be considered.
1.4 The Global Sulfur Budget
An important contribution of the global cycles and of atmospheric
chemistry is their use in calculating the lifetimes for various atmospheric species.
The lifetimes for a number of sulfur species is indicated in Table 1.3. With the
exception of carbonyl sulfide, most sulfur species have short atmospheric
residence times, measured in days. The short lifetimes as compared to global,
or even hemispheric mixing time, result in nonhomogeneity of the atmospheric
reservoir. As a consequence, patchy geographical distribution occurs, a fact
with important implications for studies of sulfur in the environment. Although
anthropogenic emissions certainly constitute an overwhelming augmentation of
8
atmospheric sulfur in heavily industrialized regions, there may be large portions
of the earth where human activities scarcely influence the sulfur cycle (e.g.,
much of the southern hemisphere). In addition, it is apparent that the sulfur
cycle can be realistically studied only on a regional basis; therefore, the
calculation of global sulfur budgets is obligatorily an unavoidably laborious
process of collecting a myriad of seasonal measurements over a number of
regions followed by statistical averaging.
Among the sulfur species, the most studied are sulfate deposition to the
surface of the earth via rainwater, and sulfur dioxide emissions from combustion
sources. The primary increase in the source of sulfur has been associated
primarily with the burning of biomass, coal, oil, and gas as energy sources.
Calculations using chronicled data pertaining to fossil fuel consumption have
provided a reliable estimation of the sulfur flux resulting from energy
consumption. Combustion wastes contribute approximately 85 to 90% of the
anthropogenic sulfur in the atmosphere, with 95% of the sulfur gases being
released as SO2 (Kellogg etaj., 1972; Cullis and Hirschler, 1980; Smil, 1985).
The only other major man-made contribution to atmospheric sulfur is attributed to
the smelting of non-ferrous ores, which account for roughly 10% of the total
(Cullis and Hirschler, 1980; Warneck, 1988). These two documented sources
contribute essentially the whole of the total sulfur flux, and the emissions from
these sources has received significant investigation. However, there has been
less attention paid to other sources for atmospheric sulfur including reduced
sulfur gases arising as fugitive emissions during the production of natural gas
and oil.
Total sulfur emissions into the biosphere are not always directly
measured, but are frequently estimated based upon the sulfur content assayed
for a reservoir coupled with the sources and sinks of the reservoir (National
Research Council, 1978). The values for sulfur compounds released into the
atmosphere are based on the following two assumptions (Cullis and Hirschler,
1979):
1. Sulfur compounds are not accumulating in the atmosphere,
2. Sources introducing sulfur to the atmosphere are balanced by sinks
removing sulfur from the atmosphere.
Because of the patchy and episodic nature of atmospheric sulfur distribution, the
resulting calculations based on these assumptions has lead to widely varying
values for both the total emissions and the flux of sulfur compounds in the
atmosphere (National Research Council, 1978; Aneja, 1990).
Reviews of the estimates of the global sulfur budget (total annual flux of
sulfur through the atmosphere) indicate disagreement between the various
investigators (Kellogg etaj., 1972; Cullis and Hirschler, 1979; Moller, 1984; Smil,
1985; Aneja 1990). Table 1.4, based on Aneja (1990), illustrates the disparity in
the sulfur budget estimates as presented in one of the reviews. There is also
disagreement concerning the contribution of the various natural and
anthropogenic sources to this total sulfur budget. An accurate balancing of the
10
global sulfur budget is possible only with a more accurate knowledge of the
amount of sulfur compounds released from all of the various geological,
biogenic, and anthropogenic sources. Increased reliability of sulfur flux
estimates resulting from these sources would be of significant interest in many
regions, including the State of Texas, a major producer of oil and natural gas.
An extensive search of available databases indicated, however, that no data
relative to oil field fugitive emissions are available for Texas, or for that matter,
any other part of the continental United States.
1.5 Oil Production and Sulfur Content
The Oil and Gas Division of the Railroad Commission of Texas is the
state agency that has oversight and regulatory responsibility for the oil and
natural gas industry in Texas. The map in Figure 1.1 delineates the Texas
Railroad Commission Districts 8 and 8A, which constitute the oil fields of West
Texas (Guerrero et a]., 1991). West Texas Intermediate Crude oil is a
benchmark for crude oil and is not considered to be a substantially "sour" crude.
Nevertheless, even from such "sweet" crude oil, a significant outgassing of
hydrogen sulfide is apparent even to a casual traveler passing by a West Texas
oil field. The shaded areas in Figure 1.1 silhouette the underground oil
reservoirs of the San Andres, Fusselman, Edwards, and Smackover formations
(Garlick, 1992), which are associated with the major areas of sour gas
production in Texas. The high levels of sour gas production in the West Texas
11
area Is partially explained by the fact that over 50 percent of the statewide oil
production comes from Districts 8 and 8A. Table 1.5 tabulates the 1991 oil
production by month for all Railroad Commission Districts. The 1991 totals for
districts 8 and 8A accounted for 342,716,116 of the state total 644,514,016
barrels recovered.
The flux of sulfur gas associated with the production of 645 million barrels
(103x10^ liters) is not precisely known. In addition, because of the regional
nature and assumed minor contribution to the total atmospheric sulfur burden,
this source has not been accounted for in the sulfur budgets thus far reported in
the literature. However, information on the fugitive emissions related to oil
production is important on a local basis to West Texas communities, and on a
larger scale, in increased scope of the global sulfur budget. The scope of the
work described in this dissertation was to quantify reduced sulfur gases in the
atmosphere providing a database from which to calculate the flux associated
with oil production. The basic requirements were an instrument capable of real
time hydrogen sulfide concentration measurements, means of recording
fundamental meteorological, temporal, and spatial parameters, and a method of
deploying the equipment to field locations. The development and deployment of
a Mobile Atmospheric Research Laboratory (MARL) outfitted with both
meteorological instruments and a sensitive sensor for the near real time
detection of reduced sulfur gases was proposed as the best method for the
investigating the contribution of H2S to the Texas sulfur budget. The
12
development of a suitable measurement technique, acquisition of data, and
conclusions therefrom form the basis of the following chapters.
1.6 Global. Regional, and Local Impact
The conspicuous pathway of sulfur through the atmosphere originates
with the injection of low oxidation state gases followed eventually by removal as
sulfate. This pathway involves a change in oxidation state and phase, and
consequently the lifetime of sulfur in the atmosphere is regulated by both the
kinetics of the chemistry and physics of the atmosphere. Presently, the sulfur
gases present in the atmosphere are believed to be approximately 50% from
natural origins and 50% man-made, although an ever increasing fraction is
coming from anthropogenic activities (Aneja, 1990). Although the flux of sulfur
through the atmosphere is quite large, ca. 103 Tg S yr" (Kellogg et aj., 1972;
Cullis and Hirschler, 1979; Moller, 1984; Smil, 1985; Aneja, 1990), the
instantaneous quantity present is quite low due to the short turnover time of the
species present. Associated with the short turnover time is the lack of
homogeneity in the atmospheric reservoir, resulting in inadequate geographical
coverage of the existing database (Andreae, 1990). The situation at present is
perhaps characterized best by Charlson who reports "In sum, the qualitative
picture of the atmospheric sulfur cycle now appears to be in good focus,
although many quantitative details remain to be filled in" (Charlson et a]., 1992,
p. 298). In an attempt to reduce the ambiguity of some of the data and
13
estimations in regards to the biosphere's sulfur cycle, the impact of the fugitive
emissions of reduced sulfur gases from oil and gas recovery operations was
studied.
14
1.7 References
Andreae M. O. (1990) Ocean-atmosphere interactions in the global biogeochemical sulfur cycle. Marine Ctiemistry 30,1-29.
Aneja V. P. (1990) Natural sulfur emissions into the atmosphere. Journal of the Air and Waste Management Association 40, 469-476.
Barnes I., Bastian V., Becker K. H., Fink E. H. and Nelsen W. (1986) Oxidation of sulphur compounds in the atmosphere: I. Rate constants of OH radical reactions with sulphur dioxide, hydrogen sulphide, aliphatic thiols and thiophenol. Journal of Atmospheric Chemistry^, 445-466.
Becker K. H., Inocenncio A. and Schurath U. (1975) The reaction of ozone with hydrogen sulfide and its organic derivatives. International Journal of Chemical Kinetics 7, 205-220.
Charlson R. J., Anderson T. L and McDuff R. E. (1992) The Sulfur Cycle. In Global Biogeochemical Cycles, Vol. 50, (edited by Butcher S. 8., Charlson R. J., Orians G. H. and Wolfe G. V.), Academic Press, San Diego.
Cullis C. 8. and Hirschler M. M. (1979) Emissions of sulphur into the atmosphere. Symposium: Sulphur Emissions and the Environment, paper 1, The Society of Chemical Industry, London.
Cullis C. 8. and Hirschler M. M. (1980) Atmospheric Sulfur: Natural and man-made sources. Atmospheric Environment A^, 1263-1278.
Garlick D. M., Ed. (1992) Statewide Rule 36 Hydrogen Sulfide Safety. Railroad Commission of Texas Field Operations - Oil and Gas Division, Austin.
Guerrero L., Nugent J. E. and Krueger B. (1991) 1991 Oil and Gas Annual Report: Volume 1. Railroad Commission of Texas: Oil and Gas Division. 1991
Jaeschke W., Claude H. and Herrmann J. (1980) Sources and sinks of atmospheric H2S. Journal of Geophysical Research S5, 5639-5644.
Kellogg W. W., Cadle R. D., Allen E. R., Lazrus A. L and Martell E. A. (1972) The sulfur cycle. Science 175, 587-596.
Lovelock J. E. (1987) Gaia, Oxford University Press, New York.
Moller D. (1984) On the global natural sulphur emission. Atmospheric Environment ^^, 29-39.
15
National Research Council: Committee on Medical and Biological Effects of Environmental Pollutants: Subcommittee on Hydrogen Sulfide (1978) Hydrogen Sulfide, University Park Press, Baltimore.
Natusch D. F. 8., Klonis H. B., Axelrod H. D., Teck R. J., James P. and Lodge J. (1972) Sensitive method for measurement of atmospheric hydrogen sulfide. Analytical Chemistry 4, 2067-2069.
Rodhe H. (1992) Modeling Biogeochemical Cycles. In Global Biogeochemical Cycles, Vol. 50, (edited by Butcher 8. 8., Charlson R. J., Orians G. H. and Wolfe G. v.). Academic Press, San Diego.
Seinfeld J. H. (1986) Atmospheric Chemistry and Physics of Air Pollution, John Wiley and Sons, New York.
Servant J. and Delpart M. (1982) Daily variation of the H2S content in atmospheric air at ground-level in France. Atmospheric Environment ^6, 1047-1052.
Smil V. (1985) Carbon, Nitrogen, Sulfur, Plenum Press, New York.
Spedding D. J. and Cope D. M. (1984) Field measurements of hydrogen sulphide oxidation. Atmospheric Environment 1Q, 1791-1795.
Stumm W. and Morgan J. J. (1981) Aquatic Chemistry John Wiley and Sons, New York.
Thompson A. M. Johnson J. E. Torres A. L Bates T. 8. Kelly K. C. Atlas E. Greenberg J. P. Donahue N. M. Yvon 8. A. Saltzman E. 8. (1993) Ozone observations and a model of marine boundary layer photochemistry during SAGA 3. Journal of Geophysical Research 98,16955-16968.
Toon O. B., Kasting J. F., Turco R. P. and Liu M. 8. (1987) The sulfur cycle in the marine atmosphere. Journal of Geophysical Research 92, 943-963.
Warneck P. (1988) Chemistry of the Natural Atmosphere, Academic Press, Inc., San Diego.
Yin F., Grosjean D. and Seinfeld J. H. (1990) Photooxidation of dimethyl sulfide and dimethyl disulfide. I: Mechanism development. Journal of Atmospheric Chemistry 11, 309-364.
Yvon 8. A., Cooper D. J., Koropalov V. and Saltzman E. 8. (1993) Atmospheric hydrogen sulfide over the equatorial Pacific (SAGA 3). Journal of Geophysical Research 98, 16979-16983.
16
Zhang G., Dasgupta P. K. and Sigg A. (1992) Determination of gaseous hydrogen peroxide at parts per trillion levels with a Nafion membrane diffusion scrubber and a single-line flow-injection system. Analytica Chimica Acta 260, 57-64
17
Table 1.1 Overview of reactions involved in the oxidation of H2S in the atmosphere.
10.
Reaction
1. H2S + O3
2. H2S + O
3. H2S + HO2
4. H2S + OH
5. HS + O2
6. HS + O3
7. HSO + O2
8. HSO + O3 9. SO + O2
8 0 + 0.
Heat of Reaction (kJ/mol)
^298
products
HS + OH
products
HS + H2O
OH+ 80
SO2 + H
HSO + O2
OH + SO +
HO2 + SO
OH + SO +
SO2 + O
SO2 + O2
0
O2
-114
-102
-225
<-234
+4
<+27
-77.8
-52.6
-445
(cm /molecule s)
2 x 1 0 •20
2.7x10
5 x 1 0
-14
•12
5.2x10 -12
< 4 x 10
3.1 xlO
-17
•12
9 x 1 0
6 x 1 0
-18
14
Sources: Toon et aj., 1987; Warneck, 1988; Yin et aj., 1990; Thompson etaj., 1993.
18
Table 1.2 Ambient atmospheric concentrations of selected species.
Compound Ambient Concentration 3x (molecule cm')
O3 5.01x10^^
O2 5.38x10'^
O I.OxlO^to 1.0x10^
OH 6.0x10^ to 7.0x10^
H2O2 1.08x10^^
H2S 8.0x10^ to 8.0x10^
Sources: Kellogg eta]., 1972; Natusch etaj., 1972; Jaeschke eta]., 1980; Servant and Delpart, 1982; Spedding and Cope, 1984; Warneck, 1988; Zhang et aj. 1992; Thompson et a]., 1993; Yvon etaj., 1993.
Table 1.3 Estimated atmospheric lifetimes of selected sulfur species.
Compound Lifetime in the troposphere
H2S
CH3SH
CH3SCH3
CH3SSCH3
CS2
COS
S02
0.4 - 4.4 days
0.3 days
0.6 days
0.1 days
12 days
44 years
0.5-6 days
Sources: Natusch etaj., 1972; Jaeschke et a]., 1980; Servant and Delpart, 1982; Spedding and Cope, 1984; Warneck, 1988; Thompson etaj., 1993; Yvon et a]., 1993.
19
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SAN ANDRES
SIVIACKOVER
Figure 1.1 Railroad Commission of Texas; Oil and Gas Division; Districts 8 and 8A. Shaded portions indicate areas of major sour gas production in the state (Guerrero et a)., 1991; Garlick, 1992).
22
CHAPTER 2
INSTRUMENTATION DEVELOPMENT
AND DEPLOYMENT
2.1 Introduction
A project to estimate sulfur fluxes from local West Texas oil and natural
gas operations was envisioned. The strategy was based on recording multipoint
measurements of sulfur gases in the regions of interest. The subsequent map of
sulfur concentration data combined with simultaneously recorded meteorological
parameters would be examined via available dispersion models to estimate
sulfur fluxes due to the fugitive emissions. Obtaining the necessary information
in an opportune and timely manner required facile deployment from a mobile
platform, relatively low power consumption, and unattended operation.
2.2 A Mobile Atmospheric Research Laboratory
A Mobile Atmospheric Research Laboratory (MARL) provided convenient
and quick deployment of the required battery of instrumentation and support
services. The MARL was constructed on a 25 foot Southwind Motorhome as
originally manufactured by Fleetwood Corporation. Extensive modifications
were required to convert the motor home into a working laboratory. The toilet,
shower, bedroom, and wardrobe facilities were removed. The carpeting was
also removed and replaced with vinyl flooring. The original gasoline powered
23
3.5 kVA power generator was replaced with a liquid propane powered generator
which provided 6.5 kVA 110 VAC power. The propane fuel was preferred to
minimize atmospheric inferences and no detectable emissions from this source
were apparent when the generator exhaust was vented downwind.
The interior rear portion of the MARL was fitted with a framework of B-22
struts (B-line Systems, Highland, IL) to provide adjustable/expandable
instrument bays. The strut skeleton also enhanced the structural integrity of the
MARL for anticipated off-road excursions. Shelving fabricated from 1.6 cm birch
plywood was secured to the skeletal framework and provided a means of support
and attachment for the instrumentation. A general layout of the MARL as shown
in Figure 2.1, indicates placement of the two main instrument bays, one located
on each side at the rear of the vehicle. Each multitier bay was approximately 3
m X 0.76 m, with a 0.76 m aisle/access-area in between.
The motorhome was originally equipped with a distribution system for
both of the factory installed electrical systems (12 VDC and 120 VAC).
