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A Threshold Line for Safe Geologic CO2 Storage Based on Field Measurement of Soil CO2 Flux

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  • Institute for Future Engineering

Abstract and Figures

Carbon capture and storage (CCS) is an established and verified technology that can implement zero emissions on a large enough scale to limit temperature rise to below 2 °C, as stipulated in the Paris Agreement. However, leakage from CCS sites must be monitored to ensure containment performance. Surface monitoring of carbon dioxide (CO2) concentrations at onshore CCS sites is one method to locate and quantify CCS site leakage. Employing soil accumulation chambers, we have established baseline data for the natural flux of CO2 as a threshold alert to detect CO2 leakage flux to ensure the safety of onshore CCS sites. Within this context, we conducted on-site CO2 measurements at three different locations (A, B, and C) on the INAS test field at the Ito campus, Kyushu University (Japan). Furthermore, we developed a specific measurement system based on the closed-chamber method to continuously measure CO2 flux from soil and to investigate the correlation between CO2 flux from the soil surface and various parameters, including environmental factors and soil sample characteristics. In addition, gas permeability and the effect of different locations on soil CO2 flux are discussed in this study. Finally, we present an equation for estimating the soil CO2 flux used in the INAS field site that includes environmental factors and soil characteristics. This equation assists in defining the threshold line for an alert condition related to CO2 leakage at onshore CCS sites.
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Journal of
Carbon Research
C
Article
A Threshold Line for Safe Geologic CO2Storage Based on Field
Measurement of Soil CO2Flux
Takashi Kuriyama 1, Phung Quoc Huy 2, * , Salmawati Salmawati 3and Kyuro Sasaki 2


Citation: Kuriyama, T.; Quoc Huy, P.;
Salmawati, S.; Sasaki, K. A Threshold
Line for Safe Geologic CO2Storage
Based on Field Measurement of Soil
CO2Flux. C2021,7, 34.
https://doi.org/10.3390/c7020034
Academic Editor: Patricia Luis
Received: 10 February 2021
Accepted: 24 March 2021
Published: 27 March 2021
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Copyright: © 2021 by the authors.
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This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
1Japan Oil, Gas and Metals National Corporation (JOGMEC), Minato-ku, Tokyo 105-0001, Japan;
kuriyama-takashi@jogmec.go.jp
2Department of Earth Resources Engineering, Faculty of Engineering, Kyushu University,
Fukuoka 819-0395, Japan; krsasaki@mine.kyushu-u.ac.jp
3PT Tura Consulting Indonesia, South Jakarta 12520, Indonesia; salmawatimustakar@gmail.com
*Correspondence: phung.quoc.huy.278@mine.kyushu-u.ac.jp
Abstract:
Carbon capture and storage (CCS) is an established and verified technology that can
implement zero emissions on a large enough scale to limit temperature rise to below 2
C, as
stipulated in the Paris Agreement. However, leakage from CCS sites must be monitored to ensure
containment performance. Surface monitoring of carbon dioxide (CO
2
) concentrations at onshore
CCS sites is one method to locate and quantify CCS site leakage. Employing soil accumulation
chambers, we have established baseline data for the natural flux of CO
2
as a threshold alert to detect
CO
2
leakage flux to ensure the safety of onshore CCS sites. Within this context, we conducted on-site
CO
2
measurements at three different locations (A, B, and C) on the INAS test field at the Ito campus,
Kyushu University (Japan). Furthermore, we developed a specific measurement system based on the
closed-chamber method to continuously measure CO
2
flux from soil and to investigate the correlation
between CO
2
flux from the soil surface and various parameters, including environmental factors
and soil sample characteristics. In addition, gas permeability and the effect of different locations
on soil CO
2
flux are discussed in this study. Finally, we present an equation for estimating the soil
CO
2
flux used in the INAS field site that includes environmental factors and soil characteristics. This
equation assists in defining the threshold line for an alert condition related to CO
2
leakage at onshore
CCS sites.
Keywords:
soil CO
2
flux; geologic CO
2
storage; threshold line; field measurement; safety;
CO2leakage
1. Introduction
Carbon dioxide (CO
2
) emissions to the atmosphere have gradually increased, causing
a global warming phenomenon over the past one to two centuries. According to the Inter-
governmental Panel on Climate Change (IPCC), global CO
2
emissions are currently rising
at approximately 42
±
3 Pg C per year [
1
]. Consequently, surface temperatures will be 2
C
higher than in the pre-industrial era (before 1876) in the next coming decades. Currently, a
number of different approaches are being considered to mitigate CO
2
emissions [
2
], as set
out in the Paris Agreement and include the following:
1. Improve energy efficiency and promote energy conservation.
2.
Increase usage of low-carbon fuels, including natural gas, hydrogen, or nuclear power.
3. Utilize renewable energy such as solar, wind, hydropower, and bioenergy.
4. Apply geoengineering approaches, for example afforestation and reforestation.
5. CO2capture and storage (CCS) or CO2capture, usage, and storage (CCUS).
Of these methods, CCS can potentially achieve zero emissions on a large enough scale
to decrease the forecast temperature rise to less than 2
C. In 2019, the number of large-scale
CCS facilities increased to 65, including 26 operational, three under construction, two
C2021,7, 34. https://doi.org/10.3390/c7020034 https://www.mdpi.com/journal/carbon
C2021,7, 34 2 of 18
have been suspended, 13 in advanced development, and 21 in early development [
3
]. The
global capture and storage capacity of projects currently in operation or under construction
equates to approximately 40 million tons per annum.
However, for reasons concerning health, safety, and the surrounding environment,
geological CO
2
storage sites need to monitor all types of CO
2
leakage into the atmosphere.
Monitoring methods include seismic monitoring, geo-electrical methods, temperature logs,
gravity methods, remote sensing, geochemical sampling, atmospheric monitoring, tracers,
soil gas, and microbiology. Of these, atmospheric monitoring methods play an important
role in the detection of environmental abnormalities. In particular, the monitoring of
subsurface CO
2
leakage from natural fractures or tectonic faults is essential. Leakage
monitoring can be conducted by continuously measuring soil CO
2
flux from the soil
surface to identify possible leakage sources [411].
A number of studies have concluded that soil, as a carbon source, can store approxi-
mately 2300 Pg C in the upper 100 cm of soil [
12
]. The amount of CO
2
flux emitted from
soil to the atmosphere ranges from 280 Pg C per year [
13
] to 359 Pg C per year [
14
], which
is approximately one-quarter of the total emissions in the carbon cycle. Principally, CO
2
gas in the soil is produced by respiration of plant roots, decomposition of soil organic
matter (SOM), and microbial activities [
15
]. As the CO
2
concentration in the soil layer
increases, a higher rate of diffusion into the atmosphere occurs at the soil surface due to
the concentration gradient effect.
The emission of CO
2
from the soil surface is a complicated process affected by many
factors. Among these, environmental elements such as soil temperature, soil water content
(moisture), and SOM content are the primary factors that have been investigated by several
researchers [
13
,
16
20
]. A number of studies have shown that soil CO
2
flux depends on
soil temperature, moisture content, and oxygen concentration [
21
23
]. Furthermore, soil
characteristics such as porosity and water saturation have also been shown to be important,
because they affect the transport of gas in the soil. Although numerous studies have been
conducted within this field, the flux of CO
2
from soils is still not well understood due to
complicated environmental and soil-related factors.
In this study, we developed an equation to estimate the threshold line to find a
possibility of CO
2
leakage at onshore geological CO
2
storage sites. The established baseline
play an essential role as a threshold alert to ensure the safety of onshore CCS sites. Once
abnormal CO
2
flux from soil surface is detected, it is necessary to take action immediately.
In addition, the effect of various environmental factors and soil characteristics on soil
CO
2
flux was also investigated at the INAS test field site located on the Ito campus,
Kyushu University.
2. Methods and Study Area
2.1. Study Area
Site investigations for this study were conducted at the INAS test field site
(Figure 1)
,
located on the west side of Ito campus, Kyushu University (Japan) at latitude 33
35
0
N and
longitude 130
12
0
E. The test field has previously been used for various environmental
studies. Based on data obtained from the official website of the Japan Meteorological
Agency (JMA), the average temperature in 2017 was 17.6
C, with minimum and maximum
monthly average temperatures of 7.4
C in January and 29.5
C in August, respectively. A
maximum precipitation of 289.5 mm was recorded in October, with a minimum of 23.5 mm
recorded in November.
C2021,7, 34 3 of 18
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Figure 1. Map of the INAS test field study area with three different measuring locations, A, B, and
C, located at Ito campus, Kyushu University, Japan.
Because specific soil characteristics could influence results, the following three locations
within the INAS test field were selected for our study:
Location A: covered with leaf litter and several clusters of living grasses.
Location B: soft soil surface covered with living grasses.
Location C: hard soil with many pebbles and no grass or leaf litter.
2.2. Soil CO
2
Flux
To accurately measure soil CO
2
flux, the authors developed a soil CO
2
flux measuring
system based on the closed-chamber method that includes a measuring chamber and con-
trolling system. An airtight chamber, 0.20 m in diameter and 0.35 m in height, was used
to trap emitted gas from the soil (Figure 2). In addition, a CO
2
gas sensor (GMP-343,
VAISALA Inc, Helsinki, Finland) was used to measure CO
2
concentrations and calibrated
using ±0.5% accurate gases at 0, 200, 370, 600, 1000, 4000 ppm, and 2%. While a high but-
terfly valve with an automated close-open regime was located inside the chamber at 0.26
m from the soil surface, a circulated fan located at the top of the chamber was used to
replace the air in the chamber with atmospheric air. Thermocouples (T- type, CHINO Inc,
Tokyo, Japan) with a range from 0 to 200 °C and ± 1.0 °C or ± 0.75% in accuracy were set
up to measure the temperature at different depths. Moisture sensors (EC-5, METTER Inc,
Pullman, WA, USA) with a range from 0 to 100% were then inserted into the subsurface
at a depth of 5 to 10 cm near the measuring chamber. A controlling system (Logger 308,
CYBER MELON, Hyogo, Japan) was used to control and record signals from these sen-
sors.
