Introduction
Sulfur hexafluoride (SF6) is an anthropogenic greenhouse gas which is
mainly used as an electrical insulator, with other applications as a
quasi-inert gas. Although its main sources are in the Northern Hemisphere,
its atmospheric abundance is increasing globally in response to these
emissions and its long atmospheric lifetime (defined as the ratio of the
atmospheric burden of a trace gas to its rate of loss from the atmosphere).
SF6 is characterized by large absorption cross sections for terrestrial
infrared radiation such that the presently increasing SF6 abundance will
contribute a positive radiative forcing over many centuries. The important
known removal sources are electron attachment and photolysis. Recently,
Totterdill et al. (2015) have also measured bimolecular rate
constants for the reaction of SF6 with mesospheric metals.
Harnisch and Eisenhauer (1998) reported that SF6 is naturally present
in fluorites, and outgassing from these materials leads to a natural
background atmospheric abundance of 0.01 pptv. However, at present the
anthropogenic emissions of SF6 exceed the natural ones by a factor of
1000 or more and are responsible for the rapid increase in its atmospheric
abundance. Surface measurements show that atmospheric SF6 has increased
steadily since the 1980s (Geller et al., 1997; Maiss and
Brenninkmeijer, 1998) and is still increasing fairly linearly. The current
global mean surface mixing ratio is 8.60 pptv, which is increasing by about
0.33 pptv yr-1 (∼ 4 % yr-1; Dlugokencky et al., 2016).
SF6 provides a useful tracer of atmospheric transport in both the
troposphere and stratosphere. Rates for transport of pollutants into,
within and out of the stratosphere are important parameters that regulate
stratospheric composition. The basic characteristics of the stratospheric
Brewer–Dobson circulation (BDC) are known from observations of trace gases
such as SF6: air enters the stratosphere at the tropical tropopause,
rises at tropical latitudes, and descends at middle and high latitudes to
return to the troposphere. Understanding the rate of this transport on a
global scale is crucial in order to predict the response of stratospheric
ozone to climatic or chemical change. SF6 is essentially inert in the
troposphere to middle stratosphere and is removed by electron attachment and
photolysis in the upper stratosphere and mesosphere (Ravishankara et al., 1993). This tracer therefore provides an ideal probe of transport on
timescales of importance in the stratospheric circulation and quantitative
information on mean air mass age for the lower and middle stratosphere.
The mean age of air (AoA) is the interval between the time when the volume
mixing ratio of a linearly increasing atmospheric tracer reaches a certain
value at a given location in the stratosphere and an earlier time when this
mixing ratio was reached at a reference location. Mean AoA is expressed as
(Hall and Plumb, 1994; Waugh and Hall, 2002)
AoA=t(χ,l,z)-t(χ,l0,z0),
where t is time, χ is the volume mixing ratio, l and
z are latitude and altitude, and the 0 subscripts denote the
reference latitude and altitude, which are chosen to be the upper tropical
troposphere (for the purposes of our simulations we chose the grid point
latitude = 1∘ N, altitude = 13.9 km). In principle the trend of AoA
can be used to diagnose changes in the strength of the Brewer–Dobson circulation
(BDC); in practice, however, it is very difficult to obtain unambiguous
results on trends from this or any other trace gas (Garcia et al.,
2011). Ideally, AoA should be determined experimentally using a tracer with a very small (or zero) chemical sink in the stratosphere or mesosphere.
Otherwise, a correction must be applied to account for this loss. A
correction would also be necessary for any non-linear tropospheric growth.
However, for the period considered for diagnosing age of air in this paper
(2002–2007), the growth of SF6 is approximately linear, so we can
reasonably neglect such a correction for SF6-derived AoA (Hall and
Plumb, 1994).
Ravishankara et al. (1993) reported the atmospheric lifetime of
SF6 to be 3200 years by considering electron attachment and vacuum
ultraviolet (VUV) photolysis. They also studied the loss of SF6 by
reaction with O(1D) but found the rate too slow to be important. They
deduced that electron attachment was the dominant loss process and
quantified this process using a 2-D model, wherein they assumed that all
SF6 molecules are destroyed after attachment of an electron (with a
rate constant of 10-9 cm3 molecule-1 s-1). They
therefore argued that their lifetime of 3200 years could be a lower limit,
but clearly this result depends on the accuracy of the 2-D electron density,
which was calculated using only photochemistry. Morris et al. (1995) subsequently extended the work of Ravishankara et al. (1993)
by including an ion chemistry module in the same 2-D model. They also made
other assumptions to maximize the impact of electron attachment on SF6
loss and derived a lifetime as short as 800 years (which could be further
sporadically decreased by large solar proton events). Using a 3-D middle
atmosphere model, Reddmann et al. (2001) estimated the lifetime to
be 472 years when SF6 is irreversibly destroyed purely by direct
electron attachment and to be 9379 years when SF6 loss is assumed to
occur only via indirect loss (via the formation of SF6-) and
ionization via the reactions with O2+ and N2+. They
concluded that the estimated lifetime depends strongly on the electron
attachment mechanism because the efficiency of this process as a permanent
removal process of SF6 depends on the competition between the reaction of
SF6- with H and HCl and the photodetachment and reaction with O and
O3. Here we extend the above studies and investigate the SF6
lifetime using a state-of-the-art 3-D chemistry climate model with a domain
from the surface to 140 km. Our modelled electron density is based on
results of a detailed ion chemistry model, and we use a detailed methodology
for treating the atmospheric background electrons, which is based on Troe's
formalism (Troe et al., 2007a, b; Viggiano et al., 2007).
