Introduction
Solar geoengineering, or solar radiation management (SRM) has the possibility
of deliberately introducing changes to the Earth's radiative balance to
partially offset the radiative forcing of accumulating greenhouse gases and
so lessen the risks of climate change. Most research on SRM has concentrated
on the possibility of adding aerosols to the stratosphere, and essentially
all atmospheric modeling of stratospheric aerosol injection has focused on
increasing the loading of aqueous sulfuric acid aerosols (Rasch et al., 2008;
Heckendorn et al., 2009; Niemeier et al., 2011; Pitari et al., 2014). The
possibility that solid aerosol particles might offer advantages over
sulfates, such as improved scattering properties, was first suggested almost
2 decades ago, but analysis has been almost exclusively limited to
conceptual studies or simple radiative transfer models (Teller et al., 1997;
Blackstock et al., 2009; Keith, 2010; Ferraro et al., 2011; Pope et al.,
2012).
Any solid aerosol injected directly into the stratosphere for geoengineering
purposes would be subject to coagulation with itself and with the natural
background or volcanic sulfate aerosol. Aggregates of solid aerosols have
very different physical structure and scattering properties than liquid
sulfate aerosol particles do. The lifetime and scattering properties of a solid
aerosol are strongly dependent on these dynamical interactions, and the
chemical properties of the aerosol depend on the extent to which it becomes
coated by the ambient sulfate.
We have modified the Atmospheric and Environmental Research (AER)
two-dimensional (2-D) chemistry–transport–aerosol model (Weisenstein et al., 2004,
2007) to capture the dynamics of interacting solid and liquid aerosols in
the stratosphere. Our model now includes a prognostic size distribution for
three categories of aerosols: liquid aerosols, solid aerosols, and
liquid-coated solid aerosols. The model's coalescence kernel has been
modified and extended to parameterize the interactions of particles across
size bins and between all combinations of the three categories. The surface
area, sedimentation speed, and coalescence cross section of an aggregate of
solid particles depend on the geometry of the aggregate. The model
parameterizes this physics using a fractal dimension and allows that fractal
dimension to change with age or with a liquid coating. The chemistry and
aerosol schemes in the model are interactive, while dynamical fields are
prescribed.
Turning now to the context of this work, it is useful to divide overall
consideration of the risks and efficacy of SRM into two components. First,
the ability, or efficacy, of idealized SRM – conceived as a reduction in the solar
constant – to compensate for the risks of accumulating greenhouse gases
and, second, the technology-specific risks of any specific engineered intervention that produces a
change in radiative forcing. Uncertainty in the efficacy of SRM, the first
component, rests on uncertainty in the climate's large-scale response to
forcing. Results from a large set of climate models suggest that idealized
SRM can do a surprisingly good job in reducing model-simulated climate
changes, both locally and globally, which, in our view, is a primary
motivation for continued research on SRM (Kravitz et al., 2014; Moreno-Cruz
et al., 2011).
Evaluation of the technology-specific risks depends on the specific
technology. For sulfate aerosols these risks include, but are not limited
to, (a) ozone loss, (b) radiative heating of the lower stratosphere which
causes changes in atmospheric temperature and dynamical transport, and (c) the fact that sulfates produce a relatively high ratio of downward
scattering to upward scattering so that they substantially increase the
ratio of diffuse to direct radiation (Kravitz et al., 2012) which in turn
may alter atmospheric chemistry and ecosystem functioning (Mercado et al.,
2009; Wilton et al., 2011). In addition to the risks, it may be difficult to
produce sufficiently large radiative forcings using SO2 because of the
decreasing efficiency at higher SO2 inputs (Heckendorn et al., 2009;
English et al., 2012).
The use of solid particles for SRM offers the potential to address all of the
limitations of sulfate particles. Solid aerosols do not, for example,
directly increase the stratospheric volume of the aqueous sulfuric acid that
drives hydrolysis reactions, an important pathway through which sulfate
aerosols cause ozone loss. In addition, some solid aerosols (e.g., diamond,
alumina, or titania) have optical properties that may produce less heating
in the lower stratosphere (Ferraro et al., 2011), and any solid with a high
index of refraction can reduce forward scattering.
The use of solid aerosols, however, introduces new risks that require
evaluation. The dry surfaces of the solid aerosols, for example, may
catalyze reactions that cause ozone loss (Tang et al., 2014a, b). This
risk is hard to evaluate because the rates of many potentially important
chemical reactions remain unmeasured for substances such as diamond that are
novel in the stratosphere. Moreover, by spreading the natural background
sulfuric acid over a larger surface area as will occur when background
sulfate coats the solid particles, the addition of solid aerosols will
increase reactions that depend on sulfate surface area density rather than
sulfate volume.
Our motivation for studying solid particles is the possibility that they
enable a decrease in the risks of SRM (e.g., ozone loss) or an increase in
its efficacy such as the ability to produce larger radiative forcings, or an
improved ability to “tune” the spectral or spatial characteristics of the
radiative forcing (Blackstock et al., 2009; Keith, 2010). This is in
contrast to much of the prior literature that has focused on the potential
of solid particles to deliver higher mass-specific scattering efficiency,
thus reducing the amount of material needed to produce a given radiative
forcing. We do not see this as an important motivation as it appears that
the cost of lofting materials to the stratosphere is sufficiently low that
cost is not an important barrier to implementation of SRM (McClellan et al.,
2012).
In this paper, our focus is on developing the tools and methodology for
assessing the risks and performance of solid particles injected into the
stratosphere for SRM. The tool described here is a new solid–liquid
stratospheric aerosol model, and the methodology is a comparison of
environmental side effects such as ozone loss and forward scattering as a
function of the global radiative forcing. We use aluminum oxide (alumina)
aerosol as the primary example. Diamond appears to be superior to alumina in
several respects, perhaps the most important being that it has minimal
absorption in the thermal infrared. We examine diamond, but choose alumina
as the primary example because there is a broad basis to examine alumina's
potential environmental impacts. Unlike many other solid particles proposed
for SRM, there is prior work examining alumina's impacts on stratospheric
chemistry (Danilin et al., 2001; Jackman et al., 1998; Ross and Sheaffer,
2014), work that was produced from NASA-funded studies starting in the late
1970's motivated by concerns about the ozone impact of space shuttle
launches (alumina is a major component of the shuttle's solid rocket exhaust
plume). Moreover, alumina is a common industrial material with a high index
of refraction for which there is substantial industrial experience with the
production of nanoparticles (Hinklin et al., 2004; Tsuzuki and McCormick,
2004). With respect to potential environmental impacts of alumina deposition
on Earth's surface, the fact that aluminum oxides are a common component of
natural mineral dust deposition provides a basis for assessing impacts
(Lawrence and Neff, 2009). For diamond, there is evidence that diamond
nanoparticles are nontoxic to biological systems (Shrand et al., 2007). A
much more substantive assessment of the human health and ecosystems impacts
of any proposed solid aerosol would be required, however, prior to serious
consideration of their use for geoengineering.
The remainder of this paper is organized as follows: the solid–liquid model
is presented in Sect. 2, results for geoengineering injection of alumina
and diamond in Sect. 3, and discussion in Sect. 4.
Aerosol model
We have incorporated solid aerosols into the AER 2-D
chemistry–transport–aerosol model (Weisenstein et al., 1997, 2004, 2007). The
aerosol module, which employs a sectional scheme, has been modified to
include three separate classes of aerosols, each with its own size
distribution: solid particles, liquid H2SO4–H2O particles,
and mixed solid–liquid particles. To fully specify the mixed particles we
keep track of the volume of liquid H2SO4–H2O solution coating
the mixed particles. Unlike liquid particles that coagulate into larger
spheres, solid particles coagulate into fractal structures with more complex
properties. The fractal properties are required to predict the effective
size of the particles appropriate to determining coagulation interactions
and gravitational settling. Fractal properties are also needed to determine
the condensation rate of H2SO4 gas onto alumina particles and the
aerosol surface area density that is important to heterogeneous chemistry
and ozone depletion.
The AER 2-D model includes standard chemistry relevant to ozone (Weisenstein
et al., 2004) as well as aerosol microphysics, and the relevant sulfur
chemistry (Weisenstein et al., 1997, 2007). The model includes
sulfur-bearing source gases dimethyl sulfide (DMS), CS2, H2S, OCS,
and SO2 emitted by industrial and biogenic processes as well as the
product gases methyl sulfonic acid (MSA), SO2, SO3, and
H2SO4. Chemical reactions affecting sulfur species are listed in
Weisenstein et al. (1997) and their rates have been updated according to
Sander et al. (2011). Values of OH and other oxidants are calculated
interactively along with ozone and aerosols (Rinsland et al., 2003;
Weisenstein et al., 2004). Further description of the chemistry directly
relevant to ozone is included in Sect. 3.5. The model's 2-D transport is
prescribed based on calculations by Fleming et al. (1999) for each year from
1978 to 2004, employing observed temperature, ozone, water vapor, zonal
wind, and planetary waves. Different phases of the quasi-biennial
oscillation (QBO) are included in the observational data employed. We
average the transport fields over the years 1978–2004 into a climatology and
employ that circulation each year of our 10-year calculations. Temperature
fields are also prescribed based on climatological observations for the same
averaging period. The domain is global, from the surface to 60 km, with
resolution of 1.2 km in the vertical and 9.5∘ in latitude. Though the
model is primarily suited to modeling the stratosphere and upper
troposphere, it does contain a parameterization of tropospheric convection
(Dvortsov et al., 1998) that serves to elevate SO2 concentrations in
the tropical upper troposphere.
The AER 2-D aerosol model, along with several other 2-D and 3-D models, was
evaluated and compared to observations in SPARC (2006). The AER model was
found to reasonably represent stratospheric aerosol observations in both
nonvolcanic conditions and in the period following the eruption of Mt.