Figure 1.
Map of the INAS test field study area with three different measuring locations, A, B, and C,
located at Ito campus, Kyushu University, Japan. Because specific soil characteristics could influence
results, the following three locations within the INAS test field were selected for our study: Location
A: covered with leaf litter and several clusters of living grasses. Location B: soft soil surface covered
with living grasses. Location C: hard soil with many pebbles and no grass or leaf litter.
2.2. Soil CO2Flux
To accurately measure soil CO
2
flux, the authors developed a soil CO
2
flux measuring
system based on the closed-chamber method that includes a measuring chamber and
controlling system. An airtight chamber, 0.20 m in diameter and 0.35 m in height, was
used to trap emitted gas from the soil (Figure 2). In addition, a CO
2
gas sensor (GMP-343,
VAISALA Inc., Helsinki, Finland) was used to measure CO
2
concentrations and calibrated
using
±
0.5% accurate gases at 0, 200, 370, 600, 1000, 4000 ppm, and 2%. While a high
butterfly valve with an automated close-open regime was located inside the chamber at
0.26 m from the soil surface, a circulated fan located at the top of the chamber was used to
replace the air in the chamber with atmospheric air. Thermocouples (T-type, CHINO Inc.,
Tokyo, Japan) with a range from 0 to 200
C and
±
1.0
C or
±
0.75% in accuracy were set
up to measure the temperature at different depths. Moisture sensors (EC-5, METTER Inc.,
Pullman, WA, USA) with a range from 0 to 100% were then inserted into the subsurface
at a depth of 5 to 10 cm near the measuring chamber. A controlling system (Logger 308,
CYBER MELON, Hyogo, Japan) was used to control and record signals from these sensors.
C2021,7, 34 4 of 18
C 2021, 7, x FOR PEER REVIEW 4 of 17
Figure 2. System for measuring soil CO
2
flux using a closed-chamber method including a) schematic diagram of the system
and b) operational stages using a butterfly valve in the measurement cycle.
The following procedure was used to measure soil CO
2
flux:
All measuring apparatuses and related devices were carefully prepared to ensure
that they were in good working order. A power supply was set up to allow continu-
ous measurements to be taken, while a vinyl sheet was used to cover and protect all
measuring apparatuses and devices from rain. In addition, all measuring locations
were cleaned and leveled to ensure measurement stability.
The chamber was inserted vertically at the selected area to a depth of 1.5 cm to min-
imize interference from the surrounding atmosphere. In addition, the installation of
the chamber was completed 1 to 2 hours before measurements were taken to ensure
precise and accurate results.
Figure 2.
System for measuring soil CO
2
flux using a closed-chamber method including (
a
) schematic diagram of the system
and (b) operational stages using a butterfly valve in the measurement cycle.
The following procedure was used to measure soil CO2flux:
All measuring apparatuses and related devices were carefully prepared to ensure that
they were in good working order. A power supply was set up to allow continuous
measurements to be taken, while a vinyl sheet was used to cover and protect all
measuring apparatuses and devices from rain. In addition, all measuring locations
were cleaned and leveled to ensure measurement stability.
The chamber was inserted vertically at the selected area to a depth of 1.5 cm to
minimize interference from the surrounding atmosphere. In addition, the installation
of the chamber was completed 1 to 2 h before measurements were taken to ensure
precise and accurate results.
C2021,7, 34 5 of 18
The CO
2
sensor, fan, butterfly valve, thermocouples, and moisture sensors were
connected to the controlling system, with one end of the thermocouple and moisture
sensors inserted into the soil at a depth of 7 cm.
The power source was connected to the controlling system with adapters, and all
switches were turned on.
The butterfly valve was opened fully, the fan was turned on for approximately one
min for gas circulation, and CO
2
concentrations were stabilized to atmospheric levels
(400–500 ppm). Next, the butterfly valve was gradually closed until completely shut.
Finally, the CO
2
concentration inside the chamber was measured for 10 min, together
with other parameters such as soil temperature and moisture content.
Soil CO2flux was calculated using the following equation [24]:
J=V
A·C
t·1
22.4 ×103(1)
where J(
µ
mol
·
m
2·
s
1
) represents the soil CO
2
flux emitted from the soil surface,
C
t
(ppm
·
s
1
) is the time gradient of CO
2
concentration in the chamber, V(m
3
) is the volume
of the chamber, A(m
2
) is the soil area covered by the chamber, and 22.4
×
10
3
(m
3
/mol)
is the molar volume of an ideal gas at standard temperature and pressure.
The total time for a measuring cycle was 16 min, which included ten minutes for
measuring, one minute for air circulation, and five minutes for opening and closing the
butterfly valve. All data, including CO
2
concentrations and soil temperature, were recorded
every four seconds. In contrast, the time gradient of the CO
2
concentration was recorded
and calculated every 16 min using a data logger (Serial Ghost DB9, KEELOG, Minami,
FL, USA).
2.3. Measurement of Soil Moisture
In this study, soil moisture was measured with soil moisture sensors using capac-
itance/frequency domain technology. Principally, soil capacitance is measured by the
sensor output with a range from 0 to 2500 mV, equivalent to a moisture content of 0 and
100%, respectively. Therefore, soil moisture is calculated from the correlation between
output voltage and measured soil moisture. As soil moisture–capacitance is correlated to
soil type, the soil moisture output must be calibrated using the sampled soil. Several soil
samples were taken from locations A, B, and C at the INAS test field to verify the correlation
between the output voltage from soil moisture sensors and moisture measurements in the
laboratory. Using this correlation, an appropriate amount of water was added to the dried
soil in the laboratory to prepare mixed soil samples with different moisture contents. Soil
samples were then packed into plastic containers that matched the original volume in the
field. Two soil moisture sensors were inserted into the soil samples, and sensor outputs,
water saturation, volumetric water content, and gravimetric water content of soils were
recorded for varying moisture contents.
Water saturation can be described as the volume of water per unit of pore volume
using the following equation:
Sw=Vw
Vpore
·100 (2)
where S
w
(%) represents water saturation, V
w
(cm
3
) is the volume of water, and V
pore
(cm
3
) is the volume of the pores in the soil. Soil water content includes gravimetric and
volumetric soil water measured as mass or volume [25]. Gravimetric soil water content is
the mass of water in the soil, measured as the difference between moist soil and the soil
dried at 105
C, or oven-dry weight. Notably, gravimetric soil water content is expressed
per unit mass of oven-dried soil using the following equation:
GWC =m1m2
m2
·100 (3)
C2021,7, 34 6 of 18
where GWC (%) is the gravimetric soil water content, m
1
(g) is the mass of moist soil, and
m
2
(g) is the mass of the oven-dried soil. Measurements of soil gravimetric water content
are considered destructive (oven-drying) and therefore, the soil sample was not used for
further chemical analysis.
Volumetric soil water content is the volume of water per unit volume of soil expressed
by the following equation:
VWC =Vw
Vs
·100 (4)
where VWC (%) is the volumetric soil water content, V
w
(cm
3
) is the volume of water, and
Vs(cm3) is the volume of soil.
Soil moisture data were calculated using Equations (2) to (4) together with output data
from the sensors at each water weight level to investigate the correlation between output
voltage and analyzed soil moisture for samples from locations A, B, and C (Figures 35).
C 2021, 7, x FOR PEER REVIEW 6 of 17
where GWC (%) is the gravimetric soil water content, m1 (g) is the mass of moist soil, and
m2 (g) is the mass of the oven-dried soil. Measurements of soil gravimetric water content
are considered destructive (oven-drying) and therefore, the soil sample was not used for
further chemical analysis.
Volumetric soil water content is the volume of water per unit volume of soil ex-
pressed by the following equation:
VWC =
∙ 100 (4)
where VWC (%) is the volumetric soil water content, Vw (cm3) is the volume of water, and
vs. (cm3) is the volume of soil.
Soil moisture data were calculated using Equation (2) to (4) together with output data
from the sensors at each water weight level to investigate the correlation between output
voltage and analyzed soil moisture for samples from locations A, B, and C (Figure 3–5).
Figure 3. Calibrated results of water saturation at three locations (A, B, and C) using two sensors.
Figure 4. Calibrated results of volumetric water content at three locations (A, B, and C) using two
sensors.
Figure 3. Calibrated results of water saturation at three locations (A, B, and C) using two sensors.
C 2021, 7, x FOR PEER REVIEW 6 of 17
where GWC (%) is the gravimetric soil water content, m1 (g) is the mass of moist soil, and
m2 (g) is the mass of the oven-dried soil. Measurements of soil gravimetric water content
are considered destructive (oven-drying) and therefore, the soil sample was not used for
further chemical analysis.
Volumetric soil water content is the volume of water per unit volume of soil ex-
pressed by the following equation:
VWC =
∙ 100 (4)
where VWC (%) is the volumetric soil water content, Vw (cm3) is the volume of water, and
vs. (cm3) is the volume of soil.
Soil moisture data were calculated using Equation (2) to (4) together with output data
from the sensors at each water weight level to investigate the correlation between output
voltage and analyzed soil moisture for samples from locations A, B, and C (Figure 3–5).
Figure 3. Calibrated results of water saturation at three locations (A, B, and C) using two sensors.
Figure 4. Calibrated results of volumetric water content at three locations (A, B, and C) using two
sensors.
Figure 4.
Calibrated results of volumetric water content at three locations (A, B, and C) using
two sensors.
