The gas-phase formation mechanism of iodic acid as an atmospheric aerosol source

Iodine is a reactive trace element in atmospheric chemistry that destroys ozone and nucleates particles. Iodine emissions have tripled since 1950 and are projected to keep increasing with rising O3 surface concentrations. Although iodic acid (HIO3) is widespread and forms particles more efficiently than sulfuric acid, its gas-phase formation mechanism remains unresolved. Here, in CLOUD atmospheric simulation chamber experiments that generate iodine radicals at atmospherically relevant rates, we show that iodooxy hypoiodite, IOIO, is efficiently converted into HIO3 via reactions (R1) IOIO + O3 → IOIO4 and (R2) IOIO4 + H2O → HIO3 + HOI + (1)O2. The laboratory-derived reaction rate coefficients are corroborated by theory and shown to explain field observations of daytime HIO3 in the remote lower free troposphere. The mechanism provides a missing link between iodine sources and particle formation. Because particulate iodate is readily reduced, recycling iodine back into the gas phase, our results suggest a catalytic role of iodine in aerosol formation.

Iodine is a reactive trace element in atmospheric chemistry that destroys ozone and nucleates particles. Iodine emissions have tripled since 1950 and are projected to keep increasing with rising O 3 surface concentrations. Although iodic acid (HIO 3 ) is widespread and forms particles more efficiently than sulfuric acid, its gas-phase formation mechanism remains unresolved. Here, in CLOUD atmospheric simulation chamber experiments that generate iodine radicals at atmospherically relevant rates, we show that iodooxy hypoiodite, IOIO, is efficiently converted into HIO 3

via reactions (R1) IOIO + O 3 → IOIO 4 and (R2) IOIO 4 + H 2 O → HIO 3 + HOI + (1) O 2 .
The laboratory-derived reaction rate coefficients are corroborated by theory and shown to explain field observations of daytime HIO 3 in the remote lower free troposphere. The mechanism provides a missing link between iodine sources and particle formation. Because particulate iodate is readily reduced, recycling iodine back into the gas phase, our results suggest a catalytic role of iodine in aerosol formation.
Iodine is a trace constituent of the atmosphere that is particularly efficient at forming new particles. While sulfuric acid (H 2 SO 4 ) 1-3 , methanesulfonic acid 1,4 and nitric acid 5 all require an additional vapour (ammonia, NH 3 or dimethylamine (DMA)) to form particles, highly oxygenated organic molecules (HOMs) 6 and iodine [7][8][9] can do so alone. Iodine nucleation rates exceed those of H 2 SO 4 (in excess NH 3 ) at comparable concentrations of iodic acid (HIO 3 ) 10 . Furthermore, HIO 3 growth rates of nanoparticles are both charge-and dipole-enhanced, exceeding the neutral collision rate 10,11 .
Currently, iodine particle formation is rarely represented in atmospheric models-such models form most particles from the nucleation of H 2 SO 4 and include iodine primarily because of its ozone-destroying potential 12 . While sulfur emissions are projected to decrease due to pollution control measures (probably to a few tens of teragrams of SO 2 per year by 2100 (ref. 13 ), iodine emissions have been increasing due to human activity. Iodine is primarily emitted from oceans by the reaction of O 3 with iodide (I − ) dissolved in surface waters, which liberates volatile iodine species (hypoiodous acid (HOI) and iodine (I 2 )) to the atmosphere 14,15 . This marine source is enhanced as a result of O 3 pollution on local and hemispheric scales 16,17 as well as the thinning of sea ice 18 , and now accounts for iodine emissions of ~3 Tg yr −1 (refs. 19,20 ).
Over the past 70 years, iodine concentrations have tripled in ice-core records in Greenland 18 , Alpine glaciers 17 and tree-ring records in Tibet 21 .
