ACPAtmospheric Chemistry and PhysicsACPAtmos. Chem. Phys.1680-7324Copernicus PublicationsGöttingen, Germany10.5194/acp-18-13135-2018Quantifying the vertical transport of CHBr3 and CH2Br2 over the western PacificCHBr3 and CH2Br2 over western PacificButlerRobynPalmerPaul I.pip@ed.ac.ukhttps://orcid.org/0000-0002-1487-0969FengLiangAndrewsStephen J.AtlasElliot L.https://orcid.org/0000-0003-3847-5346CarpenterLucy J.https://orcid.org/0000-0002-6257-3950DonetsValeriaHarrisNeil R. P.https://orcid.org/0000-0003-1256-3006MontzkaStephen A.https://orcid.org/0000-0002-9396-0400PanLaura L.SalawitchRoss J.SchaufflerSue M.School of GeoSciences, University of Edinburgh, Edinburgh, UKDepartment of Chemistry, Wolfson Atmospheric Chemistry
Laboratories, University of York, York, UKUniversity of Miami, Department of Atmospheric Science, Miami, Florida, USADepartment of Chemistry, University of Cambridge, Cambridge, UKNational Oceanic and Atmospheric Administration, Boulder, Colorado, USANational Center for Atmospheric Research, Boulder, Colorado, USAUniversity of Maryland, Department of Atmospheric and Oceanic Science, College Park, Maryland, USAnow at: Centre for Atmospheric Informatics and Emissions Technology, Cranfield University, Cranfield, UKPaul I. Palmer (pip@ed.ac.uk)12September20181817131351315320October201629November20162July20184July2018This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/3.0/This article is available from https://acp.copernicus.org/articles/18/13135/2018/acp-18-13135-2018.htmlThe full text article is available as a PDF file from https://acp.copernicus.org/articles/18/13135/2018/acp-18-13135-2018.pdf
We use the GEOS-Chem global 3-D atmospheric chemistry transport model to
interpret atmospheric observations of bromoform (CHBr3) and
dibromomethane (CH2Br2) collected during the CAST and CONTRAST
aircraft measurement campaigns over the western Pacific, January–February 2014. We use a new linearized, tagged version of CHBr3 and
CH2Br2, allowing us to study the influence of emissions from
specific geographical regions on observed atmospheric variations. The model
describes 32 %–37 % of CHBr3 and 15 %–45 % of
CH2Br2 observed variability during CAST and CONTRAST, reflecting
model errors in vertical transport. The model has a mean positive bias of
30 % that is larger near the surface, reflecting errors in the poorly
constrained prior emission estimates. We find using the model that observed
variability of CHBr3 and CH2Br2 is driven by open ocean
emissions where there is deep convection. Atmospheric variability above
6 km includes a significant contribution from coastal oceans, but it is
still dominated by emissions from the open ocean and by older air masses that
originate upwind. In the absence of reliable ocean emission estimates, we use
a new physical age-of-air simulation to determine the relative abundance of
halogens delivered by CHBr3 and CH2Br2 to the tropical
transition layer (TTL). We find that 76 % (92 %) of air masses that
originate from the ocean reach the TTL within two (three) atmospheric
e-folding lifetimes of CHBr3 and almost all of them reach the TTL
within one e-folding lifetime of CH2Br2. Over the duration of
CAST and CONTRAST, and over our study region, oceans delivered a mean (range)
CHBr3 and CH2Br2 mole fraction of 0.46 (0.13–0.72) and
0.88 (0.71–1.01) pptv, respectively, to the TTL, and a mean (range) Bry
mole fraction of 3.14 (1.81–4.18) pptv from source gases to the upper
troposphere.
Introduction
Halogenated very short-lived substances (VSLSs) are gases that have a
tropospheric e-folding lifetime of <6 months. This lifetime is shorter than
the characteristic timescale associated with atmospheric transport of
material from the surface to the tropopause. Natural sources of VSLSs
represent a progressively larger fraction of the inorganic halogen budget in
the stratosphere that drives halogen-catalysed ozone loss, as anthropogenic
halogenated compounds continue to decline in accordance with international
agreements. Quantifying the magnitude of and variation in these natural VSLS
fluxes to the stratosphere is therefore a research priority for environmental
science. VSLSs include a wide range of gases such as bromoform
(CHBr3), dibromomethane (CH2Br2), bromochloromethane
(CH2BrCl), dibromochloromethane (CHBr2Cl), and
bromodichloromethane (CHBr2Cl). Here we focus on CHBr3 and
CH2Br2, which collectively represent >80 % of the organic
bromine in the marine boundary layer and upper troposphere and are dominated
by marine sources . We use aircraft observations of
CHBr3 and CH2Br2 collected over the western Pacific in
January and February 2014 to quantify the regional flux of these compounds to
the stratosphere.
The main sources of CHBr3 and CH2Br2 include
phytoplankton, particularly diatoms, and various species of seaweed
. The magnitude and distribution
of these emissions reflect supersaturation of the compounds and nutrient-rich
upwelling waters . Tropical, subtropical, and shelf waters
are important sources of CHBr3 and CH2Br2 with high
spatial and temporal variability . Current emission
inventories, informed by sparse ship-borne data, have large uncertainties
.
The atmospheric lifetime of CHBr3 is ∼ 24 days, determined
primarily by photolysis and to a lesser extent by OH oxidation.
CH2Br2 has an atmospheric lifetime of ∼ 123 days determined
by OH oxidation .
Vertical ascent of CHBr3 and CH2Br2 and their oxidation
products to the upper troposphere–lower stratosphere (UTLS) represent a
source of bromine that acts as a catalyst for ozone loss in the stratosphere.
Balloon-borne and satellite observations estimate that brominated VSLSs and
their degradation products contribute 2–8 ppt to stratospheric Bry.
Model estimates range between 2 and 7 ppt for this contribution
. This
contribution mainly originates from areas of deep convection over the
tropical Indian ocean, over the western Pacific, and off the Pacific coast of Mexico
. The
stratospheric community has categorized two methods of delivering VSLSs to the
stratosphere: (1) source gas injection (SGI), which describes the direct
transport of the emitted halogenated compounds (e.g. CHBr3 and
CH2Br2), and (2) product gas injection (PGI), which refers to the
transport of the degradation products of these emitted compounds. Previous
model-based calculations
have estimated that
15 %–75 % of the stratospheric inorganic bromine budget from VSLSs is
delivered by SGI, with uncertainty of the total Bry reflecting uncertainty
of wet deposition of PGI product gases in the UTLS
.
The tropical tropopause layer (TTL) represents a gradual transition from the
troposphere to the stratosphere . It extends
over a few kilometres within the upper troposphere between where the
atmospheric lapse rate is at a minimum (∼12–13 km) and the cold point
tropopause (∼17 km) . The TTL is the dominant
transport pathway for SGI and PGI gases to the lower stratosphere. TTL
temperatures vary zonally, with the smallest values between
130 and 180∘ E throughout the year, corresponding to the
tropical warm pool over the western Pacific where convective activity is
largest . Estimates of SGI within this region are highly
dependent on the strength and spatial variability of source regions, and how
they couple with atmospheric transport mechanisms.
We use data from two coordinated aircraft campaigns over the western Pacific
during 2014, the Coordinated Airborne Studies in the Tropics (CAST,
) and the CONvective Transport of Active Species in the
Tropics (CONTRAST, ), to study the emission, vertical
transport, and chemical transformation of halogenated gases. The CAST and
CONTRAST campaigns measured a suite of trace gases and aerosols centred on
the Micronesian region in the western Pacific, including Guam, Chuuk, and
Palau during January and February 2014. We interpret aircraft measurements of
CHBr3 and CH2Br2 mole fraction using the GEOS-Chem
atmospheric chemistry transport model.
In the next section we describe CAST and CONTRAST and the data we used.
Section describes the GEOS-Chem model and how it is used to
interpret the airborne data. In Sect. we evaluate the
model and describe our results. We conclude the paper in Sect. .