Pinatubo. Noted deficiencies, common to most models, included values of aerosol
extinction in the tropics calculated to be too high between the
tropopause and 25 km as compared to SAGE II extinctions at 0.525 and 1.02 µm during nonvolcanic periods. The growth and decay of the
stratospheric aerosol layer following the Mt. Pinatubo eruptions was
generally well-represented by the AER model as compared to lidar and
satellite observations from 1991 to 1997, though uncertainties in the
initial SO2 injection amount and vertical distribution limit our
interpretation. Dynamical variability on short timescales was
underestimated by the model.
Sulfate aerosol formation is thought to be initiated mainly by binary
homogeneous nucleation of H2SO4 and H2O vapors, primarily in
the tropical tropopause region. The aerosol size distribution is modified by
condensation and evaporation of gas-phase H2SO4 and by coagulation
among particles (Brock et al., 1995; Hamill et al., 1997). Sulfate aerosol
particles are assumed to be liquid spheres with equilibrium composition
(H2SO4 and H2O fractions) determined by the local grid box
temperature and water vapor concentration (Tabazadeh et al., 1997). The
model uses a sectional representation of particle sizes, with 40
logarithmically spaced sulfate aerosol bins, representing sizes from 0.39 nm
to 3.2 µm, with aerosol volume doubled between adjacent bins. Particle
distributions are also modified by sedimentation and by rainout/washout
processes in the troposphere. The sedimentation formulation is described
below. Rainout/washout process are represent by a first-order loss term in
the troposphere with removal lifetime ranging from 5 days at the surface to
30 days at the tropopause.
Solid particles are modeled with a similar sectional representation; in this
case it is the number of monomers per particle that is doubled in successive
bins. Only the monomers, the primary particles directly injected into the
atmosphere, are assumed to be spherical. Larger particles produced by coagulation
assume fractal structures that obey a statistical scaling law where the
fractal dimension Df determines how the size of an aggregate of
particles is related to the number of primary particles (Filippov et al.,
2000; Maricq, 2007). The radius of gyration Rg of a fractal (the
root-mean-square distance from the center of mass) is given
by
Rg=R0(Ni/kf)(1/Df),
where R0 is the primary particle radius, Ni the number of monomers
in the fractal of bin i, and kf is a prefactor. Thus particle mass is
proportional to RgDf. The fractal dimension Df for a given
material has been found to be invariant for a wide range of R0 and
Ni values.
The surface area (S) for a fractal particle can be parameterized with an
effective radius Reff which can be related to primary radius and the
number of monomer cores in the particle:
Reff=R0(Ni/kh)(1/Dh)Si=(4πR02)×(Ni/kh)(2/Dh),
where Dh and kh are the scaling exponent and prefactor specific to
surface transfer processes. With fractal dimension Df<2.0,
Dh can be assumed to be equal to 2.0. With Df>2.0,
Dh can be assumed to be equal to Df (Filippov et al., 2000). When
Dh = 2.0, the surface area of a fractal particle is equal to the
surface area of the monomer multiplied by the number of monomers in the
aggregate. This formalism is most appropriate for large values of Ni (i.e., greater than 100). For consistency at small values of Ni, we
assume that kf=kh=1, since we find that simulations
producing only small Ni values are most efficient for geoengineering.
The solid particles are allowed to interact with background stratospheric
sulfate particles by coagulation, and with gas-phase H2SO4 and
H2O by condensation and evaporation. We use Rg as the particle
radius when calculating the coagulation kernel, the probability that two
particles will combine into one on collision (Maricq, 2007). The coagulation
formulation between and among different particle types is detailed in
Appendix A. The condensation rate, also detailed in Appendix A, depends on
particle surface area, and secondarily, on a radius of curvature for the
Kelvin correction. We use R0 as the radius-of-curvature in the
condensation equation, since gas molecules see the individual monomers
making up the fractal. We model mixed-phase particles by tracking particle
number per bin and mass of H2SO4 per bin in the mixed particles.
Volume and surface area of the mixed particles depends also on the H2O
present in the equilibrium H2SO4–H2O solution. Above about 35 km, coated particles will lose their sulfate coating by evaporation and
become dry again.
The sedimentation velocity of fractal particles represents a balance between
the gravitational force, proportional to particle mass, Mp, and the
drag force, proportional to the particle velocity and the 2-D
surface area projection of the particle, A2-D, and inversely
proportional to the particle radius Rp. Sedimentation velocity is
modified by the Cunningham slip-flow correction, G, which accounts for
larger sedimentation velocities with lower air density (Seinfeld and Pandis,
2006). We obtain sedimentation velocity Wsed from
Wsed=(MpgRpG)/(6ηA2-D),
where η is the viscosity of air and g the gravitational constant. For
spheres, Wsed is proportional to Rp2. For all fractal cases,
Rp is taken to be Rg, and with Df≥2, the area
projection is taken to be πRg2, yielding a Wsed
proportional to G×Ni(Df-1)/Df. With Df<2, the
fractal is porous and the area projection is Ni×πR02,
yielding a Wsed proportional to G×Ni(1/Df) (Johnson et al.,
1996). For coated particles, the particle mass, Mp, is the sum of the
solid particle mass and H2SO4–H2O mass, and particle radius
is taken to be Rg increased by the thickness of a uniform coating.
However, when the radius of a sphere enclosing the total particle volume is
larger than Rg plus a monolayer of H2SO4, we use the
spherical radius rather than Rg.
Model results
Before turning to the results, we use the following sub-section to describe
(and provide some rationale for) the solid aerosol particles that we choose
as test cases, and then in Sect. 3.2 we describe a few results regarding
the sedimentation of aggregates that are useful in understanding the model
results.
Test cases: alumina and diamond aerosol particles
Several prior studies have examined a range of possible solid aerosols and
performed some simple optimizations (Teller et al., 1997; Pope et al., 2012;
Blackstock et al., 2009). For simplicity we only considered spherical
dielectric particles made of materials that have negligible solubility in
the aqueous sulfuric acid found under typical stratospheric conditions. An
ideal material for SRM would have (a) a high index of refraction, (b) a
relatively low density, (c) negligible absorption for both solar and thermal
infrared spectral regions, and finally (d) it should have well-understood
surface chemistry under stratospheric conditions. In addition, even though
this research is exploratory, materials are more plausible as candidates for
deployment for SRM if they have low and well-understood environmental
toxicity and if there is a track record of production of industrial
quantities of the material in the appropriate half micron size regime.
We chose alumina, or aluminum oxide (Al2O3), as our primary test
case because it has a relatively high index of refraction (n=1.77 in the
middle of the solar band) and because there is a substantial literature on
its chemistry (Molina et al., 1997; Sander et al., 2011) and stratospheric
chemical impact (Danilin et al., 2001; Jackman et al., 1998). However,
alumina has infrared absorption bands in the thermal infrared that will
reduce its net radiative forcing and will cause some heating of the lower
stratosphere (Ross and Sheaffer, 2014).
Overview of experiments performed with the AER 2-D model.
Substance
Injected particle
Injection rate
Fractal dimension
Comments
injected
radius
(Tg yr-1)
Df
Alumina
R0=80 nma
1, 2, 4, 8
1.6, 2.8
Alumina
R0=160 nma
1, 2, 4, 8
1.6, 2.8
Alumina
R0=240 nma
1, 2, 4, 8, 16
1.6, 2.8
Alumina
R0=320 nma
1, 2, 4, 8
1.6, 2.8
Diamond
R0=160 nma
1, 2, 4, 8
1.6
SO2
Gas phase
1, 2, 4, 10c
Replication of Pierce et al. (2010)
H2SO4
Rg=95 nm, σ=1.5b
1, 3, 6, 15c
Replication of Pierce et al. (2010)
a monomers of uniform radius;
b log-normal distribution defined by mode radius, Rg,
and width, σ, representing distribution after plume processing;
c based on molecular weight of SO2 or H2SO4, not S
alone.
We chose diamond as a secondary test case because of its near-ideal optical
properties: it has a very high index (n=2.4) and negligible absorption for
both solar and thermal infrared spectral regions. Despite this we did not
choose diamond as the primary test case because there are few data about
the chemistry of relevant compounds on diamond surfaces under stratospheric
conditions, and also, while industrial synthetic submicron diamond is now
available at under USD 100 per kilogram, there is still far less industrial
heritage on diamond production to assess the challenges of scaling
production technologies to hundreds of thousands of tons per year.
Alumina is an important industrial material as a precursor for aluminum
production and for a variety of uses, from sunscreen compounds applied to the
skin to industrial catalysis. The global production rate is approximately
100 Tg yr-1 (USGS, 2014). There is a very large body of experience in
making alumina nanoparticles. For example, liquid-feed flame spray pyrolysis
is used to make structured nanoparticles of alumina in quantities greater
than 1 kt yr-1 (Hinklin et al., 2004). As we will see, the optimal size
for a spherical alumina particles used as a scatterer in the stratosphere is
of order 200 nm radius. Most of the industrial effort is focused on making
smaller particles for catalysis but there are examples of production of
relatively monodisperse particles with radii greater than 50 nm (Hinklin et
al., 2004; Tsuzuki and McCormick, 2004).
For the purposes of this paper we will assume that it is possible to make
roughly spherical alumina particles with a size range between 50 and 400 nm
radius. This is a working assumption that seems plausible based on the very
large technical literature (> 1000 papers in the last decade on
alumina nanoparticles) and industrial base devoted to production of these
materials. But it is simply an assumption. A significant effort involving
experts from industry and academia would be required to meaningfully assess
the difficulty of producing large quantities of alumina with a suitable size
and morphology for solar geoengineering.
There is rapidly growing industrial production of sub-micron diamond powders
(Krueger, 2008), so there is no doubt that particles with appropriate
morphology can be produced. However, the industrial production volumes and
academic literature on production technologies are far smaller than for
alumina.
