On the contribution of chemical oscillations to ozone depletion events in the polar spring
This paper presents a numerical study of the oscillations (or recurrences) of tropospheric ozone depletion events (ODEs) using the further-developed one-dimensional KInetic aNALysis of reaction mechanics with Transport (KINAL-T) chemistry transport model. Reactive bromine is the major contributor to the occurrence of ODEs. After the termination of an ODE, the reactive bromine in the air is deposited onto aerosols or on the snow surface, and the ozone may regenerate via NOx-catalyzed photochemistry or by turbulent transport from the free troposphere into the boundary layer. The replenished ozone then is available for the next cycle of autocatalytic bromine release (bromine explosion) leading to another ODE. The oscillation periods are found to be as short as 5 d for the purely chemically NOx-driven oscillation and 30 d for a diffusion-driven oscillation. An important requirement for oscillation of ODEs to occur is found to be a sufficiently strong inversion layer. In a parameter study, the dependence of the oscillation period on the nitrogen oxides' concentration, the inversion layer strength, the ambient temperature, the aerosol density, and the solar radiation is investigated. Parameters controlling the oscillation of ODEs are discussed.
Oscillating chemical systems have been a topic of scientific interest for well over a hundred years. One of the most simple systems, theoretical chemical oscillation was formulated by Lotka (1909) in analogy to the predator–prey equations. Briggs and Rauscher (1973) found “an oscillating iodine clock”, an oscillating reaction mechanism involving iodate, which could readily be reproduced in the laboratory.
Oscillations in tropospheric chemistry, involving the species NOx, HOx, CO, and O3 with oscillation periods of the order of several weeks to centuries were found by several researchers (e.g., White and Dietz, 1984; Poppe and Lustfeld, 1996; Hess and Madronich, 1997; Tinsley and Field, 2001). Kalachev and Field (2001) investigated a system involving the species CO, O3, NO, NO2, HO, and HO2 with a total of seven reactions and three emissions. They found an oscillation period of 1 month and managed to reduce the chemical system to four species. Moreover, low NOx, high HOx, high NOx, and low HOx regimes were identified.
Hess and Madronich (1997) investigated a similar but more complex chemical system which they were able to reduce to a two-variable system in which O3 and CO oscillate on timescales of years to centuries. Tinsley and Field (2001) developed a two-variable model with a similar mechanism and used it to investigate the excitability behavior of the phase space. It should be noted that these tropospheric chemical systems involve not only gas-phase chemistry but are driven externally by the emission and the deposition of various species.
Fox et al. (1982) describe stratospheric instabilities involving three steady-state solutions for the partitioning of chlorine. Their chemical, purely gas-phase mechanism consists of chlorine compounds as well as the NOy and HOx families. Two of the steady-state solutions were found to be stable, which releases the potential of the system to oscillate which, however, was not investigated.
An oscillating chemical system can only occur if the system comprises both nonlinearities and feedback cycles. The chemistry of ozone depletion events (ODEs) consists of nonlinearities and an auto-catalytic reaction cycle, suggesting the potential for an oscillating system.
Tang and McConnell (1996) studied the ozone depletion events using a box model where an oscillation of an ODE was found after about 5 d. Evans et al. (2003) found indications for chemical oscillations involving ODEs, where only photochemical recovery of O3 was considered, and an oscillation period of approximately 3 d was found. This oscillation timescale is among the fastest found in a model of tropospheric chemistry. The chemical reaction mechanism consists of both gas-phase and aerosol-phase reactions. In addition, the oscillations are driven externally by emissions and depositions. In the present work, an extensive investigation of the oscillation potential of ODEs is conducted, and simulations with conditions similar to those described by Evans et al. (2003) performed in order to evaluate the present simulations, which, however, are performed in a one-dimensional configuration considering a more advanced chemical reaction mechanism and a more sophisticated aerosol treatment. An overview of ODEs is given in the following paragraphs.
ODEs typically occur in the boundary layer in both the Arctic and Antarctic during spring and sometimes also in fall. During a full ODE, ozone concentrations drop below 1 nmol mol−1 and for partial ODEs to levels of less than 10 nmol mol−1 (e.g., Oltmans, 1981; Bottenheim et al., 1986; Hausmann and Platt, 1994; Frieß et al., 2004; Wagner et al., 2007; Halfacre et al., 2014). Barrie et al. (1988) were the first to find an anti-correlation of the ozone and bromine concentrations during an ODE. Hausmann and Platt (1994) then found experimental evidence for the chemical reaction mechanism that is most likely responsible for the destruction of the ozone by Br atoms, which was suggested by Barrie et al. (1988):
resulting in the following net reaction:
In this mechanism, the destruction rate of O3 is limited by the BrO self-reaction (R2) and thus a function of the square of the BrO concentration. The two different reaction paths in the self-reaction (R2) of BrO occur in a ratio of 78 : 22 at 258 K and 73 : 27 at 238 K, which are the two temperatures at which the present study is performed. The recycling of two Br atoms through reaction cycle (R1) through (R3) may occur 50–100 times before reacting to HBr via reactions of the type (R12); see below.
The primary source of the bromine in the polar boundary layer is still under discussion (e.g., Simpson et al., 2015). However, the snow-covered sea ice and the sea salt aerosols contain a significant amount of bromide (Br−). Bromide can be released from both solid and liquid phases via the heterogenous reaction cycle (Fan and Jacob, 1992; McConnell et al., 1992; Platt and Janssen, 1995):
resulting in the net reaction
Thus, in each cycle, the number of gas-phase bromine atoms can grow by a factor α≤2:
The bromine explosion requires acidity as can be seen from the net reaction (R9). In fact, both laboratory and field measurements found that lower pH values as well as a higher bromide-to-chloride ratio in the snow speed up the evolution of the Br2 formation, whereas a pH value larger than 6 hinders the occurrence of a bromine explosion (Huff and Abbatt, 2002; Adams et al., 2002; Abbatt et al., 2012; Wren et al., 2013; Pratt et al., 2013). In particular, Pratt et al. (2013) reported that in the presence of snow with pH values in the range of 4.6 to 6.3 and ratios between 1∕38 and 1∕148, a considerable amount of Br2 is produced, whereas for and , no BrO is obtained. In the presence of snow with pH = 5.3 and a ratio of 1∕468, Br2 is only produced if [O3] > 100 nmol mol−1. Wren et al. (2013) found that in the case of pre-freezing and pH >6.2, no Br2 was released.
Bromide can also be activated by the species BrONO2, involving NO2, via the reactions
In the snow, the produced nitrate is photolyzed to NOx (Honrath et al., 2000; Dubowski et al., 2001; Cotter et al., 2003; Chu and Anastasio, 2003), so that this process is catalyzed by NO2, and it is auto-catalytic with respect to Brx. A major source of polar NOx, i.e., NO and NO2, might be a snowpack as discussed, for instance, by Jones et al. (2000, 2001). The release mechanism of NOx probably is that the UV absorption spectrum of HNO3 on ice is somewhat shifted towards longer wavelengths so that ice-adsorbed HNO3 can photolyze considerably faster than gas-phase HNO3, and thereby, it is reconverted into NOx (Dubowski et al., 2001; Beine et al., 2003; Grannas et al., 2007).
Br atoms can also react with several organic species to form HBr and thus Br−, for instance, with aldehydes
effectively reducing α; cf. Eq. (1). During an ODE, once the ozone concentration has dropped to a sufficiently low level, α drops to values of less than unity, causing the bromine explosion to retard and eventually to terminate.
Other halogen species such as iodine and chlorine radicals play a smaller role than bromine for the occurrence of ODEs. Detectable amounts of iodine were never found in the Arctic and rarely in the Antarctic (Saiz-Lopez et al., 2007), probably since the concentration of iodine (I− and ) is only approximately 0.05 % of that of Br− in seawater (Luther et al., 1988; Grebel et al., 2010). Cl− is more than 600 times more abundant than bromide in seawater and in frost flowers (Simpson et al., 2005; Millero et al., 2008). However, chlorine cannot undergo a “chlorine explosion” in the same way as bromine due to the reaction of Cl with the very abundant methane to HCl, thus always reducing α in a hypothetical Cl explosion to values below unity. HCl quickly deposits to aerosols or to the snow surface. However, the presence of even a few pmol mol−1 of chlorine or iodine could speed up the ODEs through a recycling of BrO since the reaction of ClO or IO with BrO is approximately 1 order of magnitude faster than the BrO self-reaction (R2), i.e., (Atkinson et al., 2007)
with X=Cl or I compared to X=Br. The presence of chloride may also increase the speed of the bromine explosion. In the liquid phase, the reaction of deposited HOBr with chloride (Simpson et al., 2007),
occurs at a much faster rate than the reaction with bromide due to the larger concentration of chloride and the higher reaction constant of Reaction (R17) compared to Reaction (R7). A large fraction of the BrCl can then react with bromide to ultimately produce Br2, which is then released into the gas phase. However, some of the deposited HOBr instead releases BrCl, effectively reducing the α described above. Whether the presence of chloride speeds up or slows down the bromine explosion depends on the reduction of α and the quicker release of Br2 due to Reaction (R17). A similar reaction involving HOCl also occurs:
although at a much smaller reaction rate.