Observational dataCAST and CONTRAST CHBr3 and CH2Br2 mole fraction data
We use CHBr3 and CH2Br2 mole fractions from the CAST and
CONTRAST aircraft campaigns . Here for the sake of
brevity we provide only brief details about the CHBr3 and
CH2Br2 data and refer the reader to for a
more comprehensive description of the data collection and analysis procedures
used during the campaigns.
Measurement distribution of CHBr3 and CH2Br2
mole fractions from the CAST (a) and CONTRAST (b) aircraft
campaigns as a function of altitude (km). Relevant island waypoints are shown
inset: Guam (G), Palau (P), and Chuuk (C).
Figure shows the spatial distribution of whole air
samples (WASs) collected during CAST and CONTRAST. For CAST, WAS canisters
were filled aboard the Facility for Airborne Atmospheric Measurements (FAAM)
BAe-146 aircraft. These canisters were analysed for CHBr3 and
CH2Br2 and other trace compounds within 72 h of collection.
The WAS instrument was calibrated using the National Oceanic and Atmospheric
Administration (NOAA) 2003 scale for CHBr3 and the NOAA 2004 scale
for CH2Br2. For CONTRAST, a similar WAS system was employed to
collect CHBr3 and CH2Br2 measurements on the NSF/NCAR
Gulfstream-V HIAPER (High-performance Instrumented Airborne Platform for
Environmental Research) aircraft. A working standard was used to regularly
calibrate the samples, and that working standard was calibrated using a
series of dilutions of high concentration standards that are linked to
National Institute of Standards and Technology standards. The mean absolute
percentage error for CHBr3 and CH2Br2 measurements
between 0 and 8 km is 7.7 % and 2.2 %, respectively, representing the combined
error between the two WAS systems and two accompanying GC/MS instruments.
Mean measurement statistics for CHBr3 and
CH2Br2
mole fraction data as a function of altitude for CAST and CONTRAST
aircraft campaigns. x‾, σ, and n denote the
mean value, the standard deviation, and the number of data points
used to determine the statistics.
AltitudeCHBr3CH2Br2CAST CONTRAST CAST CONTRAST (km)x‾1σ& range (ppt)nx‾1σ& range (ppt)nx‾1σ& range (ppt)x‾1σ& range (ppt)0–20.950.450.42–3.005020.890.230.51–1.55751.010.130.72–1.641.070.110.83–1.272–40.610.160.29–0.981470.620.180.29–1.24480.910.050.73–1.060.940.090.78–1.134–60.440.170.03–0.79590.560.180.20–1.127430.850.110.63–1.060.900.100.70–1.066–80.380.250.02–0.81530.600.200.24–1.01430.850.110.63–1.060.900.100.70–1.068–100.480.340.14–0.8220.620.170.24–1.00430.900.130.77–1.030.930.090.72–1.0710–13––––0.590.250.00–1.38130–––0.870.190.21–1.10TTL––––0.480.160.18–1.17280–––0.860.080.64–1.06
Table shows mean measurement statistics of
CHBr3 and CH2Br2 for the CAST and CONTRAST campaigns.
CHBr3 is generally more variable than CH2Br2 throughout
the study region, reflecting its shorter atmospheric lifetime, so that
sampling differences between CAST and CONTRAST will introduce larger
differences for this gas. CAST measurements of CHBr3 are typically
lower than for CONTRAST, but CAST recorded the highest and lowest
CHBr3 mole fractions at 0–2 and 6–8 km, respectively. We
define the TTL from 13 km to the local tropopause determined
from the GEOS5–FP-analysed meteorological fields, as described below.
CONTRAST measured a minimum CHBr3 value indistinguishable from zero
just below the TTL at 10–13 km. Measurements of CH2Br2 are
generally consistent between CAST and CONTRAST at all altitudes. There is
only a small vertical gradient for CH2Br2 above 2 km with a
mean value of ∼ 0.91 pptv. CONTRAST measured the lowest value of
0.21 pptv just below the TTL. Within the TTL, CONTRAST reports mean
(maximum) values of 0.42 pptv (0.85 pptv) and 0.84 pptv (1.05 pptv) for
CHBr3 and CH2Br2, respectively, providing some evidence
of rapid convection of surface emissions to the upper troposphere.
Location and code of NOAA/ESRL ground-based stations.
Table summarizes the independent surface measurements
of CHBr3 and CH2Br2 collected by the NOAA Earth System
Research Laboratory (ERSL), which we have used to evaluate the GEOS-Chem atmospheric
chemistry model simulation on a global scale. This evaluation was undertaken
to report on model performance and is not used to provide additional data
over the western Pacific.
These measurements are part of the ongoing NOAA/ESRL global monitoring
program (https://www.esrl.noaa.gov/gmd/, last access: 4 September 2018). CHBr3 and CH2Br2
measurements are obtained approximately weekly using paired steel flasks,
which are then analysed by GC/MS. Further details about their sampling are
given in . In Appendix , we evaluate the
model using mean monthly statistics at each site from 1 January 2005 to 31
December 2011.
The GEOS-Chem global 3-D atmospheric chemistry transport model
To interpret CAST and CONTRAST data we use v9.02 of the GEOS-Chem global 3-D
atmospheric chemistry transport model (www.geos-chem.org, last access: 4 September 2018), driven by
GEOS5–FP-analysed meteorological fields provided by the Global Modelling and
Assimilation Office (GMAO) at NASA Goddard Space Flight Centre. For our
experiments we degrade the native meteorological fields to a model horizontal
spatial resolution of 2∘ latitude × 2.5∘ longitude
described on 47 vertical levels, with a top pressure of 0.01 hPa. Dynamic
tropopause height and convective mass flux (CMF) from the meteorological
fields are given on a 1-hourly and 3-hourly averaging period, respectively.
Below we describe two new GEOS-Chem simulations that we developed to
interpret observed variations in CHBr3 and CH2Br2 during
CAST and CONTRAST airborne campaigns: (1) a tagged simulation of CHBr3
and CH2Br2 to better understand source attribution, and (2) an
age-of-air simulation to improve understanding of the vertical transport of
these short-lived halogenated compounds. For both simulations, we sample the
model at the time and location of CAST and CONTRAST observations.
Tagged CHBr3 and CH2Br2 simulation
The purpose of this simulation is to relate observed atmospheric variations
to surface emissions from individual sources and/or geographical regions. To
achieve this we use pre-computed monthly 3-D fields of OH and photolysis
rates for CHBr3 and CH2Br2 from the full-chemistry
version of GEOS-Chem, allowing us to linearize the chemistry so that we can
isolate the contributions from individual sources and geographical regions.
The structure of the model framework follows closely other tagged simulations
within GEOS-Chem (e.g. ). We
use the following temperature-dependent (temperature is denoted by T) reaction rate constants that
describe oxidation of CHBr3 and CH2Br2 by OH
: for CHBr3,
k(T)=1.35×10-12exp(-600/T) cm3 molec-1 s-1; and for
CH2Br2, k(T)=2.00×10-12exp(-840/T) cm3 molec-1 s-1.
Surface emissions of CHBr3 (1013 kg m-2 s-1)
and CH2Br2 (1014 kg m-2 s-1) taken from
for the time and study domain of the CAST and CONTRAST
campaigns.
Figure shows the magnitude and spatial
distribution of our prior emissions of CHBr3 and CH2Br2. These emission estimates were derived from airborne
measurements in the troposphere and lower stratosphere over the western Pacific and North America. has global annual totals of
425 Gg Br yr-1 for CHBr3 and 57 Gg Br yr-1 for
CH2Br2. These emissions integrated over the geographical region
and duration of the campaign are 3 and 0.4 Gg Br yr-1
for CHBr3 and CH2Br2, respectively. We temporally
distribute emissions every 30 min without any diurnal variation. We found
that other commonly used emission inventories for CHBr3 and
CH2Br2 (e.g. and ) were
not noticeably better than at describing the CAST and
CONTRAST data (not shown). We chose to use because it has a
consistent bias for CHBr3 and CH2Br2.
