Introduction
A key player in the coupling between climate change and
atmospheric chemical composition is the oxidative capacity of the
troposphere, primarily characterized by the burden of the four most abundant
and reactive oxidants: OH, ozone, H2O2, and NO3. Estimates of the
oxidative capacity of past atmospheres remain uncertain due to the limited
number of historical and paleo-observations, which hinders our ability to
understand the chemical, climatic, and ecological consequences of past
changes in the oxidative capacity. Multiple factors govern the abundance of
tropospheric oxidants, including emissions of reactive volatile organic
compounds (VOCs). Isoprene (2-methyl-1,3-butadiene, C5H8), primarily
emitted by plants, is the most abundant VOC in the present-day atmosphere
after methane (Pike and Young, 2009). Recent studies have suggested the need
to revise our understanding of the environmental factors controlling biogenic
isoprene emissions and of its atmospheric photo-oxidation mechanism (e.g.,
Paulot et al., 2009a, b; Possell and Hewitt, 2011). These advances call into
question the validity of existing model estimates of the oxidative capacity
of past atmospheres. In this study, we use a climate–biosphere–chemistry
modeling framework (Murray et al., 2014) to explore the sensitivity of the
simulated oxidative capacity to uncertainties in isoprene emissions and
photochemistry and the implications for radiative forcing on
preindustrial–present and on glacial–interglacial timescales. To our
knowledge, this study is the first systematic evaluation of the effects of
these recent developments on model estimates of the chemical composition of
past atmospheres.
The atmospheric oxidative capacity determines the lifetime of many trace
gases important to climate, chemistry, and human health (e.g., Isaksen and
Dalsøren, 2011; Fiore et al., 2012). It may also induce oxidative stress
or alter the deposition of oxidized nutrients to terrestrial and marine
ecosystems (Sitch et al., 2007;
Paulot et al., 2013). Furthermore, oxidants modify the radiative effects of
aerosols by influencing their evolution, lifetime, and physical properties
(Sofen et al., 2011). However, due to the high reactivity of most atmospheric
oxidants, direct measurement of their past abundances is not currently
possible for most species. Late 19th-century surface ozone measurements exist
but their accuracy has been debated (Pavelin et al., 1999). Atmospheric
oxidants, except for H2O2, are not directly preserved in the
ice-core record. Even for H2O2, however, post-depositional processes
impede quantitative interpretation of this record (Hutterli et al., 2002). As
summarized in Murray et al. (2014), Table 1, prior modeling studies that
investigated past changes in the abundance of tropospheric oxidants disagree
on the magnitude and even the sign of change. Such discrepancies call into
question our ability to quantify the relative roles of sources and sinks in
driving past variations in atmospheric methane concentrations. Previous
studies attributed these variations to changes in wetland emissions, the
dominant natural source of methane to the atmosphere (e.g., Khalil and
Rasmussen, 1987; Brook et al., 2000). However, more recent modeling studies
suggested that potential variations in OH – the primary sink for methane –
may be larger than previously thought, driven by changes in biogenic VOC
emissions (e.g., Kaplan, 2002; Valdes et al., 2005; Harder et al., 2007).
This issue remains an ongoing debate (e.g., Levine et al., 2011b; Quiquet et
al., 2015).
Tropospheric oxidants are strongly coupled through atmospheric photochemical
reactions, and their abundances respond to meteorological conditions, changes
in surface and stratospheric boundary conditions, and changes in emissions of
key chemical species such as reactive nitrogen oxides (NOx= NO + NO2) and VOCs. Present-day natural emissions of VOCs, which
far exceed those from anthropogenic sources on a global scale, are dominated
by plant isoprene emissions, which have an estimated global source ranging
from approximately 500 to 750 Tgyr-1 (Lathière et al., 2005;
Guenther et al., 2006). This large emission burden is accompanied by high
reactivity; isoprene has an atmospheric chemical lifetime on the order of
minutes to hours (Pike and Young, 2009). Isoprene and its oxidation products
react with OH, ozone, and the nitrate radical and are thus major players in
the oxidative chemistry of the troposphere (Beerling et al., 2007). The
oxidation products of isoprene also substantially contribute to secondary
organic aerosol (SOA) formation (Henze and Seinfeld, 2006). Biogenic SOA,
like other aerosols, affects climate by scattering and absorbing solar
radiation and by altering the properties and lifetimes of clouds, but the net
climate effect is poorly characterized (Scott et al., 2014). Therefore,
uncertainties in the preindustrial-to-present-day changes in biogenic VOC
emissions, and subsequently in SOA burdens, lead to large uncertainties in
the anthropogenic indirect radiative forcing estimates over the industrial
period (e.g., Carslaw et al., 2013; Scott et al., 2014).
Results from the Atmospheric Chemistry and Climate Model Intercomparison
Project (ACCMIP) demonstrate that uncertainties remain in our understanding
of the long-term trends in OH and methane lifetime and that these
uncertainties primarily stem from a lack of adequate constraints on natural
precursor emissions and on the chemical mechanisms in the current generation
of chemistry–climate models (Naik et al., 2013). Recent field and laboratory
findings have called into question prior estimates of global
isoprene burdens for the past and future
atmospheres and have revealed new details of the isoprene photo-oxidation
mechanism. First, isoprene emission from plants is well known to be strongly
dependent on plant species and, for a given species, on environmental factors
including temperature, light availability, and leaf age (Guenther et
al., 2012). However, recent empirical studies have shown that isoprene
emission by several plant taxa is also inversely correlated with atmospheric
CO2 levels, but this relationship is not yet well constrained (e.g.,
Wilkinson et al., 2009; Possell and Hewitt, 2011). The biochemical mechanism
for this effect remains unresolved, but evidence suggests that CO2
concentration plays a role in partitioning carbon-substrate availability
between the chloroplast and cytosol of a plant cell and in mobilizing stored
carbon sources (Trowbridge et al., 2012). Such bio-mechanisms involving a
CO2 dependence of isoprene emissions may have evolved in plants long ago.
Second, recent field studies in major isoprene-emitting regions, such as the
Amazon forest (Lelieveld et al., 2008), South East Asia (Hewitt et
al., 2010) and China (Hofzumahaus et al., 2009), reported large
discrepancies between measured and modeled HOx (OH + HO2)
concentrations, suggesting that VOC oxidation under low-NOx conditions may
recycle OH more efficiently than previously understood. These findings
motivated numerous theoretical and experimental studies, which in turn led to
extensive updates in the gas-phase isoprene photo-oxidation mechanism, in
which there is greater regeneration and recycling of HOx and NOx under
high-NOx conditions and of HOx under low-NOx conditions (e.g.,
Paulot et al., 2009a, b). In general, greater OH-recycling enhances the
efficiency of atmospheric oxidation, while greater NOx-recycling enhances
the efficiency of ozone production. However, the improved mechanism is still
unable to fully reconcile measured and modeled OH concentrations (Mao et
al., 2012). Moreover, global and regional modeling studies indicate that the
heterogeneous HO2 uptake by aerosols presents a potentially important
HOx sink. There remains, however, considerable uncertainty in the
magnitude of this sink and its impact on tropospheric chemistry (Thornton et
al., 2008). Mao et al. (2013a) proposed a new scheme in which HO2 uptake
by aerosols leads to H2O rather than H2O2 formation via coupling of
Cu(I) / Cu(II) and Fe(II) / Fe(III) ions. Since H2O2 can be
readily photolyzed to regenerate OH, this new mechanism provides a more
efficient HOx removal pathway. Cu and Fe are ubiquitous components of
crustal and combustion aerosols (Mao et al., 2013a). Observations and model
studies suggest that during the Last Glacial Maximum (LGM) and preindustrial, natural dust
distributions were higher than that in the present day (Mahowald et
al., 2006). In particular, during the LGM, Fe(II) and Fe(III) ion
concentrations in dust increased by at least 2 times relative to
interglacial levels (Spolaor et al., 2013). Likewise, positive Cu anomalies
during the last glacial period have been measured in ice cores (Oyarzun et
al., 2005).
In support of the ICE age Chemistry And Proxies (ICECAP) project, Murray et
al. (2014) developed a new climate–biosphere–chemistry modeling framework for
simulating the chemical composition of the present and past tropospheres,
focusing on preindustrial-to-present and glacial–interglacial transitions.
The Last Glacial Maximum (∼ 19–23 ka) spans the coldest
interval of the last glacial period (∼ 11.5–110 ka) and is
relatively well recorded in ice-core and sediment records, making the
LGM-to-preindustrial transition a convenient glacial–interglacial analogue.
Disparities in existing model studies of past tropospheric oxidant levels are
partly due to differences in the model components of the Earth system allowed
to vary with climate and the differing degrees of complexity in the
representation of those components (Murray et al., 2014). The ICECAP project
is the first 3-D model framework to consider the full suite of key factors
controlling the oxidative capacity of the troposphere at and since the LGM,
including the effect of changes in the stratospheric column ozone on
tropospheric photolysis rates. Murray et al. (2014) found that (1) the
oxidative capacities of the preindustrial and LGM atmospheres were both lower
than that of the present day; (2) tropospheric mean OH levels appear to be
well buffered in the LGM-to-preindustrial transition – a result at odds with
most prior studies; (3) past changes in atmospheric methane concentrations
were predominantly source driven; and (4) the key parameters controlling the
oxidative capacity over LGM–present-day timescales are tropospheric mean
ozone photolysis rates, water vapor abundance, and total emissions of NOx
and reactive carbon.