Table 1 lists the numerical experiments performed for this study with the
AER 2-D model. Simulations with alumina particles employ a range of injected
monomer sizes, from 80 to 320 nm in radius. These simulations allow us to
analyze the trade-offs between sedimentation rate, radiative forcing, and
ozone depletion. For diamond, we perform simulations only for injected
monomer sizes of 160 nm, near the radiative optimum. We also repeat
simulations performed by Pierce et al. (2010) for geoengineering injections
of SO2 and H2SO4. A range of injection rates is used for each
injected substance and each injected monomer radius to test linearity of the
response. Each scenario is calculated with a 10-year integration period,
using dynamical fields representing the 1978–2004 average repeated each year
and fixed boundary conditions from approximately the year 2000, until an
annually repeating result is achieved. We analyze results from the final
year of each calculation, concentrating on annual average conditions.
Factors controlling settling of aggregates
As discussed above, the dynamics of aggregated particles depend on their
fractal dimension Df. No observational data on the fractal dimension of
∼ 100 nm hard spheres aggregating under stratospheric
conditions are available. As a guide, we adopt the value of Df obtained
in studies of the formation of fractal alumina aggregates from much smaller
monomers at atmospheric pressure produced by combustion and oxidation of
liquid aluminum drops that can result from burning solid rocket fuel. These
studies, which produced aggregates of approximately 1 µm composed of
primary particles of a few tens of nanometers in diameter, determined that
the fractal dimension Df for alumina is 1.60 ± 0.04 (Karasev et
al., 2001, 2004), implying a sparsely packed fractal. For comparison, soot
aggregates typically have Df values of ∼ 2.0 (Kajino and
Kondo, 2011; Maricq and Nu, 2004), while a value of 3.0 is appropriate for
liquid particles which remain spherical upon coagulation. The density of
alumina particles is taken to be 3.8 g cm-3 and that of diamond to be
3.5 g cm-3. We assume the same fractal dimensions for diamond as for
alumina.
Annual average sedimentation velocity (km yr-1) versus
altitude for (a) uncoated alumina particles and pure sulfate particles and
(b) sulfate-coated aged alumina paticles with compact fractal structures
averaged over the region from 20∘ S to 20∘ N latitude.
Solid colored lines represent monomers, dashed lines depict fractals with N=4,
dash–dot lines depict fractals with N=32, and dotted lines depict fractals with N=256
(for R0=80 nm only). Fractal dimension Df=1.6 for uncoated
particles represented in panel (a), Df=2.8 for coated and compacted
particles shown in panel (b). The black lines represent the annual average
upwelling velocity of the model's advective transport averaged over the
region from 20∘ S to 20∘ N latitude for comparison.
Sedimentation velocity strongly influences stratospheric lifetimes. Figure 1a
shows annual average sedimentation velocities in the tropics as a
function of altitude for uncoated alumina particles for monomer radii from
80 to 320 nm. Sedimentation velocities are shown for individual monomers and
for fractals with N=4 and N=32, all with fractal dimension
Df=1.6. N=32 fractals are not shown for monomers larger than 160 nm
because significant numbers of such fractals do not form in our simulations,
however we do show N=256 fractals with 80 nm monomers. Alumina monomers
fall at a faster rate than sulfate particles of the same diameter, given
their greater density (3.8 g cm-3 for Al2O3, approximately
1.7 g cm-3 for stratospheric H2SO4–H2O particles),
and diamond particles (not shown) fall only slightly slower than alumina
particles of the same radius owing to 8 % smaller density. Fractal
particles fall faster than the monomers they are composed of in the
troposphere and lower stratosphere, but at the same rate in the middle and
upper stratosphere where the Knudsen number Kn > 1 and the
slip-flow correction have the opposite size dependence as the other terms.
Figure 1 also shows the model's average upward advective velocity in the
tropics as a function of altitude for comparison. Where sedimentation
velocity exceeds average upwelling velocity, we expect alumina lifetime and
vertical extent to be greatly impacted. This occurs only above 30 km for 80 nm monomers, but above 24 km for 160 nm monomers and 19 km for 240 nm
monomers. For 240 and 320 nm monomers injected into the tropics at 20–25 km altitude, only a fraction of the injected mass will be lofted to higher
altitudes and distributed to high latitudes by the Brewer–Dobson
circulation.
Mass mixing ratio of alumina in ppbm (panels a and b) and number
density of alumina particles in cm-3 (panels c and d) with
geoengineering injections of 1 Tg yr-1 of 80 nm monomers (panels a and
c) and 1 Tg yr-1 of 240 nm monomers (panels b and d) for annual average
conditions.
It is known that soot particles, which form fractals similar to alumina
particles, eventually assume a more compact structure in the atmosphere
after acquiring a liquid coating (Kajino and Kondo, 2011; Mikhailov et al.,
2006). Observations on the liquid uptake properties of alumina and their
potential shape compaction are not available. For simplicity, we assume that
the alumina particles are hydrophobic until they are coated with a
sulfate–water mixture by coagulation with existing sulfate particles, and
then they may take up additional H2SO4 and H2O by
condensation. The effects of this assumption are expected be small under
nonvolcanic conditions, as most (> 95 %) stratospheric sulfate
mass exists in condensed form. To test the potential effect of compaction of
liquid-coated solid alumina particles, we perform additional model
calculations, assuming that the wetted particles change their fractal
dimension Df from 1.6 to 2.8, and their surface area scaling exponent
Dh from 2.0 to 2.8, likely the maximum compaction that could be
achieved. While a time lag from initial wetting to shape compaction may be
appropriate, we assume instantaneous compaction on wetting for calculations
labeled “compact coated” as a way to bracket the effect. When the
compacted particles lose their H2SO4 by evaporation, they are
assumed to retain their compact shape. Sedimentation velocities for these
coated and compacted particles are shown in Fig. 1b. In this case, higher-order fractals fall at faster velocities than their respective monomers at
all altitudes, which will affect the residence time of alumina and its
calculated atmospheric burden.
Aerosol distribution and burden
We model geoengineering by injection of alumina particles for a number of
parametric model scenarios to evaluate the effect of (1) injected particles
size, (2) injection rate, and (3) the fractal geometry of sulfate-coated
alumina particles. For all scenarios, injection occurs in a broad band from
30∘ S to 30∘ N and from 20 to 25 km in altitude. This is
the same injection region used in Pierce et al. (2010) and was chosen to
maximize the global distribution and residence time of geoengineered
aerosols while minimizing localized injection overlaps. We assume that it is
feasible to emit alumina particle monomers with a uniform diameter, either
by a flame process at the injection nozzle or by releasing prefabricated
particles. Particles are released continuously at injection rates of 1, 2,
4, or 8 Tg per year, all as monomers of a single radius (80, 160, 240, or 320 nm), as detailed in Table 1. Stratospheric particle injections
are continuous in time and the simulations are continued for 10 years until
a steady atmospheric concentration is reached. Alumina particles that become
coated with sulfate are treated either as retaining their sparse structure
with fractal dimension Df of 1.6 or instantaneously becoming more
compact fractal particles with Df of 2.8. We use a 2-D model for
computation efficiency in this first evaluation of geoengineering by solid
particle injection, and thus we implicitly mix the injected material into
zonally uniform bands dictated by the model's spatial resolution of
9.5∘ latitude by 1.2 km altitude. The impact of this simplification,
along with the neglect of enhanced coagulation in injection plumes, will be
discussed in Sect. 4.
We first examine the calculated concentration and size distribution of
atmospheric alumina under a geoengineering scenario with an injection rate
of 1 Tg yr-1, assuming no particle compaction on coating with sulfate.
Figure 2, top panels, shows the mass mixing ratio of alumina (ppbm) with
injections of 80 nm monomers and 240 nm monomers. Significant alumina
concentration exist up to 40 km altitude when 80 nm particles are injected,
but only below 30 km for the injection of 240 nm particles due to the difference
in sedimentation speeds. The peak mass mixing ratio of alumina injected with 80 nm
monomers is 40 % larger than that injected with 240 nm monomers.
The lower panels of Fig. 2 show the concentration of particles (cm-3)
for the same cases. Particle concentrations of up to 25 cm-3 are found
for 1 Tg yr-1 injection of 80 nm monomers but remain less than 3 cm-3 for the injection of 240 nm monomers. The particle concentration drops
away from the injection region as the monomers coagulate into fractals and
have time to settle downward. The low number densities with R0=240 nm
result in minimal coagulation between alumina particles.
Distribution of integrated stratospheric alumina mass into
monomers and fractals for geoengineering injection of 1 Tg yr-1 of
alumina as 80 nm monomers at (a) the equator and (b), globally integrated,
and for injection of 1 Tg yr-1 of alumina as (c) 160 nm and (d) 240 nm
monomers, globally integrated. Red bar length represents the mass fraction in
dry alumina and blue bar length the mass fraction in coated alumina. Annual
average conditions are represented.
Calculated global annual average stratospheric mass fractions of
alumina as a function of the number of monomers contained in a fractal
particle for (a) monomer injections of 80 nm radius, (b) monomer injections
of 160 nm, and (c) monomer injections of 240 nm radius, with emission rates
ranging from 1 to 8 Tg yr-1.
The distribution of stratospheric alumina mass into monomers and fractals is
shown in Fig. 3 at the equator with 80 nm monomers injected (panel a) and
for the global average injected with 80, 160, and 240 nm monomers (panels
b–d), all with 1 Tg yr-1 of emissions. With the injection of 80 nm
monomers, 27 % of the mass remains in monomers at the equator, with no
more than 13 % of the mass in any size bin with two or more monomers in the
fractal. Some fractal particles comprised of 1024 monomers exist. At higher
latitudes, the monomer fraction drops and the proportion in higher-order
fractals increases, as seen in the global average (panel b). The fraction of coated
monomers, shown as the blue portion of each bar, increases with
distance from the tropical injection region. Coated fractions also increase
with increasing numbers of monomers per fractal particle. This reflects both
the longer residence time of the larger particles and their large
cross section, which enhances coagulation with sulfate particles. Virtually
all of the alumina mass is coated for fractals with more than 128 monomers
per particle. Alumina in the troposphere is almost all coated with sulfate
due to the large sulfate concentrations there, though alumina concentrations
are small. With the injection of 160 nm alumina monomers, 71 % of the global
mass remains in monomers, and fractals composed of only 2–16 monomers are
found in significant concentrations. Results for diamond closely resemble
those for alumina injected with 160 nm monomers. With the injection of 240 nm
alumina monomers, 94 % of the mass remains in monomers, and with 320 nm
monomers injected, 98 % remains in monomers. Larger fractions of the alumina mass
are coated in these latter cases.