C2021,7, 34 7 of 18
C 2021, 7, x FOR PEER REVIEW 7 of 17
Figure 5. Calibrated results of gravimetric water content at three locations (A, B, and C) using two
sensors.
As shown in Figures 3, 4, and 5, the correlation coefficient (R2) between sensor output
and water content was over 0.94 across all samples. Therefore, it is possible to use mois-
ture sensor output data to calculate soil moisture using correlation equations. In this
study, VWC represents soil moisture in all calculations and discussions and was calculated
using the following equations:
Samples at Location A: 𝑦 = 0.173 ∙ 𝑥 − 57.36 (5)
Samples at Location B: 𝑦 = 0.174 ∙ 𝑥 − 57.03 (6)
Samples at Location C: 𝑦 = 0.156 ∙ 𝑥 − 51.28 (7)
where y (%) represents the volumetric soil water content and x (mV) represents the sensor
output data.
2.4. Measurement of soil organic matter (SOM)
Soil organic matter (SOM) and soil moisture were analyzed in the laboratory using 1
g soil samples taken from a 2.5 cm subsurface soil layer at the INAS testing field locations.
First, the weight of moisture (WW) was derived by subtracting the weight of the soil sample
after placing it in a drying oven at 105 °C for 1 h from the weight of the initial soil sample.
Next, to determine the weight of ash (WC), soil samples were placed in an electric furnace
at 500 °C for 1 h. Then, the temperature was increased to 800 °C for 45 min and cooled
down for 3 h in a vacuum canister. Subsequently, WC was calculated by determining the
difference between the sample weights before and after heating. Finally, the weight of
SOM (WO) was derived by subtracting the weight of moisture and ash from the weight of
the initial soil sample.
The amount of SOM rate was calculated using the following equation:
SOM =
(8)
where WO (g) refers to the weight of soil organic matter and WS (g) is the weight of the soil
sample.
The weight of SOM, WO was calculated from the proximate analysis results of mois-
ture and ash content in soil using the following equation:
W=W
−W
−W
(9)
where WS (g) represents the weight of the soil sample, WW (g) is the weight of moisture,
and WC (g) the weight of the ash.
Figure 5.
Calibrated results of gravimetric water content at three locations (A, B, and C) using
two sensors.
As shown in Figures 35, the correlation coefficient (R
2
) between sensor output and
water content was over 0.94 across all samples. Therefore, it is possible to use moisture
sensor output data to calculate soil moisture using correlation equations. In this study,
VWC represents soil moisture in all calculations and discussions and was calculated using
the following equations:
Samples at Location A : y=0.173·x57.36 (5)
Samples at Location B : y=0.174·x57.03 (6)
Samples at Location C : y=0.156·x51.28 (7)
where y(%) represents the volumetric soil water content and x(mV) represents the sensor
output data.
2.4. Measurement of Soil Organic Matter (SOM)
Soil organic matter (SOM) and soil moisture were analyzed in the laboratory using 1 g
soil samples taken from a 2.5 cm subsurface soil layer at the INAS testing field locations.
First, the weight of moisture (W
W
) was derived by subtracting the weight of the soil sample
after placing it in a drying oven at 105
C for 1 h from the weight of the initial soil sample.
Next, to determine the weight of ash (W
C
), soil samples were placed in an electric furnace
at 500
C for 1 h. Then, the temperature was increased to 800
C for 45 min and cooled
down for 3 h in a vacuum canister. Subsequently, W
C
was calculated by determining the
difference between the sample weights before and after heating. Finally, the weight of SOM
(W
O
) was derived by subtracting the weight of moisture and ash from the weight of the
initial soil sample.
The amount of SOM rate was calculated using the following equation:
SOM =WO
WS
(8)
where W
O
(g) refers to the weight of soil organic matter and W
S
(g) is the weight of the
soil sample.
The weight of SOM,W
O
was calculated from the proximate analysis results of moisture
and ash content in soil using the following equation:
WO=WSWWWC(9)
C2021,7, 34 8 of 18
where W
S
(g) represents the weight of the soil sample, W
W
(g) is the weight of moisture,
and WC(g) the weight of the ash.
2.5. Laboratory Measurement of Gas Permeability
The decrease in soil CO
2
flux from the soil surface after rainfall is primarily due to an
increase in soil water saturation (S
w
> 0.4). This is due to a reduction in CO
2
gas diffusion as
pores are filled by water. Therefore, in this study, the physical effect of soil water saturation
was estimated from CO
2
gas permeability using packed soil (6.38 cm
2
cross-section, 21.8 cm
length) from locations A and B (Figure 6). Gas permeability of soil can be correlated to
the gas diffusion coefficient through soil porosity (
ε
). Furthermore, based on the Kozeny-
Carman equation [
26
], permeability k(mD) is expressed by a function of
εn
/(1
ε
)
2
, where
n= 3–4, while the gas diffusion coefficient D(m
2
/s) is approximately proportional to
ε
.
Therefore, although both increase with an increase in
ε
,kis more sensitive to
ε
than D. In
the laboratory-based investigations, permeability was calculated using pressure drop and
CO2gas flow rate through soil packed in acrylic pipes using Darcy’s equation [27].
C 2021, 7, x FOR PEER REVIEW 8 of 17
2.5. Laboratory measurement of gas permeability
The decrease in soil CO2 flux from the soil surface after rainfall is primarily due to an
increase in soil water saturation (Sw > 0.4). This is due to a reduction in CO2 gas diffusion
as pores are filled by water. Therefore, in this study, the physical effect of soil water satu-
ration was estimated from CO2 gas permeability using packed soil (6.38 cm2 cross-section,
21.8 cm length) from locations A and B (Figure 6). Gas permeability of soil can be corre-
lated to the gas diffusion coefficient through soil porosity (
ε
). Furthermore, based on the
Kozeny-Carman equation [26], permeability k (mD) is expressed by a function of εn/(1 -
ε)2, where n = 3–4, while the gas diffusion coefficient D (m2/s) is approximately propor-
tional to
ε
. Therefore, although both increase with an increase in ε, k is more sensitive to ε
than D. In the laboratory-based investigations, permeability was calculated using pressure
drop and CO2 gas flow rate through soil packed in acrylic pipes using Darcy’s equation
[27].
Figure 6. Soil packed into an acrylic pipe for measurement of gas permeability (6.38 cm2 cross-
section, 21.8 cm length).
Results regarding gas permeability of soils are shown in Figure 7. As water saturation
increases, CO2 gas permeability decreases because of the declining porosity. The clear cor-
relation between gas permeability and water saturation indicates that CO2 diffusion is
constrained by increasing water content in soil. Consequently, soil CO2 flux decreased
with increasing soil moisture, due to the physical effect of moisture on soil. However, in
lower soil moisture ranges (Sw 0.3), the soil gas flux may be affected differently owing to
enhanced biological activity in the soil. We will discuss in detail the effect in Section 3.2.
In summary, our results indicate the permeability of soil at Location A to be lower than
that at Location B.
Figure 7. Carbon dioxide (CO2) gas permeability versus water saturation (Sw) at Locations A and
B.
Figure 6.
Soil packed into an acrylic pipe for measurement of gas permeability (6.38 cm
2
cross-section,
21.8 cm length).
Results regarding gas permeability of soils are shown in Figure 7. As water saturation
increases, CO
2
gas permeability decreases because of the declining porosity. The clear
correlation between gas permeability and water saturation indicates that CO
2
diffusion
is constrained by increasing water content in soil. Consequently, soil CO
2
flux decreased
with increasing soil moisture, due to the physical effect of moisture on soil. However, in
lower soil moisture ranges (S
w
0.3), the soil gas flux may be affected differently owing to
enhanced biological activity in the soil. We will discuss in detail the effect in Section 3.2. In
summary, our results indicate the permeability of soil at Location A to be lower than that
at Location B.
Figure 7.
Carbon dioxide (CO
2
) gas permeability versus water saturation (S
w
) at Locations A and B.
C2021,7, 34 9 of 18
3. Results and Discussion
3.1. Soil Temperature at Different Depths
Soil temperature is one of the most significant parameters related to soil CO
2
flux.
To determine the appropriate depth at which to measure soil temperature, temperature
measurements were taken on the surface and at 5, 7, and 10 cm depths. Temperature
readings were carried out simultaneously with soil CO2flux measurements.
Our results indicate that soil temperature on the surface and at a depth of 5 cm had
a wide range of fluctuation, while temperatures at a depth of 7 cm were more stable and
consistent and showed the highest correlation coefficient with soil CO
2
flux (Figure 8).
Hence, our results and discussion, we primarily focus on temperature data recorded at a
depth of 7 cm.
C 2021, 7, x FOR PEER REVIEW 9 of 17
3. Results and discussion
3.1. Soil temperature at different depths
Soil temperature is one of the most significant parameters related to soil CO2 flux. To
determine the appropriate depth at which to measure soil temperature, temperature
measurements were taken on the surface and at 5, 7, and 10 cm depths. Temperature read-
ings were carried out simultaneously with soil CO2 flux measurements.
Our results indicate that soil temperature on the surface and at a depth of 5 cm had
a wide range of fluctuation, while temperatures at a depth of 7 cm were more stable and
consistent and showed the highest correlation coefficient with soil CO2 flux (Figure 8).
Hence, our results and discussion, we primarily focus on temperature data recorded at a
depth of 7 cm.
Figure 8. Soil temperature on the surface and at three different depths, recorded at Location A (Dec 21, 2016 to Jan 2, 2017).