In light of recent developments in our understanding of the isoprene
photo-oxidation mechanism and of the sensitivity of plant isoprene emissions
to atmospheric CO2 levels, we build on the model study by Murray et
al. (2014) to explore the sensitivity of the simulated tropospheric oxidative
capacity at and since the LGM and the ramifications for our understanding of
the factors controlling the oxidative capacity. We also discuss the
implications for changes in short-lived climate forcers and for interpreting
the ice-core methane record. We examine, in a systematic manner, the effects
of all of the above developments on the chemical composition of the
troposphere over the last glacial–interglacial time interval and the
industrial era.
Methods: model framework, model developments, and project
description
The ICECAP model framework
Figure 1 illustrates the stepwise, offline-coupled
climate–biosphere–chemistry model framework of the ICECAP project. This
setup relies on four global models. GEOS-Chem is a global 3-D chemical
transport model (CTM) with a long history in simulating present-day
tropospheric ozone–NOx–CO–VOC–BrOx–aerosol chemistry
(http://www.geos-chem.org; Bey et al., 2001; Park et al., 2004;
Parrella et al., 2012). The version used here includes online linearized
stratospheric chemistry (McLinden et al., 2000), which allows for calculation
of photolysis rates more consistent with changing climate and chemical
conditions. We use version 9-01-03 with modifications as described in Murray
et al. (2014) and below. ICECAP is driven by meteorological fields from
ModelE, a climate model developed at the NASA Goddard Institute of Space
Studies (GISS). ModelE and related models at GISS have been used extensively
in paleo-climate studies (e.g., LeGrande et al., 2006; Rind et
al., 2001, 2009). Here we use the ModelE version with a horizontal resolution
of 4∘ latitude by 5∘ longitude and 23 vertical layers
extending from the surface to 0.002 hPa in the atmosphere. Climate in ModelE
is forced by prescribed greenhouse gas levels, orbital parameters,
topography, and sea ice and sea surface temperatures (SSTs) relevant to each
time slice of interest. The final components are the BIOME4–trace-gas
(BIOME4-TG) equilibrium terrestrial biosphere model (Kaplan et al., 2006) and
the Lund–Potsdam–Jena Lausanne–Mainz fire (LPJ-LMfire) dynamic global
vegetation model (Pfeiffer et al., 2013). BIOME4-TG is used to determine
static vegetation distributions, while LPJ-LMfire simulates biomass burning
regimes. Meteorology from ModelE drives both these models, and the resulting
land-cover characteristics and dry matter burned are implemented into
GEOS-Chem. The basal biogenic emission factors per plant functional types
used in the BIOME4-TG model, which do not change between the climate
scenarios, can be found in Murray et al. (2014), Table 5.
The ICE age Chemistry And Proxies (ICECAP) model framework consists
of four global models, represented here by boxes with solid lines. The
stratospheric and tropospheric chemistry schemes are coupled online in the
GEOS-Chem chemical transport model (CTM). Arrows indicate the flow of model
output. The ICECAP model framework was especially designed for simulating the
oxidative capacity of past atmospheres. (Adapted from Murray et al., 2014,
Fig. 1.)
A detailed description of the ICECAP model framework and its evaluation
against observations can be found in Murray et al. (2014). The present-day
simulation has been evaluated against a suite of sonde, aircraft, satellite,
and surface measurements of trace gases, aerosols, and radionuclides. The
simulated LGM climate scenarios have also been evaluated against pollen-based
climate reconstruction from Bartlein et al. (2011). The ICECAP model
overestimates transport from the stratosphere due to an overly vigorous
Brewer–Dobson circulation (Murray et al., 2014). Rather than fixing the
transport fluxes to better match present-day values, we accept this bias in
order to allow the stratospheric columns of ozone to adjust freely to
different climate scenarios. For example, Murray et al. (2014) found that
reductions in greenhouse gases weaken the stratospheric residual circulation
and lead to an increase in tropical stratospheric ozone columns.
As in Murray et al. (2014), we perform simulations for four different climate
scenarios: present day (ca. 1990s), preindustrial (ca. 1770s), and two
different representations of the LGM (∼ 19–23 ka) to span the range
of likely conditions. The simulated average global surface air temperatures
are 14.9 ∘C for the present day, 14.3 ∘C for the
preindustrial, 10.7 ∘C for the warm LGM, and 6.1 ∘C for the
cold LGM (Murray et al., 2014, Table 4). The two LGM scenarios differ in the
degree of cooling of tropical SSTs. Such differences have implications for
LGM dynamics because of the influence of tropical SSTs on meridional
temperature gradients and low-latitude circulation (Rind et al., 2009). The
“warm LGM” uses SST reconstructions from the Climate: Long range
Investigation, Mapping, and Prediction project (CLIMAP Project
Members, 1976), with an average change in SST within 15∘ of the
Equator relative to the preindustrial (ΔSST15∘S-∘N) of -1.2 ∘C. The
“cold LGM” uses SSTs from Webb et al. (1997), who found ΔSST15∘S-∘N of -6.1 ∘C. By
imposing an ocean heat transport flux in an earlier version of the GISS
model, Webb et al. (1997) achieved a better match with certain paleo-proxies
of temperature such as corals (Guilderson et al., 1994; Stute et al., 1995).
The warm LGM SSTs yield a change of mean global surface air temperature of
-3.6 ∘C relative to the preindustrial, while the cold LGM SSTs
yield a change of -8.2 ∘C. These values lie within the range of
temperature changes reported by Holden et al. (2010), and they span the
approximately -7 ∘C change inferred from Gildor et al. (2014) for
the LGM relative to the present day. The MARGO project, which is the current
best assumption of tropical SSTs at the LGM, found ΔSST15∘S-∘N of -1.7 ± 1.0 ∘C
(Waelbroeck et al., 2009). These estimates are more similar to the warm LGM
than the cold LGM scenario used in
this study.
Murray et al. (2014) also tested the sensitivity of their model results to
uncertainties in lightning and fire emissions. Comparison with
paleo-observations suggests that their “low-fire, variable-lightning, warm
LGM” scenario was the best representation of the LGM atmosphere, in which
lightning NOx emissions are parameterized to reflect changes in convective
cloud top heights, and the LPJ-LMfire fire emissions are scaled to match
observational records inferred from the Global Charcoal Database (Power et
al., 2007, 2010). The model simulations in this study are performed using the
Murray et al. (2014) “best estimate” fire and lightning emission scenarios
relevant for each climate.
Uncertainties in biogenic isoprene emissions
Biogenic VOC emissions in GEOS-Chem are calculated interactively by the Model
of Emissions of Gases and Aerosols from Nature (MEGAN v2.1) (Guenther et
al., 2012). The canopy-level flux of isoprene is computed as a function of
plant function type (PFT)-specific basal emission rate, scaled by activity
factors (γi) to account for environmental controlling factors
including temperature, light availability, leaf age, and leaf area index. Tai
et al. (2013) recently implemented an additional activity factor,
γC, to account for the effect of atmospheric CO2
concentrations. They used the empirical relationship from Possell and
Hewitt (2011): γC=a/1+abC, where the
fitting parameters a and b have values of 8.9406 and
0.0024 ppm-1, respectively, and C represents the atmospheric
CO2 concentration (γC= 1 at C= 370 ppm). To
date, Possell and Hewitt (2011) studied the widest range of plant taxa and
atmospheric CO2 concentrations. Their CO2–isoprene emission response
curve shows a higher sensitivity at CO2 concentrations below present-day
levels than others from similar studies (e.g., Wilkinson et al., 2009),
likely providing an upper limit of this effect for past climates. We have not
considered the effect of CO2 sensitivity
on other plant VOC emissions, such as monoterpenes and sesquiterpenes, due to
lack of conclusive evidence of this effect (Peñuelas and Staudt, 2010).
In all four climate scenarios, isoprene constitutes more than 60 % of
total biogenic VOC emissions.
In this study, we follow the Tai et al. (2013) implementation, which uses the
empirical relationship from Possell and Hewitt (2011). Table 1 summarizes the
prescribed CO2 mixing ratios, as well as the estimated total annual
isoprene burdens with and without consideration of the CO2 sensitivity of
plant isoprene emissions, for each climate scenario. When the CO2
sensitivity is considered, we find relative increases in the total biogenic
isoprene source of 4 % for the present day, 28 % for the
preindustrial, 78 % for the warm LGM, and 77 % for the cold LGM
scenarios.
Uncertainties in the fate of the oxidation products of isoprene
Isoprene photo-oxidation mechanism
Murray et al. (2014) used the original GEOS-Chem isoprene photo-oxidation
mechanism, which is largely based on Horowitz et al. (1998). Here we apply
recent updates to the mechanism by Mao et al. (2013b) and Paulot et
al. (2009a, b), which Mao et al. (2013b) evaluated in GEOS-Chem through
comparison with present-day observations of ozone, isoprene, and oxidation
products. Daytime oxidation of isoprene by OH leads to the formation of
hydroxyl–peroxy radicals (ISOPO2). The new scheme includes a more
explicit treatment of the production and subsequent reactions of organic
nitrates, acids, and epoxides from reactions of the ISOPO2 radicals. Such
reactions lead to greater HOx- and NOx-regeneration and recycling than
in the original mechanism, especially under low-NOx conditions, which is
of particular relevance for past atmospheres (Mao et al., 2013b). The new
scheme also includes an update for the aerosol reactive uptake coefficient of
NO3 radicals, in which the value is increased from 10-4 to 0.1 (Mao
et al., 2013b). Beyond Mao et al. (2013b), we also change the stoichiometry
of the (ISOPO2+ HO2) reaction to that recommended by the laboratory
study of Liu et al. (2013), which has smaller uncertainties and leads to
relatively smaller yields (by ∼ 50 %) of HOx, methyl vinyl
ketone, and methacrolein from this pathway. Our work tests the sensitivity of
model results to these updates in the isoprene photo-oxidation mechanism.
