Technical Note: Cost-efficient approaches to measure carbon dioxide (CO2) fluxes and

Technical Note: Cost-efficient approaches to measure carbon dioxide (CO2) fluxes and
Technical Note: Cost-efficient approaches to
measure carbon dioxide (CO2) fluxes and
concentrations in terrestrial and aquatic
environments using mini loggers
David Bastviken, Ingrid Sundgren, Sivakiruthika Natchimuthu, Henrik Reyier and Magnus
Gålfalk
Linköping University Post Print
N.B.: When citing this work, cite the original article.
Original Publication:
David Bastviken, Ingrid Sundgren, Sivakiruthika Natchimuthu, Henrik Reyier and Magnus
Gålfalk, Technical Note: Cost-efficient approaches to measure carbon dioxide (CO2) fluxes
and concentrations in terrestrial and aquatic environments using mini loggers, 2015,
Biogeosciences, (12), 12, 3849-3859.
http://dx.doi.org/10.5194/bg-12-3849-2015
Copyright: European Geosciences Union (EGU) / Copernicus Publications
http://www.egu.eu/
Postprint available at: Linköping University Electronic Press
http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-120295
Biogeosciences, 12, 3849–3859, 2015
www.biogeosciences.net/12/3849/2015/
doi:10.5194/bg-12-3849-2015
© Author(s) 2015. CC Attribution 3.0 License.
Technical Note: Cost-efficient approaches to measure carbon
dioxide (CO2) fluxes and concentrations in terrestrial and
aquatic environments using mini loggers
D. Bastviken, I. Sundgren, S. Natchimuthu, H. Reyier, and M. Gålfalk
Department of Thematic Studies – Environmental Change, Linköping University, Linköping, Sweden
Correspondence to: D. Bastviken ([email protected])
Received: 15 December 2014 – Published in Biogeosciences Discuss.: 4 February 2015
Revised: 31 May 2015 – Accepted: 1 June 2015 – Published: 24 June 2015
Abstract. Fluxes of CO2 are important for our understanding
of the global carbon cycle and greenhouse gas balances. Several significant CO2 fluxes in nature may still be unknown
as illustrated by recent findings of high CO2 emissions from
aquatic environments, previously not recognized in global
carbon balances. Therefore, it is important to develop convenient and affordable ways to measure CO2 in many types of
environments. At present, direct measurements of CO2 fluxes
from soil or water, or CO2 concentrations in surface water,
are typically labor intensive or require costly equipment. We
here present an approach with measurement units based on
small inexpensive CO2 loggers, originally made for indoor
air quality monitoring, that were tested and adapted for field
use. Measurements of soil–atmosphere and lake–atmosphere
fluxes, as well as of spatiotemporal dynamics of water CO2
concentrations (expressed as the equivalent partial pressure,
pCO2aq ) in lakes and a stream network are provided as examples. Results from all these examples indicate that this
approach can provide a cost- and labor-efficient alternative
for direct measurements and monitoring of CO2 flux and
pCO2aq in terrestrial and aquatic environments.
1
Introduction
The carbon dioxide (CO2 ) exchange across soil–atmosphere
or water–atmosphere interfaces is of fundamental importance
for the global carbon cycle. Soil respiration returns substantial amounts of the carbon fixed by plants to the atmosphere
and contributes to the net ecosystem exchange of carbon
(Denman et al., 2007). Inland waters, including lakes, reser-
voirs, and rivers/streams, are often showing a net emission of
CO2 from degradation or weathering processes in surrounding soils, sediments, and water columns (Aufdenkampe et
al., 2011; Battin et al., 2009). The inland water emissions
have been estimated to be 2.1 Pg yr−1 (Raymond et al., 2013)
which is in the same order of magnitude as the estimated land
carbon sink (2.6 Pg yr−1 ; Denman et al., 2007).
Direct measurements of CO2 fluxes across the soil–
atmosphere and water–atmosphere surface often rely on flux
chamber (FC) measurements, representing a conceptually
straightforward technique where the system in focus is covered by a chamber, and the change in CO2 over time in the
chamber headspace is used to calculate the flux (Davidson et
al., 2002). Because of the heating inside soil chambers, and
potentially rapid equilibration of the chamber headspace for
chambers on water, it is usually recommended to use shortterm deployments with repeated samplings during each deployment (e.g., sampling every fifth minute for 30 min). For
replicated and robust measurements, it is also recommended
to perform repeated deployments over extended periods. At
the same time it is necessary to have multiple measurement
units to account for spatial variability. Therefore, measurements accounting for both spatial and temporal variability
tend to be laborious if relying on manual sampling or costly
in terms of equipment if automated chamber systems are
used.
Because direct flux measurements are time consuming,
simpler alternatives have been tried. For aquatic environments, the CO2 flux is often estimated from surface water
concentrations (usually expressed as equivalent partial pressure of CO2 according to Henry’s law; pCO2aq ) and the pis-
Published by Copernicus Publications on behalf of the European Geosciences Union.