3.2. Effect of environmental factors on soil CO2 flux
Results from our study indicate a general trend of an increase in soil temperature
leading to an increase in soil CO2 flux (Figure 9). Notably, a similar tendency was observed
with the vertical fluctuation of soil temperature and soil CO2 flux, indicating a specific
correlation between soil temperature and soil CO2 flux. Furthermore, as soil temperature
fluctuated ahead of the soil CO2 flux in both increasing and decreasing soil temperature
trends, we conclude that CO2 flux from soils was affected by the respiration of plant roots
and soil microorganisms. As described by Pavelka [28], CO2 molecules produced by res-
piration diffuse to the soil surface and are then released into the atmosphere. Therefore,
soil temperature is a significant environmental factor that affects CO2 flux from soils.
Figure 8.
Soil temperature on the surface and at three different depths, recorded at Location A (Dec 21, 2016 to Jan 2, 2017).
3.2. Effect of Environmental Factors on Soil CO2Flux
Results from our study indicate a general trend of an increase in soil temperature
leading to an increase in soil CO
2
flux (Figure 9). Notably, a similar tendency was observed
with the vertical fluctuation of soil temperature and soil CO
2
flux, indicating a specific
correlation between soil temperature and soil CO
2
flux. Furthermore, as soil temperature
fluctuated ahead of the soil CO
2
flux in both increasing and decreasing soil temperature
trends, we conclude that CO
2
flux from soils was affected by the respiration of plant
roots and soil microorganisms. As described by Pavelka [
28
], CO
2
molecules produced by
respiration diffuse to the soil surface and are then released into the atmosphere. Therefore,
soil temperature is a significant environmental factor that affects CO2flux from soils.
Together with the correlation between soil CO
2
flux and soil temperature, we also
investigated the effect of precipitation on CO
2
flux. (Figure 10). Precipitation was recorded
from Dec 14, 2016 (0:00 a.m.) to Dec 15, 2016 (0:00 a.m.), with no rain recorded from Dec
17, 2016 (0:00 a.m.) to Dec 19, 2016 (9:00 a.m.). Our results indicate a high correlation
between CO
2
flux from soil and soil temperature when precipitation was near zero (from
Dec 17, 2016 (9:00 a.m.) to Dec 19, 2016 (9:00 a.m.)). On the other hand, during rainfall
periods (from Dec 14, 2016 (0:00 a.m.) to Dec 15, 2016 (0:00 a.m.)), the correlation with soil
C2021,7, 34 10 of 18
temperature was unclear. We suggest that under saturated conditions, soil CO
2
is partly
dissolved by water and stored in the soil pores rather than being emitted to the surface.
The amount of soil CO
2
flux over rainy days (Dec 14–15) was substantially lower than
that over dry days (Dec 17–19) by an average of 0.15
µ
mol
·
m
2·
s
1
. Therefore, we can
conclude that precipitation caused a reduction in CO2flux from soil.
C 2021, 7, x FOR PEER REVIEW 10 of 17
Figure 9. Variation trend of soil flux and soil temperature at a depth of 7 cm, as recorded at Loca-
tion A (Dec 30, 2016 to Dec 31, 2016).
Together with the correlation between soil CO2 flux and soil temperature, we also
investigated the effect of precipitation on CO2 flux. (Figure 10). Precipitation was recorded
from Dec 14, 2016 (0:00 am) to Dec 15, 2016 (0:00 am), with no rain recorded from Dec 17,
2016 (0:00 am) to Dec 19, 2016 (9:00 am). Our results indicate a high correlation between
CO2 flux from soil and soil temperature when precipitation was near zero (from Dec 17,
2016 (9:00 am) to Dec 19, 2016 (9:00 am)). On the other hand, during rainfall periods (from
Dec 14, 2016 (0:00 am) to Dec 15, 2016 (0:00 am)), the correlation with soil temperature was
unclear. We suggest that under saturated conditions, soil CO2 is partly dissolved by water
and stored in the soil pores rather than being emitted to the surface. The amount of soil
CO2 flux over rainy days (Dec 14-15) was substantially lower than that over dry days (Dec
17-19) by an average of 0.15 μmol. m2.s1. Therefore, we can conclude that precipitation
caused a reduction in CO2 flux from soil.
Figure 9.
Variation trend of soil flux and soil temperature at a depth of 7 cm, as recorded at Location
A (Dec 30, 2016 to Dec 31, 2016).
C 2021, 7, x FOR PEER REVIEW 11 of 17
Figure 10. Correlation between CO
2
flux from soils and soil temperature together with rainfall
data recorded at Location A (Dec 14, 2016 to Dec 20, 2016).
Furthermore, soil CO
2
flux levels declined not only on rainy days, but also for several
days thereafter. We suggest that this occurred because soil pores were filled with water,
leading to a lowering of gas diffusivity. Consequently, CO
2
gas does could not diffuse into
the atmosphere due to the displacement of CO
2
-rich soil by rainwater.
To investigate the relationship between CO
2
flux from soils and soil temperature, we
collected long-term monitoring data at Location A, from Dec 1, 2016 to Nov 23, 2017 (Fig-
ure 11). This figure demonstrates that soil CO
2
flux (J) increased exponentially with a rise
in soil temperature (T) at a range of 0 to 28 °C, with a peak of 8 μmol. m
2
.s
1
(3.8 g. m
2
.day
1
). However, when soil temperatures were above 28 °C, soil CO
2
flux decreased, specifically
by 75% at 35 °C. This phenomenon can be explained by a long period of high soil temper-
atures (above 28 °C) with no rain for approximately two weeks in August, which resulted
in a decrease in the activities of CO
2
-producing soil microbes. Davidson used the same
method with us, he reported that the natural soil CO
2
flux range from 1 to 30 g CO
2
.
m
2
.day
1
at a depth of 1 to 100m [29]. In our study, soil CO
2
flux was up to 8 μmol. m
2
.s
1
or 3.8 g. m
2
.day
1
at a depth of 7 cm.
Figure 10.
Correlation between CO
2
flux from soils and soil temperature together with rainfall data
recorded at Location A (Dec 14, 2016 to Dec 20, 2016).
C2021,7, 34 11 of 18
Furthermore, soil CO
2
flux levels declined not only on rainy days, but also for several
days thereafter. We suggest that this occurred because soil pores were filled with water,
leading to a lowering of gas diffusivity. Consequently, CO
2
gas does could not diffuse into
the atmosphere due to the displacement of CO2-rich soil by rainwater.
To investigate the relationship between CO
2
flux from soils and soil temperature,
we collected long-term monitoring data at Location A, from Dec 1, 2016 to Nov 23, 2017
(Figure 11). This figure demonstrates that soil CO
2
flux (J) increased exponentially with
a rise in soil temperature (T) at a range of 0 to 28
C, with a peak of 8
µ
mol
·
m
2·
s
1
(3.8 g
·
m
2·
day
1
). However, when soil temperatures were above 28
C, soil CO
2
flux
decreased, specifically by 75% at 35
C. This phenomenon can be explained by a long
period of high soil temperatures (above 28 C) with no rain for approximately two weeks
in August, which resulted in a decrease in the activities of CO
2
-producing soil microbes.
Davidson used the same method with us, he reported that the natural soil CO
2
flux range
from 1 to 30 g CO
2·
m
2·
day
1
at a depth of 1 to 100 m [
29
]. In our study, soil CO
2
flux was
up to 8 µmol·m2·s1or 3.8 g·m2·day1at a depth of 7 cm.
C 2021, 7, x FOR PEER REVIEW 12 of 17
Figure 11. Long-term monitoring of soil CO2 flux and soil temperature at Location A (Dec 1, 2016
to Nov 23, 2017).
Our results are consistent with those of Allison [30] that indicate that a warming soil
could reduce carbon-use efficiency and reduce carbon decomposition by microbes,
thereby limiting the production of CO2. Furthermore, Tang [19] indicates root and micro-
organism activity to be typically low under dry conditions, resulting in a low soil CO2
flux.
As a result, soil CO2 flux increased with soil moisture at a soil moisture range of 0 to
30%, but substantially decreased at soil moisture levels of above 30% (Figure 12). This,
again, highlights the reduction in CO2 flux from soils at high moisture levels due to soil
pores filling with water and consequently, lowering gas diffusivity from the soil to the
atmosphere. Although an increase in soil moisture generally increases bio-activity in the
soil, under very high soil moisture conditions, total soil CO2 flux is reduced due to the
limited diffusion of oxygen and subsequent reduction in CO2 emissions [20].
Figure 12. Soil CO2 flux (J) and soil temperature (T) across various soil moisture levels, recorded at
Location A (Dec 5, 2016 to Oct 9, 2017).
Results from soil CO2 flux data across various water saturation levels at Location A
show the reduction in soil CO2 flux not only during rain hours, but also for a specific post-
rain period (Figure 10). This indicates that CO2 flux was directly affected by precipitation.
More specifically, precipitation firstly increased the water saturation in soil porosity and
Figure 11.
Long-term monitoring of soil CO
2
flux and soil temperature at Location A (Dec 1, 2016 to
Nov 23, 2017).
Our results are consistent with those of Allison [30] that indicate that a warming soil
could reduce carbon-use efficiency and reduce carbon decomposition by microbes, thereby
limiting the production of CO
2
. Furthermore, Tang [
19
] indicates root and microorganism
activity to be typically low under dry conditions, resulting in a low soil CO2flux.
As a result, soil CO
2
flux increased with soil moisture at a soil moisture range of 0
to 30%, but substantially decreased at soil moisture levels of above 30% (Figure 12). This,
again, highlights the reduction in CO
2
flux from soils at high moisture levels due to soil
pores filling with water and consequently, lowering gas diffusivity from the soil to the
atmosphere. Although an increase in soil moisture generally increases bio-activity in the
soil, under very high soil moisture conditions, total soil CO
2
flux is reduced due to the
limited diffusion of oxygen and subsequent reduction in CO2emissions [20].