The mass fraction in monomers versus higher-order fractals varies with
injection rate. Figure 4 shows mass fraction vs the number of monomers
per particle for injection of 80 nm monomers at rates varying from 1 to 8 Tg yr-1. The 1 Tg yr-1 cases (green lines) match
the global mass fractions shown in Fig. 3. As the injection rate
increases, the mass fraction of monomers decreases while the peak
distribution shifts to larger fractals. At injection rates of 2, 4, and 8 Tg yr-1, the size distribution peaks at 32, 64, and then 128 monomers per
particle, and fractals composed of 2000 monomers are found. Figure 4b
shows a similar figure with injection of alumina as 160 nm radius monomers.
Because these particles contain 8 times the mass of the 80 nm monomers,
particle concentrations are considerably smaller and coagulation is less
effective. Fractals containing more than 128 monomers do not occur in
significant concentrations, even with 8 Tg yr-1 of emission. For
injection of 240 nm monomers (Fig. 4c), 70 % of the particles remain as
monomers even with 8 Tg yr-1 of emission, and fractals exceeding 16
monomers exist at only insignificant concentrations. For the injection of 320 nm
monomers (not shown), significant concentrations are found only for monomers
and fractals composed of two and four monomers even with 8 Tg yr-1 of
emission.
Annual average stratospheric burden of (a) alumina and (b)
condensed sulfate versus injection rate for various sizes of injected
alumina monomers. For comparison, we plot sulfate burden in Tg-S as a
function of the rate of injection of SO2 and H2SO4 (Pierce et
al., 2010) in Tg-S yr-1 along with alumina burden in (a). Panel (b)
shows the fate of natural sulfate as a function of alumina injection rate,
where the total sulfate burden is plotted on the left-hand axis (thick lines
with circles) and the fraction of that burden that is on the alumina
particles is shown on the right-hand axis (thin lines). The dashed lines
represent simulations in which the coated alumina particles are assumed to
become more compact in shape.
Figure 5a shows the stratospheric alumina burden as a function of
injection rate for four different radii of injected monomers. Alumina burden
is seen to be approximately linear with injection rate. This is in contrast
to a more strongly decreasing rate of change with increasing injection rate
seen for geoengineering by injection of SO2 or H2SO4, also
shown in Fig. 5a. In the case of sulfur injection, particles that grow to
larger spherical sizes have shorter atmospheric residence times. For alumina
particles with sparse fractal structure (Df=1.6), the fractal
particles do not increase their sedimentation velocities in the middle and
upper stratosphere as they grow by coagulation, resulting in residence times
remaining almost constant over the alumina size distribution. The cases that
produce the fewest fractals (R0=240 and 320 nm) have the most linear
response. The calculated atmospheric burden for diamond (not shown) is
almost identical to that for alumina of the same size injected monomer. Also
shown in Fig. 5 as dashed lines are simulations with coated alumina
particles assumed to adopt a more compact fractal shape (Df=2.8). For
these scenarios, total stratospheric burden is reduced due to the faster
sedimentation of the coated fractal particles, while the mass fraction in
monomers is increased due to fewer high-order fractals to scavenge the
monomers. Only the 80 and 160 nm cases show significant differences under
the assumption that coated particles become more compact.
The stratospheric burden of sulfate is shown in Fig. 5b under various
geoengineering scenarios with alumina injection. Thick lines (left-hand axis
labels) represent the total stratospheric burden of condensed sulfate as a
function of geoengineering injection rate of alumina while thin lines (right-hand axis labels) represent the fraction of stratospheric liquid sulfate on
the surface of alumina particles. With injection of 80 nm alumina monomers,
total stratospheric sulfate increases above background for injections less
than 1.5 Tg yr-1, but then decreases with higher injection rates. Up to
86 % of the total stratospheric sulfate is found on alumina particles in
these cases, a result of the large alumina surface area available and high
coagulation rates with large fractals. Alumina injection cases with larger
monomer diameters lead to decreases in the total stratospheric burden of
liquid sulfate because of the faster sedimentation of the larger alumina
particles along with their sulfate coatings. The maximum decrease in total
stratospheric sulfate is about 30 %. The fraction of total stratospheric
sulfate found on alumina particles is as much as 82 % with 160 nm
monomers, 61 % with 240 nm monomers, and 32 % with 320 nm monomers. The
calculated thickness of the sulfate coating on alumina particles in the
stratosphere varies from 5 to 15 nm with 80 nm monomers and from 10 to 40 nm
with 240 nm monomers with 1 Tg yr-1 of injection. However, as the
geoengineering injection rate increases, the sulfate layer on alumina
particles becomes thinner since the stratospheric sulfate burden will then
be distributed over a larger alumina surface area.
Radiative forcing assessment
In this work, we confine our assessment of radiative forcing (RF) to reflected
solar radiation, acknowledging that absorption of thermal infrared radiation
generates a longwave radiative forcing as well. For some materials, this
longwave forcing can be significant, reaching approximately 20 % of the
shortwave radiative forcing in the case of sulfate. Compared to the
shortwave forcing, however, the longwave forcing is a much more sensitive
function of profiles of atmospheric temperature, humidity, ozone, and
well-mixed greenhouse gases. Furthermore, the instantaneous longwave forcing
adjusts in response to changes in the temperature profile caused by
radiative heating rate perturbations due to the aerosol particles. We
therefore restrict our analysis to shortwave radiative forcing to narrow the
scope of radiative transfer calculations and to reduce the number of
radiative forcing values presented.
Comparison of radiative scattering properties of alumina and
diamond monomers and sulfate aerosol particles as functions of particle
radius. Panel (a) shows the upscatter efficiency which is the upscatter
cross section divided by the geometric cross section (a dimensionless
ratio). Panel (b) shows the upscatter cross section divided by the particle
volume (units of µm-1), and panel (c) shows the ratio of
downscatter cross section to upscatter cross section integrated over the
solar band.
Alumina particles are known to be more efficient scatterers than sulfate
particles, and thus are expected to be more efficient per unit mass for
geoengineering applications. Figure 6 compares the Mie scattering properties
in the solar band of alumina and diamond monomers and sulfate particles as a
function of particle radius. We calculated the solid particle monodisperse
single scatter albedo values from Mie theory (Bohren and Huffman, 2008) using
tabulated complex refractive index data for diamond (Edwards and Philipp,
1985) and alumina (Thomas and Tropf, 1997). The upscatter and downscatter
cross sections are calculated from Wiscombe and Grams (1976), utilizing the
scattering-phase function from Mie theory and the same complex refractive
index data. Figure 6a shows the ratio of upscatter cross section to
geometric cross section for the three particle types. The sulfate profile is
fairly flat, with a cross section of about 0.3 for particles greater than
0.5 µm, whereas the alumina profile shows a 30 % drop from its peak
of 0.6 between 0.2 and 0.6 µm to 0.4 at 2 µm. The diamond
profile shows a peak of 0.9 between 0.15 and 0.5 µm, dropping to about
0.55 at radii greater than 1.2 µm. Figure 6b shows strong peaks in
upscatter per unit volume for alumina and diamond monomers as a function of
radius. In contrast, sulfate particles exhibit a much flatter function of
upscatter per unit volume as a function of radius. Alumina monomers scatter
most efficiently per unit particle volume at about 200–250 nm. At this
radius, they have 3 times the upscatter per unit volume as sulfate
particles. Upscatter per unit mass however, due to the difference in density
of alumina relative to sulfate, shows less contrast. For diamond monomers,
the upscatter per unit volume peaks at around 150 nm radius, with over twice
the peak upscatter of alumina monomers. Figure 6c shows the ratio of
downscatter cross section to upscatter cross section for alumina, diamond,
and sulfate as a function of radius. Alumina monomers have about half the
downscatter per unit of upscatter as sulfate particles, while diamond
monomers have half the downscatter of alumina. Thus in geoengineering
applications, alumina and diamond would scatter radiation back to space and
produce substantially smaller increases in diffuse radiation at the surface
than sulfate particles producing the same change in RF would.
Shortwave globally averaged clear-sky radiative forcing per
teragram burden (W m-2 Tg-1) of alumina or diamond particles as a
function of the number of monomer cores per fractal particle (panel a).
Calculated globally averaged shortwave radiative forcing as a function of
injection rate for geoengineering scenarios (panel b) for annual average
cloud-free conditions. The dashed lines represent simulations in which the
coated alumina particles are assumed to become more compact in shape.
We use a scattering code which integrates the Mie scattering function over
shortwave spectral bands and scattering angles as a function of particle
size (monomers and fractals) using an efficient impulse-function method.
Multiple scattering is ignored as solid particle optical depths are small.
For purposes of radiative forcing, we assume that solid particles with thin
sulfate coatings behave the same as bare particles. We follow Rannou et al. (1999) for scattering by fractals, and follow the approximation in Charlson
et al. (1991) by scaling our calculated RF values by (1-α)2,
where α represents surface albedo, here taken to be 0.2. Figure 7a
shows the shortwave globally averaged clear-sky radiative forcing functions,
in W m-2 per Tg of aerosol burden, obtained by our scattering code as a
function of monomer radius and fractal size (number of cores per particle).