Iodine is highly reactive and participates in catalytic reaction cycles that enhance its atmospheric impact. A catalytic role is well known for O 3 loss, but has, as of yet, not been suggested for particle formation. Iodine in the lower stratosphere has a 6-15 and 400-1,000 times higher O 3 destruction potential per atom than bromine and chlorine 22 . Extremely low mixing ratios of iodine oxide (IO) radicals (for example, ~0.1 parts per trillion by volume (pptv); IO = 10 −13 volume mixing ratio) can therefore affect the lifetime of climate-active gases (for example, O 3 and CH 4 ) 19,23,24 . This chemical reactivity extends to heterogeneous reactions involving aerosol iodide (I − ) 14,15 and iodate (IO 3 − ) (refs. 25,26 and references therein), which is the thermodynamically most stable form of iodine. The efficient multiphase chemistry of IO 3 − is markedly different from that of inert aerosol sulfate (SO 4 2− ), which accumulates without further chemical conversion until it is scavenged from the atmosphere by wet or dry deposition.
Iodine is ubiquitous in the atmosphere 22,23,27,28 , and HIO 3 has been detected in coastal marine air 9,10,29 , the Arctic and Antarctic boundary layer 9,10,30-32 , various continental sites 10 and in the lower free troposphere 10,33 . Several precursors for HIO 3 have been suggested: hydrated Article https://doi.org/10.1038/s41557-022-01067-z the gas-phase chemical kinetics during the early stages of the iodine photolysis experiments. Interestingly, iodine oxide clusters I x O y (x ≥ 2, y ≥ 3) larger than IOIO are formed too late to explain the rapid formation of HIO 3 as an early generation product (Extended Data Fig. 2 and Supplementary Table 2). Figure 2 shows that the extended model accurately predicts the measured HIO 3 production rates, pHIO 3 , over a wide range of I radical production rates, pI (10 4 -10 6 molec cm −3 s −1 ). Here, pHIO 3 is calculated from HIO 3 concentration measurements and the well-known loss rates to the chamber walls, and pI is calculated from the photolysis of I 2 . The HIO 3 yield, defined as the ratio of pHIO 3 and pI, is a function of the experimental conditions and varies between 10 and 20%. This variability is iodine atoms 10,34 , hydrated IO radicals 34 , iodine dioxide (OIO) radicals 35 and larger iodine oxides (I 2 O 3 , I 2 O 4 and I 2 O 5 ; refs. 34,[36][37][38]. However, these mechanisms remain speculative and have not been demonstrated experimentally, leaving atmospheric HIO 3 observations unexplained. Recent field observations of iodine-induced nucleation over remote oceans 31 and of IO 3 − in stratospheric aerosols 22 suggest a widespread role of iodine particle formation, but the conundrum of the missing HIO 3 source mechanism blocks our ability to connect iodine sources to particle formation in atmospheric models.

CLOUD measurements
In this Article we report iodine chemistry and particle formation experiments under marine boundary layer conditions at the CERN CLOUD chamber (Methods). Because of the large chamber volume (26.1 m 3 ) and associated long wall-loss lifetime (~8 min; comparable to typical condensation rates in the atmosphere), precursor gas-phase concentrations do not need to be increased above atmospheric levels (Supplementary Table 1). Experiments were conducted at 283 K and 263 K, with I 2 at a typical volume mixing ratio of 8 pptv (range of <0.5-330 pptv), 40% relative humidity (RH, <3-90%) and 40 ppbv O 3 (<1-80 parts per billion by volume (ppbv)). The chemistry is driven by photolysis of I 2 , which is measured by cavity-enhanced differential optical absorption spectroscopy (CE-DOAS; Methods) and bromide chemical ionization mass spectrometry (Br − -MION-CIMS). HIO 3 is measured quantitatively by NO 3 − -CIMS, and HOI by Br − -MION-CIMS. Both instruments also allow insights into the evolution of other iodine species (IO, OIO, I 2 O 2 , I 2 O 4 and so on; Methods).