Heterogeneous HO2 uptake by aerosols
As parameterized in the standard GEOS-Chem model, gaseous HO2 uptake by
aqueous aerosols leads to H2O2 formation and has a γ(HO2)
value typically less than 0.1, where γ(HO2) is a measure of the
efficacy of uptake, defined as the fraction of HO2 collisions with aerosol
surfaces resulting in reaction. (Note that γ traditionally refers to
both the aerosol uptake efficiency and biogenic emissions flux activity
factor.) Atmospheric observations, however, suggest that HO2 uptake by
aerosols may in fact not produce H2O2 (de Reus et al., 2005; Mao et
al., 2010). In light of these findings, Mao et al. (2013a) implemented a new
uptake scheme in GEOS-Chem in which HO2 uptake yields H2O via coupling
of Cu(I) / Cu(II) and Fe(II) / Fe(III) ions, and we follow that
approach here. As in Mao et al. (2013a), we use the upper limit of γ(HO2)= 1.0 for all aerosol types to evaluate the implications of this
uptake for the HOx budgets and for the fate of the oxidation products of
isoprene.
Outline of model sensitivity experiments
Table 2 summarizes the different climate, chemistry, and plant isoprene
emission scenarios tested in this model study. For each climate scenario, we
apply to GEOS-Chem the archived meteorology and land-cover products from the
“best estimate” fire and lightning emission scenarios from Murray et
al. (2014). We test three different chemistry schemes in GEOS-Chem: C1 uses
the original isoprene chemistry and original HO2 uptake, C2 uses the new
isoprene chemistry and original HO2 uptake, and C3 uses the new isoprene
chemistry and new HO2 uptake mechanisms. Each chemistry scheme is tested
either with (w) or without (wo) inclusion of the CO2 sensitivity of
biogenic isoprene emissions, except for the present day. As Table 1 shows,
consideration of the CO2 sensitivity for the present day results in only a
4 % change in the global isoprene burden (γC= 1 at C=370 ppm), and so we assume that the present-day model simulations with
consideration of the CO2 sensitivity of biogenic isoprene emissions are
representative of their respective “without” scenarios. Our “C1-wo” model
simulations match the isoprene emissions and photochemistry schemes used by
Murray et al. (2014). We perform 21 simulations in total.
Simulated sensitivity of the tropospheric mean mass-weighted oxidant
burdens of OH, O3, H2O2, and NO3 to each combination of climate,
chemistry, and plant isoprene emission scheme. Simulations are as described
in Table 2. The climate scenarios are present day, preindustrial, warm LGM,
and cold LGM, with decreasing sea surface temperatures within 15∘ of
the Equator (SST15∘S-∘N), going from left to
right along the abscissa. The chemistry schemes are C1 (orange curves), C2
(green), and C3 (blue). Plant isoprene emissions are modeled without
(light shaded) or with (dark shaded) sensitivity to atmospheric CO2
concentrations. The tropospheric burdens are calculated with the tropopause
determined from the thermal lapse rate. The dotted light-orange line
represents the results reported in Murray et al. (2014) for their “best
estimate” lightning and fire emissions scenarios.
For each climate scenario, we use 4 subsequent years of archived
meteorology from the GISS climate model. Each GEOS-Chem simulation is
initialized with a 10-year spin-up, repeatedly using the first year of
archived meteorology, to reach equilibrium with respect to
stratosphere–troposphere exchange. We then perform 3 more years of
simulations for analysis, using the 3 subsequent years of archived
meteorology. All of the quantities considered here are global means or
averages over large spatial regions. We find that the interannual
variability of such quantities is small compared to the differences between
the climate scenarios, and that 3 years is sufficient for our analysis.
In GEOS-Chem, atmospheric methane concentrations are prescribed with imposed
meridional gradients derived from observations, except for the tropical LGM
in which model results are used (Murray et al., 2014, Table 3). The
tropospheric mean values are 1743 ppbv for the present day, 732 ppbv for
the preindustrial, and 377 ppbv for the LGM scenarios.
Results
Tropospheric mean oxidant burdens
Figure 2 shows the simulated tropospheric mean mass-weighted burdens of OH,
ozone, H2O2, and NO3 for each combination of climate, chemistry, and
plant isoprene emission scenarios. The dotted orange line represents results
using the “best estimate” lightning and fire emission scenarios of Murray
et al. (2014). The plots show the varying sensitivity of oxidant levels to
assumptions about the tropospheric chemical mechanism and the global isoprene
burden.
Consideration of the CO2 sensitivity of plant isoprene emissions yields
larger isoprene emissions for the preindustrial and LGM scenarios (Table 1).
For a given chemistry scheme and climate scenario, this leads to a decrease
in the tropospheric mean OH burden, an increase in H2O2, and small
changes in ozone and NO3. This result can be understood by considering the
classical tropospheric ozone–HOx–NOx–CO catalytic cycle (e.g., Rohrer
et al., 2014, Fig. 1). In general, daytime oxidation of VOC by reaction with
OH leads to formation of oxidized organic products and HO2. Efficient
HOx-cycling depends on the presence of NOx. Since low-NOx conditions
prevail in past atmospheres, an increased isoprene burden represents a net OH
sink but an HO2 source. The self-reaction of HO2 leads to H2O2
formation. Under low-NOx conditions, tropospheric ozone production is
relatively insensitive to changes in the reactive carbon burden. The
tropospheric NO3 burden also shows little change since the abundances of
its precursors (NO2+ O3) hardly vary with the global isoprene burden.
Atmospheric CO2 concentrations and global annual terrestrial
plant isoprene emissions for each climate scenario.
Climate scenario
[CO2]
Global annual terrestrial
Percent change in global isoprene emissions with CO2
(ppmv)
plant isoprene emissions
sensitivity relative to without (%)
without
with*
CO2 sensitivity
CO2 sensitivity
(TgCyr-1)
(TgCyr-1)
Present day
354
536
557
+3.9
Preindustrial
280
580
740
+28
Warm LGM
188
478
849
+78
Cold LGM
188
261
463
+77
* This study uses the empirical relationship from Possell
and Hewitt (2011) to test the sensitivity of plant isoprene emissions to
atmospheric CO2 concentrations.
Implementation of the new isoprene oxidation mechanism leads to large changes
in tropospheric oxidant burdens of OH and O3, but not H2O2 and NO3,
for the past atmospheres. For a given climate scenario, the largest source of
uncertainties in global mean OH arises from differences between the original
and new isoprene photo-oxidation mechanisms. Increases in the tropospheric
mean OH burdens result from greater HOx-regeneration in the new isoprene
photo-oxidation cascade (Mao et al., 2013b). The ozone production efficiency
– the number of ozone molecules produced per molecule of NOx consumed
(Liu et al., 1987) – is greater in the new isoprene mechanism, leading to
increases in the tropospheric ozone burdens. This is because the newly added
reactions of recycling of isoprene nitrates, formed in the (ISOPO2 + NO)
reaction pathway, can lead to NOx-regeneration, thereby representing a
less permanent NOx sink than nitric acid (Paulot et al., 2012). The
present-day burden of NO3 shows a large decrease in response to the new
isoprene oxidation scheme, while those of the past atmospheres show little
change. The muted NO3 response for the past atmospheres is due to two
competing effects in the new scheme: (1) an increased aerosol reactive uptake
coefficient of NO3 radicals (from 10-4 to 0.1) leading to greater
NO3 depletion (Mao et al., 2013b) and (2) increased abundances in both
NO3 precursors (NO2+ O3) enhancing its formation. The latter effect
is due to greater NOx-recycling and regeneration in the new scheme through
isoprene nitrate recycling and hence greater ozone production efficiency and
increased lifetime of NOx reservoir species. For the present day, the
increased abundances of NO3 precursors are smaller than those of the past
atmospheres. Finally, implementation of the new scheme of HO2 uptake by
aerosols leads to significant decreases in the tropospheric mean OH and
H2O2 burdens in all simulations. This is due to both the higher
efficacy of uptake than previously assumed and the formation of H2O
instead of H2O2 as a by-product of the uptake, yielding a more
efficient HOx removal pathway.
Summary of the different climate, chemistry, and plant isoprene
emission scenarios tested in this model study. For each climate scenario
except for the present day, all possible combinations of chemistry and
emission schemes are tested (for the present day, only the “with”
CO2 sensitivity scheme is used). We perform 21 simulations in total.