Scattering by 80 nm alumina monomers is much less efficient (factor of 4)
than scattering by 160 nm alumina monomers. There is little difference in
scattering between 240 and 320 nm alumina monomers, both with about
50 % greater RF per teragram burden than 160 nm monomers. Fractals
scatter much less efficiently than monomers. A fractal aggregate of two
cores scatters only 50 % as much radiation per unit mass as a
corresponding monomer, and higher-order fractals scatter even less
efficiently. An aggregate of 16 alumina monomers has negligible scattering
per unit mass. The functions with fractal dimension of both Df=1.6
(solid lines) and Df=2.8 (dashed lines, labeled “compact coated”)
are shown for alumina, however, this produces only a minor difference in
radiative forcing per unit mass. The radiative forcing function for diamond
with 160 nm monomers (the radius of peak backscatter efficiency) shows
significantly greater forcing than alumina, 2.7 times greater than 160 nm
alumina monomers and 1.8 times greater than 240 nm alumina monomers.
We obtain averages of solid aerosol mass in each bin size (monomers and
fractals) integrated vertically and averaged over latitude and season. The
integrated and averaged aerosol mass per bin is multiplied by the
spectrally integrated radiative forcing per teragram burden for each bin to
obtain the total radiative forcing for each geoengineering scenario. The
global annual average top-of-atmosphere shortwave radiative forcing due to
alumina and diamond is shown in Fig. 7b as a function of injection rate
for specified sizes of injected monomers under clear-sky conditions. As
stated at the beginning of this section, our analysis focuses on shortwave
radiative forcing, as it provides for a less ambiguous comparison, relative
to combined shortwave plus longwave forcing, of the efficacy of different
particles in offsetting surface warming. However, we note that the longwave
radiative forcing is about 10 % of the shortwave RF for alumina, though of
opposite sign, and is negligible for diamond.
Calculated annual average surface area density (µm2 cm-3)
of uncoated alumina particles due to geoengineering with 1 Tg yr-1 injection of (a) 80 nm alumina monomers and (b) 240 nm alumina
monomers.
For alumina, shortwave RF for cases with 80, 160, 240, and 320 nm injected
monomer size are shown in Fig. 7b as a function of injection rate. Cases
with 80 nm monomer injections have very low RF, due both to inefficient
scattering for monomers of that size, and the large proportion of fractals
to monomers. The RF for the 80 nm injection case increases very little with
increasing injection rate, as increasing injections produce fractals
composed of more than 64 monomers which produce almost no scattering per
unit mass. The case with injection of 320 nm alumina monomers produces less
RF than the case with the injection of 240 nm alumina monomers. Though monomers
of 320 nm produce slightly more RF per teragram than monomers of 240 nm,
the 320 nm injection cases yield a smaller burden due to their faster
sedimentation rates. The injection of 240 nm monomers is found to produce the
most radiative forcing per teragram of alumina injected annually,
consistent with the peak of the upscatter per unit volume curve shown in
Fig. 6b. We calculate radiative forcing for diamond injections of 160 nm
monomers only, also shown in Fig. 7b. Atmospheric burden of diamond is
very similar to that for alumina of the same radius, but RF is much larger
owing to more efficient scattering. Diamond injection at a rate
of 4 Tg yr-1 results in -1.8 W m-2 of shortwave forcing, while the same
alumina injection results in only -1.2 W m-2 of shortwave forcing. The
increase in downward diffusive flux is also calculated by our radiative
forcing code and is shown in Table 2 for selected cases which each produce
-2 W m-2 of shortwave radiative forcing. For equivalent radii and
injection rate, diamond produces up to twice the diffuse downward radiation
as alumina, however, per unit change in top-of-atmosphere shortwave
radiative forcing, diamond produces less diffuse downward radiation.
Comparison of alumina, diamond, and sulfate solar geoengineering,
based on a top-of-atmosphere shortwave radiative forcing of -2 W m-2
for each case.
Metric
Alumina 240 nm
Diamond 160 nm
Sulfate as H2SO4
Sulfate as SO2
Comments
Shortwave radiative forcing per unit injected mass flux (W m-2 (Tg yr-1)-1)
-0.26
-0.42
-0.25a
-0.20a
Other than diamond, the differences are minor.
Ozone impact (global average column change)
-5.6 %
-6.1 % to -7.1 %b
-13 %c
-11 %c
Alumina and diamond have less ozone depletion than sulfates, though there is considerable uncertainty.
Diffuse light increase (W m-2)
10.1
6.3
21
19
Alumina and diamond are both better (less diffuse light) than sulfates. Exact results would require a more sophisticated radiative transfer model.
Longwave and shortwave heating rate (K day-1) in tropical lower stratosphere
0.052–0.060d
0.007–0.010d
0.22
0.30
Alumina is probably better (less heating) than sulfates, but this estimate is subject to considerable uncertainty. Diamond is much better.
a Sulfate emission fluxes based on mass of
H2SO4 or SO2 injected annually. Sulfate fluxes needed to
achieve a given RF would increase by approximately 20 % if the longwave RF
component were included, decreasing the RF efficiencies shown here.
b The results for diamond are a range based on two cases,
with and without Reaction (R1) occurring on bare diamond surfaces.
c Note that the overall ozone loss from H2SO4
and SO2 injection is higher than reported in most previous studies
because we consider short-lived bromine species
d The range for alumina and diamond is based on average particle number
densities of monomers and of total particles.
Our method produces only a globally averaged value of shortwave radiative
forcing by solid particles. Our results are not meant to be of high
accuracy, as they do not account for clouds or molecular scattering and are
limited by the index of refraction data, uncertainties in fractal
scattering, and our averaging method. Nevertheless, it is useful to obtain
well-founded estimates of radiative forcing for comparison with sulfate
geoengineering, and relative efficiencies among solid particle scenarios as
a function of injected monomer diameter. The RF plot in Fig. 7b shows
clear-sky shortwave radiative forcing from two sulfur geoengineering
scenarios as well. The scenario results were calculated with the AER 2-D
model, as applied in Pierce et al. (2010) but using the radiative scattering
code applied to alumina and diamond. Note that we plot them here relative to
the total SO2 or H2SO4 injection mass per year, not the
sulfur mass injected per year. The most efficient alumina geoengineering
scenario, with 240 nm monomers injected, has roughly the same RF efficiency
per teragram of injection as geoengineering by the injection of
H2SO4. However, if a geoengineering methodology were to transport
only sulfur to the stratosphere and create H2SO4 in situ, then
sulfur geoengineering would be more efficient than alumina per teragram per
year transported.
Aerosol heating of the tropical lower stratosphere is another potential risk
of geoengineering. Heckendorn et al. (2009) investigated this effect and the
resulting increase in stratospheric water vapor, primarily caused by
longwave heating, for sulfate aerosol. To estimate lower stratospheric
heating by solid particles, we use the Rapid Radiative Transfer Model (RRTM)
developed by Atmospheric and Environmental Research (Mlawer et al., 1997;
Clough et al., 2005) to calculate radiative heating rates for mean cloud-free
tropical atmospheric profiles with and without a uniform aerosol density of
1 cm-3 between 18 and 23 km. The combined longwave and shortwave
heating rates shown in Table 2 for alumina, diamond, and sulfate are
generated by scaling the RRTM results for number densities of 1 cm-3 to
the average number density in the 18–23 km region between 30∘ S
and 30∘ N for scenarios predicted to produce -2 W m-2 of
shortwave radiative forcing. For alumina and diamond, the RRTM calculation
uses only the monomer size of 240 or 160 nm, respectively, ignoring
fractal particles and treating coated monomers the same as uncoated
monomers. The range provided for heating by alumina and diamond in Table 2
uses monomer number densities for the low estimate and total particle number
densities for the high estimate as multipliers for the heating rate
determined from RRTM with average number density of 1 cm-3. For sulfate
particles, we employ a size distribution due to the sensitivity of heating
rates to particle diameter and the range of diameters generated in
geoengineering scenarios. We find that the lower stratospheric heating rate
from alumina is approximately 4–5 times less than the heating rate from
sulfate, comparing scenarios which each generate -2 W m-2 of shortwave
RF. Shortwave heating from alumina is about 15 % of the total heating by
gases and aerosols, and from sulfate about 20 %. The total heating rate
from diamond is almost entirely due to shortwave effects, but is still much
less than that for alumina with the same top-of-atmosphere shortwave
radiative forcing.
Ozone impacts
Heterogeneous reactions on stratospheric particles play an important role in
ozone chemistry by converting inactive forms of chlorine and bromine to
forms that contribute directly to catalytic destruction of ozone. In
addition, the heterogeneous conversion of N2O5 to HNO3
reduces NOx concentrations. This increases ozone concentrations in the
middle stratosphere where NOx reactions dominate the ozone loss cycles,
but it decreases ozone concentrations in the lower stratosphere where
HOx, ClOx, and BrOx loss cycles dominate. Transient increases
in sulfate aerosols following volcanic eruptions have caused temporary
depletions in ozone (Solomon, 1999). Geoengineering by stratospheric aerosol
injection would be expected to lead to analogous ozone depletion, depending
on the heterogeneous reactions that occur on the particle surfaces and their
rates.
Ozone loss due to geoengineering injections of sulfate precursors has been
explored by several authors (Heckendorn et al., 2009; Tilmes et al., 2008,
2009, 2012; Pitari et al., 2014). Here we provide a preliminary assessment
of ozone loss from geoengineering injection of alumina and diamond solid
particles. To enable a relative comparison of the ozone impact of sulfate
geoengineering, we use the same model to compute changes in ozone abundance
arising from injections of both solid particles and of sulfate aerosols. We
use the AER 2-D chemistry–transport–aerosol model which includes full ozone
chemistry, with 50 transported species, an additional 51 radical species,
286 two- and three-body chemical reactions, 89 photolysis reactions, and 16
rainout/washout removal processes coupled to our aerosol model (Weisenstein
et al., 1998, 2004; Rinsland et al., 2003). Reaction rates are from the
Jet Propulsion Laboratory (JPL) compendium (Sander et al., 2011). The model parameterizes polar
stratospheric clouds (PSCs) using thermodynamic equilibrium, employing the
formulas of Hanson and Mauersberger (1988) and Marti and Mauersberger (1993)
for equilibrium vapor pressures over solid HNO3 and ice, respectively,
assuming no supersaturation and prescribing the particle radii. A comparison
with observed ozone trends between 1979 and 2000 is presented in Anderson et
al. (2006) for the AER model and several other models. Our simulations of
ozone change due to SO2 injections are similar to those of Heckendorn
et al. (2009) if we compare equivalent scenarios, but larger than those of
Tilmes et al. (2012). This model does not include radiative or dynamical
feedbacks; temperature and circulation are fixed with a climatology averaged
over the years 1978 through 2004. Thus our evaluation of ozone changes due
to geoengineering by the injection of solid particles includes only chemical
perturbations due to heterogeneous reactions on particle surfaces and not
due to changes in temperature or dynamics induced by the geoengineering.
