Photochemical release of iodine from snow has been suggested as a source of reactive iodine to the Arctic atmosphere, however understanding of the underlying mechanism and potential source strength is hindered by a lack of measurements of iodine concentration and speciation in snow. Moreover, the origin of snow iodine is also unknown. Here, we report iodine speciation measurements in Arctic snow on sea ice at a range of snow depths from 177 samples, representing 80 sampling events, from December 2019 to October 2020 collected during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. We demonstrate that while there appears to be a source of iodine, in particular iodate, to the base of the snow over first year ice, this does not influence iodine concentration in the surface snow. There is instead evidence of a top-down source of iodine, potentially from iodine-enriched marine aerosol, as well as some evidence for episodic influx of iodate with dust. The potential for photochemical release of molecular iodine (I2) from iodide in surface snow was investigated, and it was demonstrated that this could provide an iodine emission flux to the Arctic atmosphere comparable to oceanic fluxes. Knowledge of the prevalence and speciation of iodine in Arctic snow will contribute to better understanding of its contribution to observed concentrations of polar iodine oxide (IO), and hence its contribution to the depletion of tropospheric ozone in the Arctic.

Iodine at the ocean's surface impacts climate and health by removing ozone (O3) from the troposphere both directly via ozone deposition to seawater and indirectly via the formation of iodine gases that are released into the atmosphere. Here we present a new box model of the ocean surface microlayer that couples oceanic O3 dry deposition to inorganic chemistry to predict inorganic iodine emissions. This model builds on the previous work of Carpenter et al. (2013), improving both chemical and physical processes. This new box model predicts iodide depletion in the top few micrometres of the ocean surface due to rapid chemical loss to ozone competing with replenishment from underlying water. From this box model, we produce parameterized equations for HOI and I2 emissions, which are implemented into the global chemical transport model GEOS-Chem along with an updated sea surface iodide climatology. Compared to the previous model, inorganic iodine emissions from some tropical waters decrease by as much as half, while higher-latitude emissions increase by a factor of ≫10. With these large local changes, global total inorganic iodine emissions increased by ∼49 % (2.99 to 4.48 Tg) compared to the previous parameterization. This results in a negligible change in average tropospheric OH (<0.2 %) and tropospheric methane lifetime (<0.2 %). The annual mean tropospheric O3 burden decreases (−1.5 % to 325 Tg); however, higher-latitude surface O3 concentrations decrease by as much as 20 %.

The reaction between ozone and iodide is one of the main drivers of tropospheric ozone deposition to the ocean due to the ubiquitous presence of iodide in the ocean surface and its rapid reaction with ozone. Despite the importance of this sea surface reaction for tropospheric ozone deposition and also as the major source of atmospheric iodine, there is uncertainty in its rate and dependence on aqueous-phase temperature. In this work, the kinetics of the heterogeneous second-order reaction between ozone and iodide are investigated using conditions applicable to coupled ocean–atmosphere systems (1 × 10−7–1 × 10−5 M iodide; 40 ppb ozone; 288–303 K; 15.0 psi). The determined Arrhenius parameters of A = 5.4 ± 23.0 × 1010 M-1s-1 and Ea = 7.0 ± 10.5 kJ mol−1 show that the reaction has a negligible positive temperature dependence, which could be weakly negative within errors. This is in contrast to a previous study that found a strong positive activation energy and a pre-exponential factor many orders of magnitude greater than determined here. The re-measured kinetics of ozone and iodide were used to constrain a state-of-the-art sea surface microlayer (SML) model. The model replicated results from a previous laboratory study of the temperature dependence of hypoiodous acid (HOI) and molecular iodine (I2) emissions from an ozone-oxidised iodide solution. This work has significance for the global modelling of the dry deposition of ozone to the ocean and the subsequent emissions of iodine-containing species, thus improving the understanding of the feedback between natural halogens, air quality and climate change.

