Global Chemistry-climate Model Research Articles

Age of air from in situ trace gas measurements: insights from a new technique

Abstract. The age of air is an important transport diagnostic that can be derived from trace gas measurements and compared to global chemistry climate model output. We describe a new technique to calculate the age of air, measuring transport times from the Earth's surface to any location in the atmosphere based on simultaneous in situ measurements of multiple key long-lived trace gases. The primary benefits of this new technique include (1) optimized ages of air consistent with simultaneously measured SF6 and CO2; (2) age of air from the upper troposphere through the stratosphere; (3) estimates of the second moment of age spectra that have not been well constrained from measurements; and (4) flexibility to be used with measurements across multiple instruments, platforms, and decades. We demonstrate the technique on aircraft and balloon measurements from the 1990s, the last period of extensive stratospheric in situ sampling, and several recent missions from the 2020s, and compare the results with previously published and modeled values.

The contribution of transport emissions to ozone mixing ratios and methane lifetime in 2015 and 2050 in the Shared Socioeconomic Pathways (SSPs)

Abstract. We quantify the contributions of emissions from the transport sector to tropospheric ozone and the hydroxyl radical (OH) by means of model simulations with a global chemistry-climate model equipped with a source attribution method. For the first time we applied a method which also allows for quantifying contributions to OH which is invariant upon disaggregation or recombination and additive. Based on these quantified contributions, we analyse the ozone radiative forcing (RF) and methane lifetime reductions attributable to emissions from the transport sectors. The contributions were analysed for each transport sector separately and for 2015 as well as for 2050 under the Shared Socioeconomic Pathways (SSPs) SSP1-1.9, SSP2-4.5, and SSP3-7.0. In line with previous publications using the source attribution approach, we quantify ozone RF attributable to emissions from land transport, shipping, and aviation for the year 2015 of 121, 60, and 31 mW m−2, respectively. At the same time, we diagnose a relative reduction in methane lifetime due to transport emissions of 14.3 % (land transport), 8.5 % (shipping), and 3.8 % (aviation). These reductions are significantly larger than reported by previous studies due to the application of the source attribution method. Compared to 2015, only SSP1-1.9 shows a strong decrease in ozone RF and methane lifetime reduction attributable to the entire transport sector in 2050. For the projections of SSP2-4.5, we find similar effects of the total transport sector as for 2015, while the effects in SSP3-7.0 increase compared to 2015. This small change in the effects for the two projections compared to 2015 is caused by two main factors. Firstly, aviation emissions are projected to increase in SSP2-4.5 (increase of 107 %) and SSP3-7.0 (+86 %) compared to 2015, resulting in projected ozone RF of 55 mW m−2 (+78 %) and 50 mW m−2 (+61 %) for the year 2050 from aviation emissions. Secondly, the non-linear effects of atmospheric chemistry in polluted regions such as Europe and North America lead to rather small reductions in ozone and OH in response to emission reductions, especially from land transport emissions. In addition, the increase in emissions from land transport in other parts of the world, particularly in South Asia, leads to an increased contribution of ozone and OH. In particular, ozone formed by land transport emissions from South Asia causes strong RF that partially offsets the reductions in Europe and North America. Moreover, our results show that besides the non-linear response, lack of international cooperation, as in the SSP3-7.0 projection, hinders mitigation of ground-level ozone.

Global modeling of aerosol nucleation with a semi-explicit chemical mechanism for highly oxygenated organic molecules (HOMs)

Abstract. New particle formation (NPF) involving organic compounds has been identified as an important process affecting aerosol particle number concentrations in the global atmosphere. Laboratory studies have shown that highly oxygenated organic molecules (HOMs) can make a substantial contribution to NPF, but there is a lack of global model studies of NPF with detailed HOM chemistry. Here, we incorporate a state-of-the-art biogenic HOM chemistry scheme with 96 chemical reactions to a global chemistry–climate model and quantify the contribution to global aerosols through HOM-driven NPF. The updated model captures the frequency of NPF events observed at continental surface sites (normalized mean bias changes from −96 % to −15 %) and shows reasonable agreement with measured rates of NPF and sub-20 nm particle growth. Sensitivity simulations show that compared to turning off the organic nucleation rate, turning off organic initial growth results in a more substantial decrease in aerosol number concentrations. Globally, organics contribute around 45 % of the annual mean vertically integrated nucleation rate (at 1.7 nm) and 25 % of the vertically averaged growth rate. The inclusion of HOM-related processes leads to a 39 % increase in the global annual mean aerosol number burden and a 33 % increase in cloud condensation nuclei (CCN) burden at 0.5 % supersaturation compared to a simulation with only inorganic nucleation. Our work predicts a greater contribution of organic nucleation to NPF than previous studies due to the semi-explicit HOM mechanism and an updated inorganic NPF scheme. The large contribution of biogenic HOMs to NPF on a global scale could make aerosol sensitive to changes in biogenic emissions.