However, there was a need to remove unnecessary and/or abandoned portions
of the 12 VDC system and reroute it to the instrument bays. The hollow strut
was used as a raceway for the 12 VDC wires and outlets were placed on each
upright of the strut framework. The 12 VDC battery-backed system was used to
provide uninterruptible power for certain mission critical equipment located in the
MARL. The original distribution system for the 120 VAC power was too small to
safely handle the increased generator capacity. Because the new generator
24
provided separate 3.5 and 3.0 kVA sources, the original system could be
connected to either of these sources without overload. As a result, no
distribution main was required to limit power into the original system. A second
120 VAC panel dedicated to the instrument bay and air compressor was
installed to manage the increased generator capacity. Plugmold® brand
sequential outlets, with a single 15 amp receptacle located every 6 inches, was
installed across the back of each shelf to provide AC power to the instrument
bay area. Regulation of the power supply was necessary for proper operation of
the computers, CIMs, and ozone monitor, and was provided via a power line
conditioner (Sola Electric, Chicago, IL).
Plumbing and pneumatic distribution lines were installed through both
instrument bays. Figure 2.2 shows the front view of the H2S measurement
instrumentation bay. Compressed gas cylinders with a capacity of 244 cubic
feet each were secured in the cylinder bay as indicated. The cylinders of
nitrogen, hydrogen, and breathing air provided carrier gas, FPD fuel, and safety
air respectively. A 3/4 HP air compressor able to provide 2 cfm @ 90 psi was
installed in the subfloor area. Compressed air storage was provided by a 7.5
gallon tank mounted externally under the MARL. The compressed air assembly
provided both consumable air and pneumatic power for the instruments. A
sampling inlet was installed 1.7 m above the MARL roof to provide atmospheric
samples from 5 meters above ground level. Ambient air was continuously drawn
from this inlet via PTFE Teflon tubing (9 SW, 3 mm i.d., 4 mm o.d.; Zeus
25
Industrial Products, Raritan, NJ) from which a simple manifold distributed the
sample air to the various instruments. All flow rates were controlled with mass
flow controllers (Tylan General, Torrance, CA) which were operated between
10% and 100% of their rated range.
2.3 An Instrument to Detect Acidic Sulfur Gases
2.3.1 Initial Techniques
Initially we believed that direct measurement by gas chromatography-
flame photometric detection (GC-FPD) as described by Steudler (1984) would
provide sufficient detection sensitivity at the anticipated field concentrations.
Experience indicated, however, that the sensitivity and detection limits of this
technique were inadequate to obtain reliable measurements even within a few
hundred meters of typical point sources in the region. Even increasing the
chromatographic sample loop size to a very large value (e.g., 10 mL) was
ineffective in overcoming the limitations of this method. Because early
experiments indicated H2S to be substantially the most abundant sulfur gas,
attention was centered on methods to analyze low concentration of this species.
2.3.2 Gas Chromatograph
Benner and Stedman recently evaluated the performance of commercial
instruments available for the indirect measurement of sulfur gases (1990). The
reported results made it clear that reliable measurement at the sub-ppbv level is
26
not possible by such instruments. The literature also contains examples of
direct measurement techniques that have not necessarily become
commercialized, and these methods were appraised as to their utility. Of these,
chemiluminescence detection based on reaction with CIO2 (Spurlin and Yeung,
1982), O3 (Kelly etaj., 1983) and formation of excited SO (Benner and Stedman,
1989) have been reported. With a limit of detection (LOD) of 130 parts per
trillion by volume (pptv), the last technique is the only one with an adequately
low threshold for the intended purpose. However, based on the published
characteristics, it would be difficult to use this approach in an environment with
large concentrations of hydrocarbons. Johnson and Lovelock have described an
extraordinarily sensitive technique based on an electron capture detector (1988).
However, the need for extremely aggressive reagents like fluorine led us to
decide against its use. Complex methods such as gas chromatography/isotope
dilution mass spectrometry (Bandy etaj., 1985; Lewin et aJ., 1987) were beyond
both our means and expertise.
2.3.3 Search for Solid Absorbents
The capabilities of real-time sulfur detectors are currently being stretched
to the limit (Benner and Stedman, 1990) and improved, more sensitive detectors
are needed. A common method of enhancing instrumental detection limits and
sensitivity is to preconcentrate the sample prior to chromatographic analysis.
One established method of preconcentration is cryogenic trapping and this
27
procedure has been reported by several authors (Sandalls and Penkett, 1977;
Farwell et aj., 1980; Leek and B^gander, 1988). However, the attainable
temporal resolution coupled with anticipated difficulties in field deployment to
remote locations suggested that alternatives should be sought.
Preconcentration by capturing the analyte onto an appropriate solid sorbent
followed by thermal desporption has also been reported by a number of authors
(Black eta]., 1978; Bandy etaj., 1985). However, a limited number of operating
cycles (on the order of 1-2) were reported for these adsorbents.
Because of the potential ease of use and simplicity of regeneration, a
considerable amount of effort was expended in the search for an appropriate
solid sorbent. Trials with different solids including molecular sieves 4A and 5A,
activated carbon, Tenax GC, Hayesep® D, Carbopack®-BHT-100, and silica gel
were largely unsuccessful. Breakthrough experiments indicated that each of
these materials had some affinity for reduced sulfur gases with some candidates
exhibiting exceptional capacity for H2S adsorption. However, we could not
achieve reproducible recovery over a large number of thermal desorption cycles
with any of these sorbents. In most cases, the analyte desorption was a slow
process, often accompanied by sample decomposition and at least in one case
sorbent decomposition. For Hayesep® D, the solid sorbent was found to be
stable up to 100°C in ambient air, but the material with sorbed hydrogen sulfide
or methyl mercaptan decomposed at 76°C and fouled the chromatographic
28
system. We have since learned that other researchers searching for suitable
sorbents have encountered similar difficulties (Farwell, 1992).
Kagel and Farwell (1986) have reported a preconcentration technique
using adsorption of reduced sulfur gases onto suitable metal foils followed by
flash volatilization. When the sample is flashed from the foil in ambient air it is
also oxidized, thus preventing chromatographic separation of the collected
components. Because the foils have varying affinities toward different reduced
sulfur species, calibration for a multi-component matrix mimicking the anticipated
field conditions is necessary and difficult. Several authors have also reported on
the use of filter collection methods followed by off-line analysis (Natusch et aj.,
1972; Jaeschke, 1978; Farwell etaj., 1987). However, these methods do not
allow the temporal resolution necessary for the plume dispersion studies, and
they have a tendency to introduce artifacts due to interactions of the samples
with particulate matter collected on the filter surface. The search for a solid
desorber was therefore abandoned and attention was focused toward other
preconcentration techniques.
2.3.4 Gas Chromatograph/Scrubber/Desorber System
2.3.4.1 Introduction
Diffusion denuders have been effectively used as a means of collecting
and preconcentrating atmospheric gases (Perm, 1979, 1986). The simplest form
29
of a diffusion denuder is a tube which has its inner surface coated with an
appropriate sorbent. The sample gas is drawn through the denuder where the
analyte diffuses to the surface and is adsorbed by the coating. After sampling
for a prescribed period, the analyte laden coating is washed from the denuder
and the analyte measured therein. There exists a variety of geometries
available for the device and the coated surfaces but the principle of operation is
the same in each case. With the exception of the artifacts from particulate
matter, the impediments enumerated for filter collection/off-line analysis would
apply to this device as well. However, if a collecting surface were continuously
renewed and the analyte continuously removed from the system, facile
integration into an on-line continuous analyzer could be possible.
2.3.4.2 Scrubber
The membrane-based diffusion scrubber first described by Dasgupta
(1984) in 1984 provides a denuder with a continuously regenerated sorption
surface. In the diffusion scrubber, a membrane replaces the collecting surface
and the sample gas is drawn across one side of this membrane. An absorbing
scrubber liquid flows across the opposite surface of the membrane and
transports the collected analyte away for detection. The original diffusion
scrubbers used a hydrophilic cation exchange membrane but the availability of
inert polypropylene membrane tubes with surface porosity in the range of 70%
have contributed to simpler scrubber designs of increased utility. The average
30
0.2 pm pore size of these hydrophobic membrane tubes, in combination with the
high surface tension of the aqueous scrubber solution, impedes liquid flow
across the membrane but allows ready diffusion of the gaseous analyte into the
aqueous medium. Diffusion scrubbers have been successfully used to collect a
variety of atmospheric trace gases into a liquid stream for analysis and
quantification (Dasgupta, 1984, 1993; Dasgupta etaj., 1986, 1988; Simon and
Dasgupta, 1993; Tanner et a]., 1986).
The acidic sulfur gases, in particular hydrogen sulfide with its large
diffusion coefficient and acid nature, should be effectively collected by an
alkaline scrubber liquid. Sensitive methods for wet analysis of collected sulfide
have been described (Dasgupta and Yang, 1986; Kuban etaj., 1992). However,
it was desirable to use the gas chromatograph (GC) and associated equipment
that was already installed in the MARL from initial attempts to develop a direct
injection gas chromatograph with flame photometric detector (GC-FPD) based
method. By acidifying the collected aqueous stream, the acidic gases collected
in the liquid phase would be liberated back into the gas phase, thus allowing
analysis by GC-FPD. A membrane desorber, very similar in design to the
membrane scrubber, was fashioned to release the acidic gases into a N2 stream
for chromatographic analysis. The final assemblage allowed sensitive
measurement of ambient H2S and lower mercaptans with a temporal resolution
of 2.5 minutes per sample.
31
Figure 2.3 shows the construction of the scrubber used in the sulfide
detector. Fabrication began by reaming out one end of a 1/4-inch tee (A) such
that a 9 gauge (3.0 mm internal diameter (i.d.)) PTFE tube (B) would seal when
inserted up to the cross arm. A length of Accurel® tubular membrane (C) was
inserted through the full 20 cm length of the jacket tube (B) and allowed to
extend ~4 mm past the end of each tee. A length of 13 gauge (1.9 mm i.d.)
PTFE tubing (E) was force-fitted into each end of the membrane tube (C),
compressing it against the tee's inner surface thereby sealing the fluid channel
(D) at the scrubber ends. A PTFE spacer (F) provided a secure connection of
the 30 gauge (0.33 mm i.d.) PTFE liquid inlet/outlet line (G) while restricting
dead volume to a minimum. During sampling operations the air sample was
aspirated through the center lumen of the scrubber at 3.5 to 6 standard liters per
minute (SLPM).
2.3.4.3 Desorber
A porous polypropylene membrane tube was utilized to fabricate the
desorber as well. The desorber, as indicated in Figure 2.4, differs from the
scrubber in size as well as in other details. Construction was similar to that
described for the scrubber. A 3/16 inch tee (T) was enlarged at one end
permitting insertion of a 21 cm length of 12 gauge (2.2 mm i.d.) PTFE tubing (B)
to form the external shell. Aqueous solution enters and leaves the desorber via
32
24 gauge (0.56 mm i.d.) PTFE tubing (I) sealed into the desorber via plug (P)
which was formed from a 6 mm length of 1.0 mm i.d. poly vinyl chloride pump
tubing. The scrubber solution passes next through a 17 cm length of the tubular
membrane lumen (M) releasing the acidic gases into the nitrogen flow and then
to waste (W). A 16 cm length of a solid Teflon rod (not shown) was inserted into
the membrane's center to reduce the dead volume of the aqueous pathway.
Nitrogen enters and exits the desorber via 13 gauge (1.9 mm i.d.) PTFE tubing
Nl and NO respectively. Typically, the nitrogen flows through the 0.75 mm
annular space between the membrane and desorber shell at 4.0 standard cubic
centimeters per minute (SCCM).
2.3.4.4 Final Confiouration of Analvtical Svstem
Figure 2.5 is a block diagram indicating arrangement of the components
for the custom liquid-scrubber/gas chromatographic/flame photometric system
for analysis of reduced sulfur gases (LS-GC-FPD). Sampling occurs in the
scrubber portion of the device where ambient air is aspirated into the inlet (I) and
dumped to waste (W) by the diaphragm pump (P). The spent sample air exits
the diffusion scrubber via a vacuum flask (VF) which protects the down stream
components from the caustic liquid in the case of an accidental membrane
failure. The soda lime cartridge (SL) protects the mass flow controller (FA) and
pump from corrosive gases, whereas the 4 liter reservoir (R) dampens air flow
pulsation caused by the diaphragm pump.
33
A 0.1 M sodium hydroxide absorbing solution is injected into the scrubber
through port B and flows at 110 pl/min through the 200 pm annular gap of the
scrubber. Acid gases diffuse from the sample air through the membrane pores
where they are captured by the alkaline liquid. Downstream from the scrubber,
0.1 M phosphoric acid is injected at port A also at a flow of 110 pl/min The
alkaline scrubber effluent and the acidic solution mix together at the tee (T). The
stream is further mixed via flow through a 0.3 x 1000 mm knotted PTFE mixing
coil (MO). The aqueous solutions are pumped by a multichannel Gilson Minipuls
2 peristaltic pump using 0.5 mm i.d. tubing at speed 200. The acidified aqueous
solution next flows through the central lumen of the desorber where H2S is
liberated from the acidified solution into the desorber body.
Pressurized nitrogen flows into the desorber via port N at a nominal flow
of 4.0 SCCM as controlled by the needle valve (V). The nitrogen transports
analyte gases from the desorber into one of the 2 mL sample loops (SL1 and
SL2) under control of the GC injection valve (V1). The injection valve is an
8-port dual stack electropneumatically actuated slider valve connected such that
one sample loop is being filled, while the other is being chromatographed on the
column (0). The chromatograph is equipped with a flame photometric detector
(D) operated in the sulfur selective mode by incorporation of a 394 nm
interference filter. The dotted enclosure of Figure 2.5 indicates that these
components are housed within the oven of the gas chromatograph operated
34
isothermally at 70 °C, while the injector and detector were maintained at 130 °C.
A 6' X 1/8" FEP-Teflon column packed with Chromosil 310 was used for all of the
sulfur gas separations.
The preconcentration provided by the instrument results from the
difference in flow rates of the sampled and chromatographed gases. Each
minute the scrubber strips analyte from 5.00 liters of air and transfers it to 4.0
milliliters of nitrogen. There was no attempt to determine the percentage of
analyte actually transferred to the detector inasmuch as the system provided
adequately low detection limits and high sensitivity with reproducible and
quantifiable output.
2.3.5 Analytical System Performance
Initially the system produced poorly reproducible results with a relative
standard deviation (RSD) greater than 35%. However, detailed examination of
the data showed a synchronous cycle matching the on-off cycle of the laboratory
heater. Individual thermostating of the various system components showed that
the mixing coil, desorber, and sample loops are extremely temperature sensitive.
The inclusion of the indicated components in the GC oven along with the
analytical column improved signal reproducibility to a relative standard deviation
(RSD) of less than 6%. Further attempts to improve the precision of the system
under field operating conditions were largely unsuccessful, nevertheless, the
level or reproducibility attained was deemed adequate for to our field studies.
35
Carbonyl sulfide elutes from the chromatographic column immediately
prior to H2S and this fact affects the limit of detection. Figure 2.6 Is a
chromatogram of H2S (peak A) obtained near the detection limit of the
instrument. The baseline drop at 6 minute intervals signifies the sample
injection onto the column. The first peak observed, C, is an injection peak that
has not been totally characterized. This peak is not detected in blank air but Is
always observed in conjunction with H2S, where it is constant and independent
of the H2S concentration above a minimum value of 200 pptv. The peak height
of C is, however, proportional to the length of the scrubber. The H2S peak, A,
occurs on the shoulder of this injection peak, and the 20 cm diffusion scrubber
was determined to be the optimum device length, providing maximum sulfide
absorption while limiting interference from the tail of peak C.
2.3.6 Analytical System Calibration
Initial calibration work was carried out with a zero air generator from
AADCO (Clearwater, FL). However, this instrument consumed considerable
compressed air prompting us to seek an alternative for mobile deployment.
Investigations utilizing compressed ambient air passed through a soda-lime
packed column indicated quantitative removal of the acid sulfur gases. Field
blanks were thus generated. All other gases used (N2, Hg, etc.) were also
passed through soda-lime tubes to remove acid sulfur gas interference. Primary
calibration sources were individual permeation devices with emission rates that
36
were gravimetrically calibrated (ng/min in parenthesis) H2S (2 devices, 21.0 and
156.6), CH3SH (185.4) and n-CsHySH (44.1), respectively. All permeation
devices were kept in a thermostated bath maintained at 30° C. The bath was
constructed from an insulated beverage container, with an automotive
windshield wiper pump for circulation and a thermistor based temperature
controller. Temperature recording over a 2.5 month period indicated a daily
temperature variation of < 0.2° C.
Calibration of the sulfur gas instrument was achieved using the
permeation devices in combination with an air dilution system. The calibration
system is shown schematically in Figure 2.7 and it operates as follows.
Compressed air (A) was cleaned of acidic gases by a soda-lime trap (SL). The
zero air is then passed over the permeation device (G) where a steady state
concentration of the sample is entrained. The 1.0 SLPM flow is then split and
advances to flow controllers FA and FB. The stainless steel flow controllers
were tested for inertness to low concentrations of reduced sulfur gases and
showed no removal of the hydrogen sulfide or the lower mercaptans even at
moderate concentrations. Concerted adjustment of flow controllers FA and FB
provides the first stage of dilution by directing 0 to 90% of the sample flow to
waste (W) with the remainder proceeding to the proportioning valve V1. VI and
V2 are electrically activated 3-way valves with PTFE bodies that direct sample
air and zero air respectively into a 4.0 liter mixing chamber (MC). Actuation of
37
valve V1 in a duty cycle between 10-100% provided further reduction of sample
flux into the mixing chamber by removing a second portion of the analyte flow.