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D. Bastviken et al.: Cost-efficient approaches to measure carbon dioxide (CO2 ) fluxes
ton velocity (k) according to
F = k · KH · (pCO2aq − pCO2air ),
(1)
where F is the flux between the water and the atmosphere
(e.g., mol m−2 d−1 ), k is the piston velocity (e.g., m d−1 ;
linked to the water turbulence and can be seen as the
part of the water column exchanging gas with the atmosphere per time unit), KH is the Henry’s law constant (e.g.,
mol m−3 atm−1 ), and pCO2air is the partial pressure of CO2
in the air above the water surface (pCO2aq and pCO2air in
units of atm; Liss and Slater, 1974). Several ways to estimate k from, e.g., wind speed, and various ways to measure
water turbulence (for water bodies) or slope (for running waters) have been used (Abril et al., 2009; Cole and Caraco,
1998; Gålfalk et al., 2013; Raymond et al., 2013; Wallin et
al., 2011), but although models may work well in the systems
where they were developed, extrapolations to other systems
are uncertain (Borges et al., 2004; Schilder et al., 2013; Wanninkhof, 1992).
pCO2aq is typically either estimated from pH and alkalinity or measured directly. The estimation of pCO2aq from pH
and alkalinity measurements is most common because of the
large amounts of pH and alkalinity data available from national monitoring measurements (Raymond et al., 2013), but
such indirect pCO2aq estimation becomes unreliable at low
alkalinity, at pH below 6, or at high levels of organic acids
(e.g., in humic waters), so direct measurements are preferable
(Abril et al., 2015; Hunt et al., 2011). Therefore, direct measurements of fluxes and pCO2aq are needed to constrain the
present estimates of CO2 fluxes (Abril et al., 2015). It should
also be noted that pCO2aq is not solely used for flux calculations – it is a useful variable in itself for biogeochemical
studies of aquatic ecosystems, e.g., in assessments of ecosystem carbon metabolism.
The most common way to directly measure pCO2aq manually is by filling a large bottle (1–2 L) completely with water, thereafter introducing a small headspace which is equilibrated with the water by shaking, and then the headspace
CO2 concentration is measured (Cole et al., 1994). Considering both indirect and direct approaches, there are presently
data from approximately 7900 water bodies and 6700 running water locations (Raymond et al., 2013). However, these
values typically represent snapshots in time for each system
as monitoring of temporal dynamics is demanding in terms
of time or equipment. Daytime measurements predominate
in spite of expectations of higher pCO2aq during night when
respiration dominates over photosynthesis in many types of
systems.
Due to the importance of CO2 fluxes and concentrations,
and the need to cover temporal variability, a number of automated techniques have been developed. Apart from the
eddy covariance technique for large-scale net fluxes, commercial automated flux chamber systems to measure CO2
flux from soil environments are available (e.g., www.li-cor.
com). For pCO2aq , an increasing number of commercial
Biogeosciences, 12, 3849–3859, 2015
systems have recently become available (e.g., SAMI-CO2,
http://sunburstsensors.com, measures CO2 indirectly via pH
measurements in a reagent solution; Pro-Oceanus Mini-Pro
CO2 , http://www.pro-oceanus.com; Contros HydroC-CO2 ,
http://www.contros.eu). The costly components in those systems are typically the instrumentation to measure and log
CO2 levels. For monitoring pCO2aq , recent method developments have demonstrated the possibility of using a nearinfrared CO2 gas sensor (e.g., VAISALA GMT220) under
water by protecting it with a waterproof but gas-permeable
membrane (Johnson et al., 2010). This technique is seeing increased use, which represents important progress, although it
is relatively expensive (considering both the CO2 sensor and
the separate logger unit needed) and power demanding (requiring large and heavy batteries for long-term remote use).
Recently, flow-through equilibrators have become increasingly used for pCO2aq measurements in various designs allowing remote or long-term use (e.g., Abril et al., 2015, 2006;
Sutton et al., 2014). Water and air are pumped through the
equilibrator system and in some designs the gas is exchanged
across a membrane surface while other types of equilibrators are based on rapid direct gas exchange to an equilibrator
headspace by, e.g., purging (Santos et al., 2012). A related
approach is to pump air through gas-permeable tubing in the
water (Hari et al., 2008). The air can be sampled by syringe
or circulated through an external infrared gas analyzer.
The high cost of measuring equipment means that only a
few measurement units are affordable for simultaneous use,
and thereby information on spatial variability is sacrificed.
This is a severe limitation for constraining present estimates
of CO2 exchange across land or water surfaces and the atmosphere. Having low-cost equipment that could measure this
exchange over time at multiple well-constrained locations
would be highly valuable. The aim of this study was to test if
low-cost CO2 loggers developed for, e.g., monitoring indoor
air quality and regulate ventilation in buildings, could also
be used efficiently in environmental research. These types
of sensors typically do not have the same high performance
and sensitivity as present commercial instruments for CO2
measurements in environmental science (e.g., by companies
such as Los Gatos Research, Picarro, LI-COR, PP Systems,
and Quantek Instruments). However, if they are shown to be
good enough for some environmental applications, the lower
cost (allowing for simultaneous deployment of a large number of measurement units) will make such loggers highly advantageous.