C2021,7, 34 12 of 18
C 2021, 7, x FOR PEER REVIEW 12 of 17
Figure 11. Long-term monitoring of soil CO2 flux and soil temperature at Location A (Dec 1, 2016
to Nov 23, 2017).
Our results are consistent with those of Allison [30] that indicate that a warming soil
could reduce carbon-use efficiency and reduce carbon decomposition by microbes,
thereby limiting the production of CO2. Furthermore, Tang [19] indicates root and micro-
organism activity to be typically low under dry conditions, resulting in a low soil CO2
flux.
As a result, soil CO2 flux increased with soil moisture at a soil moisture range of 0 to
30%, but substantially decreased at soil moisture levels of above 30% (Figure 12). This,
again, highlights the reduction in CO2 flux from soils at high moisture levels due to soil
pores filling with water and consequently, lowering gas diffusivity from the soil to the
atmosphere. Although an increase in soil moisture generally increases bio-activity in the
soil, under very high soil moisture conditions, total soil CO2 flux is reduced due to the
limited diffusion of oxygen and subsequent reduction in CO2 emissions [20].
Figure 12. Soil CO2 flux (J) and soil temperature (T) across various soil moisture levels, recorded at
Location A (Dec 5, 2016 to Oct 9, 2017).
Results from soil CO2 flux data across various water saturation levels at Location A
show the reduction in soil CO2 flux not only during rain hours, but also for a specific post-
rain period (Figure 10). This indicates that CO2 flux was directly affected by precipitation.
More specifically, precipitation firstly increased the water saturation in soil porosity and
Figure 12.
Soil CO
2
flux (J) and soil temperature (T) across various soil moisture levels, recorded at
Location A (Dec 5, 2016 to Oct 9, 2017).
Results from soil CO
2
flux data across various water saturation levels at Location A
show the reduction in soil CO
2
flux not only during rain hours, but also for a specific post-
rain period (Figure 10). This indicates that CO
2
flux was directly affected by precipitation.
More specifically, precipitation firstly increased the water saturation in soil porosity and
secondly, increased the soil moisture content. Furthermore, our results indicate that the
CO
2
flux reached a peak at S
w
= 0.4 (Figure 13). Several studies have presented a similar
quadratic correlation between soil CO
2
flux and soil water content, with soil CO
2
flux
reaching a peak at a certain soil water level [24,31].
C 2021, 7, x FOR PEER REVIEW 13 of 17
secondly, increased the soil moisture content. Furthermore, our results indicate that the
CO2 flux reached a peak at Sw = 0.4 (Figure 13). Several studies have presented a similar
quadratic correlation between soil CO2 flux and soil water content, with soil CO2 flux
reaching a peak at a certain soil water level [24,31]
Figure 13. Correlation between CO2 flux from soil (J) and water saturation (Sw), recorded at Loca-
tion A (Jul 31, 2017 to Oct 9, 2017).
Under conditions where Sw > 0.4, the exchange of CO2 and oxygen molecules via gas-
eous diffusion is reduced due to reduced porosity in the soil [32]. In addition, the diffusion
of CO2 in the soil matrix is limited due to pores being filled with water [33].
The correlation between soil CO2 flux and water saturation is expressed in Equation
(10).
J(S,T) J

= −3.09S
+ 2.77S+0.37 (10)
However, under low water saturation levels (Sw < 0.4), CO2 gas generated by decom-
posing carbon from roots and plants is accelerated by moisture under sufficient oxygen
molecules diffused from the surface. Overall, it can be concluded that when Sw = 0.4, soil
CO2 flux (J) reaches a peak by satisfying oxygen diffusion and enhancing carbon decom-
position by microorganisms in the soil. Therefore, both extreme dry and wet conditions
result in reduced CO2 gas flux from the soil to the surface.
3.3. Soil CO2 flux at different locations
To investigate the influence of different soil characteristics and environmental factors
on soil CO2 flux, we compared data collected from three study locations, namely Location
A (Dec 1, 2016 to Nov 26, 2017), B (Nov 1 to Dec 19, 2018), and C (Oct 25 to Nov 1, 2018).
Data on the relationship between soil CO2 flux and soil temperature at the three study
locations indicate that the soil CO2 flux at Location A increased exponentially with in-
creasing soil temperature (Figure 14). A similar trend was also recorded at Location B with
a substantially higher amount of soil CO2 flux than at Location A. On the contrary, only a
minimal amount of the soil CO2 flux was recorded at Location C.
Based on the results from Figure 14, the following three equations were obtained:
For Location A: 𝐽 = 0.487𝑒. (11)
For Location B: 𝐽 = 1.76𝑒. (12)
For Location C: 𝐽 = 0.128𝑒. (13)
where JMax (μmol. m2.s1) is the soil CO2 flux from the soil surface, and T (°C) represents
soil temperature.
Figure 13.
Correlation between CO
2
flux from soil (J) and water saturation (S
w
), recorded at Location
A (Jul 31, 2017 to Oct 9, 2017).
C2021,7, 34 13 of 18
Under conditions where S
w
> 0.4, the exchange of CO
2
and oxygen molecules via
gaseous diffusion is reduced due to reduced porosity in the soil [
32
]. In addition, the
diffusion of CO2in the soil matrix is limited due to pores being filled with water [33].
The correlation between soil CO
2
flux and water saturation is expressed in
Equation (10).
J(Sw,T)/Jmax =3.09S2
w+2.77Sw+0.37 (10)
However, under low water saturation levels (S
w
< 0.4), CO
2
gas generated by decom-
posing carbon from roots and plants is accelerated by moisture under sufficient oxygen
molecules diffused from the surface. Overall, it can be concluded that when S
w
= 0.4, soil
CO
2
flux (J) reaches a peak by satisfying oxygen diffusion and enhancing carbon decompo-
sition by microorganisms in the soil. Therefore, both extreme dry and wet conditions result
in reduced CO2gas flux from the soil to the surface.
3.3. Soil CO2Flux at Different Locations
To investigate the influence of different soil characteristics and environmental factors
on soil CO
2
flux, we compared data collected from three study locations, namely Location
A (Dec 1, 2016 to Nov 26, 2017), B (Nov 1 to Dec 19, 2018), and C (Oct 25 to Nov 1, 2018).
Data on the relationship between soil CO
2
flux and soil temperature at the three
study locations indicate that the soil CO
2
flux at Location A increased exponentially with
increasing soil temperature (Figure 14). A similar trend was also recorded at Location B
with a substantially higher amount of soil CO
2
flux than at Location A. On the contrary,
only a minimal amount of the soil CO2flux was recorded at Location C.
C 2021, 7, x FOR PEER REVIEW 14 of 17
Figure 14. Comparison of the relationship between CO2 flux from soil (J) and soil temperature (T)
at Location A (Dec 1, 2016 to Nov 26, 2017), B (Nov 1, to Dec 9, 2018), and C (Oct 25, to Nov, 2018).
To investigate the difference in soil CO2 flux between the three study area locations,
porosity and SOM were examined as characteristics related to soil CO2 flux (Figure 15).
Our results indicate that Location B, covered with living grasses, had the highest SOM
value of 0.173, while a SOM of 0.082 was measured at Location A, and the lowest SOM
value of 0.036 was measured at Location C, which was covered with pebbles.
Furthermore, the larger the SOM, the larger the fluctuation range of soil CO2 flux at
the same soil temperature. For example, at a temperature of 16 °C, the soil CO2 flux ranged
from 0.910 to 2.583 μmol.m2.s1 and from 3.833 to 6.695 μmol.m2.s1 at Locations A and B,
respectively, while less than 0.311 μmol.m2.s1 at Location C (Figure 14). Overall, soil CO2
flux was significantly affected by the SOM of each soil location and the presence of plant
roots and microorganisms.
Figure 15. Soil organic matter (SOM) and porosity at three study locations (A, B, and C).
Soil CO2 flux measurements at 0 °C (CJ) across different SOM values indicate that soil
CO2 flux increased exponentially with an increase in SOM (Figure 16). For example, the
soil CO2 flux was 0.128 μmol.m2.s1 at a SOM of 0.036 at Location C, but showed an ap-
proximately four-fold increase at Location A and an almost fourteen-fold increase at Lo-
cation B with values of 0.082 and 0.173, respectively. Overall, the larger the amount of
SOM in the soil, the larger the soil CO2 flux.
Figure 14.
Comparison of the relationship between CO
2
flux from soil (J) and soil temperature (T) at
Location A (Dec 1, 2016 to Nov 26, 2017), B (Nov 1, to Dec 9, 2018), and C (Oct 25, to Nov, 2018).
Based on the results from Figure 14, the following three equations were obtained:
For Location A : JMax =0.487e0.099T(11)
For Location B : JMax =1.76e0.099T(12)
For Location C : JMax =0.128e0.099T(13)
where J
Max
(
µ
mol
·
m
2·
s
1
) is the soil CO
2
flux from the soil surface, and T(
C) represents
soil temperature.
C2021,7, 34 14 of 18
To investigate the difference in soil CO
2
flux between the three study area locations,
porosity and SOM were examined as characteristics related to soil CO
2
flux (Figure 15).
Our results indicate that Location B, covered with living grasses, had the highest SOM
value of 0.173, while a SOM of 0.082 was measured at Location A, and the lowest SOM
value of 0.036 was measured at Location C, which was covered with pebbles.
C 2021, 7, x FOR PEER REVIEW 14 of 17
Figure 14. Comparison of the relationship between CO2 flux from soil (J) and soil temperature (T)
at Location A (Dec 1, 2016 to Nov 26, 2017), B (Nov 1, to Dec 9, 2018), and C (Oct 25, to Nov, 2018).
To investigate the difference in soil CO2 flux between the three study area locations,
porosity and SOM were examined as characteristics related to soil CO2 flux (Figure 15).
