Aerosol inhibition on photochemical surface ozone formation under future climate and air quality scenarios

Aerosol inhibition on photochemical surface ozone formation under future climate and air quality scenarios | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Aerosol inhibition on photochemical surface ozone formation under future climate and air quality scenarios Daniel Westervelt, G S Gopikrishnan, Jayanarayanan Kuttippurath This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5932296/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 25 Apr, 2025 Read the published version in npj Climate and Atmospheric Science → Version 1 posted 9 You are reading this latest preprint version Abstract ​Aerosols significantly influence tropospheric oxidation and ozone formation by modulating photolysis rates and radical sinks.​ This study employs the GEOS-Chem model to analyze different aerosol heterogeneous uptake coefficients (0, 0.1, 0.2, 0.4) and their effects on photochemical ozone levels across regions in the near-present and under future Shared Socioeconomic Pathways (SSP) scenarios. Higher uptake coefficients enhance the sink of radical species like HO 2 and expand the aerosol-inhibited regime (AIR), particularly in otherwise NO x -limited regions like India and East Asia, leading to a notable increase in surface ozone (40–50%), especially during colder months. Projections for 2046 indicate a global reduction in AIR areas, resulting from stricter emission controls. By 2096, the extent of AIR further diminishes, with regions such as Southeast Asia transitioning to NOx-limited conditions, though aerosol uptake of HO 2 continues to elevate surface ozone levels by 10–15% in heavily aerosol-loaded areas. Earth and environmental sciences/Environmental sciences Earth and environmental sciences/Environmental sciences/Environmental chemistry Aerosol uptake Surface Ozone SDG SSP GEOS Chem GCAP Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Highlights ● Higher aerosol uptake enhances radical sinks, increasing surface ozone levels by 40–60% in 2018. ● North America, Europe and East-Asia remain under an aerosol-inhibited photochemical regime (AIR) in future scenarios. ● However, total AIR extent reduces in both near and distant future simulations. 1. Introduction The heterogeneous chemistry in the lower atmosphere is significant in areas with high aerosol loading and gas-phase pollutants 1 . For example, the heterogeneous interaction of N 2 O 5 with aerosols significantly influences the NO x -O 3 cycle in the atmosphere, depleting atmospheric NO x and leading to reduced surface ozone levels in the lower atmosphere (800—1000 hPa) 2 , 3 . However, the termination of these reactions is also important in determining the chemistry of the lower atmosphere. For instance, surface ozone (O 3 ) is formed through radical chain reactions involving the oxidation of volatile organic compounds (VOCs) and nitrogen oxides (NOx), initiated by the photolysis of compounds like O 3 and HCHO 4 – 7 . Termination occurs via peroxyl radical self-reactions or the reaction of hydroxyl radicals with NO 2 , influencing whether reductions in NOx or VOC emissions are more effective for controlling O 3 pollution 8 , 9 . In ozone mitigation efforts, these reactions are typically considered within two regimes called “NOx-limited” and “VOC-limited” 10 – 12 . The NOx-limited chemical regime describes conditions in which NOx emissions reductions are most beneficial to reduce ozone, while the VOC-limited regime represents situations where lowering emissions of organic compounds would be most effective. Wang et al. 13 noted that the trade-off between ozone (O 3 ) and particulate matter (PM 2.5 ) has arisen as an unexpected result of China's Clean Air Action Plan, which sought to mitigate air pollution. Subsequent to the plan's execution, ozone concentrations elevated during summer in the North China Plain, attributed to diminished NO x emissions and stable or escalating VOC emissions, along with substantial declines in PM 2.5 levels. This suggests that tackling ozone pollution necessitates a more sophisticated comprehension than merely classifying it into NOx-limited and VOC-limited categories, wherein the impact of PM 2.5 and aerosols are important 14 . Consequently, forthcoming air quality control systems globally must account for the complicated links among ozone, particulate matter and precursor emissions to successfully mitigate both pollutants concurrently. Ivatt et al. 15 presented a third regime, termed the Aerosol-Inhibited Regime, in which hydroperoxyl radicals on particulate surfaces influence ozone formation. The experiment conducted with GEOS Chem, a global chemical transport model, demonstrated that between 1970 and 2014, the percentage of the Northern Hemisphere's population residing in this regime increased from 2 to 21%. At first, in 1750, regions dependent on biomass burning experienced the most significant effects, but industrialised areas such as North America and Europe had become the most affected by 1970. By 2014, the regions of South and East Asia, with a particular emphasis on South Asia, emerged as the most impacted areas. To address the rise in surface ozone due to a 50% reduction in PM 2.5 precursors, a 40% decrease in NOx emissions is essential, highlighting the complicated interactions among various pollutants in the pursuit of effective air quality management. Therefore, it is essential to take into consideration not only the trade-offs between ozone and particulate matter but also the influence of aerosol particles on ozone formation. This emphasises the necessity for more detailed and regionally tailored approaches to effectively tackle both ozone and particulate pollution in the present and future emission contexts 16 , 17 . Shared Socioeconomic Pathways (SSPs) represent scenarios designed to investigate various potential futures related to climate change and its effects 18 . This framework discusses the connection between different levels of socioeconomic development, technological progress and demographic shifts and their effects on greenhouse gas emissions and susceptibility to climate-related impacts. Five scenarios exist, starting with SSP1, which is defined by sustainable development and low emissions and extending to SSP5, which envisages rapid economic growth and high fossil fuel consumption. Each pathway presents unique challenges for climate mitigation and adaptation, assisting experts and decision-makers in assessing potential climate strategies. For example, SSP2 illustrates a balanced scenario that underscores the complexity and unpredictability in reaching climate objectives, whereas SSP3 emphasises a divided world characterised by elevated emissions stemming from insufficient collaboration. The SSP framework allows for the evaluation of climate impacts, adaptation requirements and mitigation approaches across different scenarios, and thereby supporting informed decision-making 19 . Additionally, the SSPs are frequently integrated with Representative Concentration Pathways (RCPs) to simulate various climate scenarios influenced by differing levels of greenhouse gas concentrations 20 , 21 . This study aims at estimating the surface ozone concentrations using the GEOS-Chem framework under different SSP-RCP scenarios, addressing both near-future (2046) and distant-future (2096) scenarios, inclusive and exclusive of aerosol uptake effects. The growing complexity of ozone dynamics, especially considering the unforeseen effects of air quality policies—exemplified by those in China—underscores the imperative to integrate aerosol interactions into atmospheric models. The relationship between reduced PM 2.5 emissions and increased ozone levels highlights the necessity of a holistic strategy for air quality management 22 . The study utilises the SSP framework for clarifying the impact of diverse socioeconomic trajectories on ozone pollution across distinct aerosol conditions. Understanding these interactions is essential for developing effective climate and air quality measures, as the anticipated rise in populations residing in aerosol-inhibited areas presents considerable hazards to public health and environmental sustainability. This could further benefit policy makers in determining effective strategies for decreasing ozone levels while maintaining improvements in particulate matter and aerosol reduction 23 . As international initiatives to combat climate change escalate, it is essential to understand the ozone generation processes to formulate adaptive policies that address both local and global air quality issues. 2. Data and Methods 2.1 GEOS Chem model GEOS-Chem is a Chemical Transport Model (CTM) developed for modelling complex oxidant-aerosol chemistry in the troposphere and stratosphere 24 , 25 . Employing the Kinetic PreProcessor (KPP) 3.0 as its chemical solver, GEOS-Chem integrates sophisticated functionalities via the FlexChem interface, facilitating a flexible methodology for chemical kinetics 26 . The model complies with the most recent JPL/IUPAC guidelines for chemical mechanisms, with substantial modifications that improve the depiction of diverse chemical processes, including those related to isoprene, aromatics and nitrates 27 . Recent advancements have enhanced the treatment of intricate reactions, including methanol synthesis and mercury redox chemistry, facilitating more precise atmospheric forecasts. Additionally, the model incorporates the reactive absorption of nitrogen oxides by aerosols and computes aerosol hygroscopicity, which is essential for comprehending aerosol-cloud interactions. GEOS-Chem offers a comprehensive framework for investigating atmospheric chemistry and its effects on air quality and climate change by accommodating various chemical species and reactions, including halogens and hydroxymethanesulfonate. This model provides thorough understanding into ozone generation mechanisms and pollutant interactions, serving as an essential resource for addressing air quality challenges and comprehending the wider implications of atmospheric dynamics. GEOS-Chem has been rigorously validated by researchers globally. For instance, Travis et al. 28 showed that, despite the successful simulation of ozone and its precursors in the SEAC4RS aircraft data below 1 km of altitude, Maximum Daily 8-hour average surface ozone (MDA-8) was biased high in the model by + 6 ppb on average. David et al. 29 used the GEOS-Chem transport model over India and observed that the model reasonably simulated the tropospheric O 3 abundances and vertical profiles, with a mean bias of 1–3 DU compared to observations for the period 2000–2015. Christiansen et al. 30 observed that the GEOS-Chem model, when validated against 25 ozonesonde sites, aircraft, and satellite observations globally, has a reasonable agreement with a mean bias of 1–3 DU for the period from 1990 to 2017. Mao et al. 31 reported that the GEOS-Chem model, validated against MDA8 O 3 observations in central and eastern China from May to July 2017, had a strong correlation of 0.77 (95% confidence level). In Nanjing, the simulated MDA8 O 3 concentrations converged with the observed trend, with a correlation coefficient of 0.65, a normalised mean bias (NMB) of 5%, and a normalised mean error (NME) of 21%. 2.2 GCAP 2.0 model The Global Change and Air Pollution (GCAP 2.0) framework signifies a notable technological enhancement compared to the original GCAP model, first articulated by Wu et al. 32 and subsequently refined by Murray et al. 33 . This revised model utilises meteorological data sourced from version E2.1 of the NASA Goddard Institute for Space Studies (GISS) General Circulation Model (GCM), allowing the GEOS-Chem to conduct simulations across diverse scenarios, including pre-industrial, recent historical and multiple future conditions in accordance with the CMIP6 experiments 33 – 35 . GCAP 2.0 resolves significant difficulties noted in previous iterations, notably the excessive mass transfer from the stratosphere to the troposphere that complicated the tropospheric ozone budget. This problem frequently obstructed the analysis of polar ice-core data, particularly with the integration of online interactive stratospheric chemistry in GEOS-Chem. To address these complexities, GCAP 2.0 employs a unidirectional offline coupling technique, enabling the GEOS-Chem CTM to utilise stored meteorological data from any historical or forthcoming time. Essential attributes encompass the incorporation of a cohesive chemical mechanism spanning from the surface to the mesopause, facilitating enhanced atmospheric representations, alongside a versatile emissions pre-processor to accommodate diverse emissions situations. GCAP 2.0 facilitates global simulations encompassing 72 vertical layers down from 1000 hPa to 0.01 hPa. The model integrates innovations such as one- and two-way linked nested regional simulations, enabling localised air quality investigations in conjunction with global evaluations and an adjoint for inverse modelling that improves its functionality. 2.3 Methods THe GEOS Chem and GCAP2.0 are run on a 2.5 o x2.5 o grid resolution globally. GEOS Chem classic version has 72 vertical levels from the surface (1000 hPa) to the top of the atmosphere (0.01 hPa), whereas GCAP2.0 has a 41-level vertical gridding. One year spin up simulations with different aerosol uptake coefficients are used to generate the model restart files. Termination rates of chain reactions were determined using archived species concentrations and physical parameters such as temperature, pressure and humidity, in addition to aerosol properties, as per Ivatt et al. 15 . Although we do not classify radical product generation in peroxyl-radical self-reactions as termination stages, we regard non-radical products as ongoing termination processes. The heterogeneous loss rate of HO 2 was assessed by evaluating the radius and surface area of different aerosol forms. For our simulations, we employed a baseline HO 2 reactive uptake coefficient (γHO 2 ) of 0.2. Laboratory studies of pure synthetic aerosols indicate lower uptake coefficients (γHO 2 < 0.2), whereas real-world aerosol studies reveal values between 0.08 to 0.40, implying that elements such as transition metals may increase aerosol uptake 36 – 38 . To assess the influence of HO 2 uptake, we performed simulations with γHO 2 values zero aerosol uptake, 0.1 (half of the baseline), 0.2 (baseline for future projections in this study) and 0.4 (twice the baseline). Though we presumed H 2 O to be the exclusive product of HO 2 absorption, our results remain valid when H 2 O 2 is taken into account. Employing a singular γHO 2 value likely oversimplifies the variability, as existing models fail to account for its temporal oscillations 39 , 40 . The seasons are defined as December-January-February (DJF), March-April-May (MAM), June-July-August (JJA) and September-October-November (SON) in this study. 3. Results 3.1 Sensitivity of Aerosol Uptake Coefficients on Photochemical Ozone Regimes The aerosol uptake coefficient notably affects chemistry by modifying the interactions between aerosols and trace gases, including O₃, NO₂ and VOCs. Aerosols, consisting of fine particulate matter suspended in the atmosphere, serve as surfaces for heterogeneous reactions with gases. With an increase in the aerosol uptake coefficient, the likelihood of aerosols to react with radical species such as HO 2 improves, resulting in higher surface ozone formation from precursors. Here, we assess the effect of varying aerosol uptake coefficients (γHO 2 )—0, 0.1, 0.2 and 0.4—on the distribution of AIR and their relationship with NOx-limited and VOC-limited regimes across the tropical and extratropical locations and seasons. The aerosol uptake coefficient is essential in regulating the interaction between aerosols and atmospheric gas-phase chemistry, specifically in assessing the degree to which aerosols impede or facilitate chemical reactions in the atmosphere 41 , 42 . Our analysis shows that an increase in the γHO 2 results in a rise in the percentage of pixels categorised as the aerosol-inhibited area. This effect is especially evident in areas where NO x -limited regimes typically dominate. In the NH winter season, an increase in the aerosol absorption coefficient from 0.0 to 0.2 results in a substantial reduction of around 13% of the NOx-limited regime, whereas the aerosol-inhibited regime expands by almost 15% (compare Fig. 1 with Supplementary Fig. 1 ). Supplementary Figs. 1–3 show the spatial variation of the extent of AIR with different γHO 2 . This transition indicates that increased aerosol reactive uptake reduces the availability of reactive gases such as HO x and NO x , and thus, amplifying the AIR at the expense largely of the NOx-limited regime. A similar pattern exists in other seasons, characterised by a steady decline of 5–10% in NO x -limited regions and a commensurate rise in aerosol-inhibited areas. For instance, India is characterised consistently by an AIR across all seasons, but with occasional seasonal variations. In DJF, the Indo-Gangetic Plain (IGP) region, noted for its lush vegetation 43 , has higher VOC emissions, resulting in the formation of VOC-limited regimes. The elevated VOC emissions in these seasons may account for a shift in chemical regimes, since VOCs serve as precursors for atmospheric ozone generation, affecting the equilibrium between NOx-limited and VOC-limited regimes 44 . Also, during winter (DJF), lower temperatures and stagnant atmospheric conditions reduce the dispersion of pollutants, leading to high concentrations of VOCs 45 , 46 . Simultaneously, reduced NOx emissions, due to less efficient combustion processes, form a VOC-limited regime where ozone formation is constrained by the lack of available NOx to interact with VOCs 47 . Nevertheless, the AIR persists throughout the rest of the year (MAM, JJA, SON). East Asia also shows a consistent AIR for most of the year, except in SON. The shift from aerosol-inhibited to VOC-limited regimes in this area could be affected by seasonal fluctuations in emissions and atmospheric dynamics, particularly in autumn, owing to changes in vegetation and air mass transport 48 , 49 . The Sahara region in Africa also shows a year-round AIR. Nevertheless, during JJA, the extent of the area under AIR markedly diminishes compared to DJF and MAM. This decrease can be attributed to the decreasing dust concentration in the atmosphere during this period 50 , 51 . The Sahara, a substantial producer of dust, has its aerosol concentrations affected by the intensity and direction of trade winds, which can reduce dust particles over extensive regions during JJA, and thus reduce the impact of aerosol absorption in the area 52 . Also, weaker winds during the summer monsoon are less effective at picking up dust from the desert surface compared to the stronger westerly winds in winter 53 . The seasonal distribution of dust in the Sahara could influence the AIR, as dust aerosols interact with other atmospheric substances, affecting the heterogeneous chemical equilibrium. Furthermore, the extratropical regions of Northern North America and Southern South America show a pronounced seasonal change in AIR, characterised by widespread aerosol-inhibited regions during the winter months. The seasonal variations can be attributed to variations in atmospheric circulation patterns, temperature and aerosol concentrations, which fluctuate with the seasons and affect the degree of the AIR. In these regions, the winter months generally result in stable atmospheres with temperature inversions and augmented aerosol accumulation due to high heating demand, which could foster the formation of AIR 54 , 55 . 