We here present approaches to measure CO2 fluxes and
concentrations in nature using a small CO2 logger that is positioned inside a chamber headspace. The cost of this type
of CO2 logger system is estimated to be < 1–20 % of the alternative systems presently available and used for environmental studies. Apart from testing logger performance under
different environmental conditions, we provide examples of
the following types of measurements:
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D. Bastviken et al.: Cost-efficient approaches to measure carbon dioxide (CO2 ) fluxes
– fluxes between soil and atmosphere
– fluxes between lake surface water and the atmosphere
– Measurements of surface water concentrations
(pCO2aq ) by monitoring CO2 in the headspace of
floating chambers in which the headspace CO2 concentration was allowed to be equilibrated with the
water. This represents a new type of in situ pCO2aq
measurement, supplementing the previous approaches
using submerged sensors or equilibrators. By measuring
CO2 in a headspace, biofilm formation on the sensor,
which is a common problem for all sensors in contact
with water, can be avoided. These types of pCO2aq
measurements were illustrated by measurements in a
lake and in a stream network.
We also provide detailed information on how to prepare loggers and on how to use them under different conditions in the
Supplement.
2
Material and methods
2.1
Logger description
We used the ELG CO2 logger made by SenseAir. It was chosen because of promising specifications, including the following:
– CO2 detection by non-dispersive infrared (NDIR) spectroscopy over a guaranteed range of 0–5000 ppm (we
discovered an actual linear range of 0–10 000 ppm; see
below)
– simultaneous logging of CO2 , temperature, and relative
humidity
– operating temperature range of 0–50 ◦ C
temperature-compensated CO2 values
with
– full function at high humidity – 0–99 % (noncondensing conditions)
– includes an internal logger (5400 logging events), and
adjustable measurement intervals from 30 s to 0.5 years
– operating at 5.5–12 VDC (a small standard 9 V battery
worked fine for extended periods as long as the battery
voltage is above 7.5 V) and has low power consumption
(depending on the measurement frequency, ∼ 250 µA if
one measurement h−1 , ∼ 50 µA in sleep, ∼ 60 mA average during active measurement sequence (∼ 12s), see
detailed information at www.senseair.com)
– quick and easy calibration by the user (see Supplement)
– freely available user-friendly software for sensor control
and data management (see the Supplement)
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– easily available documentation allowing supplementary
modifications of the sensor for field use
– possibility to control one peripheral device connected to
the logger (e.g., a pump)
More technical specifications and sensor documentation are
available at the manufacturer’s web page (www.senseair.se).
2.2
Sensor modification for field use and initial
calibration
The loggers are sold as electrical board modules that are vulnerable to corrosion and do not have suitable connections for
power supply, data communication, and calibration. Therefore, modifications for field use were required. First, suitable
connectors (power cable, data communication cable, pins for
calibration start/stop jumper, and pins for manual start/stop
of logging using a jumper) were soldered onto the board. A
UART data communication cable was also made. Thereafter
all parts of the board, except the connector pins, the temperature and RH sensors, and the CO2 sensor membrane surface,
were covered with several layers of varnish for moisture protection. A detailed description on how to make this is available in the Supplement.
The loggers were connected to power (individual 9 V batteries for each logger) and calibrated batch-wise in N2 (representing zero CO2 gas) by connecting the calibration pins according to the manufacturer’s instructions (zero calibration).
Calibration is made repeatedly as long as the jumpers are
connected with improved results over time. Our typical procedure was to run the zero calibration for approximately 3 h.
Alternative ways of calibration are also possible as described
in the Supplement, and were used when zero calibration was
not possible (e.g., in the field).
2.3
Sensor performance tests
Adequate sensor performance is a prerequisite for successful
field use. Therefore we first performed tests of the calibration
and linear measurement range (described below), and tests of
the influence of temperature and humidity on the measurements (explained in detail in the Supplement).
2.3.1
Test of calibration and linear measurement range
After calibration, each sensor was tested by being set to log
concentrations over time in a gas-tight box connected to a
Los Gatos Research greenhouse gas analyzer (LGR; DLT100) so that the gas in the box with the batch of CO2 loggers was continuously circulated through the LGR instrument. CO2 levels in the box were changed over time either
by injection of standard gases, or simply by breathing into the
box to increase concentrations, or by putting an active plant
in the box to reduce CO2 concentrations over time (by photosynthesis). In this way, the response of the loggers and the
Biogeosciences, 12, 3849–3859, 2015
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D. Bastviken et al.: Cost-efficient approaches to measure carbon dioxide (CO2 ) fluxes
LGR to CO2 levels ranging from 200 to 10 000 ppmv could
be compared.