Further dilution was obtained in the mixing chamber from the addition of diluent
air via controller FD.
The duty cycle of valve VI affects the total volume of air entering the
mixing chamber the effect of which is offset by the inclusion of flow controller FC
and valve V2. The valve plumbing was connected such that when sample flow
through VI was directed to waste, flow through V2 proceeded to the mixing
chamber and vice-versa. Flow controllers FB and FC were set to identical flow
rates and the valves VI and V2 were operated in tandem such that the net flow
into the mixing chamber was constant. A Micromaster LS-100 microcontroller
from Minark Electric provided automated control of the V1/V2 duty cycle. Typical
operation of the calibration system was such that the total flow into the mixing
chamber was 6.00 SLPM of which 5.00 SLPM was aspirated from the sampling
port (S) for analysis with excess calibrant being vented to waste via port (W).
The completed system furnished a large range (25 pptv to 20 ppbv) of sample
concentrations for instrument calibration.
A typical measurement of calibrant gases using the sulfur gas analytical
instrument is reproduced in Figure 2.8, with analyte peaks during the 30 - 35
minute cycle labeled A and B for hydrogen sulfide and methyl mercaptan
respectively. This figure shows a one hour series in which the analytical cycles
38
repeat every 5 minutes. The analyte concentration is increased stepwise every
fourth injection with the shaded regions indicating transitional periods of
indeterminate concentration. The data from the concentration changeover
periods was excluded from the calibration data set. Using the calibration system
described above, a data set covering the range from 500 pptv to 16.75 ppbv was
obtained with the results summarized graphically in a log-log plot of signal (mV)
versus H2S concentration (ng/l) shown in Figure 2.9. The data were collected on
two separate runs with the H2S concentration increasing stepwise in the first run
(circles) and decreasing stepwise in the second run (diamonds). Error bars
indicating ± one standard deviation are also included, however, they are
generally of smaller dimensions than the plotted data points. Based on the peak
height of repetitive injections at a constant hydrogen sulfide concentration, the
instrument provides a RSD maximum of less that 6% over the instrument's useful
analytical range, verifying satisfactory stability for the desired field studies.
Statistical fitting of the calibration data over the 0.5 to 20 ppbv
concentration range yields calibration responses of:
log(signal, mV) = 2.114±0.026 log(H2S, ppbv)
+ 1.343 ±0.020, r =0.9973 (2.1)
and
log(signal, mV) = 2.114± 0.013 log(H2S, ppbv)
+ 1.34710.041, r2= 0.9970'
39
for the ascending and descending runs, respectively. Statistically these
calibrations are identical, indicating the absence of significant hysteresis in
either the instrument or the calibration system. This squared response of the
flame photometric detector is anticipated because the excited dimeric sulfur
species, S2*, Is the actual luminophore (Olesik et al., 1989). Calibration trials
also established the limit of detection for the instrument at 200 pptv with a
chromatogram near the limit of detection was discussed previously in reference
to Figure 2.6.
2.4 Meteorological Data Acouisition
A length of 1" rigid conduit was used to make the extendible portion of an
telescoping mast. This mast mounted on the rear of the MARL allowed simple
deployment of the anemometric sensors to a height 5 m above ground level.
Initially, the mast contained the mechanical sensor portion of a PCW Weather
Station (Digitatr, Hayward, CA) and the meteorological data were collected onto
an 8086 based PC computer (JAMECO, Belmont, CA). The use of the PCW
Expanded Software in conjunction with a custom program written in (see
Appendix A) PASCAL allowed automated collection of wind speed, direction,
temperature, and barometric pressure at 2.5 minute intervals. Difficulties in
sensor leveling combined with inadequate response at low wind velocities
prompted the installation of a sonic anemometer (SWS-101/2K, Applied
Technologies, Inc., Boulder, CO). This new anemometer with a response rate of
100 Hz provided wind speed, direction, and air temperature with a faster
40
response and a lower detection threshold compared to the mechanical model.
The sonic anemometer in conjunction with a compiled BASIC (Microsoft)
program (see Appendices B and C) allowed automated logging of wind speed,
direction and temperature at a rate of 5 Hz via a 80286/16 SX computer (IBM,
Armonk, NY).
2.5 Miscellaneous Data Acouisition
Initially the longitude and latitude of data acquisition locations were
estimated using published maps. In addition, the Texas Tech University
Department of Civil Engineering provided surveys of selected locations as
indicated. A Sony IPS-360 global positioning system was acquired and installed
in 1993 to provide more timely and accurate spatial information. This device
furnished spatial position with a specified accuracy of 30 meters for the
determined longitude, latitude, and elevation.
Miscellaneous instruments were installed in the MARL to provide other
information as applicable and to help gather and store the data. A UV
photometric instrument Model 1003 AH by Dasibi Corp. was installed to provided
ozone measurements. Insolation intensity was measured with a Sol-A-Meter
calibrated silicon photocell from Matrix Inc. Two Computer Interface Modules
(CIM) donated by Dionex Corporation (Sunnyvale, CA) were used to accumulate
the various analog signals from the installed instrumentation. These modules
converted 1 Volt analog signals to digital data which were then down loaded to
41
the two shock-mounted 386 class Personal Computers. The chromatographic
data files were typically processed using Dionex AI-450 chromatographic data
analysis software to interpret peak attributes which were subsequently exported
to a spreadsheet (Microsoft Excel) for final analysis and reports.
42
2.6 References
Bandy A. R.. Tucker B. J. and Maroulis P. J. (1985) Determination of part-per-trlllion by volume levels of atmospheric carbon disulfide by gas chromatography/mass spectrometry. Analytical Chemistry 57, 1310-1314.
Benner R. L and Stedman D. H. (1989) Universal sulfur detection by chemiluminescence. Analytical Chemistry 6A, 1268-1271.
Benner R. L and Stedman D. H. (1990) Field evaluation of the sulfur chemiluminescence detector. Environmental Science and Technology 24, 1592-1596.
Black M. S., Herbst R. P. and Hitchcock D. R. (1978) Solid adsorbent preconcentration and gas chromatographic analysis of sulfur gases. Analytical Chemistry 50, 848-851.
Dasgupta P. K. (1984) A diffusion scrubber for the collection of atmospheric gases. Atmospheric Environment Q, 1593-1599.
Dasgupta P. K., McDowell W. L. and Rhee J.-S. (1986) Porous membrane-based diffusion scrubber for the sampling of atmospheric gases. Analyst ^'\^, 87-90.
Dasgupta P. K. and Yang H.-C. (1986) Trace determination of aqueous sulfite, sulfide, and Methanethiol by fluorometric flow injection analysis. Analytical Chemistry 5S, 2839-2844.
Dasgupta P. K., Dong S., Hwang H., Yang H.-C. and Genfa Z. (1988) Continuous liquid-phase fluorometry coupled to a diffusion scrubber for the real-time determination for atmospheric formaldehyde, hydrogen peroxide, and sulfur dioxide. Atmospheric Environment 22, 949-963.
Dasgupta P. K. (1993) Automated measurement of atmospheric trace gases. In Advances in chemistry series: Measurement challenges in atmospheric chemistry, Vol. 232, (edited by Verman L.), American Chemical Society, Washington, DC, pp. 41-90.
Farwell S. O., Kagel R. A., Barinaga C. J., Goldan P. D., Kuster W. C, Fehsenfeld F. C. and Albritton D. A. (1987) Intercomparison of two techniques for the preparation of gaseous sulfur calibration standards in the low to sub-ppb range. Atmospheric Environment 2^, 1983-1987.
43
Farwell S. O., Liebowitz D. P., Kagel R. A. and Adams D. F. (1980) Determination of total biogenic sulfur gases by filter/flash vaporization/flame photometry. Analytical Chemistry 52, 2370-2375.
Farwell S. O. (1992) Personal communication. University of Idaho, Moscow, Idaho.
Perm M. (1979) Method for determination of atmospheric ammonia. Atmospheric Environment 13,1385-1393.
Perm M. (1986) A Na2C03-coated denuder and filter for determination of gaseous HNO3 and particulate NO3" in the atmosphere. Atmospheric Environment 20, 1193-1201.
Jaeschke W. (1978) New methods for the analysis of SO2 and H2S in remote areas and their application to the atmosphere. Atmospheric Environment ^2, 715-721.
Johnson J. E. and Lovelock J. E. (1988) Electron capture sulfur detector: Reduced sulfur species detection at the femtomole level. Analytical Chemistry 60,812-816.
Kagel R. A. and Farwell S. O. (1986) Evaluation of metallic foils for preconcentration of sulfur-containing gases with subsequent flash desorption/flame photometric detection. Analytical Chemistry 58,1197-1202.
Kelly T. J., Gaffney J. S., Phillips M. F. and Tanner R. L (1983) Chemiluminescent detection of reduced sulfur compounds with ozone. Analytical Chemistry 55,135-138.
Kuban V., Dasgupta P. K. and Marx J. N. (1992) Nitroprusside and methylene blue methods for silicone membrane differentiated flow injection determination of sulfide in water and wastewater. Analytical Chemistry 84, 36-43.
Leek C. and Bagander L. E. (1988) Determination of reduced sulfur compounds in aqueous solutions using gas chromatography flame photometric detection. Analytical Chemistry 60, 1680-1683.
Lewin E. E., Taggart R. L., Lalevic M. and Bandy A. R. (1987) Determination of atmospheric carbonyl sulfide by isotope dilution gas chromatography/mass spectrometry. Analytical Chemistry 59,1296-1301.
44
Natusch D. F. S., Klonis H. B., Axelrod H. D., Teck R. J. and James P. Lodge, Jr. (1972) Sensitive method for measurement of atmospheric hydrogen sulfide. Analytical Chemistry 44,2067-2069.
Olesik S. v., Pekay L. A. and Paliwoda E. A. (1989) Characterization and optimization of flame photometric detection in supercritical fluid chromatography. Analytical Chemistry 8^, 58-65.
Sandalls F. J. and Penkett S. A. (1977) Measurements of carbonyl sulfide and carbon disulfide in the atmosphere. Atmospheric Environment ^^, 197-199.
Simon P. K. and Dasgupta P. K. (1993) Wet effluent denuder coupled liquid/ion chromatography systems: Annular and parallel plate denuders. Analytical Chemistry 65, 1134-1139.
Spurlin S. R. and Yeung E. S. (1982) On-line chemiluminescence detector for hydrogen sulfide and methyl mercaptan. Analytical Chemistry 54, 318-320.
Steudler P. S. and Kijowski W. (1984) Determination of reduced sulfur gases in air and solid adsorbent preconcentration and gas chromatography. Analytical Chemistry 56, 1432-1436.
Tanner R. L., Markovits G. Y., Ferreri E. M. and Kelly T. J. (1986) Sampling and determination of gas-phase hydrogen peroxide following removal of ozone by gas-phase reaction with nitric oxide. Analytical Chemistry 58, 1857-1865.
45
/
l
^ •
• J
DC <
o "co o n CO
o CO CD tn CD
CC g '\— CD SI Q. (O O
E
o 0)
o
• >
c o
• D a. o
CM
O)
46
CO
c 0 E
DC <
g)
g > "3 o 0 "c 0 O
c\i CN 0 3 O)
47
Figure 2.3. Diffusion scrubber detail. A - tee body; B - outer PTFE sheath; C inner Accurel® porous tubular membrane; D - annular aqueous channel; E -gaseous inlet/outlet; F - PTFE spacer plug; G - aqueous inlet/outlet.
m >^ A
I
u NO
^
u B Nl
^
W
Figure 2.4. Diffusion desorber detail. I - solution inlet tubing; P - gas tight seal; T - tee body; NO - sample gas outlet; M - porous tubular membrane; Nl -nitrogen gas inlet; W - spent aqueous solution.
48
B - >
Figure 2.5 Reduced sulfur gas analytical instrument. Dotted line indicates interior of gas chromatograph oven; I - sample gas inlet; VF - vacuum flask; SL - soda lime trap; FA - mass flow controller; R - vacuum reservoir; P -vacuum pump; B - aqueous alkaline inlet; A - aqueous acid inlet; T - aqueous mixing tee; MC - aqueous mixing coil; N - nitrogen inlet; V2 - nitrogen metering valve; SL1, SL2 - sample loops; GC - carrier gas inlet; VI - sample injection valve; C - chromatographic column; D - flame photometric detector; W - various waste streams.
49
Figure 2.6. Chromatogram indicating response of the reduced sulfur gas analytical system near the limit of detection for hydrogen sulfide. A - hydrogen sulfide (-230 pptv); C - injection artifact.
Figure 2 7 Sulfur gas calibration system. A - compressed air supply; SL-soda lime trap; G - permeation; FA, FB, FC, FD - mass flow controllers; VI , V2 -dilution control valves; MC - dilution chamber; S - sample port; W - waste.
50
10 mV
5 min
JLUJ \
LJJJLIJJLJULJL. Figure 2.8. Typical chromatogram from reduced sulfur gas analytical instrument using calibrant gases. A - hydrogen sulfide (-920 pptv to 1.4 ppbv); B - methyl mercaptan (-5.7 to 8.6 ppbv); C - injection artifact.
51
10000 —I
1000 —
>
(0 c o Q. (0 0)
CC
% 100 •-> 0) Q
10
o Increasing [H^S]
Decreasing [H^S]
1 \ \ I I I I
10 [H S] (ppbv)
Figure 2.9. Calibration of the reduced sulfur gas analytical instrument.
52
CHAPTER 3
MODELING FUGITIVE EMISSIONS
3.1 Introduction
Oil production presents a unique investigative problem due to the sprawl
associated with oil wells and associated equipment. A large number of scattered
sources to which access is often physically and/or legally hindered, as well as
corrosive and hazardous site conditions, all combine to hinder direct assessment
of sulfur gas flux from the various field sites. Remote determination of gaseous
releases from such locations consequently becomes a desirable objective.
Measurement of atmospheric constituents at varied locations surrounding
analyte sources, combined with an appropriate model to account for analyte
dissipation resulting from atmospheric processes, provides an indirect method to
estimate the gaseous effluvium. Atmospheric dispersion models were originally
developed to estimate toxic concentrations of chemicals released due to
industrial accidents (e.g., fire, explosion, accidental release toxic vapors) and as
such have been used to facilitate site selection, equipment design, and exposure
compliance for industrial sites. The most widely used models are the Gaussian
dispersion models. These have been in use for over thirty years and are the
current basis for many present day health and safety regulations. The models,
as conceived, are designed to calculate atmospheric concentration of analyte as
53
a function the analyte's release rate. However, the models also provide a
feasible means to back-calculate efflux from identified sources.
A dispersion model is a mathematical expression relating the effects of
the atmosphere to the spatial relocation of the air constituents. Included in the
model are sources (input of constituents Into the atmosphere), effects of
advection (transport from the site of introduction) as well as dispersion (dilution
by the wind and dispersal due to turbulence). The model may also include
considerations of plume rise, wind shear, chemical transformations, physical
conversions, and sinks (removal mechanisms). The eddy correlation technique
is the best established micrometeorological modeling method for the
determination of atmospheric chemical fluxes. However, this method requires a
rigid platform coupled with fast-response chemical and meteorological sensors.
Because of the present lack of a species-specific sulfur sensor with a sufficiently
rapid response time, the use of eddy-correlation was precluded in this
investigation. To estimate emissions, we needed to use a model which operated
on ambient concentration measurements in addition to dispersion factors as
represented by atmospheric physics. Such models are available (Turner, 1970;
Bass and Hoffnagle, 1977; Draxler, 1987; Zanetti, 1990; Piccot et al., 1994), for
example:
1. Climatological Dispersion Model (CDM),
2. CRSTER Model,
3. VALLEY Model (C9M3D),
54
4. Point/Multiple Point Model (PTMTP),
5. Point/Maximum Model (PTMAX),
6. Point/Distance Model (PTDIS).
For a variety of reasons, the models above were not directly applicable
for use in this study of fugitive emissions. Some of the models have not been
adequately tested or verified, with review and evaluation as to suitability and
accuracy still ongoing, while others failed to include all of the sampling
limitations and requisites (Taylor etaj., 1986; Hanna, 1988; Weil eta]., 1992).
The Climatological Dispersion model is used primarily for estimation of long -
term (seasonal, annual) concentrations and exceeds the time frame of the this
study. The CRYSTER model is applicable from a temporal standpoint but
requires a 1-year or longer historical record of sequential hourly meteorological
data, which is not available for the area to be studied. VALLEY is a model
intended for use in rough terrain and as such it does not match the conditions at
the field site. The Point/Multiple Point model is designed for multiple sources
and sensors and did not match the field conditions encountered. Point/Maximum
Model is equivalent to the PTDIS model except it is adjusted to provide the
maximum concentration whereas for this study an average concentration is
necessary.
The Point/Distance Model is a conventional Gaussian plume model based
on the Pasquill-Glfford-Turner dispersion coefficients and the Pasquill stability
classes. It is the most applicable of the models available and meets the general
55
requirements of the study. The Pasquill-Glfford-Turner model as described by
Turner (1970) in the Workbook of Atmospheric Dispersions Estimates was used
as the basis of calculations used in the plume dispersion studies of fugitive
emissions.