3.2 Surface O 3 sensitivity to aerosol uptake coefficients 3.2.1. Recent-past (2018) Figure 2 shows the percentage difference in surface ozone concentrations between a simulation with γHO 2 of 0 and 0.2, representing the impact of a reduction in the aerosol heterogeneous uptake sink on surface O 3 . ( Supplementary Figs. 4–6 show the percentage change in surface ozone concentrations for γHO 2 of 0 with 0.1 and 0.4, respectively). The γHO 2 of 0.2 is used as the baseline for analysing surface ozone variations in 2018 15,56,57 . Changes are most pronounced in the terrestrial regions, with negligible variation over the marine atmosphere. The most marked changes in surface ozone levels are observed in South and East Asia, where aerosols are most abundant globally currently and in 2018 58,59 , especially during the Northern Hemisphere winter, where ozone concentrations increase by about 8–10 ppb (30–40%) due to the weakening of the radical sink. Although surface ozone variations are considerable in these regions during different seasons, the percentage change generally lies between 20 and 30%. Conversely, central Africa exhibits minimal surface ozone variations, between 5 and 10%, with a modest reduction between the Southern Hemisphere summer (JJA) and autumn (SON). Eastern North America also shows an increase in surface ozone, but only during the Northern Hemisphere winter, which is generally within 10–15% in 2018. The regional distribution of ozone variations is uniform, but the extent of these changes is more substantial with elevated aerosol uptake coefficients. With a γHO 2 of 0.4, surface ozone increases by around 40–50% in East and South Asia, but this is limited to 15–25% when the HO 2 uptake coefficient of 0.1. This change indicates that the γHO 2 profoundly influences surface ozone concentrations, with more uptake resulting in more pronounced change in ozone levels, particularly in densely inhabited and industrialised regions such as East and South Asia. 3.2.2 Near-Future (2046) Using GCAP2.0, we modelled the future development of AIR globally under the SSP1–2.6, SSP2–4.5 and SSP5–8.5 scenarios to analyse the impact of aerosols on surface ozone levels by 2046. Figure 3 shows the photochemical ozone formation regimes under SSP2–4.5 and Supplementary Figs. 7 and 8 show the same under the SSP1-2.6 and SSP5-4.5 scenarios, respectively. AIR regions show a notable decrease in extent in future scenarios relative to current levels, as aerosols impede ozone formation via heterogeneous reactions 56 . Regions such as India and Sahara, which currently experience year-round AIR, exhibit a reduction in their extent. In the SSP2–4.5 scenario, the global extent of AIR shrinks to 10.8% in December–February (DJF), 3.6% in March–May (MAM), 1.2% in June–August (JJA) and 4.2% in September–November (SON), due to a mid-century decline in aerosol and precursor emissions in most world regions. The SSP1–2.6 scenario, characterised by even more stringent mitigation efforts and reduced emissions, indicates a further decline in the extent of AIR by about 8.5%, 1.2%, 0.9% and 4.4% in DJF, MAM, JJA and SON, respectively. The decline can be attributed to lower aerosol emissions and concentrations due to cleaner air policies, reduced emissions and alterations in the availability of aerosol precursors, resulting in diminished aerosol-induced inhibition of ozone formation 60 , 61 . In the SSP2-4.5 scenario, by 2046, we observe a significant reduction in the total aerosol surface area by about 50—100% (0.5–0.75 × 10⁻⁶ cm² cm⁻³) throughout much of East and South Asia and the Middle East, where the AIR regions dominated in the recent past ( Supplementary Fig. 9 ). This decrease could be attributed to the changes in aerosol emissions and atmospheric conditions influenced by socio-economic and climate trajectories. Furthermore, Black Carbon (BC) emissions in the near future are projected to rise by about 25—50% (0.25–0.5 × 10⁻⁶ cm² cm⁻³) across East Asia, signifying an escalating contribution to regional air pollution and possible effects on climate forcing in the SSP 2–4.5 emission scenario ( Supplementary Fig. 10 ). Sulphate aerosols will likely rise by 20—40% (2–3 × 10⁻⁶ cm² cm⁻³), especially during the Northern Hemisphere winter, across East Asia, North America, and Northern Asia 62 , which could be due to the changes in industrial emissions and atmospheric transport patterns ( Supplementary Fig. 11 ). Despite the overall reduction in the extent of AIR, their geographic distribution shifts, becoming more pronounced in areas such as the United States and Europe. This shift can be due to the near-zeroing of NOx emissions in these countries, which outpaces aerosol emissions reductions and indicates that aerosol-induced ozone inhibition may become considerable in densely populated areas there, intensifying air quality challenges in regions already facing health impacts from air pollution. The rise in sulphate aerosol surface area may contribute to the expansion of AIR in the US, notably in NH winter, as the spatial distribution of sulphate aerosols correlates highly with the extension of AIR there compared to that in 2018 ( Supplementary Fig. 11 ). Furthermore, by 2046, it is projected that nearly 90% of the globe will be in a NOx-limited regime across all SSP scenarios, suggesting that NO x will emerge as the primary limiting factor for ozone production. We also compare the effect of aerosol uptake on surface ozone levels under various SSP scenarios by comparing simulations that include aerosol uptake to those that do not, using a γHO 2 of 0.2. Figure 4 shows the absolute changes of surface ozone in the SSP2–4.5 scenario and Supplementary Figs. 12–14 show the percentage change in surface ozone with and without aerosol uptake for the different SSP scenarios compared to that of the recent past. We observe a consistent increase in ozone, especially in areas with high aerosols, including South and East Asia, with the reduction of the heterogenous radical sink. In the SSP1–2.6 scenario, ozone concentrations increase by approximately 5–10% in these regions throughout the seasons. However, the increase is small during MAM and JJA, within 5%. The increase in ozone levels is linked to a lower aerosol uptake, which facilitates the formation of ozone through heterogeneous reactions. There is also a notable increase in surface ozone in the Southern Hemisphere during the JJA and SON. In areas characterised by elevated aerosol concentrations, including South and East Asia, the SSP2–4.5 and SSP5–8.5 scenarios indicate a more pronounced increase in ozone levels, by approximately 10–20%, in contrast to the rise of 5–10% observed in the SSP1-2.6 scenario. This is much lower than recent past (2018) sensitivity of O 3 concentration to γHO 2 (30–40% in Asia), which further confirms that the AIR will reduce in the future. 3.2.3 Far - Future (2096) A comparison of these projected results for 2046 and 2096 reveals a decrease in the extent of AIR in 2096 under the SSP1-2.6 and SSP2-4.5 scenarios (Fig. 3 and Supplementary Fig. 15 ). The global extent of AIR diminishes from 10.8–7.4% in DJF, 3.6–1.3% in MAM, 1.2–0.4% in JJA, and 4.2–3.1% in SON. The shrink is particularly evident in the United States in the winter months (DJF). India continues to be primarily within a VOC-limited regime in both 2046 and 2096, with AIR decreasing to fewer than 10% globally by 2096. In Northern Europe, most regions continue to be in AIR in both 2046 and 2096. The observed spatial patterns are similar in both the SSP1–2.6 and SSP2–4.5 scenarios. However, under the extreme SSP5–8.5 scenario, a notable transformation takes place in North America, where northern areas of the US and Canada fall entirely in AIR, while southern regions of the US shift to a VOC-limited regime ( Figure S16 ). Furthermore, Southeast Asia is in aerosol-limited regime in 2046, but it turns out to be predominantly NOx-limited by 2096. The γHO 2 further impacts surface ozone concentrations, with regional variations observed during 2096 as well (Fig. 4 and Supplementary Figs. 17–19 ). For instance, in the SSP 2-4.5 scenario, the comparison of γHO 2 ranging from 0 to 0.2 indicates an increase in surface ozone levels by approximately 10–15% in the regions including South and East Asia during the DJF season. The northern extratropics, encompassing the US, Canada, China, Russia, and Europe, exhibit a notable reduction in ozone of 5–10%, except in JJA, during which a decrease of less than 5% is found. These changes are more pronounced in the SSP 5–8.5 scenario and less evident in SSP 1-2.6, analogous to that observed in 2046. An additional decrease in total aerosol levels by the end of the century compared to that of current levels, along with reductions in sulphate and black carbon emissions, is anticipated to reduce surface ozone, as shown in Supplementary Figs. 9–11 . Aerosols, especially sulphates and BC, influence ozone production, impact the availability of hydroxyl radicals (OH), and thus influence the extent of AIR. 3.3 Future projections of Surface Ozone 3.3.1 Near future (2046) We also estimate the total surface O 3 change from future to present. Surface ozone levels in the Northern Hemisphere tropics are projected to rise by approximately 50–75% by 2046 when compared to the current levels in 2018, with an increase of about 150–200% in areas such as South America and East Asia, although these variations are seasonal in the SP 2-4.5 scenario (Fig. 5 and Supplementary Fig. 21 ). Using our γHO 2 sensitivity simulations, we attribute that about 40–60% of the total O 3 enhancement is due to aerosol reductions in the AIR. Northern South America is expected to see a continuous increase in surface ozone of approximately 200%, irrespective of the seasons, whereas mid-Africa is anticipated to experience a steady rise of 50–100% year-round, with an exception in DJF. India also has a seasonal rise of about 30 ppb in surface ozone levels, especially during JJA. The observed spatial patterns are uniform across all SSP scenarios (SSP1–2.6, SSP2–4.5 and SSP5–8.5), with more increase in ozone levels noted in the SSP2–4.5 and SSP5–8.5 scenarios, which is about 20–30% higher when compared to current levels ( Supplementary Figs. 20–22) . The distribution of ozone in higher emission scenarios shows a more widespread pattern, mainly in the Northern Hemisphere extratropics, where an increase of 50–75% is noted throughout the globe. Nevertheless, regions within AIR regions in the near future mainly affects North America, Northern Europe, and East Asia, especially during the Northern Hemisphere winter, with an approximate increase of 50–60% surface ozone over North America and Northern Europe, and about 20–30% over Northern Asia. Biogenic emissions strongly impact ozone formation, which is also impacted by atmospheric NO 2 concentrations 63 . The oxidation of VOCs contributes to the generation of secondary organic aerosols, with the degree of contribution influenced by temperature, vegetation type, and foliar mass 64 . These characteristics are acutely responsive to climate change and alterations in vegetation distribution 65 . For instance, Supplementary Fig. 23 shows the projected global rise in agricultural land and forest cover, which will subsequently increase biogenic VOC emissions. Furthermore, agricultural waste burning may increase by 1.5 to 2 times across different emission scenarios by the end of the century, resulting in elevated NO x and VOC emissions, enhancing ozone formation from these precursors. Urbanisation, energy use and air pollution are closely related. Urban Heat Islands (UHI) in densely populated cities raise temperatures, and thus, increase the demand for cooling energy 66 , 67 . This results in increased residential emissions, but it varies by region. Specifically, Supplementary Figs. 24 and 25 show that NO x and VOC emissions in the Middle East and Africa will increase in the future, and exacerbate the secondary production of ozone. In these areas, residential emissions are projected to rise until the mid-century, before reverting to historical levels by 2100. These findings emphasise the necessity for efficient control methods to guarantee improved air quality in the future. Tian et al. 68 studied energy consumption and air pollution trends in China since 1990, providing recommendations for sustainable energy utilisation, air pollution management, and CO 2 reduction. By 2003, China's total primary energy consumption had attained 1,678 million tonnes of standard coal equivalent. Consequently, emissions of SO 2 and NOx increased to 21.58 million tonnes and 16.13 million tonnes, respectively. This suggests that more rigorous laws, standards, and efficient economic strategies are needed for resolving those challenges. Supplementary Table 1 lists the energy demand in various sectors globally. Thus, the increasing demand of energy would lead to more emissions, but can be tackled using a clean and sustainable practice for energy production 69 . Also, climate change is anticipated to modify atmospheric circulation and precipitation patterns, impacting meteorological conditions that deteriorate air quality. In a warming climate, the buildup of particulate matter in the atmosphere, especially during winter, is expected to rise due to stagnation. This stagnation is characterised by lack of precipitation, weak surface winds and poor vertical mixing, all of which facilitate the accumulation of pollution at the surface. Stagnation events can exacerbate PM 2.5 pollution even in the absence of substantial emissions. Zhou et al. 70 found that changes in stagnation patterns are influenced by both global CO 2 -induced circulation modifications and local aerosol-driven meteorological reactions. By 2100, winter stagnation in the Indo-Gangetic Plain (IGP) is projected to extend by 7 ± 3 days, resulting in an increase in PM 2.5 concentrations by roughly 7 µg/m³ under high-warming and high-aerosol scenarios. Nevertheless, annual stagnation instances are anticipated to diminish in most of India. Horton et al. 71 used an air stagnation index and a series of bias-corrected climate model simulations to evaluate potential alterations in stagnation frequency and duration due to global warming. Their study indicates that stagnation events may rise in regions encompassing 55% of the global population, with the affected population in these areas being ten-fold greater than in regions experiencing a decline in stagnation. By the late twenty-first century, substantial increases—up to 40 additional days a year—are predicted for many areas in the tropics, subtropics, and certain mid-latitude regions. These alterations will probably exert most notable impacts on countries such as India, Mexico, and the western United States, where the large populations coincide with prolonged stagnation episodes. This stagnation may result in the prolonged existence of trace gases in the atmosphere, and thus, increase ozone exposure in the densely populated areas. 3.3.2 Far - future (2096) In 2096, the change in surface ozone levels were smaller than those in 2046 across all SSP scenarios, as shown in Fig. 5 and Supplementary Figs. 26–28 . The reduction is attributable to several factors, including stricter emission controls, enhanced air quality regulations, and possible alterations in atmospheric dynamics that may decrease ozone formation 72 , 73 . The dispersion of ozone from hotspot regions diminishes by roughly 25–50% in a large number of areas. The reduction is noticeable particularly in the tropical marine atmosphere. The spatial extent of hotspot regions in 2096 is similar to that of 2046, with consistently higher ozone levels (100–150%) in regions such as northern South America and Central Africa, irrespective of the seasons. These regions may persistently experience increasing ozone attributable to local sources of ozone precursors, including biomass burning or industrial emissions, together with climate conditions favourable to ozone formation 74 – 77 . East and South Asia show an increase in ozone during DJF and JJA, likely influenced by seasonal emission variations, including elevated industrial activity in winter and agricultural burning in summer 78 , 79 . Furthermore, surface ozone levels in North America are projected to be higher by 20–30 ppb in 2096 compared to that of 2018, potentially attributable to changes in transportation emissions, urbanisation, or a lag in atmospheric chemistry's response to reductions in precursor pollutants 80 , 81 . 