The measurements are accompanied by chemical box modelling, building on state-of-the-art iodine chemistry (Methods). The model is constrained by measurements of I 2 concentrations, actinic fluxes, temperature, humidity and losses of molecules to the chamber walls (stainless steel, characterized via H 2 SO 4 ) and chamber dilution (~2 h). Established iodine chemistry only contains a single reaction predicted from theory 35 that could form HIO 3 from OIO + OH. This reaction does not form HIO 3 in the HO x -free conditions when I 2 is photolysed by green light 10 . Even if OH radicals were present, they would be predominately scavenged by other species. The model base case does not form any HIO 3 or HOI under the experimental conditions probed (Fig. 1). Based on the comprehensive experimental evidence of this work, and supported by theoretical calculations, the base case model is extended to include the following two reactions: and considers an update to the thermal lifetime of IOIO (extended model, Supplementary Section 3). Figure 1 shows that HIO 3 and HOI concentrations rapidly increase to exceed 1 × 10 7 molecules per cm 3 (molec cm −3 ) within a few minutes of the onset of I 2 photolysis by green light (grey lines). While zero HIO 3 and zero HOI are predicted by the base case model (current state of the art), the extended model achieves excellent agreement with regard to the measured concentrations and the timing of HIO 3 and HOI formation. The extended model also improves the closure of timing and concentrations measured for OIO, IOIO and I 2 O 4 . Measured HIO 3 concentrations reach a steady state after ~8 min, consistent with the wall-loss lifetime of other sticky molecules 3 measured at CLOUD (Extended Data Fig. 1). HOI continues to accumulate due to a lower effective wall uptake. Notably, the IO radical concentrations closely resemble those in the remote marine boundary layer (compare Supplementary Table 1) and do not exceed 1 pptv (1 pptv = 2.68 × 10 7 molec cm −3 at 273 K and 1 atm pressure). The timing of IO radicals is predicted very well from both the base case and the extended model, reflecting the high level of trust in Article https://doi.org/10.1038/s41557-022-01067-z most pronounced for low pI (<10 5 molec cm −3 s −1 ) and is quantitatively explained by the wall loss of HIO 3 precursors becoming progressively more relevant at lower gas concentrations. We corroborated that HIO 3 formation from I atoms is a multistep process by carrying out an experiment with enhanced stirring (by two fans at the top and bottom of the chamber), thereby decreasing the wall accommodation lifetime of HIO 3 from the standard ~8 min to ~2 min, while holding all other parameters constant. The HIO 3 concentration decreased by more than one order of magnitude, indicating that the HIO 3 suppression exceeds that expected from a change in lifetime alone (Extended Data Fig. 1). The extended model reproduces this superlinear response under the reasonable assumption of efficient reactive uptake of IO radicals on the chamber walls (red dashed line, Fig. 2). Indeed, if the extended model is run while disregarding IO wall loss (blue dashed line, Fig. 2), a constant and high yield of ~20% applies over the full pI range probed.
That HIO 3 formation is first order in pI ( Fig. 2) explains the presence of HIO 3 over remote oceans, where pI is low (Supplementary Table 1) 10,31 . This finding also carries key mechanistic information, in that it is incompatible with the hypothesis that larger I x O y (x ≥ 3) species are HIO 3 precursors 34 at CLOUD. If such I x O y were the precursor, the HIO 3 yield would not be constant, but would increase progressively with pI, and pHIO 3 would follow a higher-order rate law ( Supplementary Fig. 2). This is not observed. We regularly detect I 2 O 2 and I 2 O 4 , in agreement with predictions by the extended model ( Fig. 1 and Extended Data Fig. 3), indicating that there is no fundamental limitation to our analytical capabilities to detect I x O y species. Interestingly, I 2 O 3 is generally not detected, except in experiments that employ extremely high I 2 concentrations (ppbv levels), which can bias reaction pathways to favour the formation of larger I x O y species (Supplementary Table 1 Fig. 4 and Supplementary Fig. 1). This suggests that neither O 3 nor H 2 O are rate-limiting to HIO 3 formation under the conditions probed. The rate-limiting step is the formation of IOIO, which is fully converted into HIO 3 (Extended Data Fig. 4). We observe excellent closure between pHIO 3 and pIOIO during the O 3 ramps, where pIOIO is based on the well-known IO + IO rate coefficients 40 .
At O 3 concentrations below a few ppbv, the chemistry slows down sufficiently that other sinks become relevant for IOIO (for example, wall loss and thermal decomposition), resulting in a slight dependence of the pHIO 3 -to-pIOIO ratio on O 3 . That slight dependence is captured by the extended model (assuming an IOIO wall uptake coefficient γ wall (IOIO) = 1). In contrast, a pronounced O 3 sensitivity would be expected if IO⋅H 2 O or OIO were HIO 3 precursors ( Supplementary  Fig. 1). The absence of an O 3 and H 2 O sensitivity is difficult to reconcile with any mechanism that does not quantitatively convert a single precursor. The comprehensive evidence (Supplementary Table 2 and Supplementary Section 2) strongly supports a rapid and quantitative conversion of IOIO into HIO 3 and HOI.