The amount of ozone loss induced by stratospheric aerosols is strongly
dependent on the concentrations of halogen species, primarily Cl and Br.
Future concentrations of halogens are expected to decline as a result of
emissions controls, so the impact of stratospheric aerosols on ozone
will – all else being equal – decline over time. To err on the side of
caution by overstating the ozone impacts, we use present-day trace gas
concentration throughout this study with 3.4 ppbv of total chlorine and 23 pptv
of total bromine, including 6 pptv of inorganic bromine derived from
the very short-lived (VSL) organic compounds CH2Br2 and
CHBr3. Tilmes et al. (2012) showed that inclusion of VSL bromine
increases ozone depletion in geoengineering scenarios. A more detailed
evaluation of ozone impacts of solid particle geoengineering will await
further studies with coupled aerosol–chemistry–climate models.
Aerosol surface area density (SAD in units of µm2 cm-3)
contributes to determining the rates of heterogeneous chemical reactions
that occur on particle surfaces. Heterogeneous reactions may occur on bare
alumina surfaces in the stratosphere, as well as on sulfate surfaces. The
reaction ClONO2+HCl → Cl2+HNO3 has been measured on
alumina surfaces (Molina et al., 1997; Sander et al., 2011) and would be
expected to cause ozone depletion (Danilin et al., 2001; Jackman et al.,
1998), though uncertainties in this reaction and the surface properties of
alumina aerosol remain unexplored. Figure 8 shows bare alumina surface area
density for the cases with 1 Tg yr-1 injection of 80 nm monomers (left
panel) and 240 nm monomers (right panel). Alumina SAD is largest in the
tropics where particles are injected, and is lower at higher latitudes where
a larger fraction of the surfaces are coated with sulfate. Alumina SAD
extends to higher altitudes, up to 40 km and above, with injection of 80 nm
monomers, whereas the 240 nm monomers and their fractal derivatives sediment
fast enough to preclude significant SAD above 30 km. Note that sulfate
aerosols generally evaporate above about 35 km altitude, and thus
geoengineering with solid particles may introduce significant surface area
density in regions that currently are not greatly impacted by heterogeneous
chemistry.
Calculated annual average sulfate surface area density (µm2 cm-3) of (a) sulfate particles without geoengineering, and
surface area density increase (µm2 cm-3) with geoengineering
injections of (b) 1 Tg yr-1 of 80 nm alumina monomers and (c) 1 Tg yr-1 of 240 nm alumina monomers. Panel (d) shows sulfate aerosol
surface area density increase (µm2 cm-3) with 1 Tg yr-1
of SO2 injection.
Figure 9 shows sulfate SAD from the calculated background atmosphere without
geoengineering (panel a) and the increase in sulfate SAD in an atmosphere
with 1 Tg yr-1 of geoengineering injection of 80 nm alumina monomers
(panel b) or 240 nm alumina monomers (panel c). While the addition of
alumina particles has produced only a small change in the total
stratospheric condensed sulfate (see Fig. 5b), it has produced significant
increases in sulfate surface area density. This is a result of sulfate being
distributed in thin layers on the surfaces of alumina particles. With
injection of 80 nm monomers, the sulfate SAD has increased by factors of 2–4
in the lower stratosphere, with maximum SAD at high latitudes where
significant concentration of complex alumina fractals exist to scavenge the
smaller sulfate particles. With injection of 240 nm monomers, the maximum
sulfate SAD occurs in the tropics as the faster sedimentation of alumina in
this case results in a smaller concentration of mostly monomers at high
latitudes. Figure 9 (panel d) shows the increase in sulfate SAD for a
geoengineering scenario with 1 Tg yr-1 of SO2 injection as calculated by the AER 2-D model. The SAD
increase is similar in magnitude to the case with injection of 80 nm alumina
monomers, but has a distribution similar to the 240 nm alumina injection
case. A similar injection of sulfur as H2SO4, as in Pierce et al. (2010),
produces more than double this SAD increase. For reactions whose
rate is dominated by liquid sulfate surface area density, we would expect
similar chemical ozone loss from similar changes in sulfate SAD whether due
to geoengineering by SO2, H2SO4, or alumina injection.
Global annual average stratospheric surface area density between
15 and 25 km altitude for (a) uncoated alumina, and (b) total sulfate. The
dashed lines represent simulations in which the coated alumina particles are
assumed to become more compact in shape.
The SAD generated by alumina geoengineering is reduced when the monomer size
of the injected particles increases. Optimizing the injected monomer size
would be an important strategy to minimize stratospheric ozone depletion.
Figure 10 illustrates this, showing annual averaged SAD between 15 and 25 km
for bare alumina (panel a) and total sulfate (pure sulfate plus
sulfate-coated alumina, panel b) as a function of injection rate with
injections of 80, 160, 240, and 320 nm monomers. The SAD for bare alumina
drops by factors of 1.8 to 3.1, depending on injection rate, when the
monomer size is increased from 80 nm to 160 nm. The alumina SAD is roughly
linear with injection rate, since the alumina surface area density does not
decrease as particles coagulate when Dh=2.0. The total sulfate SAD
(Fig. 10b) is even more dependent on monomer diameter than the uncoated
alumina SAD is. Even though the burden of stratospheric sulfate on alumina
varies slowly with injection rate, the sulfate SAD varies more rapidly with
injection rate as the sulfate becomes spread more thinly over a greater
numbers of alumina particles. The dashed lines in Fig. 10 represent cases
where the coated particles take on a more compact fractal shape, and thus
sediment faster, greatly decreasing sulfate SAD for the 80 and 160 nm
injection cases. Our diamond simulation is similar to the alumina simulation
with injection of 160 nm monomers.
Our model evaluation of ozone impacts from alumina geoengineering considers
the following reaction on bare alumina surfaces:
ClONO2+HCl→HNO3+Cl2.
This reaction, with reaction probability γ of 0.02, has been studied
in relation to ozone depletion resulting from space shuttle launches
(Danilin et al., 2001; Jackman et al., 1998). We assume that this reaction
occurs catalytically with no surface poisoning. Other potential reactions on
alumina surfaces have been investigated in the laboratory (see Sander et
al., 2011), and further investigation is needed to determine how additional
heterogeneous and photocatalytic reactions could modify stratospheric
chemistry or change the surface properties of alumina in the stratosphere.
Measurements of potential heterogeneous reactions on diamond surfaces are
not available. Thus we perform diamond injection calculations assuming Reaction (R1)
on diamond at the same rate as for alumina, and assuming no reactions on
bare diamond surfaces.
We also consider heterogeneous reactions on the sulfate-coated surfaces of
solid particles. These reactions include
N2O5+H2O→2HNO3ClONO2+HCl→HNO3+Cl2ClONO2+H2O→HNO3+HOClHOCl+HCl→H2O+Cl2BrONO2+H2O→HNO3+HOBrBrONO2+HCl→HNO3+BrClHOBr+HCl→H2O+BrClHOBr+HBr→H2O+Br2.
Due to the solubility of HCl, ClONO2, HOCl, and HOBr in sulfuric acid
solutions, Reactions (R3), (R4), (R5), and (R8) can be considered bulk
processes or hybrid bulk-surface processes governed by a reaction-diffusion
process. For liquid spherical particles we use standard methods to
calculating the reaction probability as a function of radius (Shi et al.,
2001). For reactions on coated solid particles, we use the same functions,
substituting the thickness of the sulfate layer in place of the radius of a
spherical particle.
Ozone changes due to the injection of alumina aerosol. Column ozone
changes (%) are shown as a function of latitude and month (left panels)
and annual average local ozone changes (%) as a function of latitude and
altitude (right panels). Results are shown for an injection rate of 1 Tg yr-1 of 80 nm (top panels) and 240 nm (bottom panels) alumina monomers.
Note ozone increases in the upper stratosphere where the NOx cycle
dominates, and decreases in the lower stratosphere where the ClOx and
BrOx cycles dominate.
Calculated changes in ozone due to heterogeneous reactions on alumina
surfaces (bare alumina and sulfate-coated alumina) are shown in Fig. 11 for
cases with injection of 80 and 240 nm monomers at an injection rate of 1 Tg yr-1. Column ozone depletion ranges from 2 % in the tropics to
6–10 % at mid-latitudes and up to 14 % at the poles in springtime with
the injection of 80 nm monomers. With the injection of 240 nm monomers, ozone
depletion is much smaller, ranging from 0.3 to 2.5 %. The annual
average ozone change as a function of latitude and altitude (Fig. 11, right
hand panels) shows features linked to local balances in ozone's formation
rate, chemical destruction rate, and local transport rates. In the tropics,
ozone concentrations are determined by the chemical production via UV
radiation that is balanced by transport out of the tropics to higher
latitudes. Thus ozone changes due to increased loss mechanisms are minimal
in the tropics in the stratosphere, though increased penetration of UV to
lower altitudes in the tropics can produce ozone increases. In the middle
stratosphere at 25–35 km altitude, the NOx cycle dominates ozone loss.
Increases in aerosol surface area density in this region reduce NO and
NO2 while increasing HNO3 via the N2O5+H2O
reaction. Thus the NOx loss cycle is diminished and ozone increases.