Tropospheric reactive gaseous chlorine (Cl y ) impacts the atmosphere's oxidation capacity with implications for chemically reduced gases such as methane. Here we use Greenland ice‐core records of chlorine, sodium, and acidity, and global model simulations to show how tropospheric Cl y has been impacted by anthropogenic emissions since the 1940s. We show that anthropogenic contribution of nonsea‐salt chlorine significantly influenced total chlorine and its trends after the 1940s. The modeled regional 170% Cl y increase from preindustrial to the 1970s was driven by acid displacement from sea‐salt‐aerosol, direct emission of hydrochloric acid (HCl) from combustion, and chemical reactions driven by anthropogenic nitrogen oxide (NO x ) emissions. Since the 1970s, the modeled 6% Cl y decrease was caused mainly by reduced anthropogenic HCl emissions from air pollution mitigation policies. Our findings suggest that anthropogenic emissions of acidic gases and their emission control strategies have substantial impacts on Cl y with implications for tropospheric oxidants, methane, and mercury.

Abstract. A fast response (10 Hz) chemiluminescence detector for ozone (O3) was used to determine O3 fluxes using the eddy covariance technique at the Penlee Point Atmospheric Observatory on the south coast of the UK during April and May 2018. The median O3 flux was −0.132 mg m−2 h−1 (0.018 ppbv m s−1) corresponding to a deposition velocity of 0.037 cm s−1 (interquartile range 0.017–0.065 cm s−1) – similar to the higher values previously reported for open ocean flux measurements, but not as high as some other coastal results. Eddy covariance footprint analysis of the site indicates that the flux footprint was predominantly over water (> 96 %), varying slightly with tide. At moderate-to-high wind speeds, ozone deposition increased with wind speed, and showed a linear dependence with friction velocity of comparable magnitude to predictions from the one-layer model of (Fairall et al., 2007). Deposition was also elevated at very low wind speeds, most likely because the footprint contracted to include a greater land contribution in these conditions.

A fast-response (10 Hz) chemiluminescence detector for ozone (O3) was used to determine O3 fluxes using the eddy covariance technique at the Penlee Point Atmospheric Observatory (PPAO) on the south coast of the UK during April and May 2018. The median O3 flux was −0.132 mg m−2 h−1 (0.018 ppbv m s−1), corresponding to a deposition velocity of 0.037 cm s−1 (interquartile range 0.017–0.065 cm s−1) – similar to the higher values previously reported for open-ocean flux measurements but not as high as some other coastal results. We demonstrate that a typical single flux observation was above the 2σ limit of detection but had considerable uncertainty. The median 2σ uncertainty of deposition velocity was 0.031 cm s−1 for each 20 min period, which reduces with the square root of the sample size. Eddy covariance footprint analysis of the site indicates that the flux footprint was predominantly over water (> 96 %), varying with atmospheric stability and, to a lesser extent, with the tide. At very low wind speeds when the atmosphere was typically unstable, the observed ozone deposition velocity was elevated, most likely because the footprint contracted to include a greater land contribution in these conditions. At moderate to high wind speeds when atmospheric stability was near-neutral, the ozone deposition velocity increased with wind speed and showed a linear dependence with friction velocity. This observed dependence on friction velocity (and therefore also wind speed) is consistent with the predictions from the one-layer model of Fairall et al. (2007), which parameterises the oceanic deposition of ozone from the fundamental conservation equation, accounting for both ocean turbulence and near-surface chemical destruction, while assuming that chemical O3 destruction by iodide is distributed over depth. In contrast to our observations, the deposition velocity predicted by the recently developed two-layer model of Luhar et al. (2018) (which considers iodide reactivity in both layers but with molecular diffusivity dominating over turbulent diffusivity in the first layer) shows no major dependence of deposition velocity on wind speed and underestimates the measured deposition velocities. These results call for further investigation into the mechanisms and control of oceanic O3 deposition.