Quantum chemical calculations
We employed quantum chemical calculations (density functional theory (DFT) methods M062X/aug-cc-pVTZ-PP, followed by coupled-cluster single-point energy corrections; Methods) to explore the reactivity of IOIO with O 3 , H 2 O and other available reactants to form HIO 3 and HOI. IOIO reacts reasonably quickly with O 3 to form HIO 3 , HOI and singlet oxygen via reaction sequences (R1) and (R2). Figure 3 shows the reaction coordinate. The reactions (R1) and (R2) are exothermic and free of prohibitively large barriers. Accurately predicting energies and rate coefficients for iodine is challenging because of the inherent complexity of iodine atoms (atom size, number of electrons and relativistic effects). The strong sensitivity towards varying levels of theory is illustrated by comparing bond dissociation energies (BDEs) and proton affinities for simple iodine oxides where measurements are available ( Table 1). The method used in this study has improved skill in the coupled-cluster part of the calculations, primarily due to a more balanced description of the basis set on iodine and the other atoms (Methods), and is found to reproduce experimental values within ~3 kcal mol −1 (with the exception of the OIO BDE), which translates into approximately one order of magnitude uncertainty in rate constants.
The transition states in Fig. 3 translate into the rate coefficients for reactions (R1) and (R2) at 298 K as shown in Table 1 (for temperature dependencies see Supplementary Fig. 6). Notably, the experimentally derived k 1 ≥ 1.5 × 10 −13 molec −1 cm 3 s −1 is supported within the error margins of theory and maintains the quantitative conversion of IOIO into HIO 3 even at low O 3 concentrations ( Supplementary Fig. 1). Our results led to a reassessment of the thermal lifetime of IOIO, which is predicted to be substantially longer than previously thought (Table 1), consistent with observations of IOIO (Extended Data Fig. 3), and its persistently quantitative conversion into HIO 3 even at extremely low O 3 concentrations at 263 K (Supplementary Fig. 5 and Supplementary Section 3). Reaction (R2) is predicted to proceed with k 2 = 5.7 × 10 −16 molec −1 cm 3 s −1 at 298 K (Table 1 and Supplementary Fig. 6), corresponding to a typical conversion of IOIO 4 into HIO 3 within fractions of a second. Competing pathways of IOIO 4 into other products than HIO 3 were investigated ( Supplementary Fig. 4, Supplementary Table 4 and Supplementary Section 3), but found to be unlikely. The marginal detection of IOIO 4 (Extended Data Fig. 3 and Supplementary Section 2.4) is consistent with a value of k 2 ≈ 2.0 × 10 −16 molec −1 cm 3 s −1 at 263 K. The detection of IOIO 4 at the observed levels suggests that reaction (R2) is enhanced by water reacting with hot IOIO 4 (Supplementary Section 3.3); assuming a lower k 2 from thermalized IOIO 4 leads to IOIO 4 accumulation in the extended model that is not observed. We recommend The HIO 3 production rate pHIO 3 scales in first order with the I atom production rate pI (median (solid line) and 25-75% and 5-95% inter-percentile ranges (dark and light grey shading)). The yield η is substantial (~20%) and near constant for pI larger than 10 5 molec cm −3 s −1 .
At smaller pI, losses of intermediates to chamber walls reduce η. This effect is captured by the model (red line (median)) and is explained by IO radical wall losses (compare blue dashed and red dotted lines (medians)). If larger I x O y clusters were the HIO 3 precursor, a higher-order yield would be expected-this is not consistent with the observations. Article https://doi.org/10.1038/s41557-022-01067-z temperature-dependent rate coefficients for k 1 and k 2 for the development of atmospheric models (Supplementary Section 3). Overall, the theory-predicted rates support the experimentally derived rates within the uncertainty of the calculations.