Our results indicate that Location B, covered with living grasses, had the highest SOM
value of 0.173, while a SOM of 0.082 was measured at Location A, and the lowest SOM
value of 0.036 was measured at Location C, which was covered with pebbles.
Furthermore, the larger the SOM, the larger the fluctuation range of soil CO2 flux at
the same soil temperature. For example, at a temperature of 16 °C, the soil CO2 flux ranged
from 0.910 to 2.583 μmol.m2.s1 and from 3.833 to 6.695 μmol.m2.s1 at Locations A and B,
respectively, while less than 0.311 μmol.m2.s1 at Location C (Figure 14). Overall, soil CO2
flux was significantly affected by the SOM of each soil location and the presence of plant
roots and microorganisms.
Figure 15. Soil organic matter (SOM) and porosity at three study locations (A, B, and C).
Soil CO2 flux measurements at 0 °C (CJ) across different SOM values indicate that soil
CO2 flux increased exponentially with an increase in SOM (Figure 16). For example, the
soil CO2 flux was 0.128 μmol.m2.s1 at a SOM of 0.036 at Location C, but showed an ap-
proximately four-fold increase at Location A and an almost fourteen-fold increase at Lo-
cation B with values of 0.082 and 0.173, respectively. Overall, the larger the amount of
SOM in the soil, the larger the soil CO2 flux.
Figure 15. Soil organic matter (SOM) and porosity at three study locations (A, B, and C).
Furthermore, the larger the SOM, the larger the fluctuation range of soil CO
2
flux at
the same soil temperature. For example, at a temperature of 16
C, the soil CO
2
flux ranged
from 0.910 to 2.583
µ
mol
·
m
2·
s
1
and from 3.833 to 6.695
µ
mol
·
m
2·
s
1
at Locations A
and B, respectively, while less than 0.311
µ
mol
·
m
2·
s
1
at Location C (Figure 14). Overall,
soil CO
2
flux was significantly affected by the SOM of each soil location and the presence
of plant roots and microorganisms.
Soil CO
2
flux measurements at 0
C (C
J
) across different SOM values indicate that
soil CO
2
flux increased exponentially with an increase in SOM (Figure 16). For example,
the soil CO
2
flux was 0.128
µ
mol
·
m
2·
s
1
at a SOM of 0.036 at Location C, but showed
an approximately four-fold increase at Location A and an almost fourteen-fold increase at
Location B with values of 0.082 and 0.173, respectively. Overall, the larger the amount of
SOM in the soil, the larger the soil CO2flux.
C 2021, 7, x FOR PEER REVIEW 15 of 17
Figure 16. Correlation between CJ and soil organic matter (SOM) at locations A, B, and C.
Figure 17. Plots of soil CO2 flux measured at Locations A, B, and C.
The correlation between soil CO2 flux and related factors can be expressed by the
following equation:
J =C
∙C
∙e
 (14)
where CJ is correlation coefficient related to SOM, Cs is the correlation coefficient related
to water saturation, T represents soil temperature,
β
is the attenuation of soil CO2 flux,
and
β
= 0.099 for all measuring locations.
The relationship between CJ and SOM can be demonstrated by Equation (15).
C= 46.27SOM+ 2.13SOM (15)
while the relationship between Cs and Sw is expressed in Equation (16).
C= −3.09S
+2.77S
+0.37 (16)
Based on Equation (14), (15), and (16), the following comprehensive equation was
developed, which includes soil temperature, water saturation, and SOM :
J =(46.27SOM
+ 2.13SOM) ∙ (−3.09S
+2.77S
+0.37)e
. (17)
This equation represents the maximum baseline for soil CO2 flux (JMax), determined
from the data collected at the INAS test field site (Figure 17). This data can be used to
Figure 16. Correlation between CJand soil organic matter (SOM) at locations A, B, and C.
C2021,7, 34 15 of 18
The correlation between soil CO
2
flux and related factors can be expressed by the
following equation:
JMax =CJ·Cs·eβT(14)
where C
J
is correlation coefficient related to SOM,C
s
is the correlation coefficient related to
water saturation, Trepresents soil temperature,
β
is the attenuation of soil CO
2
flux, and
β= 0.099 for all measuring locations.
The relationship between CJand SOM can be demonstrated by Equation (15).
CJ=46.27SOM2+2.13SOM (15)
while the relationship between Csand Swis expressed in Equation (16).
Cs=3.09S2
w+2.77Sw+0.37 (16)
Based on Equations (14)–(16), the following comprehensive equation was developed,
which includes soil temperature, water saturation, and SOM:
JMax =46.27SOM2+2.13SOM·3.09S2
w+2.77Sw+0.37e0.099T(17)
This equation represents the maximum baseline for soil CO
2
flux (J
Max
), determined
from the data collected at the INAS test field site (Figure 17). This data can be used to
identify CO
2
gas leakages from CCS onshore sites. The threshold line represents the soil
CO
2
flux across different soil temperatures under normal conditions for the INAS field site.
Hence, a CO
2
flux value above the limit determined from the threshold line indicates that
a CO
2
leakage has occurred through natural fractures or tectonic faults and wide-range
monitoring should be implemented to localize leakage areas on the soil surface.
C 2021, 7, x FOR PEER REVIEW 15 of 17
Figure 16. Correlation between CJ and soil organic matter (SOM) at locations A, B, and C.
Figure 17. Plots of soil CO2 flux measured at Locations A, B, and C.
The correlation between soil CO2 flux and related factors can be expressed by the
following equation:
J =C
∙C
∙e
 (14)
where CJ is correlation coefficient related to SOM, Cs is the correlation coefficient related
to water saturation, T represents soil temperature,
β
is the attenuation of soil CO2 flux,
and
β
= 0.099 for all measuring locations.
The relationship between CJ and SOM can be demonstrated by Equation (15).
C= 46.27SOM+ 2.13SOM (15)
while the relationship between Cs and Sw is expressed in Equation (16).
C= −3.09S
+2.77S
+0.37 (16)
Based on Equation (14), (15), and (16), the following comprehensive equation was
developed, which includes soil temperature, water saturation, and SOM :
J =(46.27SOM
+ 2.13SOM) ∙ (−3.09S
+2.77S
+0.37)e
. (17)
This equation represents the maximum baseline for soil CO2 flux (JMax), determined
from the data collected at the INAS test field site (Figure 17). This data can be used to
Figure 17. Plots of soil CO2flux measured at Locations A, B, and C.
4. Conclusions
Our investigations and field measurements at the INAS test field, Kyushu University
(Japan) have been carried out. To summarize our results, we highlight the following
significant points:
The threshold line for geologic CO
2
storage site is estimated and expressed by the
following equation:
JMax =46.27SOM2+2.13SOM·3.09S2
w+2.77Sw+0.37e0.099T
C2021,7, 34 16 of 18
Soil CO
2
flux is tightly correlated to soil temperature, soil water, and SOM. There-
fore, these parameters must be considered before setting out the alert condition at CO
2
storage sites.
The threshold line can be used for the early detection of CO
2
leakage from the CO
2
storage sites based on the proposed equation for the INAS field. Once abnormal CO
2
flux from soil surface is detected, it is necessary to take remedial action in the case that
leakage occurs.
We suggest that future work focuses on the construction of a robust and reliable soil
CO
2
flux monitoring system using an independent power supply such as solar or wind
energy. By using this system, soil CO
2
flux can be monitored at all sites, regardless of
local conditions.
Author Contributions:
Conceptualization, K.S., P.Q.H. and T.K.; methodology, K.S. and S.S.; valida-
tion, K.S., S.S. and P.Q.H.; formal analysis, T.K.; investigation, T.K.; resources, T.K.; data curation,
P.Q.H.; writing—original draft preparation, P.Q.H.; writing—review and editing, K.S., P.Q.H.; visual-
ization, P.Q.H.; supervision, K.S.; funding acquisition, K.S. All authors have read and agreed to the
published version of the manuscript.
Funding: This research was partly funded by JSPS KAKENHI, grant number 20H02684.
Conflicts of Interest: The authors declare no conflict of interest.
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Short Biography of Authors
1
AUTHORS BIOGRAPHY
Kyuro Sasaki is a professor of the Department of Earth Resources
Engineering, Faculty of Engineering, Kyushu University, Japan since 2005.
He had taught Akita University for 20 years and moved to Kyushu University
engaging education on mining and petroleum engineering. He holds BS, MS
and PhD degrees from Hokkaido University, Japan. His research interests are
mineral resources production, fluid mechanics and heat & mass transfer
phenomena in mining and petroleum productions. He has published papers
on Mine Ventilation, Open-pit Optimization, SAGD, Methane hydrate
production, Enhanced coal bed methane recovery, Enhanced oil recovery,
CO2 Geological Storage, Spontaneous combustion of coal and Natural soil
CO2 emission. He is recently proposing the carbon reverse engineering
contributing mitigating CO2 emission by the geological CO2 storage, and CO2
and CH4 gas monitoring system to check their leakages from underground to
the surface.
Takashi Kuriyama has achieved BS and MS degrees in Earth Resources
Engineering, Faculty of Engineering, Kyushu University, Japan.
After the graduation, he joined Japan Oil, Gas and Metals National
Corporation (JOGMEC) as a reservoir engineer from April, 2019.
He is currently working in the Carbon Capture and Storage (CCS) department
to design and research CCS, mainly focusing on CO2 migration and trap
mechanisms.
Salmawati is a consultant in the fields of energy, mining and the environment.
She holds a B.S and M.S from Bandung Institute of Technology, West Java,
Indonesia, and PhD from Kyushu University, Fukuoka, Japan. Currently, she
is working at PT Tura Consulting Indonesia, an integrated mining and energy
consultant in Indonesia as mining environment and green energy specialist.