The underlying reaction mechanism may be an initial source for bromine, initiating the bromine explosion. The complete set of reactions can be found in Tables A3 and A4 in Appendix A. The release may need sunlight to occur efficiently (Pratt et al., 2013).
The meteorological conditions under which ODEs occur are also still under discussion. Often proposed are shallow, stable boundary layers (Wagner et al., 2001; Frieß et al., 2004; Lehrer et al., 2004; Koo et al., 2012). The inversion layer limits the loss of BrO from the boundary layer and also the replenishing of ozone from aloft.
ODEs occur predominantly at temperatures below −20 ∘C (Tarasick and Bottenheim, 2002) but could also be observed at temperatures of up to −6 ∘C (Bottenheim et al., 2009). Pöhler et al. (2010) found a nearly linear decrease of BrO concentrations with increasing temperature in the temperature range from −24 to −15 ∘C. Causes for the temperature dependence probably are a stronger surface-to-air flux of bromine, resulting from a stronger temperature gradient between the warm ice surface and cold air as well as the temperature-dependent reaction constants that may favor an ODE.
Frequently, successions of ODEs are measured at the same location over the year (e.g., Halfacre et al., 2014). It is suggested (Hausmann and Platt, 1994; Tuckermann et al., 1997; Bottenheim and Chan, 2006; Frieß et al., 2011; Oltmans et al., 2012; Helmig et al., 2012) that their cause is transport of air containing varying amounts of reactive Br and O3 from different locations to the measurement site, leading to recurrence. Jacobi et al. (2010) discussed the role of changing local and mesoscale weather conditions as well as a possibility of a replenishment of ozone via vertical diffusion from aloft. Toyota et al. (2011) demonstrated the occurrence and termination of ODEs by meteorological drivers in a numerical modeling study. Moore et al. (2014) found that narrow openings in the sea ice create vastly different vertical mass exchange rates between the boundary layer and the free troposphere, allowing replenishment of ozone from aloft. Cao et al. (2016) demonstrated in a modeling study the recurrence of an ODE by an instantaneously changing boundary layer structure. Currently unknown is the contribution of chemical oscillations to ODEs, which is the focus of the present study. Ozone-rich air is transported to the polar boundary layer from aloft by turbulent diffusion from the free troposphere. An inversion layer limits the rate of this replenishment. Ozone is also photochemically produced in situ by the well-known NOx-catalyzed O3-formation mechanism:
NO2 in turn is produced primarily by the reaction of NO and HO2:
where most of the HO2 is produced by
In the present study, it is shown that the chemical system coupled with vertical turbulent diffusion shows periodicity even without horizontal transport. After a bromine explosion, the ozone concentration drops to a negligible level. As a consequence, the formation of BrO via Reaction (R5) drops to nearly zero, so that Br instead reacts with HO2 or aldehydes to form HBr or with alkenes to form halogenated VOCs (e.g., Sander et al., 1997; Toyota et al., 2004; Keil and Shepson, 2006). In many models, including the present formulation, the reactions forming halogenated VOCs are simplified in a surrogate approach to form HBr instead. HBr then dissolves in the aerosols. Both gas-phase and dissolved HBr are chemically inert. Now that there is no more active bromine to destroy the ozone, the ozone concentration can increase again by either downward mixing into the boundary layer from the free troposphere or via NOx-catalyzed photochemical O3 formation. Together with the ozone, the active bromine species can also recover. However, due to the nonlinear nature of the bromine explosion, the reactivation speed of the inactive bromine in the aerosols scales with the amount of already active bromine. The reactivation of the inactive bromine thus starts out much slower than the ozone regeneration, allowing ozone to replenish before a new ODE occurs.
In the present study, the 1-D KINAL-T (KInetic aNALysis of reaction mechanics with Transport) model based on the work of Cao et al. (2016) is employed to calculate the oscillation of ODEs, where oscillation does not necessarily imply perfect periodic behavior. Finding experimental evidence for chemical oscillations is expected to be very difficult, since meteorological effects such as wind transport conceal the oscillating properties. Chemical oscillations of ODEs were never observed to the authors' knowledge. In measurements, it may be nearly impossible to disentangle the mechanisms involved in the recovery of ozone due to the role of, e.g., horizontal transport, vertical diffusion, or NO2 photolysis. Nevertheless, the present model provides important insight into the oscillations of ODEs.
In the present study, the former model of Cao et al. (2016) is extended and optimized in order to account for the oscillations of ODEs. For simplicity, constant temperature, zero vertical velocity, and prescribed turbulent diffusion coefficients (cf. Sect. 2.1.1) are assumed.
2.1 The differential equations
The chemical reaction system is described by the temporal and spatial variations of the species concentrations ci,j, where is the species number and denotes the discretized grid number. Since the gas temperature is assumed to be constant, density changes of the gas phase are neglected. Using central differences for the discretization of the physical space, the governing equations for the species concentrations yield (Cao et al., 2016)
The dry deposition term is assumed to be non-zero only in the lowest grid cell, j=1. The diffusion flux is given by
where the molecular diffusion coefficient D=0.2 cm2 s−1 and . In the one-dimensional grid under consideration, zj denotes the position of the center of grid cell j, and hj is the size of the grid cell j, . The turbulent diffusion coefficient at the interface of the grid cell is denoted by ; cf. Eq. (3).
The evaluation of the turbulent diffusion coefficient needs special attention since its parameterization depends on the meteorological conditions, which will be given in the next subsection. Moreover, the gas-phase reactions and the aerosol treatment will be provided.
2.1.1 Turbulent diffusion coefficient
The height-dependent turbulent diffusion coefficient k(z) is chosen to be similar to that by Cao et al. (2016), using the first-order parameterization of Pielke and Mahrer (1975) combined with an expression for the boundary layer height (Neff et al., 2008) for both neutrally and strongly stratified boundary layers, using the following empirical polynomial equation:
The discretized turbulent diffusion coefficients are determined by . In Eq. (4), L is the boundary layer height up to the inversion layer. L0 is the height of the surface layer which is assumed to be 10 % of the boundary layer height (Stull, 1988). is the turbulent diffusion coefficient at the top of the surface layer. κ=0.41 is the von Karman constant and the friction velocity, where v is the reference wind speed at the top of the surface layer, which is assumed to be v=5 m s−1. The surface roughness length for snow/ice, z0, is taken as m (Huff and Abbatt, 2000, 2002).
with the Brunt–Väisälä frequency:
The Coriolis parameter ( s−1) is calculated at the North Pole. g=9.81 m s−2 is the gravitational acceleration. For the two different temperatures of T=258 and 238 K under consideration, vertical potential temperature gradients of and K m−1, respectively, are considered, both of which correspond to the boundary layer height of L=200 m employed in this work. An inversion layer of thickness Linv is inserted at the top of the boundary layer, where the turbulent diffusion coefficient kt,inv is assumed to be constant and treated as a free parameter.
The turbulent diffusion coefficient kf in the free troposphere is assumed to be constant throughout the free troposphere. The reported values for turbulence in the free troposphere vary strongly between 0.01 and 100 m2 s−1 (Wilson, 2004; Ueda et al., 2012).
An example of the resulting profile of the turbulent diffusion coefficient as defined through Eq. (4) is displayed in Fig. 1, where the boundary layer height is 200 m, the wind speed is 5 m s−1, and inversion layer thickness is 50 m. The values of kt,inv and kf are 10 and 10 m2 s−1, respectively; these values refer to the base case discussed further below. The vertical diffusion between the boundary layer and the free troposphere is limited by a significantly reduced value of k(z). The value of kf is chosen to be large, since it allows the free troposphere to be nudged to the initial concentrations on a timescale of hours. Without the nudging, the ozone concentration at the top of the inversion layer (250 m) would be depleted on a timescale of a few dozen days due to ozone being transported downwards to the boundary layer and ozone losses through bromine that is transported upwards from the boundary layer. The nudging could be explained by horizontal transport of ozone-rich air to the free troposphere. The current implementation of the nudging was chosen due to its very simple implementation.
The profile of the turbulent diffusivities was chosen to be constant in the present paper. A gradually changing k profile, either by prescribing a time dependence or using real measurements, could force additional oscillations to occur, similar to the recurrence found by Cao et al. (2016), potentially hiding the influence of the chemistry on the oscillations.