Flux of CHBr3 from total, open, and coastal ocean tracers.
Relevant island waypoints are shown inset: Guam (G), Palau (P), and Chuuk
(C).
Figure shows the ocean (open and coastal) tagged
tracer regions we use in the GEOS-Chem model. These geographical definitions
are informed by the NOAA ETOPO2v2 Global Relief map , which
combines topography and ocean depth data at 2 min spatial resolution:
heights between 0 and -200 m are defined as coastal oceans, and heights below
-200 m are open ocean. Each 2 min cell that falls within a model grid box
is assigned a coastal or open ocean. Each model grid box can then be
described as fractional contributions (Rx) to the open and coastal ocean
tagged regions. We have explicitly included elevated coastal emissions from
the inventory in the coastal tracer. We assign individual tracers to major
islands within our study domain, including Guam (13.5∘ N,
144.8∘ E), Chuuk (7.5∘ N, 151.8∘ E), Palau (7.4∘ N,
134.5∘ E), and Manus (2.1∘ S, 147.4∘ E). We assume these island land
masses account for 100 % of a grid box irrespective of whether their area
fills the grid box. This gives a total of 18 tagged tracers, evenly split
between CHBr3 and CH2Br2, including a total tracer and a
background tracer.
For global model evaluation using the NOAA data, described above, we
initialize model tagged tracers in January 2004 with near-zero values and run
the simulation to January 2013. We discard the first model year to minimize
the impact of the initial conditions. For model evaluation using the
CAST/CONTRAST data, we initialize the tagged tracers in January 2014 with
near-zero values. Background initial conditions were determined from a
12-month integration of the full-chemistry model, which are then, in the
tagged model, subject to atmospheric transport and loss processes. For model
evaluation, we sample at the time and location of each observation. For the
NOAA data described above, we calculate monthly mean statistics from 1 January 2005 to 31 December 2011.
Physical age-of-air model calculation
We use the age-of-air simulation to understand how short-lived halogenated
compounds are transported to the TTL, independent of emission inventories.
The method uses only knowledge of the distribution of emissions, and not the
magnitude, so we can investigate the
influence of the emissions source region with respect to respective
CHBr3 and CH2Br2 atmospheric e-folding lifetimes. We
use the GEOS-Chem model to determine the physical age of air A, building on
previous studies , and we use a consistent set of
geographical regions in our tagged CHBr3
and CH2Br2 simulations (Fig. ).
For each model tracer we define a surface boundary volume mixing ratio B
that linearly increases with time t so that smaller values correspond to
older physical ages:
B=f×t,
where f is a constant (1 × 10-15 s-1). B describes a volume
mixing ratio of each tracer dependent on their time of emission. Fractional
contributions of tracers are calculated based on Rx, where the finalized
B (Bfinal) in the surface boundary condition is calculated
using the following:
Bfinal=(B×Rx)+(1-Rx×X),
where X denotes the mixing ratio of tracers within the grid box. As time
progresses, smaller volume mixing ratios represent older air that has spent
more time away from the surface boundary.
We initialize this model in July 2013 and run for 6 months until the start
of January 2014 so that at least one e-folding lifetime of
CH2Br2 has been achieved. We then sample the resulting 3-D field
of model tracer mixing ratios (X), at the time and location of CAST and
CONTRAST measurements. The physical age of a tracer A since it last came
into contact with a ocean surface is given by the following:
A=t-X/f.
We account for atmospheric dispersion by using the GEOS-Chem model, but we do
not consider any chemical losses.
To explicitly evaluate marine convection in GEOS-Chem we also developed a
short-lived tagged tracer simulation with an e-folding lifetime of 4 days,
comparable to that of methyl iodide (CH3I) in the tropics
. We emit the tracer with an equilibrium mole fraction
of 1 pptv over all oceanic regions described in Fig. . We initialize the model on 1 January 2014 with an
empty 3-D atmospheric field and run for 2 months until 1 March 2014. Model
output is archived every 2 h and the model is sampled along the
aircraft flight tracks. By comparing our model with CH3I observations, we
find that GEOS-Chem captures mean marine convective flow over the study
region. We also find that the model captures fast, infrequent, large-scale
convective transport that results in upper tropospheric ages of 3–5 days, but
does not capture small-scale variations due to rapid convection. Appendix
includes a more detailed report on the results.
ResultsModel evaluation
We evaluate our tagged model of atmospheric CHBr3 and
CH2Br2 using NOAA surface data, and CAST and CONTRAST aircraft
data during January and February 2014.
Model evaluation using the NOAA data is described in Appendix .
In brief, the model generally has a positive bias but reproduces 30 %–60 % of
the seasonal variation (Pearson correlation coefficients in Table ),
depending on geographical location.
Model errors in reproducing the observed seasonal cycle reflect errors in
production and loss rates. The model generally has less skill at reproducing
observations collected at coastal sites close to emission sources.
Seasonal mean statistics for NOAA ground station sites
(Table ) showing Pearson correlations, r2, between
observed and climatological monthly mean CHBr3 and
CH2Br2 mole fraction data, and corresponding model biases.
CHBr3CH2Br2DJF MAM JJA SON DJF MAM JJA SON Stationr2%biasr2%biasr2%biasr2%biasr2%biasr2%biasr2%biasr2%biasALT0.003.80.550.10.055.50.4319.30.0912.40.210.00.2310.00.3121.0SUM0.0525.10.01-17.10.23-12.00.5420.60.06-2.70.15-13.00.154.80.607.0BRW0.00-41.30.52-30.20.13-26.50.80-26.50.159.50.07-8.70.00-4.40.1415.9MHD0.00-40.80.18-72.40.04-80.60.08-61.20.05-20.50.11-35.90.14-42.70.03-16.8LEF0.0345.70.0115.50.0339.30.7351.20.1713.40.253.10.4418.20.6620.8HFM0.0652.20.0130.10.1546.90.3852.30.0320.00.069.30.2227.10.4525.7THD0.1955.30.1515.80.3611.70.1740.20.0916.90.060.90.018.60.0618.0NWR0.0243.30.4925.90.0121.80.3138.70.202.30.554.90.4011.90.5514.7KUM0.0020.20.37-1.90.050.90.016.80.25-0.30.504.40.4715.60.389.9MLO0.1861.90.6060.30.0265.10.5864.70.1414.80.3215.20.2122.80.2725.0SMO0.238.20.02-4.90.043.00.114.70.396.90.38-0.90.19-0.20.095.6CGO0.23-39.00.01-12.80.057.70.00-19.60.13-8.70.13-1.60.04-1.40.12-9.5PSA0.19-13.90.2526.40.0131.70.05-1.90.00-1.70.2911.70.1510.30.05-2.0SPO0.506.60.126.70.0719.20.11-7.30.014.80.064.60.113.70.00-0.6
Comparison of model and observed (a, c, e)CHBr3
(pptv) and (b, d, f)CH2Br2 (pptv) mole fraction data
for CAST (denoted by blue) and CONTRAST (denoted by red). Panels (a, b) describe
the comparison between model (dotted line) and observed (solid line) values
as a box-and-whiskers plot on 2 km altitude bins. Panels (c, d) describe
the model and data comparison as a scatter plot. Pearson correlations (r2)
and percentage biases are shown inset. Black, red, and blue dashed lines
denote the 1 : 1 line, and the best fit linear models for CONTRAST and CAST,
respectively. Panels (e, f) show the relative model error, described as a
box-and-whiskers plot on 2 km altitude bins. The vertical dashed line
denotes the zero error line.
