Atmospheric radon ((222)Rn) and carbon dioxide (CO2) concentrations were used to gain insight into fugitive emissions in an Australian coal seam gas (CSG) field (Surat Basin, Tara region, Queensland). (222)Rn and CO2 concentrations were observed for 24 h within and outside the gas field. Both (222)Rn and CO2 concentrations followed a diurnal cycle with night time concentrations higher than day time concentrations. Average CO2 concentrations over the 24-h period ranged from ~390 ppm at the control site to ~467 ppm near the center of the gas field. A ~3 fold increase in maximum (222)Rn concentration was observed inside the gas field compared to outside of it. There was a significant relationship between maximum and average (222)Rn concentrations and the number of gas wells within a 3 km radius of the sampling sites (n = 5 stations; p < 0.05). A positive trend was observed between CO2 concentrations and the number of CSG wells, but the relationship was not statistically significant. We hypothesize that the radon relationship was a response to enhanced emissions within the gas field related to both point (well heads, pipelines, etc.) and diffuse soil sources. Radon may be useful in monitoring enhanced soil gas fluxes to the atmosphere due to changes in the geological structure associated with wells and hydraulic fracturing in CSG fields.
Atmospheric radon ((222)Rn) and carbon dioxide (CO2) concentrations were used to gain insight into fugitive emissions in an Australian coal seam gas (CSG) field (Surat Basin, Tara region, Queensland). (222)Rn and CO2 concentrations were observed for 24 h within and outside the gas field. Both (222)Rn and CO2 concentrations followed a diurnal cycle with night time concentrations higher than day time concentrations. Average CO2 concentrations over the 24-h period ranged from ~390 ppm at the control site to ~467 ppm near the center of the gas field. A ~3 fold increase in maximum (222)Rn concentration was observed inside the gas field compared to outside of it. There was a significant relationship between maximum and average (222)Rn concentrations and the number of gas wells within a 3 km radius of the sampling sites (n = 5 stations; p < 0.05). A positive trend was observed between CO2 concentrations and the number of CSG wells, but the relationship was not statistically significant. We hypothesize that the radon relationship was a response to enhanced emissions within the gas field related to both point (well heads, pipelines, etc.) and diffuse soil sources. Radon may be useful in monitoring enhanced soil gas fluxes to the atmosphere due to changes in the geological structure associated with wells and hydraulic fracturing in CSG fields.
The past decade has seen a dramatic increase
in unconventional
gas extraction worldwide. Unconventional gas differs from conventional
gas in that conventional gas is trapped in natural pores or fractures
in sedimentary layers while unconventional gas can also be adsorbed
to the sediment itself. One of these unconventional gases is coal
seam gas (CSG), also known as coal bed methane. Production of CSG
relies on the extraction of water, which reduces pore pressures and
thereby allows gases to desorb and flow through fractures and micropores
in a coal seam. Technological advances such as directional drilling
and hydraulic fracturing (i.e., the injection of fluid and proppants
under pressure into the wellbore to fracture geological strata), have
allowed greater access to these gas reserves through increasing the
connective matrix in subsurface sediments. Initial studies have shown
that unconventional shale gas extraction may increase groundwater–methane
concentrations in the vicinity of gas production wells.[1] However, there is also the potential for unintentional
or “fugitive” emissions produced through the CSG mining
process to be released into the atmosphere.Fugitive emissions
are gases that are unintentionally lost to the
atmosphere through the gas extraction, collection, processing and
transportation processes. These emissions can emanate from point sources
(e.g., venting, equipment leaks, and distribution) and enhanced diffusion
of gas from soils. Emissions include greenhouse gases (GHG) such as
carbon dioxide (CO2) and methane (CH4). While
not harmful to human health at low concentrations, these emissions
should be accounted for when estimating the net greenhouse gas footprint
of CSG operations. The release of methane is of particular interest
as it is a powerful greenhouse gas with a global warming potential
25 times that of CO2 over a 100-year time horizon.[2] Importantly, the atmospheric presence of these
gases may suggest the release of other gaseous substances, such as
volatile organic carbons[3,4] which may be harmful
to human health.[5] Without a quantitative
knowledge of the gases produced and their sources and sinks, it is
difficult to unequivocally estimate gas fluxes through modeling approaches.[6]Monitoring of radon (222Rn)
has been undertaken for
decades in enclosed spaces such as mines and dwellings where the build-up
of the gas can be harmful to human health.[7] Enhanced radon concentrations in groundwater and the atmosphere
have also been linked to earthquakes.[8] Radon
is a radioactive (half-life = 3.84 days) noble gas that is produced
in the 238U decay chain.[9,10] Since uranium
is present in nearly all rocks and sediments, soil-gas exchange represents
a nearly continuous source of radon to the atmosphere. Radon is an
excellent natural soil gas tracer because it is unreactive and its
short half-life prevents any significant build-up in the atmosphere
over long time scales. Therefore, the presence of 222Rn
in the atmosphere requires a nearby source. In addition, radon can
be easily detected by portable instruments that can be deployed in
the field.We hypothesize that measurement of atmospheric 222Rn
concentrations may provide a simple and effective way to gain insight
into fugitive emissions from CSG mining activities. The aim of this
study was to assess whether atmospheric 222Rn and CO2 concentrations are enriched within an Australian CSG field
relative to nearby areas outside the CSG field. We postulate that
a relationship between gas concentrations and the number of nearby
CSG wells will emerge if CSG extraction processes represent a significant
source of 222Rn and CO2 to the atmosphere.