2.4
Field measurements
Three types of field measurements were tried and are presented here as examples of how the loggers can be used:
(1) flux measurements from soil, (2) flux measurements from
water, and (3) measurements of CO2 concentration in water
(pCO2aq ). The flux measurements were based on monitoring of concentration changes over time with loggers placed
in static flux chambers. The pCO2aq measurements were
also performed by measuring CO2 concentrations inside a
chamber allowing the chamber headspace to reach equilibrium with the water, thereby making headspace CO2 concentrations reflect surface water concentrations according to
Henry’s law.
For all these measurements, the chambers used were made
of plastic buckets (7.5 L volume, 30 cm diameter) covered
with reflective alumina tape to minimize internal heating.
This type of chamber has been shown to provide unbiased
measurements of the water–atmosphere gas exchange (Cole
et al., 2010; Gålfalk et al., 2013). The CO2 loggers were
attached inside the chamber as shown in the Supplement
(Fig. S5 in the Supplement). The battery was protected by
a gas-tight plastic box. For the soil measurements, the logger was left uncovered in the chamber, but for measurements
over the water, protection against direct water splash as well
as condensation was needed. We tried the simplest possible
approach by covering the sensor with a plastic box with multiple 7 mm diameter holes drilled on one side to allow for
the exchange of air (see Fig. S6). The air was forced to pass
over plastic plate in the box before reaching the logger to
make some of the expected condensation occur on the plastic
plate instead of on the sensor itself. This way of protecting
the sensor from condensation and splashing water could potentially delay the response time if the air exchange between
the chamber headspace and the box is restricted, but a test
described in the Supplement showed that this was not the
case in our type of measurements. The routines used for calibration and measurement validation, including taking manual samples to check for potential sensor drift over time, are
described in the Supplement.
2.4.1
Soil CO2 flux measurements
The soil flux measurements represented a simple test of
logger suitability. The chambers were put gently onto nonvegetated hardwood forest soil and the risk for extensive
lateral gas leakage was reduced by packing soil against the
outer walls of the chamber. This procedure does not follow
common recommendations regarding soils chambers (e.g.,
having pre-installed frames going into the soils) but shows
when the loggers, per se, are suitable for soil flux measurements regardless of what type of chamber is used. As traBiogeosciences, 12, 3849–3859, 2015
ditional flux measurements in soil chambers can be biased
by the gas sampling (which can induce pressure changes in
the chamber disturbing the gas concentration gradients in the
soil; Davidson et al., 2002), it is also favorable to have a logger inside the chambers eliminating the need for gas sampling during the flux measurement period. The headspace
CO2 concentrations were logged over time at 2 min intervals throughout measurement periods of 40 min. The change
in headspace CO2 content over time was calculated by the
common gas law considering chamber volume and area, and
represented the measured fluxes. In our tests, new measurement periods were started by simply lifting the chamber for
a few minutes to vent the headspace and then replacing the
chamber onto the soil.
2.4.2
Aquatic CO2 flux measurements
For aquatic flux measurements, floating chambers were put
on a small boreal forest lake. In the examples presented here,
CO2 fluxes during morning and evening were measured over
4 days. The logger unit was started indoors before going to
the lake and measurements were made every sixth minute
throughout the whole 4-day period. Fluxes were calculated
from the change in CO2 content over time in the chamber headspace. To start a new measurement, the chamber
was lifted, vented for 5 min, and then replaced on the water.
This venting procedure was undertaken in the morning and
evening, generating two flux estimates per day valid for the
period right after venting and restarting the measurements.
After the 4-day period, the chambers were taken from the
lake and data were downloaded from the logger when back
in the laboratory. We also performed additional flux measurements on a pond at the Linköping University Campus using
both data from the CO2 logger inside a chamber, and from
manual samples taken by syringe from the same chamber
which were analyzed by gas chromatography. This comparison was made to verify that the change in headspace CO2
content over time measured with loggers corresponded to traditional manual measurements.
2.4.3
Surface water pCO2aq measurements
Our pCO2aq measurements are based on the principle that
after a floating chamber headspace has equilibrated with the
water, the measured partial pressure of CO2 in the chamber
headspace will represent this surface water pCO2aq . In this
way pCO2aq can be measured in a chamber headspace without any submerged sensors being at risk of damage from water intrusions or resulting in bias from biofilms on the submerged sensor surface. On the other hand, the pCO2aq response in a chamber headspace will be delayed due to the
equilibration time which will depend on the piston velocity
(k) and chamber dimensions. The response time can potentially be shortened by mixing of the headspace or the surface
water under the chamber by installing fans or by pumping.
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D. Bastviken et al.: Cost-efficient approaches to measure carbon dioxide (CO2 ) fluxes
3853
©Lantmäteriet
Figure 1. Map indicating the locations of the chambers on lake
Tämnaren. The map is published with permission from Lantmäteriet, Sweden, according to agreement i2012/898 with Linköping
University.