Figure shows that CAST and CONTRAST observed
and model vertical profiles CHBr3 and CH2Br2 have an
inverted “S” shape . This suggests that GEOS-Chem
has skill in describing the broad-scale atmospheric transport over the
study region. From Pearson correlation coefficients, we find that GEOS-Chem
reproduces more than 30 % of the observed variability of CHBr3
from CAST and CONTRAST and between 15 % (CAST) and 45 % (CONTRAST) of
the observed variability of CH2Br2. Larger differences in the
correlations for CH2Br2 is likely due to differences in the
sampled air masses that have originated far upwind.
Figure also shows that GEOS-Chem has a
positive model bias of 30 % for both campaigns, which we calculate using
100/NiΣi(modi-obsi)/(max(modi,obsi)). The relative
model error is reasonably constant with altitude for CHBr3 and
CH2Br2, suggesting that this bias is representative of prior
surface emissions. Consequently, we remove this bias from subsequent
calculations. We attribute the variations about the mean bias to errors due
to model atmospheric transport.
Model mole fractions (pptv) of CHBr3 over the study domain
as a function of altitude, averaged between 18 January 2014 and 28 February 2014,
from the total (column 1), open (column 2), and coastal ocean
(column 3) tagged tracers. The corresponding mean model convective mass
flux (kg m-2 s-1) is shown in column 4. Tagged tracers are averaged
from 2 h fields and convective mass fluxes are averaged from
daily fields.
Tagged-VSLS model output
Figures and show a
strong region of convection south of Chuuk and along the Equator that
transports CHBr3 and CH2Br2 directly from open oceanic
emission sources to the mid-troposphere. Above the mid-troposphere (10 km)
convective mass fluxes get smaller and advection plays a more important role
in distributing the gases. This results in an inverted “S” shape in the
vertical profiles of CHBr3 and CH2Br2, as discussed
above. There is also a strong convection region west of Papua New
Guinea and the north of Australia, which transports coastal emissions to the mid-troposphere and
upper troposphere.
As Fig. but for CH2Br2 (pptv).
The percentage contributions from total ocean, open oceans, and
coastal oceans to total (a)CHBr3 and
(b)CH2Br2 described as a box-and-whiskers plot on
1 km altitude bins.
Probability density functions of the age of air A for
(blue) total ocean, (green)
open oceans, and (black) coastal ocean tracers, described as 2 km altitude regions from the surface
to the TTL (13 km to the tropopause) averaged over the whole study domain between 18 January 2014 and 28 February 2014.
Model mean mole fractions of CHBr3 are ≃ 1.4 ppt throughout the
boundary layer (0–2 km), determined by open ocean emissions, but fall off
rapidly as a function of altitude due to chemical losses. At the TTL over the
study domain and during the campaign period, mean CHBr3 mole
fractions range 0.4–0.6 ppt mainly due to open ocean emissions. Coastal
emissions are typically much larger than open ocean emissions but they play a
much smaller role in observed variations throughout the troposphere, except
over the strong convective regions over Papua New Guinea and the north of Australia.
Prevailing easterly transport of gases over the region is dominated by the
vast area of open ocean sources that appear to weaken the magnitude of
spatially limited coastal emissions . The vertical
and spatial distributions of CH2Br2 mole fractions are
consistent with CHBr3, although they deplete less rapidly with
altitude by virtue of its longer atmospheric lifetime. At the TTL, averaged
over the campaign study, CH2Br2 mole fractions range
0.1–0.3 ppt mainly due to smaller magnitude of ocean emissions compared to
CHBr3. Coastal sources contribute up to 0.1 ppt of
CH2Br2 in the TTL, with the remaining originating from an open
ocean source.
Figure shows that ocean emissions provide the largest
fractional contribution to CHBr3 during CAST, typically more than
80 % throughout the low to mid troposphere, with the remainder originating
from emissions prior to the campaigns. This is dominated by open ocean
emissions that range between 50 % and 70 % of the total tracer. Coastal ocean emissions
represent a smaller contribution to CHBr3 at lower altitudes, but
increase their influence above 6 km in the CONTRAST data with contributions
from geographical regions immediately outside the study region that reach a
maximum of 60 % of the total CHBr3 tracer in the TTL. This results in
an inverted “S” shape observed over the vertical profile, which is described
above. Island land masses generally represent only a minor contribution to
the vertical profile at our model resolution, and we have excluded them from
further analysis.
The ocean, in particular the open ocean, represents the largest contributions
to total CH2Br2 over the campaign period. They typically
represent 20 % of the total CH2Br2 and reach a maximum of
28 % in the TTL for the CONTRAST measurements. Maximum contributions of
coastal emission sources peak at 15 % of total CH2Br2 tracer in
the TTL, much less than for CHBr3. The remaining contributions are
representative of emissions prior to the campaign period.
Different CHBr3 and CH2Br2 emission scenarios
vary with spatial distribution and magnitude
of coastal and open ocean emissions, leading to uncertainties of atmospheric
mixing ratios . This would have
implications for results presented here, as source region mixing ratios will
vary depending on the emission scenario used. We developed the age-of-air
calculation to ascertain the influence of ocean emission regions independent
of emission scenarios.
Physical age of air
Figure shows that the air masses over the open
ocean study domain are responsible for the youngest air throughout the
troposphere. Coastal ocean contributions are only present in the younger age
profile up to 4 km. At progressively higher altitudes the probability
distribution shifts towards older ages, as expected, corresponding to longer
periods from the point of contact with the surface. However, at 10–13 km we
see a noticeable shift towards younger ages, reflecting the peak of the
convective outflow of surface air. Within the TTL, mean age increases to a
value greater than the e-folding lifetime of atmospheric
CHBr3. However, we find, using our CH3I–like tracer (mean
lifetime of approximately 4 days), that air masses can be transported to
the TTL within 3–5 days but these are infrequent events and so are not easily
observed (Appendix ).
As Fig. but sampled along CAST and
CONTRAST flight tracks.
Box-and-whiskers plot of model CHBr3 mole fractions from
the entire ocean tracer as a function of 2 km altitude intervals and
a nominal 24-day e-folding lifetime (τ). Data are averaged over
18 January–28 February 2014 and over 10∘ S–30∘ N,
125–175∘ E. Blue values correspond to results determined by all available data,
and red values correspond to results determined by convective mass fluxes >95th percentile. Solid
lines denote the percentage of occurrence rate over the period and
region denoted above. Percentage of occurrence rate refers to how often air masses fall within the specified age range.
Assuming an indicative e-folding atmospheric lifetime τ of 24 days for
CHBr3 and 123 days for CH2Br2, we calculate that the
majority of air over the ocean has an age within
3τCHBr3 and 1τCH2Br2. We find that 76 %
(92 %) of oceanic emissions reach the TTL within 2τCHBr3
(3τCHBr3), with 64 % (88 %) of open ocean emissions and 9 %
(50 %) of coastal emissions being transported in the same time frames. The
corresponding statistics for CH2Br2 are 99 % of air over
the ocean reaches the TTL within 1τCH2Br2, and 99 % (97 %)
of air emitted from the open (coastal) ocean.
Figure shows that the atmospheric sampling
adopted by the CAST and CONTRAST campaigns captures a similar distribution of
physical ages discussed above. CAST represents a profile dominated within the
boundary layer, with CONTRAST more representative of age profiles outside of
the boundary layer that reflects its more extensive horizontal and vertical
sampling domain. Despite intensive measurements around coastal land masses of
the region, CAST did not capture coastal emissions very well. This is
reflective of a model resolution that is too coarse to capture such localized
effects on a sub-model grid scale.