The sedimentation rate of alumina particles is significant, as the scenario
with the injection of 80 nm monomers yields significant increases in aerosol
surface area density and ozone changes above 25 km, whereas the scenario
with 240 nm monomers injected does not. In the lower stratosphere at mid-latitudes and
high latitudes, the heterogeneous reactions on particle surfaces increase
the ratio of chlorine and bromine in their radical forms that destroy ozone
(Cl, ClO, Br, and BrO). In addition, the N2O5+H2O reaction
leads to more HNO3 and less ClONO2 and BrONO2, thus
indirectly increasing halogen radicals as well. Local ozone depletions in
the lower stratosphere are as large as 24 % with 80 nm monomer injections
and 5 % with 240 nm monomer injections, on an annual average basis.
Figure 12a shows annual average changes in ozone column as a function of
latitude with 1 Tg yr-1 of geoengineering injections. Results with the
injection of 80, 160, and 240 nm alumina monomers are shown, along
with the injection of 160 nm diamond monomers. We do not calculate ozone changes
due to the injection of 320 nm alumina monomers because these scenarios produce
less radiative forcing than the injection of 240 nm monomers for similar
injection rates. Ozone changes, similar to SAD increases, are found to be
very sensitive to injected monomer size. However, assuming that coated
alumina particles assume a more compact shape (shown by dashed lines in the
figure) significantly reduces calculated ozone depletion for the
R0=80 nm case, and modestly reduces ozone depletion for the
R0=160 nm case. Also shown in Fig. 12a are changes in ozone column
due to the injection of 1 Tg yr-1 of SO2 and H2SO4, which
are roughly similar to those calculated with 1 Tg yr-1 of 80 nm alumina
monomers.
Annual average column ozone change in percent as a function of
latitude for (a) cases with 1 Tg yr-1 injections of alumina monomers of
80 nm, 160 nm, and 240 nm, and diamond monomers of 160 nm and SO2 and
H2SO4, (b) cases with injection of 240 nm alumina monomers at
rates of 1, 2, 4, and 8 Tg yr-1, and (c) cases with injection of 160 nm
diamond monomers at rates of 1, 2, 4, and 8 Tg yr-1. Cases in which
coated particles are assumed to become more compact in shape are shown with
dashed lines in panels (a) and (b). For diamond, cases without Reaction (R1)
occurring on dry diamond particle surfaces are shown with dotted lines in
panel (c).
Figure 12b shows calculated ozone changes for injection rates of 1, 2, 4,
and 8 Tg yr-1 with the injection of 240 nm alumina monomers. Note than
ozone changes increase at a less than linear rate with increasing injection
rates, and that the effect of compaction of coated alumina particles becomes
more significant at higher injection rates due to the formation of higher-order
fractals. Figure 12c shows calculated ozone changes due to geoengineering
injection of diamond monomers of 160 nm radius. Solid lines are for results
including the Reaction (R1) on uncoated particles, and dotted lines omit
this reaction. Reaction (R1) has a greater effect in the tropics than at mid-latitudes due to higher concentrations of uncoated particles there. The
northern high latitudes show greater sensitivity to geoengineering
injections than the southern high latitudes at the higher emission levels,
likely due to the dominant role of PSCs over the Antarctic.
Global annual average column ozone change (in percent) (a) as a
function of injection rate and (b) as a function of associated shortwave radiative
forcing. Ozone change for diamond is shown with and without Reaction (R1) on
uncoated diamond particles. Calculations with SO2 and H2SO4
injections employ the same model to calculate radiative forcing and ozone
depletion as for alumina and diamond.
Global average column ozone changes are shown in Fig. 13a as functions of
injected monomer size and injection rate. Figure 13b shows changes in
global average ozone as a function of the associated shortwave radiative forcing for
each scenario. This makes it clear that geoengineering injection of 80 nm
alumina monomers is completely unworkable, producing excessive ozone
depletion (5 % with 1 Tg yr-1 injection and 14 % with 8 Tg yr-1 injection) and minimal radiative forcing. Geoengineering by
injection of 240 nm alumina monomers, however, could potentially be an
effective climate control strategy, similar to geoengineering by injection
of sulfur in its radiative forcing effectiveness but with less ozone
depletion potential. Note that radiative forcing and associated ozone
depletion with 16 Tg yr-1 injection of 240 nm alumina monomers is
included in Fig. 13b, yielding -3.6 W m-2 of RF with about 8 %
ozone depletion. Injection of 160 nm diamond monomers produces ozone loss
per teragram of injection similar to 160 nm alumina monomers, but with
radiative forcing per teragram of injection greater than for similar
injections of 240 nm alumina monomers. We show diamond results both
including and excluding Reaction (R1) on bare diamond surfaces. This
reaction makes about a 10–15 % difference in ozone depletion due to
diamond injection. Note that the SO2 results plotted in Fig. 13 show
more ozone depletion than in Heckendorn et al. (2009) because that study did
not include the short-lived bromine source gases and used a narrower
injection region. More studies will be needed to evaluate potential impacts
on stratospheric chemistry such as tropopause heating and changes in the
Brewer–Dobson circulation that are not evaluated here.
Discussion
We have developed a new aerosol model and used it to quantitatively explore
the interactions of solid particles with sulfate aerosol in the
stratosphere. This analysis allows a preliminary assessment of some of the
trade-offs that might arise in using solid aerosols such as alumina or
diamond rather than sulfates for solar geoengineering. We first discuss
salient limitations of our model before turning to analysis of trade-offs.
Limitations
Injection mechanism
We do not model the mechanism for injection and dispersion of aerosols. If
aerosols were injected from aircraft, there would be small-scale dynamical
effects in the injection nozzle and in the aircraft plume in which particle
concentrations would be much larger than found after dilution to the scale
of a model grid box, possibly leading to rapid coagulation. Effects during
particle generation or injection from a nozzle would occur on very short
scales of time and space and cannot be estimated here. We can, however,
estimate the impact of coagulation in an expanding plume using the method of
Pierce et al. (2010). We allow the plume cross section to dilute from 6 m2 to 17×106 m2 over a 48 h period, assuming that alumina
particles are released at a rate of 30 kg km-1 of flight path. We find
the fraction of alumina mass remaining as monomers after 48 h of plume
dilution to be 37, 86, 96, and 98 % for injected monomers of
80, 160, 240, and 320 nm, respectively. For monomer injections of 240 and
320 nm, only two-monomer fractals are created within 48 h. We conclude
that plume dynamics and processing are unlikely to have a substantial effect
on alumina geoengineering if injected monomer size is greater than 160 nm.
For 240 nm monomer, the most relevant case, our 2-D model calculation would
be expected to have 4 % less mass in monomers if plume dynamics were
considered.
Two-dimensional model
A second limitation is the use of a 2-D model. Since the geoengineering
scenarios discussed in this work deal with particle injection in the 20–25 km altitude region and spread between 30∘ S and 30∘ N,
assuming zonal symmetry, as a 2-D model implicitly does, does not detract
greatly from the validity of our results. In particular, if the method of
injecting alumina particles attempts to distribute them uniformly in space
and time and avoid overlapping emissions as much as possible, then a
zonally symmetric spread may be a fairly good approximation. However,
details of transport near and below the tropopause are not well-represented
in 2-D models. Thus a 3-D model would be needed to accurately represent this
region. And if a specific geoengineering injection methodology were to be
investigated, a 3-D model with fine resolution would be needed to examine
heterogeneities in the resulting aerosol distribution.
Geometry of aggregates, effects of size binning
The fractal geometry of aggregates likely depends on the formation
mechanism, and it is plausible that the actual fractal dimensions might
differ significantly from the Df value of 1.6 we use here for alumina
and diamond. While the fractal dimension of alumina has been measured for
monomer cores much smaller than considered here, that of diamond has not. It
is also plausible that variables kf and kh should have values
other than 1.0, at least for cases that calculate many high-order fractals.
The behavior of aggregates under stratospheric conditions has not been
studied extensively. The formulations we have adopted for coagulation,
condensation, and sedimentation are based on theoretical studies or on
tropospheric or liquid-medium experiments, and thus should be considered
uncertain. Our formulation also assumes that all injected monomers are of a
uniform radius. While it appears reasonable to assume that industrial
production of alumina or diamond nanoparticles could produce particles
within a narrow size range, our assumption is a simplification. Likewise,
our assumption of maximal compaction instantaneously on wetting is likely
not realistic but meant to show the greatest possible effect of potential
particle compaction on aging. Observational studies in the laboratory and in
the stratosphere would be needed to determine whether compaction of alumina
particles occurs and to what extent. However, compaction has a minor effect
on the radiative properties and ozone depletion potential of particles with
monomer sizes of ∼ 200 nm or greater.
Numerical errors result from the discrete aerosol size binning we employ.
The discretization leads to a broadening of the size distribution during the
coagulation process. Appendix A details the coagulation methodology, in
which coagulation of two solid particles often leads to a new particle with
size intermediate between two bins. In this case, particle mass is
apportioned between two bins, leading to mass transfer into a bin larger
than that of the combined new particle. This broadening of the distribution
will lead to somewhat excessive sedimentation, whose error depends on the
coarseness of the bin spacing. Coagulation between liquid and solid
particles does not produce numerical broadening of the size distribution as
the binning for mixed solid–liquid particles depends only on the size of the
solid particle.
Ozone chemistry
The surface chemistry of alumina and other solid particles potentially
useful for geoengineering has not been studied as extensively as that of
sulfate particles. We include only one reaction, ClONO2+HCl, on
alumina and diamond particles in this modeling study. Laboratory studies
have investigated some additional reactions on alumina surfaces, and there
may be others not yet explored. Reported reactions on Al2O3
surfaces include the uptake of NO2 and HNO3 and reactions of
several volatile organic compounds, including formaldehyde, methanol, and
acetic acid (Sander et al., 2011). In addition, photocatalysis reactions of
several species on Al2O3 surfaces have been reported (De Richter
and Caillol, 2011), and may depend on the exact composition or impurities of
the particle surface. Photocatalysis of chlorofluorocarbons (CFC) compounds has been considered as
a method to mitigate the atmospheric burden of greenhouse gases if augmented
by artificial UV radiation in the troposphere. However, if these reactions
were effective in the stratosphere, they would contribute to the formation
of free radical chlorine and bromine, possibly increasing ozone depletion,
while reducing the lifetime the CFCs. Studies of these and other reactions
under stratospheric photochemical conditions would need to be performed on
any solid particle under consideration for geoengineering application.