We evaluated the effect of equilibration time during a diel
measurement cycle with and without fans and pumps (no notable effect observed) and performed additional modeling accounting for a greater range of k values and testing effects of
reducing the chamber volume to area ratio. A comparison between pCO2aq from instantaneous chamber headspace measurements and bottle headspace extractions were also made.
The details of the evaluation and comparison are presented
in detail in the Results and discussion section below and in
the Supplement. Based on the outcome we here focused on
exploring the use of the pCO2aq chamber units further without any fans/pumps because we wanted to first try the simplest and most power-efficient approach. As peripheral devices can conveniently be connected and controlled by the
loggers, the addition of fans or pumps can be explored further
in certain cases, depending on the specific research questions.
In general, the tests and examples provided here represent a
start and we expect that future users will develop additional
ways to use the loggers presented.
We made environmental pCO2aq measurements in several
ways including the following:
1. Test of spatiotemporal variability in a large shallow lake
(Tämnaren, Uppsala, Sweden). Here seven units were
deployed for approximately 2 days with a logging interval of 5 min, near the north and south shores and at the
center of the lake, respectively (Fig. 1).
2. Test of a 20-day deployment with a 1 h logging interval
at a small shallow boreal lake (in the Skogaryd Research
Catchment, Vänersborg, Sweden).
3. Test of measuring stream pCO2aq at 14 locations in a
stream network (Skogaryd, Vänersborg, Sweden) over
a 24 h period with a logging interval of 1 min.
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Figure 2. Comparison of CO2 mixing ratio (ppm) measured with
a Los Gatos Research greenhouse gas analyzer (LGR; DLT100)
and the Senseair (ELG) CO2 logger. Measurements were made with
ELG loggers from two different batches at two separate occasions
(diamonds forming bold lines and circles). The ELGs have a maximum limit at 10 000 ppm in their present configuration. The LGR
is affected by saturation/quenching effects in the measurement cell
starting at 6000 ppm, explaining the slight offset compared to the
1 : 1 line.
3
3.1
Results and discussion
Test of calibration, linear response range, and
influence of temperature and humidity
The results of the sensors were always well correlated with
LGR results (Fig. 2). Above 7000 ppmv, the LGR response
started to become nonlinear but the CO2 loggers kept a linear response up to 10 000 ppmv (confirmed also by additional
analyses using gas chromatography). The combined influence of temperature and humidity was found to be small,
causing an error of < 7.6 % (see Supplement). Logger drift
over time was not notable in the tests and examples provided
here, but is expected during long-term use (the manufacturer
estimate a drift of 50 ppmv per year under indoor conditions).
It is therefore recommended to collect occasional manual
samples for drift check and correction (see Supplement) and
to recalibrate the loggers frequently.
3.2
Flux measurements
Examples of results from the flux measurements are shown
in Fig. 3. Clear and consistent linear responses of CO2 concentrations over time in the chambers, suitable for the calculation of fluxes, were collected with very limited effort in
both terrestrial and aquatic environments. The work primarily consisted of starting the units, deploying chambers, flushing the chamber headspace at the desired time intervals to
restart measurements, and downloading the data. The calcuBiogeosciences, 12, 3849–3859, 2015
D. Bastviken et al.: Cost-efficient approaches to measure carbon dioxide (CO2 ) fluxes
A
1st flux measurement
Flushing
chamber
Closing
chamber
k (m d-1)
CO2 (ppm)
3854
1st flux
measurement
B
Starting
logger in
lab.
CO2 (ppm)
Chamber
deployment
on lake
Day of Year
Lifting chamber to
restart measurement
Chamber headspace
approaching equilibration
pCO2aq (µatm)
CO2 (ppm)
Time (h)
C
Figure 3. Examples of CO2 measurements from loggers inside flux
chambers. Panel (a) shows changes in CO2 concentration with time
inside a chamber (used to calculated fluxes) due to soil CO2 efflux in three repeated experiments. Panel (b) shows logger raw data
from eight repeated measurements on a small wind sheltered boreal lake using a floating chamber. The different work steps in this
example are indicated in the figure. In this example, chamber deployments were restarted manually at low temporal frequency due
to additional parallel field work and depending on priorities such
measurements can be made at much higher frequency. The CO2
logger can also be used in automatic chambers (Duc et al., 2013).
Panel (c) shows a comparison between data from CO2 loggers inside two floating chambers on a pond (solid lines with dots) and
manual samples taken from the same chambers and analyzed by
gas chromatography (circles). Gray and black symbols denote the
two different measurements.
lation of the flux is based on the slope of the CO2 change in
the chamber headspace during the deployment. Thus, a flux
measurement is based on a relative CO2 change which is not
sensitive to moderate drift or to exact absolute values. Nevertheless, as a part of our general measurement routines, occasional manual measurements were taken before flushing the
chamber for sensor validation and drift correction (no drift
correction was needed for any data presented in this study).