The co-benefits of a low-carbon future for PM2.5 and O3 air pollution in Europe

Abstract. There is considerable academic interest in the potential for air quality improvement as a co-benefit of climate change mitigation. Few studies use regional air quality models for simulating future co-benefits, but many use global chemistry–climate model output. Using regional atmospheric chemistry could provide a better representation of air quality changes than global chemistry–climate models, especially by improving the representation of elevated urban concentrations. We use a detailed regional atmospheric-chemistry model (WRF-Chem v4.2) to model European air quality in 2050 compared to 2014 following three climate change mitigation scenarios. We represent different climate futures by using air pollutant emissions and chemical boundary conditions (from CESM2-WACCM output) for three shared socioeconomic pathways (SSP1-2.6, SSP2-4.5 and SSP3-7.0: high-, medium- and low-mitigation pathways respectively). We find that in 2050, following SSP1-2.6, mean population-weighted PM2.5 concentrations across European countries are reduced by 52 % compared to 2014. Under SSP2-4.5, this average reduction is 34%. The smallest average reduction is 18 %, achieved following SSP3-7.0. Maximum 6-monthly-mean daily-maximum 8 h (6mDM8h) ozone (O3) is reduced across Europe by 15 % following SSP1-2.6 and by 3 % following SSP2-4.5, but it increases by 13 % following SSP3-7.0. This demonstrates clear co-benefits of climate mitigation. The additional resolution allows us to analyse regional differences and identify key sectors. We find that the mitigation of agricultural emissions will be key for attaining meaningful co-benefits of mitigation policies, as evidenced by the importance of changes in NO3 aerosol mass to future PM2.5 air quality and changes in CH4 emissions to future O3 air quality.

Arctic halogens reduce ozone in the northern mid-latitudes

While the dominant role of halogens in Arctic ozone loss during spring has been widely studied in the last decades, the impact of sea-ice halogens on surface ozone abundance over the northern hemisphere (NH) mid-latitudes remains unquantified. Here, we use a state-of-the-art global chemistry-climate model including polar halogens (Cl, Br, and I), which reproduces Arctic ozone seasonality, to show that Arctic sea-ice halogens reduce surface ozone in the NH mid-latitudes (47°N to 60°N) by ~11% during spring. This background ozone reduction follows the southward export of ozone-poor and halogen-rich air masses from the Arctic through polar front intrusions toward lower latitudes, reducing the springtime tropospheric ozone column within the NH mid-latitudes by ~4%. Our results also show that the present-day influence of Arctic halogens on surface ozone destruction is comparatively smaller than in preindustrial times driven by changes in the chemical interplay between anthropogenic pollution and natural halogens. We conclude that the impact of Arctic sea-ice halogens on NH mid-latitude ozone abundance should be incorporated into global models to improve the representation of ozone seasonality.

Significant chlorine emissions from biomass burning affect the long-term atmospheric chemistry in Asia.

Biomass burning (BB) is a major source of trace gases and particles in the atmosphere, influencing air quality, radiative balance, and climate. Previous studies have mainly focused on the BB emissions of carbon and nitrogen species with less attention on chlorine. Reactive chlorine chemistry has significant effects on atmospheric chemistry and air quality. However, quantitative information on chlorine emissions from BB, particularly the long-term trend and associated atmospheric impacts, is limited both on regional and global scales. Here, we report a long-term (2001-2018) high-resolution BB emission inventory for the major chlorine-containing compounds (HCl, chloride, and CH3Cl) in Asia based on satellite observations. We estimate an average of 730 Gg yr-1 chlorine emitted from BB activity in Asia, with China contributing the largest share at 24.2% (177 Gg yr-1), followed by Myanmar at 18.7% and India at 18.3%. Distinct seasonal patterns and significant spatial and interannual variability are observed, mainly driven by human-mediated changes in agricultural activity. By incorporating the newly developed chlorine emission inventory into a global chemistry-climate model (CAM-Chem), we find that the BB-chlorine emissions lead to elevated levels of HCl and CH3Cl (monthly average up to 2062 and 1421 parts per trillion by volume (pptv), respectively), subsequently resulting in noticeable changes in oxidants (up to 3.1% in O3 and 17% in OH radicals). The results demonstrate that BB is not only a significant source of air pollutants but also of oxidants, suggesting a larger role of BB emissions in the atmospheric chemistry and oxidation process than previously appreciated. In light of the projected increase in BB activity toward the end of the century and the extensive control of anthropogenic emissions worldwide, the contribution of BB emissions may become fundamental to air quality composition in the future.