3.2 Description of Plume Models
Figure 3.1 presents a sketch of a point source plume upon which the
Gaussian dispersion model is based. The plume as shown is formed from a
continuous release of analyte at the point (0,0,h). Many plumes are formed as a
result of thermal processes which creates lofting of the hot gases to an effective
release height H. Wind transports the analyte along the x axis where turbulence
disperses the sample both horizontally and vertically. However, the turbulent
mixing creates inhomogeneity in the plume and demands detailed and highly
specialized meteorological information to model the plume's concentration
profile. Dispersion coefficients were introduced by Gifford (1961) to provide an
easy method for estimating atmospheric dispersion based on routine
meteorological observations. By defining the plume edge as that point where
the concentration has decreased to 10 percent of its centerline value, the plume
width and height can be characterized statistically by use of standard deviations
of the plume concentration distribution. The dispersion coefficients, denoted as
ay and GZ, are related to the plume width and height, respectively, and vary with
downwind distance and atmospheric turbulence. Atmospheric turbulence, most
56
accurately described In terms of complicated atmospheric physics, was
simplified by Pasquill who reduced it to a function of the commonly observed
meteorological parameters of wind velocity, daylight intensity, and cloud cover
(Pasquill 1961). Table 3.1 catalogues the range of atmospheric conditions as
organized by Pasquill. The table enumerates the six basic categories extending
from extremelv unstable to moderately stable, and labeled from A to F
respectively. Curves representing the horizontal dispersion coefficient as a
function of distance downwind from the source and atmospheric stability
conditions are presented in Figure 3.2 with curves for the similar vertical
dispersion coefficient presented in Figure 3.3. As originally introduced by
Gifford (1961) in 1961 and revised by Turner (1970) in 1970, use of the
dispersion coefficients required manual abstraction of values from the provided
graphs. However, to facilitate computations via a computer program or
spreadsheet analysis, power law approximations for the sigma curves were
introduced by Lees (1986) and are listed in Table 3.2. Other methods for
calculation of the sigma curves have been proposed (Tadmor and Gur, 1969;
Davidson, 1990), however, for uniformity and convenience, all calculations
contained herein will utilize the approximations made by Lees. Dispersion
coefficients as a function of the downwind distance from the source, x, are given
by:
ay =ax b. (3.1)
57
a, = ax". (3.2)
With the parameters a, b, c, and d as specified in Table 3.2.
Gas releases from storage tanks in the oil fields typically occur at or near
ambient temperature, and as a result the effective release height coincides with
the actual release height (i.e., H = h). The plume formed from a steady state
release of analyte Into a wind traveling in the x direction has been modeled
(Pasquill, 1961) with the analyte concentration, C, at a point x, y, z given by the
generalized Gaussian plume formula:
C(x, y, z, H) = Q
271 Gy (5J, U exp 2
exp 2 2
z - H
\ ^z J + exp 2
z - H
y ^z J
(3.3)
The definition and units for the variables are:
C = ambient concentration (g m" ),
Q = point source emission rate (g sec' ),
X = downwind distance from source (m).
y
z
H
ay
u
= lateral (crosswind) distance from the plume centerline (m),
= vertical height of sample collection (m),
= effective analyte release height (m),
= horizontal crosswind dispersion coefficient (m),
= vertical dispersion coefficient (m),
= wind velocity (m sec' ).
58
For concentrations calculated at ground level, i.e., z=0, the equation
simplifies to:
C(x, y,0, H) = Q
7C ay a^ u exp
2 2 exp
1 H ^
\^zj (3.4)
For calculation of the concentration at ground level along the plume
centerline, i.e., z=0 and y=0, the equation further reduces to:
C(x,0,0, H) = Q
7c ay a2 u exp
2 2 v^yy
(3.5)
3.3 Assumptions of Plume Models
Atmospheric turbulence is the major factor responsible for dispersion. It
is several orders larger than molecular diffusion which is not typically included in
dispersion calculations (Seinfeld, 1986). Atmospheric dispersion is strongly
affected by meteorological conditions such as wind and atmospheric stability.
Dispersion is also strongly affected by topographical conditions including ground
slope, surface roughness, and obstructions (e.g., buildings). Certain
assumptions are included in the model to account for the topographical and
meteorological conditions incurred and include the following:
1. Computed values do not represent instantaneous concentrations,
2. Analyte emission rate and meteorological conditions are steady state,
3. The velocity profile in the x direction is constant (i.e., flat).
59
4. Gaussian distribution occurs In the y and z directions,
5. Negligible diffusion occurs in the x direction,
6. The plume is totally reflected at the earth's surface,
7. Chemical reactions are negligible.
3.4 Model Usage
In general, these models were developed and designed to calculate
atmospheric concentrations from relatively simple data. However, acceptable
models can also be used in a converse manner to assess the average point-
source-flux of a species from ambient concentrations, an approach used by
several investigators (Draxler, 1987; Piccot etaj., 1994). As such, they provide
an ideal method for estimating emission rates in situations where direct flux
measurements are not feasible. This approach simplifies field measurements by
reducing the required data collection to: ambient air species concentration, wind
speed, and wind direction.
Field observations will be used to accumulate data as indicated above,
from which the amount of sulfur gases released in the oil fields can be
estimated. Validation and use of the Pasquill-Gifford-Turner model to estimate
hydrogen sulfide flux from selected field locations is discussed in detail in
Chapter 4.
60
3.5 References
Bass A. and Hoffnagle G. F. (1977) Gaussian Dispersion Models Applicable to Refining Emissions, American Petroleum Institute, Washington DC.
Davidson G. A. (1990) A modified power law representation of the Pasquill-Gifford dispersion coefficients. Journal of the Air and Waste Management Association 40, 1146-47.
Draxler R. A. (1987) Estimating emissions from air concentration measurements. Journal of the Air and Waste Management Association 37, 708-714.
Gifford, Jr., F. A. (1961) Use of routine meteorological observations for estimating atmospheric dispersion. Nuclear Safety 2, 47-51.
Hanna S. R. (1988) Air quality model evaluation and uncertainty. Journal of the Air and Waste Management Association 38, 406-412.
Lees F. P. (1986) Loss Prevention in the Process Industries, Butten^/orths, London.
Pasquill F. (1961) The estimation of the dispersion of windborne material. Meteorological Magazine 90, 33-49.
Piccot S. D., Masemore S. S., Ringler E. D., Srinivasan S., Kirdhgessner D. A. and Herget W. F. (1994) Validation of a method for estimating pollution emission rates from area sources using open-path FTIR spectroscopy and dispersion modeling techniques. Journal of the Air and Waste Management Association 44, 271-279.
Seinfeld J. H. (1986) Atmospheric Chemistry and Physics of Air Pollution, John Wiley and Sons, New York.
Tadmor J. and Gur Y. (1969) Analytical expressions for the vertical and lateral dispersion coefficients in atmospheric diffusion. Atmospheric Environment 8, 688-690.
Taylor J. A., Jakeman A. J. and Simpson R. W. (1986) Modeling distributions of air pollutant concentrations-l. Identification of statistical models. Atmospheric Environment 20, 1781-1789.
Turner D. B. (1970) Workbook of Atmospheric Dispersion Estimates, US Government, Cincinnati.
61
Weil J. C , Sykes R. I. and Venkatram A. (1992) Evaluating air-quality models: Review and outlook. Journal of Applied Meteorology 3^, 1121-1145.
Zanetti P. (1990) Air Pollution Modeling: Theories, Computational Methods, and Available Software, Van Nostrand Reinhold, New York.
62
Table 3.1: Meteorological categories A-F, as defined by wind speed, sunlight, and cloudiness.
A: Extremely unstable conditions D: Neutral conditions^
B: Moderately unstable conditions E: Slightly stable conditions
C: Slightly unstable conditions F: Moderately stable conditions
Daytime insolation Nighttime conditions
Surface wind Thin overcast speed, or > 4/8 < 3/8 m/sec Strong Moderate Slight cloudiness* cloudiness
<2
2
4
6
>6
A
A-B
B
C
C
A-B
B
B-C
C-D
D
B
C
C
D
D
E
D
D
D
F
E
D
D
Source: Gifford, 1961.
* Applicable to heavy overcast, day or night.
*The degree of cloudiness is defined as that fraction of the sky above the local apparent horizon which is covered with clouds.
63
Table 3.2 Equations and constants used to calculate the Pasquill-Gifford dispersion coefficients for stability classes A through F as a function of distance, X, from the source.
Pasquill stability class
A
B
C
D
E
F
Dispersion coefficients ay =a)f
a
0.493
0.337
0.195
0.128
0.091
0.067
(m) b
0.88
0.88
0.90
0.90
0.91
0.90
Cz = CA (m)
c
0.087
0.135
0.112
0.093
0.082
0.057
d
1.10
0.95
0.91
0.85
0.82
0.80
Source: Lees, 1986.
64
(x,-y,0)
Figure 3.1. Schematic representation of plume dispersion from a point source. Adapted from Turner (1970).
65
1E-I-3 —
1E-I-2 —
1 F-i-1 1 C + 1 ^
1 F j . n 1 C-rU
.^^— ^.^ ^^-''^ ^
• ^ ^^
A pd y^\
s ^ :
,,--^^,----
it^^^J^ ; = ^ : P - ^ ^ ^—'
r ' ^ -n
—^ ^ ^ : .^'
^„^^^
-.'^^^ ? ^
^
^
; ^ ^ _ _ - ^ < = _
iS-': ^ - ' ^
1E-I-2 1E-h3 1E-I-4
Distance Downwind from Source (m)
1E-H5
Figure 3.2 Horizontal dispersion coefficient as a function of downwind distance from the source. Adapted from Turner (1970).
N
1 C-h^ —
AT~ . r%
1 L-l-o —
1 T J - O I C- t -^ ^ ;
1E-h1 - ^
^ ^ rv
1E-I-0
^ ^ ^ -^^
\
-''
f l - - ^ ^
- - ^ ^ ^ ' ^ '^ .^^—'
— =
D - ' " " ^ ' = ^ . ^
,^
p;^]
"" F"
1E-I-2 1E-I-3 1E-I-4
Distance Downwind from Source (m)
1E-I-5
Figure 3.3 Vertical dispersion coefficient as a function of downwind distance from the source. Adapted from Turner (1970).
66
CHAPTER 4
AMBIENT AIR MAPPING
4.1 Introduction
From its inception, a major intent of the Mapping Fugitive Emissions
project was the development of an instrument based approach which would
provide a means of using ambient measurements to calculate fugitive emission
rates. A basic understanding of plume characteristics allowed the selection of
an appropriate model the parameters and requirements of which closely
matched the available conditions and resources. Instrumentation for measuring
the requisite data were accumulated and assembled into a mobile laboratory. A
program was developed to provide a proper data set able to verify the predictive
behavior of the model toward a hydrogen sulfide plume. Subsequent to model
validation, a program of mapping fugitive emissions in the oil fields was
launched in order to build a database from which to estimate the sulfur flux
attributable to oil production in selected regions of West Texas (Lenschow and
Hicks, 1989).
4.2 Experimental Design
Field studies of atmospheric sulfur flux at remote sites in West Texas oil
fields was accomplished using a Mobile Atmospheric Research Laboratory
(MARL), as detailed in Chapter/Section 2.2. Detection of hydrogen sulfide at
67
parts-per-trillion levels was accomplished via a custom liquid-scrubber/gas
chromatographic/flame photometric system for reduced sulfur gases (LS-GC-
FPD), the construction of which has been previously described in
Chapter/Section 2.3. A spreadsheet application program (Excel, Microsoft
Corp., Redmond, WA) was used to compile, tabulate, and average the collected
chemical, meteorological, and spatial data, providing ten minute running
averages of the accumulated data for reports and for correlation studies. The
significance of a running average is visually demonstrated in Figure 4.1, in which
graphs for both wind speed and direction are displayed. In each graph, the
broad black band delineates the instantaneous intensity, and the 10 minute
running average is shown as an embedded white line. In sharp contrast to the
wide variations observed in the instantaneous signal, the 10 minute running
average results in substantially less noise, and renders the data suitable for use
in the Gaussian plume dispersion models.
4.3 Atmospheric Trends of Reduced Sulfur Gases: Initial Investigations
Preliminary investigations of fugitive emissions associated with oil and
natural gas production were centered around the identification of detectable
species and their sources. Field investigations showed that of the reduced
sulfur gases anticipated, only H2S was routinely observed in quantifiable
amounts, and that in general, lower weight mercaptans were detectable only in
68
the immediate vicinity of gasoline production plants or natural gas sweetening
plants. In each of these facilities hydrogen sulfide and mercaptans are removed
from the crude and natural gas as part of the production process, and emissions
of these compounds, concentrated during the processing, provide detectable
levels of mercaptans near such plants. Figure 4.2 shows methyl mercaptan
detected in the ambient air down wind from one such facility. Atmospheric data
were collected on July 23, 1993 near a natural gas processing plant in Hockley
County, Texas (33°28' N Latitude, 102°33' W Longitude). The chromatogram in
Figure 4.2 shows hydrogen sulfide and methyl mercaptan detected downwind
from the plant (peaks labeled as A and B, respectively). With an instrument duty
cycle of 2.5 minutes per injection, the 30 minute segment of data presented
covers 12 samples of ambient air, in which a significant level of methyl
mercaptan is observed for several of the samples. Although the instrument was
not calibrated for methyl mercaptan, and as a result the exact level of methyl
mercaptan is not known, the largest peaks correspond to concentrations
estimated in the low (1 to 100) ppbv range. Because of a limited number of such
facilities in the study area with access restricted, no data were collected in
respect to these sites beyond identifying them as significant emission sources
for hydrogen sulfide and the lower mercaptans.
Data resulting from initial investigations identified hydrogen sulfide as the
principal reduced sulfur gas in the oil producing regions. As a result of this
determination, ambient concentration of hydrogen sulfide was measured in the
69
vicinity of assorted oil field equipment. The pump jacks, recovery injection wells,
and natural gas pumping stations did not, as a general rule, provide detectable
emissions of reduced sulfur gas. However, in addition to the gasoline and gas
sweetening plants noted previously, tank farms used to collect and store crude
oil were found to be a significant source of hydrogen sulfide emissions. Closer
investigation revealed tank vents as the major source of hydrogen sulfide gas
with ambient concentration ranging from mid pptv to low ppbv.
4.4 Diurnal Pattern
Initial investigations also demonstrated a consistently strong diurnal
pattern in the atmospheric level of hydrogen sulfide. Typically the hydrogen
sulfide pattern was composed of a nighttime/early morning maxima ranging from
1 to 5 ppbv followed by rapid disappearance with sunrise. The hydrogen sulfide
concentration consistently decreased below the instrumental detection limit of
200 pptv by 10:00 to 11:00 AM and did not rise to detectable levels before the
following late night or early morning hours. Figure 4.3 provides an illustration of
the typical diurnal pattern observed for hydrogen sulfide in the Slaughter oil field
near Levelland, Texas.
The origin of the diurnal phenomena is not fully understood, but studies
were designed and executed to identify the underlying reason for the pattern
observed. Because there are no significant bodies of water in the immediate
region, the chemical and physical processes controlling atmospheric
70
concentrations depend basically upon interactions with the lithosphere (soils) or
with the atmosphere. Investigations and conclusions with respect to interactions
of H2S with the lithosphere are presented and discussed in Chapter 5. Studies
with respect to atmospheric mechanisms continue in the present chapter
beginning in section 4.4.1 below.
4.4.1 Photolytic Decomposition
A series of investigations were completed to ascertain the role of
photodecomposition and/or photoactivation in the reduction of the daytime
concentrations of hydrogen sulfide. All studies were executed at ground level
during typical ambient conditions in West Texas. The reaction chamber required
for this study was formed from a large 75 cm X 90 cm X 2 mil. transparent
polyethylene bag. A spectral analysis of the polyethylene material indicated
greater than 50 percent transmittance for all wavelengths between 250 and 800
nm. Taking into consideration that essentially no solar radiation below a
wavelength of 300 nm reaches the earth's surface (Goody and Yung, 1989),
polyethylene is a suitable material from which to construct an enclosure for the
study of sunlight activated chemical reactions.
To maintain the bag in an inflated configuration, an endoskeleton was
formed from two springy metal hoops which were located inside of the
polyethylene bag. The 87 cm diameter hoops were assembled from three 91 cm
lengths of stainless steal welding rods coupled together via Teflon tubing. The
71
chamber opening was sealed with tape and the two internal hoops were oriented
to form a 50 cm X 65 cm X 25 cm semi-rigid reaction chamber. The reaction
chamber volume of ca. 80 L provided an analyte residence time of 16 minutes
based on a sampling rate of 5.00 SLPM. The sample chamber was equipped
with 4 PTFE (I/O) ports, providing two inlet (I) ports centered at one end of the
chamber and two outlet (O) ports centered at the opposite end. The system
evolved through several configurational iterations as required by the specific
requirements of individual experiments.
Sample atmospheres for analysis were prepared by passing a zero-air as
the carrier gas at a nominal flow of 40 SCCM across thermostated permeation
devices. This flow was introduced into one inlet port of the reaction chamber
and diluted by 5 to 10 SLPM air flow introduced at the other inlet port. The
chamber contents were sampled at 5.00 SLPM from one outlet port with excess
chamber pressure vented at the remaining outlet port.