The approach of placing a CO2 logger inside each chamber leads to several new benefits for flux measurements including the following:
1. It allows chambers to be individual units that can be
distributed much more widely than a system where the
chambers are connected by tubing to one single external
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Time of day (hours)
Figure 4. Example where k values (piston velocity; see text) were
calculated from wind speed according to (Cole and Caraco, 1998)
for three real scenarios with different diel variability (a), and then
used to model the diel pattern in pCO2aq chambers of the type
we used compared to the expected cases based on instantaneous
pCO2aq levels (b). The expected case is hypothetical but inspired
by levels found for a pond with large diel variability (Natchimuthu
et al., 2014).
analyzer. This is important for capturing spatial variability and to not be restricted to a limited area around a gas
analyzer.
2. Substantial time is saved by eliminating the need for
manual sampling and subsequent sample handling and
analyses. This allows much more time to be spent on
better coverage of spatial or temporal variability in the
fluxes or on accessory measurements.
The low cost of each flux chamber unit together with the time
savings per unit adds substantial value even for short-term,
non-automated flux measurement efforts. The same work effort normally needed for manual flux measurements (including not only sampling but also sample preservation and manual sample analyses) with one chamber can now yield flux
measurements from more than 10 chambers with logger units
inside.
The fluxes obtained for the soils were 2534–
2954 mg C m−2 d−1 (Fig. 3a), which corresponds well
with the previous range found for soil fluxes in corresponding environments (Raich and Schlesinger, 1992). The lake
fluxes measured were 216–666 and 364–427 mg C m−2 d−1
(Fig. 3b and c, respectively), which are also well within
the range previously found in aquatic ecosystems (Selvam
et al., 2014; Trolle et al., 2012). The flux data from the
logger inside the chamber were nearly identical to data
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pCO2aq from bottle headspace extractions (µatm)
Figure 5. Comparison between instantaneous daytime measurements from pCO2aq chambers (allowed to reach equilibrium) and
traditional bottle headspace extractions (1025 mL total volume,
50 mL headspace, not corrected for enclosing a limited amount of
inorganic carbon in the bottle; see text). R 2 for a linear regression
is 0.94. The dashed line is the 1 : 1 line (see text for discussion of
the deviation from this line).
from manual sampling and gas chromatography analysis
(Fig. 3c). Thus, given their low price and suitable sensitivity,
these chamber-logger units seem highly useful in most types
of flux chamber measurements and have the potential to
substantially increase the data generation per work effort.
3.3
3855
TET90(h)
pCO2aq from chambers (µatm)
D. Bastviken et al.: Cost-efficient approaches to measure carbon dioxide (CO2 ) fluxes
pCO2aq measurements
The pCO2aq values in all the examples were in the expected range of 200 to > 10 000 found in various types of
water (Abril et al., 2014; Marotta et al., 2009; Raymond
et al., 2013; Selvam et al., 2014). The most common traditional methods to measure pCO2aq are the alkalinity–pH
method and the bottle headspace equilibration technique
(hereafter called the bottle method). The superiority of the
bottle method compared to the alkalinity–pH method has already been thoroughly addressed (Abril et al., 2015). Therefore we here focus on comparing the bottle and the pCO2aq
chamber (i.e., chamber equilibrator) approaches.
The principle behind the pCO2aq chamber approach is exactly the same as the principle for the bottle method and constitutes the fundamental principle behind Henry’s law, i.e.,
that gas exchange between a confined gaseous headspace and
a connected water volume will eventually approach an equilibrium at which the headspace concentration or partial pressure corresponds with the concentration in the water near the
water–headspace interface. So in essence, the methods are
similar. There are however at least three reasons to believe
that instantaneous pCO2aq measurements from the common
bottle headspace extraction and our pCO2aq chamber technique are not always identical:
1. The headspace-to-water volume ratio affects the measurements as the CO2 transferred to the headspace could
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k (m d-1)
Figure 6. Theoretical equilibration time to within 90 % (TET90 )
of the true pCO2aq after deploying the described chambers (solid
lines) at different piston velocities (k), a temperature of 20 ◦ C, and
a pCO2aq of 2000 µatm (gray) or 8000 µatm (black). The dashed
lines show TET90 for chambers with a twice higher area-to-volume
ratio compared to the chambers we used. Another way to speed up
equilibration time is by mixing the water below the chambers (see
text).
reduce the amount of CO2 left in the water if the water volume is too small, resulting in underestimated
pCO2aq values. This can bias the bottle values depending on the headspace and water volumes and this is
why it is often recommended to use a large bottle (1–
2 L) and a small headspace (25–50 mL) in the bottle
method. Even when following this recommendation, the
headspace-to-water volume ratio will be much smaller
for the pCO2aq chamber approach (e.g., a few liters of
headspace vs. many m3 or even large parts of the mixed
water layer of a lake), which should therefore be more
accurate in this regard. Fortunately, the bottle method
bias is in most cases small (about 5 % for a 20 ◦ C scenario with a 1 L bottle, a 50 mL headspace, and no available bicarbonate that can buffer the loss of CO2 to the
headspace) and can be corrected for although it is not
always clear if such corrections are made.
