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Measurements from actinic flux spectroradiometers on board the NASA DC-8 during the Atmospheric Tomography (ATom) mission provide an extensive set of statistics on how clouds alter photolysis rates (J values) throughout the remote Pacific and Atlantic Ocean basins. J values control tropospheric ozone and methane abundances, and thus clouds have been included for more than three decades in tropospheric chemistry modeling. ATom made four profiling circumnavigations of the troposphere capturing each of the seasons during 2016-2018. This work examines J values from the Pacific Ocean flights of the first deployment, but publishes the complete Atom-1 data set (29 July to 23 August 2016). We compare the observed J values (every 3s along flight track) with those calculated by nine global chemistry-climate/transport models (globally gridded, hourly, for a mid-August day). To compare these disparate data sets, we build a commensurate statistical picture of the impact of clouds on J values using the ratio of J-cloudy (standard, sometimes cloudy conditions) to J-clear (artificially cleared of clouds). The range of modeled cloud effects is inconsistently large but they fall into two distinct classes: (1) models with large cloud effects showing mostly enhanced J values aloft and or diminished at the surface and (2) models with small effects having nearly clear-sky J values much of the time. The ATom-1 measurements generally favor large cloud effects but are not precise or robust enough to point out the best cloud-modeling approach. The models here have resolutions of 50-200 km and thus reduce the occurrence of clear sky when averaging over grid cells. In situ measurements also average scattered sunlight over a mixed cloud field, but only out to scales of tens of kilometers. A primary uncertainty remains in the role of clouds in chemistry, in particular, how models average over cloud fields, and how such averages can simulate measurements.

Oxidation of biogenic volatile organic compounds (BVOC) by the nitrate radical (NO3) represents one of the important interactions between anthropogenic emissions related to combustion and natural emissions from the biosphere. This interaction has been recognized for more than 3 decades, during which time a large body of research has emerged from laboratory, field, and modeling studies. NO3-BVOC reactions influence air quality, climate and visibility through regional and global budgets for reactive nitrogen (particularly organic nitrates), ozone, and organic aerosol. Despite its long history of research and the significance of this topic in atmospheric chemistry, a number of important uncertainties remain. These include an incomplete understanding of the rates, mechanisms, and organic aerosol yields for NO3-BVOC reactions, lack of constraints on the role of heterogeneous oxidative processes associated with the NO3 radical, the difficulty of characterizing the spatial distributions of BVOC and NO3 within the poorly mixed nocturnal atmosphere, and the challenge of constructing appropriate boundary layer schemes and non-photochemical mechanisms for use in state-of-the-art chemical transport and chemistry-climate models. This review is the result of a workshop of the same title held at the Georgia Institute of Technology in June 2015. The first half of the review summarizes the current literature on NO3-BVOC chemistry, with a particular focus on recent advances in instrumentation and models, and in organic nitrate and secondary organic aerosol (SOA) formation chemistry. Building on this current understanding, the second half of the review outlines impacts of NO3-BVOC chemistry on air quality and climate, and suggests critical research needs to better constrain this interaction to improve the predictive capabilities of atmospheric models.

The Amazon Basin plays key role in atmospheric chemistry, biodiversity and climate change. In this study we applied nanoelectrospray (nanoESI) ultra-high-resolution mass spectrometry (UHRMS) for the analysis of the organic fraction of PM2.5 aerosol samples collected during dry and wet seasons at a site in central Amazonia receiving background air masses, biomass burning and urban pollution. Comprehensive mass spectral data evaluation methods (e.g. Kendrick mass defect, Van Krevelen diagrams, carbon oxidation state and aromaticity equivalent) were used to identify compound classes and mass distributions of the detected species. Nitrogen-and/or sulfur-containing organic species contributed up to 60% of the total identified number of formulae. A large number of molecular formulae in organic aerosol (OA) were attributed to later-generation nitrogen-and sulfur-containing oxidation products, suggesting that OA composition is affected by biomass burning and other, potentially anthropogenic, sources. Isoprene-derived organosulfate (IEPOX-OS) was found to be the most dominant ion in most of the analysed samples and strongly followed the concentration trends of the gas-phase anthropogenic tracers confirming its mixed anthropogenic-biogenic origin. The presence of oxidised aromatic and nitro-aromatic compounds in the samples suggested a strong influence from biomass burning especially during the dry period. Aerosol samples from the dry period and under enhanced biomass burning conditions contained a large number of molecules with high carbon oxidation state and an increased number of aromatic compounds compared to that from the wet period. The results of this work demonstrate that the studied site is influenced not only by biogenic emissions from the forest but also by biomass burning and potentially other anthropogenic emissions from the neighbouring urban environments.