4.4.1.1 Direct Photolvtic Decomposition
The exceptional reactivity of both the hydroxyl radical and ozone ensures
that the concentration of these oxidants will be insignificant in the zero-air feed.
The level of NO2, a necessary precursor for the timely photoregeneration of O3
and ultimately the OH radical, is also very low in the zero-air. With the
availability of strong oxidants restricted, the described configuration of the
apparatus tested for direct photodegradation of hydrogen sulfide.
72
Hydrogen sulfide was introduced into the reaction vessel at a constant
rate of 80 ng/min along with an excess of zero-air for dilution. A water trap at the
chamber vent was employed to exclude ambient air. The chamber was
continuously sampled at 5 SLPM, while exposure to direct sunlight was
controlled by covering the reaction vessel with an opaque covering. To assure
steady state conditions, the system was operated under direct sunlight for 3
hours during which time a uniform hydrogen sulfide concentration was observed.
Following the initialization period, light was blocked from the test chamber and
sampling continued for another 3 hours. For the full duration of the trial, no
significant variance was observed in the hydrogen sulfide concentration. There
appeared, therefore, to be no loss of atmospheric hydrogen sulfide as a result of
interactions with direct sunlight.
4.4.1.2 Indirect Photolvtic Decomposition
Since direct photooxidation of hydrogen sulfide did not account for the
diurnal pattern observed, the reaction chamber was modified to test for
interaction with ambient oxidants. One outlet tube was removed from the
chamber, and one inlet tube was replaced with a 25 cm length of larger PTFE
tubing (1.0 cm i.d.). The modifications allowed unrestricted introduction of
ambient air into the reaction chamber as a means to probe for oxidation by
ozone, hydroxyl radical, or other oxidants prevalent in ambient air.
73
Hydrogen sulfide was introduced as described previously and ambient air
was utilized for dilution. The chamber was sampled at 5.0 SLPM. Figure 4.4
shows the results of a 24 hour test for hydrogen sulfide oxidation by reactants
present in the ambient atmosphere. The introduction of hydrogen sulfide into
the chamber was synchronous with the beginning of the trial resulting in the
initial increase observed in the signal. After the hydrogen sulfide reached a
level of approximately 16 ng/L, the concentration remained essentially stable
over the remainder of the test period. The experiment was conducted
continuously for 24 hours under varied lighting conditions. The reaction
chamber was illuminated as follows: direct sunlight for approximately 8 hours,
indirect daylight light for approximately 4 hours, and no illumination for
approximately 12 hours. The prevailing weather consisted of typical West
Texas autumn conditions with a temperature range of 11.6 to 29.4°C and relative
humidity of 18 to 82%.
Statistically, under the conditions of the test there was no significant
reduction of atmospheric hydrogen sulfide concentration resulting from exposure
to either direct or indirect sunlight. Significant fluctuations were observed in the
hydrogen sulfide signal during the afternoon of 10/2/93, and can be explained by
the following scenario. The winds were light and variable in the morning but
became strong and gusty (-10 m/s) in the afternoon. The reaction chamber is
not a rigid structure and it "breathes" through the large input port as a result of
74
unsteady wind load on the chamber wall. The breathing of the reaction vessel
influences the analyte dilution, resulting in the noisy signal observed.
4.5 Hvdrooen Sulfide Rainout
In addition to the diurnal pattern observed for fugitive emissions,
significant reductions in atmospheric hydrogen sulfide levels were observed in
conjunction with rain. Figure 4.5 shows graphically the rainout observed during
a nighttime rain storm east of Levelland, Texas (33°34'N Latitude, 102°35' W
Longitude), with shading on the plot indicating the two periods of precipitation.
The first precipitation episode was a very light sprinkle occurring between 8:30
and 9:30 in the evening. Later, a moderately intense shower began about 10:30
PM and continued until just after midnight. The measured hydrogen sulfide
concentrations are shown as open circles in the lower section of the chart. The
hydrogen sulfide showed a significant decrease shortly after the inception of the
first precipitation event. The light rain ceased at 21:40 and the H2S level began
to rise briefly, but a heavy rain began shortly thereafter and the hydrogen sulfide
level again fell. The wind during this observation was calm, aside from of the
period between 21:30 to 23:30 when the velocity rose briefly to a maximum of 6
m/s.
Hydrogen sulfide displays limited solubility in water and its Henry's law
constant of 0.102 M atm' (Smith and Martell, 1976), can be used to calculate
removal from the atmosphere in the dissolved phase by rain. A light
75
precipitation of 0.5 cm per hour, would provide 0.5 mL of rain per hour onto a 1
square centimeter area. Assume the following conditions: a homogenous
atmosphere, a hydrogen sulfide concentration of 660 pptv (-1.0 ng/L), a
boundary layer height of 1000 meters, rapid equilibrium between the gas phase
and the dissolved phase in the cloud and rain droplets. Under these conditions
the hydrogen sulfide concentration in the rain water will be approximately 6.5 nM
and the precipitation will remove 3.2 pmol hour' onto a 1 cm^ area. With the
H2S burden above a 1 cm^ area being 29.5 pmol, it is readily apparent that the
precipitation event by itself is incapable of reducing the hydrogen sulfide levels
as observed in Figure 4.5.
4.6 Model Validation Specific for Hydrogen Sulfide
4.6.1 Safety
Hydrogen sulfide poisoning is not always catastrophic nor immediately
apparent. Chronic exposure to non-lethal levels of hydrogen sulfide may cause:
watering of the eyes, headache, weakness, irritability, insomnia, loss of appetite,
weight loss, nausea, and vomiting (Arena, 1986; Burnett, 1977; Ellenhorn,
1988). These symptoms, similar to food poisoning or stomach virus, sometimes
occur with the onset delayed by as much as 12 hours, and may appear for
several months following acute exposure. However, this compound is very toxic
being an immediate threat to life at concentrations as low as 500 ppmv. All
basic safety precautions were observed during procedures which involved
76
working with hydrogen sulfide. Breathing air and properly fitted masks were
available at all times and were utilized as conditions warranted. Other safety
equipment included fire extinguishers, eye washes, and showers. All testing
was conducted in uninhabited areas with restricted access to uninitiated
personnel. To test particular assumptions pertaining to the atmospheric
behavior of hydrogen sulfide, small quantities of this gas were cautiously
released into the atmosphere.
4.6.2 Point Source Release of Hydrogen Sulfide
The collection of plume data with regard to hydrogen sulfide occurred in
two stages. The first stage involved the controlled release of measured amounts
of hydrogen sulfide. A program was developed to verify the plume dispersion
model with respect to hydrogen sulfide. A metered discharge of hydrogen
sulfide was coupled with the concurrent measurement of all parameters required
by the Pasquill-Gifford model. Hydrogen sulfide (99% pure) was discharged
from a well regulated source at a nominal rate of 45 mL/min. The gas was
discharged from a 3 mm diameter orifice at a height of 3 meters, and ambient air
samples were analyzed for hydrogen sulfide at varied positions relative to the
release point. The calculated flow of the discharged gas is 0.1 meter per
second, an order of magnitude lower than the wind velocity encountered under
typical West Texas conditions. To prevent any discrepancy due to lofting, the
discharge was always oriented horizontal to the ground in the direction of the
77
wind. However, we did not make any efforts to account for the horizontal
velocity of the analyte at the release point. The MARL, outfitted with the
reduced sulfur gas detector, was used to measure and record hydrogen sulfide
concentrations. Also recorded were the spatial relationship between the
detector and the source, meteorological data, and other atmospheric
information.
The Pasquill-Gifford model, as a specific form of the Gaussian plume
dispersion model applicable to conditions and the terrain prevalent in West
Texas, was introduced and characterized in Chapter 3. This was used to
calculate the theoretical downwind concentrations, C(x,y,z,H), at various
sampling positions. Figures 4.6 and 4.7 show plots of modeled versus
measured concentrations from data collected on September 26, 1992 and
October 9, 1992. From the graphs it is readily observed that the model
consistently overpredicts hydrogen sulfide concentration by approximately 20
times, and the precision is low. Initial attempts to correct the model were only
partially successful. No acceptable linear correction was found. However,
Hagemann proposed a second order polynomial correction (Hagemann, 1992).
Unfortunately, this approach yielded acceptable results only over a rather limited
distance range, as characterized by the original validation data set. This
correction generated unrealistically high estimations when extrapolated beyond
the range of the validation audits.
78
The dispersion coefficients for use in the Pasquill-Gifford model are
considered pertinent for gases and aerosols at distances of 0.1 to 100 km from
the plume source. However, it was postulated that the conditions specific to our
method required an adjustment to these coefficients, and Turner (1970, p. 3)
suggests that "If the dispersion parameters from a specific experiment are
considered to be more representative than those suggested in this workbook,
the parameter values can be used with the equations given here." A reiterative
least squares analysis of the validation data from 9/26/92 and 10/9/92 was used
to render appropriate coefficients for use in Equations 3.1 and 3.2. This
procedure provided values of 0.0528, 1.3740, 0.1300, and 1.7000 for the
coefficients a, b, c, and d, respectively. The graph in Figure 4.8 shows
validation data from both 9/26/92 and 10/9/92 evaluated via the modified
dispersion coefficients as compared to the measured ambient concentrations.
The modified diffusion coefficients, as described, were subsequently used for
the estimation of fugitive emissions from oil field sources.
4.6.3 Fugitive Emissions of Hydrogen Sulfide from Crude Oil Storage Tank Vents
Hydrogen sulfide is somewhat soluble in organic solvents and is observed
in the oil and natural gas recovered from West Texas oil fields. In addition,
many of the oil fields in West Texas are subjected to water injection as a means
of enhancing oil recovery. Introduction of water into the oil bearing strata has
79
been shown to promote the souring of reservoirs by enhanced growth of
microorganisms that produce hydrogen sulfide (Anonymous, 1993). Sulfate
reducing bacteria are able to grow in a wide temperature range (10-80°C); those
that survive even higher temperatures (121°C) have been identified. Even
though the organisms require anaerobic conditions for growth, they are able to
remain viable for extended periods in the presence of oxygen, such that the
introduction of oxygenated water into the reservoir does not significantly disrupt
the process of a well turning sour. The water injected into area wells dissolves
and suspends various materials in the reservoir, including hydrogen sulfide,
creating a mixture of oil and brackish water in the reservoir which is
subsequently pumped to the surface. The recovered mixture is routed to storage
tanks where the water and oil separate, permitting re-injection of the recovered
water. Re-injection of reclaimed water contaminated with thermophilic sulfate
reducing bacteria into the well serves to reinforce the cycle of souring.
The tanks where the oil/water mixtures are stored typically operate at or
near ambient atmospheric pressure with the tank contents vented directly into
the atmosphere. The arrangement is such that as a storage tank fills, the vapors
accumulated above the rising liquid are exhausted into the atmosphere. The
volume of head space vapor exhausted is thus proportional to the quantity of oil
pumped. Vent emissions are enhanced by the fact that continued heavy
pumping in the West Texas oil fields has significantly reduced the available
reserves, resulting in a pump overcapacity. As a result, oil can be removed from
80
a well much faster than it can refill the bore. Operating the pump jacks
intermittently allows recovery time for the oil to flow from bearing strata into the
well bores. However, the resulting interruptions in oil supply to the tank
Increases time for equilibration between the liquid and the vapor in tank. As a
result, hydrogen sulfide commonly reaches concentrations as high as 17% in the
tank vapor space. As a tank fills this entire process results in copious quantities
of hydrogen sulfide being vented into the atmosphere.
Pigeons frequently use oil field equipment as roosting and nesting sites,
and oil field workers can often gauge the amount of H2S in the vicinity of a tank
battery by the number of dead birds nearby. Nonetheless, periodically workers
get caught by surprise themselves. A man at Andrews, Texas, was found dead
beside a tank battery where he had apparently been overcome by H2S inhalation
(Anonymous, 1992). This case is typical of many similar incidents. In another
instance one roustabout was found dead, and a coworker was also found
unconscious nearby. This and similar cases serve to highlight the significance
of hydrogen sulfide outgassing from storage tanks.
Oil field operators are required to regularly submit forms containing
various field details, including the quantity of oil produced. The data from these
forms is summarized and reported annually by the Oil and Gas Division of the
Railroad commission (Guerrero etaj., 1991a, 1991b). Details available for the
Mallet lease of the Slaughter field, located approximately 2 miles West-
Northwest from the town of Sundown in Hockley County, Texas, enumerate
81
69,858 total barrels produced during 1991 from this lease (Guerrero et aJ.,
1991a), or roughly 191 barrels (30,365 L) daily. Using production statistics as
the tank fill rate, along with the H2S concentration of 177,000 ppmv reported for
this tank farm, the displaced effluvium is calculated to contribute an estimated
17.5 tons per year of sulfur into the atmosphere. Hockley county alone produces
nearly 3 million barrels of oil per year which could, by these estimates, disburse
as much as 751 tons of sulfur per year from fugitive emissions. Because the
estimated fill rates are based solely on reported oil production, and do not
account for any injected water entrained in the oil, the calculated value is likely
to be somewhat conservative.
Based on the understanding that tank vents are a significant but
undocumented source of fugitive emissions, specific tank farms were selected
for in depth studies to quantify the actual sulfur flux. Tank farm selection was
based primarily on a suitable combination of site accessibility, isolation, and
topography. All sites chosen contained at the least one primitive road permitting
facile entrance to and egress from the location. The sites were also relatively
flat (<2% grade), permitting essential off road access with the MARL. Sites were
chosen in rural areas with no buildings, trees, or other physical obstructions
except for the tanks and an occasional pump jack. Most sites were located in
ranching areas where there was no soil cultivation, and livestock, when present,
was typically at a maximum density of 1 cow per 5 acres (2 hectares).
Undisturbed top soil is a more important issue in soil studies, which are
82
considered in the following chapter, however, it was an important consideration
for each site selection.
Tanks collecting oil on the Mallet lease (33°28'N Latitude, 102°34'W
Longitude) is typical of the sites available and was one of several selected for
study. At the Mallet location, a battery of 4 storage tanks are connected by a
common flue which ducts the head space vapors to a single 2.5 inch diameter
exhaust outlet. The tank vapors discharge at a height of 7 meters above ground
level and at a distance 15 meters from the closest tank, as measured
perpendicular to the prevailing winds. There is no major equipment or other
topographical obstacles either upwind or downwind from the tank outlet. This
site was readily accessible to the MARL and the physical characteristics were
ideal for evaluation via the Pasquill-Gifford model.
Ambient levels of hydrogen sulfide were recorded downwind from the tank
vent at various distances. On 9/5/92 only data recorded at 55 meters downwind
from the vent provided useable data. On 7/24/93 reliable observations were
noted at 20, 74, and 141 meters downwind from the vent. The background
hydrogen sulfide concentration in the direction upwind from the vent was also
determined. Data collected from the experimental trials was compiled into
tabular form allowing use of a spread sheet to compute the sulfur flux
attributable to the tank vent. The results of this activity are presented
graphically in Figure 4.9 and Figure 4.10. On each chart the measured
hydrogen sulfide concentrations are metered along the left hand axis and
83
indicated by the circles. The Pasquill-Gifford plume dispersion model (Equation
3.3) was used to estimate sulfur flux from the tank vent based upon the ambient
hydrogen sulfide concentrations and concurrently recorded meteorological and
spatial data. The dispersion coefficients required by the model were calculated
using the modified parameters detailed in Section 4.6 in conjunction with
Equation 3.1 and 3.2. The estimated flux reported in tons of sulfur per year is
metered along the right hand side of the graphs and plotted as diamonds.
Although there is a substantial amount of variability in the estimates, a flux in the
range of ones to tens of tons of sulfur per year can be inferred. These estimates
are comparable in scale to the flux estimates based on tank fill.
4.7 Conclusions from Atmospheric Studies
West Texas Intermediate Crude is a benchmark crude classification
encompassing relatively sweet crude oil. The sulfur flux from this "sweet" oil
region has been demonstrated as substantial, and signifies significant
implications on the sulfur budget of the West Texas region where over 300
million barrels of oil are produced annually (Guerrero etaj., 1991a). Under the
typical conditions described above for tank vapor concentrations and fill rates,
fugitive emissions from oil production in West Texas alone could discharge in
excess of 85,810 tons of sulfur per year into the atmosphere. For the state of
Texas as a whole in excess of 161,375 tons per year could be added to the
atmospheric sulfur burden. This estimated statewide flux of 0.146 Tg S yr"
84
would account for only 0.1% of the total anthropogenic emissions of -100+ Tg S
year*\ However, for a single industry in a single state this is a significant
contribution to the global sulfur budget, and its impact on the state of Texas
warrants continued investigation. Under similar production conditions, the total
world oil production of 2.19 x 10 ° barrels per year (West, 1992) could emit as
much as 5.33 Tg S y" into the local atmospheres. This emission equals
approximately 5% of the total manmade production and as such is a significant
yet overlooked contribution to the global sulfur budget.