4. Discussion A comparison of Fig. 4 with Fig. 5 shows the impact of γHO 2 on surface ozone concentrations in both the near and distant future, compared to the recent past. In comparing the results from 2018 to those from 2046, East and South Asia have the most dominant effect of γHO 2 on ozone concentrations, with an increase of around 10 ppb, which is nearly four times less than the contribution noted in the recent past (as shown in Fig. 2 ). Future projections indicate that surface ozone levels in India will significantly rise during summer monsoon (JJA), with an overall increase of 30 ppb, of which 10 ppb is ascribed to the impact of γHO 2 , or around 30–40% of the total increase. In East Asia, the most significant increase is anticipated in winter, when aerosol effects are more evident, contributing 5–7.5 ppb to the total 30 ppb rise, corresponding to approximately 25% of the ozone increase. In West Africa, γHO 2 is expected to contribute roughly 5 ppb during the dry season (DJF), whereas Central Africa will have a contribution of about 5 ppb in the fall (SON). The anticipated total increase in surface ozone in West and Central Africa is around 15–20 ppb, with γHO 2 contributing 25–30% to this rise. By 2096, the influence of γHO 2 on surface ozone is expected to continue to decline, with the most significant effect prevailing in India, where the contribution will be less than 5 ppb, which represents approximately 20% of the overall rise. Conversely, by the end of the century, Central and West Africa will continue to have an increased impact than East Asia, although this will account for merely 10% of the total ozone enhancement attributed to higher aerosol uptake by HO 2 . Additionally, Fig. 5 also shows that regions that have lower surface ozone show more variation in the future, approximately 100–200% (20–40 ppb). Ozone precursors are, in general, more difficult to control and ozone levels have a larger impact from remote sources as well as increasing methane concentrations 82 . We found that in the SSP scenarios, regional ozone levels do show clear increase in the future. For instance, Northern South America currently has an ozone level of 10 ppb, which is projected to increase by around 200%, reaching about 30–40 ppb by the end of the century in the SSP2–4.5 scenario. This is also analogous to several other regions, including Northern Europe and East Asia. Current hotspot regions, such as Central Africa, show an increase of 50–100%, resulting in levels around 20–30 ppb by 2100. India currently has higher ozone levels (70–80 ppb), which are projected to remain stable by 2100. This indicates that the majority of worldwide regions would experience ozone levels of 40–80 ppb in the future, which is above the World Health Organization's recommended guideline, increasing the population's susceptibility to pre-existing health problems associated with air pollution. The results show a substantial influence of γHO 2 on the distribution of aerosol-inhibited regimes and surface ozone concentrations in different global regions. The increase in γHO 2 correlates with an expansion in the AIR, especially in otherwise NOx-limited regions like South and East Asia, particularly evident in colder months when lower temperatures and stagnant atmospheric conditions intensify aerosol effects. Future projections across various SSP scenarios indicate a global reduction in AIR extent, linked to decreased aerosol concentrations and more stringent emission regulations. The incorporation of these iterative impacts could modify the concentrations of these contaminants 82 . The future trajectory of air quality, especially with higher ozone and lower aerosol levels, poses considerable concerns and health dangers worldwide. Projections based on the SSP-RCP scenarios indicate geographical variances in ozone concentrations, with regions such as Northern South America, Northern Europe and East Asia anticipated to experience notable increases by the end of the century. The rise in ozone is primarily influenced by many elements, such as aerosol reactive uptake, agricultural emissions, forest fires and the impact of climate change on vegetation and air circulation. The increase in biogenic VOC emissions, coupled with improved agricultural techniques and garbage incineration, will intensify ozone formation, particularly in areas such as Africa and Asia 83,84 . The interaction between urbanisation, energy consumption and air pollution highlights the pressing necessity for greener energy alternatives and efficient pollution mitigation strategies. Climate-induced alterations in weather patterns, including stagnation episodes, would exacerbate particulate matter concentrations and extend exposure to detrimental pollutants, especially in densely populated regions. Therefore, efforts to reduce aerosol concentrations must be integrated with policies that tackle the broader impacts of climate change, including reducing the possibility of wildfires and agricultural emissions, as these elements will intensify ozone formation. Furthermore, policies that advocate for cleaner energy choices, urban air quality control and sustainable agricultural methods will be essential in alleviating the total environmental burden. Considering the health hazards linked to increased ozone concentrations, it is imperative for states to collaborate in establishing and enforcing international norms in accordance with the WHO's recommendations. These initiatives must encompass investment in research and technology to assess air quality and evaluate the efficacy of executed actions. Declarations Credit authorship contribution statement GSG: Writing – review & editing, Writing – original draft, Visualization, Validation, Software, Methodology, Investigation, Formal analysis, Data curation. DMW: Writing – review & editing, Writing – original draft, Supervision, Visualization, Validation, Software, Methodology, Investigation, Conceptualisation . JK: Writing – review & editing, Writing – original draft, Supervision, Visualization, Validation, Methodology, Investigation, Conceptualisation. Acknowledgements We thank all the data managers and the scientists who made available those data for this study. GSG acknowledges the Prime Minister's Research Fellowship (PMRF; Grant No: 2402787), Ministry of Education, India, for funding his Doctoral study at IIT KGP and the United States India Education Foundation for his grant through the Fulbright-Kalam Climate fellowship for Doctoral Research (Grant No: 3067/FNDR/2024-2025) at the Lamont-Doherty Earth Observatory and Columbia Climate School, Columbia University, New York. JK and GSG thank the Director, Indian Institute of Technology Kharagpur (IIT Kgp), HoC, CORAL IIT Kgp and the Ministry of Education (MoE) for facilitating the study. Data availability GEOS CHEM and GCAP model is available via https://geos-chem.readthedocs.io/en/stable/ SSP data is available via https://tntcat.iiasa.ac.at/SspDb Competing interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. References Brasseur, G.P. and Jacob, D.J., 2017. Modeling of atmospheric chemistry. Cambridge University Press. Macintyre, H.L. and Evans, M.J., 2010. Sensitivity of a global model to the uptake of N 2 O 5 by tropospheric aerosol. Atmospheric Chemistry and Physics, 10(15),7409–7414. Dentener, F.J. and Crutzen, P.J., 1993. Reaction of N2O5 on tropospheric aerosols: Impact on the global distributions of NO x, O3 and OH. Journal of Geophysical Research: Atmospheres, 98(D4), 7149–7163. Kuttippurath, J., Abbhishek, K., Gopikrishnan, G.S. and Pathak, M., 2022. Investigation of long–term trends and major sources of atmospheric HCHO over India. Environmental Challenges, 7, 100477. Kuttippurath, J., Gopikrishnan, G.P., Müller, R., Godin-Beekmann, S. and Brioude, J., 2024. No severe ozone depletion in the tropical stratosphere in recent decades. Atmospheric Chemistry and Physics, 24(11), 6743–6756. Gopikrishnan, G.S., Kuttippurath, J., Raj, S., Singh, A. and Abbhishek, K., 2022. Air quality during the COVID–19 lockdown and unlock periods in India analyzed using satellite and ground-based measurements. Environmental Processes, 9(2), 28. Gopikrishnan, G.S. and Kuttippurath, J., 2024. Global tropical and extra-tropical tropospheric ozone trends and radiative forcing deduced from satellite and ozonesonde measurements for the period 2005–2020. Environmental Pollution, 361, 124869. Tan, Z., Lu, K., Jiang, M., Su, R., Dong, H., Zeng, L., Xie, S., Tan, Q. and Zhang, Y., 2018. Exploring ozone pollution in Chengdu, southwestern China: A case study from radical chemistry to O3-VOC-NOx sensitivity. Science of the Total Environment, 636, 775–786. Szopa, S., Aumont, B. and Madronich, S., 2005. Assessment of the reduction methods used to develop chemical schemes: building of a new chemical scheme for VOC oxidation suited to three-dimensional multiscale HO x-NO x-VOC chemistry simulations. Atmospheric Chemistry and Physics, 5(9), 2519–2538. Duncan, B.N., Yoshida, Y., Olson, J.R., Sillman, S., Martin, R.V., Lamsal, L., Hu, Y., Pickering, K.E., Retscher, C., Allen, D.J. and Crawford, J.H., 2010. Application of OMI observations to a space-based indicator of NOx and VOC controls on surface ozone formation. Atmospheric Environment, 44(18), 2213–2223. Westervelt, D.M., Ma, C.T., He, M.Z., Fiore, A.M., Kinney, P.L., Kioumourtzoglou, M.A., Wang, S., Xing, J., Ding, D. and Correa, G., 2019. Mid-21st century ozone air quality and health burden in China under emissions scenarios and climate change. Environmental Research Letters, 14(7), 074030. Fiore, A.M., Mickley, L.J., Zhu, Q. and Baublitz, C.B., 2024. Climate and tropospheric oxidizing capacity. Annual Review of Earth and Planetary Sciences, 52. Wang, Y., Wild, O., Chen, X., Wu, Q., Gao, M., Chen, H., Qi, Y. and Wang, Z., 2020. Health impacts of long-term ozone exposure in China over 2013–2017. Environment International, 144, 106030. Zhao, K., Yuan, Z., Wu, Y., Huang, J., Yang, F., Zhang, X., Huang, D. and Jiang, R., 2023. Identification of synergistic control for ozone and PM2.5 pollution during a large-scale emission reduction in China. Atmospheric Research, 295, 107025. Ivatt, P.D., Evans, M.J. and Lewis, A.C., 2022. Suppression of surface ozone by an aerosol-inhibited photochemical ozone regime. Nature Geoscience, 15(7), 536–540. Liu, Q., Liu, T., Chen, Y., Xu, J., Gao, W., Zhang, H. and Yao, Y., 2019. Effects of aerosols on the surface ozone generation via a study of the interaction of ozone and its precursors during the summer in Shanghai, China. Science of the Total Environment, 675, 235–246. Qu, Y., Voulgarakis, A., Wang, T., Kasoar, M., Wells, C., Yuan, C., Varma, S. and Mansfield, L., 2021. A study of the effect of aerosols on surface ozone through meteorology feedbacks over China. Atmospheric Chemistry and Physics, 21(7), 5705–5718. Van Vuuren, D.P., Riahi, K., Calvin, K., Dellink, R., Emmerling, J., Fujimori, S., Samir, K.C., Kriegler, E. and O’Neill, B., 2017. The Shared Socio-economic Pathways: Trajectories for human development and global environmental change. Global Environmental Change, 42, 148–152. O’Neill, B.C., Kriegler, E., Riahi, K., Ebi, K.L., Hallegatte, S., Carter, T.R., Mathur, R. and Van Vuuren, D.P., 2014. A new scenario framework for climate change research: the concept of shared socioeconomic pathways. Climatic Change, 122, pp.387-400. Gidden, M.J., Riahi, K., Smith, S.J., Fujimori, S., Luderer, G., Kriegler, E., Van Vuuren, D.P., Van Den Berg, M., Feng, L., Klein, D. and Calvin, K., 2019. Global emissions pathways under different socioeconomic scenarios for use in CMIP6: a dataset of harmonized emissions trajectories through the end of the century. Geoscientific Model Development, 12(4), 1443–1475. Arnell, N.W., Lowe, J.A., Bernie, D., Nicholls, R.J., Brown, S., Challinor, A.J. and Osborn, T.J., 2019. The global and regional impacts of climate change under representative concentration pathway forcings and shared socioeconomic pathway socioeconomic scenarios. Environmental Research Letters, 14(8), 084046. Liao, K.J., Tagaris, E., Napelenok, S.L., Manomaiphiboon, K., Woo, J.H., Amar, P., He, S. and Russell, A.G., 2008. Current and future linked responses of ozone and PM2. 5 to emission controls. Environmental Science and Technology, 42, 4670–4675 Rypdal, K., Berntsen, T., Fuglestvedt, J.S., Aunan, K., Torvanger, A., Stordal, F., Pacyna, J.M. and Nygaard, L.P., 2005. Tropospheric ozone and aerosols in climate agreements: scientific and political challenges. Environmental Science & Policy, 8(1), 29–43. Zhang, L., Jacob, D.J., Downey, N.V., Wood, D.A., Blewitt, D., Carouge, C.C., van Donkelaar, A., Jones, D.B., Murray, L.T. and Wang, Y., 2011. Improved estimate of the policy-relevant background ozone in the United States using the GEOS-Chem global model with 1/2× 2/3 horizontal resolution over North America. Atmospheric Environment, 45(37), 6769–6776. Kim, P.S., Jacob, D.J., Fisher, J.A., Travis, K., Yu, K., Zhu, L., Yantosca, R.M., Sulprizio, M.P., Jimenez, J.L., Campuzano-Jost, P. and Froyd, K.D., 2015. Sources, seasonality and trends of southeast US aerosol: an integrated analysis of surface, aircraft and satellite observations with the GEOS-Chem chemical transport model. Atmospheric Chemistry and Physics, 15(18), 10411–10433. Lin, H., Long, M.S., Sander, R., Sandu, A., Yantosca, R.M., Estrada, L.A., Shen, L. and Jacob, D.J., 2023. An Adaptive Auto‐Reduction Solver for Speeding Up Integration of Chemical Kinetics in Atmospheric Chemistry Models: Implementation and Evaluation in the Kinetic Pre‐Processor (KPP) Version 3.0. 0. Journal of Advances in Modeling Earth Systems, 15(2), e2022MS003293. Bates, K.H., Evans, M.J., Henderson, B.H. and Jacob, D.J., 2024. Impacts of updated reaction kinetics on the global GEOS-Chem simulation of atmospheric chemistry. Geoscientific Model Development, 17(4), 1511–1524. Travis, K.R., Jacob, D.J., Fisher, J.A., Kim, P.S., Marais, E.A., Zhu, L., Yu, K., Miller, C.C., Yantosca, R.M., Sulprizio, M.P. and Thompson, A.M., 2016. Why do models overestimate surface ozone in the Southeast United States?. Atmospheric Chemistry and Physics, 16(21), 13561–13577. David, L.M., Ravishankara, A.R., Brewer, J.F., Sauvage, B., Thouret, V., Venkataramani, S. and Sinha, V., 2019. Tropospheric ozone over the Indian subcontinent from 2000 to 2015: Data set and simulation using GEOS-Chem chemical transport model. Atmospheric Environment, 219, 117039. Christiansen, A., Mickley, L.J., Liu, J., Oman, L.D. and Hu, L., 2022. Multidecadal increases in global tropospheric ozone derived from ozonesonde and surface site observations: can models reproduce ozone trends?. Atmospheric Chemistry and Physics, 22(22), 14751–14782. Mao, Y.H., Shang, Y., Liao, H., Cao, H., Qu, Z. and Henze, D.K., 2024. Sensitivities of ozone to its precursors during heavy ozone pollution events in the Yangtze River Delta using the adjoint method. Science of the Total Environment, 925, 171585. Wu, S., Mickley, L.J., Jacob, D.J., Logan, J.A., Yantosca, R.M. and Rind, D., 2007. Why are there large differences between models in global budgets of tropospheric ozone?. Journal of Geophysical Research: Atmospheres, 112(D5). Murray, L.T., Mickley, L.J., Kaplan, J.O., Sofen, E.D., Pfeiffer, M. and Alexander, B., 2014. Factors controlling variability in the oxidative capacity of the troposphere since the Last Glacial Maximum. Atmospheric Chemistry and Physics, 14(7), 3589–3622. Kelley, M., Schmidt, G.A., Nazarenko, L.S., Bauer, S.E., Ruedy, R., Russell, G.L., Ackerman, A.S., Aleinov, I., Bauer, M., Bleck, R. and Canuto, V., 2020. GISS‐E2. 1: Configurations and climatology. Journal of Advances in Modeling Earth Systems, 12(8), e2019MS002025. Miller, R.L., Schmidt, G.A., Nazarenko, L.S., Bauer, S.E., Kelley, M., Ruedy, R., Russell, G.L., Ackerman, A.S., Aleinov, I., Bauer, M. and Bleck, R., 2021. CMIP6 historical simulations (1850–2014) with GISS‐E2. 1. Journal of Advances in Modeling Earth Systems, 13(1), e2019MS002034. Kolb, C.E., Cox, R.A., Abbatt, J.P.D., Ammann, M., Davis, E.J., Donaldson, D.J., Garrett, B.C., George, C., Griffiths, P.T., Hanson, D.R. and Kulmala, M., 2010. An overview of current issues in the uptake of atmospheric trace gases by aerosols and clouds. Atmospheric Chemistry and Physics, 10(21), 10561–10605. Christian, K.E., Brune, W.H., Mao, J. and Ren, X., 2018. Global sensitivity analysis of GEOS-Chem modeled ozone and hydrogen oxides during the INTEX campaigns. Atmospheric Chemistry and Physics, 18(4), 2443–2460. Mao, J., Jacob, D.J., Evans, M.J., Olson, J.R., Ren, X., Brune, W.H., St Clair, J.M., Crounse, J.D., Spencer, K.M., Beaver, M.R. and Wennberg, P.O., 2010. Chemistry of hydrogen oxide radicals (HO x) in the Arctic troposphere in spring. Atmospheric Chemistry and Physics, 10(13), 5823–5838. Stavrakou, T., Müller, J.F., Boersma, K.F., Van Der A, R.J., Kurokawa, J., Ohara, T. and Zhang, Q., 2013. Key chemical NO x sink uncertainties and how they influence top-down emissions of nitrogen oxides. Atmospheric Chemistry and Physics, 13(17), 9057–9082. Sheehy, P.M., Volkamer, R., Molina, L.T. and Molina, M.J., 2010. Oxidative capacity of the Mexico City atmosphere–Part 2: A RO x radical cycling perspective. Atmospheric Chemistry and Physics, 10(14), 6993–7008. Andreae, M.O. and Crutzen, P.J., 1997. Atmospheric aerosols: Biogeochemical sources and role in atmospheric chemistry. Science, 276(5315), 1052-1058. McNeill, V.F., 2017. Atmospheric aerosols: clouds, chemistry, and climate. Annual Review of Chemical and Biomolecular Engineering, 8(1), 427–444. Kuttippurath, J. and Kashyap, R., 2023. Greening of India: forests or croplands?. Applied Geography, 161, 103115. Kuttippurath, J., Abbhishek, K., Gopikrishnan, G.S. and Pathak, M., 2022. Investigation of long–term trends and major sources of atmospheric HCHO over India. Environmental Challenges, 7, 100477. Yadav, M., Soni, K., Soni, B.K., Singh, N.K. and Bamniya, B.R., 2019. Source apportionment of particulate matter, gaseous pollutants, and volatile organic compounds in a future smart city of India. Urban Climate, 28, 100470. Sahu, L.K., Yadav, R. and Pal, D., 2016. Source identification of VOCs at an urban site of western India: Effect of marathon events and anthropogenic emissions. Journal of Geophysical Research: Atmospheres, 121(5), 2416–2433. Carter, W.P. and Seinfeld, J.H., 2012. Winter ozone formation and VOC incremental reactivities in the Upper Green River Basin of Wyoming. Atmospheric Environment, 50, 255–266. Xu, L., Myneni, R.B., Chapin III, F.S., Callaghan, T.V., Pinzon, J.E., Tucker, C.J., Zhu, Z., Bi, J., Ciais, P., Tømmervik, H. and Euskirchen, E.S., 2013. Diminished temperature and vegetation seasonality over northern high latitudes. Nature Climate Change, 3, 581–586. Yi, C., Wei, S. and Hendrey, G., 2014. Warming climate extends dryness-controlled areas of terrestrial carbon sequestration. Scientific Reports, 4(1), 5472. Harr, B., Pu, B. and Jin, Q., 2024. The emission, transport, and impacts of the