SF6 loss reactions included in WACCM.
Loss process
Rate constant
Reference and comments
Na + SF6
k = 1.80 × 10-11exp(-590.5/T)
From Totterdill et al. (2015); refitted for mesospheric temperatures 215–300 K.
K + SF6
k = 13.4 × 10-11exp(-860.6/T)
From Totterdill et al. (2015); refitted for mesospheric temperatures 215–300 K.
Electron attachment
Associative attachment: kEA,ass= kat × (k(SF6- + H)[H] + k(SF6- + HCl)[HCl])/ (jPD+ k(SF6- + H)[H] + k(SF6- + HCl)[HCl] +
k(SF6- + O3)[O3] + k(SF6- + O)[O]) Dissociative attachment: kEA,diss= kat × β, where β is the fraction of SF6- that dissociates into SF5-.
Totterdill et al. (2015).
Photolysis
Lyman α: σ (121.6 nm) = 1.37 × 10-18 cm2
Parameterized expression over the range of 115–180 nm, based on previous measurements.
Totterdill et al. (2015).
In addition to determining the SF6 lifetime, in this study we report
new measurements of the infrared absorption cross sections for SF6 and
input these into a line-by-line radiative transfer model in order to obtain
radiative forcings and efficiencies. These values are then used to determine
more accurate values of global warming potentials (GWPs) based on their
cloudy-sky adjusted radiative efficiencies. GWP is the metric used by the
World Meteorological Organisation (WMO) and Intergovernmental Panel on
Climate Change (IPCC) to compare the potency of a greenhouse gas relative to
an equivalent emission of CO2 over a set time period. The definitions
of these radiative terms are given in Appendix A.
Methodology
WACCM 3-D model
To simulate atmospheric SF6 we have used the Whole Atmosphere Community
Climate Model (WACCM). Here we use WACCM 4 (Marsh et al., 2013),
which is part of the NCAR Community Earth System Model (CESM; Lamarque
et al., 2012), configured to have 88 pressure levels from the
surface to the lower thermosphere (5.96 × 10-6 Pa, 140 km) and
a horizontal resolution of 1.9∘ × 2.5∘ (latitude × longitude). The model contains a detailed treatment of middle
atmosphere chemistry including interactive treatments of Na and K (Plane
et al., 2015). We use the specified dynamics (SD) version of the
model to allow comparison with observations (see Garcia et al., 2014, for details). The SF6 surface emission flux and initial global
vertical profiles were taken from a CCMI (Chemistry Climate Model
Initiative) simulation using the same version of SD-WACCM with the same
nudging analyses (D. Kinnison, personal communication, 2013).
Lyman-α photolysis is the only SF6 loss reaction in the
standard version of WACCM, and in this work we have added the additional
processes given in Table 1. The rate constants for the SF6 +
metal reactions have been measured in our laboratory for mesospheric
conditions (Totterdill et al., 2015); here we use the experimental
values for the reactions with Na and K. For the photolysis of SF6 we
used the standard WACCM methodology but with the updated Lyman-α
cross section from our laboratory of 1.37 × 10-18 cm2 molecule-1 (Totterdill et al., 2015).
The WACCM Lyman-α flux is taken from Chabrillat and Kockarts (1997).
Electron attachment to SF6 plays a major role in its atmospheric
removal and so both dissociative and non-dissociative attachment are
considered in this study. The detailed method is described in a recent paper
(Totterdill et al., 2015) and here only a brief summary is given.
The removal process by the attachment of low-energy electrons to SF6
can be described using Troe's theory (Troe et al., 2007a, b;
Viggiano et al., 2007). In the middle and lower mesosphere,
electrons are mostly attached to neutral species in the form of anions.
However, above 80 km the concentration of free electrons increases and the
direct electron attachment to SF6 becomes more likely. This can happen
either by associative attachment forming the SF6- anion, which can
then undergo chemical reactions with H, O, O3 and HCl, or by
dissociative attachment forming the SF5- anion fragment. The
probability β of dissociative attachment when an electron is
captured by SF6 is given by
βp,T=kdiskat+kdis,
where kdis is the rate constant for dissociative attachment
and kat is the rate constant for associative attachment.
β can be expressed as
βp,T=exp-4587T+7.74×104.362-0.582log10p/Torr-0.0203log10pTorr2/5.26×10-4,
where T is the temperature in K and p is the pressure in
Torr (Totterdill et al., 2015).
Positive and negative ions included in WACCM-SIC.