Climate
Notes
Present day
ca. 1990s
Preindustrial
ca. 1770s
Warm LGM
19–23 ka; SSTs from CLIMAP Project Members (1967) with ΔSST15∘S-∘Na of -1.2 ∘C
Cold LGM
19–23 ka; SSTs from Webb et al. (1997) with ΔSST15∘S-∘Na of -6.1 ∘C
Chemistry
Notes (color scheme used in figures)
C1b
Original isoprene chemistry and original HO2 uptake (orange)
C2
New isoprene chemistry and original HO2 uptake (green)
C3
New isoprene chemistry and new HO2 uptake (blue)
CO2 sensitivity of plant isoprene emission
Notes
Without (wo)b
Controlling factors include temperature, light availability, leaf age, and leaf area index
With (w)
Controlling factors include the above and atmospheric CO2 concentrations
a The average change in sea surface temperature (SST)
within
15∘ of the Equator relative to the preindustrial. b The “C1-wo” combination corresponds to the schemes used by
Murray et al. (2014) in their “best estimate” scenarios.
Percent changes (%) in the tropospheric mean mass-weighted OH
burden for a range of scenarios relative to their respective preindustrial
scenarios (e.g., C1-w present day relative to C1-w preindustrial).
Simulations are as described in Table 2. The climate scenarios are present
day, preindustrial, warm LGM, and cold LGM. The chemistry schemes are C1
(orange bars), C2 (green), and C3 (blue). Plant isoprene emissions are
modeled without (light shaded) or with (dark shaded) sensitivity to
atmospheric CO2 concentrations. For the present day, test simulations with
and without CO2 sensitivity yield nearly identical isoprene emissions. We
therefore perform all present-day simulations with CO2 sensitivity turned
on and assume that these model results apply to the respective present-day
“without” scenarios. (Note: The percent change at the warm LGM relative to
the preindustrial is very small when the C1 chemistry scheme is used without
consideration of the CO2 sensitivity (C1-wo), and so no light-orange bar
is apparent in the middle panel.)
Despite uncertainties in the isoprene emissions and photochemistry, we find
reduced levels of ozone, H2O2, and NO3 in each combination of
chemistry and isoprene emission scenarios for the past atmospheres relative
to the present day, a result consistent with Murray et al. (2014). However,
their conclusion that OH is relatively well buffered on glacial–interglacial
timescales relative to other tropospheric oxidants does not hold for some of
the uncertainties explored in this study. Figure 3 shows the simulated
percent changes in the tropospheric mean OH burden for the present day, warm
LGM, and cold LGM scenarios, relative to their respective preindustrial
scenarios (e.g., C1-w present day relative to C1-w preindustrial).
Consideration of the CO2 sensitivity of plant isoprene emissions alone
(C1-w) leads to 23 and 29 % reductions in the tropospheric mean OH burden
in the warm and cold LGM scenarios relative to that of the preindustrial,
while the present-day burden is 17 % greater than that of the
preindustrial. When the new chemistry schemes are applied without
consideration of the CO2 sensitivity, the modeled changes in OH relative
to the preindustrial are less dramatic but have opposite signs to those
calculated under the C1-w scenarios for the present day and warm LGM. When
all effects are considered (C2-w and C3-w), changes in the tropospheric mean
OH burden across the warm LGM-to-preindustrial and preindustrial-to-present-day transitions do not exceed 5 %, a result consistent with Murray et
al. (2014). The varying sensitivity of the tropospheric mean OH burden to
assumptions about the isoprene photochemistry and emissions has implications
for our understanding of past methane and SOA burdens and radiative forcing
calculations, as discussed in Sect. 3.3 and 3.4.
Comparison with observations
We evaluate the results of the model sensitivity experiments against four
different categories of observations. First, Table 3 compares the simulated
methyl chloroform (CH3CCl3) and methane lifetimes against loss from
tropospheric OH under different chemistry schemes with observations for the
present day. The global lifetimes of methyl chloroform and of methane against
oxidation by tropospheric OH are calculated as the global burden divided by
the total loss rate summed over all grid boxes in the troposphere:
τX,OH=∫surfaceTOAXdxdydz∫surfacetropopausekX+OH(T)[OH]Xdxdydz,
where X represents either methyl chloroform or methane, and kX+ OH(T) is the temperature-dependent rate constant of the reaction. We
assume that the mixing ratio of methyl chloroform is uniform throughout the
troposphere and is 92 % lower than the total atmospheric concentration
(Bey et al., 2001; Prather et al., 2012). For methane, the global burden is
calculated from the mean surface concentration using a conversion factor of
2.75 TgCH4ppbv-1 from Prather et al. (2012). In our
present-day simulations (ca. 1990s), we prescribe the mean surface
concentration as 1743 ppbv.
Calculated present-day methyl chloroform (MCF) and methane lifetimes
against tropospheric oxidation by OH (τMCF, OH,
τCH4,OH), with consideration of CO2 sensitivity of plant
isoprene emissions.
Lifetime
Calculated from different
Inferred from
model chemistry schemesa
observations
C1
C2
C3
τMCF,OH (years)
4.8
4.1
4.5
6.0-0.4+0.5 b
τCH4,OH (years)
10.3
8.9
9.6
11.2 ± 1.3 c
a See Table 2 for a full description of the different
chemistry schemes tested in this study.b Inferred from observations (Prinn et al., 2005).c Inferred from observations (Prather et al., 2012).
The combination of new isoprene and original HO2 uptake chemistry (C2) has
the largest simulated tropospheric mean OH burden (Fig. 2) and so yields the
shortest methyl chloroform and methane lifetimes: 4.1 and 8.9 years,
respectively. Prinn et al. (2005) inferred an average methyl chloroform
lifetime of 6.0-0.4+0.5 years for the years 1978–2004 based on
observations of methyl chloroform and knowledge of its emissions. Our
present-day model results range between 4.1 and 4.8 years, which are all
lower than the range derived from observations but comparable to recent
multi-model estimates of 5.7 ± 0.9 years for 2000 (Naik et al., 2013).
Based on observations and emission estimates, the mean methane lifetime
against loss from tropospheric OH is estimated to be 10.2-0.7+0.9
years between 1978 and 2004 by Prinn et al. (2005) and to be 11.2 ± 1.3 years
for 2010 by Prather et al. (2012). The values given by the C1 (10.3 years)
and C3 (9.6 years) chemistry schemes fall within these ranges. The lowest
value given by C2 (8.9 years) does not fall within the ranges derived from
observations but is still within the range of estimates reported by recent
multi-model studies: 10.2 ± 1.7 years (Fiore et al., 2009),
9.8 ± 1.6 years (Voulgarakis et al., 2013), and 9.7 ± 1.5 years
(Naik et al., 2013). Reconciling the magnitude of the inferred OH burden with
modeled results remains an ongoing challenge (Holmes et al., 2013).
Second, we also assess our model results for present-day OH by evaluating the
simulated inter-hemispheric ratios (N / S) of tropospheric mean OH.
Estimates of this ratio based on methyl chloroform measurements from 1980 to
2000 range between 0.85 and 0.98 (Montzka et al., 2000; Prinn et al., 2001;
Krol and Lelieveld, 2003; Bousquet et al., 2005), whereas the recent ACCMIP
multi-model study finds a mean ratio of 1.28 ± 0.10 for 2000 (Naik et
al., 2013). In our present-day sensitivity experiments, we calculate ratios
of 1.20 for C1, 1.11 for C2, and 1.07 for C3. The C1 value falls within the
ACCMIP range, but the C3 value best matches the ratio inferred from
observations. Models participating in the ACCMIP study did not consider
HOx-recycling pathways under low-NOx condiions through reactions of
peroxy and HO2 radicals (Naik et al., 2013). As previously described,
HOx-recycling in the absence of NOx can occur in our new isoprene
photochemistry scheme (C2), which leads to a lower present-day N / S
ratio of tropospheric mean OH. The ratio decreases further and becomes more
comparable with the observations when the upper limit of efficacy of HO2
uptake by aerosols is also considered
(C3). This result is due to the large anthropogenic aerosol loadings in the
Northern Hemisphere.
Comparison of model results with observations of CO surface
concentrations (ppbv) over Antarctica for the preindustrial (1770s) and
present-day (1990s) simulations. The maroon crosses represent observations
from different sources for each time slice. Wang et al. (2010) measured
ice-core CO concentrations at the South Pole of 48 ± 4 ppbv for the
year 1777 (±110 years); the associated errors represent analytical
uncertainties. The mean CO surface concentration measured at the South Pole
by the NOAA Global Monitoring Division for the 1990s is 49 ± 2 ppbv;
the associated errors represent interannual variability. The squares
represent values averaged over Antarctica from our model simulations tested
with different chemistry and isoprene emission schemes for the preindustrial
and present-day scenarios. Simulations are as described in Table 2; colors
are as in Fig. 2. Error bars associated with the model results represent
±1 standard deviation of the spatially averaged mean value.
Third, we compare modeled CO for the preindustrial and present-day
simulations against observed CO surface concentrations over Antarctica
(Fig. 4). CO influences the oxidative capacity of the troposphere through
reaction with its primary sink, OH, which can subsequently affect the ozone
budget (Fiore et al., 2012). In this context, CO can thus be a useful tool
for evaluating the ability of chemistry transport models to simulate the
tropospheric oxidative capacity (Haan and Raynaud, 1998). CO has a
tropospheric lifetime of ∼ 2 months (Novelli et al., 1998), and CO
surface concentrations over Antarctica are thus influenced by oxidation
processes throughout much of the Southern Hemisphere (Haan and Raynaud, 1998;
van der Werf et al., 2013). The NOAA Global Monitoring Division measured a
mean CO surface concentration of 49 ± 2 ppbv for the 1990s, which is
matched by all of our present-day simulations tested with different chemistry
schemes. Wang et al. (2010) recently provided a 650-year Antarctic ice-core
record of concentration and isotopic ratios of atmospheric CO. They measured
CO surface concentrations at the South Pole of 48 ± 4 ppbv for the
year 1777 (± 110 years). Only one (C1-w) out of the six preindustrial
simulations tested with different chemistry and isoprene emission schemes
falls within the range of the observed value. However, in situ production of
CO from organic substrates trapped within the ice may complicate the
comparison between ice-core CO and preindustrial model results (Faïn et
al., 2014; Guzmán et al., 2007; Haan and Raynaud, 1998).