extreme Saharan dust storm of 2015. Atmospheric Chemistry and Physics, 24(15), 8625–8651. Caton Harrison, T., Washington, R., Engelstaedter, S., Jones, R.G. and Savage, N.H., 2021. Influence of Orography Upon Summertime Low‐Level Jet Dust Emission in the Central and Western Sahara. Journal of Geophysical Research: Atmospheres, 126(23), e2021JD035025. Prospero, J.M., 2007. African dust: Its large-scale transport over the Atlantic ocean and its impact on the Mediterranean region. In Regional climate variability and its impacts in the Mediterranean area (15–38). Dordrecht: Springer Netherlands. Zhang, M., Mu, P., Chen, X., Wu, D., Lu, F., Qi, P., Li, L.B. and Gong, W., 2023. Study on the Optical–Physical Properties of Aerosol Layers in Africa Based on a Laser Satellite. Atmosphere, 14(10), 1524. Hoelzemann, J.J., Longo, K.M., Fonseca, R.M., Do RosáRio, N.M., Elbern, H., Freitas, S.R. and Pires, C., 2009. Regional representativity of AERONET observation sites during the biomass burning season in South America determined by correlation studies with MODIS Aerosol Optical Depth. Journal of Geophysical Research: Atmospheres, 114(D13). Piketh, S.J., Swap, R.J., Maenhaut, W., Annegarn, H.J. and Formenti, P., 2002. Chemical evidence of long‐range atmospheric transport over southern Africa. Journal of Geophysical Research: Atmospheres, 107(D24), ACH-7. Jacob, D.J., 2000. Heterogeneous chemistry and tropospheric ozone. Atmospheric Environment, 34(12-14), 2131–2159. Li, M., Su, H., Li, G., Ma, N., Pöschl, U. and Cheng, Y., 2019. Relative importance of gas uptake on aerosol and ground surfaces characterized by equivalent uptake coefficients. Atmospheric Chemistry and Physics, 19(16), 10981–11011. Kuttippurath, J. and Raj, S., 2021. Two decades of aerosol observations by AATSR, MISR, MODIS and MERRA-2 over India and Indian Ocean. Remote Sensing of Environment, 257, 112363. Zhang, Z., Wu, W., Fan, M., Wei, J., Tan, Y. and Wang, Q., 2019. Evaluation of MAIAC aerosol retrievals over China. Atmospheric Environment, 202, 8-16. Kloster, S., Dentener, F., Feichter, J., Raes, F., Van Aardenne, J., Roeckner, E., Lohmann, U., Stier, P. and Swart, R., 2008. Influence of future air pollution mitigation strategies on total aerosol radiative forcing. Atmospheric Chemistry and Physics, 8(21), 6405–6437. Amann, M., Kiesewetter, G., Schöpp, W., Klimont, Z., Winiwarter, W., Cofala, J., Rafaj, P., Höglund-Isaksson, L., Gomez-Sabriana, A., Heyes, C. and Purohit, P., 2020. Reducing global air pollution: the scope for further policy interventions. Philosophical Transactions of the Royal Society A, 378(2183), 20190331. Pye, H.O.T., Liao, H., Wu, S., Mickley, L.J., Jacob, D.J., Henze, D.K. and Seinfeld, J.H., 2009. Effect of changes in climate and emissions on future sulfate‐nitrate‐ammonium aerosol levels in the United States. Journal of Geophysical Research: Atmospheres, 114(D1). Schade, G. W., and A. H. Goldstein (2001), Fluxes of oxygenated volatile organic compounds from a ponderosa pine plantation, Journal of Geophysical Research, 106, 3111–3123. Tsigaridis, K., and M. Kanakidou (2003), Global modelling of secondary organic aerosol in the troposphere: A sensitivity analysis, Atmospheric Chemistry and Physics, 3, 1849–1869. Lathiere, J., Hauglustaine, D.A., De Noblet‐Ducoudré, N., Krinner, G. and Folberth, G.A., 2005. Past and future changes in biogenic volatile organic compound emissions simulated with a global dynamic vegetation model. Geophysical Research Letters, 32(20). Sun, Y. and Augenbroe, G., 2014. Urban heat island effect on energy application studies of office buildings. Energy and Buildings, 77, 171–179. Raj, S., Paul, S.K., Chakraborty, A. and Kuttippurath, J., 2020. Anthropogenic forcing exacerbating the urban heat islands in India. Journal of Environmental Management, 257, 110006. Tian, H.Z., Hao, J.M., Hu, M.Y. and Nie, Y.F., 2007. Recent trends of energy consumption and air pollution in China. Journal of Energy Engineering, 133(1), 4–12. Daioglou, V., Faaij, A.P., Saygin, D., Patel, M.K., Wicke, B. and van Vuuren, D.P., 2014. Energy demand and emissions of the non-energy sector. Energy & Environmental Science, 7(2), 482–498. Zhou, M., Xie, Y., Wang, C., Shen, L. and Mauzerall, D.L., 2024. Impacts of current and climate induced changes in atmospheric stagnation on Indian surface PM2. 5 pollution. Nature Communications, 15(1), 7448. Horton, D.E., Skinner, C.B., Singh, D. and Diffenbaugh, N.S., 2014. Occurrence and persistence of future atmospheric stagnation events. Nature Climate Change, 4(8), 698–703. Weaver, A.J., Zickfeld, K., Montenegro, A. and Eby, M., 2007. Long term climate implications of 2050 emission reduction targets. Geophysical Research Letters, 34(19). Lyon, C., Saupe, E.E., Smith, C.J., Hill, D.J., Beckerman, A.P., Stringer, L.C., Marchant, R., McKay, J., Burke, A., O’Higgins, P. and Dunhill, A.M., 2022. Climate change research and action must look beyond 2100. Global Change Biology, 28(2), 349–361. Liousse, C., Assamoi, E., Criqui, P., Granier, C. and Rosset, R., 2014. Explosive growth in African combustion emissions from 2005 to 2030. Environmental Research Letters, 9(3), 035003. Calvin, K., Pachauri, S., De Cian, E. and Mouratiadou, I., 2016. The effect of African growth on future global energy, emissions, and regional development. Climatic Change, 136, 109–125. Burton, C., Kelley, D.I., Jones, C.D., Betts, R.A., Cardoso, M. and Anderson, L., 2022. South American fires and their impacts on ecosystems increase with continued emissions. Climate Resilience and Sustainability, 1(1), p.e8. Martínez, S.H., Koberle, A., Rochedo, P., Schaeffer, R., Lucena, A., Szklo, A., Ashina, S. and van Vuuren, D.P., 2015. Possible energy futures for Brazil and Latin America in conservative and stringent mitigation pathways up to 2050. Technological Forecasting and Social Change, 98, 186–210. Kuttippurath, J., Singh, A., Dash, S.P., Mallick, N., Clerbaux, C., Van Damme, M., Clarisse, L., Coheur, P.F., Raj, S., Abbhishek, K. and Varikoden, H., 2020. Record high levels of atmospheric ammonia over India: Spatial and temporal analyses. Science of the Total Environment, 740, 139986. Tao, M., Chen, L., Wang, Z., Tao, J. and Su, L., 2013. Satellite observation of abnormal yellow haze clouds over East China during summer agricultural burning season. Atmospheric environment, 79, 632–640. Moghani, M. and Archer, C.L., 2020. The impact of emissions and climate change on future ozone concentrations in the USA. Air Quality, Atmosphere & Health, 13, 1465–1476. Archibald, A.T., Neu, J.L., Elshorbany, Y.F., Cooper, O.R., Young, P.J., Akiyoshi, H., Cox, R.A., Coyle, M., Derwent, R.G., Deushi, M. and Finco, A., 2020. Tropospheric Ozone Assessment Report: A critical review of changes in the tropospheric ozone burden and budget from 1850 to 2100. Elementa Science of the Anthropocene, 8(1), 034. Rao, S., Klimont, Z., Smith, S.J., Van Dingenen, R., Dentener, F., Bouwman, L., Riahi, K., Amann, M., Bodirsky, B.L., van Vuuren, D.P. and Reis, L.A., 2017. Future air pollution in the Shared Socio-economic Pathways. Global Environmental Change, 42, 346–358. Dhamodharan, K., Varma, V.S., Veluchamy, C., Pugazhendhi, A. and Rajendran, K., 2019. Emission of volatile organic compounds from composting: A review on assessment, treatment and perspectives. Science of The Total Environment, 695, 133725. Duan, C., Liao, H., Wang, K. and Ren, Y., 2023. The research hotspots and trends of volatile organic compound emissions from anthropogenic and natural sources: A systematic quantitative review. Environmental Research, 216, 114386. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5932296","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":410464210,"identity":"2ec934ca-7d92-4e0a-8f26-b76ca4f70ad1","order_by":0,"name":"Daniel Westervelt","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABEklEQVRIie2QMUsDMRiGPzhIl3C35hDOv/CVg7pIf0uC4OKdCC4dhA4HdRHn81+0FNL1joBdKl0Pspx7hUxSUMQ7KVXkIh0d8pAhJO/DlzcADsd/pGjXFUDQA/w68AEI8N2VXWnCYbZTyCEKtGFUPxX4Q/GXT2VhUIq58ma1gWFE2MV5Xd9A5Fe8UwlXl7zMUQupyHU/h7OYsHSB/BHi0KJgkaCiqFOp6OCIQiEmLJWMExBTm7LeoHpvlHlGT96+lQ8YW5UqaYvrdOrRgbdXxAQ42rpUGyzvUI/zpkuYY9OFvixQ3LP+w6ru/rF1EpvtSMfBbTYzZjSMgl4qn7evp8f+snvK73fud+yQuMPhcDgsfAIcd2VrVI+ZCgAAAABJRU5ErkJggg==","orcid":"","institution":"Columbia University","correspondingAuthor":true,"prefix":"","firstName":"Daniel","middleName":"","lastName":"Westervelt","suffix":""},{"id":410464211,"identity":"d1c6cd04-b93c-4685-8ec9-c51cd4267c5a","order_by":1,"name":"G S Gopikrishnan","email":"","orcid":"","institution":"CORAL, Indian Institute of Technology Kharagpur, India","correspondingAuthor":false,"prefix":"","firstName":"G","middleName":"S","lastName":"Gopikrishnan","suffix":""},{"id":410464212,"identity":"e99fd43a-0bba-49f1-9daa-6c1c977ad56d","order_by":2,"name":"Jayanarayanan Kuttippurath","email":"","orcid":"","institution":"CORAL, Indian Institute of Technology Kharagpur, India","correspondingAuthor":false,"prefix":"","firstName":"Jayanarayanan","middleName":"","lastName":"Kuttippurath","suffix":""}],"badges":[],"createdAt":"2025-01-30 19:23:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5932296/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5932296/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41612-025-01048-2","type":"published","date":"2025-04-25T15:57:53+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":75445358,"identity":"3726e383-594a-4a7d-b9a2-0dc26310d58e","added_by":"auto","created_at":"2025-02-04 16:28:09","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":174984,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePhotochemical Ozone formation regimes in 2018. (a-d) \u003c/strong\u003eThe regional distribution of various ozone generation photochemical regimes modelled with γHO\u003csub\u003e2\u003c/sub\u003e of 0.2 in 2018. Here, DJF is December-January-February, MAM is March-April-May, JJA is June-July-August, SON is September-October-November, USA is United States of America, EU is Europe, NNA is Northern North America, NSA is Northern South America and SSA is Southern South America.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5932296/v1/07844eb48b79dfcb899a4294.png"},{"id":75445359,"identity":"0b9c6422-55e7-42ca-85f2-70ee90702554","added_by":"auto","created_at":"2025-02-04 16:28:09","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":216186,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOzone changes with and without γHO\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e in 2018. (a-d) \u003c/strong\u003eThe percentage change in surface ozone between when γHO\u003csub\u003e2 \u003c/sub\u003eis\u003csub\u003e \u003c/sub\u003e0 and 0.2 in 2018. Here, DJF is December-January-February, MAM is March-April-May, JJA is June-July-August and SON is September-October-November.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5932296/v1/c2e409e9b926a1c7fdf1a89e.png"},{"id":75445362,"identity":"93d4f5df-cce9-4533-8644-cb94a065725e","added_by":"auto","created_at":"2025-02-04 16:28:09","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":274211,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFuture ozone formation regimes. (a-d) \u003c/strong\u003eThe regional distribution of ozone generation photochemical regimes modelled with γHO\u003csub\u003e2\u003c/sub\u003e of 0.2 in the SSP 2-4.5 scenario for the year 2046 \u003cstrong\u003e(e-h) \u003c/strong\u003eand 2096. Here, DJF is December-January-February, MAM is March-April-May, JJA is June-July-August and SON is September-October-November.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5932296/v1/03671189da82d2be02c6b117.png"},{"id":75445365,"identity":"80a5aaf5-b197-4e1d-b97b-0ca358ca8abe","added_by":"auto","created_at":"2025-02-04 16:28:10","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":336754,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFuture ozone changes with and without γHO\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e. \u003c/strong\u003eThe change in surface ozone between when γHO\u003csub\u003e2 \u003c/sub\u003eis\u003csub\u003e \u003c/sub\u003e0 and 0.2 in \u003cstrong\u003e(a-d) \u003c/strong\u003e2046 and \u003cstrong\u003e(e-h) \u003c/strong\u003e2096. Here, DJF is December-January-February, MAM is March-April-May, JJA is June-July-August and SON is September-October-November.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5932296/v1/c3f4b00739468a0998ded281.png"},{"id":75445366,"identity":"8421dac6-aef2-4aa7-b545-3da2e19cf7ef","added_by":"auto","created_at":"2025-02-04 16:28:10","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":471895,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eProjected surface ozone changes for 2046 and 2096. (a-d) \u003c/strong\u003eThe change in surface ozone concentrations for the SSP 2-4.5 scenario for the year 2046 and \u003cstrong\u003e(e-h) \u003c/strong\u003e2096 when compared to that of 2018. Here, DJF is December-January-February, MAM is March-April-May, JJA is June-July-August and SON is September-October-November.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-5932296/v1/a08f816f3044394d4d67a64d.png"},{"id":81569655,"identity":"b029d91e-97ba-487b-b8dd-0c6502f31022","added_by":"auto","created_at":"2025-04-28 16:09:39","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2395147,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5932296/v1/b6d6f40d-74e1-4b92-9345-6e8c952d74c3.pdf"},{"id":75445379,"identity":"8ae459fb-25be-439c-a4e0-65e9e3e519c7","added_by":"auto","created_at":"2025-02-04 16:28:11","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":29000569,"visible":true,"origin":"","legend":"","description":"","filename":"GKetalAIRsupplmental.docx","url":"https://assets-eu.researchsquare.com/files/rs-5932296/v1/5e6b479202e30e51496c7c7d.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Aerosol inhibition on photochemical surface ozone formation under future climate and air quality scenarios","fulltext":[{"header":"Highlights","content":"\u003cp\u003e● Higher aerosol uptake enhances radical sinks, increasing surface ozone levels by 40\u0026ndash;60% in 2018.\u003c/p\u003e\u003cp\u003e● North America, Europe and East-Asia remain under an aerosol-inhibited photochemical regime (AIR) in future scenarios.\u003c/p\u003e\u003cp\u003e● However, total AIR extent reduces in both near and distant future simulations.\u003c/p\u003e"},{"header":"1. Introduction","content":"\u003cp\u003eThe heterogeneous chemistry in the lower atmosphere is significant in areas with high aerosol loading and gas-phase pollutants\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. For example, the heterogeneous interaction of N\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e with aerosols significantly influences the NO\u003csub\u003ex\u003c/sub\u003e-O\u003csub\u003e3\u003c/sub\u003e cycle in the atmosphere, depleting atmospheric NO\u003csub\u003ex\u003c/sub\u003e and leading to reduced surface ozone levels in the lower atmosphere (800\u0026mdash;1000 hPa)\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. However, the termination of these reactions is also important in determining the chemistry of the lower atmosphere. For instance, surface ozone (O\u003csub\u003e3\u003c/sub\u003e) is formed through radical chain reactions involving the oxidation of volatile organic compounds (VOCs) and nitrogen oxides (NOx), initiated by the photolysis of compounds like O\u003csub\u003e3\u003c/sub\u003e and HCHO\u003csup\u003e\u003cspan additionalcitationids=\"CR5 CR6\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Termination occurs via peroxyl radical self-reactions or the reaction of hydroxyl radicals with NO\u003csub\u003e2\u003c/sub\u003e, influencing whether reductions in NOx or VOC emissions are more effective for controlling O\u003csub\u003e3\u003c/sub\u003e pollution\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. In ozone mitigation efforts, these reactions are typically considered within two regimes called \u0026ldquo;NOx-limited\u0026rdquo; and \u0026ldquo;VOC-limited\u0026rdquo;\u003csup\u003e\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. The NOx-limited chemical regime describes conditions in which NOx emissions reductions are most beneficial to reduce ozone, while the VOC-limited regime represents situations where lowering emissions of organic compounds would be most effective.\u003c/p\u003e \u003cp\u003eWang et al.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e noted that the trade-off between ozone (O\u003csub\u003e3\u003c/sub\u003e) and particulate matter (PM\u003csub\u003e2.5\u003c/sub\u003e) has arisen as an unexpected result of China's Clean Air Action Plan, which sought to mitigate air pollution. Subsequent to the plan's execution, ozone concentrations elevated during summer in the North China Plain, attributed to diminished NO\u003csub\u003ex\u003c/sub\u003e emissions and stable or escalating VOC emissions, along with substantial declines in PM\u003csub\u003e2.5\u003c/sub\u003e levels. This suggests that tackling ozone pollution necessitates a more sophisticated comprehension than merely classifying it into NOx-limited and VOC-limited categories, wherein the impact of PM\u003csub\u003e2.5\u003c/sub\u003e and aerosols are important\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Consequently, forthcoming air quality control systems globally must account for the complicated links among ozone, particulate matter and precursor emissions to successfully mitigate both pollutants concurrently.\u003c/p\u003e \u003cp\u003eIvatt et al.