2.1.2 Chemical reaction mechanism
The chemical reaction mechanism is based on the bromine/nitrogen/chlorine mechanism of Cao et al. (2014) with a few modifications to the gas-phase mechanism and more complex aerosol modeling. Both modifications are described below. The resulting mechanism encompasses 50 gas-phase species with 175 gas-phase reactions and 20 aerosol-phase species with 50 aerosol-phase reactions. The full reaction mechanism is described in Tables A1–A5 of Appendix A.
For simplicity, the gas-phase concentration of NOy is assumed to be a conserved quantity in the model. In reality, this is only partly true, since HNO3 tends to dissolve quickly in aerosols and can become inert, acting as a strong sink. This sink may be compensated by the emissions of NOx from the snow, which was discussed in the introduction, or by advection of NOx. The modeling of these processes would add more uncertainties since the emissions and depositions of the various reactive nitrogen species need to be parameterized. Also, in order to correctly model the deposition of HNO3, detailed aerosol chemistry is needed, which would increase the simulation time. Therefore, gas-phase NOy is assumed to be conserved in the present model; i.e., no emission and deposition of NOy and heterogenous reactions involving NOy are formulated to conserve gas-phase NOy.
2.1.3 Treatment of the aerosols
The aerosols are modeled as described by Sander (1999) and they are assumed to be liquid. A monodisperse aerosol with a radius r=1 µm is assumed. The pH value is fixed to 5. Simulations found little pH dependence of the oscillation periods for pH values below 7. The aerosols are assumed not to undergo any dynamics except for turbulent diffusion, and the aerosol volume fraction in air is fixed at a value of m m. Dry and wet depositions of aerosols as well as productions and emissions of aerosols are neglected. Exploratory simulations show that adding an aerosol deposition velocity in the range of 0.01–0.1 cm s−1 (Wu et al., 2018) increases the oscillation period by 10 %–40 % and decreases the bromide concentration during the build-up phases by approximately 10 %–30 %. However, if a sink for aerosol is introduced, sources for aerosols such as frost flowers or blowing snow should also be implemented. The produced/emitted aerosols are likely to have non-zero bromide content, providing a source for bromine species and potentially countering the effects of the dry and wet deposition. Therefore, for simplicity and in order to avoid the uncertainties in the production and emission mechanisms of aerosols, both sources and sinks of aerosols are neglected. The aqueous reaction constants, acid/base equilibria, mass accommodation coefficients, and Henry's law constants are taken from the box model CAABA/MECCA, version 3.8l (Sander et al., 2011), and they are summarized as follows.
The transfer rate for a gas species is given by
with the species- and temperature-dependent non-dimensional Henry's law constants Hi(T); cf. Eq. (12). The gas and the aerosol concentrations and , respectively, are in molec. cm−3. The transfer coefficient kt is calculated as
The diffusion limit for gas–aerosol mass transfer kdiff is
has been made, including the assumption of a monodisperse aerosol with radius r, the aerosol volume fraction ϕ, and aerosol surface area concentration A. The collision term kcoll (cf. Eq. 8) for the gas–aerosol mass transfer is
Here, αi is the species-dependent mass accommodation coefficient.
The temperature dependence of Henry's law constants of species i is calculated by
where is the enthalpy of dissolution divided by the universal gas constant R, and the mass accommodation coefficients are obtained from
where T0=298.15 K. The values for Henry's law constants and the mass accommodation coefficients are given in Table A3. The transfer rate for the corresponding aerosol species from the aerosol phase to the gas phase has the opposite sign.
2.2 Numerical aspects of the model
2.2.1 The numerical grid
A sketch of the numerical grid is displayed in Fig. 2. The computational domain extends 1000 m in the vertical direction and the number of exemplary grid cells is M=32. Different numerical grid resolutions were used to assure grid independence of the numerical solution of the equations; see discussion in the results section.
The lowest grid cell at the surface is m. The lowest grid cells are distributed logarithmically up to 100 m of the computational domain; cf. Fig. 3. In an intermediate regime, it is assured that at least one grid cell resides inside the inversion layer and that there are grid cells on the borders of the inversion layer to ensure a proper resolution the inversion layer. The remaining grid cells are distributed linearly up to the upper boundary at 1000 m. The numerical grid is displayed in Fig. 3, where the first 17 grid cells are logarithmically distributed, followed by five grid cells to resolve the inversion layer. The remaining 10 grid cells are distributed linearly. A black vertical line marks transition from the logarithmic to the linear regime, and the grey area marks the inversion layer.
The choice of switching from the logarithmic to the linear grid at 100 and at 200 m was tested, and the numerical results were not affected. The boundary layer height L is 200 m in the present simulations (cf. Table 1), so that the choice of 100 m for the switch of the numerical grid is chosen in order not to interfere with the height of the boundary layer.
Most simulations were conducted with 16 grid cells; simulations with 32, 48, and 64 grid cells were also performed to assure grid independence of the results. In Sect. 3.1.1, it is shown that 16 grid cells are sufficient to calculate the oscillation periods with errors smaller than one percent. In total, several hundred simulations for 200 real-time days were conducted in order to study the model parameters (see Table 1), so that the small grid size is convenient to minimize the total runtime of the simulations.
2.2.2 The numerical solver
In order to study the oscillation of ODEs for different parameter settings, the typical real time of about 20 d that was used by Cao et al. (2016) is extended to 200 d in the present study. Scanning the parameter space shown in Table 1 requires hundreds of simulations, so that at first, an optimization of the KINAL-T code (Cao et al., 2016) was conducted.
Cao et al. (2016) decoupled the diffusion terms, the chemical reactions were solved in an implicit way using the Rosenbrock 4 solver (Gottwald and Wanner, 1981), and diffusion was treated in an explicit way. The heterogenous reactions were solved as part of the chemistry equations.
This procedure has some disadvantages. Since the grid is logarithmic for z<100 m, the cell size hj is hj∝z in that regime. The diffusion timescale becomes very small for small z, which limits the time steps to the order of milliseconds if an explicit solver is chosen. Also, the heterogenous reactions on the ice surface destroy all HOBr in the lowest cell in some tens to hundreds of microseconds, depending on the size of the grid cells, so that the heterogenous reactions have to be solved as part of the diffusion equations in order to allow mixing of upper layers into the lowest cell during a single time step. Even then, however, time steps smaller than seconds are needed due to the strong coupling of the diffusion and the chemical reactions caused by the heterogenous reactions if the equations are solved completely decoupled. Thus, in the present code, the diffusion equations and the chemical reactions are solved fully coupled with the implicit, A-stable Rosenbrock 4 solver, resulting in a quite large Jacobian matrix of dimension , i.e., the product of the number of species, N, and grid cells, M. The time steps are chosen adaptively, where most time steps are of the order of minutes.
2.3 Base parameters
The base parameter settings as well as the range in which they are varied are shown in Table 1. The values for the temperature T, pressure p, boundary layer height L, aerosol volume fraction ϕ, and solar zenith angle are chosen following Cao et al. (2016).
An inversion layer thickness of Linv=50 m is chosen. Palo et al. (2017) found values ranging from 20 to 1000 m with a mean of 337 m. In the study of Neff et al. (2008), a shallow boundary layer with L≈165 m and an inversion layer thickness of Linv≈70 m were found. In the present study, it was found that a larger inversion layer thickness Linv can be compensated (i.e., leads to a similar behavior in the boundary layer) by choosing a correspondingly larger turbulent diffusion coefficient kt,inv, with a nearly linear relationship . The base parameter settings for the diffusion coefficient in the inversion layer has been determined by searching for the oscillating solutions of the numerical simulations.
The dependence of the oscillation period on [NOy] was investigated for two different temperatures (258 and 238 K) and with the chlorine mechanism turned on and off. The diffusion coefficients in the free troposphere kf were varied along with kt,inv. For sake of simplicity, the solar zenith angle (SZA) was assumed to be constant during a simulation. The base setting of a constant 80∘ corresponds to the conditions at the North Pole in mid-April.
2.4 Initial and boundary conditions
2.4.1 Initial conditions
The initial species concentrations are shown in Table 2. Initial concentrations of organic species are chosen to be consistent with the study of Hov et al. (1989). Nitrogen-containing species concentrations are varied as shown in Table 2. Emissions of nitrogen from the snow are not considered; instead, NOy is a conserved quantity in the model. Initial concentrations of bromine are zero in both the free troposphere and in the inversion layer. Starting with non-zero gas-phase bromine concentrations means that the initialization of the bromine explosion is not simulated; the simulation starts during the build-up stage of the bromine explosion.