Modeled percent changes in the surface [O3] / [OH] and
[O3] / [RO2] ratios for the present day relative to the
preindustrial and in the surface [OH] concentration for the warm and cold LGM
relative to the preindustrial for different model sensitivity experiments.
Surface [O3] / [OH] and [OH] values are averaged over the
46–66∘ S latitude band to compare with values inferred from
ice-core measurements of Δ17O(SO42-) by Sofen et al. (2014)
and Alexander et al. (2002). Surface [O3] / [RO2] are averaged over
34–54∘ S and 62.5–72.5∘ W (extratropical South America)
to compare with values inferred from ice-core measurements of Δ17O(NO3-) by Sofen et al. (2014), as described in Sect. 3.2.
Chemistry
CO2 sensitivity of
Present-day–preindustrial
Warm LGM–preindustrial
Cold LGM–preindustrial
schemea
plant isoprene emissions
Percent change in surface
[O3] / [OH] over
[O3] / [RO2] over
[OH] over
[OH] over
46–66∘ S (%)
S. America (%)
46–66∘ S (%)
46–66∘ S (%)
C1
without
35
2.3
68
87
with
39
-0.3
105
106
C2
without
42
5.1
93
95
with
42
2.8
105
101
C3
without
38
2.5
102
109
with
40
-0.4
120
117
Observation-derived estimates
260
-60 to -90
40b
40b
a See Table 2 for a full description of the different
chemistry
schemes tested in this study.b Percent increase in sulfate formed from gas-phase oxidation by
OH.
Finally, we compare our preindustrial and LGM model results to isotopic
signatures in the ice-core record. Oxidants transfer unique isotopic
signatures to the oxidation products, and we can take advantage of these
signatures in our model evaluation if they are preserved in the ice-core
record. The Δ17O (=δ17O -0.52×δ18O) of
sulfate, known as Δ17O(SO42-), and of nitrate, Δ17O(NO3-), measure the departure from mass-dependent fractionation in
its oxygen isotopes and reflect the relative importance of different oxidants
in their atmospheric production pathways (Savarino et al., 2000). Sulfate
formation primarily involves ozone, H2O2, and OH, while the main
oxidants relevant to nitrate formation are ozone, RO2 (R = H atom or
organic group), OH, and BrO (Sofen et al., 2014). Such oxygen triple-isotope
measurements have been used to infer the atmospheric formation pathways of
sulfate and nitrate in the present from atmospheric sulfate and nitrate
(e.g.,
Lee et al., 2001; Michalski, 2003) and in the past from ice-core sulfate and
nitrate (e.g., Alexander et al., 2002, 2004). The dominant source region for
Antarctic sulfate is the Southern Ocean marine boundary layer (MBL) (Sofen et
al., 2011), while that for Antarctic nitrate is extratropical South America
(Lee et al., 2014). We thus qualitatively compare our model results for these
respective regions with Antarctic ice-core measurements of
Δ17O(SO42-) and Δ17O(NO3-).
Table 4 lists the simulated percent changes in surface [O3] / [OH] and
[O3] / [RO2] in the present-day scenarios relative to their
respective preindustrial scenarios. Measurements of
Δ17O(SO42-) from the WAIS Divide ice core imply that the
[O3] / [OH] ratio in the Southern Ocean MBL may have increased by
260 % since the early 19th century. Our model results greatly
underestimate the values inferred from observations, with values ranging from
35 to 42 %. Measurements of Δ17O(NO3-) suggest that the
[O3] / [RO2] ratio in the southern hemispheric extratropical
troposphere may have decreased by 60–90 % between the 1860s and 2000,
assuming no change (≤ 5 %) in OH (Sofen et al., 2014). As with the
[O3] / [OH] ratio, the model cannot capture the sensitivity of
[O3] / [RO2] to recent climate change, with changes in the ratio
ranging from -0.4 to +5.1 % depending on the scenario. These
mismatches may be due to deficiencies in our current understanding and model
representation of remote marine boundary layer sulfate formation, as
suggested by Sofen et al. (2014), and potential model underestimates of the
sensitivity of oxidant abundances to climate change (Alexander and
Mickley, 2015).
On glacial–interglacial timescales, measurements of
Δ17O(SO42-) from the Vostok ice core imply that gas-phase
oxidation by OH contributed up to 40 % more to sulfate production during
the last glacial period relative to the interglacial periods before and after
(Alexander et al., 2002). Our simulated percent changes in surface OH
concentrations over the Southern Ocean between the LGM and preindustrial
scenarios range from 68 to 120 % for the warm LGM and 87 to 117 % for
the cold LGM scenarios (Table 4). Given the uncertainties in the model, these
values are remarkably consistent with those inferred from the
Δ17O(SO42-) measurements, both in terms of sign and
magnitude.
In summary, we find that all three chemistry schemes yield present-day methyl
chloroform lifetimes 24–35 % shorter than that inferred from
observations (Prather et al., 2012). For methane, the C1 and C3 lifetimes
fall within the range inferred from observations (Prinn et al., 2005; Prather
et al., 2012), while the C2 chemistry scheme yields a value 21 % too
short compared to the value from Prather et al. (2012). For the OH N / S
ratio, the C3 chemistry falls closest to the observations (Montzka et
al., 2000; Prinn et al., 2001; Krol and Lelieveld, 2003; Bousquet et
al., 2005). Compared to preindustrial ice-core measurements of CO,
application of the C1 scheme with CO2 sensitivity yields the best match,
with the other scenarios underestimating CO by 16–33 %. Slow in situ
production of CO in ice cores may, however, inflate the observed CO values.
Isotopic signatures in sulfate and nitrate provide a means to test the
preindustrial and LGM model estimates of the oxidation capacity. For example,
for all scenarios we find relatively good agreement of the modeled change in
OH since the LGM compared to that derived from measured
Δ17O(SO42-).
Implications for the methane budget
The global methane lifetime against oxidation by tropospheric OH, τCH4,OH, is calculated as defined by Eq. (1). In GEOS-Chem,
atmospheric methane concentrations are prescribed from observations – the
tropospheric mean concentrations are 1743 ppbv for the present day,
732 ppbv for the preindustrial, and 377 ppbv for the LGM scenarios (Murray
et al., 2014, Table 3). The approximately doubled methane concentration
across the LGM-to-preindustrial transition implies an increase in methane
emissions, in its lifetime against oxidation, or some combination of both
factors.
Table 5 and the left panels of Fig. 5 show the global methane lifetimes
against oxidation by tropospheric OH for each combination of climate,
chemistry, and isoprene emission scenarios. In Fig. 5, the dotted orange line
represents results using the “best estimate” lightning and fire emission
scenarios of Murray et al. (2014). Consideration of the CO2 sensitivity of
plant isoprene emissions alone leads to large increases in the past global
isoprene emissions, which in turn depress the tropospheric mean OH burden,
thereby lengthening the methane lifetimes by 1.2 years for the preindustrial,
5.3 years for the warm LGM, and 5.9 years for the cold LGM. Conversely,
implementation of the new isoprene photo-oxidation scheme leads to larger OH
burdens, resulting in decreases in the methane lifetimes – by 1.4 years for
the present day, 2.6 years for the preindustrial, 3.3 years for the warm LGM,
and 3.9 years for the cold LGM. Implementation of the new HO2 uptake
scheme dampens the OH burden, which in turn slightly increases the methane
lifetimes for each climate scenario.
Global methane burden and lifetime against tropospheric oxidation by
OH (τCH4,OH).
Climate
Chemistry
CO2 sensitivity
CH4 burden
Loss by OH in troposphere
τCH4,OH
(Tg)*
(Tgyr-1)
(years)
C1
w
4790
465
10.3
Present day
C2
w
4790
539
8.9
C3
w
4790
497
9.6
C1
wo
2010
184
11.0
w
2010
165
12.2
Preindustrial
C2
wo
2010
238
8.4
w
2010
230
8.7
C3
wo
2010
223
9.0
w
2010
214
9.4
C1
wo
1040
91
11.5
w
1040
62
16.8
Warm LGM
C2
wo
1040
127
8.2
w
1040
112
9.3
C3
wo
1040
120
8.7
w
1040
102
10.2
C1
wo
1040
66
15.8
w
1040
48
21.7
Cold LGM
C2
wo
1040
87
11.9
w
1040
79
13.1
C3
wo
1040
81
12.9
w
1040
72
14.5
* Global burden calculated from mean surface concentration
using a conversion factor of 2.75 TgCH4ppbv-1 (Prather et
al., 2012).