85
4.8 References
Anonymous (1992) Andrews Man found Dead. Lubbock Avalanche-Journal, 70th Year, September 12, 1992,
Anonymous (1993) Control of anaerobic bacteria. Corrosion Prevention & Control 40,1-2.
Arena M. D. Jay. M. and Drew R. P. (1986) Poisoning: Toxicology, Symptoms, Treatment, Charles C. Thomas, Springfield, IL.
Burnett W. W., King E. G., Grace M. and Hall W. F. (1977) HgS Poisoning: Review of 5 years' experience. Canadian Medical Association Journal 117, 1277-1280.
Ellenhorn M. J. and Bardeloux D. G. (1988) Medical Toxicology: Diagnosis and Treatment of Human Poisoning, Elsevier, New York.
Goody R. M. and Yung Y. L. (1989) Atmospheric Radiation, Oxford University Press, New York.
Guerrero L., Nugent J. E. and Krueger B. (1991a) 1991 Oil and Gas Annual Report: Volume 1. Railroad Commission of Texas: Oil and Gas Division.
Guerrero L., Nugent J. E. and Krueger B. (1991b) 1991 Oil and Gas Annual Report: Volume 2. Railroad Commission of Texas: Oil and Gas Division.
Hagemann J. A. (1992) Emission and Dispersion of Hydrogen Sulfide Gas Over West Texas Oil Fields. M. S. thesis, Dept. Chem. Eng., Texas Tech University.
Lenschow D. H. and Hicks B. B. (1989) Global Tropospheric Chemistry. National Center for Atmospheric Research.
Smith R. M. and Martell A. E. (1976) Critical Stability Constants, Plenum, New York.
Turner D. B. (1970) Workbook of Atmospheric Dispersion Estimates, US Government, Cincinnati.
West J. (1992) International Petroleum Encyclopedia, PennWell Publishing Co., Tulsa.
86
360
T3
O ••ts O
C
320 —I
4 — w
0) 0) Q.
CO T3
2 —
1:30 2:00 2:30 3:00 3:30
Time of Day (AM)
4:00 4:30 5:00
Figure 4.1 Instantaneous (black band) and 10 minute running average (embedded white line) values for wind speed and direction observed on a typical West Texas early morning January 27, 1994.
87
Figure 4.2 Chromatogram near a natural gas processing plant. A - H2S (-1 ppbv); B - MeSH (-1-100 ppbv).
4:00 5:00 6:00 7:00 8:00 9:00 10:00 11:00 12:00 13:00 Time of Day (Hours)
Figure 4.3 Diurnal pattern observed for atmospheric H2S concentrations.
88
20 —,
> .a a. Q.
CO 10
20:00 0:00 4:00 8:00 12:00 Time of Day (hours:minutes)
16:00
Figure 4.4 Test for effects of atmospheric oxidants on hydrogen sulfide, collected for continuous 24 hour period on 10/1/93 and 10/2/93.
Data
0.8
c
? 0.4 —
0.0
19:00 22:00 1:00 Time of Day (hours:minutes)
4:00
Figure 4.5 Effect of rain intensity on atmospheric hydrogen sulfide concentration. Shaded areas indicate precipitation events.
89
60
c o •g 40 — c 0 o c o O 0 •jo D
CO
c 0 O) o 1 -
•D >s
I TJ 0 _o CO O
20 —
O Oo
o
o o
O
O
O
O O
0 T
2 4 Measured Hydrogen Sulfide Concentration (ng/L)
Figure 4.6 Comparison of hydrogen sulfide concentrations calculated from release rate versus that measured from the sampled atmosphere. Results shown for data collected on 9/26/92.
90
60 —,
o Oo o
c c .9 •§ 40 — c 0 o c o O 0
*^ D
CO c 0 O) o
•o
I • D 0 i5 _o CO
O
o o
20 —
o o
0
o
Measured Hydrogen Sulfide Concentration (ng/L)
Figure 4.7 Comparison of hydrogen sulfide concentrations calculated from release rate versus that measured from the sampled atmosphere. Results shown for data collected on 10/9/92.
91
o o
o o o
o
o
o o
T T
0 2 4 Measured Hydrogen Sulfide Concentration (ng/L)
Figure 4.8 Comparison of hydrogen sulfide concentrations calculated from release rate versus that measured from the sampled atmosphere. Calculations are based on revised dispersion coefficients. Results shown for data collected on 9/26/94 (squares) and 10/9/92 (diamonds).
92
— 12
I — 8 ^
X
u_
(73
to UJ
0
8:30 8:45 9:00 Time of Day
9:15 9:30
Figure 4.9 Measured ambient concentration of hydrogen sulfide (circles) near a tank vent and estimated sulfur flux (diamonds) from the vent. Data set is for the Mallet lease in Hockley County as collected on September 5, 1992.
93
7:30 8:00 8:30 9:00 9:30 Time of Day
10:00 10:30
Figure 4.10 Measured ambient concentration of hydrogen sulfide (circles) near a tank vent and estimated sulfur flux (diamonds) from the vent. Data set is for the Mallet lease in Hockley County as collected on July 24, 1993.
94
CHAPTER 5
SOIL MAPPING
5.1 Introduction
The alkaline soils of West Texas are the predominant landscape feature
encountered in this region. With an average rain of less than 17 inches per
annum, the area is classified as semi-arid. The regional flora consists of
scattered short-prairie grasses (10 to 25 cm height), intermittent cacti (10 to 50
cm height), and sporadic cedar or mesquite scrub (most below 1 m in height).
To investigate the potential of alkaline soil to scavenge atmospheric acidity,
experiments were constructed to quantify the interaction of hydrogen sulfide with
area soils. Even though plants have been implicated as a sink for tropospheric
COS (Goldan, 1988), no studies on sorption of H2S by the regional flora or fauna
were performed.
5.2 Soil interactions with Atmospheric Sulfur Gases
Figure 5.1 illustrates the test chamber used to determine short term
interaction between soil and atmospheric sulfur gases. The chamber, AB, was
fabricated from a 38.0 liter low density polyethylene (LDPE) storage container
which was 51.0 cm long, 35.5 cm wide, and 21.0 cm deep. I/O ports, IP and SP,
were created by inserting PTFE tubing through the chamber wall. A soda lime
trap, formed from a 50 cc syringe barrel containing 45 cm^ of soda lime and
95
glass wool plugs at each end, was also inserted through the container wall. To
form an air tight seal at the chamber wall, each penetrating component was
forcibly inserted through a bore which was 0.7 mm smaller than the component's
nominal diameter. The tubing and trap were further sealed and secured in place
by the application of RTV silicone cement around the exterior girth of each
penetration. The container was oriented open end down such that the soil to be
examined was in contact with only the atmosphere contained within the test
chamber. The LDPE cover, AT, was installed when isolation between the
chamber atmosphere and the soil was necessary. Soil, LG, was mounded on all
sides of the enclosure and pressed firmly against the rim of the container to seal
the chamber over the test area.
To test soil-atmosphere interactions, the test chamber was utilized in two
different configurations. In each instance, the chamber contents were
continuously sampled at a rate of 5.00 SLPM from outlet port SP with the
sampled analyzed via the LS-GC-FPD. For each test configuration, data were
collected with the chamber both in contact with and isolated from the soil
surface. Infiltration of ambient air into the test chamber was avoided by
introducing a slight excess of diluent air allowing the excess volume to vent
through trap ZA.
96
5.2.1 Soil as a Source
Soil in an oil producing region was tested to ascertain its role as a
possible source of hydrogen sulfide during non daylight hours. A non-cultivated
location was selected (33°37'N Latitude, 102°23' W Longitude) and the test
chamber described previously in Section 5.2 was sealed onto the dry topsoil.
Dry zero-air was injected into the chamber inlet at 5.10 SLPM while the chamber
contents were sampled at a rate of 5.00 SLPM. To determine a blank sample,
the chamber was operated identically while isolated from soil surface by means
of the container cover. No significant signal due to hydrogen sulfide was
observed for either of the two configurations, indicating negligible out-gassing of
hydrogen sulfide from the soil. Introduction of ambient air into the test chamber
was unavoidable when switching between the two test configurations creating an
observable H2S signal. However, the H2S signal fell below the detection limit as
ambient air was swept from the sample chamber.
5.2.2 Soil as a Sink
5.2.2.1 Surface Adsorption
Scavenging of atmospheric acidity by the local alkaline soils was strongly
suspected and was examined using several methods. The initial study utilized
the test chamber described in Section 5.2. Hydrogen sulfide, (80 ng/min) in a
carrier stream of 100 SCCM dry zero air, entered the test chamber at port IP
where it was further diluted by the addition of 5.90 SLPM of zero air. The
97
chamber was continuously sampled at 5.00 SLPM and analyzed via the
LS/GC/FPD. With contact allowed between the H2S and soil, 8.1 ng/L of
hydrogen sulfide was detected. Isolation of the soil via the LDPE cover,
produced a blank reading of 13.7 ng/L of hydrogen sulfide. Residence time in
the 38.0 L test chamber was approximately 7.5 minutes during which a 41%
reduction of H2S was thus observed due to sorption by the 0.181 square meters
of soil surface.
5.2.2.2 Deposition Accrual
Subsequent to recognizing the strong interaction between dry topsoil and
hydrogen sulfide, a broader understanding of the uptake of sulfur gases by the
area soils was desired. This idea developed into a project aimed at quantifying
the accumulation of sulfate into the area soils. Considering that storage tank
vents had been previously identified as a primary source of H2S fugitive
emissions, see Section 4.3, the conjecture was that soil in the vicinity of a crude
oil storage tank should exhibit detectable accumulation of sulfur compounds.
Under ambient conditions, particularly during intimate contact with alkaline soil,
sulfur compounds would be quickly oxidized to sulfate, and a plan was
established to collect soil samples around a tank vent and analyze them for
sulfate content.
For the deposition accrual study, an oil storage tank farm in Cochran
County, Texas (33°30' N Latitude 102°39' W Longitude) was selected because
98
of its remoteness and the state of cultivation of the surrounding land. The
agricultural land use in the region is primarily either cotton farming or ranching.
Cotton production is associated with chemically intensive soil preparation
causing significant analytical interference. An appropriate site with uncultivated
land was identified and selected for sample procurement.
The three tank battery at the location discharged head space vapors via a
common conduit that vented at a height of 6 meters above ground level. Soil
samples were obtained radially with respect to the tank vent in a regular pattern.
Sampling at 10 m intervals along radii of 50°, 70°, 90°, 110°, 240°, and 270°,
beginning at 10 m, and ending at 100 m, provided 10 samples for each radius.
Structures, paving, and fencing at the site inhibited sample acquisition from
some radii, as well as from some scheduled locations. Surface samples were
obtained by collecting the top 1.5 cm of soil into sealed containers, with a total of
46 samples taken at the site. Blank soil samples were taken 45 miles west of
the tank vent (33°34' N Latitude 10r52' W Longitude) where the land use,
vegetation, and sampling conditions were similar to those of the test site with the
exception of oil production.
Data from the surface study suggested that an in-depth look at the soil
sulfate was warranted. We therefore collected of core samples from selected
locations at the site. The core sampling procedure is considerably more difficult
than the surface soil sampling method. Fourteen core samples and 2 core
blanks were obtained. The core samples were obtained by driving a 1 meter
99
length of 1.5 inch electrical metallic tubing (EMT) 60 cm into the ground. Due to
compaction each core was 7 to 28 cm short of the 60 cm ideal length. The
tubing/core assembly was withdrawn, sealed with food grade plastic, and
maintained in a vertical position to avoid mixing of any loose core portion during
transport. To remove samples from the core, the EMT was severed at 10 cm
intervals throughout the length of each core, permitting access to the appropriate
soil section.
All of the soil samples were dried for 8 hours at 130°C, and were
subsequently weighed into 500 mL plastic bottles for extraction. Five hundred
mL of deionized water was added to the each sample and shaken vigorously to
extract the soluble constituents after which the samples were left to settle
overnight. Aliquots of the sample were withdrawn through a filter and analyzed
via suppressed ion chromatography which is ideally suited for the determination
of aqueous sulfate at low concentrations. Dionex columns AS5A-5M and AG-5
were used as analytical and guard columns, respectively. A custom chemical
supressor, made in our laboratory, was used with dilute sulfuric acid as
regenerant. All chromatographic data were collected on an 386 class PC via a
Dionex ACI-450 data acquisition system.
Calibration data for the ion chromatograph were obtained at the beginning
and end of each session using Cr, NO3", and SO/' standards. Multiple
injections of each extracted soil sample were made for the analysis of sulfate ion
by the chromatograph with the average value reported. Figure 5.2 graphically
100
summarizes the sulfate data in a contour plot presenting the soil sulfate
concentration around the tank vent. The sulfate concentration of the soil ranged
from 20 to 200 parts-per-million by weight (ppmw), depending on its proximity
and bearing from the vent. The exhaust of the tank battery vent is located at the
center of the plot. A marked increase of sulfate deposition is observed along the
prevailing downwind direction with maximum deposition occurring 30 to 40
meters from the vent. These values compare to 1 ppmw for soils in adjacent
regions where there is no oil production.
Equation 3.5 was used to calculate ground level concentrations of
hydrogen sulfide predicted along a plume centerline. The particular parameters
used for this example include: 100 percent H2S, 40 mL/min release rate, 6 meter
release height, and 4 m/sec wind velocity. Solutions for the 6 different
atmospheric stability classes are exhibited graphically as the hairline plots in
Figure 5.3. Each line is inscribed with a letter corresponding to its atmospheric
stability class. The heavy line is a weighted average of the classes; with A, B, C,
D, E, and F weighted as 25, 25, 15, 15, 10, and 10 percent, respectively. The
average of the modeled results predicts maximum ground level concentration of
hydrogen sulfide at approximately 40 meters from the vent. The Pasquill-Gifford
model assumes total reflection of the plume at the ground; however, due to
adsorption by the soil, the gaseous sulfur level should diminish more rapidly
downwind of the maximum than shown. The measured concentrations of Figure
5.2 and the modeled concentrations of Figure 5.3 display remarkable agreement
101
with both Indicating a maximum sulfate concentration approximately 35 to 40
meters downwind.
The results of the surface samples piqued our Interest in the depth profile
of the sulfate concentration as it was unknown as to how the local climate would
affect the surface sulfate. Core samples were collected at locations
corresponding to the highest concentration of surface sulfate in addition to
background and blank locations. Sample collection, preparation, and analysis
procedures were described previously in Section 5.2.2.2.
The depth profile for each core displays concentration fluctuations which
are to be expected inasmuch as the soil was not entirely homogenous
throughout the full length of each core. The inclusion of vegetation such as
roots and humus at the full depth of 60 cm could affect soil density and porosity
and as a result significantly influence percolation of ionic constituents through
the soil. Depth profiles for representative core samples are presented
graphically in Figure 5.4 and Figure 5.5. These profiles have been normalized
to compensate for the soil compression created by the sampling procedure. The
normalization was linear notwithstanding the fact that compression was probably
more extreme towards the sample head.
Figure 5.4 exhibits the depth profile of the core samples obtained from
locations of highest surface concentration (50° and 70° radii, circles and
squares, respectively). The general trend observed is decreasing sulfate at
increasing depth, with the deepest subsurface concentrations exhibiting a 25 to
102
50% reduction compared to the surface concentrations. However, one core
(70°, 20 meter; open squares) revealed a different trend in which the sulfate
concentration remained relatively unchanged at 120 ppmw independent of the
sample depth. The topography of the site, including the proximity of this core to
the tanks, equipment, and paved work areas, may have affected the sulfate
profile of this core.
Figure 5.5 is a graph of sulfate concentration versus core depth for
samples from the 110° radius. These specimens are located crosswind to the
prevailing meteorological conditions and are intermediate in concentration
between the downwind and upwind samples. These four core profiles
demonstrate no discernible tendency as a function of sample depth, with each
yielding an average concentration approximating that found at the surface. Data
from the 90° radius (not shown) demonstrate similar behavior to the 110° cores
with average concentrations centered near 45 ppmw, as opposed to the average
35 ppmw observed along the 110° radius. Upwind along the 240° radius (not
shown), a tendency analogous to the crosswind data is also observed, with
average concentrations of approximately 20 ppmw. The blank surface and core
samples demonstrated a similar trend with sulfate concentrations averaging 5
ppmw; a value approximately 75 percent lower than the oil field background
levels.
103
5.3 References
Goldan P. D., Fall R., Kuster W. C. and Fehsenfeld F. C. (1988) Uptake of COS by growing vegetation: A major tropospheric sink. Journal of Geophysical Research 93, 14186-14192.
104
c AB J
SP
ZA
AT 1
IP ^
LG
iy .:.:.:.:.x...................... .........:.x.::-:?i««^ ^ U l l
Figure 5.1 Test chamber to examine H2S interaction with local soil.
105
(0 • D
C ^
ctio
in
g
0 .— . b CO
^ Q-
c o it
CO
o a. 0 Q k_
3
3
o CO 0
O) c o CO
CO k_
0 .a E 3 2 • - *
c 0 >
^ C CO *^ o c CO
• D
c 3 O CO ^^ o CO 0
C
o c o CO •
Cl CD - ^ > -D ^
| § 3E C:J)2 c **-. ; = CO
o 0 . _ ^-t
•O 0 .c E
Q. 0 I - o
O ^
o -o O 0)
<^ s 2 -
LJ- CO
106
(l/6u) [s'H]
o o d o
o p CD CO
o o CD CO
o o
40.