Atmospheric observations
The laboratory-derived mechanism can explain field measurements of HIO 3 concentrations in the remote free troposphere. We use concurrent measurements of HIO 3 (in situ, NO 3 − -CIMS), IO radicals (near-observatory, MAX-DOAS) and particle surface area measurements at the Maïdo observatory 41 to assess the relevance of CLOUD findings in the real world. The observatory is located in the southern Indian Ocean on Réunion Island at an elevation of 2,200 m, and is frequently exposed to lower free tropospheric air (mornings) and anabatic orographic flows from the ocean (afternoons). The laboratory conditions at CLOUD closely match the conditions at the Maïdo observatory (Supplementary Table 1 and Methods) regarding IO concentrations (single pptv), condensational sink (~10 −3 s −1 ) and temperature (~283 K). Figure 4 shows pHIO 3 in the field and laboratory on a common IO radical concentration axis. pHIO 3 is calculated from HIO 3 concentrations and the condensation sink surface area, assuming a steady state. IO radical concentrations are measured directly at the Maïdo observatory, and taken from the extended model at CLOUD. The solid line shown in Fig. 4 is not a fit to the data; it corresponds to pIOIO at 283 K and serves as a transfer standard to propagate the mechanistic finding of quantitative IOIO conversion into HIO 3 from CLOUD (Extended Data   The ability of our HIO 3 -formation mechanism to predict simultaneous field measurements of HIO 3 and IO radicals in the remote free troposphere is anything but trivial ( Supplementary Fig. 7), and demonstrates the ability to approximate atmospherically relevant experimental conditions at CLOUD. Interestingly, HIO 3 concentrations at Maïdo increase rapidly already under twilight conditions during sunrise ( Supplementary Fig. 7 and Supplementary Section 4). He and colleagues 10 had predicted the efficient formation of iodine oxoacids under cloudy daylight conditions, and Supplementary Fig. 7 provides field evidence in support of the rapid activation of iodine reservoir species into iodine oxoacids in the absence of ultraviolet irradiation.

Atmospheric implications
The mechanism provides a source of HIO 3 that is effective even at low iodine concentrations, and will allow atmospheric models to test HIO 3 field observations. Such model development will also help guide future laboratory experiments and field observations. The near-linear rate law of pHIO 3 in pI also enables HIO 3 formation and subsequent particle formation beyond hotspots at lower iodine concentrations in the background atmosphere 31,42,43 .
The gas-phase formation mechanism of HIO 3 we present here facilitates a missing connection between iodine sources and particle formation in atmospheric models, as illustrated in Fig. 5. The activation of iodine reservoir species (Fig. 5, step 1) liberates iodine radicals, which rapidly form IO radicals and HIO 3 (step 2) via reactions (R1) and (R2). Iodine oxoacid particle formation and growth (step 3) is driven by HIO 3 in most atmospheric environments. Indeed, recent field observations of particle formation events over the remote Arctic Ocean indicate that all of the observed events were driven by HIO 3 (ref. 31 ). I x O y species may also contribute locally in coastal hotspots with extremely high iodine concentrations. Freshly nucleated iodine particles are composed almost entirely of HIO 3 (ref. 10 ); HIO 3 is a strong acid (pK a = 0.8; ref. 44 ) that dissociates to form IO 3 − . IO 3 − is known to undergo reduction reactions that ultimately form more volatile iodine species (for example, HOI, I 2 and IO), which are re-emitted to the gas phase (step 4). Field observations and laboratory experiments show that IO 3 − is reduced via iron redox chemistry, H 2 O 2 , nitrite, photosensitized reactions, photolysis and numerous other species (refs. 25,26 and references therein), with the overall effect of recycling iodine to the gas phase. The HIO 3 formation mechanism thus completes a catalytic iodine reaction cycle, by which a single iodine atom can repeatedly form HIO 3 , driving particle formation. For each HIO 3 molecule produced from I, three O 3 molecules are consumed. The re-emission of reduced iodine species thus constitutes a multiphase reaction cycle that destroys O 3 . That iodine recycling controls the iodine partitioning between the gas and particle phases is corroborated by field measurements of the size-resolved iodine activity in radioactive fallout 45 . Among the primary radioactive elements, 132 Te, 137 Cs and 103 Ru abundances were found to correlate with the aerosol volume distribution, whereas 131 I correlated with the aerosol surface area distribution instead. These empirical observations hint at efficient recycling occurring on timescales of hours to days, consistent with rapid HIO 3 formation. Notably, although the reactive uptake of HOI on aerosols is known to be fast 46 , this reaction de facto removes halides from aerosols to the gas phase. A gas-phase source of HIO 3 adds iodine to particles and, in conjunction with iodine recycling, provides a plausible explanation for the correlation of particulate 131 I with the aerosol surface area distribution at the molecular level. Particulate IO 3 − is the primary reservoir of total (gas and particle) iodine in the stratosphere 22 . Whether HIO 3 forms in the stratosphere-and controls iodine partitioning between the gas and particle phases-deserves further study. The HIO 3 -formation mechanism fills a gap in the representation of the geochemical iodine cycle in current atmospheric models.