Positive ions
O2+, O4+, NO+, NO+(H2O),O2+(H2O), H+(H2O), H+(H2O)2,H+(H2O)3, H+(H2O)4, H+(H2O)5, H+(H2O)6, H3O+(H2O)2(CO2), H3O+(OH), O2+(CO2),H3O+(OH)(CO2), H3O+(OH)(H2O), O2+(H2O)(CO2), O2+(H2O)2, O2+(N2), NO+(H2O)2, H+(H2O)(CO2), O+, N+, N2+, NO+(H2O)3, O4+,H+(H2O)2(CO2), H+(H2O)2(N2)
Negative ions
O3-, O-, O2-, OH-, O2-(H2O), O2-(H2O)2, O4-, CO3-, CO3-(H2O), CO4-, HCO3-, NO2-, NO3-, NO3-(H2O), NO3-(H2O)2, NO3-(HNO3),NO3-(HNO3)2, Cl-, ClO-, NO2-(H2O), Cl-(H2O), Cl-(CO2), Cl-(HCl)
We include both associative and dissociative electron attachment using
WACCM-predicted electron concentrations (see Table 1). Note that
the SF6- anion is not modelled directly. As it is short-lived, we
can treat it as being in steady state and consider the relative rates of its
destruction pathways. Therefore, the net SF6 attachment loss rate is
calculated by multiplying kat by the ratio of permanent
destruction of the resulting SF6- (reactions of SF6-
with H and HCl) to the total sum of these reactions plus processes which
recycle SF6- to SF6 (reactions with O and O3, and
photodetachment). The SF6- photodetachment rate of 0.11 s-1
at midday was estimated using photodetachment cross sections from Eisfeld (2011; 280–376 nm) and Bopp et al. (2007; 376–707 nm). Note
there is a typographical error in Totterdill et al. (2015) where
the rate is stated as 1.1 s-1.
In order to use a realistic electron concentration, the role of negative
ions in the D region must be considered. The D region is
the lowest part of the ionosphere, extending from about 60 to 85 km. It is
characterized by the appearance of cluster ions (e.g. proton hydrates
H+⋅(̧H2O)n, where n≤ 6) and negative ions (e.g.
O2-, CO3- and NO3-) rather than free
electrons. These species predominate because the atmospheric pressure is
high enough to facilitate the three-body attachment of ligand species like
H2O to positive ions and electrons to neutral molecules. Therefore, a
scaling factor was introduced that converts the standard WACCM electron
concentrations, which are calculated from charge balance with the five major
positive E region ions (N+, N2+, O+,
O2+ and NO+), to more realistic electron concentrations. We
have recently incorporated the Sodankylä Ion Chemistry (SIC) model into
the standard version of WACCM to produce a new version (WACCM-SIC)
containing a detailed D region ion chemistry with cluster ions and
negative ions (Kovács et al., 2016). The mesospheric positive
and negative ions in WACCM-SIC are listed in Table 2. The electron
scaling factor in each grid box of WACCM was then defined as the annually
averaged ratio of [e]WACCM-SIC / [e]WACCM for the year 2013, where
[e]WACCM-SIC is the electron density calculated from WACCM-SIC and
[e]WACCM from the standard WACCM.
Top: annual average electron concentration for
2013 from the standard WACCM model (in 102 electrons cm-3). Middle: annual average electron concentration
for 2013 from WACCM-SIC model (in 102 electrons cm-3). Bottom: annually averaged electron
scaling factor for 2013.
Time series of volume mixing ratio profiles (pptv) of
NO+ (left panels) and
O2+ (right panels) above Halley
(76∘ S) from two WACCM-SIC simulations. Top panels
show the values obtained from the model run without medium-energy electrons
(MEE); the middle panels show the run with medium-energy electrons; and the
bottom panels show the absolute differences between the two model runs.
The scaling factor, which varies with altitude and latitude, is shown in
Fig. 1 (bottom panel) together with the electron densities from
the standard WACCM (top panel) and WACCM-SIC (middle panel) models. The
annually averaged electron concentration in the WACCM-SIC model is
significantly smaller in the lower and middle mesosphere than in the
standard WACCM, which is expected because of negative ion formation. In the
polar regions the scaling factor is around 0.01 at 50 km and 0.5 at 70 km.
Note that in the upper mesosphere (70–80 km), the electron density in
WACCM-SIC is larger than WACCM, by over a factor of 5 near the poles. This
results from the inclusion of medium-energy electrons (MEE) (electrons with
an energy between 30 keV and 2 MeV) in WACCM-SIC. Figure 2 shows the
effect of MEE by comparing WACCM-SIC runs with and without this source of
ionization in the upper mesosphere included. To describe the effect of
ionization, WACCM-SIC uses ionization rates (I) as a function of
time and pressure, which were calculated from the spectra based on the proton
energy-range measurements in standard air as described by Verronen
et al. (2005). According to Fig. 3 of Meredith et al. (2015), the annually averaged medium-energy electron flux for 2013
approximately corresponds to the long-term, 20-year average. This allows us
to assume that the annually averaged electron density of 2013 from WACCM-SIC
can be used to scale the long-term simulations using the standard WACCM
aimed at determining the atmospheric lifetime of SF6.
The WACCM simulation included five different SF6 tracers in order to
quantify the importance of different loss processes. All of these tracers
used the same emissions but differed in their treatment of SF6 loss
reactions. One SF6 tracer included no atmospheric loss (i.e. a passive
tracer). Three tracers included one of the following loss processes for
SF6: (i) reaction with mesospheric metals (Na, K), (ii) electron
attachment and (iii) UV photolysis. Finally, one “total reactive” SF6
tracer included all three loss processes. This total reactive tracer should
be the most realistic and was used in the radiative forcing calculations.
WACCM was run for the period 1990–2007, and the first 5 years were
treated as spin-up. For the analysis the monthly mean model outputs were
saved and later globally averaged for the lifetime calculations.