She is also engaged with The World Bank Group in Jakarta, Indonesia, for
the projects of Natural Resources for Sustainable Development (NR4D) and
Climate Smart Mining Initiatives for preparing the Indonesia Climate Smart
Mining Roadmap.
Phung Quoc Huy was a research associate of the Department of Earth
Resources Engineering, Faculty of Engineering, Kyushu University, Japan,
until March 2021. Currently, he is working for the Asia Pacific Energy
Research Center, Japan as a senior researcher. He holds B.S from Hanoi
University of Mining and Geology (Vietnam), M.S and PhD from Kyushu
University (Japan).
He started work as a researcher at the Institute of Mining Science and
Technology (Vietnam) from 1999 to 2019. He participated in various research
projects related to methane gas emission, mine ventilation, coal mine gas
explosion, spontaneous combustion, risk management and assessment,
mine safety, CO2 emission, greenhouse gases, CO2 sequestration.
He is currently interested in energy demand and supply, energy policies and
Carbon Capture, Utilization and Storage technology (CCUS), CO2 emission
monitoring.
Kyuro Sasaki is a professor of the Department of Earth Resources Engineering, Faculty of
Engineering, Kyushu University, Japan since 2005. He had taught Akita University for 20 years and
moved to Kyushu University engaging education on mining and petroleum engineering. He holds
BS, MS and PhD degrees from Hokkaido University, Japan. His research interests are mineral
resources production, fluid mechanics and heat & mass transfer phenomena in mining and petroleum
productions. He has published papers on Mine Ventilation, Open-pit Optimization, SAGD, Methane
hydrate production, Enhanced coal bed methane recovery, Enhanced oil recovery, CO2Geological
Storage, Spontaneous combustion of coal and Natural soil CO2emission. He is recently proposing
the carbon reverse engineering contributing mitigating CO
2
emission by the geological CO
2
storage,
and CO2and CH4gas monitoring system to check their leakages from underground to the surface.
1
AUTHORS BIOGRAPHY
Kyuro Sasaki is a professor of the Department of Earth Resources
Engineering, Faculty of Engineering, Kyushu University, Japan since 2005.
He had taught Akita University for 20 years and moved to Kyushu University
engaging education on mining and petroleum engineering. He holds BS, MS
and PhD degrees from Hokkaido University, Japan. His research interests are
mineral resources production, fluid mechanics and heat & mass transfer
phenomena in mining and petroleum productions. He has published papers
on Mine Ventilation, Open-pit Optimization, SAGD, Methane hydrate
production, Enhanced coal bed methane recovery, Enhanced oil recovery,
CO2 Geological Storage, Spontaneous combustion of coal and Natural soil
CO2 emission. He is recently proposing the carbon reverse engineering
contributing mitigating CO2 emission by the geological CO2 storage, and CO2
and CH4 gas monitoring system to check their leakages from underground to
the surface.
Takashi Kuriyama has achieved BS and MS degrees in Earth Resources
Engineering, Faculty of Engineering, Kyushu University, Japan.
After the graduation, he joined Japan Oil, Gas and Metals National
Corporation (JOGMEC) as a reservoir engineer from April, 2019.
He is currently working in the Carbon Capture and Storage (CCS) department
to design and research CCS, mainly focusing on CO2 migration and trap
mechanisms.
Salmawati is a consultant in the fields of energy, mining and the environment.
She holds a B.S and M.S from Bandung Institute of Technology, West Java,
Indonesia, and PhD from Kyushu University, Fukuoka, Japan. Currently, she
is working at PT Tura Consulting Indonesia, an integrated mining and energy
consultant in Indonesia as mining environment and green energy specialist.
She is also engaged with The World Bank Group in Jakarta, Indonesia, for
the projects of Natural Resources for Sustainable Development (NR4D) and
Climate Smart Mining Initiatives for preparing the Indonesia Climate Smart
Mining Roadmap.
Phung Quoc Huy was a research associate of the Department of Earth
Resources Engineering, Faculty of Engineering, Kyushu University, Japan,
until March 2021. Currently, he is working for the Asia Pacific Energy
Research Center, Japan as a senior researcher. He holds B.S from Hanoi
University of Mining and Geology (Vietnam), M.S and PhD from Kyushu
University (Japan).
He started work as a researcher at the Institute of Mining Science and
Technology (Vietnam) from 1999 to 2019. He participated in various research
projects related to methane gas emission, mine ventilation, coal mine gas
explosion, spontaneous combustion, risk management and assessment,
mine safety, CO2 emission, greenhouse gases, CO2 sequestration.
He is currently interested in energy demand and supply, energy policies and
Carbon Capture, Utilization and Storage technology (CCUS), CO2 emission
monitoring.
Takashi Kuriyama has achieved BS and MS degrees in Earth Resources Engineering, Faculty of
Engineering, Kyushu University, Japan.After the graduation, he joined Japan Oil, Gas and Metals
National Corporation (JOGMEC) as a reservoir engineer from April, 2019. He is currently working in
the Carbon Capture and Storage (CCS) department to design and research CCS, mainly focusing on
CO2migration and trap mechanisms.
C2021,7, 34 18 of 18
1
AUTHORS BIOGRAPHY
Kyuro Sasaki is a professor of the Department of Earth Resources
Engineering, Faculty of Engineering, Kyushu University, Japan since 2005.
He had taught Akita University for 20 years and moved to Kyushu University
engaging education on mining and petroleum engineering. He holds BS, MS
and PhD degrees from Hokkaido University, Japan. His research interests are
mineral resources production, fluid mechanics and heat & mass transfer
phenomena in mining and petroleum productions. He has published papers
on Mine Ventilation, Open-pit Optimization, SAGD, Methane hydrate
production, Enhanced coal bed methane recovery, Enhanced oil recovery,
CO2 Geological Storage, Spontaneous combustion of coal and Natural soil
CO2 emission. He is recently proposing the carbon reverse engineering
contributing mitigating CO2 emission by the geological CO2 storage, and CO2
and CH4 gas monitoring system to check their leakages from underground to
the surface.
Takashi Kuriyama has achieved BS and MS degrees in Earth Resources
Engineering, Faculty of Engineering, Kyushu University, Japan.
After the graduation, he joined Japan Oil, Gas and Metals National
Corporation (JOGMEC) as a reservoir engineer from April, 2019.
He is currently working in the Carbon Capture and Storage (CCS) department
to design and research CCS, mainly focusing on CO2 migration and trap
mechanisms.
Salmawati is a consultant in the fields of energy, mining and the environment.
She holds a B.S and M.S from Bandung Institute of Technology, West Java,
Indonesia, and PhD from Kyushu University, Fukuoka, Japan. Currently, she
is working at PT Tura Consulting Indonesia, an integrated mining and energy
consultant in Indonesia as mining environment and green energy specialist.
She is also engaged with The World Bank Group in Jakarta, Indonesia, for
the projects of Natural Resources for Sustainable Development (NR4D) and
Climate Smart Mining Initiatives for preparing the Indonesia Climate Smart
Mining Roadmap.
Phung Quoc Huy was a research associate of the Department of Earth
Resources Engineering, Faculty of Engineering, Kyushu University, Japan,
until March 2021. Currently, he is working for the Asia Pacific Energy
Research Center, Japan as a senior researcher. He holds B.S from Hanoi
University of Mining and Geology (Vietnam), M.S and PhD from Kyushu
University (Japan).
He started work as a researcher at the Institute of Mining Science and
Technology (Vietnam) from 1999 to 2019. He participated in various research
projects related to methane gas emission, mine ventilation, coal mine gas
explosion, spontaneous combustion, risk management and assessment,
mine safety, CO2 emission, greenhouse gases, CO2 sequestration.
He is currently interested in energy demand and supply, energy policies and
Carbon Capture, Utilization and Storage technology (CCUS), CO2 emission
monitoring.
Salmawati Salmawati
is a consultant in the fields of energy, mining and the environment. She holds
a B.S and M.S from Bandung Institute of Technology, West Java, Indonesia, and PhD from Kyushu
University, Fukuoka, Japan. Currently, she is working at PT Tura Consulting Indonesia, an integrated
mining and energy consultant in Indonesia as mining environment and green energy specialist. She
is also engaged with The World Bank Group in Jakarta, Indonesia, for the projects of Natural
Resources for Sustainable Development (NR4D) and Climate Smart Mining Initiatives for preparing
the Indonesia Climate Smart Mining Roadmap.
1
AUTHORS BIOGRAPHY
Kyuro Sasaki is a professor of the Department of Earth Resources
Engineering, Faculty of Engineering, Kyushu University, Japan since 2005.
He had taught Akita University for 20 years and moved to Kyushu University
engaging education on mining and petroleum engineering. He holds BS, MS
and PhD degrees from Hokkaido University, Japan. His research interests are
mineral resources production, fluid mechanics and heat & mass transfer
phenomena in mining and petroleum productions. He has published papers
on Mine Ventilation, Open-pit Optimization, SAGD, Methane hydrate
production, Enhanced coal bed methane recovery, Enhanced oil recovery,
CO2 Geological Storage, Spontaneous combustion of coal and Natural soil
CO2 emission. He is recently proposing the carbon reverse engineering
contributing mitigating CO2 emission by the geological CO2 storage, and CO2
and CH4 gas monitoring system to check their leakages from underground to
the surface.
Takashi Kuriyama has achieved BS and MS degrees in Earth Resources
Engineering, Faculty of Engineering, Kyushu University, Japan.
After the graduation, he joined Japan Oil, Gas and Metals National
Corporation (JOGMEC) as a reservoir engineer from April, 2019.
He is currently working in the Carbon Capture and Storage (CCS) department
to design and research CCS, mainly focusing on CO2 migration and trap
mechanisms.
Salmawati is a consultant in the fields of energy, mining and the environment.