Figure shows mixing ratios of
CHBr3 decreasing with altitude, but remaining fairly constant with
increasing age within each altitude range. Coastal emissions are associated
with the highest surface emissions but they are also subjected to slow ascent
rates and consequently greater photochemical losses. In contrast, open ocean
emissions are lower than coastal emissions but are convected more rapidly and
subject to less chemical loss. Consequently, CHBr3 appears to be
insensitive to age. From our analysis, we found that CHBr3 values are
determined mainly by younger air masses from the open ocean (Fig. ). Within the TTL, higher median mole fractions are
associated with the highest model convective mass flux in each age bin. The
peak frequency for the mean age of air in the TTL is 48–72 days,
corresponding to 3τCHBr3 and median values of 0.5 pptv
CHBr3 from oceanic emission sources, and 0.6 pptv in high convective
systems. However, less than 0.5 % (2 %) of air being transported to the TTL
within 24–48 (48–72) days of emission are associated with high convection
events. Weaker, mean convection plays an important role in more consistently
transporting large mole fractions to the free troposphere, which are then
transported more slowly to the TTL.
Observed (solid circles) and model (dashed-dot line) mean mole
fractions of CHBr3 (blue) and CH2Br2 (red) as a function
of altitude, January–February 2014. The solid horizontal lines associated
with each mean observation denotes the range about that mean. The coloured
envelopes associated with the model denote the uncertainty based on the bias
correction as described in the main text. The black horizontal dashed line
denotes the mean model tropopause of 16.5 km.
To estimate the mean observed transport of CHBr3 and
CH2Br2 to the TTL we remove the calculated model bias
(Sect. ), assuming this bias reflects errors in surface
emissions. Figure shows the resulting corrected mean
vertical profiles. We calculate the uncertainties using the upper and lower
limits of the bias correction, which are based on CHBr3 and
CH2Br2 data that are ±2 mean absolute deviations from the
observed mean mole fractions. For CHBr3 and CH2Br2 we
find biases that range -8 %–80 % and 19 %–43 %,
respectively, which we then apply to the model values throughout the
atmosphere over the campaign period. We find that the resulting mean model
values underestimate observed CHBr3 and CH2Br2 between 9
and 12 km, above the main region of convective outflow, with the
observations inside the model uncertainty with the exception of
CH2Br2. Mean model values within the TTL (above 13 km and below
the local tropopause) reproduce mean observations. Based on this bias
correction approach we infer a mean mole fraction and range of
0.46 (0.13–0.72) ppt and 0.88 (0.71–1.01) ppt of CHBr3 and
CH2Br2 being transported to the TTL during January and February
2014. This is a contribution of 3.14 (1.81–4.18) pptv of Br to the TTL
Bry budget over the campaign region. This is consistent with
, who estimate VSLS contribution over the Pacific from
observations in 2013 and 2014. This study estimates 3.27±0.47 pptv of bromine from CHBr3,
CH2Br2 and other minor VSLS sources at the tropopause level
(17 km).
Discussion and concluding remarks
We used the GEOS-Chem chemistry transport model to interpret mole fraction
measurements of CHBr3 and CH2Br2 over the western Pacific during the CAST and CONTRAST campaigns, January–February 2014. We
found that the model reproduced 30 % of CHBr3 measurements and 15 %
(45 %) CAST (CONTRAST) CH2Br2, but had a mean positive bias of
30 % for both compounds. CAST mainly sampled the marine boundary layer (70 %
of observations) so that biases in prior surface emissions have a greater
influence on CAST than CONTRAST, which sampled throughout the troposphere.
To interpret the CAST and CONTRAST measurements of CHBr3 and
CH2Br2 we developed two new GEOS-Chem model simulations: (1) a
linearized tagged simulation so that we could attribute observed changes to
individual sources and geographical regions, and (2) an age-of-air simulation
to improve understanding of the vertical transport of these compounds,
acknowledging that more conventional photochemical clocks are difficult to
use without more accurate boundary conditions provided by surface emission
inventories.
We have three main conclusions. First, we found that open ocean emissions of
CHBr3 and CH2Br2 are primarily responsible for observed
atmospheric mole fractions of these gases over the western Pacific. Emissions
from open ocean sources represent up to 70 % of total CHBr3, with the
largest fractional contribution in the lower troposphere. Coastal ocean
sources typically contribute 20 % to total atmospheric CHBr3 but
reach a maximum of 60 % in the TTL due to advection of air masses convected
from areas outside the study region. Based on this model interpretation, we
infer that CAST observations of CHBr3, which are mainly in the lower
troposphere, are dominated by open ocean sources. In contrast, CONTRAST
measurements have a mix of sources, including a progressively larger
contribution from coastal ocean sources in the upper troposphere.
Tropospheric measurements of CH2Br2, which has a longer
atmospheric lifetime than CHBr3, are dominated by sources from before
the campaign. The open ocean source typically represents only 15 % of the
observed variations in CH2Br2 emitted during the campaign region
throughout the troposphere.
Second, using our age-of-air simulation, we find that the majority of
CHBr3 and CH2Br2 mole fractions in the TTL correspond to
the youngest air masses being transported from open oceanic sources, with
coastal oceans representing older air masses. Within the TTL, the highest
CHBr3 mole fractions are associated with the strongest convective
mass flux events, but this represents only 2 % of the air transported to the
TTL. Weaker, slower convection processes are responsible for consistently
transporting higher mole fractions to the UT and TTL. The majority of air
(92 %) is being transported to the TTL within 3τCHBr3
(48–72 days), corresponding to the majority of weaker convection events.
And third, we estimated the flux of CHBr3 and CH2Br2 to
the TTL using model data that have been corrected for bias. We calculated a
mean and range of values 0.46 pptv (0.13–0.72 pptv) and 0.88 pptv (0.71–1.01 pptv)
for CHBr3 and CH2Br2, respectively. Together, they
correspond to a total of 3.14 pptv (1.81–4.18 pptv) Br to the TTL.
CONTRAST data are publicly available for all researchers
and can be obtained at
http://data.eol.ucar.edu/master_list/?project=CONTRAST (last access: 11 September 2018). The NOAA
surface data are available at
http://www.esrl.noaa.gov/gmd/dv/ftpdata.html (last access: 11 September 2018).
Model evaluation using NOAA surface mole fraction measurements
Figure shows that the majority of station sites
have a positive model bias with magnitude varying depending on location.
Mid-latitude stations (LEF–NWR) have similar bias values of 30 %–40 %
(10 %–20 %) for CHBr3 (CH2Br2). At the tropical
sites, which are comparable with the campaign region, the model bias varies
strongly depending on location. This variability will represent the large
variability of convective events over the region, as well as the
aforementioned errors in model emissions. KUM and MLO both sit on Hawaii,
with KUM and SMO being a near-surface coastal station and MLO sitting at an
elevated altitude of 3397 m. Model bias calculated for MLO (60 %) is
much greater than the other two near-surface sites (<10 %), however it
gives the strongest annual correlation with r2 values of 0.75 (0.55) for
CHBr3 (CH2Br2). All coastal sites (with the exception of
ALT) near emission sources have low r2 values (<0.4), suggesting the
model does not capture local variations in emissions well. This is also
representative of the variation in convection events over the tropical region
being represented within the model.
Seasonal variations within model bias and correlations of CHBr3 and
CH2Br2 are shown in Table .
The campaign season of DJF is poorly constrained within the model at all
sites, with an r2<0.5 for both gases. The annual correlation at sites
appears to be dominated by other seasons. Within the tropical stations, model
bias increases from the annual at KUM to around 20 % with no correlation
to observed values. MLO and SMO show a similar seasonal bias to the annual,
indicating that the effect is local to the KUM station site.
Figure shows that the model reproduces the
seasonal cycle well at all three sites. The emissions at these sites are not
scaled seasonally, but rather the phase is representative of the chemistry at these
sites. The shorter-lived CHBr3 profile is dominated by its loss from
photolysis, whereas the CH2Br2 cycle is dominated by oxidation
with OH. The amplitude of the seasonal cycle is overestimated in
CHBr3 at MLO, and to a lesser extent KUM. This can be indicative of
local biases within photolysis loss rates and/or emissions. The same effect
is not shown within the CH2Br2, suggesting that there is not a similar
problem associated with OH fields. This is concurrent with a recent
multi-decadal analysis which found that carbon monoxide at higher
northern latitudes does not support a major problem with similar monthly 3-D
fields of OH.