Iodine particle formation has heretofore been considered to have only limited global importance 19 . This deserves re-evaluation in light of efficient HIO 3 formation even at low concentrations, the catalytic

Fig. 5 | Simplified gas-phase iodine chemistry in the remote atmosphere.
After activation of iodine reservoirs (step 1), HIO 3 is efficiently formed (step 2) and subsequently nucleates and grows particles extremely efficiently (step 3). Iodate (IO 3 − ) can be reduced and re-emitted to the gas phase (step 4), closing an iodine-catalysed reaction cycle forming particles and destroying O 3 . HIO 3 formation from IOIO links iodine sources and new particle formation even at lower IO concentrations. This mechanism is currently missing from atmospheric models.
Article https://doi.org/10.1038/s41557-022-01067-z role of iodine in particle formation, and the increased global iodine source in recent decades. Iodine particle formation is probably already relevant on global scales today, and will become even more important in view of decreasing global sulfur emissions and increasing iodine emissions in a future climate.

Online content
Any methods, additional references, Nature Research reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at https://doi.org/10.1038/s41557-022-01067-z.

CLOUD experiments
Laboratory experiments were carried out at the CERN CLOUD chamber 3,50 in Geneva, Switzerland as part of the CLOUD12 and CLOUD13 campaigns during 2017 and 2018. The CLOUD chamber is a temperature-controlled, electropolished stainless-steel reaction vessel with a volume of 26.1 m 3 . Experiments were carried out at temperatures of 283 and 263 K. The chamber was operated as a continuous-flow reactor, and ultra-pure N 2 and O 2 at 250-300 l min −1 were continuously replenished at a pressure of 1 atm, resulting in an air exchange time of ~80 min. Two fans at the top and bottom of the chamber established near-homogeneous mixing (mixing time ~2 min). Trace gases were added at the bottom of the chamber. I 2 was produced from sublimating iodine crystals (Sigma-Aldrich, 99.999% purity), and concentrations inside the chamber were varied in the range 0.5 pptv < [I 2 ] < 330 pptv (typically ~8 pptv). O 3 was generated from UV irradiation of dry synthetic air, and the chamber was humidified using ultrapurified water, resulting typically in [O 3 ] = 40 ppbv (range < 1-80 ppbv) and RH = 40% (<3-90%). A typical experiment explored the formation of HIO 3 following the selective photolysis of I 2 using green light (light-emitting diodes (LEDs) centred at 523 nm, I 2 photolysis frequencies j I 2 ≤ 6.5 × 10 −3 s −1 ) in the presence of O 3 and humidity (Fig. 1). Actinic frequencies were spectrally determined using a spectrometer and dedicated iodine actinometry experiments (Supplementary Section 6.3). Actinic fluxes of light sources at variable intensity were monitored during actual experiments by photodiodes. Sensitivity studies during individual experiments followed the response in the HIO 3 concentration to variations in O 3 (for example, Supplementary Fig. 1), chamber wall loss during variations of the fan mixing speed (for example, Extended Data Fig. 1) and by varying selected environmental parameters. The typical duration of individual experiments varied from a few tens of minutes to a few hours, depending on the experimental conditions. I 2 was measured by closed-path CE-DOAS 51 using the unique ro-vibronic absorption bands between 508 and 554 nm. CE-DOAS is inherently calibrated from knowledge of the absorption cross-section. The I 2 limit of detection is 8 pptv for an integration time of 10 min. Median I 2 concentrations were below 8 pptv during most experiments, but elevated to up to 1.7 ppbv to calibrate the Br − -MION-CIMS, which also provides precise I 2 measurements at low concentrations. The Br − -MION-CIMS is composed of an atmospheric-pressure interfacetime of flight mass spectrometer (APi-TOF) coupled to a chemical ionization unit, using dibromomethane (CH 2 Br 2 ) as the reagent gas. The CH 2 Br 2 is fed into the sheath flow of the inlet and illuminated by a soft X-ray source. The produced bromide anions are directed into the sample flow by a negative electric field, and cluster with neutral molecules (I 2 ) in the sample air. The overall uncertainty of the resulting I 2 time series is estimated to be better than 30% 52 . The I 2 constraint imposed to the model assimilates the lower bound of the measured I 2 time series (within the 30% uncertainty), which results in the best closure between measured and predicted HIO 3 . Iodine radical production rates, pI, are calculated from the photolysis rate of I 2 concentrations. HIO 3 was measured by a NO 3 − -CIMS system comprising an APi-TOF coupled to a chemical ionization unit that uses nitric acid as the reagent gas. It is used extensively for detecting H 2 SO 4 , highly oxygenated organic molecules and HIO 3 . Details of the instrument used in the present study are provided in ref. 53 . The NO 3 − -CIMS has an ion filter integrated into its sampling line to avoid confusion with ions and charged clusters from the CLOUD chamber. It thus measures only neutral molecules and clusters in CLOUD. The uncertainty of the HIO 3 measurement is estimated to be 50%.