We compare the sensitivity of changes relative to the preindustrial in the
global methane lifetimes and in the implied emissions in the right panels of
Fig. 5. The values shown are relative to their respective preindustrial
scenarios (e.g., C1-w present day relative to C1-w preindustrial). Results
from the “best estimate” scenarios of Murray et al. (2014) suggest that
relative to the preindustrial, the global methane lifetime is reduced by
0.7 years in the present and is increased by 0.5 years at the warm LGM. (As
discussed in Sect. 2.1, comparison with paleo-observations suggests that
their “low-fire, variable-lightning, warm LGM” scenario was the best
representation of the LGM atmosphere.) This minimal increase in the lifetime
at the LGM puts a higher burden on sources in explaining the
glacial–interglacial variability of atmospheric methane concentration.
Assuming no large changes occurred in the minor loss mechanisms, methane
emissions scale with changes in its loss by OH in the troposphere (Table 5).
As defined in Sect. 3.2, the total loss rate of methane with respect to OH
oxidation in the troposphere (Tgyr-1) is calculated from the
integral: ∫surfacetropopausekCH4+OH(T)[OH]CH4dxdydz. For their “best estimate” scenarios, Murray et al. (2014)
report that total methane emissions are 150 % higher in the present
relative to the preindustrial and are reduced by 50 % at the warm LGM.
(a) Calculated global methane lifetime against oxidation by
tropospheric OH for each combination of climate, chemistry, and plant isoprene
emission scenarios. Simulations are as described in Table 2; colors are as in
Fig. 2. The dotted light-orange line represents the results reported in
Murray et al. (2014) for their “best estimate” lightning and fire emissions
scenarios. (b) Changes in the global methane lifetimes (years) and
emissions (%) relative to their respective preindustrial scenarios (e.g.,
C1-w present day relative to C1-w preindustrial). Colors are as in Fig. 3.
Changes in methane emissions are calculated by assuming that they scale with
changes in methane loss by OH in the troposphere.
(a) Tropospheric mean mass-weighted secondary organic
aerosol (SOA) burdens for each combination of climate, chemistry and plant
isoprene emission scenarios. Simulations are as described in Table 2; colors
are as in Fig. 2. The dotted light-orange line represents the results
reported in Murray et al. (2014) for their “best estimate” lightning and
fire emissions scenarios. (b) Percent changes in tropospheric mean
SOA burdens relative to their respective preindustrial scenarios (e.g., C1-w
present day relative to C1-w preindustrial). Colors are as in Fig. 3.
Consideration of the CO2 sensitivity of plant isoprene emissions alone
results in the global methane lifetime being reduced by 1.9 years in the
present and increased by 4.6 years in the warm LGM relative to the respective
preindustrial scenario. This result suggests that methane emissions are
reduced by 62 % at the warm LGM relative to the preindustrial, which
places an even larger burden on sources than in Murray et al. (2014) in
explaining the glacial–interglacial variability of atmospheric methane
concentration. Implementation of the new isoprene photo-oxidation scheme, either with or
without consideration of the CO2 sensitivity of plant isoprene emissions,
results in relatively small changes in methane lifetimes across the
glacial–interglacial or preindustrial-to-present-day timescales. The
resulting estimates of the reductions in methane emissions at the warm LGM
relative to the preindustrial (between 46 and 62 %) are consistent with
the Murray et al. (2014) “best estimate” of 50 %.
In summary, we find little variability in the implied relative
LGM–preindustrial difference in methane emissions with respect to the
uncertainties in isoprene photochemistry and emissions tested in this study.
However, the range of values derived from the loss of methane by OH across
our sensitivity simulations exceeds the 29–42 % decrease in wetland
emissions simulated by the PMIP2 ensemble members (Weber et al., 2010) and
the 16 and 23 % decreases in natural methane emissions simulated by
Kaplan et al. (2006) and Valdes et al. (2005), respectively.
Implications for SOA and radiative forcing
Isoprene oxidation products substantially contribute to SOA formation (Henze
and Seinfeld, 2006), and so our results have implications for past changes in
SOA burdens. Increasingly cooler global temperatures relative to the present
day in the preindustrial, warm LGM, and cold LGM scenarios are expected to
decrease biogenic isoprene emissions. However, such reductions are dampened
or offset when the sensitivity to atmospheric CO2 is also considered,
since biogenic isoprene emissions are enhanced at CO2 concentrations below
present-day levels. The left panel of Fig. 6 shows the global SOA burdens for
each combination of climate, chemistry, and isoprene emission scenarios. The
dotted orange line represents results using the “best estimate” lightning
and fire emission scenarios of Murray et al. (2014). Consideration of the
CO2 sensitivity of plant isoprene emissions alone leads to large increases
in the past global isoprene burdens, which subsequently increases SOA at the
preindustrial and LGM. For example, when the CO2 sensitivity is considered
under the C1 chemistry scheme (i.e., C1-w compared to C1-wo), the relative
increases in the simulated SOA burden are 24 % for the preindustrial,
93 % for the warm LGM, and 80 % for the cold LGM scenarios , as shown
in the left panels of Fig. 6. Conversely, for a given isoprene emission
scenario, changes to the isoprene photo-oxidation and HO2 uptake schemes
lead to much smaller changes in the SOA burdens in each climate scenario.
The right panel of Fig. 6 shows the percent changes in tropospheric mean SOA
burdens relative to their respective preindustrial scenarios (e.g., C1-w
present day relative to C1-w preindustrial). The “best estimate” scenarios
of Murray et al. (2014) – represented by our “C1-wo” simulations –
suggest that relative to the preindustrial, the total SOA burden is 5 %
lower in the present, 42 % lower at the warm LGM, and 50 % lower at
the cold LGM. These values, while relatively robust to variations in the
isoprene photo-oxidation and HO2 uptake schemes, are sensitive to
estimates of the global isoprene burdens for the past atmospheres;
consideration of the CO2 sensitivity of plant isoprene emissions enhances
the present-to-preindustrial difference but reduces the LGM-to-preindustrial
differences in the global SOA burden. For example, under the C1 chemistry
scheme, consideration of the CO2 sensitivity of plant isoprene emissions
leads to decreases of 23 % in the total SOA burden in the present, but
only of 10 and 28 % in the warm and cold LGM scenarios, relative to the
preindustrial.
Implications for tropospheric ozone and radiative forcing
Isoprene and its oxidation products influence the formation and loss of
tropospheric ozone (Beerling et al., 2007). As in Murray et al. (2014), we
find decreasing tropospheric mean ozone burdens in each progressively colder
scenario for each combination of isoprene photochemistry and emissions
scenarios. The “best estimate” scenarios of Murray et al. (2014) –
represented by our “C1-wo” simulations – suggest that relative to the
preindustrial, the tropospheric mean ozone burden is 33 % higher in the
present, 27 % lower at the warm LGM, and 19 % lower at the cold LGM.
These values do not vary more than 8 % for the present day and 5 %
for the LGM when the isoprene photochemistry and/or emission schemes are
varied.
Using the multi-model estimate of 0.042 Wm-2 per DU change in
the mean tropospheric column ozone across the preindustrial–present-day
transition (Stevenson et al., 2013), we estimate that across our sensitivity
simulations, changes in the mean tropospheric column ozone relative to their
respective preindustrial scenarios lead to an average forcing
contribution of +0.3 Wm-2 for the present day. If we extrapolate this
relationship to the LGM–preindustrial transition, we estimate values of
-0.3 Wm-2 for the warm LGM and -0.2 Wm-2 for
the cold LGM. However, accurate quantification of the tropospheric ozone
forcing at the LGM relative to the preindustrial would require the use of an
online radiative transfer model that convolves changes in the ozone
distribution with other radiatively active climate processes.
Factors controlling variability in the tropospheric oxidative capacity
Murray et al. (2014) identified the key parameters that appear to control
global mean OH levels on glacial–interglacial timescales. In this section, we
explore the robustness of their result to the uncertainties in isoprene
photochemistry and emissions tested in this study. Using the steady-state
equations of the ozone–NOx–HOx–CO system, Wang and Jacob (1998) derived
a linear relationship between the global mean OH burden and the ratio
SN/SC3/2, where SN and
SC are the tropospheric sources of reactive nitrogen
(TmolNyr-1) and of reactive carbon (TmolCyr-1),
respectively. Murray et al. (2014) found that on glacial–interglacial
timescales, the linear relationship can be maintained if two additional
factors, which Wang and Jacob (1998) had assumed constant in their
derivation, are also considered: (1) the mean tropospheric ozone photolysis
frequency, JO3 (s-1), and (2) the tropospheric water
vapor concentration, represented by the specific humidity, q
(gH2Okgair-1). In other words,
OH∝JO3qSN/SC3/2.
Figure 7 shows a plot of the tropospheric mean OH burden for each simulation
as a function of JO3qSN/SC3/2, divided into panels according to the chemistry scheme. As in Murray
et al. (2014), SC is calculated as the sum of emissions of CO and
NMVOCs and an implied source of methane equal to its loss rate by OH. While
Murray et al. (2014) assumed that each molecule of isoprene yields an average
2.5 carbons that go on to react in the gas phase, this assumption has been
found to not be robust for different isoprene oxidation schemes, and so we
assume that each isoprene molecule undergoes 100 % gas-phase oxidation
for all of the three chemistry schemes tested in this study.