The deposition of ozone to seawater is an important ozone sink. Despite constituting as much as a third of the total ozone deposition, it receives significantly less attention than the deposition to terrestrial ecosystems. Models have typically calculated the deposition rate based on a resistance-in-series model with a uniform waterside resistance. This leads to models having an essentially uniform deposition velocity of approximately 0.05 cm s−1 to seawater, which is significantly higher than the limited observational dataset. Following from Luhar et al. (2018) we include a representation of the oceanic deposition of ozone in the GEOS-Chem model of atmospheric chemistry and transport based on its reaction with sea-surface iodide. The updated scheme halves the calculated annual area-weighted mean deposition velocity to water from 0.0464 cm s−1 (25th and 75th percentiles of 0.0461 cm s−1 and 0.0471 cm s−1 respectively) to 0.0231 cm s−1 (25th and 75th percentiles of 0.0121 cm s−1 and 0.0303 cm s−1 respectively). The calculated ozone deposition velocity varies from 0.009 cm s−1 in polar waters to 0.040 cm s−1 at the tropics. This improves comparisons to observations. The variability is driven mainly by the temperature-dependent rate constant for the reaction between iodide and ozone, the temperature dependence of the solubility, and variations in the ocean iodide concentration. The calculated annual deposition flux of ozone to the ocean is reduced from 222 to 122 Tg yr−1, and overall deposition of ozone to all surface types reduces from 862 to 758 Tg yr−1. Tropospheric ozone burdens and global mean OH increase from 324 to 328 Tg, and from 1.17×106 to 1.18×106 molec.cm-3, respectively. A total of 34 % of surface grid boxes experience a 10 % or greater increase in ozone concentration. Comparisons between observations of surface ozone and the model are improved with the new parameterization notably around the Southern Ocean. Process-level representation of oceanic deposition of ozone thus appears essential for representing the concentration of surface ozone over the planet.

A fast-growing area of research is the development of low-cost sensors for measuring air pollutants. The affordability and size of low-cost particle sensors makes them an attractive option for use in experiments requiring a number of instruments such as high-density spatial mapping. However, for these low-cost sensors to be useful for these types of studies their accuracy and precision need to be quantified. We evaluated the Alphasense OPC-N2, a promising low-cost miniature optical particle counter, for monitoring ambient airborne particles at typical urban background sites in the UK. The precision of the OPC-N2 was assessed by co-locating 14 instruments at a site to investigate the variation in measured concentrations. Comparison to two different reference optical particle counters as well as a TEOM-FDMS enabled the accuracy of the OPC-N2 to be evaluated. Comparison of the OPC-N2 to the reference optical instruments shows some limitations for measuring mass concentrations of PM1, PM2.5 and PM10. The OPC-N2 demonstrated a significant positive artefact in measured particle mass during times of high ambient RH (> 85 %) and a calibration factor was developed based upon κ-Köhler theory, using average bulk particle aerosol hygroscopicity. Application of this RH correction factor resulted in the OPC-N2 measurements being within 33 % of the TEOM-FDMS, comparable to the agreement between a reference optical particle counter and the TEOM-FDMS (20 %). Inter-unit precision for the 14 OPC-N2 sensors of 22 ± 13 % for PM10 mass concentrations was observed. Overall, the OPC-N2 was found to accurately measure ambient airborne particle mass concentration provided they are (i) correctly calibrated and (ii) corrected for ambient RH. The level of precision demonstrated between multiple OPC-N2s suggests that they would be suitable devices for applications where the spatial variability in particle concentration was to be determined.

13 A fast growing area of research is the development of low-cost sensors for measuring air 14 pollutants. The affordability and size of low-cost particle sensors makes them an attractive 15 option for use in experiments requiring a number of instruments such as high density spatial 16 mapping. However, for these low-cost sensors to be useful for these types of studies their 17 accuracy and precision needs to be quantified. We evaluated the Alphasense OPC-N2, a 18 promising low-cost miniature optical particle counter, for monitoring ambient airborne 19 particles at typical urban background sites in the UK. The precision of the OPC-N2 was 20 assessed by co-locating 14 instruments at a site to investigate the variation in measured 21 concentrations. Comparison to two different reference optical particle counters as well as a 22 TEOM-FDMS enabled the accuracy of the OPC-N2 to be evaluated. Comparison of the OPC23 N2 to the reference optical instruments demonstrated reasonable agreement for the measured 24 mass concentrations of PM1, PM2.5 and PM10. However, the OPC-N2 demonstrated a significant 25 positive artefact in measured particle mass during times of high ambient RH (>85%) and a 26 calibration factor was developed based upon-Kohler theory, using average bulk particle 27 aerosol hygroscopicity. Application of this RH correction factor resulted in the OPC-N2 28 measurements being within 33% of the TEOM-FDMS, comparable to the agreement between 29 a reference optical particle counter and the TEOM-FDMS (20%). Inter-unit precision for the 30 14 OPC-N2 sensors of 22±13% for PM10 mass concentrations was observed. Overall, the OPC31