.00
o C\J
.00
o
^—.^ E^
^•^ c CD
> ^ C CO H £
Fro
0 o c Si to b "co
izon
t _
o X
row
lin
es a
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lass
es "
A"-
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1 - o
if) CO . CO
0 H -
c o ^ ^ 0 O)
9. 0 c > CD <0 E -D 3 0 C l ^ CO —r-
long
; a
we
CO (0
"0 0
> c 0 = ^~ ^^ -D P C O
o)-o
n at
be
le<
O CO '~-
ntra
as
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ogen
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ses"
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ydr
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osph
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107
met
er
met
er
o o •«- CM O 0
9 o
H
met
er
met
er
o o • • - CM O 0 O O 1^ N
t +
o CO
o U)
o
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o CM
o
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Q
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rom
CL
and
70°.
Sam
ra
dii o
f 50
°
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c o CO
• D
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aine
d do
w
—'
ore
sam
ples
ob
e co
ncen
trat
ion
Dep
th p
rofil
e of
c
max
imum
sur
fac
i n CO
(MLudd) [.g^OS]
CD O
Oi o ir O
108
(MUJdd) [./os]
o CO
o U)
o -
o CO
CJ CM
o
o
^^ E 3, x: • « . j
Q. 0)
n CD ^ 0 0
CO
re fr
om l
ocat
ion
CO
10°.
Sam
ples
•^
radi
us o
f
O) c 0 CO
T 3 C
^ CO CO
tain
ed c
ro
^
core
sam
ples
0
cent
ratio
n
H- C
Dep
th p
rofil
e 0
diat
e su
rfac
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Fi
gure
5.5
of
int
erm
e
109
CHAPTER 6
CONCLUSIONS
6.1 Summary
A sensitive hydrogen sulfide detector with a limit of detection of 200 parts-
per-trillion was developed. The detector provides a response every two-and-
one-half minutes providing an average value of the hydrogen sulfide
concentration for the sampling interval. This detector was assembled in
conjunction with other instruments and equipment on a mobile platform to create
a Mobile Atmospheric Environmental Laboratory (MARL). The MARL was
deployed in the oil fields of West Texas to identify fugitive sources of reduced
sulfur gases, and to quantify the amount of gases escaping from identified
sources.
6.2 Viabilitv of Models
A significant hindrance toof our early studies was a lack of understanding
of atmospheric modeling, with an especially unrealistic expectation toward the
predictive capabilities of a model. It is now understood that models cannot
produce acceptably accurate correlation between short-term predictions and
observed instantaneous data. However, models can simulate the ground-level
patterns of the concentrations fairly as demonstrated by the accumulation of
sulfate in the soil surrounding a tank vent. Also, it is has become obvious that a
110
close match between actual versus model conditions is required for suitable
results (Hanna, 1988).
6.3 Diurnal Pattern of Hydrogen Sulfide
No specific reason was discovered that could account for the diurnal
pattern observed in the hydrogen sulfide concentration The prospect of
photoinduced phenomenon was largely discounted by data from several of the
studies. Adsorption of sulfur by the soils is significant, but there is no reason to
believe that such action occurs only during daylight hours. Increased dispersion
due to the expansion of the Planetary Boundary Layer which occurs concomitant
with daylight was originally considered insufficient to account for the 2- 3 orders
of magnitude decrease in hydrogen sulfide concentration. However, in
describing conditions mirroring those of the early morning oil field observations
Turner (1979, pp. 509-510) notes that "If there is a significant contribution by
area sources or low level point sources, the same conditions as discussed in the
previous paragraph (stable with light winds) will produce build-up of
concentrations." The diurnal pattern may well partially be an aberration resulting
from the field conditions encountered.
6.4 Fate of Fugitive Sulfur Emissions
An increased understanding with regards to the fate of fugitive emissions
has resulted from the work presented herein. Previous estimations of the sulfur
111
flux from oil and natural gas operations do appear to be considerably short of the
actual total. Judging from the soil studies, a significant portion of the sulfur
escaping from the oil recovery operations is accumulated by the local soils which
highlights the regional Importance of the fugitive emissions from oil operations
as opposed to its global significance.
112
6.5 References
Hanna S. R. (1988) Air quality model evaluation and uncertainty. Journal of the Air and Waste Management Association 38, 406-412.
Turner D. B. (1979) Atmospheric dispersion modeling. Air Pollution Control Association 29, 502-519.
113
APPENDIX A
PASCAL COMPUTER SOFTWARE FOR USE WITH
DIGITAR PCW COMPUTER WEATHER STATION
114
************************************************************************
***** EXAMPLE OF TURBO PASCAL INTERFACE TO PCW SOFTWARE *****
***** THE PCW PROGRAM IS SELECTABLE AS RAM RESIDENT OR ***** ***** FOREGROUND ONLY. IN THE RAM RESIDENT MODE THE PROGRAM ***** ***** "WAKES-UP" ONCE PER MINUTE AND UPDATES ITS REGISTERS. ***** ***** ***** ***** TO USE PASCAL WITH PCW SOFTWARE YOU MUST FIRST RUN ***** ***** YOUR PCW PROGRAM AND EXIT TO BACKGROUND MODE. ***** ***** ***** ***** PASCAL MUST FIND THE PCW PROGRAM LOCATION AND THEN ***** ***** INITIALIZE POINTERS TO THE OFFSETS OF DATA REGISTERS ***** ***** THAT ARE OF INTEREST. ***** ************************************************************************ ***********************************************************************)
{$C-} (* specify this compiler option so keystrokes don't get lost *) (* ciuring ciisplay I/O. *)
/*************************************************************)
(* SET UP RECORD AND POINTER DEFINITIONS *) , * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * • * * * * * * * * * * * * * * * * * * * * * • * * * * * * * * )
TYPE
(* Define RegPack data structure as shown in T-Pascal manual *) (* this structure allows access to msdos and other software *) (* interupts. * RegPack = Record Case Integer of
1 : (AX,BX,CX,DX,BP,SI,DI,DS,ES,Flags : Integer); 2 : (Al,Ah,Bl,Bh,Cl,Ch,Dl,DH : Byte);
End; (* define pointers for data types to be extracted from the pew program*)
intDtr = ^Integer; (* pointer type for integer data*) byteptr = ' byte ; (* pointer type for byte data *)
-*************************************************************) (* DECLARATION OF POINTER VARIABLES *)
(* THE POINTER VARIABLES WILL BE INITIALIZED SO THAT THEY * * PoiNT TO DATA IN THE RAM RESIDENT PROGRAM (PCW) . *) ****^?i^LT;*2^T*******************-******-****************^
VAR
^ 4- v.whf.ntr- (* The background routine will continue update : byteptr, j^ in ^^^^^^^ ^^^ ^^^^ p^^ second while
(* this register is non-zero. Each second (* the routine decrements this register
(* until it reaches zero. After the register * eouals zero updates are once per minute. * TO request updates every second for the (* next 30 seconds, just put the value 30 in (* this register.
115
(
Hour Minute Second Day Month Year BarRel Tempi TempiLow
lowest reading TemplHigh
highest reading Temp 2 Temp2Low
of lowest reading Temp2High
highest reading WindSpeed WindAve WindHigh WindChill WindChillLow
lowest recorded WindDir : RainDaily :
accumulated daily RainYearly :
intptr intptr intptr intptr intptr intptr intptr intptr intptr
of temperature : intptr; of temperature : intptr; (* intptr;
Time of day hour (24 hour format) Time of day minute Time of day second day of the month month of the year year relative barometric pressure temperature 1 in (OF x 10)
1 (0F X 10) *)
* *' * *' * *' * *'
1 (OF X 10) temperature
*) 2 in 0F
temperature 2 (OF x 10 : intptr; of temperature
(* (* (* (*
intptr intptr intptr intptr intptr
wind chill : intptr; : intptr; rain (inches intptr;
2 (OF X 10) *) wind speed (Mph) Average of 60 samples highest wind speed (Mph) wind chill factor (OF x lo:
factor (OF x 10)*) (* wind direction
X 10)
(Degees)
* ) * ) * ) * )
(* accumulated yea r ly r a in (inches x 10)
/ * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * • • • * * * * * * * * * * * * * *
(* (* (* (*
DECLARATION OF POINTER OFFSET VALUES
DEFINE THE OFFSET THAT WILL BE ASSIGNED TO EACH POINTER * WHEN IT IS INITIALIZED. *
*************************************************************
CONST
0_Hour 0_Minute 0_Second 0_Day 0_Month 0_Year 0_BarRel 0_Templ 0_TemplLow 0_TemplHigh 0_Temp2 0_Temp2Low 0_Temp2High 0_WindSpeed 0_WindAve 0_WindHigh 0_WindChill 0_WindChillLow
= = = = = = = = = = = = =
= = = = =
516 518 520 522 524 526 530 536 538, 540, 542, 544, 546, 548, 550, 552; 554; 556;
Time of day hour (24 hour format) Time of day minute Time of day second day of the month month of the year year relative barometric pressure temperature 1 in (oF x 10) lowest reading of temperature 1 highest reading of temperature 1 temperature 2 in oF lowest reading of temperature 2 highest reading of temperature 2 wind speed (Mph) Average of 60 samples highest wind speed (Mph) wind chill factor (OF x 10) lowest recorded wind chill factor(oF x 10
116
(OF X 10)^ (OF X 10
(OF X 10)^ (OF X 10
0_WindDir 0_RainDaily 0_RainYearly
5 6 0 ; 5 6 2 ; 5 6 4 ;
(* (* (*
wind direction (Degees) accumulated daily rain (inches x 10) accumulated yearly rain (inches x 10)
*) *)
(* UPDATE O UPDATE
CONTROL REGISTER *) 514; (* CONTROLS UPDATE PERIOD(1/SEC OR 1/MIN)
*************************************************************
* PCW PROGRAM FUNCTIONS *
* DOS CALL 70 (HEX) IS USED BY PCW FOR PASSING PCW * * INFORMATION. THIS IS (SO FAR) UNUSED BY DOS. (IF ALL * * THE CPU REGISTERS ARE NOT AS DEFINED, THEN THE FUNCTION * * CALL IS PASSED TO DOS.) * * * * BX = $6060 (RETURN SEGMENT IN AX) * * BX = $7070 (CHANGE ALL $7070 REG. TO $0070) * * (USED TO VERIFY THAT PCW IS INSTALLED) * * BX=$8080 (UNINSTALL PCW AND FREE MEMORY) * * * * AX = $7070 * * CX = $7070 * * DX = $7070 * * SI = $7070 * * DI = $7070 * * BP,SP,CS,DS & ES ARE NOT DEFINED * *************************************************************
*) *)
(* PCW_Segment uses the return segment function of pew program (* BX = $6060 requests this function. The other registers are (* set to $7070 so that the pew program recognizes the function*) (* recjuest. *
Function Var
regs : begin with regs begin ax := $7070 bx := $6060 CX := $7070 dx := $7070 si := $7070 di := $7070 msdos(regs) PCW_Segment
end; end;
PCW_Segment
: regpack;
do
Integer;
(* ms-dos registers for function calls
= AX;
, . PCW_Installed uses the acknowledge P - s e - e funtion^cf^pcw^progra™ M
! : llt^flZo'irtlll Z%'^ToTr^ recognizes the function
117
(* request
Function PCW_Installed : Boolean-Var
regs : regpack; begin with regs do begin ax bx CX dx si di
(* ms-dos registers for function calls
$7070; $6060; $7 070; $7070; $7070; $7 070;
msdos(regs); PCW_Instailed
end; end;
= (bx = (dx =
ex) si)
and and
(ex (si
= dx) = di)
and and (di = $70)
(* Init_Ptrs (* (*
Procedure Init. Var Segment (* Variable to Begin Segment update Hour Minute Second Day Month Year BarRel Tempi TempiLow TemplHigh Temp 2 Temp2Low Temp2High WindSpeed WindAve WindHigh WindChill WindChillLow WindDir RainDaily RainYearly
End;
> Gets the segment location of the pew program, *) then sets each pointer to the pew segment and *) the offset from the constants declaration. *)
.Ptrs; : Integer; hold segment of pew program *)
Pew. Ptr Ptr Ptr Ptr Ptr Ptr Ptr Ptr Ptr Ptr Ptr Ptr Ptr Ptr Ptr Ptr Ptr Ptr Ptr Ptr Ptr Ptr
Segment Segment Segment Segment Segment Segment Segment Segment Segment Segment Segment Segment Segment Segment Segment Segment Segment Segment Segment Segment Segment Segment Segment
0_Update); 0_Hour); 0_Minute); 0_Second); 0_Day); 0_Month); 0_Year); 0_BarRel); 0_Templ); 0_TemplLow); 0_TemplHigh); 0_Temp2); 0_Temp2Low); 0_Temp2High); 0_WindSpeed); 0_WindAve); 0_WindHigh); 0_WindChill); 0_WindChillLow) 0_WindDir); 0_RainDaily); 0 RainYearly);
(* Use Bios Video call to turn off cursor *)
(* registers for function calls
118
Procedure Cursor_Off; Var Regs : RegPack; Begin
With Regs do Begin
AH := 1; CX := $2 000; Intr($10,Regs);
End; End;
(* Use Bios Video call to turn on cursor *) Procedure Cursor_On; Var_ Regs : RegPack; (* registers for function calls Begin
With Regs do Begin
AH := 1; CX := $0607; Intr($10,Regs);
End; End;
begin ClrSer; If Pew_Instailed then Begin
Init_Ptrs; Cursor_Off; repeat
Update'^ : = 4 ; GotoXY(l,l); Writeln('Hour Writeln('Min. Writeln('Sec. Writeln('Tempi Writeln('Barom Writeln; Writeln('press key to exit');
Until KeyPressed; end {If Pew_Installed} Else Write ('PROGRAM ABORTED > PCW program did not respond to
function calls.'); Cursor_On;
end.
,Hour^:2); ,Minute'":2) ; , Second'': 2) ; , tempi'" / 10:2:1) ; ,Barrel" / 100:5:2;
119
APPENDIX B
BASIC COMPUTER SOFTWARE FOR USE WITH
APPLIED TECHNOLOGIES
SONIC ANEMOMETER
120
'"sa_run.bas" gary tarver 7-11-92 'To allow interface from the Sonic Anemomneter to a IBM PC 'Using calibration data from sa_ealbf, the wind speed direction, 'and temperature can be calculated from the data recieved from the 'Sonic Anemometer.