Dimethyl sulfide (DMS) is the largest source of natural sulfur in the atmosphere and undergoes oxidation reactions resulting in gas‐to‐particle conversion to form sulfate aerosol. Climate models typically use independent chemical schemes to simulate these processes, however, the sensitivity of sulfate aerosol to the schemes used by CMIP6 models has not been evaluated. Current climate models offer oversimplified DMS oxidation pathways, adding to the ambiguity surrounding the global sulfur burden. Here, we implemented seven DMS and sulfate chemistry schemes, six of which are from CMIP6 models, in an atmosphere‐only Earth system model. A large spread in aerosol optical depth (AOD) is simulated (0.077), almost twice the magnitude of the pre‐industrial to present‐day increase in AOD. Differences are largely driven by the inclusion of the nighttime DMS oxidation reaction with NO3, and in the number of aqueous phase sulfate reactions. Our analysis identifies the importance of DMS‐sulfate chemistry for simulating aerosols. We suggest that optimizing DMS/sulfur chemistry schemes is crucial for the accurate simulation of sulfate aerosols. Plain Language Summary: Dimethyl sulfide (DMS) is a sulfur‐bearing gas predominantly emitted from marine biological activity. DMS is the largest natural contributor to the global sulfur cycle, but its contribution is highly uncertain. Representing the complex chemical conversion of DMS to form natural sulfur atmospheric particles accurately in Earth System Models is difficult. Complex atmospheric chemistry is expensive to implement, therefore simplistic approaches to represent the chemistry are used. Here we examine the variability between different chemistry schemes. To achieve this, we employ a state‐of‐the‐art Earth System Model to compare seven simulations with differing sulfur‐related chemical reactions. We show that sulfate chemistry contributes to large uncertainties in aerosol and cloud formation. This work underscores the need to improve sulfur chemistry to improve the accuracy of cloud and aerosol projections in a warming world. Key Points: The simulated spread in aerosol optical depth and cloud droplet number concentration is more than twice as large as the change from pre‐industrial to present‐daySimulations with similar Dimethyl sulfide burdens have very different sulfate burdens driven by the different sulfate mechanisms/oxidation pathwaysConstraining the chemistry of atmospheric sulfur is critical to constrain aerosol‐cloud interactions [ABSTRACT FROM AUTHOR]