The characteristic time for the deposition of sticky molecules to the chamber walls is 440 s with standard mixing by the fans (Extended Data Fig. 1), as characterized via H 2 SO 4 loss rates. The loss to walls is the well-defined dominant sink of HIO 3 . Experiments that formed a large particle surface area (measured by nSEMS, nano-SMPS or long-SMPS) competitive to chamber wall loss were discarded in this study to avoid introducing uncertainty due to the other less-well-defined sinks for HIO 3 and other iodine species. The HIO 3 production rates were calculated from measured concentrations under the assumption of a steady state. Periods with rapid changes of HIO 3 concentration are not considered in, for example, Fig. 2.

Box modelling
The photochemical box model builds on the framework described in refs. [22][23][24] and represents state-of-the-art iodine chemistry and HO x chemistry 25,48 . Here, the model is extended by the chamber auxiliary mechanism, which includes losses of gases to the chamber walls and to particles, losses by dilution and the actinic fluxes of the chamber lights. IO, OIO, IOIO, I 2 O 3 , I 2 O 4 , HI and HIO 3 are assumed to be lost to the walls with the same rate constant as H 2 SO 4 , the prototypical sticky molecule. Accommodation of molecules to the CLOUD chamber walls is limited by transport, not by diffusion. Thus, the effective wall accommodation coefficient of molecules (most iodine species are reasonably sticky [54][55][56] , with accommodation coefficients of multiple tens of percent or even unity) used in the model is enhanced over the accommodation coefficient for individual collisions 57 . Extended Data Fig. 1 provides evidence for the efficient loss of iodine species to the chamber walls. The model is constrained by measurements of I 2 , O 3 and H 2 O, photolysis frequencies (I 2 , IO, OIO, HOI, I 2 O 2 , I 2 O 3 and I 2 O 4 ), temperature and the aforementioned loss mechanisms. HOI is both lost to the walls and produced on the chamber walls through heterogeneous chemistry 14 , which also proceeds in dark conditions. This study did not make an attempt to describe the uptake and release of HOI at the molecular level. An empirical uptake efficiency of 25%, relative to H 2 SO 4 , establishes closure in regard to the temporal evolution and concentrations of HOI (Extended Data Fig. 3). See Supplementary Section 6 for more details.

Quantum chemical calculations
For the reactants, intermediates, transition states and products in Fig.  3 with multiple possible conformers, a systematic conformer sampling was carried out using the MMFF method in the Spartan '18 program. The conformer sampling algorithm in Spartan allows for pre-optimization and the elimination of duplicate structures, which is computationally more efficient than other conformer sampling approaches like MS-TOR. Geometry optimization and frequencies were calculated using DFT methods (M062X/aug-cc-pVTZ-PP) with the ultrafine grid, followed by coupled-cluster single-point energy corrections at the CCSD(T)// CBS/aug-cc-pV(T,Q)Z-PP level of theory. Iodine pseudopotentials were taken from the Environmental Molecular Sciences Laboratory (EMSL) basis set library 58,59 . The accuracy of the final energetics is critical to reliably estimate the rate of conversion of IOIO 4 to HIO 3 , which was simulated using the master equation solver for multi-energy well reactions (MESMER) program.