Technical note: An assessment of the performance of statistical bias correction techniques for global chemistry–climate model surface ozone fields

Abstract. State-of-the-art chemistry–climate models (CCMs) still show biases compared to ground-level ozone observations, illustrating the difficulties and challenges remaining in the simulation of atmospheric processes governing ozone production and loss. Therefore, CCM output is frequently bias-corrected in studies seeking to explore the health or environmental impacts from changing air quality burdens. Here, we assess four statistical bias correction techniques of varying complexities and their application to surface ozone fields simulated with four CCMs and evaluate their performance against gridded observations in the EU and US. We focus on two time periods (2005–2009 and 2010–2014), where the first period is used for development and training and the second to evaluate the performance of techniques when applied to model projections. We find that all methods are capable of significantly reducing the model bias. However, biases are lowest when we apply more complex approaches such as quantile mapping and delta functions. We also highlight the sensitivity of the correction techniques to individual CCM skill at reproducing the observed distributional change in surface ozone. Ensemble simulations available for one CCM indicate that model ozone biases are likely more sensitive to the process representation embedded in chemical mechanisms than to meteorology.

One-third of global population at cancer risk due to elevated volatile organic compounds levels

Outdoor air pollution, particularly volatile organic compounds (VOCs), significantly contributes to the global health burden. Previous analyses of VOC exposure have typically focused on regional and national scales, thereby limiting global health burden assessments. In this study, we utilized a global chemistry-climate model to simulate VOC distributions and estimate related cancer risks from 2000 to 2019. Our findings indicated a 10.2% rise in global VOC emissions during this period, with substantial increases in Sub-Saharan Africa, the Rest of Asia, and China, but decreases in the U.S. and Europe due to reductions in the transportation and residential sectors. Carcinogenic VOCs such as benzene, formaldehyde, and acetaldehyde contributed to a lifetime cancer burden affecting 0.60 [95% confidence interval (95CI): 0.40–0.81] to 0.85 [95CI: 0.56–1.14] million individuals globally. We projected that between 36.4% and 39.7% of the global population was exposed to harmful VOC levels, with the highest exposure rates found in China (82.8–84.3%) and considerably lower exposure in Europe (1.7–5.8%). Open agricultural burning in less-developed regions amplified VOC-induced cancer burdens. Significant disparities in cancer burdens between high-income and low-to-middle-income countries were identified throughout the study period, primarily due to unequal population growth and VOC emissions. These findings underscore health disparities among different income nations and emphasize the persistent need to address the environmental injustice related to air pollution exposure.

Development, intercomparison, and evaluation of an improved mechanism for the oxidation of dimethyl sulfide in the UKCA model

Abstract. 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: CH3SO3 decomposition, CH3S + O2, CH3SOO decomposition, and CH3SO + O3.

Using Regionalized Air Quality Model Performance and Bayesian Maximum Entropy data fusion to map global surface ozone concentration

Estimates of ground-level ozone concentrations have been improved through data fusion of observations and atmospheric chemistry models. Our previous global ozone estimates for the Global Burden of Disease study corrected for bias uniformly across continents and then corrected near monitoring stations using the Bayesian Maximum Entropy (BME) framework for data fusion. Here, we use the Regionalized Air Quality Model Performance (RAMP) framework to correct model bias over a much larger spatial range than BME can, accounting for the spatial inhomogeneity of bias and nonlinearity as a function of modeled ozone. RAMP bias correction is applied to a composite of 9 global chemistry-climate models, based on the nearest set of monitors. These estimates are then fused with observations using BME, which matches observations at measurement stations, with the influence of observations declining with distance in space and time. We create global ozone maps for each year from 1990 to 2017 at fine spatial resolution. RAMP is shown to create unrealistic discontinuities due to the spatial clustering of ozone monitors, which we overcome by applying a weighting for RAMP based on the number of monitors nearby. Incorporating RAMP before BME has little effect on model performance near stations, but strongly increases R2 by 0.15 at locations farther from stations, shown through a checkerboard cross-validation. Corrections to estimates differ based on location in space and time, confirming heterogeneity. We quantify the likelihood of exceeding selected ozone levels, finding that parts of the Middle East, India, and China are most likely to exceed 55 parts per billion (ppb) in 2017. About 96% of the global population was exposed to ozone levels above the World Health Organization guideline of 60 µg m−3 (30 ppb) in 2017. Our annual fine-resolution ozone estimates may be useful for several applications including epidemiology and assessments of impacts on health, agriculture, and ecosystems.