The North Atlantic Climate System: Integrated Study (ACSIS) was a large multidisciplinary research programme funded by the United Kingdom's Natural Environment Research Council (NERC). ACSIS ran from 2016-22 and brought together around 80 scientists from seven leading UK-based environmental research institutes to deliver major advances in understanding North Atlantic climate variability and extremes. Here we present an overview of the data generated by the ACSIS programme. The datasets cover the full North Atlantic System comprising: the North Atlantic Ocean, the atmosphere above it including its composition, Arctic Sea Ice and the Greenland Ice Sheet. Atmospheric composition datasets include measurements from 7 aircraft campaigns (between 3 and 10 flights each, 0-10 km altitude range) in the north eastern Atlantic (~40° W-5° E,~15° N-55° N) made at intervals of from 6 months to 2 years between February 2017 and may 2022. The flights measured chemical species (including greenhouse gases, ozone precursors and VOCs) and aerosols (organic, SO4, NH4, NO3, and nss-Cl) (https://dx.doi.org/10.5285/6285564c34a246fc9ba5ce053d85e5e7 (FAAM et al. (2024)). Ground based stations at the Cape Verde Atmospheric Observatory (CVAO), Penlee Point Atmospheric Observatory (PPAO) and Plymouth Marine Laboratory (PML) recorded ozone, ozone precursors, halocarbons, as well as greenhouse gases (CO2, methane), SO2 and photolysis rates. (CVAO, http://catalogue.ceda.ac.uk/uuid/81693aad69409100b1b9a247b9ae75d5, National Centre for Atmospheric Science et al. (2014)), O3 and CH4 (PPAO, https://catalogue.ceda.ac.uk/uuid/8f1ff8ea77534e08b03983685990a9b0 (Plymouth Marine Laboratory and Yang (2024)) and aerosols (PML, https://dx.doi.org/10.5285/e74491c96ef24df29a9342a3d57b5939, Smyth (2024)). Complementary model simulations of atmospheric composition were performed with the UK Earth System Model, UKESM1, for the period 1982 to 2020 using CMIP6 historical forcing up to 2014 and SSP3-7.0 scenario from 2015-2020. Model temperature and winds were relaxed towards ERA reanalysis. Monthly mean model data for ozone, NO, NO2, CO, methane, stratospheric ozone tracers and 30 regionally emitted tracers are available to download (https://data.ceda.ac.uk/badc/acsis/UKESM1-hindcasts, Abraham (2024)). ACSIS also generated new ocean heat content diagnostics https://doi.org/10/g6wm, https://doi.org/10/g8g2, Moat et al. (2021a-b) and gridded temperature and salinity based on objectively mapped Argo measurements https://doi.org/10.5285/fe8e524d-7f04-41f3-e053-6c86abc04d51 (King (2023). An ensemble of atmosphere-forced global ocean-sea ice simulations using the NEMO-CICE model was performed with horizontal resolutions of 1/4° and 1/12° covering the period 1958-2020 using several different atmosphere reanalysis based surface forcing datasets, supplemented by additional global simulations and standalone sea ice model simulations with advanced sea ice physics using the CICE model (http://catalogue.ceda.ac.uk/uuid/770a885a8bc34d51ad71e87ef346d6a8, Megann et al. (2021e). Output is stored as monthly averages and includes 3D potential temperature, salinity, zonal, meridional and vertical velocity; 2D sea surface height, mixed layer depth, surface heat and freshwater fluxes, ice concentration and thickness and a wide variety of other variables. In addition to the data presented here we provide a brief overview of several other datasets that were generated during ACSIS which have been described previously in the literature. [ABSTRACT FROM AUTHOR]

The biogeochemical formation of dimethyl sulfide (DMS) from the Southern Ocean is complex, dynamic, and driven by physical, chemical, and biological processes. Such processes, produced by marine biogenic activity, are the dominant source of sulfate aerosol over the Southern Ocean. Using an atmosphere-only configuration of the United Kingdom Earth System Model (UKESM1-AMIP), we performed eight 10-year simulations for the recent past (2009–2018) during austral summer. We tested the sensitivity of atmospheric DMS to four oceanic DMS datasets and three DMS transfer velocity parameterizations. One oceanic DMS dataset was developed here from satellite chlorophyll a. We find that the choice of oceanic DMS dataset has a larger influence on atmospheric DMS than the choice of DMS transfer velocity. Simulations with linear transfer velocity parameterizations show a more accurate representation of atmospheric DMS concentration than those using quadratic relationships. This work highlights that the oceanic DMS and DMS transfer velocity parameterizations currently used in climate models are poorly constrained for the Southern Ocean region. Simulations using oceanic DMS derived from satellite chlorophyll a data, and when combined with a recently developed linear transfer velocity parameterization for DMS, show better spatial variability than the UKESM1 configuration. We also demonstrate that capturing large-scale spatial variability can be more important than large-scale interannual variability. We recommend that models use a DMS transfer velocity parameterization that was developed specifically for DMS and improvements to oceanic DMS spatial variability. Such improvements may provide a more accurate process-based representation of oceanic and atmospheric DMS, and therefore sulfate aerosol, in the Southern Ocean region. [ABSTRACT FROM AUTHOR]