Experimental
Section
This study was performed in a CSG field near Tara,
Queensland,
Australia (∼26°50′0″S, 150°20′0″E).
The area has two main gas fields, the Talinga and the Kenya gas fields,
with wells in varying states of exploration and production. The production
and exploration of CSG in the area is associated with the extensive
Walloon Coal Measures, which are relatively permeable (>4.93 x10–13 m2 in some seams) and generally shallow
(near surface to <400 m).[11] The water
table in the area is typically at a depth of ∼40 m,[12] however there is little historical water level
monitoring information available.We deployed 24-h time-series
stations to measure atmospheric 222Rn and CO2 at three locations within the gas
fields and two stations outside of the gas fields (Figure 1). A gas intake was positioned at 2 m above the
ground at each station. The first station (hereafter referred to as
North) was adjacent to an open wheat field approximately 3 km north
of the Kenya gas field and to the east of the Talinga gas field. The
second site was located on a roadside reserve in the central part
of the Kenya gas field (Central). The third site was located directly
south of a large water holding pond in the Kenya gas field (East).
The fourth site was located approximately 3 km south of the Kenya
gas field (South). The fifth site was located approximately 8 km from
the southern boundary of the Kenya gas field (Control). For each site,
the distance to the nearest well and the number of nearby wells are
indicated in Table 1.
Figure 1
The study site in the
Surat Basin, Tara region, Queensland. Gas
wells are indicated by a red cross (data from http://mines.industry.qld.gov.au/geoscience/interactive-resource-tenure-maps.htm, accessed 24 October 2012). The red crosses may represent more than
one well if they are in close proximity. CO2 (ppm) and 222Rn (Bq m–3 ± 2σ) concentrations
over a ∼24-h period are indicated for each site. The gray areas
represent night-time, while the white areas represent daytime.
Table 1
Position and Proximity
of Sampling
Sites to CSG Well Headsa
site
lat/long
∼distance to nearest gas
well (m)
wells within
1 (km)
2 (km)
3 (km)
4 (km)
north
26° 53′S, 150° 24′E
60
4
15
27
51
central
26°
57′S, 150° 25′E
500
4
17
36
63
east
26° 57′S, 150° 28′E
250
1
9
19
27
south
27° 1′S,
150° 27′E
1500
0
2
5
7
control
27° 5′S, 150° 20′E
4400
0
0
0
0
The location of well heads was
obtained from www.mines.industry.qld.gov.au/geoscience/interactive-resource-tenure-maps.htm, accessed 24 October 2012.
The study site in the
Surat Basin, Tara region, Queensland. Gas
wells are indicated by a red cross (data from http://mines.industry.qld.gov.au/geoscience/interactive-resource-tenure-maps.htm, accessed 24 October 2012). The red crosses may represent more than
one well if they are in close proximity. CO2 (ppm) and 222Rn (Bq m–3 ± 2σ) concentrations
over a ∼24-h period are indicated for each site. The gray areas
represent night-time, while the white areas represent daytime.The location of well heads was
obtained from www.mines.industry.qld.gov.au/geoscience/interactive-resource-tenure-maps.htm, accessed 24 October 2012.Measurements of 222Rn concentrations were performed
using a commercially available continuous radon-in-air monitor (RAD-7,
Durridge Company), with two-hour averaging intervals to ensure acceptable
counting statistics. CO2 measurements were taken using
two nondispersive infrared gas analysers (Li-cor 820) and two nondispersive
differential gas analysers (Li-cor 7000) recording at one minute intervals.