2.4.2 Boundary conditions and heterogenous reactions at the ice surface
The upper boundary of the calculation domain at 1000 m is a Dirichlet boundary where all species concentrations are set to the initial concentrations given in Table 2. The presumed large diffusion coefficient of 10 m2 s−1 ensures that the free troposphere is nudged to the initial concentrations on a timescale of hours.
For the boundary at the ice surface, zero flux is assumed. The exchange with the snow/ice surface is modeled via the heterogenous reactions listed in Appendix A in Table A5. An example of the general treatment of a representative heterogenous reaction is
which is represented as a dry deposition reaction that occurs only in the lowest computational cell. The ice/snowpack itself is not modeled; instead, it is assumed that the salt content is infinite, so heterogenous reactions on the ice surface are effectively treated as
The first-order reaction constants are parameterized by
where the thickness of the lowest layer is h1 (cf. Eq. 3), and the dry deposition velocity is vd. The dry deposition velocity is modeled following the work of Seinfeld and Pandis (2006) as the inverse of the sum of three resistances (Ra, Rb, and Rc):
described as follows. The values of the resistances are calculated following the work of Huff and Abbatt (2000, 2002). First, the gas is transported from the center of the lowest grid cell z1 to the top of the interfacial layer at the surface roughness length z0 by turbulent diffusion, which leads to the aerodynamic resistance:
Then, the gas must be transported through the interfacial layer via molecular diffusion, resulting in the quasi-laminar resistance:
Finally, the surface resistance is estimated by
with the thermal velocity . Mi is the molar mass of the gas species undergoing the heterogenous reaction and R is the universal gas constant. For the range of γ in the present study (see Table A5), the aerodynamic resistance is the largest out of the three resistances. For HOBr, Eqs. (16)–(18) result in Ra=0.039 s cm−1, Rb=0.005 s cm−1, and Rc=0.003 s cm−1. Due to the small size of the lowest grid cell, the heterogenous reactions are very fast and their speed is actually limited by the turbulent diffusion of the depositing species from the upper grid cells to the lowest grid cell. The dry depositions of HCl and HBr provide sinks that prevent halogen concentrations from increasing infinitely.
In this section, the mechanism of oscillations of ozone depletion events as well as their possible termination are investigated. First, the reasons for oscillation to occur are discussed and the oscillation period is defined. Second, a closed system with aerosols as the only surface for the recycling of bromine is investigated. Moreover, a comparison to an earlier study (Evans et al., 2003) is presented. Finally, parameter studies are performed on the base parameters presented in Table 1 in order to investigate the variation of the oscillation period.
3.1 Oscillation and termination of ODEs
This section concerns the study of oscillation and termination of ODEs.
3.1.1 Oscillation of ODEs
The oscillation period of an ODE is defined as the average time difference of two consecutive ozone maxima. An ozone maximum is only accepted if the difference in mixing ratio with the preceding ozone minimum is at least 2 nmol mol−1, which is used as a threshold value to distinguish between oscillations and noise.
Figure 4 shows the oscillation of ODEs for the base setting of the present model (cf. Table 1) for 16, 32, 48, and 64 grid cells. The differences between the different grid sizes are small, the average oscillation period varies by less than 1 %, and thus 16 grid cells are sufficient to properly represent the major features of the ODEs and their oscillation.
Oscillation of ODEs may be explained as follows. After the occurrence of an ODE, there is not enough ozone left to sustain the BrO concentration through Reaction (R1), causing bromine to be converted into HBr, which deposits onto the ice/snow surface or onto aerosols and then turns into bromide; cf. Reaction (R12). The now-inactive bromide needs to undergo another bromine explosion (see Reaction R9) in order to become reactive again, which does not occur in the absence of ozone. This allows the ozone in the boundary layer to replenish via the photolysis of NO2 or by diffusion from the free troposphere through the inversion layer. Once the ozone mixing ratio is large enough, α, defined in Eq. (1), becomes larger than unity, allowing for another bromine explosion. Ozone and reactive bromine now replenish simultaneously where the formation of reactive bromine is becoming faster, increasing the ozone mixing ratio. Once the BrO mixing ratio has reached approximately 10 pmol mol−1, the ozone destruction by bromine becomes larger than the ozone regeneration. Then, another ODE occurs and the cycle repeats. Another sink of bromine in the model is the diffusion of part of the bromine species through the inversion layer, since bromine may leave the computational domain through the upper boundary, where the Dirichlet boundary conditions enforce the bromine concentrations to zero.
However, oscillations do not occur for all parameter settings as can be seen in Fig. 5, where kt,inv is increased from 10 to 50 cm2 s−1. For cm2 s−1, after the initial ODE and an oscillation with a reduced value of [O3], no further oscillation occurs. Instead, the reactive bromine and ozone establish a chemical equilibrium, and no further oscillation is observed; i.e., it terminates. The termination of an oscillation will be further discussed next.
3.1.2 Termination of ODE oscillations
In order to study the termination of ODE oscillations, the initial concentration of [NOy] is reduced to zero compared to the base case; cf. Table 1. Moreover, the turbulent diffusion coefficient in the inversion layer is increased from the base parameter of 10 cm2 s−1, displayed in Fig. 6a, to 20 cm2 s−1, shown in Fig. 6b.
If the ozone recovery rate during an ODE is too large compared to the amount of reactive bromine left for α<1 in Eq. (1), the remaining bromine is not sufficient to fully destroy the ozone, leading to shorter oscillation periods and lower levels of ozone peak concentrations as seen in Fig. 6b: bromine levels drop until ozone can regenerate, the regeneration of ozone reactivates a part of the inactive bromine, which in turn depletes ozone until the ozone and the bromine concentrations achieve an equilibrium, and thus only two oscillations occur.
The termination may occur directly after the initial ODE as shown in Fig. 5 or after a few oscillations as a dampened oscillation; see Fig. 6b. The initial ODE typically releases the largest amount of bromine because the initial ozone mixing ratio of 40 nmol mol−1 is much larger than the 10 nmol mol−1 mixing ratio of the oscillations. The total amount of bromine in boundary layer tends to drop after the initial ODE, mostly due to the dry deposition of HBr and to a lesser extent due to diffusion of bromine into the free troposphere.
This reduction in the bromine is the main dampening process. The smaller bromine mixing ratio may not be sufficient to destroy the remaining ozone once α<1 and can thus result in a termination at a later oscillation instead of the termination after the first ODE.
Both a large ozone regeneration rate and a higher Br release efficiency reduce the drop in the total bromine mixing ratio in the gas and aerosol phases that occur between successive oscillations. If the bromine release or ozone regeneration rate are sufficiently large, the bromine mixing ratio may increase for successive oscillations, as shown in Fig. 7. The additional ozone production due to an increased initial NOy mixing ratio shortens the oscillation period and therefore limits the bromine losses occurring between successive bromine explosions.
Termination may not occur at all during 200 d. Typically, the oscillation period becomes constant after the first few oscillations. The first oscillations are affected by the initial value of 40 nmol mol−1 for the ozone concentration. The fate of most of the bromine after an ODE is to be stored in aerosols as bromide. While the initial bromine explosion is mostly driven by heterogenous reactions on the ice/snow surface, the bromine explosions of the oscillations are driven by heterogenous reactions on the aerosols, which now hold a significant amount of bromide. After a few oscillations, the bromine deposited on the ice surface or diffused to the free troposphere between each oscillation becomes equal to the bromine released from the ice surface during each oscillation, resulting in a constant oscillation period thereafter.
In order to observe fast oscillations, an O3 recovery rate of more than 1 nmol mol−1 per day is required. However, as noted above, for an ODE to terminate properly, the O3 recovery rate during the termination of an ODE may not be too large. Figures 5 and 6 show a termination due to a sufficiently large kt,inv.
The effect of a strong inversion layer as well as the ozone formation via nitrogen oxides on ODEs will be studied in Sect. 3.4. The next subsection concerns different ways of initialization of ODEs.
3.2 Initialization of an ODE with only aerosols
So far, the ODEs were initiated through the assumption of a fixed value of 0.3 pmol mol−1 Brx inside the boundary layer (cf. Table 2). In the present subsection, another mechanism for the initiation is studied, where aerosols are used to initiate the ODEs. Five assumptions are changed with regard to the base case:
The concentration of Br− was set to 0.8 mol L−1, corresponding to a mixing ratio of 160 pmol mol−1 in the gas phase, which is different from the base setting of 0.05 mol L−1 (equivalent to 10 pmol mol−1) shown in Table 2.
The turbulent diffusion coefficient in the inversion layer is set to zero.
The initial concentration of gas-phase bromine is set to zero.
All heterogenous reactions on the ice/snow surface are turned off.