She holds a B.S and M.S from Bandung Institute of Technology, West Java,
Indonesia, and PhD from Kyushu University, Fukuoka, Japan. Currently, she
is working at PT Tura Consulting Indonesia, an integrated mining and energy
consultant in Indonesia as mining environment and green energy specialist.
She is also engaged with The World Bank Group in Jakarta, Indonesia, for
the projects of Natural Resources for Sustainable Development (NR4D) and
Climate Smart Mining Initiatives for preparing the Indonesia Climate Smart
Mining Roadmap.
Phung Quoc Huy was a research associate of the Department of Earth
Resources Engineering, Faculty of Engineering, Kyushu University, Japan,
until March 2021. Currently, he is working for the Asia Pacific Energy
Research Center, Japan as a senior researcher. He holds B.S from Hanoi
University of Mining and Geology (Vietnam), M.S and PhD from Kyushu
University (Japan).
He started work as a researcher at the Institute of Mining Science and
Technology (Vietnam) from 1999 to 2019. He participated in various research
projects related to methane gas emission, mine ventilation, coal mine gas
explosion, spontaneous combustion, risk management and assessment,
mine safety, CO2 emission, greenhouse gases, CO2 sequestration.
He is currently interested in energy demand and supply, energy policies and
Carbon Capture, Utilization and Storage technology (CCUS), CO2 emission
monitoring.
Phung Quoc Huy was a research associate of the Department of Earth Resources Engineering,
Faculty of Engineering, Kyushu University, Japan, until March 2021. Currently, he is working for the
Asia Pacific Energy Research Center, Japan as a senior researcher. He holds B.S from Hanoi
University of Mining and Geology (Vietnam), M.S and PhD from Kyushu University (Japan). He
started work as a researcher at the Institute of Mining Science and Technology (Vietnam) from 1999 to
2019. He participated in various research projects related to methane gas emission, mine ventilation,
coal mine gas explosion, spontaneous combustion, risk management and assessment, mine safety,
CO
2
emission, greenhouse gases, CO
2
sequestration.He is currently interested in energy demand and
supply, energy policies and Carbon Capture, Utilization and Storage technology (CCUS), CO2
emission monitoring.
ResearchGate has not been able to resolve any citations for this publication.
Article
Full-text available
Globally, soils store two to three times as much carbon as currently resides in the atmosphere, and it is critical to understand how soil greenhouse gas (GHG) emissions and uptake will respond to ongoing climate change. In particular, the soil-toatmosphere CO2 flux, commonly though imprecisely termed soil respiration (RS), is one of the largest carbon fluxes in the Earth system. An increasing number of highfrequency RS measurements (typically, from an automated system with hourly sampling) have been made over the last two decades; an increasing number of methane measurements are being made with such systems as well. Such high frequency data are an invaluable resource for understanding GHG fluxes, but lack a central database or repository. Here we describe the lightweight, open-source COSORE (COntinuous SOil REspiration) database and software, that focuses on automated, continuous and long-term GHG flux datasets, and is intended to serve as a community resource for earth sciences, climate change syntheses and model evaluation. Contributed datasets are mapped to a single, consistent standard, with metadata on contributors, geographic location, measurement conditions and ancillary data. The design emphasizes the importance of reproducibility, scientific transparency and open access to data. While being oriented towards continuously measured RS, the database design accommodates other soil-atmosphere measurements (e.g. ecosystem respiration, chamber-measured net ecosystem exchange, methane fluxes) as well as experimental treatments (heterotrophic only, etc.). We give brief examples of the types of analyses possible using this new community resource and describe its accompanying R software package.
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Following the drilling of a shallow natural CO2 reservoir at the Qinghai research site, west of Haidong, China, it was discovered that CO2 was continuously leaking from the wellbore due to well-failure. The site has become a useful research facility in China for studying CO2 leakage and monitoring technologies for application to geological storage sites of CO2. During an eight day period in 2014, soil gas and soil flux surveys were conducted to characterise the distribution, magnitude and likely source of the leaking CO2.
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Legislation and guidelines developed for Carbon Capture and Storage (CCS) have set performance requirements to minimize leakage risk, and to quantify and remediate any leaks that arise. For compliance it is necessary to have a comprehensive understanding of the possible spread, fate and impacts of any leaked CO2, and the ability to detect and quantify any CO2 seepage into marine or terrestrial environments. Over the past decade, a number of field scale CO2 release experiments have been conducted around the world to address many of the uncertainties regarding the characteristics of near-surface expression of CO2 in terms of the impact and quantitation of CO2 leaks. In these experiments, either free phase or dissolved CO2 was injected and released into the shallow subsurface so as to artificially simulate a CO2 leak into the near-surface environment. The experiments differ in a number of ways, from the geological conditions, surface environments, injection rates and experimental set-up - including the injection and monitoring strategy. These experiments have provided abundant information to aid in the development of our scientific understanding of environmental impacts of CO2 while assessing state of the art monitoring techniques. We collated a global dataset of field-scale shallow (depths < ~25 m) controlled CO2 release experiments. The dataset includes 14 different field experiment locations, of which nine intended to release CO2 to the surface, and the remaining sites intended for CO2 to remain in the shallow subsurface. Several release experiments have been conducted at half of these sites, and so in total, 41 different CO2 release tests have taken place at the 14 sites in our dataset. We scrutinized our dataset to establish: (i) the range of experimental approaches and settings explored to date (such as the environment, subsurface conditions, injection strategy and whether gaseous or dissolved CO2 were injected and in what quantities); (ii) the range of CO2 injection and surface release rates at these experiments; (iii) the collective learnings about the surface and subsurface manifestation of the CO2 release, the spread and fate of the CO2, rates of CO2 flux to surface, and methods of measuring these; (iv) the strengths and limitations of current approaches for detecting and quantifying CO2. This allowed us to highlight where uncertainties remain and identify knowledge gaps that future experiments should seek to address. Further, drawing on the collective experiences, we have identified common issues or complications which future CO2 release experiments can learn from.
Article
Carbon capture and storage (CCS) may result in negative environmental impacts if CO2 escapes into the soil layer from deep geological storage formations. In particular, little is known about the spatial scope of possible impacts of CO2 leakages. This study designed and implemented a CO2 point-source shallow release experiment to simulate CCS leakage at a rate of 1.0 L min⁻¹ and a depth of 1.5 m. The scope of crop and farmland responses to CO2 leakage were examined, with a focus on spring wheat. The experimental site had a radius of 9.0 m, and the leaked CO2 was found to influence soil CO2 concentrations up to 4.0 m from the source, or 2.67 times the depth of the leak. Furthermore, the influence radius of the CO2 leak on spring wheat height was about 1.0 m, which was 0.67 times the depth of the leak. The morphological characteristics of wheat observed directly above the leak were approximately 30–50% lower than the background levels (9.0 m from the source). CO2 leakage could therefore result in wheat field degradation along the soil surface. These findings suggest that a set of empirical parameters to assess the scope of the negative influence of CCS leakage on agriculture should be developed. Overall, the results indicate a concentric pattern of farmland and crop degradation with distance from the CCS leakage source, which may help to deepen understanding of the safety of CCS.
Article
The greenhouse effect is closely related to elevated atmospheric CO2 concentrations and therefore, carbon capture and storage (CCS) has attracted attention worldwide as a method for preventing the release of CO2 into the atmosphere, which highlights the importance of monitoring CO2 released from subsurface deposits. In this study, CO2 gas with a δ13C value of -30‰ was injected into soil through pipes installed at a depth of 2.5 m, and samples of CO2 gas released from the soil surface and three soil depths were collected from September 2015 to March 2016 to estimate subsurface CO2 movement. Before and after CO2 injection, the δ13C values of CO2 released from the soil surface ranged from -24.5 to -13.4‰ (average -20.2 ± 2.1‰, n = 25) and from -31.6 to -11.9‰ (average -23.2 ± 4.3‰, n = 49), respectively. The results indicated that the leakage of injected CO2 was successfully detected at the surface. The δ13C values were visualized using an interpolation map to estimate the subsurface CO2 distribution, which confirmed that diffusion of the injected CO2 gas extended to the soil zone where CO2 was not injected. Additionally, variation in δ13C for soil CO2 was detected at the three soil depths (15, 30, and 60 cm), where the values were -16.1, -20.0, and -22.1‰, respectively. Different δ13C values horizontally and vertically indicated that soil heterogeneity led to different CO2 migration pathways and rates. We suggest that the carbon isotope ratio of CO2 is an effective tool for concurrently monitoring CO2 leakage on and under surface in a soil zone if a thorough baseline study is carried out in the field.
Article
We outline the methodology for detection of carbon dioxide (CO2) leaks to the atmosphere from carbon capture and storage (CCS) using measurements of radiocarbon in CO2. The radiocarbon method can unambiguously identify recently added fossil-derived CO2 such as CCS leaks due to the very large isotopic difference between radiocarbon-free fossil derived CO2 and natural CO2 sources with ambient radiocarbon levels. The detection threshold of 1 ppm of fossil-derived CO2 is comparable to other proposed atmospheric detection methods for CCS leakage. We demonstrate that this method will allow detection of a 1000 ton C yr⁻¹ leak 200–300 m from the source during the day and more than 600 m away at night. Using time-integrated sampling techniques, long time periods can be covered with few measurements, making the method feasible with existing laboratory-based radiocarbon measurement methods We examine the method using previously published observations and new model simulations for a case study in Taranaki, New Zealand. Plant material faithfully records the radiocarbon content of assimilated CO2 and we show that short-lived grass leaves and cellulose from tree rings provide effective time-integrated collection methods, allowing dense spatial sampling at low cost. A CO2 absorption sampler allows collection at controlled times, including nighttime, and gives similar results.