Water vapor was removed from air sample streams using a Drierite column
in-line with the analysers. All CO2 analysers were calibrated
using 0 and 502 ± 10 ppm certified reference gases (Coregas Australia).
The uncertainty of individual CO2 detectors was less than
2%, well below the natural variability in the region. For CO2 concentrations at the South site and the final 12 h at the Control
site, CO2 was measured every four hours using a cavity
ringdown spectrometer (Picarro G2201-i CRDS). The
spectrometer calibration was within 10 ppm of the Li-cor CO2 analysers. The radon monitors were calibrated by the manufacturer
(±5%). A cross-calibration check just before deployment resulted
in agreement within the calibration uncertainty. Automated weather
stations (Davis Vantage Pro) were deployed on six-meter poles at the
South and Control sites to determine wind, temperature and humidity
fluctuations. To compare averages, one-way ANOVA and regression analyses
were done using SPSS with p values ≤0.05 considered significant.
Results
and Discussion
Time Series Observations
Calm winds
occurred during
our experiment. During the day, winds were predominantly from the
NNE and averaged ∼1.2 m s–1. At night, wind
speeds approached zero. Over the 24 h period, temperatures ranged
from 10 to 25 °C. Humidity ranged from 25% during the day to
90% at night. There was no significant difference in the average atmospheric
pressure during the day and night (1008.5 ± 3.9 mbar and 1008.9
± 1.1 mbar respectively).Concentrations of 222Rn and CO2 followed similar diurnal patterns with lower
concentrations during daylight hours (Figure 1). CO2 concentrations varied from day to night by over
60 ppm at the Central site and by as little as 5 ppm at the Control
site. Concentrations of 222Rn increased at night by ∼5
fold at the Central and South sites and approximately doubled at the
Control site. This is probably due to the formation of a temperature
inversion layer at night, trapping any emissions closer to the surface
and causing the accumulation of gases released from soils or CSG infrastructure.
The release of radon at the soil-air interface has been shown to follow
a diurnal pattern with variations governed by temperature and wind
speeds,[13] which is consistent with our
observations. The effects of night-time inversion layers on 222Rn concentrations has been previously described for non-CSG regions.[14] Lower wind speeds and a lower atmospheric mixing
height at night may allow the accumulation of soil gas in the atmosphere.
These are important considerations for assessing CSG fugitive emissions
as the time of sampling could significantly alter the concentration
of gases in the atmosphere, and as such sampling of full 24-h cycles
is essential. A distinct spike in CO2 and 222Rn concentrations occurred at the Central site approximately 13.5
to 15 h after the start of monitoring. This spike corresponded to
a distinct shift in winds from NNE at ∼1.3 m s–1 to easterly at ∼0.5 m s–1 before returning
to a NNE direction.The highest average CO2 concentration
during the 24-h
period was measured at the Central site (∼468 ppm) while the
lowest was at the Control site (∼391 ppm) (Figure 2). There were significantly higher night-time average
CO2 concentrations at sites within the gas field (North,
Central and East) (p < 0.01) than at sites outside
(South and Control), while the Central and East sites had significantly
higher CO2 concentrations during the day compared to the
other sites (p < 0.01). The only significant difference
in 222Rn concentrations between sites occurred at night
between the Central site and the Control site (p =
0.04). This was caused by the relatively large standard deviations
due to the steady increase in 222Rn concentrations during
the night coupled with the long averaging times used (2 h).
Figure 2
Average CO2 (a) and 222Rn (b) concentrations
±1 SD at different sampling sites. The maximum CO2 (a) and 222Rn (b) concentrations during the day and night
are indicated with a solid circle.
Average CO2 (a) and 222Rn (b) concentrations
±1 SD at different sampling sites. The maximum CO2 (a) and 222Rn (b) concentrations during the day and night
are indicated with a solid circle.
Correlations between Gas Concentrations and Number of CSG Wells
There was a significant relationship between the number of wells
within 3 km of sampling sites and the maximum radon concentration
over the 24 h period (r2 = 0.81, p = 0.04) (Figure 3a). If we use
the average radon concentration, then the r2 value is higher (r2 = 0.87, p = 0.02) (Figure 3b). It is difficult
to estimate the exact area influencing gas concentrations at each
station. If we use the number of wells within 1 km, then the correlations
illustrated in Figure 3a are weaker (r2 = 0.74, p = 0.06), while
if we use the number of wells within 4 km of each monitoring station,
the correlations are similar but slightly lower (r2 = 0.83, p = 0.03). There was no
significant relationship between the number of wells at 3 km and the
average day (r2= 0.30, p = 0.34) and average night (r2 =
0.65, p = 0.10) 222Rn concentrations largely
due to the 222Rn concentrations at the south site being
comparably low during the day (1.48 ± 1.07 bq m–3) and high at night (11.21 ± 4.17 bq m–3).