The [NOy] is increased from 50 to 100 pmol mol−1.
The large concentration of Br− could be caused by a blowing snow event. In this simulation, the main source of the first reactive bromine is via the heterogenous reaction of ozone; see Reaction (R19).
As a result of the different settings, the total bromine concentration is conserved during the simulation. Furthermore, the boundary layer is a closed system for this simulation. The results are shown in Fig. 8.
After 1 h, already 0.1 pmol mol−1 of reactive bromine is reactivated, which is sufficient for the bromine explosion on aerosols to become the dominant reactivation mechanism. Also, N2O5 can activate the first bromine by producing BrNO2. Reactive chlorine can also activate the first bromine, however, more slowly. Overall, 0.3 pmol mol−1 of reactive chlorine takes several days to produce an initial seed of 0.1 pmol mol−1 reactive bromine. Only in the first time steps, bromine is reactivated by the very slow release of Br via HOCl; see Reaction (R18).
After that, a regular bromine explosion occurs, albeit restarting from very low concentrations of 10−4 pmol mol−1 [Brx]. The initialization via reactivation of bromine on aerosols is much faster than reactivation via the ice surface, since the multiphase reactions involving aerosols are not diffusion limited. All other episodes start from about 30 pmol mol−1 of bromide in the aerosol phase, which is why they have longer induction stages of about 10 d compared to a few hours for this simulation.
It is of particular interest that oscillations occur without any external sources and sinks, such as dry depositions, emissions, or heterogenous reactions on the ice/snow surface. The density of each chemical element in the gas plus aerosol phase is conserved in this simulation, with hydrogen being the only exception due to the constant pH value of the aerosols. Due to the second law of thermodynamics, only reaction intermediates may oscillate. As an example, CO2 is a permanent sink for other organic species in this simulation. It is expected for the oscillations to terminate after a sufficient amount of reactive organics is converted to non-reactive organics.
3.3 Comparison to studies in the literature
The most relevant research in the area of oscillating ODEs was performed by Evans et al. (2003) which is used to validate the present model. Similar to the aerosol-only simulation of the previous subsection, aerosols are the only source and sink for bromine in the system studied by Evans et al. (2003).
A comparison between the model of Evans et al. (2003) and the present study is displayed in Fig. 9, where Fig. 9a is for a low NOx emission and an initial bromide mole fraction of 43 pmol mol−1 and Fig. 9b for elevated NOx emission by 35 % and an initial bromide mole fraction of 60 pmol mol−1.
Differences in the model and in the conditions are as follows:
The gas–aerosol mass transfer rates used by Evans et al. (2003) are approximately 20 times larger than these in the present work. Evans et al. (2003) employ the parameterization described by Michalowski et al. (2000). In that study, the diffusion-limit term kdiff (Eq. 9), which appears in the gas-to-aerosol transfer constant kin (Eq. 8) of the present paper, is neglected and only kcoll (Eq. 11) has been considered. However, the values used for kcoll and for kin are also different. For the species HOBr, for instance, the base parameters in the present study are s−1 and s−1. Using the values for the oscillating result of Evans et al. (2003) and estimating the aerosol radius via Eq. (10), which results in r=0.3 µm, the corresponding values are s−1 and s−1. These differences result not only from negligence of the diffusion limit but also from a larger accommodation coefficient (α=0.8 compared to α=0.5) as well as a larger aerosol surface area ( cm2 cm−3 versus cm2 cm−3).
NOx and HCHO are emitted from the snowpack as described by Evans et al. (2003). The emission rate is proportional to the photolysis rate of NO2 with an average emission rate of 1.2×109 molec. cm−2 s−1 for NOx and 3.6×108 molec. cm−2 s−1 for HCHO.
HNO3 transfer to aerosols is considered and it acts as a sink for NOy.
All heterogenous reactions and deposition on the ice surface are neglected. However, following Evans et al. (2003), PAN and H2O2 undergo dry depositions with velocities of vd=0.004 cm s−1 and vd=0.09 cm s−1, respectively.
The SZA is varied daily in the range of 65 to 97∘ following a cosine profile, which is consistent with a latitude of 73.4∘ on 15 April 2003.
Initial concentrations and parameters are set to the values described by Evans et al. (2003). In particular, the initial mole fraction of bromide is set to 43 pmol mol−1. In contrast to the study of Evans et al. (2003), the mixing ratio of acetaldehyde CH3CHO may evolve freely instead of being fixed to 18 pmol mol−1.
The results presented in Fig. 9 show that with an initial bromide mole fraction of 43 pmol mol−1, the oscillation period is approximately 5 d. The chemical reaction mechanism used in the present KINAL-T code predicts larger HBr and HOBr mixing ratios compared to the model employed by Evans et al. (2003), resulting in smaller BrO mixing ratios for the same total bromine mole fraction and thus slower ODEs. Ozone is completely depleted approximately 1 d after the ODE has started, which is more than twice as long as predicted by Evans et al. (2003). Also notably, ozone replenishes to approximately 8.5 nmol mol−1 before the ODE starts, whereas Evans et al. (2003) predict only approximately 4.5 nmol mol−1. This suggests that the bromine regeneration is slower or that less reactive bromine remains after an ODE in the present KINAL-T simulation. After an ODE, reactive bromine mixing ratios drop to approximately 10−4 pmol mol−1 in the present simulation. The bromine regeneration rate is approximately 1 order of magnitude per day in the present simulation. This means that if the bromine regeneration rate is the same but the reactive bromine mixing ratio obtained by Evans et al. (2003) drops to 10−2 pmol mol−1 after an ODE, which might explain the difference.
Neglecting the role of BrNO2 chemistry has been found to be of particular importance for finding oscillations of ODEs, since otherwise BrNO2 acts as a sink for both bromine and NOx. If BrNO2 chemistry is considered, similar structures to those seen in Sect. 3.4.2 for large NOy mixing ratios are found, where the large NOy concentrations cause a termination of the oscillations.
Another issue of importance is the larger gas–aerosol mass transfer constants used by Evans et al. (2003) compared to the present study. The gas-to-aerosol transfer constants used by Evans et al. (2003) are of the order of 10−3 s−1 compared to 10−4 s−1 for the base case. In the present study, the latter value has been adjusted to that used by Evans et al. (2003) in order to match their results. These increased coefficients allow for a quick recycling of HOBr, HBr, and BrONO2. With smaller gas–aerosol mass transfer constants, the bromine regeneration after an ODE slows down and, more importantly, a larger initial bromide mixing ratio (more than 100 pmol mol−1) is necessary to achieve BrO mixing ratios of at least 20 pmol mol−1 during an ODE. At an initial bromide mixing ratio of 43 pmol mol−1, the ozone depletion occurs on a timescale of weeks with the slower gas–aerosol mass transfer constant.
As discussed above, Michalowski et al. (2000) and Evans et al. (2003) ignored the diffusion limit. Staebler et al. (1994) measured a maximum value of r=0.1 µm in the aerosol size distribution at Alert, and therefore Evans et al. (2003) assumed that the diffusion correction may be neglected for this small value of aerosol size. However, even at r=0.1 µm, the HOBr transfer constants are calculated to decrease by a factor of 2 in the present study, which provides the motivation to consider its relevance in the present study. The aerosol transfer, however, is driven by the aerosol surface, which motivates the use of the aerosol surface distribution instead of the aerosol size distribution. This causes another shift towards larger aerosol sizes with an increased effect on the diffusion limit.
In order to reproduce the oscillation period of 3 d predicted by Evans et al. (2003), a second simulation with an increased initial bromide mixing ratio of 60 pmol mol−1 and increased NOx emissions by 35 % was conducted; cf. Fig. 9b. The main effect of the increased initial bromide mixing ratio alone is a decrease of the duration of the ODEs from 1 d to somewhat less than half a day and as a consequence, the oscillation period reduces by about half a day. The increased initial bromide mixing ratio, however, barely affects the bromine regeneration speed, since it is limited by the low mixing ratio of reactive gas-phase bromine (less than 10−4 pmol mol−1) after the termination of the ODEs and not by the aerosol-phase bromide concentration. The increased NOx emissions affect both the ozone regeneration and the bromine regeneration. The latter is not only increased by the larger ozone regeneration speed but also by the bromine explosion mechanism involving BrONO2. More BrO reacts to BrONO2, which quickly recycles bromide due to the large gas–aerosol mass transfer coefficients. Consequently, the ODEs start at an ozone mixing ratio of approximately 6 nmol mol−1 compared to the 8.5 nmol mol−1 for the previously used emission rate. Thus, the increased emissions reduce the oscillation period by about 1.5 d, resulting in the shorter oscillation period of ODEs found by Evans et al. (2003). The differences between the numerical results by Evans et al. (2003) and the present study are most likely due to the different chemical reaction mechanisms. Even though Evans et al. (2003) used the reaction constants provided by the same group as the present study, the knowledge about chemical reaction constants has greatly improved in the last decade (Atkinson et al., 2007). Moreover, it should be noted that Evans et al. (2003) used a box model, whereas in the present study, the one-dimensional KINAL-T code with a more advanced model for the heterogenous reactions and the aerosol treatment is used.