Tropospheric mean mass-weighted OH burden in each simulation as a
function of JO3qSN/SC3/2, where JO3 is the tropospheric mean mass-weighted
ozone photolysis frequency (s-1), q is the tropospheric mean
mass-weighted specific humidity (gkg-1), and SN and
SC are the tropospheric sources of reactive nitrogen
(TmolNyr-1) and of reactive carbon
(TmolCyr-1), respectively. SC is calculated as the
sum of emissions of CO, NMVOCs, and an implied source of methane equal to its
loss rate by OH. Model results for different chemistry schemes are separated
into three subsets as follows. Top panel: original isoprene chemistry and
original HO2 uptake (C1). Middle panel: new isoprene chemistry and
original HO2 uptake (C2). Bottom panel: new isoprene chemistry and new
HO2 uptake (C3). Different symbols denote different climate scenarios
(present day, preindustrial, warm LGM, cold LGM). Filled symbols represent
simulations in which the CO2 sensitivity of plant isoprene emission is
considered (w); unfilled symbols are those without (wo). All present-day
simulations were performed with CO2 sensitivity turned on. The orange line
shows a reduced major axis regression fit for the C1 subset, with the
regression equation and correlation coefficient (r= 0.87, p< 0.01)
inset. We do not find a statistically significant correlation between OH and
JO3qSN/SC3/2 for the
C2 (r= 0.36) and C3 (r= 0.34) subsets. When the present-day values
are excluded and a multiple regression model is fitted to the remaining
ensemble, we find that the three different chemistry schemes possess the same
values for the slopes of the linear correlation but different values for the
intercepts, as shown by the dashed grey lines (see text for details).
Only the C1 data subset shows a statistically significant correlation
coefficient (r= 0.87, n= 7, p< 0.01); a reduced major axis
regression fit is shown by the orange line in Fig. 7. The breakdown in
linearity for the C2 (r= 0.36) and C3 (r= 0.34) subsets can by
explained by examining the classical tropospheric NOx–HOx–CO–ozone
chemistry upon which the linear relationship is derived. In this classical
chemistry system, HOx-cycling is coupled to NOx-cycling. However, the
new isoprene photo-oxidation mechanism includes additional pathways for
HOx-regeneration and recycling in the absence of NOx. The new mechanism
thus permits HOx-cycling to occur without subsequent production of ozone
through NO2 photolysis, thereby weakening the sensitivity of OH to each of
the individual components of JO3qSN/SC3/2. For example, Murray et al. (2014) found that the
global mean OH independently varied weakly but most strongly with the
photolysis component (JO3) in their simulations. In this study,
the only subset of simulations exhibiting a statistically significant
correlation between OH and JO3 is C1-wo (r= 0.98, n= 4,
p= 0.02). Note that we are assuming the present-day C1-w simulation to be
representative of the C1-wo scenario. This scheme employs the original
isoprene and HO2 uptake schemes without consideration of the
CO2 sensitivity of plant isoprene emissions – i.e., the same as that used
by Murray et al. (2014).
As can be seen by inspection of Fig. 7, the relationship between OH and
JO3qSN/SC3/2 differs
between the LGM-to-preindustrial and preindustrial-to-present-day transitions
for all of the three data subsets. With the present-day values excluded, we
test whether the slope and intercept values are significantly different
between the chemistry schemes by fitting a multiple regression model with
JO3qSN/SC3/2 as a
continuous explanatory variable and chemistry scheme as a categorical
explanatory variable. We find that the three correlations have different
values for the intercepts whereas the values for the slopes do not
significantly differ (Fig. 7, dashed grey lines). The value of the intercept
is largest for the C2 ensemble, followed by C3 and then C1. This sequence
follows from our finding in Fig. 2, described in Sect. 3.1, that the new
isoprene photo-oxidation mechanism leads to larger tropospheric mean OH
burdens for each climate scenario compared to those simulated by the original
mechanism. Implementation of the new HO2 uptake scheme dampens this
increase, but values remain above those from the C1 ensemble. We postulate
two main reasons why the slope of OH to JO3qSN/SC3/2 appears to be less steep across the industrial era than across the
glacial–interglacial period. First, it is likely that heterogeneous
reactions that can also act as HOx sinks but are not considered in the
derivation of the linear relationship, such as N2O5 hydrolysis and
HO2 uptake by aerosols, become more important under present-day
conditions. In the present day, tropospheric aerosol mass loading is
17–20 % higher than the preindustrial and 36–52 % higher than the
warm and cold LGM scenarios. Second, there is a dramatic shift in the
altitudinal distribution of tropospheric NOx emissions. The ratio of
lightning to surface NOx emissions is 0.16 for the present day, 0.50 for
the preindustrial, 0.73 for the warm LGM, and 0.79 for the cold LGM. The much
lower present-day ratio is primarily due to large anthropogenic surface
NOx emissions, especially in the Northern Hemisphere (Murray et al., 2014,
Fig. 5). This could lead to relatively more efficient NOx removal by wet
and dry deposition and by formation of organic nitrates, which would both
reduce primary and secondary OH production. However, these hypotheses need to
be examined in greater detail, and an evaluation of potential weaknesses of
the linear relationship between OH and JO3qSN/SC3/2 that operate independently of the classic
photo-oxidation mechanism is described by Murray et al. (2015).
Discussion and conclusions
Using a detailed
climate–biosphere–chemistry framework, we evaluate the sensitivity of
modeled tropospheric oxidant levels to recent advances in our understanding
of biogenic isoprene emissions and of the fate of isoprene oxidation products
in the atmosphere. We focus on this sensitivity for the present day
(ca. 1990s), preindustrial (ca. 1770s), and the LGM (∼ 19–23 ka). The
3-D global ICECAP model employed here considers the full suite of key factors
controlling the oxidative capacity of the troposphere, including the effect
of changes in the stratospheric column ozone on tropospheric photolysis rates
(Murray et al., 2014). Our study, which revisits Murray et al. (2014), takes
into account the sensitivity of plant isoprene emissions to atmospheric
CO2 levels and considers the effects of a new isoprene photo-oxidation
mechanism (Paulot et al., 2009a, b) and a potentially larger role for
heterogeneous HO2 uptake (Mao et al., 2013a). We perform a systematic
evaluation of the sensitivity of the chemical composition of past atmospheres
to these developments.
We simulate two possible realizations of the LGM, one significantly colder
than the other, to bound the range of uncertainty in the extent of tropical
cooling at the LGM. For each climate scenario, we test three different
chemistry schemes: C1 uses the original isoprene chemistry and original HO2
uptake, C2 uses the new isoprene chemistry and original HO2 uptake, and C3
uses the new isoprene chemistry and new HO2 uptake
mechanisms. Each chemistry scheme
is tested with or without inclusion of the CO2 sensitivity of biogenic
isoprene emissions, except for the present day for which consideration of the
CO2 sensitivity results in only a 4 % change in the global isoprene
burden. We find that consideration of the CO2 sensitivity of biogenic
emissions enhances plant isoprene emissions by 27 % in the preindustrial
and by 77–78 % at the LGM relative to respective estimates that do not
take into account the CO2 sensitivity. This implementation increases
global isoprene emissions in the warm LGM scenario by 15 % relative to
the preindustrial. At the LGM, lower sea levels
exposed extensive land area in
equatorial Asia and Australia, resuling in large regional increases in
plant isoprene emissions (Murray et al., 2014, Fig. 7). When we account for
the potential increase in biogenic isoprene emissions at low CO2
concentrations, this implementation swamps the effect of cooler temperatures
in the warm LGM scenario.
We find that different oxidants have varying sensitivity to the assumptions
tested in this study, with OH being the most sensitive. Although Murray et
al. (2014) estimated that OH is relatively well buffered on
glacial–interglacial timescales, we find that this result is not robust to
all of the assumptions tested in this study. Across our sensitivity
simulations, changes in the global mean OH levels for the
LGM-to-preindustrial transition range between -29 and +7 % and those
for the preindustrial-to-present-day transition range between -8 and
+17 %. However, consistent with Murray et al. (2014), we find reduced
levels of ozone, H2O2, and NO3 for the past atmospheres relative to
the present day in our ensemble of sensitivity simulations. That study also
reported a linear relationship between OH and tropospheric mean ozone
photolysis rates, water vapor, and total emissions of NOx and reactive
carbon (JO3qSN/SC3/2) on
LGM-to-present-day timescales. We find that the new isoprene photo-oxidation
mechanism causes a breakdown in this linear relationship across the entire
period, as the new mechanism permits HOx-cycling to occur without
subsequent production of ozone through NO2 photolysis, thereby weakening
the feedback on OH production per RO2 consumed. We propose that the
sensitivity of OH to changes in JO3qSN/SC3/2 may be lower for the preindustrial-to-present-day
than the LGM-to-preindustrial transition. This is most likely because NOx
and HOx loss processes not considered in the classical
NOx–HOx–CO–ozone system (from which the linear relationship is
derived) become more important under present-day conditions.