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e presented a third regime, termed the Aerosol-Inhibited Regime, in which hydroperoxyl radicals on particulate surfaces influence ozone formation. The experiment conducted with GEOS Chem, a global chemical transport model, demonstrated that between 1970 and 2014, the percentage of the Northern Hemisphere's population residing in this regime increased from 2 to 21%. At first, in 1750, regions dependent on biomass burning experienced the most significant effects, but industrialised areas such as North America and Europe had become the most affected by 1970. By 2014, the regions of South and East Asia, with a particular emphasis on South Asia, emerged as the most impacted areas. To address the rise in surface ozone due to a 50% reduction in PM\u003csub\u003e2.5\u003c/sub\u003e precursors, a 40% decrease in NOx emissions is essential, highlighting the complicated interactions among various pollutants in the pursuit of effective air quality management. Therefore, it is essential to take into consideration not only the trade-offs between ozone and particulate matter but also the influence of aerosol particles on ozone formation. This emphasises the necessity for more detailed and regionally tailored approaches to effectively tackle both ozone and particulate pollution in the present and future emission contexts\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eShared Socioeconomic Pathways (SSPs) represent scenarios designed to investigate various potential futures related to climate change and its effects\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. This framework discusses the connection between different levels of socioeconomic development, technological progress and demographic shifts and their effects on greenhouse gas emissions and susceptibility to climate-related impacts. Five scenarios exist, starting with SSP1, which is defined by sustainable development and low emissions and extending to SSP5, which envisages rapid economic growth and high fossil fuel consumption. Each pathway presents unique challenges for climate mitigation and adaptation, assisting experts and decision-makers in assessing potential climate strategies. For example, SSP2 illustrates a balanced scenario that underscores the complexity and unpredictability in reaching climate objectives, whereas SSP3 emphasises a divided world characterised by elevated emissions stemming from insufficient collaboration. The SSP framework allows for the evaluation of climate impacts, adaptation requirements and mitigation approaches across different scenarios, and thereby supporting informed decision-making\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Additionally, the SSPs are frequently integrated with Representative Concentration Pathways (RCPs) to simulate various climate scenarios influenced by differing levels of greenhouse gas concentrations\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThis study aims at estimating the surface ozone concentrations using the GEOS-Chem framework under different SSP-RCP scenarios, addressing both near-future (2046) and distant-future (2096) scenarios, inclusive and exclusive of aerosol uptake effects. The growing complexity of ozone dynamics, especially considering the unforeseen effects of air quality policies\u0026mdash;exemplified by those in China\u0026mdash;underscores the imperative to integrate aerosol interactions into atmospheric models. The relationship between reduced PM\u003csub\u003e2.5\u003c/sub\u003e emissions and increased ozone levels highlights the necessity of a holistic strategy for air quality management\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. The study utilises the SSP framework for clarifying the impact of diverse socioeconomic trajectories on ozone pollution across distinct aerosol conditions. Understanding these interactions is essential for developing effective climate and air quality measures, as the anticipated rise in populations residing in aerosol-inhibited areas presents considerable hazards to public health and environmental sustainability. This could further benefit policy makers in determining effective strategies for decreasing ozone levels while maintaining improvements in particulate matter and aerosol reduction\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. As international initiatives to combat climate change escalate, it is essential to understand the ozone generation processes to formulate adaptive policies that address both local and global air quality issues.\u003c/p\u003e"},{"header":"2. Data and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 GEOS Chem model\u003c/h2\u003e \u003cp\u003eGEOS-Chem is a Chemical Transport Model (CTM) developed for modelling complex oxidant-aerosol chemistry in the troposphere and stratosphere\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Employing the Kinetic PreProcessor (KPP) 3.0 as its chemical solver, GEOS-Chem integrates sophisticated functionalities via the FlexChem interface, facilitating a flexible methodology for chemical kinetics\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. The model complies with the most recent JPL/IUPAC guidelines for chemical mechanisms, with substantial modifications that improve the depiction of diverse chemical processes, including those related to isoprene, aromatics and nitrates\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Recent advancements have enhanced the treatment of intricate reactions, including methanol synthesis and mercury redox chemistry, facilitating more precise atmospheric forecasts. Additionally, the model incorporates the reactive absorption of nitrogen oxides by aerosols and computes aerosol hygroscopicity, which is essential for comprehending aerosol-cloud interactions. GEOS-Chem offers a comprehensive framework for investigating atmospheric chemistry and its effects on air quality and climate change by accommodating various chemical species and reactions, including halogens and hydroxymethanesulfonate. This model provides thorough understanding into ozone generation mechanisms and pollutant interactions, serving as an essential resource for addressing air quality challenges and comprehending the wider implications of atmospheric dynamics. GEOS-Chem has been rigorously validated by researchers globally. For instance, Travis et al.\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e showed that, despite the successful simulation of ozone and its precursors in the SEAC4RS aircraft data below 1 km of altitude, Maximum Daily 8-hour average surface ozone (MDA-8) was biased high in the model by +\u0026thinsp;6 ppb on average.\u003c/p\u003e \u003cp\u003eDavid et al.\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e used the GEOS-Chem transport model over India and observed that the model reasonably simulated the tropospheric O\u003csub\u003e3\u003c/sub\u003e abundances and vertical profiles, with a mean bias of 1\u0026ndash;3 DU compared to observations for the period 2000\u0026ndash;2015. Christiansen et al.\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e observed that the GEOS-Chem model, when validated against 25 ozonesonde sites, aircraft, and satellite observations globally, has a reasonable agreement with a mean bias of 1\u0026ndash;3 DU for the period from 1990 to 2017. Mao et al.\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e reported that the GEOS-Chem model, validated against MDA8 O\u003csub\u003e3\u003c/sub\u003e observations in central and eastern China from May to July 2017, had a strong correlation of 0.77 (95% confidence level). In Nanjing, the simulated MDA8 O\u003csub\u003e3\u003c/sub\u003e concentrations converged with the observed trend, with a correlation coefficient of 0.65, a normalised mean bias (NMB) of 5%, and a normalised mean error (NME) of 21%.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 GCAP 2.0 model\u003c/h2\u003e \u003cp\u003eThe Global Change and Air Pollution (GCAP 2.0) framework signifies a notable technological enhancement compared to the original GCAP model, first articulated by Wu et al.\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e and subsequently refined by Murray et al.\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. This revised model utilises meteorological data sourced from version E2.1 of the NASA Goddard Institute for Space Studies (GISS) General Circulation Model (GCM), allowing the GEOS-Chem to conduct simulations across diverse scenarios, including pre-industrial, recent historical and multiple future conditions in accordance with the CMIP6 experiments\u003csup\u003e\u003cspan additionalcitationids=\"CR34\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. GCAP 2.0 resolves significant difficulties noted in previous iterations, notably the excessive mass transfer from the stratosphere to the troposphere that complicated the tropospheric ozone budget. This problem frequently obstructed the analysis of polar ice-core data, particularly with the integration of online interactive stratospheric chemistry in GEOS-Chem. To address these complexities, GCAP 2.0 employs a unidirectional offline coupling technique, enabling the GEOS-Chem CTM to utilise stored meteorological data from any historical or forthcoming time. Essential attributes encompass the incorporation of a cohesive chemical mechanism spanning from the surface to the mesopause, facilitating enhanced atmospheric representations, alongside a versatile emissions pre-processor to accommodate diverse emissions situations. GCAP 2.0 facilitates global simulations encompassing 72 vertical layers down from 1000 hPa to 0.01 hPa. The model integrates innovations such as one- and two-way linked nested regional simulations, enabling localised air quality investigations in conjunction with global evaluations and an adjoint for inverse modelling that improves its functionality.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Methods\u003c/h2\u003e \u003cp\u003eTHe GEOS Chem and GCAP2.0 are run on a 2.5\u003csup\u003eo\u003c/sup\u003ex2.5\u003csup\u003eo\u003c/sup\u003e grid resolution globally. GEOS Chem classic version has 72 vertical levels from the surface (1000 hPa) to the top of the atmosphere (0.01 hPa), whereas GCAP2.0 has a 41-level vertical gridding. One year spin up simulations with different aerosol uptake coefficients are used to generate the model restart files. Termination rates of chain reactions were determined using archived species concentrations and physical parameters such as temperature, pressure and humidity, in addition to aerosol properties, as per Ivatt et al.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Although we do not classify radical product generation in peroxyl-radical self-reactions as termination stages, we regard non-radical products as ongoing termination processes. The heterogeneous loss rate of HO\u003csub\u003e2\u003c/sub\u003e was assessed by evaluating the radius and surface area of different aerosol forms. For our simulations, we employed a baseline HO\u003csub\u003e2\u003c/sub\u003e reactive uptake coefficient (γHO\u003csub\u003e2\u003c/sub\u003e) of 0.2. Laboratory studies of pure synthetic aerosols indicate lower uptake coefficients (γHO\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.2), whereas real-world aerosol studies reveal values between 0.08 to 0.40, implying that elements such as transition metals may increase aerosol uptake\u003csup\u003e\u003cspan additionalcitationids=\"CR37\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. To assess the influence of HO\u003csub\u003e2\u003c/sub\u003e uptake, we performed simulations with γHO\u003csub\u003e2\u003c/sub\u003e values zero aerosol uptake, 0.1 (half of the baseline), 0.2 (baseline for future projections in this study) and 0.4 (twice the baseline). Though we presumed H\u003csub\u003e2\u003c/sub\u003eO to be the exclusive product of HO\u003csub\u003e2\u003c/sub\u003e absorption, our results remain valid when H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e is taken into account. Employing a singular γHO\u003csub\u003e2\u003c/sub\u003e value likely oversimplifies the variability, as existing models fail to account for its temporal oscillations\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e,\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. The seasons are defined as December-January-February (DJF), March-April-May (MAM), June-July-August (JJA) and September-October-November (SON) in this study.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Sensitivity of Aerosol Uptake Coefficients on Photochemical Ozone Regimes\u003c/h2\u003e \u003cp\u003eThe aerosol uptake coefficient notably affects chemistry by modifying the interactions between aerosols and trace gases, including O₃, NO₂ and VOCs. Aerosols, consisting of fine particulate matter suspended in the atmosphere, serve as surfaces for heterogeneous reactions with gases. With an increase in the aerosol uptake coefficient, the likelihood of aerosols to react with radical species such as HO\u003csub\u003e2\u003c/sub\u003e improves, resulting in higher surface ozone formation from precursors. Here, we assess the effect of varying aerosol uptake coefficients (γHO\u003csub\u003e2\u003c/sub\u003e)\u0026mdash;0, 0.1, 0.2 and 0.4\u0026mdash;on the distribution of AIR and their relationship with NOx-limited and VOC-limited regimes across the tropical and extratropical locations and seasons. The aerosol uptake coefficient is essential in regulating the interaction between aerosols and atmospheric gas-phase chemistry, specifically in assessing the degree to which aerosols impede or facilitate chemical reactions in the atmosphere\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e,\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. Our analysis shows that an increase in the γHO\u003csub\u003e2\u003c/sub\u003e results in a rise in the percentage of pixels categorised as the aerosol-inhibited area. This effect is especially evident in areas where NO\u003csub\u003ex\u003c/sub\u003e-limited regimes typically dominate. In the NH winter season, an increase in the aerosol absorption coefficient from 0.0 to 0.2 results in a substantial reduction of around 13% of the NOx-limited regime, whereas the aerosol-inhibited regime expands by almost 15% (compare Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cb\u003ewith Supplementary Fig.\u0026nbsp;1\u003c/b\u003e). \u003cb\u003eSupplementary Figs.\u0026nbsp;1\u0026ndash;3\u003c/b\u003e show the spatial variation of the extent of AIR with different γHO\u003csub\u003e2\u003c/sub\u003e. This transition indicates that increased aerosol reactive uptake reduces the availability of reactive gases such as HO\u003csub\u003ex\u003c/sub\u003e and NO\u003csub\u003ex\u003c/sub\u003e, and thus, amplifying the AIR at the expense largely of the NOx-limited regime. A similar pattern exists in other seasons, characterised by a steady decline of 5\u0026ndash;10% in NO\u003csub\u003ex\u003c/sub\u003e-limited regions and a commensurate rise in aerosol-inhibited areas.\u003c/p\u003e \u003cp\u003eFor instance, India is characterised consistently by an AIR across all seasons, but with occasional seasonal variations. In DJF, the Indo-Gangetic Plain (IGP) region, noted for its lush vegetation\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e, has higher VOC emissions, resulting in the formation of VOC-limited regimes. The elevated VOC emissions in these seasons may account for a shift in chemical regimes, since VOCs serve as precursors for atmospheric ozone generation, affecting the equilibrium between NOx-limited and VOC-limited regimes\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e. Also, during winter (DJF), lower temperatures and stagnant atmospheric conditions reduce the dispersion of pollutants, leading to high concentrations of VOCs\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e,\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. Simultaneously, reduced NOx emissions, due to less efficient combustion processes, form a VOC-limited regime where ozone formation is constrained by the lack of available NOx to interact with VOCs\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. Nevertheless, the AIR persists throughout the rest of the year (MAM, JJA, SON). East Asia also shows a consistent AIR for most of the year, except in SON. The shift from aerosol-inhibited to VOC-limited regimes in this area could be affected by seasonal fluctuations in emissions and atmospheric dynamics, particularly in autumn, owing to changes in vegetation and air mass transport\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e,\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe Sahara region in Africa also shows a year-round AIR. Nevertheless, during JJA, the extent of the area under AIR markedly diminishes compared to DJF and MAM. This decrease can be attributed to the decreasing dust concentration in the atmosphere during this period\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e,\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e. The Sahara, a substantial producer of dust, has its aerosol concentrations affected by the intensity and direction of trade winds, which can reduce dust particles over extensive regions during JJA, and thus reduce the impact of aerosol absorption in the area\u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e. Also, weaker winds during the summer monsoon are less effective at picking up dust from the desert surface compared to the stronger westerly winds in winter\u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e. The seasonal distribution of dust in the Sahara could influence the AIR, as dust aerosols interact with other atmospheric substances, affecting the heterogeneous chemical equilibrium. Furthermore, the extratropical regions of Northern North America and Southern South America show a pronounced seasonal change in AIR, characterised by widespread aerosol-inhibited regions during the winter months. The seasonal variations can be attributed to variations in atmospheric circulation patterns, temperature and aerosol concentrations, which fluctuate with the seasons and affect the degree of the AIR. In these regions, the winter months generally result in stable atmospheres with temperature inversions and augmented aerosol accumulation due to high heating demand, which could foster the formation of AIR\u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e,\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Surface O\u003csub\u003e3\u003c/sub\u003e sensitivity to aerosol uptake coefficients\u003c/h2\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e3.2.1. Recent-past (2018)\u003c/h2\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the percentage difference in surface ozone concentrations between a simulation with γHO\u003csub\u003e2\u003c/sub\u003e of 0 and 0.2, representing the impact of a reduction in the aerosol heterogeneous uptake sink on surface O\u003csub\u003e3\u003c/sub\u003e. (\u003cb\u003eSupplementary Figs.