3.4 Study of model parameters influencing the oscillation period
This subsection concerns the variation of some environmental parameters that affect the oscillation of ODEs: the strength of the inversion layer, the turbulent diffusion in the free troposphere, the NOy mixing ratio, the aerosol volume fraction as well as the solar zenith angle on the oscillation period of the ODEs; cf. Table 1. The variation of the NOy mixing ratio is investigated for T=258 K (base setting) and T=238 K, as well as simulations where the chlorine mechanism is used (base setting) or neglected.
In the following, three properties of the oscillations of ODEs will be considered: the average oscillation period, i.e., the time difference between two ozone maxima, the number of oscillations, and the average maximum of the ozone mixing ratio; these characteristics are evaluated for a real time of 200 d.
3.4.1 Strength of the inversion layer
Diffusion from aloft is one of the two mechanisms that replenishes the ozone in the model. Since the thickness of the inversion layer is fixed (see Table 1), the turbulent diffusion constant kt,inv is the most important parameter controlling the strength of this replenishment. The turbulent diffusion constant in the free troposphere, kf, also plays an important role.
In order to eliminate the influence of the ozone regeneration by NO2, the concentration of NOy is set to zero for evaluation purposes. In Fig. 10, the dependence of the oscillation characteristics on the variations of kt,inv and kf is shown (cf. Fig. 10a–c), and the variation of the mixing ratios of O3 and Br at two different heights (100 and 225 m; Fig. 10d) for the base settings.
The smallest oscillation period of approximately 20 d is found for the turbulent diffusion coefficient of kf=105 cm2 s−1 in the free troposphere and for cm2 s−1. For very small turbulent diffusion coefficients of less than cm2 s−1, no oscillations occur since the ozone regeneration rate is too slow in the considered time of 200 d.
The oscillation period does not increase linearly with kt,inv since the ozone mixing ratio in the inversion layer changes with increased diffusion; three processes determine the ozone mixing ratio:
In the inversion layer, ozone is lost by diffusion into the boundary layer.
Ozone is replenished by its diffusion from the free troposphere into the inversion layer.
Bromine is mixed into the inversion layer and lost to the free troposphere, resulting in a partial ODE inside the inversion layer.
Inside the inversion layer, reactive bromine may survive due to the sustained ozone supply from the free troposphere. It turns out that larger diffusion coefficients inside the inversion layer result in increased ozone mixing ratios, converging to approximately 20 nmol mol−1 for kinv>20 cm2 s−1, which is half of the value at the top boundary of the computational domain. This is the reason for the sharp, nonlinear increase in the number of oscillations during 200 d.
For kinv<14 cm2 s−1, the oscillation period decreases strongly, and for larger values of kinv, termination is initiated. The mixing ratios for O3 and Br in the first regime, i.e., for kinv=10 cm2 s−1, are displayed in Fig. 10d. After the first ODE, the ozone regeneration due to diffusion is not very much affected by an ongoing ODE since the ozone mixing ratio is only slightly varying inside the inversion layer, severely limiting the ozone regeneration rate without termination.
Since the standard value of kf=105 cm2 s−1 used in the present simulation corresponds to an almost perfectly mixed free troposphere, even larger values do not affect the simulation results. By neglecting horizontal mixing and transport, it is essentially assumed that the air mass in the boundary layer is confined. However, the free troposphere will still have very different wind velocities, so it is reasonable that the air in the free troposphere is exchanged quickly with fresh air even though the boundary layer is confined. A large turbulent diffusion coefficient in the free troposphere ensures a quick exchange of the air with the upper simulation boundary.
The influence of a reduction of kf to values of 104 and 103 cm2 s−1 is presented in Fig. 10a–c. The value of kf=104 cm2 s−1 still corresponds to nearly perfect mixing inside the free troposphere as can be seen by the negligible differences in the mean oscillation period between kf=105 cm2 s−1 and kf=104 cm2 s−1. All resulting profiles are very similar.
Reducing kf to 103 cm2 s−1, however, has a large impact, since bromine transported to the free troposphere will stay there for several weeks (as may be estimated from the diffusion timescale) before being transported to the upper boundary. Ozone is also transported much more slowly to the lower layers of the free troposphere, causing the ozone levels to drop to approximately 15 nmol mol−1 at 500 m for cm2 s−1; ozone levels decrease further with increased values of kt,inv, converging to 12 nmol mol−1 for kt,inv exceeding 50 cm2 s−1. The ozone mixing ratio in the inversion layer drops to less than 10 nmol mol−1, reducing the ozone recovery rate in the boundary layer and also limiting the maximum levels to which ozone can be recovered.
Oscillations occur only at larger turbulent diffusion coefficients of kt,inv > 14 cm2 s−1, and they terminate for kt,inv > 50 cm2 s−1; see Fig. 10b. In contrast to the larger values kf, the ozone mixing ratio in the inversion layer decreases with increasing kt,inv in the present case. Also, the time between two oscillations tends to increase progressively after each oscillation since a larger turbulent diffusion coefficient in the inversion layer causes a greater loss of bromine to the free troposphere, which in turn decreases the speed of the bromine explosion in the boundary layer.
In cases where only two or three maxima occur, i.e., kinv > 16 cm2 s−1, due to the termination of the oscillations, the standard deviation of both the oscillation period and the ozone maxima increase sharply, since the first few oscillations are still affected by the first ODE, and the oscillations before the termination tend to have ozone maxima that are closer to the equilibrium mixing ratio of ozone.
3.4.2 The role of NOy, T and chlorine
In the present model, NOy is treated as a conserved quantity. In this subsection, the NOy mixing ratio is varied as the major parameter influencing NOx-catalyzed photochemical O3 formation (see Reaction R20), and its effect on the ODEs is investigated.
Figure 11 shows the variation of the oscillation period with NOy mixing ratios of up to 300 pmol mol−1 for two different temperatures of 258 K (standard value) and the reduced value of 238 K; cf. Fig. 11a. Oscillation periods of less than 5 d are obtained for 258 K. The number of oscillations increases linearly with the NOy mixing ratio (Fig. 11b), with a y intercept given by the regeneration of ozone purely via diffusion through the inversion layer. At about [NOy]=200 pmol mol−1 for T=258 K, oscillations tend to terminate. Once the mixing ratio of NOy is very large, the bromine released during an ODE is not able to completely destroy all NOx. Thus, even during an ODE, ozone is produced by the NO2 photolysis, increasing ozone regeneration and making a termination more likely. The non-zero NOx concentrations also result in more BrNOx (which is the sum of BrNO2 and BrONO2) formation during the termination. BrNOx then makes up approximately 60 % of the total gas-phase bromine.
Moreover, the chlorine mechanism has been deactivated by setting all chlorine initial concentrations to zero and changing the heterogenous reaction of HOBr to only release Br2; see Fig. 11a and b. While the presence of chlorine may enhance the ODE by enhanced O3 destruction through the very fast reaction of BrO with ClO, the bromine explosion is actually slowed down by the presence of chlorine. This is due to the fact that when chlorine is included, part of the heterogenous reactions release BrCl instead of Br2; thus, the amount of released bromine is reduced. Also, without chlorine, the slower ODE increases the duration of the bromine explosion, which also increases the bromine released, resulting overall in faster oscillations, since further oscillations contain more bromine in aerosols that can be reactivated. As a side effect, the ozone maximum value is slightly smaller without the chlorine chemistry.
For T=238 K, the oscillation period is smaller compared to T=258 K for small [NOy], as can be seen in Fig. 11c. However, termination of oscillations starts already at around 70 pmol mol−1 of NOy instead of at around 200 pmol mol−1 for T=258 K. Figure 11d shows a termination for T=238 K after 80 d. In this temperature region, HNO4 becomes very stable due to the decay of HNO4 being nearly 2 orders of magnitude slower (see Reaction 56 in Table A1) and replaces PAN as the most abundant nitrogen species. The shift towards HNO4 formation reduces the NO2 concentration, retarding the ozone regeneration.
At the lower temperature, the ODE mechanism becomes more efficient, e.g., the reaction constant in the Br2-producing BrO self-reaction increases by 33 % (Reaction 5 in Table A1), while many of the HBr-producing reactions, e.g., Reactions (9) and (10) in Table A1, slow down by around 20 %. The total amount of bromine released for the first ODE increases, whereas the amount of bromine released for the oscillations decreases due to the slower ozone regeneration.