Mean annual percentage model bias (blue) calculated at NOAA ground
station sites (Table ) for CHBr3 (dots) and
CH2Br2 (crosses). The horizontal dashed line denotes zero bias.
The right-hand-side y axis describes the ability of the model to reproduce
observed variations (r2) (red). The vertical dotted lines define the
tropical stations.
Observed (green) and model (blue) mole fractions of
(a)CHBr3 and (b)CH2Br2 at tropical
NOAA sites. The seasonal cycle is shown as the climatological monthly mean
anomaly calculated by subtracting the annual mean from the climatological
monthly mean (pptv). Horizontal bars on observed values denote ±1σ.
Evaluation of model convection
To evaluate model convection over the marine environment during the CAST and
CONTRAST campaigns, we developed a short-lived tagged tracer simulation with
an e-folding lifetime comparable to CH3I, as described in Sect. .
We emitted CH3I at an equilibrium mole fraction of 1 pptv over
ocean regions and applied an atmospheric e-folding lifetime of 4 days,
similar to that CH3I in the tropics . We can
then use the model mole fraction to determine the effective mean age-of-air
parcels throughout the troposphere, and to compare the qualitative
CH3I values to observed CH3I values collected during the
CONTRAST campaign.
Figure shows that the model can generally
reproduce the quantitative vertical distribution of CH3I: a
decrease from the surface source up to an altitude of 10–11 km. Above this,
there is a 1–2 km altitude region where values are higher than those in the
free troposphere, suggestive of outflow from convection. As expected, the
youngest air masses are close to the surface with the ages as young as
5–6 days in the upper troposphere. These ages are indicative of fast
convective transport but they are not as young as would be expected from some
of the highest observed mole fractions, which are likely due to faster,
sub-grid-scale convective transport.
Figure shows that the model captures infrequent
fast, large-scale convective transport over the study domain, with ages as
young as 3–4 days reaching the upper troposphere. One metric to describe the
convective transport is the marine convection index (MCI), following
: the ratio of mean upper tropospheric CH3I
(8–12 km) to lower tropospheric CH3I (0–2.5 km). The CONTRAST
observations have an MCI of 0.38 and the corresponding model MCI sampled for
these observations is 0.19. The MCI for the model domain for the duration of
CONTRAST is 0.28. These values are consistent with those found in
over similar Pacific regions.
Overall, we find that the model describes the mean convective flow over the
region and can capture instances of rapid, large-scale convective transport.
Differences in the MCI suggest the significant role of rapid, sub-grid scale
vertical transport that is not captured by our coarse model resolution.
Vertical profiles of observed (blue) and synthetic (coloured as a
function of age) CH3I mole fraction data sampled along flight
tracks corresponding to AWAS samples collected during CONTRAST as a function
of altitude.
Probability distribution of the physical age of CH3I for
the 3-D study domain (solid line) and as sampled by the aircraft
(dashed line) between 11 and 15 km during CONTRAST, 18 January–28 February 2014. The dotted line indicates 1τCH3I of
4 days.
RB and PIP designed the computational experiments with RB
conducting the calculations with contributions from LF about the tagged
models. PIP and RB wrote the paper, with contributions with the other
authors.
The authors declare that they have no conflict of
interest.
Acknowledgements
We are grateful to the Harvard University GEOS-Chem group, who maintain the
model. Robyn Butler was funded by the United Kingdom Natural Environmental
Research Council (NERC) studentship NE/1528818/1, Liang Feng was funded by
NERC grant NE/J006203/1, and Paul I. Palmer gratefully acknowledges his Royal
Society Wolfson Research Merit Award. Ross J. Salawitch acknowledges support
from NSF grant AGS1228495. Elliot L. Atlas
acknowledges support from NSF grant AGS1261689 and
thanks Richard Lueb, Roger Hendershot, Xiaorong Zhu, Maria Navarro, Leslie
Pope for technical and engineering support. CAST is funded by NERC and STFC,
with grants NE/I030054/1 (lead award), NE/J006262/1, 472 NE/J006238/1,
NE/J006181/1, NE/J006211/1, NE/J006061/1, NE/J006157/1, NE/J006203/1,
NE/J00619X/1 (UoYork CAST measurements), and NE/J006173/1. The CONTRAST
experiment is sponsored by the NSF. Edited by:
Rolf Müller Reviewed by: Qing Liang and two anonymous
referees
ReferencesAndrews, S. J., Carpenter, L. J., Apel, E. C., Atlas, E., Donets, V.,
Hopkins, J. R., Hornbrook, R. S., Lewis, A. C., Lidster, R. T., Lueb, R.,
Minaeian, J., Navarro, M., Punjabi, S., Riemer, D., and Schauffler, S.: A
comparison of very short lived halocarbon (VSLS) and DMS aircraft
measurements in the tropical west Pacific from CAST, ATTREX and CONTRAST,
Atmos. Meas. Tech., 9, 5213–5225, 10.5194/amt-9-5213-2016,
2016.Aschmann, J. and Sinnhuber, B.-M.: Contribution of very short-lived substances to
stratospheric bromine loading: uncertainties and constraints, Atmos. Chem. Phys., 13,
1203–1219, 10.5194/acp-13-1203-2013, 2013.Aschmann, J., Sinnhuber, B.-M., Atlas, E. L., and Schauffler, S. M.: Modeling
the transport of very short-lived substances into the tropical upper
troposphere and lower stratosphere, Atmos. Chem. Phys., 9, 9237–9247,
10.5194/acp-9-9237-2009, 2009.Ashfold, M. J., Harris, N. R. P., Atlas, E. L., Manning, A. J., and Pyle, J. A.:
Transport of short-lived species into the Tropical Tropopause Layer, Atmos.
Chem. Phys., 12, 6309–6322, 10.5194/acp-12-6309-2012, 2012.Bell, N., Hsu, L., Jacob, D. J., Schultz, M. G., Blake, D. R., Butler, J. H.,
King, D. B., Lobert, J. M., and Maier-Reimer, E.: Methyl iodide: Atmospheric
budget and use as a tracer of marine convection in global models, J. Geophys. Res.-Atmos., 107, 4340, 10.1029/2001JD001151, 2002.
Carpenter, L., Reimann, S., Burkholder, J., Clerbaux, C., Hall, B., Hossaini,
R., Laube, J., and Yvon-Lewis, S.: Chapter 1: Update on Ozone-Depleting
Substances (ODSs) and Other Gases of Interest to the Montreal Protocol, pp.
21–125, Global Ozone Research and Monitoring Project Report, World
Meteorological Organization (WMO), 2014.Carpenter, L. J. and Liss, P. S.: On temperate sources of bromoform and
other reactive organic bromine gases, J. Geophys. Res., 105, 20539,
10.1029/2000JD900242, 2000.Dorf, M., Butz, A., Camy-Peyret, C., Chipperfield, M. P., Kritten, L., and Pfeilsticker,
K.: Bromine in the tropical troposphere and stratosphere as derived from balloon-borne BrO
observations, Atmos. Chem. Phys., 8, 7265–7271, 10.5194/acp-8-7265-2008, 2008.Fernandez, R. P., Salawitch, R. J., Kinnison, D. E., Lamarque, J.-F., and
Saiz-Lopez, A.: Bromine partitioning in the tropical tropopause layer:
implications for stratospheric injection, Atmos. Chem. Phys., 14,
13391–13410, 10.5194/acp-14-13391-2014, 2014.Finch, D. P., Palmer, P. I., and Parrington, M.: Origin, variability and age
of biomass burning plumes intercepted during BORTAS-B, Atmos. Chem. Phys.,
14, 13789–13800, 10.5194/acp-14-13789-2014, 2014.Fueglistaler, S., Wernli, H., and Peter, T.: Tropical
troposphere-to-stratosphere transport inferred from trajectory calculations,
J. Geophys. Res.-Atmos., 109, d03108, 10.1029/2003JD004069, 2004.Fueglistaler, S., Dessler, A. E., Dunkerton, T. J., Folkins, I., Fu, Q., and
Mote, P. W.: Tropical tropopause layer, Rev. Geophys., 47, RG1004,
10.1029/2008RG000267, 2009.Gettelman, A. and Forster, P. M. D. F.: A Climatology of the Tropical
Tropopause Layer., J. Meteorol. Soc. Japan, 80, 911–924,
10.2151/jmsj.80.911, 2002.Gettelman, A., Salby, M. L., and Sassi, F.: Distribution and influence of
convection in the tropical tropopause region, J. Geophys. Res., 107, 4080,
10.1029/2001JD001048, 2002.Harris, N. R. P., Carpenter, L. J., Lee, J. D., Vaughan, G., Filus, M. T.,
Jones, R. L., OuYang, B., Pyle, J. A., Robinson, A. D., Andrews, S. J.,
Lewis, A. C., Minaeian, J., Vaughan, A., Dorsey, J. R., Gallagher, M. W.,
Breton, M. L., Newton, R., Percival, C. J., Ricketts, H. M. A., Baugitte, S.