\u0026nbsp;4\u0026ndash;6\u003c/b\u003e show the percentage change in surface ozone concentrations for γHO\u003csub\u003e2\u003c/sub\u003e of 0 with 0.1 and 0.4, respectively). The γHO\u003csub\u003e2\u003c/sub\u003e of 0.2 is used as the baseline for analysing surface ozone variations in 2018\u003csup\u003e15,56,57\u003c/sup\u003e. Changes are most pronounced in the terrestrial regions, with negligible variation over the marine atmosphere. The most marked changes in surface ozone levels are observed in South and East Asia, where aerosols are most abundant globally currently and in 2018\u003csup\u003e58,59\u003c/sup\u003e, especially during the Northern Hemisphere winter, where ozone concentrations increase by about 8\u0026ndash;10 ppb (30\u0026ndash;40%) due to the weakening of the radical sink. Although surface ozone variations are considerable in these regions during different seasons, the percentage change generally lies between 20 and 30%. Conversely, central Africa exhibits minimal surface ozone variations, between 5 and 10%, with a modest reduction between the Southern Hemisphere summer (JJA) and autumn (SON). Eastern North America also shows an increase in surface ozone, but only during the Northern Hemisphere winter, which is generally within 10\u0026ndash;15% in 2018. The regional distribution of ozone variations is uniform, but the extent of these changes is more substantial with elevated aerosol uptake coefficients. With a γHO\u003csub\u003e2\u003c/sub\u003e of 0.4, surface ozone increases by around 40\u0026ndash;50% in East and South Asia, but this is limited to 15\u0026ndash;25% when the HO\u003csub\u003e2\u003c/sub\u003e uptake coefficient of 0.1. This change indicates that the γHO\u003csub\u003e2\u003c/sub\u003e profoundly influences surface ozone concentrations, with more uptake resulting in more pronounced change in ozone levels, particularly in densely inhabited and industrialised regions such as East and South Asia.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e3.2.2 Near-Future (2046)\u003c/h2\u003e \u003cp\u003eUsing GCAP2.0, we modelled the future development of AIR globally under the SSP1\u0026ndash;2.6, SSP2\u0026ndash;4.5 and SSP5\u0026ndash;8.5 scenarios to analyse the impact of aerosols on surface ozone levels by 2046. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the photochemical ozone formation regimes under SSP2\u0026ndash;4.5 and \u003cb\u003eSupplementary Figs.\u0026nbsp;7 and 8\u003c/b\u003e show the same under the SSP1-2.6 and SSP5-4.5 scenarios, respectively. AIR regions show a notable decrease in extent in future scenarios relative to current levels, as aerosols impede ozone formation via heterogeneous reactions\u003csup\u003e\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e. Regions such as India and Sahara, which currently experience year-round AIR, exhibit a reduction in their extent. In the SSP2\u0026ndash;4.5 scenario, the global extent of AIR shrinks to 10.8% in December\u0026ndash;February (DJF), 3.6% in March\u0026ndash;May (MAM), 1.2% in June\u0026ndash;August (JJA) and 4.2% in September\u0026ndash;November (SON), due to a mid-century decline in aerosol and precursor emissions in most world regions. The SSP1\u0026ndash;2.6 scenario, characterised by even more stringent mitigation efforts and reduced emissions, indicates a further decline in the extent of AIR by about 8.5%, 1.2%, 0.9% and 4.4% in DJF, MAM, JJA and SON, respectively. The decline can be attributed to lower aerosol emissions and concentrations due to cleaner air policies, reduced emissions and alterations in the availability of aerosol precursors, resulting in diminished aerosol-induced inhibition of ozone formation\u003csup\u003e\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e,\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e. In the SSP2-4.5 scenario, by 2046, we observe a significant reduction in the total aerosol surface area by about 50\u0026mdash;100% (0.5\u0026ndash;0.75 \u0026times; 10⁻⁶ cm\u0026sup2; cm⁻\u0026sup3;) throughout much of East and South Asia and the Middle East, where the AIR regions dominated in the recent past (\u003cb\u003eSupplementary Fig.\u0026nbsp;9\u003c/b\u003e). This decrease could be attributed to the changes in aerosol emissions and atmospheric conditions influenced by socio-economic and climate trajectories. Furthermore, Black Carbon (BC) emissions in the near future are projected to rise by about 25\u0026mdash;50% (0.25\u0026ndash;0.5 \u0026times; 10⁻⁶ cm\u0026sup2; cm⁻\u0026sup3;) across East Asia, signifying an escalating contribution to regional air pollution and possible effects on climate forcing in the SSP 2\u0026ndash;4.5 emission scenario (\u003cb\u003eSupplementary Fig.\u0026nbsp;10\u003c/b\u003e). Sulphate aerosols will likely rise by 20\u0026mdash;40% (2\u0026ndash;3 \u0026times; 10⁻⁶ cm\u0026sup2; cm⁻\u0026sup3;), especially during the Northern Hemisphere winter, across East Asia, North America, and Northern Asia\u003csup\u003e\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e, which could be due to the changes in industrial emissions and atmospheric transport patterns (\u003cb\u003eSupplementary Fig.\u0026nbsp;11\u003c/b\u003e). Despite the overall reduction in the extent of AIR, their geographic distribution shifts, becoming more pronounced in areas such as the United States and Europe. This shift can be due to the near-zeroing of NOx emissions in these countries, which outpaces aerosol emissions reductions and indicates that aerosol-induced ozone inhibition may become considerable in densely populated areas there, intensifying air quality challenges in regions already facing health impacts from air pollution. The rise in sulphate aerosol surface area may contribute to the expansion of AIR in the US, notably in NH winter, as the spatial distribution of sulphate aerosols correlates highly with the extension of AIR there compared to that in 2018 (\u003cb\u003eSupplementary Fig.\u0026nbsp;11\u003c/b\u003e). Furthermore, by 2046, it is projected that nearly 90% of the globe will be in a NOx-limited regime across all SSP scenarios, suggesting that NO\u003csub\u003ex\u003c/sub\u003e will emerge as the primary limiting factor for ozone production.\u003c/p\u003e \u003cp\u003eWe also compare the effect of aerosol uptake on surface ozone levels under various SSP scenarios by comparing simulations that include aerosol uptake to those that do not, using a γHO\u003csub\u003e2\u003c/sub\u003e of 0.2. Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows the absolute changes of surface ozone in the SSP2\u0026ndash;4.5 scenario and \u003cb\u003eSupplementary Figs.\u0026nbsp;12\u0026ndash;14\u003c/b\u003e show the percentage change in surface ozone with and without aerosol uptake for the different SSP scenarios compared to that of the recent past. We observe a consistent increase in ozone, especially in areas with high aerosols, including South and East Asia, with the reduction of the heterogenous radical sink. In the SSP1\u0026ndash;2.6 scenario, ozone concentrations increase by approximately 5\u0026ndash;10% in these regions throughout the seasons. However, the increase is small during MAM and JJA, within 5%. The increase in ozone levels is linked to a lower aerosol uptake, which facilitates the formation of ozone through heterogeneous reactions. There is also a notable increase in surface ozone in the Southern Hemisphere during the JJA and SON. In areas characterised by elevated aerosol concentrations, including South and East Asia, the SSP2\u0026ndash;4.5 and SSP5\u0026ndash;8.5 scenarios indicate a more pronounced increase in ozone levels, by approximately 10\u0026ndash;20%, in contrast to the rise of 5\u0026ndash;10% observed in the SSP1-2.6 scenario. This is much lower than recent past (2018) sensitivity of O\u003csub\u003e3\u003c/sub\u003e concentration to γHO\u003csub\u003e2\u003c/sub\u003e (30\u0026ndash;40% in Asia), which further confirms that the AIR will reduce in the future.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003ch2\u003e3.2.3 Far - Future (2096)\u003c/h2\u003e \u003cp\u003eA comparison of these projected results for 2046 and 2096 reveals a decrease in the extent of AIR in 2096 under the SSP1-2.6 and SSP2-4.5 scenarios (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e \u003cb\u003eand Supplementary Fig.\u0026nbsp;15\u003c/b\u003e). The global extent of AIR diminishes from 10.8\u0026ndash;7.4% in DJF, 3.6\u0026ndash;1.3% in MAM, 1.2\u0026ndash;0.4% in JJA, and 4.2\u0026ndash;3.1% in SON. The shrink is particularly evident in the United States in the winter months (DJF). India continues to be primarily within a VOC-limited regime in both 2046 and 2096, with AIR decreasing to fewer than 10% globally by 2096. In Northern Europe, most regions continue to be in AIR in both 2046 and 2096. The observed spatial patterns are similar in both the SSP1\u0026ndash;2.6 and SSP2\u0026ndash;4.5 scenarios. However, under the extreme SSP5\u0026ndash;8.5 scenario, a notable transformation takes place in North America, where northern areas of the US and Canada fall entirely in AIR, while southern regions of the US shift to a VOC-limited regime (\u003cb\u003eFigure S16\u003c/b\u003e). Furthermore, Southeast Asia is in aerosol-limited regime in 2046, but it turns out to be predominantly NOx-limited by 2096.\u003c/p\u003e \u003cp\u003eThe γHO\u003csub\u003e2\u003c/sub\u003e further impacts surface ozone concentrations, with regional variations observed during 2096 as well (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and \u003cb\u003eSupplementary Figs.\u0026nbsp;17\u0026ndash;19\u003c/b\u003e). For instance, in the SSP 2-4.5 scenario, the comparison of γHO\u003csub\u003e2\u003c/sub\u003e ranging from 0 to 0.2 indicates an increase in surface ozone levels by approximately 10\u0026ndash;15% in the regions including South and East Asia during the DJF season. The northern extratropics, encompassing the US, Canada, China, Russia, and Europe, exhibit a notable reduction in ozone of 5\u0026ndash;10%, except in JJA, during which a decrease of less than 5% is found. These changes are more pronounced in the SSP 5\u0026ndash;8.5 scenario and less evident in SSP 1-2.6, analogous to that observed in 2046. An additional decrease in total aerosol levels by the end of the century compared to that of current levels, along with reductions in sulphate and black carbon emissions, is anticipated to reduce surface ozone, as shown in \u003cb\u003eSupplementary Figs.\u0026nbsp;9\u0026ndash;11\u003c/b\u003e. Aerosols, especially sulphates and BC, influence ozone production, impact the availability of hydroxyl radicals (OH), and thus influence the extent of AIR.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Future projections of Surface Ozone\u003c/h2\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003e3.3.1 Near future (2046)\u003c/h2\u003e \u003cp\u003eWe also estimate the total surface O\u003csub\u003e3\u003c/sub\u003e change from future to present. Surface ozone levels in the Northern Hemisphere tropics are projected to rise by approximately 50\u0026ndash;75% by 2046 when compared to the current levels in 2018, with an increase of about 150\u0026ndash;200% in areas such as South America and East Asia, although these variations are seasonal in the SP 2-4.5 scenario (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e \u003cb\u003eand Supplementary Fig.\u0026nbsp;21\u003c/b\u003e). Using our γHO\u003csub\u003e2\u003c/sub\u003e sensitivity simulations, we attribute that about 40\u0026ndash;60% of the total O\u003csub\u003e3\u003c/sub\u003e enhancement is due to aerosol reductions in the AIR. Northern South America is expected to see a continuous increase in surface ozone of approximately 200%, irrespective of the seasons, whereas mid-Africa is anticipated to experience a steady rise of 50\u0026ndash;100% year-round, with an exception in DJF. India also has a seasonal rise of about 30 ppb in surface ozone levels, especially during JJA. The observed spatial patterns are uniform across all SSP scenarios (SSP1\u0026ndash;2.6, SSP2\u0026ndash;4.5 and SSP5\u0026ndash;8.5), with more increase in ozone levels noted in the SSP2\u0026ndash;4.5 and SSP5\u0026ndash;8.5 scenarios, which is about 20\u0026ndash;30% higher when compared to current levels (\u003cb\u003eSupplementary Figs.\u0026nbsp;20\u0026ndash;22)\u003c/b\u003e. The distribution of ozone in higher emission scenarios shows a more widespread pattern, mainly in the Northern Hemisphere extratropics, where an increase of 50\u0026ndash;75% is noted throughout the globe. Nevertheless, regions within AIR regions in the near future mainly affects North America, Northern Europe, and East Asia, especially during the Northern Hemisphere winter, with an approximate increase of 50\u0026ndash;60% surface ozone over North America and Northern Europe, and about 20\u0026ndash;30% over Northern Asia.\u003c/p\u003e \u003cp\u003eBiogenic emissions strongly impact ozone formation, which is also impacted by atmospheric NO\u003csub\u003e2\u003c/sub\u003e concentrations\u003csup\u003e\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u003c/sup\u003e. The oxidation of VOCs contributes to the generation of secondary organic aerosols, with the degree of contribution influenced by temperature, vegetation type, and foliar mass\u003csup\u003e\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e\u003c/sup\u003e. These characteristics are acutely responsive to climate change and alterations in vegetation distribution\u003csup\u003e\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e\u003c/sup\u003e. For instance, \u003cb\u003eSupplementary Fig.\u0026nbsp;23\u003c/b\u003e shows the projected global rise in agricultural land and forest cover, which will subsequently increase biogenic VOC emissions. Furthermore, agricultural waste burning may increase by 1.5 to 2 times across different emission scenarios by the end of the century, resulting in elevated NO\u003csub\u003ex\u003c/sub\u003e and VOC emissions, enhancing ozone formation from these precursors.\u003c/p\u003e \u003cp\u003eUrbanisation, energy use and air pollution are closely related. Urban Heat Islands (UHI) in densely populated cities raise temperatures, and thus, increase the demand for cooling energy\u003csup\u003e\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e,\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e\u003c/sup\u003e. This results in increased residential emissions, but it varies by region. Specifically, \u003cb\u003eSupplementary Figs.\u0026nbsp;24 and 25\u003c/b\u003e show that NO\u003csub\u003ex\u003c/sub\u003e and VOC emissions in the Middle East and Africa will increase in the future, and exacerbate the secondary production of ozone. In these areas, residential emissions are projected to rise until the mid-century, before reverting to historical levels by 2100. These findings emphasise the necessity for efficient control methods to guarantee improved air quality in the future. Tian et al.\u003csup\u003e\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e\u003c/sup\u003e studied energy consumption and air pollution trends in China since 1990, providing recommendations for sustainable energy utilisation, air pollution management, and CO\u003csub\u003e2\u003c/sub\u003e reduction. By 2003, China's total primary energy consumption had attained 1,678\u0026nbsp;million tonnes of standard coal equivalent. Consequently, emissions of SO\u003csub\u003e2\u003c/sub\u003e and NOx increased to 21.58\u0026nbsp;million tonnes and 16.13\u0026nbsp;million tonnes, respectively. This suggests that more rigorous laws, standards, and efficient economic strategies are needed for resolving those challenges. \u003cb\u003eSupplementary Table\u0026nbsp;1\u003c/b\u003e lists the energy demand in various sectors globally. Thus, the increasing demand of energy would lead to more emissions, but can be tackled using a clean and sustainable practice for energy production\u003csup\u003e\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAlso, climate change is anticipated to modify atmospheric circulation and precipitation patterns, impacting meteorological conditions that deteriorate air quality. In a warming climate, the buildup of particulate matter in the atmosphere, especially during winter, is expected to rise due to stagnation. This stagnation is characterised by lack of precipitation, weak surface winds and poor vertical mixing, all of which facilitate the accumulation of pollution at the surface. Stagnation events can exacerbate PM\u003csub\u003e2.5\u003c/sub\u003e pollution even in the absence of substantial emissions. Zhou et al.\u003csup\u003e\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e\u003c/sup\u003e found that changes in stagnation patterns are influenced by both global CO\u003csub\u003e2\u003c/sub\u003e-induced circulation modifications and local aerosol-driven meteorological reactions. By 2100, winter stagnation in the Indo-Gangetic Plain (IGP) is projected to extend by 7\u0026thinsp;\u0026plusmn;\u0026thinsp;3 days, resulting in an increase in PM\u003csub\u003e2.5\u003c/sub\u003e concentrations by roughly 7 \u0026micro;g/m\u0026sup3; under high-warming and high-aerosol scenarios. Nevertheless, annual stagnation instances are anticipated to diminish in most of India. Horton et al.\u003csup\u003e\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e\u003c/sup\u003e used an air stagnation index and a series of bias-corrected climate model simulations to evaluate potential alterations in stagnation frequency and duration due to global warming. Their study indicates that stagnation events may rise in regions encompassing 55% of the global population, with the affected population in these areas being ten-fold greater than in regions experiencing a decline in stagnation. By the late twenty-first century, substantial increases\u0026mdash;up to 40 additional days a year\u0026mdash;are predicted for many areas in the tropics, subtropics, and certain mid-latitude regions. These alterations will probably exert most notable impacts on countries such as India, Mexico, and the western United States, where the large populations coincide with prolonged stagnation episodes. This stagnation may result in the prolonged existence of trace gases in the atmosphere, and thus, increase ozone exposure in the densely populated areas.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e \u003ch2\u003e3.3.2 Far - future (2096)\u003c/h2\u003e \u003cp\u003eIn 2096, the change in surface ozone levels were smaller than those in 2046 across all SSP scenarios, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e and \u003cb\u003eSupplementary Figs.