Infrared absorption spectrum and radiative forcing
Previous quantitative infrared absorption spectra of SF6 have been
compared in Hodnebrog et al. (2013; their Table 12). There are
differences of ∼ 10 % between existing integrated
cross section estimates, and the measurements cover different spectral
ranges. We therefore performed a more complete set of measurements over a
wider spectral range, in order to reduce uncertainty in the absorption
spectrum and hence the radiative efficiency of SF6. Measurements were
taken using an experimental configuration consisting of a Bruker Fourier
transform spectrometer (Model IFS/66), which was fitted with a mid-infrared
(MIR) source used to generate radiation which passed through an evacuable
gas cell with optical path length 15.9 cm. The cell was fitted with KBr
windows, which allow excellent transmission between 400 and 40 000 cm-1. The choice of source and window were selected so as to admit
radiation across the mid-IR range where bands of interest are known to
occur. Room temperature (296 ± 2 K) measurements were carried out
between 400 and 2000 cm-1 at a spectral resolution of 0.1 cm-1 and
compiled from the averaged total of 128 scans to 32 background scans at a
scanner velocity of 1.6 kHz. Gas mixtures were made using between 8 and 675
Torr of SF6 diluted up to an atmosphere using N2, according to the
method described in Totterdill et al. (2016).
Radiative forcing calculations were made using the Reference Forward Model
(RFM; Dudhia, 2013), which is a line-by-line radiative transfer model based
on the previous GENLN2 model (Edwards, 1987). Results obtained from this
model were validated against the DISORT radiative transfer solver (Stamnes
et al., 2000) included within the libRadtran (Library for Radiative
Transfer) package (Mayer and Kylling, 2005). A full description of these
models and parameters used alongside discussion of the treatment of clouds and
model comparison is also given in Totterdill et al. (2016).
Partial (reactions with electrons, photolysis and metals; K, Na) and total atmospheric lifetimes (years) of SF6 from different
studies. Numbers in parentheses show relative percentage contributions of
loss due to the different processes.
Lifetime/years
Study
Photolysis
Electron attachment
Total
Model dimensions
Ravishankara et al. (1993)
13 000 (24 %)
4210 (76 %)
3200
2-D
Morris et al. (1995)
N/A
N/A
800
2-D
This work
48 000 (2.6 %)
1339 (97.4 %)
1278
3-D
Seasonal mean volume mixing ratios (pptv) of the
different SF6 tracers for the polar regions
(60–90∘ N and
60–90∘ S
latitudes) in 2007 as a function of altitude for MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) satellite-observed
SF6 (black symbols with standard deviations for ±1σ; Stiller et al., 2012), the total
WACCM-SF6 (blue solid line), the photolysis
WACCM-SF6 tracer (green solid line) and the inert
WACCM SF6 tracer (red dashed line).
Results
Global distributions of SF6 from WACCM simulations
Figure 3 shows typical zonal mean profiles of the WACCM SF6
tracers in the north and south polar regions for different seasons, compared
to MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) observations for the year 2007 (Haenel et al., 2015).
Although the MIPAS SF6 data provide much more coverage horizontally
and vertically compared to in situ aircraft and balloon data, they have only
been validated up to 35 km (Stiller et al., 2008). Validation at
higher altitudes is not possible due to the lack of suitable reference data.
Details of the validation of the MIPAS data version used here
(V5h_SF6_20 for the full-resolution product
from 2004 and earlier; V5r_SF6_222 and
V5r_SF6_223 for the reduced-resolution period
of 2005 and later) can be found in Haenel et al. (2015), including
Fig. S2 of their Supplement. The WACCM passive SF6
tracer has a mixing ratio profile that is almost constant with altitude in
the stratosphere and lower mesosphere below 60 km and then decreases by about
10 % by 70 km, after which it decreases more rapidly. Comparison of the
tracers that include loss processes show that the removal of SF6 is
dominated by electron attachment, with a small contribution (< 3 %) directly from photolysis. The mesospheric metals make a negligible
contribution because the Na and K layers occur in the upper mesosphere above
80 km (with peaks around 90 km), and the concentrations of these metal atoms
are too low. Figure 3 shows that the model mean profile agrees well
with the MIPAS mean in the polar lower stratosphere (around 20 km) but
exhibits a positive bias of around 1 pptv at higher altitudes in the middle
stratosphere. However, the figure also shows that the variability in the
observed SF6 at high latitudes is large. The time variation of modelled
SF6 shown in Fig. 4 corresponds to an emission rate (slope)
of 6.5 × 10-3 Tg yr-1, i.e. a 0.29 pptv yr-1 increase in
global mean volume mixing ratio, and a volume mixing ratio of 6.4 pptv by
the end of 2007.
Variation of the total annual atmospheric burden of
SF6 during the simulation from 1995 to 2007.
According to this the emission rate (slope) was determined to be
6.5 × 10-3 Tg yr-1, corresponding to 0.29 pptv yr-1.
Annual zonal mean latitude–height volume mixing ratios
(pptv) of the different WACCM SF6 tracers in 2007:
(a) inert SF6 tracer; (b) SF6
tracer removed by photolysis only; (c) SF6 tracer
removed by mesospheric metals only; (d) SF6 tracer
removed by electron attachment only; and (e) total reactive
SF6. Panel (f) shows the SF6
volume mixing ratio for 2007 from MIPAS observations. Note the different
altitude ranges and contour intervals for panels (a)–(d) versus panels
(e)–(f).