Emulating lateral gravity wave propagation in a global chemistry–climate model (EMAC v2.55.2) through horizontal flux redistribution

Abstract. The columnar approach of gravity wave (GW) parameterisations in weather and climate models has been identified as a potential reason for dynamical biases in middle-atmospheric dynamics. For example, GW momentum flux (GWMF) discrepancies between models and observations at 60∘ S arising through the lack of horizontal orographic GW propagation are suspected to cause deficiencies in representing the Antarctic polar vortex. However, due to the decomposition of the model domains onto different computing tasks for parallelisation, communication between horizontal grid boxes is computationally extremely expensive, making horizontal propagation of GWs unfeasible for global chemistry–climate simulations. To overcome this issue, we present a simplified solution to approximate horizontal GW propagation through redistribution of the GWMF at one single altitude by means of tailor-made redistribution maps. To generate the global redistribution maps averaged for each grid box, we use a parameterisation describing orography as a set of mountain ridges with specified location, orientation and height combined with a ray-tracing model describing lateral propagation of so-generated mountain waves. In the global chemistry–climate model (CCM) EMAC (ECHAM MESSy Atmospheric Chemistry), these maps then allow us to redistribute the GW momentum flux horizontally at one level, obtaining an affordable overhead of computing resources. The results of our simulations show GWMF and drag patterns that are horizontally more spread out than with the purely columnar approach; GWs are now also present above the ocean and regions without mountains. In this paper, we provide a detailed description of how the redistribution maps are computed and how the GWMF redistribution is implemented in the CCM. Moreover, an analysis shows why 15 km is the ideal altitude for the redistribution. First results with the redistributed orographic GWMF provide clear evidence that the redistributed GW drag in the Southern Hemisphere has the potential to modify and improve Antarctic polar vortex dynamics, thereby paving the way for enhanced credibility of CCM simulations and projections of polar stratospheric ozone.

Meteorology-driven PM2.5 interannual variability over East Asia

Atmospheric fine particulate matter (PM2.5) is a human health risk factor, but its ambient concentration depends on both precursor emissions and meteorology. While emission reductions are used to set PM2.5-related health policies, the effect of meteorology is often overlooked. To explore this aspect, we examined PM2.5 interannual variability (IAV) associated with meteorological parameters using the long-term simulation from the Community Earth System Model (CESM1), a global climate-chemistry model, with fixed emissions. The results are subsequently contrasted with the MERRA-2 reanalysis dataset, which inherently considers emission and meteorology effects. Over continental East Asia, the CESM1 domain-average PM2.5 IAV is 6.7 %, mainly attributed to humidity, precipitation, and ventilation variation. The grid-cell PM2.5 IAVs over southern East China are larger, up to 12 % due to the more substantial influence of El Niño-induced meteorological anomalies. Under such climate extreme, sub-regional PM2.5 concentration may occasionally exceed WHO air quality guideline levels despite the compliance of the long-term mean. The simulated PM2.5 IAV over continental East Asia is ~25 % of that derived from the MERRA-2 data, which highlights the influence of both emission and meteorology-driven variations and trends inherent in the latter. Although emission-driven variability is significant to PM2.5 IAV, in remote areas downwind of major source regions in East Asia, North America, and Western Europe, the MERRA-2 data revealed that meteorological variations contributed more to PM2.5 IAV than emission variations. Thus, when setting policies for complying with the WHO PM2.5-related air quality guideline levels, the highest annual PM2.5 associated with climate extremes should be considered instead of that based on average climate conditions.