J.-B., Nott, G. J., Wellpott, A., Ashfold, M. J., Flemming, J., Butler, R.,
Palmer, P. I., Kaye, P. H., Stopford, C., Chemel, C., Boesch, H., Humpage,
N., Vick, A., MacKenzie, A. R., Hyde, R., Angelov, P., Meneguz, E., and
Manning, A. J.: Co-ordinated Airborne Studies in the Tropics (CAST), B. Am. Meteorol. Soc., 98, 145–162, 10.1175/BAMS-D-14-00290.1,
2016.Hossaini, R., Chipperfield, M. P., Monge-Sanz, B. M., Richards, N. A. D.,
Atlas, E., and Blake, D. R.: Bromoform and dibromomethane in the tropics: a
3-D model study of chemistry and transport, Atmos. Chem. Phys., 10, 719–735,
10.5194/acp-10-719-2010, 2010.Hossaini, R., Chipperfield, M. P., Feng, W., Breider, T. J., Atlas, E.,
Montzka, S. A., Miller, B. R., Moore, F., and Elkins, J.: The contribution of
natural and anthropogenic very short-lived species to stratospheric bromine,
Atmos. Chem. Phys., 12, 371–380, 10.5194/acp-12-371-2012,
2012.Hossaini, R., Mantle, H., Chipperfield, M. P., Montzka, S. A., Hamer, P.,
Ziska, F., Quack, B., Krüger, K., Tegtmeier, S., Atlas, E., Sala, S.,
Engel, A., Bönisch, H., Keber, T., Oram, D., Mills, G., Ordóñez,
C., Saiz-Lopez, A., Warwick, N., Liang, Q., Feng, W., Moore, F., Miller, B.
R., Marécal, V., Richards, N. A. D., Dorf, M., and Pfeilsticker, K.:
Evaluating global emission inventories of biogenic bromocarbons, Atmos. Chem.
Phys., 13, 11819–11838, 10.5194/acp-13-11819-2013, 2013.Hossaini, R., Patra, P. K., Leeson, A. A., Krysztofiak, G., Abraham, N. L.,
Andrews, S. J., Archibald, A. T., Aschmann, J., Atlas, E. L., Belikov, D. A.,
Bönisch, H., Carpenter, L. J., Dhomse, S., Dorf, M., Engel, A., Feng, W.,
Fuhlbrügge, S., Griffiths, P. T., Harris, N. R. P., Hommel, R., Keber,
T., Krüger, K., Lennartz, S. T., Maksyutov, S., Mantle, H., Mills, G. P.,
Miller, B., Montzka, S. A., Moore, F., Navarro, M. A., Oram, D. E.,
Pfeilsticker, K., Pyle, J. A., Quack, B., Robinson, A. D., Saikawa, E.,
Saiz-Lopez, A., Sala, S., Sinnhuber, B.-M., Taguchi, S., Tegtmeier, S.,
Lidster, R. T., Wilson, C., and Ziska, F.: A multi-model intercomparison of
halogenated very short-lived substances (TransCom-VSLS): linking oceanic
emissions and tropospheric transport for a reconciled estimate of the
stratospheric source gas injection of bromine, Atmos. Chem. Phys., 16,
9163–9187, 10.5194/acp-16-9163-2016, 2016.Jones, D. B. A., Bowman, K. W., Palmer, P. I., Worden, J. R., Jacob, D. J.,
Hoffman, R. N., Bey, I., and Yantosca, R. M.: Potential of observations from
the Tropospheric Emission Spectrometer to constrain continental sources of
carbon monoxide, J. Geophys. Res.-Atmos., 108, 4789, 10.1029/2003JD003702, 2003.
Ko, M. and Poulet, G.: Chapter 2: Very short-lived halogen and sulfur
substances, in: Scientific Assessment of Ozone Depletion: 2002 Global Ozone
Research and Monitoring Project, Report No. 47, World Meteorological
Organization, Geneva, Switzerland, 2003.Liang, Q., Stolarski, R. S., Kawa, S. R., Nielsen, J. E., Douglass, A. R., Rodriguez,
J. M., Blake, D. R., Atlas, E. L., and Ott, L. E.: Finding the missing stratospheric
Bry: a global modeling study of CHBr3 and CH2Br2, Atmos. Chem.
Phys., 10, 2269–2286, 10.5194/acp-10-2269-2010, 2010.Liang, Q., Atlas, E., Blake, D., Dorf, M., Pfeilsticker, K., and Schauffler,
S.: Convective transport of very short lived bromocarbons to the
stratosphere, Atmos. Chem. Phys., 14, 5781–5792,
10.5194/acp-14-5781-2014, 2014.Mackie, A. R., Palmer, P. I., Barlow, J. M., Finch, D. P., Novelli, P., and
Jaegl'e, L.: Reduced Arctic air pollution due to decreasing European and
North American emissions, J. Geophys. Res.-Atmos., 121,
8692–8700, 10.1002/2016JD024923, 2016.McLinden, C. A., Haley, C. S., Lloyd, N. D., Hendrick, F., Rozanov, A.,
Sinnhuber, B.-M., Goutail, F., Degenstein, D. A., Llewellyn, E. J., Sioris,
C. E., Van Roozendael, M., Pommereau, J. P., Lotz, W., and Burrows, J. P.:
Odin/OSIRIS observations of stratospheric BrO: Retrieval methodology,
climatology, and inferred Bry, J. Geophys. Res.-Atmos.,
115, d15308, 10.1029/2009JD012488, 2010.Montzka, S. A., Krol, M., Dlugokencky, E., Hall, B., Jöckel, P., and
Lelieveld, J.: Small Interannual Variability of Global Atmospheric Hydroxyl,
Science, 331, 67–69, 10.1126/science.1197640, 2011.National Geographic Data Center, NOAA: 2-minute Gridded Global Relief Data
(ETOPO2) v2, National Oceanic and Atmospheric
Administration, 10.7289/v5j1012q, 2006.Navarro, M. A., Atlas, E. L., Saiz-Lopez, A., Rodriguez-Lloveras, X.,
Kinnison,
D. E., Lamarque, J.-F., Tilmes, S., Filus, M., Harris, N. R. P., Meneguz, E.,
Ashfold, M. J., Manning, A. J., Cuevas, C. A., Schauffler, S. M., and Donets,
V.: Airborne measurements of organic bromine compounds in the Pacific
tropical tropopause layer, P. Natl. Acad. Sci.,
112, 13789–13793, 10.1073/pnas.1511463112, 2015.Ordóñez, C., Lamarque, J.-F., Tilmes, S., Kinnison, D. E., Atlas,
E. L., Blake, D. R., Sousa Santos, G., Brasseur, G., and Saiz-Lopez, A.:
Bromine and iodine chemistry in a global chemistry-climate model: description
and evaluation of very short-lived oceanic sources, Atmos. Chem. Phys., 12,
1423–1447, 10.5194/acp-12-1423-2012, 2012.Palmer, P. I., Jacob, D. J., Jones, D. B. A., Heald, C. L., Yantosca, R. M.,
Logan, J. A., Sachse, G. W., and Streets, D. G.: Inverting for emissions of
carbon monoxide from Asia using aircraft observations over the western
Pacific, J. Geophys. Res.-Atmos., 108, 8828, 10.1029/2003JD003397,