Dimethyl sulfide (DMS) is an important trace gas emitted from the ocean. The oxidation of DMS has long been recognised as being important for global climate through the role DMS plays in setting the sulfate aerosol background in the troposphere. However, the mechanisms in which DMS is oxidised are very complex and have proved elusive to accurately determine in spite of decades of research. As a result the representation of DMS oxidation in global chemistry–climate models is often greatly simplified. Recent field observations and laboratory and ab initio studies have prompted renewed efforts in understanding the DMS oxidation mechanism, with implications for constraining the uncertainty in the oxidation mechanism of DMS as incorporated in global chemistry–climate models. Here we build on recent evidence and develop a new DMS mechanism for inclusion in the UK Chemistry Aerosol (UKCA) chemistry–climate model. We compare our new mechanism (CS2-HPMTF) to a number of existing mechanisms used in UKCA (including the highly simplified three-reactions–two-species mechanism used in CMIP6 studies with the model) and to a range of recently developed mechanisms reported in the literature through a series of global and box model experiments. Global model runs with the new mechanism enable us to simulate the global distribution of hydroperoxylmethyl thioformate (HPMTF), which we calculate to have a burden of 2.6–26 Gg S (in good agreement with the literature range of 0.7–18 Gg S). We show that the sinks of HPMTF dominate uncertainty in the budget, not the rate of the isomerisation reaction forming it and that, based on the observed DMS / HPMTF ratio from the global surveys during the NASA Atmospheric Tomography mission (ATom), rapid cloud uptake of HPMTF worsens the model–observation comparison. Our box model experiments highlight that there is significant variance in simulated secondary oxidation products from DMS across mechanisms used in the literature, with significant divergence in the sensitivity of the rates of formation of these products to temperature exhibited; especially for methane sulfonic acid (MSA). Our global model studies show that our updated DMS scheme performs better than the current scheme used in UKCA when compared against a suite of surface and aircraft observations. However, sensitivity studies underscore the need for further laboratory and observational constraints. In particular our results suggest that as a priority long-term DMS observations be made to better constrain the highly uncertain inputs into the system and that laboratory studies be performed that address (1) the uptake of HPMTF onto aerosol surfaces and the products of this reaction and (2) the kinetics and products of the following reactions: CH 3 SO 3 decomposition, CH 3 S + O 2 , CH 3 SOO decomposition, and CH 3 SO + O 3. [ABSTRACT FROM AUTHOR]

Hydrogen is expected to play a key role in the global energy transition to net zero emissions in many scenarios. However, fugitive emissions of hydrogen into the atmosphere during its production, storage, distribution and use could reduce the climate benefit and also have implications for air quality. Here, we explore the atmospheric composition and climate impacts of increases in atmospheric hydrogen abundance using the UK Earth System Model (UKESM1) chemistry–climate model. Increases in hydrogen result in increases in methane, tropospheric ozone and stratospheric water vapour, resulting in a positive radiative forcing. However, some of the impacts of hydrogen leakage are partially offset by potential reductions in emissions of methane, carbon monoxide, nitrogen oxides and volatile organic compounds from the consumption of fossil fuels. We derive a refined methodology for determining indirect global warming potentials (GWPs) from parameters derived from steady-state simulations, which is applicable to both shorter-lived species and those with intermediate and longer lifetimes, such as hydrogen. Using this methodology, we determine a 100-year global warming potential for hydrogen of 12 ± 6. Based on this GWP and hydrogen leakage rates of 1 % and 10 %, we find that hydrogen leakage offsets approximately 0.4 % and 4 % respectively of total equivalent CO 2 emission reductions in our global hydrogen economy scenario. To maximise the benefit of hydrogen as an energy source, emissions associated with hydrogen leakage and emissions of the ozone precursor gases need to be minimised. [ABSTRACT FROM AUTHOR]