Figure 5 shows the zonal mean annual mean SF6 distribution
from the five WACCM tracers and MIPAS observations for 2007. Figure 5a (and Fig. 3) shows that there is a rapid decrease in SF6
above 75 km even for the inert tracer. This can be explained by diffusive
separation, which becomes pronounced in the upper mesosphere because
SF6 is a relatively heavy molecule (molar mass 0.146 kg) compared to
the mean mass of air molecules (mean molar mass 0.0288 kg; cf. Garcia
et al. 2014, where similar behaviour is seen for CO2,
another relatively heavy molecule). Panels a–c of the figure all show
SF6 decreasing above ∼ 80 km, and panels a and c are
almost identical, while in panel b the decrease begins about 4 km lower.
This is all consistent with the notion that metals do not affect SF6
and photolysis contributes only slightly. The fact that diffusive separation
prevents SF6 from reaching altitudes where photolysis is faster must be
contributing to the very long lifetime (48 000 years, Table 3)
found when photolysis is the only loss considered. By contrast, in
Fig. 5d SF6 decreases rapidly above 70 km, which is related
to the fact that loss via electron attachment is important at these lower
altitudes. Thus, in this case, SF6 loss occurs below the altitudes
(∼ 90 km) where diffusive separation is important (and where
air density is higher), which makes it a much more effective loss mechanism.
The WACCM SF6 tracer that includes all loss processes (Fig. 5e) has a very similar distribution to that which only treats loss due to
electron attachment (Fig. 5d), which emphasizes how this process
dominates SF6 loss in the model. This model tracer can be compared to
the MIPAS observations in Fig. 5f, which shows that
WACCM appears to reproduce the general features of the MIPAS distribution
(note the smaller altitude range in panels e and f of Fig. 5). However, it is also clear that WACCM SF6, even with all losses
considered, decreases with altitude much more slowly at all latitudes than
MIPAS SF6. This could indicate a problem with the model's meridional
transport. However, a BDC that is too fast would tend to produce low levels of
SF6 at middle and high latitudes in the descending branch, which does
not seem to be the case. Therefore, at least two other possible scenarios
could be responsible for the discrepancy: SF6 loss in WACCM is still
somewhat underestimated despite the inclusion of the electron attachment, or
MIPAS SF6 is biased low above ∼ 20 km.
(a) Variation in atmospheric lifetime of SF6 (solid line) and 10.7 cm solar radio
flux (dashed line) during the WACCM simulation. (b) Variation of the WACCM
electron concentration (cm-3) at 80 km, averaged over
polar latitudes (60–90∘ N and 60–90∘ S).
Annual mean age of stratospheric air (years) for the
period of 2002–2007 determined from a WACCM simulation using (a) the inert
SF6 tracer; (b) the total reactive
SF6 tracer; (c) the idealized AOA1 tracer. Panel (d) shows the age values derived for the same period from our analysis of MIPAS
SF6 observations.
Atmospheric lifetime
The atmospheric lifetime is defined as the ratio of the atmospheric burden
to the atmospheric loss rate. This definition was used to calculate annual
mean lifetime values from the WACCM output containing the individual rates
for the different loss processes. During the simulation the total
atmospheric burden of SF6 increased linearly as expected (see
Fig. 4) from 3.4 × 1032 molecules with an annual
increment of 2.3 × 1031 molecules yr-1. Figure 6 shows
the variation in SF6 lifetime from 1995 to 2007, corresponding to a
full solar cycle (the solar minima occurred in May 1996 and January 2008).
The figure demonstrates that the lifetime has a strong dependence on solar
activity, being anti-correlated with solar activity, for example as measured
by the radio flux at 10.7 cm (2800 MHz; Tapping, 2013), which ranges over
(72–183) × 10-22 W m-2 Hz-1, with an average
value of 90.3 × 10-22 W m-2 Hz-1. The mean SF6
lifetime over the same solar cycle period is 1278 years, with a range from
1120 to 1475 years. The annual averaged electron number density in the polar
regions is also plotted in Fig. 6; as expected, it is correlated
with the 10.7 cm radio emission (Tapping, 2013).
Mean age values at 20 km altitude derived from MIPAS
satellite (dashed magenta line) and ER-2 aircraft observations
(SF6 red open circles, CO2
black crosses; Hall et al., 1999). The error
bars apply to the age derived from the ER-2 observations. Also shown is the
mean age derived from WACCM tracers: reactive SF6
(dashed blue line), passive SF6 (light blue line) and
AoA tracer (AOA1, solid green line).
Infrared absorption spectrum of SF6
at ∼ 295 K on (a) a logarithmic y axis and (b) a linear
y axis. The logarithmic scale in panel (a) highlights the relative positions
of the minor bands.
As noted in Sect. 1, the SF6 lifetime has been reported to be 3200
years by Ravishankara et al. (1993). For this they used a total
electron attachment rate constant of kEA= 10-9 cm3 s-1. In Morris et al. (1995) the calculated lifetime
decreased to 800 years by considering ion chemistry and assuming that the
associative attachment forming SF6- does not regenerate the parent
molecule, thereby obtaining a lower limit for the lifetime. Reddmann
et al. (2001) estimated the lifetime to be 472 years when SF6
is irreversibly destroyed purely by direct electron attachment and to be
9379 years when SF6 loss is assumed to occur only via indirect loss
(via the formation of SF6-) and ionization via the reactions with
O2+ and N2+. In the present study we have directly
applied Troe's theory (Troe et al., 2007a, b; Viggiano et al., 2007) to determine the efficiency of electron attachment as a function
of temperature and pressure and the branching ratio for dissociative
attachment (Eq. 2), which we extrapolated to mesospheric conditions
(Totterdill et al., 2015).