DIM SHARED AxisAngle(2) DIM SHARED AxisCount(2, 2) DIM SHARED AxisDist(2) DIM SHARED AxisOffset(2) DIM SHARED AxisVelocity(2) DIM SHARED BufVal(2, 9) DIM SHARED CountTot DIM SHARED DataCol DIM SHARED DataRow DIM SHARED DecodeVal(2) DIM SHARED Direction 'DIM SHARED False DIM SHARED FrameOffset DIM SHARED GetTime DIM SHARED FileName DIM SHARED InpBufCol DIM SHARED InpBufRow DIM SHARED InpCurVal DIM SHARED InSyncFlag DIM SHARED OldBufRow DIM SHARED Speed DIM SHARED Temp DIM SHARED TestVal DIM SHARED TimeCount DIM SHARED Trial 'DIM SHARED True
AS DOUBLE AS DOUBLE AS DOUBLE AS DOUBLE AS DOUBLE AS INTEGER AS LONG AS INTEGER AS INTEGER AS DOUBLE AS DOUBLE AS INTEGER AS INTEGER AS STRING AS STRING AS INTEGER AS INTEGER AS INTEGER AS INTEGER AS INTEGER AS DOUBLE AS DOUBLE AS INTEGER AS LONG AS INTEGER AS INTEGER
CONST True% = -1, False% = 0
DECLARE FUNCTION SyneStart% () DECLARE FUNCTION InSyne% () DECLARE FUNCTION GetComDataTime% ( DECLARE FUNCTION FileDataTime% ()
DECLARE DECLARE DECLARE DECLARE DECLARE DECLARE DECLARE DECLARE
SUB SUB SUB SUB SUB SUB SUB SUB
InpBufChar () InpBufSet () Synchronize () WorkData () FileData () DisplayData () CalcWindParameters () GetComData ()
'initialize variables AxisDist(l) = .1550083374481374# 'Ud in meters from the calibration AxisOffset(l) = 0# 'Uoff in m/s from the calibration AxisDist(2) = .1536159592278677# 'Vd in meters from the calibration AxisOffset(2) = -.1006846876532566#
'Voff in m/s from the calibration
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CountTot = 100 'Time in 1/100 seconds to average into a data set FileName = "C:\DATA\940127 w.csv"
'setup screen for diaplay CLS PRINT "WORKING" PRINT PRINT PRINT " PRINT " Temperature PRINT "Time oC
Wind" Speed m/s
Direction Deg. "
'open file to hold the data and initialize for the day OPEN FileName FOR OUTPUT AS #2 PRINT #2, USING "Data collected on \ \"; DATE$ WRITE #2, "", "", "Wind" WRITE #2, "", "Temperature", "Speed", "Direction" WRITE #2, "Time", "OC", "m/s", "Deg." CLOSE
'clear buffer so can sync upon initialization FOR InpBufRow = 0 TO 2
FOR InpBufCol = 0 TO 9 BufVaKInpBufRow, InpBufCol) = 0
NEXT InpBufCol NEXT InpBufRow
InpBufCol = 0 InpBufRow = 0
DO 'begin the routine to collect data IF GetComDataTime THEN
GetComData IF InSyncFlag THEN CalcWindParameters DisplayData FileData IF FileDataTime THEN
' FileData END IF
END IF
LOOP WHILE INKEY$ = "" END
'"Enter Ambient Temperature in degrees Centigrade" DegC# =22.6 DegK# = DegC# + 273.15 SpeedSound# = (403.24 * DegK#) " .5 'calculate speed of sound in m/s
FOR 1% = 0 TO 3 60 STEP 10 x! = COS(I% * 3.141593 / 180) y! = SIN(I% * 3.141593 / 180) Theta# = ATO(y! / x!) * 180 ( 3.141593 IF Theta# < 0 THEN Theta# = l O -H Theta# _ IF y! < 0 THEN phi! = 180 ^ Theta# ELSE P^^' " T^eta# LPRINT USING "###.### "; 1%' ^''' ^ ' ^^^^^' ^^^'
NEXT 1%
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SUB CalcWindParameters
FOR^I% =^i''T0^2^°'' ° convert to calibration data
FOR J% = 1 TO 2 AxisCount(I%, J%) = AxisCount(I%, J%) / CountTot convert running total of counts into an average
AxisCount(I%, J%) = AxisCount(I%, J%) - 220 'subtract electronic delay correction factor AxisCount(I%, J%) = 1 / AxisCount(I%, J%) 'invert for subsequent use in formula
NEXT J% NEXT 1% 'calculate the Axis raw velocities FOR 1% = 1 TO 2
AxisVelocity (1%) = ((AxisCount (l%, 1) - AxisCount(l%, 2)) * AxisDist(I%) / 2 * 1.2E+07) - AxisOffset(1%)
NEXT 1% 'calculate the axis angle 'FOR 1% = 1 TO 2
IF AxisVelocity(l) = 0 THEN AxisAngle(l) = 90
ELSE AxisAngle(l) = ATN(AxisVelocity(2) / AxisVelocity(1)) * 180 /
3.14159265359# END IF IF AxisVelocity(2) = 0 THEN
AxisAngle(2) = 90 ELSE
AxisAngle(2) = ATN(AxisVelocity(1) / AxisVelocity(2) ) * 180 / 3.14159265359#
END IF 'NEXT 1% 'correct axis velocity for obstruction by the device. FOR 1% = 1 TO 2
IF ABS(AxisAngle(I%)) >= 70 THEN AxisVelocity(1%) = AxisVelocity (1%) / (.84 + (.16 * ABS (AxisAngle(I%) ) / 70))
NEXT 1% 'calculate wind speed Speed = ( (AxisVelocity(1) " 2) + (AxisVelocity(2) "2)) " .5 'calculate direction Direction = ATN (AxisVelocity (2) / AxisVelocity (1) ) * 180 /
3.14159265359# IF Direction < 0 THEN Direction = 180 + Direction IF AxisVelocity(2) < 0 THEN Direction = 180 + Direction
Direction = 360 - Direction 'calculatge temperature 'get speed of sound Temp = AxisDist(l) / 2 * (AxisCount(1, 1) + AxisCount(1, 2)) *
1.2E+07 'correct for crosswind distortion Temp = ((Temp " 2) + (AxisVelocity(2) " 2)) 'calculate temperature Temp = (Temp / 403.24) - 273.15
END SUB
SUB DisplayData IF InSyncFlag THEN
'print data to sereen LOCATE 7,1 PRINT " LOCATE 7, 1
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PRIN-r USING "\ \ ###.# ###.#^ #####"; GetTime; Temp; Speed; Direction
ELSE 'print bad data read to screen LOCATE 7, 1 PRINT USING "\ \ Sync Lost Data Not Recorded"; GetTime
END IF END SUB
SUB FileData 'print data to file 'open file to hold the data OPEN FileName FOR APPEND AS #2 IF InSyncFlag THEN
PRINT #2, USING "\ \_, ###.#_,###.##_,###"; GetTime; Temp; Speed; Direction
ELSE PRINT #2, USING "\ \ Sync lost no data recorded"; GetTime
END IF 'close file to force buffer flush so do not lose data CLOSE
END SUB FUNCTION FileDataTime%
TestValue! = (VAL (MID$ (GetTime, 4, 2)) * 10) + (VAL(RIGHT$ (GetTime, 2)) / 6)
IF ((TestValue! MOD 25) < 1) OR ((TestValue! MOD 50) < 1) THEN FileDataTime% = True
ELSE FileDataTime% = False
END IF END FUNCTION
SUB GetComData 'open com port for data input OPEN "COMl:9600,N,8,l,CD0,CS0,DS0,OP0,RS,TB2048,RB32767" FOR RANDOM
AS #1 Synchronize IF InSyncFlag THEN
FOR TimeCount = 1 TO CountTot 'provide visual indication of working if more than 1 second
interval 'turn this feature off 'IF (TimeCount MOD 100) = 0 THEN PRINT TimeCount
InpBufSet IF InSync THEN
DataRow = OldBufRow DataCol = FrameOffset
ELSE InSyncFlag = False EXIT FOR
END IF 'break into 2 directions FOR 1% = 1 TO 2
FOR J% = 1 TO 2 •get 2 data bytes per direction FOR K% = 1 TO 2
DataCol = (DataCol + 1) MOD 9 , . ., IF DataCol = 0 THEN DataRow = (DataRow -H 1) MOD 2 DecodeVal(K%) = BufVal(DataRow, DataCol)
SsCount(I%, J%) = AxisCount (1%, J%) ^ ( (DecodeVal (1) *
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256) + DecodeVal(2)) 'combine 2 data bytes into count number and add to total
so can get average 'running axis count total (not individual axis count)
NEXT J% NEXT 1%
NEXT TimeCount END IF 'data input routine completed CLOSE
END SUB
FUNCTION GetComDataTime% IF (VAL(RIGHT$(TIME$, 2)) MOD 5) < 1 THEN
GetComDataTime = True GetTime = TIME$
ELSE GetComDataTime = False
END IF END FUNCTION
SUB InpBufChar InpBufCol = (InpBufCol + 1) MOD 9 IF InpBufCol = 0 THEN
OldBufRow = InpBufRow InpBufRow = (InpBufRow + 1) MOD 2
END IF InpCurVal = ASC(INPUT$(1, #1)) BufVal(InpBufRow, InpBufCol) = InpCurVal
END SUB
SUB InpBufSet FOR 1% = 0 TO 8
InpBufChar NEXT 1%
END SUB
FUNCTION InSync% IF SyncStart THEN
'PRINT "in Sync" IF BufVal (OldBufRow, FrameOffset) = TestVal THEN
InSync = True ELSE
InSync = False END IF
ELSE InSync = False
END IF END FUNCTION
SUB Synchronize InSyncFlag = False FOR Trial = 1 TO 100
InpBufSet FOR FrameOffset = 0 TO 8
IF InSync THEN InSyncFlag = True EXIT SUB
END IF NEXT FrameOffset
NEXT Trial . . , y sianal" PRINT "Unable to Synchronize with the signal
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PRINT "************************************" BEEP BEEP BEEP
END SUB
FUNCTION SyncStart% SELECT CASE BufVal(InpBufRow, FrameOffset)
CASE 90 TestVal = 165 SyncStart = -1
CASE 165 TestVal =90 SyncStart = -1
CASE ELSE SyncStart = 0
END SELECT END FUNCTION
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APPENDIX C
BASIC COMPUTER SOFTWARE FOR CALIBRATON
OF APPLIED TECHNOLOGIES
SONIC ANEMOMETER
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'"sa_calbf.bas" gary tarver 7-10-92 'To allow interface from tho c:rr,•! -A 'and to get the calibration da?a?of^"'°"^^^^^ ° ^^^ P^ 'installed and the tempera?ur2 l 5 ° ^T^'. ^^^ ^^^° ^^ chamber must be before temperature measured and placed the variable DegC# 'running this calibratin program. DIM SHARED InpBuf Row%, OldRnfRnurSt T^^T^ ^ -. o DIM SHARED FrLeOffse«?'?estVaI%; Da?aRoS%'*iataColT*' ^"^^^l*'^' ^' DIM^Ax.sCount,2. 2, AS LONG, Axisiount^o^u! "fS^LONO, CountTot AS
DECLARE FUNCTION SyncStart% (InVal%) DECLARE FUNCTION InSync% () DECLARE SUB InpBufChar () DECLARE SUB InpBufSet () DECLARE SUB Synchronize () DECLARE SUB WorkData ()
'clear buffer so can sync upon initialization FOR InpBufRow% = 0 TO 2
FOR InpBufCol% = 0 TO 9 BufVal%(InpBufRow%, InpBufCol%) = 0
NEXT InpBufCol% NEXT InpBufRow% CLS PRINT "WORKING"
InpBufCol% = 0 InpBufRow% = 0
REM OPEN "COMl:300,N,8,l,CD0,CS0,DS0,OP0,RS,TB2048,RB2048" FOR RANDOM AS #1 OPEN "COM2:9600,N,8,l,CD0,CS0,DS0,OP0,RS,TB2048,RB32767" FOR RANDOM AS #1 ' OPEN "a:\temp.anm" FOR OUTPUT AS #2
'establish Synchronized link so can read in the data Synchronize
'begin the routine to collect data for 10 minutes for the calibration CountTot = 60000 'count for 10 minutes to get average FOR TimeCount! = 1 TO CountTot
'provide visual indication of working since 10 minute interval 'IF (TimeCount! MOD 100) = 0 THEN PRINT TimeCount! LOCATE 7, 1
InpBufSet IF InSync% THEN
WorkData ELSE
PRINT "SYNC LOST" Synchronize
END IF
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'break into 2 directions FOR 1% = 1 TO 2
FOR J% = 1 TO 2 'get 2 data bytes per direction FOR K% = 1 TO 2
DataCol% = (DataCol% + 1) MOD 9 IF DataCol% = 0 THEN DataRow% = (DataRow% + 1) MOD 2 DecodeVal#(K%) = BufVal%(DataRow%, DataCol%)
NEXT K% v,ux-B/
'combine 2 data bytes into count number AxisCount(I%, J%) = (DecodeVal# (1) * 256) + DecodeVal# (2) 'add to total so can get average AxisCountTot(I%, J%) = AxisCountTot(I%, J%) + AxisCount(I%, J%) PRINT AxisCountTot(I%, J%) / TimeCount!, AxisCount(1%, J%)
NEXT J% NEXT 1%
NEXT TimeCount! 'data input routine completed 'close COM: buffer so do not have overflow error CLOSE
'Begin calculation to convert to calibration data FOR 1% = 1 TO 2 FOR J% = 1 TO 2
AvrgAxisCount%(I%, J%) = AxisCountTot (1%, J%) / CountTot 'find average counts for each axis and direction) AxisTime#(I%, J%) = (AvrgAxisCount% (1%, J%) - 220) / 12000000 'Find time of flight for each axis and direction '220 is electronic time delay correction specified in the
procedure '12000000 is because count 12MHz clock so get count in second PRINT AvrgAxisCount%(I%, J%) ;
NEXT J% PRINT
NEXT 1% '"Enter Ambient Temperature in degrees Centegrade" DegC# =33.7 DegK# = DegC# + 273.15 SpeedSound# = (403.24 * DegK#) " .5 'calculate speed of sound in m/s FOR 1% = 1 TO 2
AxisDist#(I%) = (SpeedSound# * (AxisTime# (1%, 1) + AxisTime#(I%, 2))) / 2
'calculate axis distance AxisOf fset#(I%) = (AxisDist#(I%) / 2) * (d / AxisTime# (1%, 1)) - (1
/ AxisTime#(I%, 2))) 'Calculate axis offset
NEXT 1% PRINT "Ud = "; AxisDist#(l) ; " m" PRINT "Uoff = "; AxisOffset#(l) ; " m/s" PRINT "Vd = "; AxisDist# (2) ; " m" PRINT "Voff = "; AxisOffset#(2) ; " m/s" PRINT PRINT "Calibration Complete" PRINT "record these numbers for future use. END SUB InpBufChar ^ .
InpBufCol% = (InpBufCol% + 1) MOD 9 IF InpBufCol% = 0 THEN
01dBufRow% = InpBufRow% InpBufRow% = (InpBufRow% + 1) MOD 2
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END IF
InpCurVal% = ASC(INPUT$(1 #1))
END 30^^''^^*^'''^^^^^°''*' I^PBuicol%) = lnpcurval%
SUB InpBufSet FOR 1% = 0 TO 8 InpBufChar NEXT 1%
END SUB
FUNCTION InSync% IF SyncStart%(BufVal%(InpBufRow%, FrameOf fset%) ) THEN 'PRINT "in Sync" «^-^M mr ixj
IF BufVal%(01dBufRow%, FrameOffset%) = TestVal% THEN InSync% = -1
ELSE InSync% = 0
END IF ELSE
InSync% = 0 END IF
END FUNCTION
SUB Synchronize InSyncFlag% = 0 FOR trial% = 1 TO 100
InpBufSet FOR FrameOffset% = 0 TO 8
IF InSync% THEN InSyncFlag% = -1 EXIT SUB
END IF NEXT FrameOffset%
NEXT trial% PRINT "Unable to Synchronize with the signal" PRINT "************************************" END SUB
FUNCTION SyncStart% (InVal%)
SELECT CASE InVal% CASE 90
TestVal% = 165 SyncStart% = -1
CASE 165 TestVal% =90 SyncStart% = -1
CASE ELSE SyncStart% = 0
END SELECT END FUNCTION
SUB WorkData DataRow% = 01dBufRow% DataCol% = FraineOffset% FOR 1% = 1 TO 8
DataCol% = (DataCol% + 1) MOD 9 ^ ,, ,, ^ IF DataCol% = 0 THEN DataRow% = (DataRow% + 1) MOD 2 PRINT BufVal%(DataRow%, DataCol%) ;
NEXT 1% PRINT
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APPENDIX D
BASIC COMPUTER SOFTWARE FOR INTERFACE
OF METONE PARTICLE COUNTER
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' PART_CNT. BAS Particle counter program to get data dump of all records from ' MetOne particle counter '6-30-93 Gary Tarver '7-13-93 revised to provide full functions DECLARE SUB ActivateAndCount () CLS LOCATE 4, 1 PRINT " Establishing Comunications Link with MET ONE Counter" 'open disk file DiskFile$ = "c:\data\Met_One.txt" DiskFile$ = UCASE$(DiskFile$) OPEN DiskFile$ FOR APPEND AS #1 'open RS232 port OPEN "COM1:9600,N,8,2,ASC" FOR RANDOM AS #2 'check how much data to get PRINT #2, "U"; 'universal select to activate the counter;
Temp$ = INPUT$(1, #2) IF Temp$ = "U" THEN PRINT "Met One Counter Selected" 'for
program debugging 'ActivateAndCount PRINT #2, "h"; 'Put counter in stand-by mode
Temp$ = INPUT$(1, #2) ' PRINT Temp$, "Counter in stand by mode" 'for program debugging 'PRINT PRINT #2, "D"; 'Ask counter for number of events in the buffer Temp$ = INPUT$(1, #2) NumOfRec$ = "" NumOfRec$ = INPUT$(1, #2) NumOfRec$ = NumOfRec$ + INPUT$(1, #2) NumOfRec$ = NumOfRec$ + INPUT$(1, #2)
PRINT NumOfRec$, VAL(NumOfRec$) 'for program debugging NumOfRec% = VAL(NumOfRec$) ' PRINT #1, NumOfRec% 'for program debugging IF NumOfRec% = 0 THEN
CLS LOCATE 5, 1 PRINT " The MET ONE buffer is empty of data' PRINT " NO DATA from MET ONE counter was transferred to PRINT " a disk file"
ELSE LOCATE 4, 1 ^ „ PRINT "Collecting Data from MET ONE Counter LOCATE 5, 1 FOR 1% = 1 TO NumOfRec%
PRINT #2 "A"; T TNP INPUT #2' Temp$ 'Read records from file with LINE iNPUi y , leiupp , program debugging PRINT Temp$ i-ui. i Vd PRINT "."; PRINT #1, Temp$
NEXT 1% CLS PR?OT^"'' ' ••; NumOtRec?,- " records of data from MET ONE counter"
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PRINT " was appended to the disk file " PRINT " "; DiskFile$
END IF CLOSE #1 'close disk file CLOSE #2 'close RS232 END
SUB ActivateAndCount PRINT #2, "d"; 'Start counting (counter controlled);
Temp$ = INPUT$(1, #2) PRINT Temp$, "Counting Started"
FOR 1% = 1 TO 60 'waste some time to count for a while LOCATE 4, 4 PRINT 1% FOR J% = 1 TO 2048
LOCATE 5, 5 PRINT J%
NEXT J% NEXT 1% PRINT #2, "e"; 'stop counter
Temp$ = INPUT$(1, #2) PRINT Temp$, "Counting Stopped"
PRINT END SUB
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