2. For the bottle approach, the transfer of water into large
bottles without the risk of losing volatile solutes is not
trivial. Water pumping and transfer from water samplers
can cause degassing. Hence the water sampling can result in loss of CO2 causing underestimation of the real
pCO2aq . In the pCO2aq chamber approach, there is no
water sampling and the risk of water sampling bias is
therefore removed.
3. Another reason that numbers may not be identical is the
potential delayed response of the pCO2aq in the chamber while the bottle approach gives a snapshot value
valid for the sampled water volume. This delay differs
depending on the piston velocity (k; see Fig. 4) and
means that daytime CO2 values in the pCO2aq chambers
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D. Bastviken et al.: Cost-efficient approaches to measure carbon dioxide (CO2 ) fluxes
Figure 8. Example of long-term monitoring of pCO2aq at 1h intervals in a small shallow boreal wetland pond (mean depth 1 m). Panel
(a) shows raw data indicating spikes in the data most likely due to
condensation events (or possibly related to animals temporary visiting the chambers; insects, frogs, etc.), particularly towards the end
of the deployment. Panel (b) shows the same data as in (a) after
a simple filtering procedure, removing data points that were more
than 10 % greater than the −4 to +4 h median of surrounding the
data point.
Figure 7. Illustration of spatial variability of pCO2aq (expressed
as mixing ratio – ppm) in a large shallow (mean depth 2 m) lake
determined by seven CO2 logger-chamber units. The locations of
each chamber are indicated in Fig. 1. See text for details. Note the
different y axis scales and that this lake was wind exposed with
variable wind conditions during the measurement period.
may be influenced by the higher pCO2aq from the previous night, thereby overestimating the instantaneous
daytime pCO2aq . Accordingly, nighttime CO2 values in
the chamber may underestimate the instantaneous night
pCO2aq by influence from lower daytime pCO2aq .
Essentially, all the three points above show that single
pCO2aq chamber measurements, representing a longer time
period, are not directly comparable with instantaneous bottle
values, making it likely that chamber pCO2aq values measured during daytime should be slightly higher than corresponding bottle pCO2aq measurements. This is also what we
find when comparing single daytime pCO2aq samples from
chambers and bottles (Fig. 5). The difference seems to increase with pCO2aq levels which is what would be expected
if the bias were to be caused by loss from sampling (point 2
above) or by a strong diel cycling (point 3 above).
We find that while the principles behind both the bottle
and the chamber approach are robust, there may be a delayed
response of the pCO2aq chamber depending on k (Fig. 4).
Thus single snapshot measurements from the chambers during daytime can be overestimated (see Fig. 5). However, the
daily averages from the pCO2aq chambers were representative in a wide range of k scenarios (in Fig. 4 the mean daily
pCO2aq chamber values were on an average 97% of the real
values; range of 92–99 %). There is also potential to speed up
Biogeosciences, 12, 3849–3859, 2015
the temporal response of the pCO2aq chambers by changing
the chamber design (decreasing the volume and increasing
the area; see also Fig. 6). Another way to speed up the response time would be to let the logger control a pump that
draws air from the logger box and releases it just below the
water surface under the chamber, resulting in surface water
purging favoring rapid equilibration. This modification could
easily be made but requires a larger battery for long-term use.
The time of initial equilibration after deployment may be
long at low k values (Fig. 6). For example, in a water body
at wind speeds below 0.6 m s−1 (corresponding to k values lower than 0.5 m d−1 using one common wind speed–
k model; Cole and Caraco, 1998), the equilibration time is
> 10 h given the volume to area ratio of our chambers (Fig. 6).
As stated above, this limits the use of the chamber pCO2aq
approach for diel variability, particularly during the first period after deployment. The delay in the chamber response
when being near equilibrium levels is also much shorter at k
values, making it possible to distinguish diel variability although with delay and hampered amplitude requiring careful
consideration (Fig. 4).
The measurements from chambers with equilibrated
headspace revealed large spatial differences in pCO2aq with
synchronous temporal variability in the large lake (Fig. 7).
Data from a long-term deployment (20 days) showed a consistent diel pattern with increasing pCO2aq during night and
decreasing levels during the day as expected (Fig. 4 and
above discussion). The long-term tests showed that our passive approach with a protective box to avoid condensation
in the logger measurement cell worked well for 1–2 weeks.
Over time, moisture accumulated in the sensor protection
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D. Bastviken et al.: Cost-efficient approaches to measure carbon dioxide (CO2 ) fluxes
3857
Figure 9. Example of 24 h of data from 14 CO2 logger-chamber units placed in the main streams in a catchment stream network to log
stream pCO2aq . Yellow squares (D1–D4) denote water discharge stations representing stream regions and the water flows from D1 to D4;
the D3 stream is a tributary which joins the main stream upstream of station D4. The red dots represent the CO2 logger-chamber units. Data
(with the initial time of chamber equilibration removed) are displayed region-wise in the sub-panels together with the measured discharge.