\u0026nbsp;26\u0026ndash;28\u003c/b\u003e. The reduction is attributable to several factors, including stricter emission controls, enhanced air quality regulations, and possible alterations in atmospheric dynamics that may decrease ozone formation\u003csup\u003e\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e,\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e\u003c/sup\u003e. The dispersion of ozone from hotspot regions diminishes by roughly 25\u0026ndash;50% in a large number of areas. The reduction is noticeable particularly in the tropical marine atmosphere. The spatial extent of hotspot regions in 2096 is similar to that of 2046, with consistently higher ozone levels (100\u0026ndash;150%) in regions such as northern South America and Central Africa, irrespective of the seasons. These regions may persistently experience increasing ozone attributable to local sources of ozone precursors, including biomass burning or industrial emissions, together with climate conditions favourable to ozone formation\u003csup\u003e\u003cspan additionalcitationids=\"CR75 CR76\" citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e\u003c/sup\u003e. East and South Asia show an increase in ozone during DJF and JJA, likely influenced by seasonal emission variations, including elevated industrial activity in winter and agricultural burning in summer\u003csup\u003e\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e,\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e\u003c/sup\u003e. Furthermore, surface ozone levels in North America are projected to be higher by 20\u0026ndash;30 ppb in 2096 compared to that of 2018, potentially attributable to changes in transportation emissions, urbanisation, or a lag in atmospheric chemistry's response to reductions in precursor pollutants\u003csup\u003e\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e,\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eA comparison of \u003cstrong\u003eFig. 4\u003c/strong\u003e with \u003cstrong\u003eFig. 5\u003c/strong\u003e shows the impact of \u0026gamma;HO\u003csub\u003e2\u003c/sub\u003e on surface ozone concentrations in both the near and distant future, compared to the recent past. In comparing the results from 2018 to those from 2046, East and South Asia have the most dominant effect of \u0026gamma;HO\u003csub\u003e2\u003c/sub\u003e on ozone concentrations, with an increase of around 10 ppb, which is nearly four times less than the contribution noted in the recent past (as shown in \u003cstrong\u003eFig. 2\u003c/strong\u003e). Future projections indicate that surface ozone levels in India will significantly rise during summer monsoon (JJA), with an overall increase of 30 ppb, of which 10 ppb is ascribed to the impact of \u0026gamma;HO\u003csub\u003e2\u003c/sub\u003e, or around 30\u0026ndash;40% of the total increase. In East Asia, the most significant increase is anticipated in winter, when aerosol effects are more evident, contributing 5\u0026ndash;7.5 ppb to the total 30 ppb rise, corresponding to approximately 25% of the ozone increase. In West Africa, \u0026gamma;HO\u003csub\u003e2\u003c/sub\u003e is expected to contribute roughly 5 ppb during the dry season (DJF), whereas Central Africa will have a contribution of about 5 ppb in the fall (SON). The anticipated total increase in surface ozone in West and Central Africa is around 15\u0026ndash;20 ppb, with \u0026gamma;HO\u003csub\u003e2\u003c/sub\u003e contributing 25\u0026ndash;30% to this rise. By 2096, the influence of \u0026gamma;HO\u003csub\u003e2\u003c/sub\u003e on surface ozone is expected to continue to decline, with the most significant effect prevailing in India, where the contribution will be less than 5 ppb, which represents approximately 20% of the overall rise. Conversely, by the end of the century, Central and West Africa will continue to have an increased impact than East Asia, although this will account for merely 10% of the total ozone enhancement attributed to higher aerosol uptake by HO\u003csub\u003e2\u003c/sub\u003e.\u003c/p\u003e\n\u003cp\u003eAdditionally, \u003cstrong\u003eFig. 5\u0026nbsp;\u003c/strong\u003ealso shows that regions that have lower surface ozone show more variation in the future, approximately 100\u0026ndash;200% (20\u0026ndash;40 ppb). Ozone precursors are, in general, more difficult to control and ozone levels have a larger impact from remote sources as well as increasing methane concentrations\u003csup\u003e82\u003c/sup\u003e. We found that in the SSP scenarios, regional ozone levels do show clear increase in the future. For instance, Northern South America currently has an ozone level of 10 ppb, which is projected to increase by around 200%, reaching about 30\u0026ndash;40 ppb by the end of the century in the SSP2\u0026ndash;4.5 scenario. This is also analogous to several other regions, including Northern Europe and East Asia. Current hotspot regions, such as Central Africa, show an increase of 50\u0026ndash;100%, resulting in levels around 20\u0026ndash;30 ppb\u003csup\u003e\u0026nbsp;\u003c/sup\u003eby 2100. India currently has higher ozone levels (70\u0026ndash;80 ppb), which are projected to remain stable by 2100. This indicates that the majority of worldwide regions would experience ozone levels of 40\u0026ndash;80 ppb in the future, which is above the World Health Organization\u0026apos;s recommended guideline, increasing the population\u0026apos;s susceptibility to pre-existing health problems associated with air pollution.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe results show a substantial influence of \u0026gamma;HO\u003csub\u003e2\u003c/sub\u003e on the distribution of aerosol-inhibited regimes and surface ozone concentrations in different global regions. The increase in \u0026gamma;HO\u003csub\u003e2\u003c/sub\u003e correlates with an expansion in the AIR, especially in otherwise NOx-limited regions like South and East Asia, particularly evident in colder months when lower temperatures and stagnant atmospheric conditions intensify aerosol effects. Future projections across various SSP scenarios indicate a global reduction in AIR extent, linked to decreased aerosol concentrations and more stringent emission regulations. The incorporation of these iterative impacts could modify the concentrations of these contaminants\u003csup\u003e82\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThe future trajectory of air quality, especially with higher ozone and lower aerosol levels, poses considerable concerns and health dangers worldwide. Projections based on the SSP-RCP scenarios indicate geographical variances in ozone concentrations, with regions such as Northern South America, Northern Europe and East Asia anticipated to experience notable increases by the end of the century. The rise in ozone is primarily influenced by many elements, such as aerosol reactive uptake, agricultural emissions, forest fires and the impact of climate change on vegetation and air circulation. The increase in biogenic VOC emissions, coupled with improved agricultural techniques and garbage incineration, will intensify ozone formation, particularly in areas such as Africa and Asia\u003csup\u003e83,84\u003c/sup\u003e. The interaction between urbanisation, energy consumption and air pollution highlights the pressing necessity for greener energy alternatives and efficient pollution mitigation strategies. Climate-induced alterations in weather patterns, including stagnation episodes, would exacerbate particulate matter concentrations and extend exposure to detrimental pollutants, especially in densely populated regions. Therefore, efforts to reduce aerosol concentrations must be integrated with policies that tackle the broader impacts of climate change, including reducing the possibility of wildfires and agricultural emissions, as these elements will intensify ozone formation. Furthermore, policies that advocate for cleaner energy choices, urban air quality control and sustainable agricultural methods will be essential in alleviating the total environmental burden. Considering the health hazards linked to increased ozone concentrations, it is imperative for states to collaborate in establishing and enforcing international norms in accordance with the WHO\u0026apos;s recommendations. These initiatives must encompass investment in research and technology to assess air quality and evaluate the efficacy of executed actions.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCredit authorship contribution statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGSG:\u0026nbsp;\u003c/strong\u003eWriting \u0026ndash; review \u0026amp; editing, Writing \u0026ndash; original draft, Visualization, Validation, Software, Methodology, Investigation, Formal analysis, Data curation. \u003cstrong\u003eDMW:\u0026nbsp;\u003c/strong\u003eWriting \u0026ndash; review \u0026amp; editing, Writing \u0026ndash; original draft, Supervision, Visualization, Validation, Software, Methodology, Investigation, Conceptualisation\u003cstrong\u003e. JK:\u0026nbsp;\u003c/strong\u003eWriting \u0026ndash; review \u0026amp; editing, Writing \u0026ndash; original draft, Supervision, Visualization, Validation, Methodology, Investigation, Conceptualisation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank all the data managers and the scientists who made available those data for this study. GSG acknowledges the Prime Minister\u0026apos;s Research Fellowship (PMRF; Grant No: 2402787), Ministry of Education, India, for funding his Doctoral study at IIT KGP and the United States India Education Foundation for his grant through the Fulbright-Kalam Climate fellowship for Doctoral Research (Grant No: 3067/FNDR/2024-2025) at the Lamont-Doherty Earth Observatory and Columbia Climate School, Columbia University, New York. JK and GSG thank the Director, Indian Institute of Technology Kharagpur (IIT Kgp), HoC, CORAL IIT Kgp and the Ministry of Education (MoE) for facilitating the study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGEOS CHEM and GCAP model is available via https://geos-chem.readthedocs.io/en/stable/\u003c/p\u003e\n\u003cp\u003eSSP data is available via https://tntcat.iiasa.ac.at/SspDb\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBrasseur, G.P. and Jacob, D.J., 2017. Modeling of atmospheric chemistry. Cambridge University Press.\u003c/li\u003e\n\u003cli\u003eMacintyre, H.L. and Evans, M.J., 2010. Sensitivity of a global model to the uptake of N 2 O 5 by tropospheric aerosol. Atmospheric Chemistry and Physics, 10(15),7409\u0026ndash;7414.\u003c/li\u003e\n\u003cli\u003eDentener, F.J. and Crutzen, P.J., 1993. Reaction of N2O5 on tropospheric aerosols: Impact on the global distributions of NO x, O3 and OH. Journal of Geophysical Research: Atmospheres, 98(D4), 7149\u0026ndash;7163.\u003c/li\u003e\n\u003cli\u003eKuttippurath, J., Abbhishek, K., Gopikrishnan, G.S. and Pathak, M., 2022. Investigation of long\u0026ndash;term trends and major sources of atmospheric HCHO over India. Environmental Challenges, 7, 100477.\u003c/li\u003e\n\u003cli\u003eKuttippurath, J., Gopikrishnan, G.P., M\u0026uuml;ller, R., Godin-Beekmann, S. and Brioude, J., 2024. No severe ozone depletion in the tropical stratosphere in recent decades. Atmospheric Chemistry and Physics, 24(11), 6743\u0026ndash;6756.\u003c/li\u003e\n\u003cli\u003eGopikrishnan, G.S., Kuttippurath, J., Raj, S., Singh, A. and Abbhishek, K., 2022. Air quality during the COVID\u0026ndash;19 lockdown and unlock periods in India analyzed using satellite and ground-based measurements. Environmental Processes, 9(2), 28.\u003c/li\u003e\n\u003cli\u003eGopikrishnan, G.S. and Kuttippurath, J., 2024. Global tropical and extra-tropical tropospheric ozone trends and radiative forcing deduced from satellite and ozonesonde measurements for the period 2005\u0026ndash;2020. Environmental Pollution, 361, 124869.\u003c/li\u003e\n\u003cli\u003eTan, Z., Lu, K., Jiang, M., Su, R., Dong, H., Zeng, L., Xie, S., Tan, Q. and Zhang, Y., 2018. Exploring ozone pollution in Chengdu, southwestern China: A case study from radical chemistry to O3-VOC-NOx sensitivity. Science of the Total Environment, 636, 775\u0026ndash;786.\u003c/li\u003e\n\u003cli\u003eSzopa, S., Aumont, B. and Madronich, S., 2005. Assessment of the reduction methods used to develop chemical schemes: building of a new chemical scheme for VOC oxidation suited to three-dimensional multiscale HO x-NO x-VOC chemistry simulations. Atmospheric Chemistry and Physics, 5(9), 2519\u0026ndash;2538.\u003c/li\u003e\n\u003cli\u003eDuncan, B.N., Yoshida, Y., Olson, J.R., Sillman, S., Martin, R.V., Lamsal, L., Hu, Y., Pickering, K.E., Retscher, C., Allen, D.J. and Crawford, J.H., 2010. Application of OMI observations to a space-based indicator of NOx and VOC controls on surface ozone formation. Atmospheric Environment, 44(18), 2213\u0026ndash;2223.\u003c/li\u003e\n\u003cli\u003eWestervelt, D.M., Ma, C.T., He, M.Z., Fiore, A.M., Kinney, P.L., Kioumourtzoglou, M.A., Wang, S., Xing, J., Ding, D. and Correa, G., 2019. Mid-21st century ozone air quality and health burden in China under emissions scenarios and climate change. Environmental Research Letters, 14(7), 074030.\u003c/li\u003e\n\u003cli\u003eFiore, A.M., Mickley, L.J., Zhu, Q. and Baublitz, C.B., 2024. Climate and tropospheric oxidizing capacity. Annual Review of Earth and Planetary Sciences, 52.\u003c/li\u003e\n\u003cli\u003eWang, Y., Wild, O., Chen, X., Wu, Q., Gao, M., Chen, H., Qi, Y. and Wang, Z., 2020. Health impacts of long-term ozone exposure in China over 2013\u0026ndash;2017. Environment International, 144, 106030.\u003c/li\u003e\n\u003cli\u003eZhao, K., Yuan, Z., Wu, Y., Huang, J., Yang, F., Zhang, X., Huang, D. and Jiang, R., 2023. Identification of synergistic control for ozone and PM2.5 pollution during a large-scale emission reduction in China. Atmospheric Research, 295, 107025.\u003c/li\u003e\n\u003cli\u003eIvatt, P.D., Evans, M.J. and Lewis, A.C., 2022. Suppression of surface ozone by an aerosol-inhibited photochemical ozone regime. Nature Geoscience, 15(7), 536\u0026ndash;540.\u003c/li\u003e\n\u003cli\u003eLiu, Q., Liu, T., Chen, Y., Xu, J., Gao, W., Zhang, H. and Yao, Y., 2019. Effects of aerosols on the surface ozone generation via a study of the interaction of ozone and its precursors during the summer in Shanghai, China. Science of the Total Environment, 675, 235\u0026ndash;246.\u003c/li\u003e\n\u003cli\u003eQu, Y., Voulgarakis, A., Wang, T., Kasoar, M., Wells, C., Yuan, C., Varma, S. and Mansfield, L., 2021. A study of the effect of aerosols on surface ozone through meteorology feedbacks over China. Atmospheric Chemistry and Physics, 21(7), 5705\u0026ndash;5718.\u003c/li\u003e\n\u003cli\u003eVan Vuuren, D.P., Riahi, K., Calvin, K., Dellink, R., Emmerling, J., Fujimori, S., Samir, K.C., Kriegler, E. and O\u0026rsquo;Neill, B., 2017. The Shared Socio-economic Pathways: Trajectories for human development and global environmental change. Global Environmental Change, 42, 148\u0026ndash;152.\u003c/li\u003e\n\u003cli\u003eO\u0026rsquo;Neill, B.C., Kriegler, E., Riahi, K., Ebi, K.L., Hallegatte, S., Carter, T.R., Mathur, R. and Van Vuuren, D.P., 2014. A new scenario framework for climate change research: the concept of shared socioeconomic pathways. Climatic Change, 122, pp.387-400.\u003c/li\u003e\n\u003cli\u003eGidden, M.J., Riahi, K., Smith, S.J., Fujimori, S., Luderer, G., Kriegler, E., Van Vuuren, D.P., Van Den Berg, M., Feng, L., Klein, D. and Calvin, K., 2019. Global emissions pathways under different socioeconomic scenarios for use in CMIP6: a dataset of harmonized emissions trajectories through the end of the century. Geoscientific Model Development, 12(4), 1443\u0026ndash;1475.\u003c/li\u003e\n\u003cli\u003eArnell, N.W., Lowe, J.A., Bernie, D., Nicholls, R.J., Brown, S., Challinor, A.J. and Osborn, T.J., 2019. The global and regional impacts of climate change under representative concentration pathway forcings and shared socioeconomic pathway socioeconomic scenarios. Environmental Research Letters, 14(8), 084046.\u003c/li\u003e\n\u003cli\u003eLiao, K.J., Tagaris, E., Napelenok, S.L., Manomaiphiboon, K., Woo, J.H., Amar, P., He, S. and Russell, A.G., 2008. Current and future linked responses of ozone and PM2. 5 to emission controls. Environmental Science and Technology, 42, 4670\u0026ndash;4675\u003c/li\u003e\n\u003cli\u003eRypdal, K., Berntsen, T., Fuglestvedt, J.S., Aunan, K., Torvanger, A., Stordal, F., Pacyna, J.M. and Nygaard, L.P., 2005. Tropospheric ozone and aerosols in climate agreements: scientific and political challenges. Environmental Science \u0026amp; Policy, 8(1), 29\u0026ndash;43.\u003c/li\u003e\n\u003cli\u003eZhang, L., Jacob, D.J., Downey, N.V., Wood, D.A., Blewitt, D., Carouge, C.C., van Donkelaar, A., Jones, D.B., Murray, L.T. and Wang, Y., 2011. Improved estimate of the policy-relevant background ozone in the United States using the GEOS-Chem global model with 1/2\u0026times; 2/3 horizontal resolution over North America. Atmospheric Environment, 45(37), 6769\u0026ndash;6776.\u003c/li\u003e\n\u003cli\u003eKim, P.S., Jacob, D.J., Fisher, J.A., Travis, K., Yu, K., Zhu, L., Yantosca, R.M., Sulprizio, M.P., Jimenez, J.L., Campuzano-Jost, P. and Froyd, K.D., 2015. Sources, seasonality and trends of southeast US aerosol: an integrated analysis of surface, aircraft and satellite observations with the GEOS-Chem chemical transport model. Atmospheric Chemistry and Physics, 15(18), 10411\u0026ndash;10433.\u003c/li\u003e\n\u003cli\u003eLin, H., Long, M.S., Sander, R., Sandu, A., Yantosca, R.M., Estrada, L.A., Shen, L. and Jacob, D.J., 2023. An Adaptive Auto‐Reduction Solver for Speeding Up Integration of Chemical Kinetics in Atmospheric Chemistry Models: Implementation and Evaluation in the Kinetic Pre‐Processor (KPP) Version 3.0. 0. Journal of Advances in Modeling Earth Systems, 15(2), e2022MS003293.\u003c/li\u003e\n\u003cli\u003eBates, K.H., Evans, M.J., Henderson, B.H. and Jacob, D.J., 2024. Impacts of updated reaction kinetics on the global GEOS-Chem simulation of atmospheric chemistry. Geoscientific Model Development, 17(4), 1511\u0026ndash;1524.\u003c/li\u003e\n\u003cli\u003eTravis, K.R., Jacob, D.J., Fisher, J.A., Kim, P.S., Marais, E.A., Zhu, L., Yu, K., Miller, C.C., Yantosca, R.M., Sulprizio, M.P. and Thompson, A.M., 2016. Why do models overestimate surface ozone in the Southeast United States?. Atmospheric Chemistry and Physics, 16(21), 13561\u0026ndash;13577.