Our estimated partial lifetime of SF6 due to photolysis (i.e.
the lifetime calculated considering photolysis as the only atmospheric loss
process) for the SF6 tracer which includes all loss processes is 48 000 years, which is considerably longer than that the 13 000 years determined by
Ravishankara et al. (1993) despite our Lyman-α cross
section (1.37 × 10-18 cm2, Table 1) being only
∼ 22 % smaller than the value measured by
Ravishankara et al. (1.76 × 10-18 cm2). One
reason why our photolysis-related partial lifetime is longer is that WACCM
includes diffusive separation, which was not described in the earlier 2-D
model study. The inclusion of diffusive separation reduces sharply the
abundance of SF6 at high altitudes, where photolysis is most effective.
Another contributing factor could be that the VUV photolysis is important
only above 80 km, while in our model runs SF6 is mostly destroyed by
electron attachment, which results in less being transported into this upper-mesospheric region. When we analyse our WACCM SF6 tracer which is
subject to photolysis loss only, the resulting steady-state overall
lifetime (i.e. lifetime calculated using the rates of all loss processes)
for the last model year (2007) is 17 200 years, which is only 32 % larger than
the value of Ravishankara et al. (1993) and thus more consistent
with the difference in the Lyman–α cross sections. Finally, if we
do not include the electron scaling factor to reduce the electron density
below 80 km due to negative ion formation, then the SF6 lifetime
decreases to 776 years (not shown), which is similar to the value of 800 years obtained by Morris et al. (1995).
Latitude–time plots for instantaneous radiative forcing
(W m-2) by SF6 as a function of
latitude and month at (a) high-latitude resolution (1.5∘ spacing)
and (b) low-latitude resolution (9∘ spacing).
Impact of SF6 loss on mean age of
stratospheric air
As SF6 is a chemically stable molecule in the stratosphere and
troposphere and has an almost linearly increasing tropospheric abundance,
its atmospheric mixing ratio is often used to determine the mean age of
stratospheric air. This is an important metric in atmospheric science as the
distribution of ozone and other greenhouse gases depends significantly on
the transport of air into, within, and out of the stratosphere. WACCM
contains an idealized, linearly increasing age of air tracer (AOA1) that
provides model age values for model experiments (Garcia et al.,
2011).
Age of air has generally been derived from observations by treating SF6
as a passive (non-reactive) tracer. The assumption is that the global loss
rate is too slow to significantly affect the lifetime. This was confirmed by
Garcia et al. (2011) when only photolysis was included. However,
when loss via electron attachment is also considered, the lifetime may
become short enough that this assumption is no longer valid, in which case
the stratospheric mixing ratio would appear to correspond to an earlier
tropospheric mixing ratio than in reality. We have compared the passive
WACCM SF6 tracer with that subject to all loss processes, which yields
the new lifetime of 1278 years. The difference between these two tracers
indicates the error in the derived age of air that would arise in the real
atmosphere if SF6 is assumed to be a passive tracer. The error caused
by chemical removal can be expressed as
Δ(AoA)=AoA(reactive tracer)-AoA(passive
tracer),
where Δ(AoA) is the difference in the age of air value caused by
chemical loss, AoA(reactive tracer) is the calculated age of air considering
the chemical removal and AoA (passive tracer) is the value obtained from a
non-reactive tracer. The expression for the age of air at any point in the
stratosphere can be obtained from a simplified version of (Eq. 1) that is
derived from a Taylor series expansion, retaining only the linear term. It
is then expressed as
AoA=[(χ0(SF6)-χ(SF6))/r(SF6)],
where χ(SF6) and χ0(SF6) are the SF6 volume
mixing ratios at the actual and the reference (tropical tropopause) points,
respectively, while r(SF6) is the rate of increase in tropospheric SF6. In our simulations r(SF6) is 0.29 pptv yr-1 (Fig. 4), which is an approximation as the growth rate
is not constant in reality. Stiller et al. (2012) report a value of
0.24 pptv yr-1 based on observations over the MIPAS period. These two
simplifications will lead to deviations between WACCM and MIPAS age data. If Eq. (5) is substituted into Eq. (4) then the error in age of air will be
Δ(AoA)=(χ(SF6, passive)-χ(SF6, reactive))/r(SF6).
Integrated absorption cross sections for SF6 measured
in this work and ratios with values obtained by GEISA (Gestion et Etude des Informations Spectroscopiques Atmosphériques; Jacquinet-Husson et
al., 2011; Hurley, 2003; Varanasi, 2001) and HITRAN (HIgh-resolution TRANsmission molecular absorption database; Rothman et al., 2012).