The main reason for the earlier termination of the oscillations at T=238 K is a strong shift towards the increased HNO4 formation. During an ODE, the HNO4 can be destroyed to directly produce NO2 by reacting with OH or by decaying through Reactions (56) and (57) in Table A1. PAN, however, is more stable during an ODE at 258 K due to a larger formation of CH3CO3 via, e.g., Reaction (34) in Table A1 caused by the larger OH formation during an ODE, consuming NO2 (Reaction 65) instead of producing it through Reaction (84) or through the photolysis of PAN. The shift from PAN as the most stable species towards HNO4 for the lower temperature increases the ozone recovery during an ODE. Since a larger ozone recovery during an ODE facilitates chemical equilibrium with the reactive bromine, this results in earlier terminations of the oscillations of ODEs.
3.4.3 The influence of the aerosol density
In order to study the influence of the aerosol characteristics, the standard value of the aerosol volume fraction of 10−11 m3 m−3 is varied between 10−12 and m3 m−3; see Fig. 12. For small aerosol concentrations, the recycling of HBr is too weak for a full ODE to occur since only small bromine concentrations are released before the termination of an ODE. Only a partial ODE and no oscillations take place.
For larger aerosol mixing ratios, the faster bromine recycling reduces the oscillation period; however, the ozone does not regenerate faster. Thus, the ozone maximum decreases so that the oscillations release less bromine, resulting in a larger net bromine loss per oscillation. Also, the reactivation strength of aerosol bromine increases relative to the activation on the ice surface, resulting in a lower bromine release from the ice, also increasing the net bromine loss for each oscillation, which ultimately leads to the termination of the oscillations for aerosol volume fractions larger than about m3 m−3.
3.4.4 Variation of the solar zenith angle
The mean oscillation period displayed in Fig. 13a hardly changes when the SZA is varied from its standard value of 80∘ (see Table 1) within the range of 70 and 83∘. The variations stay within 1 standard deviation. For , the ODEs do no longer occur due to the slow photolysis frequencies. Surprisingly, the oscillation period does not monotonically decrease with increased SZA; instead, there is a minimum at . For a lower SZA, some or even all ODEs are only partial, as Fig. 13b demonstrates for the value of . In particular, the minimum ozone mixing ratio for the six oscillations shown is approximately 10 nmol mol−1 and the ozone depletion restarts at an ozone mixing ratio of about 18 nmol mol−1. For a SZA of 70∘, the NO2 mixing ratio decreases to about 5 pmol mol−1 during the ODEs instead of to nearly zero at 80∘. Also, BrNOx and PAN are photolyzed faster, increasing the NOx formation. Only about 80 pmol mol−1 of bromine is released at during the first ODE, which is about two-thirds of the value at 80∘. Interestingly, gas-phase bromine does not drop to zero for the later oscillations; however, the BrO concentration drops to nearly zero. BrO mixing ratios do not exceed 10 pmol mol−1, which is much lower than the typical mixing ratio of 30–40 pmol mol−1 of numerical simulations with a SZA of 80∘; this is most likely a result of the increased formation of HO2.
Another characteristics are the faster photolysis reactions of BrO and HOBr for lower SZA. For , 80 % of the BrO photolyzes to Br and to O3, which results in a null cycle. The resulting smaller BrO mixing ratio also decreases the rate of self-recycling, which is part of the ozone-destroying cycle. Overall, 70 % of the HOBr photolyzes to HO and Br, slowing down the bromine explosion substantially and consuming HO2 in the process. The faster Br2 photolysis, however, does not further enhance the ozone destruction, since Br2 is already photolyzed extremely fast even at .
For , the fastest reaction of BrO is with NO, producing NO2 and Br in the process. NO2 is photolyzed to ozone, resulting in a net null cycle. For , the BrO self-reaction is stronger than its reaction with NO, favoring a full ODE.
In the present study, the one-dimensional KINAL-T model developed by Cao et al. (2016) was extended and optimized in order to study the potential of ODEs to recur. The extension concerns the chemical reaction mechanism as well as the treatment of aerosols and the improvement of the numerical solver. The model was employed to study both the oscillation and the termination of ODEs, and several parameters were varied to investigate their influence on the oscillation period, the maximum ozone mixing ratio, and the number of oscillations of the ODEs. After an ODE, ozone can be replenished by the diffusion of ozone from the free troposphere to the boundary layer and/or by the photolysis of NO2; it is found that either of these two O3 sources is sufficient to drive the oscillations. Another result of the present study is that the chemistry of ODEs coupled with the vertical diffusion alone can cause the oscillation of ODEs at the surface even without the existence of horizontal transport.
A strong inversion layer was found to be essential for the oscillation of ODEs since the steady mixing of the ozone back into the boundary layer may provide a sufficiently high ozone level to keep the reactive bromine in the boundary layer at a significant level, which then establishes chemical equilibrium with the remaining ozone.
Without the presence of reactive nitrogen oxides, the system is a chemically heterogenous, diffusion-driven oscillating system, the fastest periods of which were found to be approximately 20 d. Fast replenishment of the air in the free troposphere was found to lead to faster oscillations. It may be possible to find conditions leading to even shorter oscillation periods such as a slightly smaller SZA and moderately higher aerosol mixing ratios.
The replenishment of ozone via the photolysis of NO2 is a chemical gas-phase process. Faster oscillation periods of approximately 5 d are found due to the destruction of NOx during an ODE. However, at sufficiently high nitrogen oxide levels, the amount of bromine released during the bromine explosion is not large enough to keep the NO2 mixing ratio low, so that the oscillations can terminate due to the ozone regeneration, keeping the reactive bromine at a significant level. With high NOy mixing ratios, oscillations are possible even if the boundary layer does not interact at all with the free troposphere. Deactivation of the chlorine mechanism speeds up the bromine explosion, since the heterogenous reactions of HOBr on aerosols and snow/ice surfaces always produce Br2 instead of Br2 and BrCl. The absence of chlorine thus results in faster oscillations.
More sunlight, for a SZA up to 77∘, and a higher aerosol volume fraction of up to m3 m−3 are beneficial for faster oscillations, at even higher values, the oscillation retards or terminates. Since bromine may be lost over time due to dry deposition and mixing into the upper troposphere, a strong release of bromine for each oscillation is important to enable the fast destruction of ozone so that no chemical equilibrium of bromine with the ozone may be established.
The present simulations were compared to results of an earlier study by Evans et al. (2003). Using the same initial bromide mixing ratio of 43 pmol mol−1 and the same NOx emissions, a shorter oscillation period of 5 d was found in comparison with 3 d predicted by Evans et al. (2003). The difference in the oscillation periods is caused by a slower reactive bromine regeneration after an ODE or a stronger bromine depletion during the termination of the ODEs in the present model. By assuming an increased initial bromide mixing ratio of 60 pmol mol−1 and stronger NOx emissions by 35 %, the oscillation period of 3 d found by Evans et al. (2003) could be reproduced. The differences may be attributable to different chemical reaction mechanisms, a more advanced treatment of the aerosol in the present study as well as to the use of a box model by Evans et al. (2003) versus a 1-D model in the present simulation.
Even though the present simulations are based on somewhat idealized assumptions, they demonstrate that there are additional reasons for the observed oscillations of ODEs that go beyond modified environmental conditions or advection of air masses with varying ozone and halogen content. Experimental validation of these simulations could be a challenge since these external causes of oscillations and intrinsic oscillations are likely to occur simultaneously. However, it is possible that the conditions simulated in the present paper can be found, e.g., at high latitudes in the Arctic where day/night cycles do not play any role and oscillations may be observed. Thus, the present study provides valuable insight into parametric dependencies of the characteristics of the oscillations of ODEs and their termination.
An interesting extension of the present model could be the consideration of snowpacks. A finite amount of sea salt that is consumed during the bromine explosion and redeposited after the bromine explosion may have an interesting effect on the oscillations. This may also allow for the modeling of NOx emissions from the snow, relaxing the present assumption of a conserved NOy mixing ratio.
The consideration of more realistic meteorological effects requires the use of more advanced 3-D simulations which are currently being developed in extension of the previous work of Cao and Gutheil (2013). The new simulations will include horizontal advection and vertical transport explicitly.
The data may be obtained from the corresponding author upon request.