Final product fractions were calculated using the MESMER program 60 . In the simulation, IOIO + O 3 was modelled to directly lead to IOIO 4 using the MesmerILT method with a pre-exponential value of 2.7 × 10 −14 molec −1 cm 3 s −1 , which corresponds to the transition-state-theory-derived bimolecular rate. The unimolecular isomerization reactions of intermediate complexes were treated using the SimpleRRKM method with Eckart tunnelling. The Mesmer-ILT method with a pre-exponential value of 2.0 × 10 −10 molec −1 cm 3 s −1 was used for the bimolecular reaction of IOIO 4 with H 2 O, with the latter set as the excess reactant with a defined initial concentration. All intermediate complexes were assigned as 'modelled' with Lennard-Jones potentials of σ = 6.5 Å and ϵ = 300 K. These are identical to those used by Galvez and colleagues for their iodine systems 61 . MESMER uses the exponential down (ΔE down ) model for simulating the collisional energy transfer; a value of 225 cm −1 was used in the simulations, which is within the 175-275 cm −1 range recommended by MESMER for nitrogen bath gas. Article https://doi.org/10.1038/s41557-022-01067-z The energetics of ozonolysis reactions are difficult to calculate accurately using single-reference methods. The inherent uncertainties are probably even more pronounced for complex iodine-containing systems. Although no experimental values are available for the gas-phase ozonolysis reaction of iodine systems, proton affinities (PAs) and BDEs of simple molecules such as HI, HOI, IO and OIO are available. Table 1 shows that the differences between the literature values and the theoretical values calculated in this work are less than 3 kcal mol −1 (with the exception of the BDE of OIO). Previous quantum chemical calculations on iodine oxide reactions 34,47 are included in Table 1 for comparison, highlighting the improved skill of the method used in this study in the coupled-cluster part of the calculation, as benchmarked through comparisons with experimental PAs and BDEs. Previous studies used a double-zeta basis set (LanL2DZ) for I atoms, but a larger triple-zeta basis set (aug-cc-pVTZ) for O and H atoms, leading to substantial overestimation of the exothermicity of bond-forming reactions involving iodine. Our approach uses a large basis set for all atoms, substantially reducing this overestimation.

Field measurements
The field data were collected during an intensive operating period in April 2018 at the Maïdo observatory 41 , Réunion island, southern Indian Ocean (21° S, 55° E). The observatory is located at 2,200 m above sea level and is frequently exposed to lower free tropospheric air (mornings) and flows from the ocean (afternoons). Near-instrument altitude volume mixing ratios of IO radicals were retrieved from CU MAX-DOAS scattered sunlight observations. The retrieval 62,63 leverages the high sensitivity of the limb viewing geometry to the atmospheric layers nearest to the instrument altitude, allowing for the parameterization of aerosol effects on the observed light path. Gas-phase HIO 3 was measured directly by a NO 3 − -CIMS system using a methodology similar to that used in the laboratory experiments. The instrument was calibrated in the field in its actual field campaign sampling configuration by in situ-produced H 2 SO 4 , which resulted in a calibration factor of c = 1.7 × 10 10 molec cm −3 . This same calibration factor was used for all quantifications, so the determined concentrations here represent lower limits. The uncertainty of the determined [HIO 3 ] was estimated similarly as [H 2 SO 4 ], at −50% and +100% following the work in ref. 64 . Particles were size-selected by a differential mobility particle sizer and counted with a condensation particle counter to determine the available particle surface area. The box modelling constraints are described in Supplementary Section 4.1. TUV calculated spectral fluxes 65 were used to determine the photolysis frequencies of individual iodine species.

Data availability
The output files of quantum chemical calculations and a MESMER input file are provided in the public data repository at https://doi. org/10.5281/zenodo.6637910. The box model supporting the findings of this study is described in detail in the Supplementary Information (Supplementary Tables A5-A9 and text). Source data are provided with this paper. concentrations recover by a factor 12. The superlinear response is evidence for a reasonably long-lived precursor (that is, IO) that gets lost to the chamber walls. At 20:25 UTC, light is turned off, HIO 3 production stops, and the HIO 3 concentration is efficiently lost to the chamber walls. The model reproduces the observed behaviour if IO is considered to efficiently get lost to the chamber wall.