Ratio of integrated cross sections
in this work to previous studies
Band limits
Integrated
Hurley
Varanasi
HITRAN
(cm-1)
cross section
(2003)
(2001)
(10-16 cm2
molec-1 cm-1)
925–955
2.02
1.07
1.01
0.99
650–2000
2.40
–
1.09
–
This error, along with the mean age itself was calculated from WACCM output
for 2007. Figure 7 shows the annual mean ages determined from the
WACCM simulation from 2002 to 2007 using the total reactive and the inert
SF6 tracers and the idealized AOA1 age tracer. There is a clear
difference between the age values derived from the passive SF6 and the
idealized AoA tracer. If Eq. (5) is used to determine the age values, there is no guarantee that the age values derived from the two tracers will
be identical; the rate was determined from the increase in the SF6
burden (0.29 pptv yr-1) and this was provided by the linear fit
(Fig. 4), which can misrepresent the growth rate at a specific
time. Figure 7 also shows the difference between the age values
obtained from the reactive and inert SF6 tracers. It can be seen that
consideration of the reactive SF6 tracer does indeed affect the
determined mean age values, mostly where electron attachment dominates. The
age estimates at high latitudes are most sensitive to chemical loss because
the air that reaches these locations has descended from the high altitudes
where SF6 loss predominantly occurs. According to the MIPAS satellite
observations (Stiller et al., 2012; Haenel et al., 2015.),
the derived age value over the tropical lower stratosphere at 25 km is
slightly more than 3 years, while the WACCM simulations with the reactive
SF6 tracer predicts 3 years. Comparing Fig. 7a and b, the effect of chemical removal in this region is minor (0.01-year or
0.5 % change), and therefore it does not have much impact on the inferred
atmospheric transport. At the poles the effect is much more significant; the
difference at 25 km between the reactive and inert SF6 tracers is up to
0.55 years (9 %). In summary, in the troposphere–stratosphere at low
latitudes, the effect of chemical removal is not very significant and the
error on the estimated mean age caused by the assumption of SF6 being a
passive tracer is not important. However, the effect of chemical removal
becomes more significant at high latitudes.
We can also compare modelled and observed mean age values in the lower
stratosphere (20 km). Figure 8 shows the mean age profiles from
WACCM tracers, ER-2 observations (Hall et al., 2009) and our
analysis of MIPAS SF6 satellite data at 20 km. From this it can be seen
that in the tropical region the mean age values are similar between the
idealized age tracer and the inert and reactive SF6 tracers. This is
consistent with no loss of SF6 having occurred in air parcels in the
deep tropics. At high latitudes there is an up to 0.5-year difference in the
modelled mean ages, with the reactive SF6 tracer producing the oldest
apparent age. The differences in mean age between the tracers is larger in
the SH polar region than in the NH because the polar region is less well
mixed. The tendency is very similar when we compare the WACCM mean ages to
the MIPAS observations. Note that the satellite observations show more
seasonal variability in the middle and high latitudes than in the tropics.
Calculated instantaneous and stratospheric adjusted
radiative forcings and radiative efficiencies of SF6 in clear and
all-sky conditions.*
Instantaneous
Stratospheric adjusted
Clear
All-sky
Clear
All-sky
Radiative forcing (m Wm-2)
76.43
48.91
81.81
56.01
Radiative efficiency (W m-2 ppbv-1)
0.77
0.50
0.85
0.59
* Based on present day atmospheric SF6 surface concentration of 9.3 pptv.
Comparison of 20-, 100- and 500-year global warming
potentials for SF6 from this work with values from IPCC (2013).
Global warming potential
GWP20
GWP100
GWP500
This worka
18 000
23 700
31 300
IPCC (2013)b
17 500
23 500
32 600c
Difference (%)
+3%
+1%
-4 %
(This work – IPCC)
a Based on our atmospheric lifetime of 1278 years and radiative efficiency (RE) of 0.59 W m-2 ppbv-1.
b Based on an atmospheric lifetime of 3200 years and RE of 0.57 W m-2 ppbv-1 .
c Based on an atmospheric lifetime of 3200 years and RE of
0.52 W m-2 ppbv-1 from IPCC AR4 (Forster et al., 2007).
Radiative efficiency and forcing
To determine the radiative efficiency and global warming potential of
SF6, integrated cross sections were taken from two public molecular
spectroscopic databases: (i) the GEISA-2009/2011 (Gestion et Etude des Informations Spectroscopiques Atmosphériques) spectroscopic database
(Jacquinet-Husson et al., 2011), which uses the data of Varanasi (2001) and Hurley (2003), and (ii) the HITRAN-2012 (HIgh-resolution TRANsmission molecular absorption database) molecular spectroscopic
database (Rothman et al., 2012), which uses the data of the Pacific
Northwest National Laboratory Infra-Red Database (Sharpe et al.,
2004). Values were also measured in this study. The literature values are
presented in Table 4 for comparison with our experimentally
determined values, and the full SF6 spectrum obtained in this study is
given in Fig. 9. In our study the spectrometer error is ±1.0 % for all experiments, and the uncertainty in the sample
concentrations of SF6 was calculated to be 0.7 %. Spectral noise was
averaged at ±5 × 10-21 cm2 molecule-1 per 1 cm-1 band. However, at wavenumbers < 550 cm-1, towards
the edge of the mid-infrared where opacity of the KBr optics increases, this
value was 1 × 10-20 cm2 molecule-1 per 1 cm-1 band. The error from determining the scaling cross section was 5 %. This
results in an average overall error of ±5 % in the cross sections.
The intensities of the main SF6 absorption bands (925–955 cm-1)
measured in this study are 7 % greater than those reported by Hurley (2003), 1 % greater than Varanasi (2001) and 1 % lower than those given
in HITRAN (Rothman et al., 2012; Table 4). Comparison of
our results to Varanasi (2001) between 650 and 2000 cm-1 gives an
agreement within 9 %. Note that these differences are within the combined
error of both experiments.