A1 Gas-phase reactions
Reaction (70) denotes the photolysis of HNO3 inside the aerosol phase. Since emissions of NOx and transfers of NOy to the aerosol phase are not considered in the present model, Reaction (70) is necessary to recycle HNO3. Its rate is calculated by the transfer rate of HNO3 to the aerosol phase (Cao et al., 2014). Bottenheim et al. (1986) found that the majority of NOy is in the form of PAN, as predicted by this model, whereas the HNO3 mixing ratio corresponds to a few percent of the NOy mixing ratio. Without Reaction (70), however, the model predicts that more than 80 % of gas-phase NOy is in the form of HNO3. It was proposed (Zhu et al., 2010; Ye et al., 2016) that a re-noxification of HNO3 may occur due to photolysis in the snowpack and aerosol phase, which occurs at a much faster rate than in the gas phase. Zhu et al. (2010) found an absorption cross-section of HNO3 on ice surfaces enhanced by 3 orders of magnitude. Ye et al. (2016) found an enhancement of the photolysis rate of particulate HNO3 of 300 compared to the gas-phase photolysis, corresponding to photolysis rates on the order of 10−4 s−1, which is consistent with the rate of Reaction (70).
A2 Photolysis reactions
A3 Gas–aerosol mass transfer constants
Table A3 shows Henry's law constants H and mass accommodation coefficients α with their temperature dependence TH and Tα as well their molecular mass M for all species undergoing a reaction of the form
All constants are taken from the CAABA/MECCA model (Sander et al., 2011). The calculation of the transfer constants is outlined in Sect. 2.1.2. Perfect solubility is assumed for BrONO2 and N2O5, which is denoted by a Henry's law constant of infinity. No transfer from the aerosol to the gas phase occurs for those species. These species directly undergo aqueous-phase reactions where the reaction rate is proportional to the gas-to-aerosol transfer constant kin in Eq. (8); see Table A4.
A4 Aqueous-phase reactions and equilibria
All aqueous reaction constants are taken from Sander et al. (2011). Acid/base equilibria are treated as very fast reactions where the ratio of the reaction constants is equal to the equilibrium constant. A few reactions are proportional to the gas-to-aerosol transfer constant kin (Eq. 8) of the depositing species.
A5 Heterogenous reactions and dry depositions
Table A5 shows all heterogenous reactions and dry depositions occurring on the snow surface. The calculation of the reaction constants, which are non-zero only in the lowest grid cell, is described in Sect. 2.4. The mass accommodation coefficient is γ=0.06 (Sander and Crutzen, 1996) for most species. Since the strongest resistance is the species-independent turbulent resistance, the deposition velocities for the different species vary only slightly around 21 cm s−1. Deposition velocities in the present model are relatively large since the lowest grid cell is at 10−4 m, reducing the turbulent resistance by a large factor compared to models using a linear grid. Also, the surface resistance is usually the largest resistance and widely calculated using parameterizations outlined by Wesely (1989), which, however, does not hold for ice/snow surfaces. Due to the large deposition velocity, the heterogenous reactions are rate limited by the downward diffusion of the depositing species, replenishing in the lowest grid cell.Atkinson et al. (2004)Atkinson et al. (2004)Atkinson et al. (2007)Atkinson et al. (2007)Atkinson et al. (2007)Atkinson et al. (2007)Atkinson et al. (2004)Atkinson et al. (2007)Atkinson et al. (2007)Atkinson et al. (2007)Atkinson et al. (2007)Atkinson et al. (2007)Borken (1996)Borken (1996)Barnes et al. (1993)Barnes et al. (1993)Atkinson et al. (2006)Alfonso et al. (1997)Alfonso et al. (1997)Atkinson et al. (2004)Atkinson et al. (2004)Atkinson et al. (2004)Atkinson et al. (2004)Atkinson et al. (2004)Atkinson et al. (2004)Atkinson et al. (2006)Atkinson et al. (2006)Atkinson et al. (2006)Sander et al. (1997)Atkinson et al. (2006)Atkinson et al. (2006)Atkinson et al. (2006)Atkinson et al. (2006)Atkinson et al. (2006)Atkinson et al. (2006)Atkinson et al. (2006)Atkinson et al. (2006)Mallard et al. (1993)Atkinson et al. (2006)Atkinson et al. (2006)Atkinson et al. (2006)Atkinson et al. (2006)Atkinson et al. (2006)Sander et al. (1997)Sander et al. (1997)Sander et al. (1997)Sander et al. (1997)Atkinson et al. (2004)Atkinson et al. (2004)Atkinson et al. (2004)Atkinson et al. (2004)Atkinson et al. (2004)Atkinson et al. (2004)Atkinson et al. (2004)Atkinson et al. (2004)Atkinson et al. (2004)Atkinson et al. (2004)Atkinson et al. (2004)Atkinson et al. (2004)Atkinson et al. (2006)Atkinson et al. (2006)Atkinson et al. (2006)Atkinson et al. (2006)Atkinson et al. (2006)Atkinson et al. (2006)Atkinson et al. (2007)Atkinson et al. (2007)Atkinson et al. (2007)Atkinson et al. (2007)Cao et al. (2014)Atkinson et al. (2004)Atkinson et al. (2004)Atkinson et al. (2004)Atkinson et al. (2004)Atkinson et al. (2004)Atkinson et al. (2004)Atkinson et al. (2004)Atkinson et al. (2004)DeMore et al. (1997)Atkinson et al. (2006)Atkinson et al. (2007)Nesbitt et al. (1995)Atkinson et al. (2006)Atkinson et al. (2006)Atkinson et al. (2006)Atkinson et al. (2006)Atkinson et al. (2006)Atkinson et al. (2004)Atkinson et al. (2004)Atkinson et al. (2006)Atkinson et al. (2006)Atkinson et al. (2007)Atkinson et al. (2007)Atkinson et al. (2007)Atkinson et al. (2007)Atkinson et al. (2007)Atkinson et al. (2007)Atkinson et al. (2007)Atkinson et al. (2007)Atkinson et al. (2007)Atkinson et al. (2007)DeMore et al. (1997)Atkinson et al. (2007)Atkinson et al. (2007)Atkinson et al. (2007)Atkinson et al. (2007)Atkinson et al. (2007)Atkinson et al. (2007)Atkinson et al. (2007)Atkinson et al. (2007)Atkinson et al. (2007)Atkinson et al. (2007)Atkinson et al. (2007)Atkinson et al. (2007)Atkinson et al. (2007)Atkinson et al. (2007)Atkinson et al. (2007)Atkinson et al. (2007)Atkinson et al. (2007)Atkinson et al. (2007)Atkinson et al. (2007)Atkinson et al. (2007)Atkinson et al. (2007)Atkinson et al. (2007)Atkinson et al. (2007)Atkinson et al. (2007)Sander et al. (1997)Sander et al. (1997)Sander et al. (1997)Sander et al. (1997)Atkinson et al. (2006)Atkinson et al. (2006)Atkinson et al. (2006)Atkinson et al. (2006)Atkinson et al. (2006)Atkinson et al. (2006)Atkinson et al. (2006)Borken (1996)Borken (1996)Atkinson et al. (2006)Atkinson et al. (2006)Atkinson et al. (2007)Atkinson et al. (2007)Atkinson et al. (2007)Atkinson et al. (2007)DeMore et al. (1997)Atkinson et al. (2006)Lehrer et al. (2004)Sander et al. (2011)Lehrer et al. (2004)Lehrer et al. (2004)Lehrer et al. (2004)Lehrer et al. (2004)Lehrer et al. (2004)Lehrer et al. (2004)Lehrer et al. (2004)Lehrer et al. (2004)Lehrer et al. (2004)Lehrer et al. (2004)Lehrer et al. (2004)Lehrer et al. (2004)Lehrer et al. (2004)Lehrer et al. (2004)Lehrer et al. (2004)Sander et al. (2011)Lehrer et al. (2004)Sander et al. (2011)Lehrer et al. (2004)Sander et al. (2011)Sander et al. (2011)Sander et al. (2011)Sander et al. (2011)
MH developed the code that was used to perform the simulations and created all figures presented in the paper. The code is based on previous work of LC, who helped to advance the present more extended code. HS contributed with respect to the model extension and validation of the results. UP and EG devised the methodology and supervised the project. The draft manuscript was edited by MH, and all authors contributed through numerous revisions of the draft paper.
The authors declare that they have no conflict of interest.
The authors thank Rolf Sander from the Max Planck Institute for Chemistry, Mainz, Germany, for very fruitful discussions concerning the chemical reaction scheme and the aerosol treatment. The authors gratefully acknowledge funding by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Projektnummer 85276297 and through HGS MathComp. Le Cao acknowledges funding through the National Natural Science Foundation of China (grant no. 41705103).
This research has been funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Projektnummer 85276297 and through HGS MathComp. Le Cao received funding through the National Natural Science Foundation of China (grant no. 41705103).
This paper was edited by Laurens Ganzeveld and reviewed by three anonymous referees.
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