Anthropogenic amplification of biogenic secondary organic aerosol production

Abstract. Biogenic secondary organic aerosols (SOAs) contribute to a large fraction of fine aerosols globally, impacting air quality and climate. The formation of biogenic SOA depends on not only emissions of biogenic volatile organic compounds (BVOCs) but also anthropogenic pollutants including primary organic aerosol, sulfur dioxide (SO2), and nitrogen oxides (NOx). However, the anthropogenic impact on biogenic SOA production (AIBS) remains unclear. Here we use the decadal trend and variability in observed organic aerosol (OA) in the southeast US, combined with a global chemistry–climate model, to better constrain AIBS. We show that the reduction in SO2 emissions can only explain 40 % of the decreasing decadal trend of OA in this region, constrained by the low summertime month-to-month variability in surface OA. We hypothesize that the rest of the OA decreasing trend is largely due to a reduction in NOx emissions. By implementing a scheme for monoterpene SOA with enhanced sensitivity to NOx, our model can reproduce the decadal trend and variability in OA in this region. Extending to a centennial scale, our model shows that global SOA production increases by 36 % despite BVOC reductions from the preindustrial period to the present day, largely amplified by AIBS. Our work suggests a strong coupling between anthropogenic and biogenic emissions in biogenic SOA production that is missing from current climate models.

Sensitivity of tropospheric ozone to halogen chemistry in the chemistry–climate model LMDZ-INCA vNMHC

Abstract. The atmospheric chemistry of halogenated species (Cl, Br, I) participates in the global chemical sink of tropospheric ozone and perturbs the oxidising capacity of the troposphere, notably by influencing the atmospheric lifetime of methane. Global chemistry–climate models are commonly used to assess the global budget of ozone and its sensitivity to emissions of its precursors, as well as to project its long-term evolution. Here, we report on the implementation of tropospheric sources and chemistry of halogens in the chemistry–climate model LMDZ-INCA (Laboratoire de Météorologie Dynamique general circulation model, LMDZ, and Interactions with Chemistry and Aerosols, INCA, version with Non-Methane HydroCarbon chemistry, vNMHC) and evaluate halogen effects on the tropospheric ozone budget. Overall, the results show that the model simulates satisfactorily the impact of halogens on the photo-oxidising system in the troposphere, in particular in the marine boundary layer. To quantify the effects of halogen chemistry in LMDZ-INCA, standard metrics representative of the behaviour of the tropospheric chemical system (Ox, HOx, NOx, CH4 and non-methane volatile organic compounds – NMVOCs) are computed with and without halogens. The addition of tropospheric halogens in the LMDZ-INCA model leads to a decrease of 22 % in the ozone burden, 8 % in OH and 33 % in NOx. Sensitivity simulations show for the first time that the inclusion of halogen chemistry makes ozone more sensitive to perturbations in CH4, NOx and NMVOCs. Consistent with other global model studies, the sensitivity of the tropospheric ozone burden to changes from pre-industrial to present-day emissions is found to be ∼20 % lower when tropospheric halogens are taken into account.

Regional Sources and Sinks of Atmospheric Particulate Selenium in the United States Based on Seasonality Profiles.

Selenium (Se) is an essential nutrient for humans and enters our food chain through bioavailable Se in soil. Atmospheric deposition is a major source of Se to soils, driving the need to investigate the sources and sinks of atmospheric Se. Here, we used Se concentrations from PM2.5 data at 82 sites from 1988 to 2010 from the Interagency Monitoring of Protected Visual Environments (IMPROVE) network in the US to identify the sources and sinks of particulate Se. We identified 6 distinct seasonal profiles of atmospheric Se, grouped by geographical location: West, Southwest, Midwest, Southeast, Northeast, and North Northeast. Across most of the regions, coal combustion is the largest Se source, with a terrestrial source dominating in the West. We also found evidence for gas-to-particle partitioning in the wintertime in the Northeast. Wet deposition is an important sink of particulate Se, as determined by Se/PM2.5 ratios. The Se concentrations from the IMPROVE network compare well to modeled output from a global chemistry-climate model, SOCOL-AER, except in the Southeast US. Our analysis constrains the sources and sinks of atmospheric Se, thereby improving the predictions of Se distribution under climate change.