The instantaneous and stratospheric adjusted SF6 radiative efficiencies
in clear and cloudy-sky conditions are given in Table 5. These are
also presented as present-day radiative forcings employing a current surface
concentration of 9.3 pptv (NOAA, 2016; see Fig. 4). The
radiative efficiency was calculated in the RFM for each month between
90∘ S and 90∘ N at latitudinal resolutions
(on which the data were averaged to obtain the zonal mean vertical profile)
of 1.5 and 9.0∘. The tropopause used the standard WMO lapse rate
definition (see Totterdill et al., 2016). Figure 10 shows
the seasonal–latitudinal variation of the instantaneous clear-sky radiative
forcing for SF6 on the high- (1.5∘) and low- (9∘) resolution grids. Employing profiles averaged over the
lower-resolution grid gives an average forcing within 1 % of the higher-resolution grid. Using only a single annually averaged global mean profile
led to a 10 % error in radiative forcing when compared to our monthly
resolved high-resolution profile, supporting the findings of Freckleton
et al. (1998) and Totterdill et al. (2016).
A selection of experiments were carried out over a range of months and
latitudes to investigate the sensitivity of the forcing calculations to the
bands used. The average contributions from the main bands were compared
to the calculation with the full measured spectrum. The results showed
that the 580–640 and 925–955 cm-1 bands contribute almost 99 %
to the instantaneous radiative forcing. Our forcing calculations suggest
that the SF6 minor bands contribute only a small amount to the final
value. This means that deviations between our experimentally determined
spectra and those in the literature only result in a significant change to
previously published radiative forcings and efficiencies when that deviation
occurs over a major band.
The SF6 adjusted cloudy-sky radiative efficiency published by the IPCC
AR5 report and used to determine its GWP values is 0.57 W m-2 ppbv-1 (Myhre et al., 2013). This compares to our
adjusted cloudy-sky radiative efficiency of 0.59 W m-2 ppbv-1
(Table 5). A review on radiative efficiencies and global warming potentials
by Hodnebrog et al. (2013) provides a comprehensive list of all
published values for these parameters for many species including SF6.
They established the range of published radiative efficiencies for SF6
to be 0.49–0.68 W m-2 ppbv-1, with a mean value of 0.56 W m-2 ppbv-1. They also made their own revised estimate using an
average of the HITRAN (Rothman et al., 2012) and GEISA
(Jacquinet-Husson et al., 2011) spectral databases and found a best estimate
of (0.565 ± 0.025) W m-2 ppbv-1. Their mean value for
radiative efficiency is very close to that determined in this study using
similar conditions (0.59 W m-2 ppbv-1).
Global warming potential
Table 6 gives our estimates of the 20-, 100- and 500-year GWPs based
on cloudy-sky adjusted radiative efficiencies of SF6 compared with
IPCC AR5 values (IPCC, 2013). Our 20-, 100- and 500-year global warming
potentials for SF6 are 18 000, 23 800 and 31 300, respectively. The
20- and 100-year values are 3 % greater and 1 % greater,
respectively, than their IPCC counterparts, and the 500-year GWP is 4 %
smaller than its AR4 counterpart (Forster et al., 2007). The
forcing efficiencies determined in this study are somewhat higher than the
previously published values (see Sect. 3.4), which would imply a higher
GWP value. However, our shorter atmospheric lifetimes would lead to a
smaller GWP estimate, with a larger effect on longer time horizons when
atmospheric loss becomes relevant. The trade-off between these competing
effects is apparent in Table 6, where SF6 exhibits a 20-year
GWP that is slightly larger than the IPCC value, while the 500-year GWP is
slightly smaller. The radiative efficiency effect is most obvious for the
case of the 20-year GWP where, because the atmospheric lifetime of SF6
is 1278 years, the species does not have time for any significant loss to
occur.
Conclusions
The 3-D Whole Atmosphere Community Climate Model was used to simulate the
SF6 atmospheric distribution over the period of 1995–2007. From the
concentrations and the knowledge of the electron attachment, photolysis and
metal reaction rates we determined the atmospheric lifetime, which shows a
significant dependence (-12 to +15 %) on the solar cycle due to
varying electron density. The mean SF6 atmospheric lifetime over a solar cycle was determined to be 1278 years
(ranging from 1120 to 1475 years), which is different to previously reported
literature values and much shorter than the widely quoted value of 3200
years. The reason is our more detailed treatment of electron attachment
using a new formalism to describe both associative and dissociative
attachment and the use of a detailed model of D region ion
chemistry to evaluate the partitioning of electrons and negative ions below
80 km. Further refinement to this lifetime estimate from modelling studies
depends on decadal length simulations of the model with detailed ion
chemistry for the realistic long-term estimation of electron density in the
upper atmosphere without the need for scaling factors as employed here.
Based on this new estimate of the SF6 lifetime, we find that the
derived mean age of stratospheric air from observations can be slightly
affected by the atmospheric removal of SF6. In the polar region the
age of air values differ by up to 9 % when the values from inert and
reactive model tracers are compared, suggesting that SF6 loss does not
have a large influence on the age values but that it should be included in
detailed analyses.
We also reinvestigated the radiative efficiency and global warming
potential of SF6. Our radiative efficiency value reported here, 0.59 ± 0.045 W m-2 ppbv-1, is slightly higher than the IPCC AR5
estimate of 0.57 W m-2 ppbv-1. The global warming potentials of
SF6 for 20, 100 and 500 years have been determined to be 18 000, 23 800
and 31 300, respectively. We find that our revised lifetime and efficiency
values cancel each other out somewhat, so overall do not play a significant
role in modifying the GWP estimates on these time horizons.