We find little variability in the implied relative LGM–preindustrial
difference in methane emissions with respect to the uncertainties in isoprene
photochemistry and emissions tested in this study. The resulting estimates of
the reductions in methane emissions at the warm LGM relative to the
preindustrial (between 46 and 62 %) are comparable to the Murray et
al. (2014) “best estimate” of 50 %. However, the range of our implied
values exceed those derived from prior model studies of wetland emission
changes (Valdes et al., 2005; Kaplan et al., 2006; Weber et al. 2010). Our
findings also have implications for radiative forcing estimates of SOA on
preindustrial–present and glacial–interglacial timescales. For example, the
“best estimate” scenarios of Murray et al. (2014) suggest that relative to
the preindustrial, the total SOA burden is 5 % lower in the present and
42 % lower at the LGM. Here, we find decreases ranging between 2 and
23 % in the present and 10 and 44 % at the LGM relative to the
preindustrial across our sensitivity experiments. The climate effects of
biogenic SOA are not well characterized but are thought to provide regional
cooling (Scott et al., 2014). Our work thus suggests that SOA reductions may
have amplified regional warming in the present but minimized regional cooling
at the LGM relative to the preindustrial. Results from these sensitivity
studies, however, underscore the large uncertainties in current model
estimates of SOA radiative forcing across long timescales (e.g., Scott et
al., 2014; Unger and Yue, 2014; Unger, 2014a). Unlike SOA, we find that
changes in tropospheric mean ozone burdens relative to the preindustrial are
insensitive to the uncertainties in isoprene emissions and photochemistry
tested in this study. Relative to the preindustrial, the absolute magnitude
of the radiative forcing from the change in tropospheric ozone at the LGM may
be comparable to that of the present day. However, accurate quantification of the tropospheric ozone forcing at the LGM relative to the preindustrial requires the use of an online radiative transfer model that convolves changes in the ozone distribution with other radiatively active climate processes. Nonetheless, most climate simulations of the LGM still use preindustrial ozone values as boundary conditions, including this study and the Paleoclimate Modelling Intercomparison Project 2 (PMIP2; Braconnot et al., 2012).
Besides SOA, changes in biogenic VOC emissions also affect the atmospheric
concentrations of other climate forcing agents. Recent studies have
demonstrated the importance of considering the net effect of human-induced
changes in biogenic VOC emissions on global climate forcing over the
industrial period (e.g., Unger, 2014a, b; Heald et al., 2014; Heald and
Spracklen, 2015). Unger (2014a) quantified the global radiative impact of
changes to the atmospheric concentrations of ozone, methane, and SOA due to a
reduction in the emission of biogenic VOCs resulting from global cropland
expansion between the 1850s and 2000s. She estimated a net cooling of
-0.11 ± 0.17 Wm-2, which is comparable in magnitude but
opposite in sign to the net forcing from the changes in surface albedo and
land carbon release associated with cropland expansion. When other known
anthropogenic influences on biogenic VOC emissions are also considered, the
net global climate forcing is estimated to be -0.17 Wm-2
(Unger, 2014b). Our work demonstrates that reducing the uncertainties on such
an estimate will require improvements in our knowledge of isoprene
photochemistry and CO2 sensitivity, as well as reconciling model estimates
of land-cover change over the industrial period.
We find that biogenic VOC emissions decrease by 8 % in the present day
relative to the preindustrial due to changing meteorology, redistribution of
natural vegetation, and cropland expansion and by 25 % when the CO2
sensitivity of isoprene emissions is also considered. The larger reduction is
comparable to results from previous studies that have estimated a
20–26 % reduction in biogenic VOC emissions from the late 19th century
to the present day (Lathiere et al., 2010; Pacifico et al., 2012; Unger,
2013). Consistent with our study, Lathiere et al. (2010) determined that the
CO2 sensitivity effect is the dominant driver of
the change in isoprene emissions between 1901 and 2002, with the impact of
land-use change about half that of CO2 sensitivity. In contrast, Pacifico
et al. (2012) and Unger (2013) found cropland expansion to be the dominant
driver of the reduction. This discrepancy likely arises for two reasons.
First, our study applied an increase of approximately 10 % in global
cropland expansion (Guenther et al., 2012), which is smaller than the
22 % change estimated by Unger (2013). Second, we apply a CO2
sensitivity algorithm that most likely provides an upper limit of this effect
for past climates (Possell and Hewitt, 2011).
The primary goal of this model study is to explore the sensitivity of the
oxidative capacity of present and past atmospheres to assumptions about
isoprene emissions and the fate of its oxidation products. We are reluctant
to offer “best guess” estimates in large part because the uncertainty in
the CO2–isoprene interaction is substantial and our knowledge of the
isoprene photo-oxidation mechanism is still evolving. Some studies have
suggested that canopy-scale processes may complement or offset the leaf-scale
response to atmospheric CO2 levels (e.g., Sun et al., 2013). Also, it is
likely that the application of the same CO2 sensitivity parameterization
to all PFTs leads to an overestimate of this effect. As discussed below,
observations of the relevant chemical species that could constrain the
oxidative capacity of past atmospheres are sparse. Laboratory and field
measurements, however, strongly suggest that the C1 chemistry scheme is an
inadequate representation of the isoprene photo-oxidation mechanism (Paulot
et al., 2009a, b; Mao et al., 2013b). Therefore, model studies that depend on
a simple, C1-like isoprene photo-oxidation scheme are likely outdated,
particularly with respect to their ability to accurately simulate the
tropospheric oxidative capacity. All of the models participating in the
ACCMIP study in support of the IPCC AR5 used a C1-like isoprene
photo-oxidation mechanism (Naik et al., 2013). Our results demonstrate that
even under identical emission scenarios, the original and new isoprene
photo-oxidation mechanisms yield different interpretations of various
parameters such as changes in global mean OH and methane lifetime across the
preindustrial–present-day transition.
Quantifying the oxidative capacity of past atmospheres remains an ongoing
challenge because the oxidants are not directly preserved in the ice-core
record, and paleo-proxies that can provide a simple and robust constraint
have not been readily identified (Levine et al., 2011a; Alexander and
Mickley, 2015). Our results call for greater attention and research efforts
in the following measurements to help constrain model estimates of the
oxidative capacity of past atmospheres. (1) Ice-core CO: quantifying the
amount of CO produced in situ from organic substrates trapped within the ice
would facilitate the use of ice-core CO measurements as constraints for model
results. (2) Ice-core Δ17O(NO3-): because of its greater
sensitivity to oxidant abundances, ice-core measurements of
Δ17O(NO3-) may in fact provide a more robust proxy than
Δ17O(SO42-) for reconstructing the oxidation capacity of past
atmospheres. For example, cloud amount and pH do not influence the isotopic
composition of nitrate as they do for sulfate (Levine et al., 2011a). In
particular, measurements of Δ17O(NO3-) in tropical ice cores,
which are so far sparse, may be highly valuable given that the dominant
natural sources of NOx and production of OH are most prevalent in the
tropics (Buffen et al., 2014); (3) field campaigns focused on measurements of
oxidant cycling in high-isoprene, low-NOx environments. Such a suite of
observations will help constrain the modeled sensitivity of tropospheric
oxidants to past climate changes.
The main scientific value of our study lies in its demonstration of the
importance of biogenic VOC emissions and the fate of their oxidation products
in influencing chemistry–climate interactions across the last
glacial–interglacial time interval and the industrial era. Because of
existing uncertainties in isoprene emissions and photochemistry, there are
larger uncertainties in model estimates of the oxidative capacity of past
atmospheres than previously acknowledged. For example, Levine et al. (2011b)
concluded that the effects of temperature and specific humidity cancel out
the effects of biogenic NMVOCs on OH across glacial timescales, with or
without consideration of OH-recycling under low-NOx conditions in the isoprene photo-oxidation mechanism. However, using a more
complex tropospheric chemical mechanism, including a more detailed
representation of OH-recycling under low-NOx conditions, as
well as considering the effects of the CO2 sensitivity of plant isoprene
emissions and of changes in the stratospheric column ozone and tropospheric
NOx emissions, we demonstrate that uncertainties in the
LGM-to-preindustrial change in OH remain substantial. Such uncertainties, in
turn, limit our confidence in estimating radiative forcing due to changes in
short-lived species such as SOA over time, as well as our ability to identify
the factors controlling global mean OH levels between the LGM and the present
day.
Constraining the anthropogenic radiative forcing over the industrial period
inherently depends on our ability to quantify the chemical composition of the
preindustrial atmosphere. In particular, assessing the radiative forcing from
changes involving biogenic processes is an ongoing challenge in the modeling
community but has importance in the coming decades as policymakers face
decisions that depend critically on accurate knowledge of the atmospheric
oxidative capacity. For example, recent studies have demonstrated the
importance of considering the net effect of human-induced changes in biogenic
VOC emissions on global climate forcing over the industrial period (e.g.,
Unger, 2014a, b; Heald et al., 2014; Heald and Spracklen, 2015). Tackling the
long-standing issue of the dynamics of future global methane sources and
sinks is also crucial for the next generation of climate projections (Quiquet
et al., 2015; Kirschke et al., 2013). However, including detailed
photochemical mechanisms in chemistry–climate models is computationally
expensive. In the ACCMIP models involved in the IPCC assessments of the
preindustrial and present day, the tropospheric chemical mechanisms of
non-methane hydrocarbons were represented in varying degrees of complexity
(Lamarque et al., 2013), and the isoprene photo-oxidation mechanisms did not
consider HOx-recycling under low-NOx conditions (Naik et al., 2013).
Chemistry–climate models attempting to explain methane trends since the Last
Glacial Maximum have also historically depended on relatively simple schemes
for isoprene photo-oxidation (e.g., Valdes et al., 2005; Kaplan et
al., 2006). Our work points to the value of incorporating into such models
both current knowledge and the associated uncertainties regarding biogenic
isoprene emissions and photochemistry.