Figure 3
Regression
plots of the number of CSG wells within 3 km of study
sites and maximum 222Rn (a), average 222Rn (b),
maximum CO2 (c), and average CO2 (d) concentrations.
Control (Co), South (S), East (E), North (N), and Central (Ce) study
sites are indicated.
Regression
plots of the number of CSG wells within 3 km of study
sites and maximum 222Rn (a), average 222Rn (b),
maximum CO2 (c), and average CO2 (d) concentrations.
Control (Co), South (S), East (E), North (N), and Central (Ce) study
sites are indicated.There was a positive, but statistically nonsignificant relationship
between the number of wells within 3 km of sampling stations and the
maximum CO2 concentration at each station (r2 = 0.72, p = 0.07) (Figure 3c). A weaker (but still positive) correlation was
found when the average CO2 concentration at each site was
used (r2 = 0.56, p = 0.14) (Figure 3d). The Central site, which
had the highest CO2 concentrations, was located approximately
30 m from a service road in the central part of the Kenya gas field
(Central). No short-term CO2 spikes similar to what would
be expected from passing vehicles was observed. The relatively low
concentrations of CO2 at the North site may be partially
due to the location of the station in relation to the prevailing wind
direction. The North site had a much smaller number of wells upwind
compared to the Central site. However, similar patterns of low 222Rn concentrations at the North site were not observed. The
diurnal variations in CO2 concentrations was likely driven
by ecosystem metabolism, leading to a reduction in CO2 through
plant uptake during the day and an increase in CO2 at night
due to respiration. The relatively higher background CO2 concentration in the atmosphere associated with a longer residence
time than radon may also have prevented stronger correlations from
emerging as a larger source could be needed to significantly alter
CO2 concentrations in the atmosphere. CO2 is
only a small fraction (<1%) of the CSG in the Surat Basin[15] and therefore CO2 release through
fugitive emissions is potentially masked by biological processes on
the surface. Alternatively, if enhanced diffusive soil fluxes occur
within the CSG field, part of the methane (which accounts for >98%
of Walloon Coal CSG[16]) may be oxidized
to CO2, and account for the general trend observed. For
example CH4 oxidation rates, and first-order rate constants,
of 45 g m–2 d–1 and −2.37
h–1 respectively have been reported for CH4-rich landfill soils.[17]In contrast
to CO2, uptake and release of atmospheric 222Rn by vegetation can be considered negligible due to its
low reactivity as a noble gas as supported by experiments with plants
growing in soils containing high uranium concentrations.[18] This, along with the nearly constant production
of 222Rn in soils and short residence time (several days)
makes 222Rn an excellent tracer of physical processes that
drive soil gas exchange. Radon has been extensively used to assess
gas exchange in conventional coal mines[19,20] and soils.[21] In the open atmosphere, 222Rn has
been used in conjunction with 14CO2 to quantify
CO2 emissions from fossil fuels in Europe.[6,22] However, the present study is the first to use 222Rn
concentrations to assess potential emissions from a CSG production
field.
Conceptual Model
We hypothesize that the high concentrations
of 222Rn and CO2 measured inside a CSG field
during this study are derived not only from gas extraction infrastructure,
but also from the depressurization (horizontal drilling, hydraulic
fracturing, groundwater extraction) of the coal seams which may increase
diffuse soil emissions (Figure 4). The changes
to subsurface strata influencing gas exhalation processes before an
earthquake may be conceptually similar to the changes imposed by CSG
extraction. Variation in 222Rn concentrations in groundwater[23] and the open atmosphere[24] has preceded large earthquakes. This is likely due to increased
subsurface stress which alters sediment pore spaces and opens or closes
cracks in the strata which releases 222Rn. For example,
an approximate 5-fold increase in atmospheric 222Rn concentrations
in the five months leading up to an earthquake was observed in Kobe,
Japan.[8]
Figure 4
Conceptual model of the potential alteration
to gas pathways through
CSG extraction. We hypothesize that the lowering of the water table
and the alteration of subsurface strata creates enhanced soil gas
exchange, which results in higher radon concentrations near CSG wells.