Rapid increase in tropospheric ozone over Southeast Asia attributed to changes in precursor emission source regions and sectors

Observations indicate that tropospheric ozone (O3) concentrations over Southeast Asia have been increasing rapidly since the 1990s. Here, we quantify source contributions from geographical regions and emission sectors of the two distinct types of O3 precursors, i.e., nitrogen oxides (NOx) and volatile organic compounds (VOCs), to the increase in tropospheric O3 in Southeast Asia during 1990–2019 using an O3 source tagging technique implemented in a global chemistry-climate model. The results show that although local anthropogenic emission of NOx in Southeast Asia only contributes 18% of the annual averaged near-surface O3 concentration, the increase in local NOx emission dominates the increasing trend of O3 concentration in Southeast Asia, accounting for 107% of the regional averaged trend of 1.07 ppb decade−1. Increases in NOx emissions from East Asia and South Asia explain 29% of the increasing trend, but 9% is offset by the emission reduction in North America. The vertical O3 trends in the troposphere contributed by individual source regions are consistent with those near the surface. Ground transportation is responsible for 79% of the rapid O3 increase, followed by 39% contribution from international shipping. Because an increase in anthropogenic NOx emissions enhances the O3 production efficiency by VOCs, the increase in O3 concentrations in Southeast Asia is thereby largely contributed by methane and biogenic VOCs.

The historical ozone trends simulated with the SOCOLv4 and their comparison with observations and reanalyses

Abstract. There is evidence that the ozone layer has begun to recover owing to the ban on the production of halogenated ozone-depleting substances (hODS) accomplished by the Montreal Protocol and its amendments and adjustments (MPA). However, recent studies, while reporting an increase in tropospheric ozone from the anthropogenic NOx and CH4 and confirming the ozone recovery in the upper stratosphere from the effects of hODS, also indicate a continuing decline in the lower tropical and mid-latitudinal stratospheric ozone. While these are indications derived from observations, they are not reproduced by current global chemistry–climate models (CCMs), which show positive or near-zero trends for ozone in the lower stratosphere. This makes it difficult to robustly establish ozone evolution and has sparked debate about the ability of contemporary CCMs to simulate future ozone trends. We applied the new Earth system model (ESM) SOCOLv4 (SOlar Climate Ozone Links, version 4) to calculate long-term ozone trends between 1985–2018 and compare them with trends derived from the BAyeSian Integrated and Consolidated (BASIC) ozone composite and MERRA-2, ERA-5, and MSRv2 reanalyses. We designed the model experiment with a six-member ensemble to account for the uncertainty of the natural variability. The trend analysis is performed separately for the ozone depletion (1985–1997) and ozone recovery (1998–2018) phases of the ozone evolution. Within the 1998–2018 period, SOCOLv4 shows statistically significant positive ozone trends in the mesosphere, upper and middle stratosphere, and a steady increase in the tropospheric ozone. The SOCOLv4 results also suggest slightly negative trends in the extra-polar lower stratosphere, yet they barely agree with the BASIC ozone composite in terms of magnitude and statistical significance. However, in some realizations of the SOCOLv4 experiment, the pattern of ozone trends in the lower stratosphere resembles much of what is observed, suggesting that SOCOLv4 may be able to reproduce the observed trends in this region. Thus, the model results reveal marginally significant negative ozone changes in parts of the low-latitude lower stratosphere, which agrees in general with the negative tendencies extracted from the satellite data composite. Despite the slightly smaller significance and magnitude of the simulated ensemble mean, we confirm that modern CCMs such as SOCOLv4 are generally capable of simulating the observed ozone changes, justifying their use to project the future evolution of the ozone layer.

Radiative impact of improved global parameterisations of oceanic dry deposition of ozone and lightning-generated NOx