2003.Pan, L. L., Paulik, L. C., Honomichl, S. B., Munchak, L. A., Bian, J.,
Selkirk,
H. B., and Vömel, H.: Identification of the tropical tropopause transition
layer using the ozone-water vapor relationship, J. Geophys. Res.-Atmos., 119, 3586–3599, 10.1002/2013JD020558, 2014.Pan, L. L., Atlas, E. L., Salawitch, R. J., Honomichl, S. B., Bresch, J. F.,
Randel, W. J., Apel, E. C., Hornbrook, R. S., Weinheimer, A. J., Anderson,
D. C., Andrews, S. J., Baidar, S., Beaton, S. P., Campos, T. L., Carpenter,
L. J., Chen, D., Dix, B., Donets, V., Hall, S. R., Hanisco, T. F., Homeyer,
C. R., Huey, L. G., Jensen, J. B., Kaser, L., Kinnison, D. E., Koenig, T. K.,
Lamarque, J.-F., Liu, C., Luo, J., Luo, Z. J., Montzka, D. D., Nicely, J. M.,
Pierce, R. B., Riemer, D. D., Robinson, T., Romashkin, P., Saiz-Lopez, A.,
Schauffler, S., Shieh, O., Stell, M. H., Ullmann, K., Vaughan, G., Volkamer,
R., and Wolfe, G.: The Convective Transport of Active Species in the Tropics
(CONTRAST) Experiment, B. Am. Meteor. Soc., 98, 106–128, 10.1175/BAMS-D-14-00272.1, 2016.Quack, B. and Wallace, D. W. R.: Air-sea flux of bromoform: Controls, rates,
and implications, Glob. Biogeochem. Cy., 17, 1–27,
10.1029/2002GB001890, 2003.Quack, B., Atlas, E., Petrick, G., and Wallace, D. W. R.: Bromoform and
dibromomethane above the Mauritanian upwelling: Atmospheric distributions and
oceanic emissions, J. Geophys. Res., 112, D09312,
10.1029/2006JD007614, 2007.Salawitch, R. J., Canty, T., Kurosu, T., Chance, K., Liang, Q., da Silva, A.,
Pawson, S., Nielsen, J. E., Rodriguez, J. M., Bhartia, P. K., Liu, X., Huey,
L. G., Liao, J., Stickel, R. E., Tanner, D. J., Dibb, J. E., Simpson, W. R.,
Donohoue, D., Weinheimer, A., Flocke, F., Knapp, D., Montzka, D., Neuman,
J. A., Nowak, J. B., Ryerson, T. B., Oltmans, S., Blake, D. R., Atlas, E. L.,
Kinnison, D. E., Tilmes, S., Pan, L. L., Hendrick, F., Van Roozendael, M.,
Kreher, K., Johnston, P. V., Gao, R. S., Johnson, B., Bui, T. P., Chen, G.,
Pierce, R. B., Crawford, J. H., and Jacob, D. J.: A new interpretation of
total column BrO during Arctic spring, Geophys. Res. Lett., 37,
l21805, 10.1029/2010GL043798, 2010.Sander, S., Friedl, R., Barker, J., Golden, D., Kurylo, M., Wine, P., Abbatt,
J., Burkholder, J., Kolb, C., Moortgat, G., Huie, R., and Orkin, V.: Chemical
Kinetics and Photochemical Data for Use in Atmospheric Studies, Evaluation
Number 17, JPL Publication 10–6, Jet Propulsion Laboratory,
http://jpldataeval.jpl.nasa.gov, 2011.Sinnhuber, B.-M. and Folkins, I.: Estimating the contribution of bromoform to
stratospheric bromine and its relation to dehydration in the tropical
tropopause layer, Atmos. Chem. Phys., 6, 4755–4761,
10.5194/acp-6-4755-2006, 2006.Sinnhuber, B.-M., Arlander, D. W., H, B., Burrows, J. P., Chipperfield,
M. P.,
Enell, C.-F., Frieb, U., Hendrick, F., Johnston, P. V., Jones, R. L., Kreher,
K., Mohamed-Tahrin, N., Muller, R., Pfeilsticker, K., Platt, U., Pommereau,
J.-P., Pundt, I., Richter, A., South, A. M., Tornkvist, K. K., Van
Roozendael, M., Wagner, T., and Wittrock, F.: Comparison of measurements
and model calculations of stratospheric bromine monoxide, J. Geophys. Res.,
107, 4398, 10.1029/2001JD000940, 2002.Sinnhuber, B.-M., Rozanov, A., Sheode, N., Afe, O. T., Richter, A.,
Sinnhuber,
M., Wittrock, F., Burrows, J. P., Stiller, G. P., von Clarmann, T., and
Linden, A.: Global observations of stratospheric bromine monoxide from
SCIAMACHY, Geophys. Res. Lett., 32, l20810, 10.1029/2005GL023839, 2005.Sioris, C. E., Kovalenko, L. J., McLinden, C. A., Salawitch, R. J.,
Van Roozendael, M., Goutail, F., Dorf, M., Pfeilsticker, K., Chance, K., von
Savigny, C., Liu, X., Kurosu, T. P., Pommereau, J.-P., Bösch, H., and
Frerick, J.: Latitudinal and vertical distribution of bromine monoxide in the
lower stratosphere from Scanning Imaging Absorption Spectrometer for
Atmospheric Chartography limb scattering measurements, J. Geophys. Res.-Atmos., 111, d14301, 10.1029/2005JD006479, 2006.
Tegtmeier, S., Krüger, K., Quack, B., Atlas, E. L., Pisso, I., Stohl, A.,
and Yang, X.: Emission and transport of bromocarbons: from the West Pacific
ocean into the stratosphere, Atmos. Chem. Phys., 12, 10633–10648,
10.5194/acp-12-10633-2012, 2012.Warwick, N. J., Pyle, J. A., Carver, G. D., Yang, X., Savage, N. H.,
O'Connor,
F. M., and Cox, R. A.: Global modeling of biogenic bromocarbons, J.
Geophys. Res., 111, D24305, 10.1029/2006JD007264, 2006.
WMO: Scientific Assessment of Ozone Depletion: 2006, Global Ozone Research
and
Monitoring Project – Report No. 50, 572 pp., Tech. Rep., World Meteorological
Organization, Geneva, 2007.Zhou, X. L., Geller, M. A., and Zhang, M.: Temperature Fields in the Tropical
Tropopause Transition Layer, J. Climate, 17, 2901–2908,
10.1175/1520-0442(2004)017<2901:TFITTT>2.0.CO;2, 2004.Ziska, F., Quack, B., Abrahamsson, K., Archer, S. D., Atlas, E., Bell, T.,
Butler, J. H., Carpenter, L. J., Jones, C. E., Harris, N. R. P., Hepach, H.,
Heumann, K. G., Hughes, C., Kuss, J., Krüger, K., Liss, P., Moore, R. M.,
Orlikowska, A., Raimund, S., Reeves, C. E., Reifenhäuser, W., Robinson,
A. D., Schall, C., Tanhua, T., Tegtmeier, S., Turner, S., Wang, L., Wallace,
D., Williams, J., Yamamoto, H., Yvon-Lewis, S., and Yokouchi, Y.: Global
sea-to-air flux climatology for bromoform, dibromomethane and methyl iodide,
Atmos. Chem. Phys., 13, 8915–8934, 10.5194/acp-13-8915-2013,
2013.