Understanding dimethyl sulfide (DMS) oxidation can help us constrain its contribution to Earth's radiative balance. Following the discovery of hydroperoxymethyl thioformate (HPMTF) as a DMS oxidation product, a range of new experimental chamber studies have since improved our knowledge of the oxidation mechanism of DMS and delivered detailed chemical mechanisms. However, these mechanisms have not undergone formal intercomparisons to evaluate their performance. This study aimed to synthesise the recent experimental studies and develop a new, near-explicit, DMS mechanism, through thorough literature review, as a reference mechanism for future work to build on. A simple box model was then used with the mechanism to simulate a series of chamber experiments, and evaluated through comparison with four published mechanisms. Our modelling shows that the mechanism developed in this work outperformed the other mechanisms on average when compared to the experimental chamber data, having the lowest fractional gross error for 8 out of the 14 DMS oxidation products studied. A box model of a marine boundary layer was also run, demonstrating that the deviations in the mechanisms seen when comparing them against chamber data are also prominent under more atmospherically relevant conditions. Although this work demonstrates the need for further experimental work, the mechanism developed in this work, having been evaluated against a range of experimental conditions, provides a good basis for a near-explicit DMS oxidation mechanism that would include other initiation reactions (e.g., halogens), and can be used to compare the performance of reduced mechanisms used in global models. [ABSTRACT FROM AUTHOR]

The nitrate radical (NO3) plays an important role in the chemistry of the lower troposphere, acting as the principle oxidant during the night together with ozone. Previous model simulations suggest that the levels of NO3 have increased dramatically since the preindustrial period. Here, we show projections of the evolution of the NO3 radical from 1850–2100 using the United Kingdom Earth System Model (UKESM1) under the Coupled Model Intercomparison Project Phase 6 (CMIP6) shared socioeconomic pathway (SSP) scenarios. Our model results highlight diverse trajectories for NO3 , with some scenarios and regions undergoing rapid growth of NO3 to unprecedented levels over the course of the 21st century and others seeing sharp declines. The local increases in NO3 (up to 40 ppt above the preindustrial base line) are driven not only by local changes in emissions of nitrogen oxides but have an important climate component, with NO3 being favoured in warmer future climates. The changes in NO3 lead to changes in the oxidation of important secondary organic aerosol precursors, with potential impacts on particulate matter pollution regionally and globally. This work highlights the potential for substantial future growth in NO3 and the need to better understand the formation of secondary organic aerosol (SOA) from NO3 to accurately predict future air quality and climate implications. [ABSTRACT FROM AUTHOR]

The biogeochemical behaviour of the Southern Ocean is complex and dynamic. The processes that affect this behaviour are highly dependent on physical, chemical, and biological constraints, which are poorly constrained in Earth System Models. We assess how emissions of dimethyl sulfide (DMS), a precursor of sulfate aerosol, change over the Southern Ocean when the chlorophyll-a distribution, which influences oceanic DMS production, is altered. Using a nudged configuration of the atmosphere-only United Kingdom Earth System Model, UKESM1-AMIP, we performed nine 10-year simulations using forcings representative of the period 2009–2018. Four different seawater DMS data sets are tested as input for these simulations. Three different DMS sea-to-air flux parameterizations are also explored. Our goal is to evaluate the changes in oceanic DMS, sea-to-air fluxes of DMS, and atmospheric DMS through these different simulations during austral summer. The mean spread across all the simulations with different oceanic DMS datasets, but the same sea-to-air flux parameterizations, is 112 % (3.3 to 6.9 TgS Yr−1). The mean spread in simulations using the same oceanic DMS dataset, but differing sea-to-air flux parameterisations is 50–60 % (2.9 to 4.7 TgS Yr−1). The choice of DMS emission parameterisation has a larger influence on atmospheric DMS than the choice of oceanic DMS source. We also find that linear relationships between wind and DMS flux generally compare better to observations than quadratic relationships. Simulations that implement a quadratic emission rate show on average 35 % higher DMS mixing ratios than the linear emission rates. Simulations using seawater DMS derived from satellite chlorophyll-a data in combination with a recently-developed flux parameterisation for DMS show the closest agreement with atmospheric DMS observations and are recommended to be included in future simulations. This work recommends for Earth System Models to include a sea-to-air parameterization that is appropriate for DMS, and for oceanic DMS datasets to include inter-annual variability based on observed marine biogenic activity. Such improvements will provide a more accurate process-based representation of oceanic and atmospheric DMS, and therefore sulfate aerosol, in the Southern Ocean region. [ABSTRACT FROM AUTHOR]