A rain event caused an increase in the discharge half way through the measurement period which seems related with increased pCO2aq in
most locations. DOY denotes day of the year. The map is published with permission from Lantmäteriet, Sweden, according to agreement
i2012/898 with Linköping University.
box and consequently unrealistic high peaks caused by water condensation inside the measurement cell, often reaching the maximum value (10 000 ppm; Fig. 8a), were noted
more frequently with time. This effect disappeared once conditions in the chamber favored drying of the sensor and
the sensors withstood occasional condensation with maintained performance. The occurrence of condensation events
increased with increasing temperature difference between
day- and nighttime temperatures and therefore the condensation events were more common on the sunlit lake surfaces
than on waters in the shade (i.e., the streams described below). To remove the condensation data peaks we adopted a
simple data filtering routine that removed data points that
were more than 10 % higher than the ±4 h median relative
to the data point (Fig. 8b). This filtering procedure for removing data influenced by condensation becomes inefficient
if condensation events are too frequent. We therefore suggest routinely drying the logger indoors overnight every 7–
14 days (depending on the local conditions) of deployment.
Given the low price, the loggers can simply be replaced with
a separate set of dry units to avoid losing data while the log-
www.biogeosciences.net/12/3849/2015/
gers are drying. For longer deployments where visits every 1
or 2 weeks are not possible, more advanced measures to prevent condensation should be considered. Potentially, silica
gel in the sensor protection box could delay extensive influence of condensation events. As the loggers can control one
peripheral unit, it is also be possible to equip the system with
a larger battery and a pump that draws air to the sensor using
a water-vapor-removing desiccant. Another potential alternative to prevent condensation is to heat the measurement cell
a few degrees above the surrounding air if there is enough
power.
The logger units were also found to be highly suitable for
logging pCO2aq in streams (Fig. 9). By anchoring the units
along the streams, equilibrium time is reduced by the turbulence induced around the chamber edges (while this is a
problem for stream flux measurements, it is beneficial for
pCO2aq measurements with our approach). Furthermore, the
low price of our units allows the use of a greater number of
units compared to other approaches, which is an advantage
for monitoring pCO2aq at multiple points in, e.g., a stream
network for doing CO2 mass balances and for studying the
Biogeosciences, 12, 3849–3859, 2015
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D. Bastviken et al.: Cost-efficient approaches to measure carbon dioxide (CO2 ) fluxes
regulation of pCO2aq over large scales. Figure 9 provides
an example where 14 units were used simultaneously in a
stream network and where spatiotemporal variability over
24 h revealed (1) significant spatial differences between locations in the catchment, providing indications of different
CO2 export from soils and also of local hotspots for CO2
emissions, and (2) how a rain event and an associated change
in discharge influenced the temporal dynamics of pCO2aq .
valuable support allowing easy access to the Skogaryd Research
Catchment, where some of the field work was performed, and
supplied discharge data. We are also grateful to many colleagues
around the world for their interest. This work was supported by
grants from Linköping University and from the Swedish Research
Council VR to D. Bastviken.
4
References
Conclusions
We conclude that the approach for measuring and logging
CO2 fluxes and pCO2aq presented here can be an important
supplement to previously presented approaches. When focusing on high temporal resolution of pCO2aq (response time
of minutes), the previous approaches using submersible sensors (e.g., Johnson et al., 2010) or rapid equilibrator systems
connected to CO2 analyzers (e.g., Abril et al., 2006; Frankignoulle et al., 2001) are probably preferred. In such cases, the
Senseair CO2 logger may be suitable for use together with
equilibrator systems. The chamber approach described here
provides a cost- and labor-efficient multi-measurement point
alternative for (i) easy flux measurements and (ii) pCO2aq
measurements which are not biased by potential biofilms on
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pCO2aq are acceptable (the delay is shorter at higher turbulence/piston velocity and can be estimated from the data obtained from the initial part of the deployment showing how
quickly water–headspace equilibrium is reached).
While well-constrained CO2 fluxes are critical for the
global carbon balance, the previous estimates are uncertain
in terms of spatiotemporal variability and flux regulation. For
aquatic environments CO2 fluxes are often based on indirect measurements demonstrated to frequently be highly biased (Abril et al., 2015). Hence there is a need to rapidly
improve the situation and increase the global availability of
high-quality data based on direct CO2 measurements. We believe the presented measurement approaches using small logger units are affordable, efficient, user friendly, and suitable
for widespread use and therefore have great potential as important tools in future CO2 studies.
The Supplement includes a manual on how to build and
use the described CO2 logger units, details about some of
our tests, and advice on the practical use of the loggers.
The Supplement related to this article is available online
at doi:10.5194/bg-12-3849-2015-supplement.
Acknowledgements. We thank Björn Österlund, Lars Nylund, and
Brian Scown for valuable assistance regarding logger functions
and modifications. Leif Klemedtsson and David Allbrand provided
Biogeosciences, 12, 3849–3859, 2015
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