Conceptual model of the potential alteration
to gas pathways through
CSG extraction. We hypothesize that the lowering of the water table
and the alteration of subsurface strata creates enhanced soil gas
exchange, which results in higher radon concentrations near CSG wells.The groundwater level in the general
Tara region is predicted to
drop as a result of CSG extraction[12] and
has been reported to drop by approximately 100 m in certain locations
since the commencement of widespread CSG mining.[25] This would increase the unsaturated soil volume, which
may increase gas exchange with the atmosphere. The depressurization
of aquifers can change the geological structure of the soil profile
and create cracks and fissures that may enhance gas exchange. Maximum
hydraulic fracture heights of ∼588 m have been reported in
stimulated hydraulic fractures in U.S. shales,[26] however no data are available on the stimulated fracture
dimensions from CSG fields in Australia. As the coal seam targeted
for CSG production in the Tara region is relatively shallow (near
surface to <400 m)[11] and CSG wells are
reported to be as shallow as 65 m,[27] diffuse
surface emissions may be enhanced.While our conceptual model
(Figure 4) appears
to be the most reasonable explanation for the patterns observed, we
highlight that other hypotheses need to be assessed. The lack of baseline
studies prevents us from determining unequivocally whether the radon
enrichments are a response to CSG, or CSG companies simply choose
to drill wells in an area of naturally elevated radon concentrations.
In addition, different atmospheric mixing heights at the different
sampling stations could mask our source assessment. However, a spatially
heterogeneous atmosphere is unlikely considering the proximity of
our stations (<25 km apart) and the flat regional topography. The
atmospheric modelling of total gas fluxes is necessary to test this
hypothesis. Longer term observations and further sampling of radon-in-soil-gas
and radon-in-groundwater measurements may further support our hypothesis.
Distinguishing the relative contribution of point infrastructure and
diffuse soil sources is paramount because reducing infrastructure
gas leakages is likely to be less challenging than restoring the original
soil structure. In order to distinguish point and diffuse sources,
future studies may need to employ detailed baseline studies or alternatively,
use the isotopic signature of gases to try to elucidate the pathways
driving changes in atmospheric chemistry.
Implications
Quantifying
fugitive emissions from CSG
is an important consideration in determining the greenhouse gas footprint
of CSG compared to traditional hydrocarbons such as coal. Past studies
have suggested that nonconventional gas has less GHG emissions than
coal.[28−30] However, these studies overlooked the fact that CSG
activities may change the geological structure and enhance diffuse
soil gas exchange processes. In addition, these studies used a global
warming potential value for methane which is now believed to be too
low.[31] Using the more recent global warming
potential value, fugitive emissions as low as 2% to 3% of production
may make the GHG footprint of CSG higher than that of oil and coal.[32] Howarth et al.[32] estimated
fugitive emissions from the high-volume hydraulic fracturing of shale
formations to be between 3.6% and 7.9%, and Pétron et al.[3] estimated a similar range of between 2.9% and
7.7%, indicating the greenhouse gas footprint for unconventional gas
mining maybe 20–100% greater than coal on a 20-year horizon.
However, some of these results have been disputed.[33] This controversy highlights the need for development of
better methods to quantify fugitive emissions from CSG.This
study showed that 222Rn may be used as a tracer to qualitatively
describe fugitive emissions from a CSG field. Importantly, this study
highlights that single measurements may not give a reliable indication
of atmospheric gases and that continuous sampling over full diurnal
cycles is necessary. Further studies that quantify fugitive emission
over the entire lifecycle of gas fields using combinations of carbon
isotope ratios of CH4 and CO2, 222Rn, and volatile organic carbon should be undertaken to fill the
current gaps in knowledge concerning fugitive emissions from CSG and
other unconventional natural gas resources. The monitoring of atmospheric
gases at more sampling locations and over longer time scales may give
more confidence to our proposed conceptual model. Monitoring atmospheric
radon before and after the development of a CSG field could help to
reveal whether CSG mining enhances soil gas fluxes over the long-term.
Authors: J Lelieveld; S Lechtenböhmer; S S Assonov; C A M Brenninkmeijer; C Dienst; M Fischedick; T Hanke Journal: Nature Date: 2005-04-14 Impact factor: 49.962
Authors: Stephen G Osborn; Avner Vengosh; Nathaniel R Warner; Robert B Jackson Journal: Proc Natl Acad Sci U S A Date: 2011-05-09 Impact factor: 11.205
Authors: Peter W Swarzenski; F William Simonds; Anthony J Paulson; Sarah Kruse; Chris Reich Journal: Environ Sci Technol Date: 2007-10-15 Impact factor: 9.028