Missing feedbacks
The modeling we present utilizes temperature and transport fields
uncoupled from the model's chemistry and aerosols and is therefore missing a
number of feedback processes that may be important in the atmosphere and may
significantly change the radiative forcing or ozone depletion estimates
given here. These include changes in stratospheric temperature due to
aerosol heating, which would modify rates of reactions important to ozone
formation and loss. Aerosol heating and enhanced equator-pole temperature
gradients would also modify the strength of the Brewer–Dobson circulation
and the polar vortex, with impacts on aerosol concentration, PSC formation,
and ozone concentration. Increases in the temperature of the tropical
tropopause layer would increase the transport of water vapor across the
tropopause, increasing stratospheric H2O and OH concentrations, and
reducing ozone (Heckendorn et al., 2009). These additional ozone changes
would further modify stratospheric temperature and circulation. However,
Heckendorn et al. (2009) found that ozone loss due to heterogeneous
chemistry, without the dynamical effects of changes in temperature, water
vapor, and the Brewer–Dobson strength, accounted for 75 % of the ozone
change.
A more uncertain feedback process is the effect of enhanced aerosol
concentrations on upper tropospheric cloudiness and cloud radiative
properties (Kuebbeler et al., 2012; Cirisan et al., 2013). A general
circulation model with stratospheric chemistry and aerosol and cloud
microphysics would be needed to evaluate these feedback effects.
Principal findings
Use of alumina particles for SRM is potentially useful only if the size of
the injected monomers is larger than about 150 nm; the best results are only
seen if the monomer radius exceeds about 200 nm. The strong dependence on
monomer size can be understood if one assumes that the injection rate will
be adjusted so as to produce a given radiative forcing, for example -2 W m-2. For alumina, the peak mass-specific upscattering efficiency occurs
at a radius of ∼ 200 nm (see Fig. 6b). As the monomer size
gets smaller a higher monomer density and mass injection rate is required to
maintain the specified radiative forcing. The coagulation rate increases as
the square of monomer density, so the fraction of monomers in aggregates
increase rapidly with monomer density. Finally, the mass-specific radiative
forcing for aggregates decreases quickly with the number of monomers in an
aggregate (see Fig. 7a), so the injection rate must be increased further to
maintain a fixed radiative forcing. The net effect is that the radiative
efficacy, the global radiative forcing per unit mass injection rate,
declines very rapidly for particle radii below 150 nm. We find that alumina
monomers with radii of roughly 240 nm provide the most radiative forcing for
a given injection rate. For particle sizes beyond 240 nm, the scattering
efficiency remains roughly constant while the sedimentation rate increases,
contributing to a decrease in radiative forcing efficiency per unit
injection rate.
As a specific example, consider the injection of 240 nm alumina monomers at
a rate of 4 Tg yr-1 evenly distributed between 30∘ S to
30∘ N and from 20 to 25 km in altitude. This produces a stratospheric
burden of 4.6 Tg (see Fig. 5a) and global radiative forcing of -1.2 W m-2 (see Fig. 7b). Under these conditions, coagulation of alumina
particles is minimal: 81 % of the alumina is in monomers and only 4 % is
in aggregates of more than two monomers (see Fig. 4c). Particle densities
are a maximum in the lower tropical stratosphere with peak concentrations of
about 4 cm-3. The net effect of interaction with the background
stratospheric sulfate is that about 50 % of the stratospheric sulfate is
found as a coating (Fig. 5b, right axis) with a typical depth of order 10 nm
on the alumina particles. The total sulfate burden is reduced from 0.11 to
0.08 Tg (Fig. 5b, left axis) because the relatively fast fall speeds of the
alumina aerosol provide a sedimentation sink for sulfates, yet the sulfate
surface area density is increased by an average of 2 µm2 cm-3
in the lower stratosphere (Fig. 10b). The annual global average
ozone column is reduced by 3.7 % (Fig. 13a) with maximum ozone loss of 4
to 7 % over polar regions for this scenario and the given modeling
assumptions.
As with sulfate aerosols, ozone concentrations increase at altitudes around
30 km in the mid-stratosphere where the NOx cycle dominates but this is
more than compensated by the halogen-catalyzed ozone loss in the lower
stratosphere. And with the injection of 240 nm monomers, sedimentation is rapid
enough to preclude significant aerosol concentrations above 25–30 km. Most
of the ozone impact of alumina aerosols is found to be due the increase in
sulfate surface area and heterogeneous reactions on the liquid sulfuric
acid. This is because most of the alumina particles are coated with sulfate
at mid-latitudes and high latitudes where ozone loss reactions largely determine the
ozone concentration. If the rate of Reaction (R1) is set to zero in our simulations,
the column ozone depletion changes by less than 15 % in the extratropics,
but up to 35 % in the tropics with injection 4 Tg yr-1 of 240 nm
alumina monomers. Thus uncertainty in the rate of Reaction (R1) or the nature of the
uncoated alumina surface does not have a strong influence on our calculated
ozone impacts. If we assume that the alumina particle surfaces remain
uncoated and that Reaction (R1) occurs on all alumina particles, we find that the
ozone depletion is much less than that obtained when the surfaces do become
coated, implying that Reaction (R1) on alumina surfaces has less effect on ozone than
sulfate heterogeneous reactions on the same surface area do, mostly due to
the effectiveness of heterogeneous bromine reactions.
We can achieve a similar radiative forcing of -1.2 W m-2 with the injection
of 160 nm radius diamond monomers at 2 Tg yr-1. This injection rate
produces a stratospheric burden of 3.3 Tg of diamond. The corresponding
ozone depletion due to diamond injection ranges between 3.8 % globally, due
to increased sulfate surface area alone, and 4.3 % when we assume that Reaction (R1)
occurs on the bare surface of diamond particles with the same reaction rate
employed for alumina. However, levels of ozone depletion are highly
uncertain, as this reaction, and other potential heterogeneous reactions on
diamond surfaces, have not been measured.
Comparison with sulfate aerosols
Whatever method is used to create an artificial radiative forcing, solar
geoengineering is – at best – an imperfect method for reducing climate
impacts. Any technology for producing radiative forcing will have a set of
technology-specific impacts, such as ozone loss arising from the introduction of aerosol particles into
the stratosphere. However the radiative forcing is produced, the efficacy of SRM is
inherently limited by the fact that a change in solar radiative forcing
cannot perfectly compensate for the radiative forcing caused by increasing
greenhouse gases (Kravitz et al., 2014; Curry et al., 2014). A central
motivation for considering solid aerosols rather than sulfates is that they
might have less severe technology-specific risks. As discussed in the
introduction, the principle technology-specific risks or side effects of
sulfate aerosols are ozone loss, increased diffuse light, and stratospheric
heating.
Loss of stratospheric ozone and an increase in diffuse light have direct
impacts on ecosystems and human health. The consequences of stratospheric
heating are indirect and more speculative. Heating of the tropical tropoause
layer (TTL) might be expected to increase the amount of water vapor entering
the stratosphere. An increase in TTL temperature of 1 K increases the
concentration of water vapor entering the stratosphere by about 0.8 ppmv
(Kirk-Davidoff, 1999). Geoengineering with sulfate aerosols might heat the
TTL region by several degrees, increasing stratospheric water vapor
concentrations by more than 2 ppmv (Heckendorn et al., 2009). This would in
turn exacerbate ozone loss and create a positive radiative forcing that
would offset some of the reduction in forcing from SRM. While there is
uncertainty about the exact consequences of heating the lower stratosphere,
it is reasonably certain that all else being equal, a geoengineering method that
does not heat the low stratosphere is preferable to one that does.
We estimate stratospheric heating for alumina, diamond, and sulfate
geoengineering scenarios with the RRTM model, as described in Sect. 3.4.
Our results for alumina are broadly consistent with the results of Ferraro
et al. (2011) for titania. Note, however, that Ross and Sheaffer (2014)
conclude that the positive infrared radiative forcing from alumina can be
larger than the negative radiative forcing from solar scattering by the same
particles. We suspect that part of this discrepancy comes from the fact that
Ferraro et al. (2011) and this paper assume a narrow size distribution close
to the optimal for solar scattering, whereas Ross and Sheaffer (2014) use a
broad alumina size distribution. However, we have not resolved this
discrepancy, so our estimate of heating for alumina should be taken as
uncertain.
As shown in Table 2, our results suggest that alumina may have less severe
technology-specific risks than sulfates. While the injected mass necessary
to achieve a -2 W m-2 radiative forcing is roughly equivalent whether
employing alumina or sulfate aerosol, the ozone depletion is more severe
with sulfate geoengineering. In addition, the increase in diffuse solar
radiation would be half as much with alumina as with sulfate, and the
stratospheric heating is expected to be considerably less, smaller by a
factor of 4–5 in our estimation. Diamond appears to offer excellent
shortwave scattering with only a small increase in diffuse light. We
estimate ozone depletion due to diamond to be less than that due to sulfate,
but uncertainty is large. Lower stratospheric heating from diamond is quite
small.
We conclude that SRM by the injection of solid particles may have some
advantages relative to sulfates and merits further study to reduce the
sizable uncertainties that currently exist. It is important to note that the
injection of substances like alumina or diamond nanoparticles have much
greater “unknown unknowns” than sulfates, as they would be novel
substances in the stratosphere. Laboratory studies of reaction kinetics for
these particles under stratospheric conditions, as well as studies of their
microphysical and radiative properties, are required to reduce
uncertainties.