Abstract. We investigated the radiative impact of recent process-based improvements to oceanic ozone (O3) dry deposition parameterisation and empirical improvements to lightning-generated oxides of nitrogen (LNOx) parameterisation by conducting a 5-year simulation of the Australian Community Climate and Earth System Simulator – United Kingdom Chemistry and Aerosol (ACCESS-UKCA) global chemistry–climate model, with radiative effects of O3, methane (CH4) and aerosol included. Compared to the base parameterisations, the global consequences of the two improved parameterisations on atmospheric composition are dominated by the LNOx change (which increases the LNOx production from 4.8 to 6.9 Tg N yr−1) and include (a) an increase in the O3 column of 3.75 DU, and this O3 change is centred on the tropical upper troposphere where O3 is most effective as a radiative forcer; (b) a decrease of 0.64 years in the atmospheric lifetime of CH4 due to an increase in hydroxyl radical, which corresponds to a decrease of 0.31 years in the CH4 lifetime per Tg N yr−1 change in LNOx; (c) an increase of 6.7 % in the column integrated condensation nuclei concentration; and (d) a slight increase in high-level cloud cover. The two combined parameterisation changes cause an increase of 86.3 mW m−2 in the globally-averaged all-sky net downward top-of-atmosphere (TOA) radiative flux (which is akin to instantaneous radiative forcing), and only 5 % of which is due to the dry deposition parameterisation change. Other global radiative changes from the use of the two parameterisations together include an increase in the downward longwave radiation and a decrease in the downward shortwave radiation at the earth's surface. The indirect effect of LNOx on aerosol and cloud cover can at least partly explain the differences in the downward shortwave flux at the surface. It is demonstrated that although the total global LNOx production may be the same, how LNOx is distributed spatially makes a difference to radiative transfer. We estimate that for a reported uncertainty range of 5±3 Tg N yr−1 in global estimates of LNOx, the uncertainty in the net downward TOA radiation is ±119 mW m−2. The corresponding uncertainly in the atmospheric methane lifetime is ±0.92 years. Thus, the value of LNOx used within a model will influence the effective radiative forcing (ERF) and global warming potential (GWP) of anthropogenic CH4, and influence the results of climate scenario modelling.

Correcting ozone biases in a global chemistry–climate model: implications for future ozone

Abstract. Weaknesses in process representation in chemistry–climate models lead to biases in simulating surface ozone and to uncertainty in projections of future ozone change. We here develop a deep learning model to demonstrate the feasibility of ozone bias correction in a global chemistry–climate model. We apply this approach to identify the key factors causing ozone biases and to correct projections of future surface ozone. Temperature and the related geographic variables latitude and month show the strongest relationship with ozone biases. This indicates that ozone biases are sensitive to temperature and suggests weaknesses in representation of temperature-sensitive physical or chemical processes. Photolysis rates are also an important factor, highlighting the sensitivity of biases to simulated cloud cover and insolation. Atmospheric chemical species such as the hydroxyl radical, nitric acid and peroxyacyl nitrate show strong positive relationships with ozone biases on a regional scale. These relationships reveal the conditions under which ozone biases occur, although they reflect association rather than direct causation. We correct model projections of future ozone under different climate and emission scenarios following the shared socio-economic pathways. We find that changes in seasonal ozone mixing ratios from the present day to the future are generally smaller than those simulated without bias correction, especially in high-emission regions. This suggests that the ozone sensitivity to changing emissions and climate may be overestimated with chemistry–climate models. Given the uncertainty in simulating future ozone, we show that deep learning approaches can provide improved assessment of the impacts of climate and emission changes on future air quality, along with valuable information to guide future model development.

TransClim (v1.0): a chemistry–climate response model for assessing the effect of mitigation strategies for road traffic on ozone

Abstract. Road traffic emits not only carbon dioxide (CO2) and particulate matter, but also other pollutants such as nitrogen oxides (NOx), volatile organic compounds (VOCs) and carbon monoxide (CO). These chemical species influence the atmospheric chemistry and produce ozone (O3) in the troposphere. Ozone acts as a greenhouse gas and thus contributes to anthropogenic global warming. Technological trends and political decisions can help to reduce the O3 effect of road traffic emissions on climate. In order to assess the O3 response of such mitigation options on climate, we developed a chemistry–climate response model called TransClim (Modelling the effect of surface Transportation on Climate). The current version considers road traffic emissions of NOx, VOC and CO and determines the O3 change and its corresponding stratosphere-adjusted radiative forcing. Using a tagging method, TransClim is further able to quantify the contribution of road traffic emissions to the O3 concentration. Thus, TransClim determines the contribution to O3 as well as the change in total tropospheric O3 of a road traffic emission scenario. Both quantities are essential when assessing mitigation strategies. The response model is based on lookup tables which are generated by a set of emission variation simulations performed with the global chemistry–climate model EMAC (ECHAM5 v5.3.02, MESSy v2.53.0). Evaluating TransClim against independent EMAC simulations reveals low deviations of all considered species (0.01 %–10 %). Hence, TransClim is able to reproduce the results of an EMAC simulation very well. Moreover, TransClim is about 6000 times faster in computing the climate effect of an emission scenario than the complex chemistry–climate model. This makes TransClim a suitable tool to efficiently assess the climate effect of a broad range of mitigation options for road traffic or to analyse uncertainty ranges by employing Monte Carlo simulations.