\u003c/li\u003e\n\u003cli\u003eDavid, L.M., Ravishankara, A.R., Brewer, J.F., Sauvage, B., Thouret, V., Venkataramani, S. and Sinha, V., 2019. Tropospheric ozone over the Indian subcontinent from 2000 to 2015: Data set and simulation using GEOS-Chem chemical transport model. Atmospheric Environment, 219, 117039.\u003c/li\u003e\n\u003cli\u003eChristiansen, A., Mickley, L.J., Liu, J., Oman, L.D. and Hu, L., 2022. Multidecadal increases in global tropospheric ozone derived from ozonesonde and surface site observations: can models reproduce ozone trends?. Atmospheric Chemistry and Physics, 22(22), 14751\u0026ndash;14782.\u003c/li\u003e\n\u003cli\u003eMao, Y.H., Shang, Y., Liao, H., Cao, H., Qu, Z. and Henze, D.K., 2024. Sensitivities of ozone to its precursors during heavy ozone pollution events in the Yangtze River Delta using the adjoint method. Science of the Total Environment, 925, 171585.\u003c/li\u003e\n\u003cli\u003eWu, S., Mickley, L.J., Jacob, D.J., Logan, J.A., Yantosca, R.M. and Rind, D., 2007. Why are there large differences between models in global budgets of tropospheric ozone?. Journal of Geophysical Research: Atmospheres, 112(D5).\u003c/li\u003e\n\u003cli\u003eMurray, L.T., Mickley, L.J., Kaplan, J.O., Sofen, E.D., Pfeiffer, M. and Alexander, B., 2014. Factors controlling variability in the oxidative capacity of the troposphere since the Last Glacial Maximum. Atmospheric Chemistry and Physics, 14(7), 3589\u0026ndash;3622.\u003c/li\u003e\n\u003cli\u003eKelley, M., Schmidt, G.A., Nazarenko, L.S., Bauer, S.E., Ruedy, R., Russell, G.L., Ackerman, A.S., Aleinov, I., Bauer, M., Bleck, R. and Canuto, V., 2020. GISS‐E2. 1: Configurations and climatology. Journal of Advances in Modeling Earth Systems, 12(8), e2019MS002025.\u003c/li\u003e\n\u003cli\u003eMiller, R.L., Schmidt, G.A., Nazarenko, L.S., Bauer, S.E., Kelley, M., Ruedy, R., Russell, G.L., Ackerman, A.S., Aleinov, I., Bauer, M. and Bleck, R., 2021. CMIP6 historical simulations (1850\u0026ndash;2014) with GISS‐E2. 1. Journal of Advances in Modeling Earth Systems, 13(1), e2019MS002034.\u003c/li\u003e\n\u003cli\u003eKolb, C.E., Cox, R.A., Abbatt, J.P.D., Ammann, M., Davis, E.J., Donaldson, D.J., Garrett, B.C., George, C., Griffiths, P.T., Hanson, D.R. and Kulmala, M., 2010. An overview of current issues in the uptake of atmospheric trace gases by aerosols and clouds. Atmospheric Chemistry and Physics, 10(21), 10561\u0026ndash;10605.\u003c/li\u003e\n\u003cli\u003eChristian, K.E., Brune, W.H., Mao, J. and Ren, X., 2018. Global sensitivity analysis of GEOS-Chem modeled ozone and hydrogen oxides during the INTEX campaigns. Atmospheric Chemistry and Physics, 18(4), 2443\u0026ndash;2460.\u003c/li\u003e\n\u003cli\u003eMao, J., Jacob, D.J., Evans, M.J., Olson, J.R., Ren, X., Brune, W.H., St Clair, J.M., Crounse, J.D., Spencer, K.M., Beaver, M.R. and Wennberg, P.O., 2010. Chemistry of hydrogen oxide radicals (HO x) in the Arctic troposphere in spring. Atmospheric Chemistry and Physics, 10(13), 5823\u0026ndash;5838.\u003c/li\u003e\n\u003cli\u003eStavrakou, T., M\u0026uuml;ller, J.F., Boersma, K.F., Van Der A, R.J., Kurokawa, J., Ohara, T. and Zhang, Q., 2013. Key chemical NO x sink uncertainties and how they influence top-down emissions of nitrogen oxides. Atmospheric Chemistry and Physics, 13(17), 9057\u0026ndash;9082.\u003c/li\u003e\n\u003cli\u003eSheehy, P.M., Volkamer, R., Molina, L.T. and Molina, M.J., 2010. Oxidative capacity of the Mexico City atmosphere\u0026ndash;Part 2: A RO x radical cycling perspective. Atmospheric Chemistry and Physics, 10(14), 6993\u0026ndash;7008.\u003c/li\u003e\n\u003cli\u003eAndreae, M.O. and Crutzen, P.J., 1997. Atmospheric aerosols: Biogeochemical sources and role in atmospheric chemistry. Science, 276(5315), 1052-1058.\u003c/li\u003e\n\u003cli\u003eMcNeill, V.F., 2017. Atmospheric aerosols: clouds, chemistry, and climate. Annual Review of Chemical and Biomolecular Engineering, 8(1), 427\u0026ndash;444.\u003c/li\u003e\n\u003cli\u003eKuttippurath, J. and Kashyap, R., 2023. Greening of India: forests or croplands?. Applied Geography, 161, 103115.\u003c/li\u003e\n\u003cli\u003eKuttippurath, J., Abbhishek, K., Gopikrishnan, G.S. and Pathak, M., 2022. Investigation of long\u0026ndash;term trends and major sources of atmospheric HCHO over India. Environmental Challenges, 7, 100477.\u003c/li\u003e\n\u003cli\u003eYadav, M., Soni, K., Soni, B.K., Singh, N.K. and Bamniya, B.R., 2019. Source apportionment of particulate matter, gaseous pollutants, and volatile organic compounds in a future smart city of India. Urban Climate, 28, 100470.\u003c/li\u003e\n\u003cli\u003eSahu, L.K., Yadav, R. and Pal, D., 2016. Source identification of VOCs at an urban site of western India: Effect of marathon events and anthropogenic emissions. Journal of Geophysical Research: Atmospheres, 121(5), 2416\u0026ndash;2433.\u003c/li\u003e\n\u003cli\u003eCarter, W.P. and Seinfeld, J.H., 2012. Winter ozone formation and VOC incremental reactivities in the Upper Green River Basin of Wyoming. Atmospheric Environment, 50, 255\u0026ndash;266.\u003c/li\u003e\n\u003cli\u003eXu, L., Myneni, R.B., Chapin III, F.S., Callaghan, T.V., Pinzon, J.E., Tucker, C.J., Zhu, Z., Bi, J., Ciais, P., T\u0026oslash;mmervik, H. and Euskirchen, E.S., 2013. Diminished temperature and vegetation seasonality over northern high latitudes. Nature Climate Change, 3, 581\u0026ndash;586.\u003c/li\u003e\n\u003cli\u003eYi, C., Wei, S. and Hendrey, G., 2014. Warming climate extends dryness-controlled areas of terrestrial carbon sequestration. Scientific Reports, 4(1), 5472.\u003c/li\u003e\n\u003cli\u003eHarr, B., Pu, B. and Jin, Q., 2024. The emission, transport, and impacts of the extreme Saharan dust storm of 2015. Atmospheric Chemistry and Physics, 24(15), 8625\u0026ndash;8651.\u003c/li\u003e\n\u003cli\u003eCaton Harrison, T., Washington, R., Engelstaedter, S., Jones, R.G. and Savage, N.H., 2021. Influence of Orography Upon Summertime Low‐Level Jet Dust Emission in the Central and Western Sahara. Journal of Geophysical Research: Atmospheres, 126(23), e2021JD035025.\u003c/li\u003e\n\u003cli\u003eProspero, J.M., 2007. African dust: Its large-scale transport over the Atlantic ocean and its impact on the Mediterranean region. In Regional climate variability and its impacts in the Mediterranean area (15\u0026ndash;38). Dordrecht: Springer Netherlands.\u003c/li\u003e\n\u003cli\u003eZhang, M., Mu, P., Chen, X., Wu, D., Lu, F., Qi, P., Li, L.B. and Gong, W., 2023. Study on the Optical\u0026ndash;Physical Properties of Aerosol Layers in Africa Based on a Laser Satellite. Atmosphere, 14(10), 1524.\u003c/li\u003e\n\u003cli\u003eHoelzemann, J.J., Longo, K.M., Fonseca, R.M., Do Ros\u0026aacute;Rio, N.M., Elbern, H., Freitas, S.R. and Pires, C., 2009. Regional representativity of AERONET observation sites during the biomass burning season in South America determined by correlation studies with MODIS Aerosol Optical Depth. Journal of Geophysical Research: Atmospheres, 114(D13).\u003c/li\u003e\n\u003cli\u003ePiketh, S.J., Swap, R.J., Maenhaut, W., Annegarn, H.J. and Formenti, P., 2002. Chemical evidence of long‐range atmospheric transport over southern Africa. Journal of Geophysical Research: Atmospheres, 107(D24), ACH-7.\u003c/li\u003e\n\u003cli\u003eJacob, D.J., 2000. Heterogeneous chemistry and tropospheric ozone. Atmospheric Environment, 34(12-14), 2131\u0026ndash;2159.\u003c/li\u003e\n\u003cli\u003eLi, M., Su, H., Li, G., Ma, N., P\u0026ouml;schl, U. and Cheng, Y., 2019. Relative importance of gas uptake on aerosol and ground surfaces characterized by equivalent uptake coefficients. Atmospheric Chemistry and Physics, 19(16), 10981\u0026ndash;11011.\u003c/li\u003e\n\u003cli\u003eKuttippurath, J. and Raj, S., 2021. Two decades of aerosol observations by AATSR, MISR, MODIS and MERRA-2 over India and Indian Ocean. Remote Sensing of Environment, 257, 112363.\u003c/li\u003e\n\u003cli\u003eZhang, Z., Wu, W., Fan, M., Wei, J., Tan, Y. and Wang, Q., 2019. Evaluation of MAIAC aerosol retrievals over China. Atmospheric Environment, 202, 8-16.\u003c/li\u003e\n\u003cli\u003eKloster, S., Dentener, F., Feichter, J., Raes, F., Van Aardenne, J., Roeckner, E., Lohmann, U., Stier, P. and Swart, R., 2008. Influence of future air pollution mitigation strategies on total aerosol radiative forcing. Atmospheric Chemistry and Physics, 8(21), 6405\u0026ndash;6437.\u003c/li\u003e\n\u003cli\u003eAmann, M., Kiesewetter, G., Sch\u0026ouml;pp, W., Klimont, Z., Winiwarter, W., Cofala, J., Rafaj, P., H\u0026ouml;glund-Isaksson, L., Gomez-Sabriana, A., Heyes, C. and Purohit, P., 2020. Reducing global air pollution: the scope for further policy interventions. Philosophical Transactions of the Royal Society A, 378(2183), 20190331.\u003c/li\u003e\n\u003cli\u003ePye, H.O.T., Liao, H., Wu, S., Mickley, L.J., Jacob, D.J., Henze, D.K. and Seinfeld, J.H., 2009. Effect of changes in climate and emissions on future sulfate‐nitrate‐ammonium aerosol levels in the United States. Journal of Geophysical Research: Atmospheres, 114(D1).\u003c/li\u003e\n\u003cli\u003eSchade, G. W., and A. H. Goldstein (2001), Fluxes of oxygenated volatile organic compounds from a ponderosa pine plantation, Journal of Geophysical Research, 106, 3111\u0026ndash;3123.\u003c/li\u003e\n\u003cli\u003eTsigaridis, K., and M. Kanakidou (2003), Global modelling of secondary organic aerosol in the troposphere: A sensitivity analysis, Atmospheric Chemistry and Physics, 3, 1849\u0026ndash;1869.\u003c/li\u003e\n\u003cli\u003eLathiere, J., Hauglustaine, D.A., De Noblet‐Ducoudr\u0026eacute;, N., Krinner, G. and Folberth, G.A., 2005. Past and future changes in biogenic volatile organic compound emissions simulated with a global dynamic vegetation model. Geophysical Research Letters, 32(20).\u003c/li\u003e\n\u003cli\u003eSun, Y. and Augenbroe, G., 2014. Urban heat island effect on energy application studies of office buildings. Energy and Buildings, 77, 171\u0026ndash;179.\u003c/li\u003e\n\u003cli\u003eRaj, S., Paul, S.K., Chakraborty, A. and Kuttippurath, J., 2020. Anthropogenic forcing exacerbating the urban heat islands in India. Journal of Environmental Management, 257, 110006.\u003c/li\u003e\n\u003cli\u003eTian, H.Z., Hao, J.M., Hu, M.Y. and Nie, Y.F., 2007. Recent trends of energy consumption and air pollution in China. Journal of Energy Engineering, 133(1), 4\u0026ndash;12.\u003c/li\u003e\n\u003cli\u003eDaioglou, V., Faaij, A.P., Saygin, D., Patel, M.K., Wicke, B. and van Vuuren, D.P., 2014. Energy demand and emissions of the non-energy sector. Energy \u0026amp; Environmental Science, 7(2), 482\u0026ndash;498.\u003c/li\u003e\n\u003cli\u003eZhou, M., Xie, Y., Wang, C., Shen, L. and Mauzerall, D.L., 2024. Impacts of current and climate induced changes in atmospheric stagnation on Indian surface PM2. 5 pollution. Nature Communications, 15(1), 7448.\u003c/li\u003e\n\u003cli\u003eHorton, D.E., Skinner, C.B., Singh, D. and Diffenbaugh, N.S., 2014. Occurrence and persistence of future atmospheric stagnation events. Nature Climate Change, 4(8), 698\u0026ndash;703.\u003c/li\u003e\n\u003cli\u003eWeaver, A.J., Zickfeld, K., Montenegro, A. and Eby, M., 2007. Long term climate implications of 2050 emission reduction targets. Geophysical Research Letters, 34(19).\u003c/li\u003e\n\u003cli\u003eLyon, C., Saupe, E.E., Smith, C.J., Hill, D.J., Beckerman, A.P., Stringer, L.C., Marchant, R., McKay, J., Burke, A., O\u0026rsquo;Higgins, P. and Dunhill, A.M., 2022. Climate change research and action must look beyond 2100. Global Change Biology, 28(2), 349\u0026ndash;361.\u003c/li\u003e\n\u003cli\u003eLiousse, C., Assamoi, E., Criqui, P., Granier, C. and Rosset, R., 2014. Explosive growth in African combustion emissions from 2005 to 2030. Environmental Research Letters, 9(3), 035003.\u003c/li\u003e\n\u003cli\u003eCalvin, K., Pachauri, S., De Cian, E. and Mouratiadou, I., 2016. The effect of African growth on future global energy, emissions, and regional development. Climatic Change, 136, 109\u0026ndash;125.\u003c/li\u003e\n\u003cli\u003eBurton, C., Kelley, D.I., Jones, C.D., Betts, R.A., Cardoso, M. and Anderson, L., 2022. South American fires and their impacts on ecosystems increase with continued emissions. Climate Resilience and Sustainability, 1(1), p.e8.\u003c/li\u003e\n\u003cli\u003eMart\u0026iacute;nez, S.H., Koberle, A., Rochedo, P., Schaeffer, R., Lucena, A., Szklo, A., Ashina, S. and van Vuuren, D.P., 2015. Possible energy futures for Brazil and Latin America in conservative and stringent mitigation pathways up to 2050. Technological Forecasting and Social Change, 98, 186\u0026ndash;210.\u003c/li\u003e\n\u003cli\u003eKuttippurath, J., Singh, A., Dash, S.P., Mallick, N., Clerbaux, C., Van Damme, M., Clarisse, L., Coheur, P.F., Raj, S., Abbhishek, K. and Varikoden, H., 2020. Record high levels of atmospheric ammonia over India: Spatial and temporal analyses. Science of the Total Environment, 740, 139986.\u003c/li\u003e\n\u003cli\u003eTao, M., Chen, L., Wang, Z., Tao, J. and Su, L., 2013. Satellite observation of abnormal yellow haze clouds over East China during summer agricultural burning season. Atmospheric environment, 79, 632\u0026ndash;640.\u003c/li\u003e\n\u003cli\u003eMoghani, M. and Archer, C.L., 2020. The impact of emissions and climate change on future ozone concentrations in the USA. Air Quality, Atmosphere \u0026amp; Health, 13, 1465\u0026ndash;1476.\u003c/li\u003e\n\u003cli\u003eArchibald, A.T., Neu, J.L., Elshorbany, Y.F., Cooper, O.R., Young, P.J., Akiyoshi, H., Cox, R.A., Coyle, M., Derwent, R.G., Deushi, M. and Finco, A., 2020. Tropospheric Ozone Assessment Report: A critical review of changes in the tropospheric ozone burden and budget from 1850 to 2100. Elementa Science of the Anthropocene, 8(1), 034.\u003c/li\u003e\n\u003cli\u003eRao, S., Klimont, Z., Smith, S.J., Van Dingenen, R., Dentener, F., Bouwman, L., Riahi, K., Amann, M., Bodirsky, B.L., van Vuuren, D.P. and Reis, L.A., 2017. Future air pollution in the Shared Socio-economic Pathways. Global Environmental Change, 42, 346\u0026ndash;358.\u003c/li\u003e\n\u003cli\u003eDhamodharan, K., Varma, V.S., Veluchamy, C., Pugazhendhi, A. and Rajendran, K., 2019. Emission of volatile organic compounds from composting: A review on assessment, treatment and perspectives. Science of The Total Environment, 695, 133725.\u003c/li\u003e\n\u003cli\u003eDuan, C., Liao, H., Wang, K. and Ren, Y., 2023. The research hotspots and trends of volatile organic compound emissions from anthropogenic and natural sources: A systematic quantitative review. Environmental Research, 216, 114386.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"npj-climate-and-atmospheric-science","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"npjclimatsci","sideBox":"Learn more about [npj Climate and Atmospheric Science](http://www.nature.com/npjclimatsci/)","snPcode":"41612","submissionUrl":"https://submission.springernature.com/new-submission/41612/3","title":"npj Climate and Atmospheric Science","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Aerosol uptake, Surface Ozone, SDG, SSP, GEOS Chem, GCAP","lastPublishedDoi":"10.21203/rs.3.rs-5932296/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5932296/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e​Aerosols significantly influence tropospheric oxidation and ozone formation by modulating photolysis rates and radical sinks.​ This study employs the GEOS-Chem model to analyze different aerosol heterogeneous uptake coefficients (0, 0.1, 0.2, 0.4) and their effects on photochemical ozone levels across regions in the near-present and under future Shared Socioeconomic Pathways (SSP) scenarios. Higher uptake coefficients enhance the sink of radical species like HO\u003csub\u003e2\u003c/sub\u003e and expand the aerosol-inhibited regime (AIR), particularly in otherwise NO\u003csub\u003ex\u003c/sub\u003e-limited regions like India and East Asia, leading to a notable increase in surface ozone (40\u0026ndash;50%), especially during colder months. Projections for 2046 indicate a global reduction in AIR areas, resulting from stricter emission controls. By 2096, the extent of AIR further diminishes, with regions such as Southeast Asia transitioning to NOx-limited conditions, though aerosol uptake of HO\u003csub\u003e2\u003c/sub\u003e continues to elevate surface ozone levels by 10\u0026ndash;15% in heavily aerosol-loaded areas.\u003c/p\u003e","manuscriptTitle":"Aerosol inhibition on photochemical surface ozone formation under future climate and air quality scenarios","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-02-04 16:28:04","doi":"10.21203/rs.3.rs-5932296/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-03-06T03:25:00+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-03-06T01:24:50+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-02-28T15:22:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"140878405094747974797719210270707941325","date":"2025-02-05T16:44:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"186669030210443925589442341768683103917","date":"2025-02-03T10:27:03+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-02-01T10:10:26+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-01-31T13:56:21+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-01-31T13:48:32+00:00","index":"","fulltext":""},{"type":"submitted","content":"npj Climate and Atmospheric Science","date":"2025-01-30T19:10:50+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"npj-climate-and-atmospheric-science","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"npjclimatsci","sideBox":"Learn more about [npj Climate and Atmospheric Science](http://www.nature.com/npjclimatsci/)","snPcode":"41612","submissionUrl":"https://submission.springernature.com/new-submission/41612/3","title":"npj Climate and Atmospheric Science","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"69d87d40-4d97-4973-9875-0cc90d8bcf9b","owner":[],"postedDate":"February 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":43758826,"name":"Earth and environmental sciences/Environmental sciences"},{"id":43758827,"name":"Earth and environmental sciences/Environmental sciences/Environmental chemistry"}],"tags":[],"updatedAt":"2025-04-28T16:02:44+00:00","versionOfRecord":{"articleIdentity":"rs-5932296","link":"https://doi.org/10.1038/s41612-025-01048-2","journal":{"identity":"npj-climate-and-atmospheric-science","isVorOnly":false,"title":"npj Climate and Atmospheric Science"},"publishedOn":"2025-04-25 15:57:53","publishedOnDateReadable":"April 25th, 2025"},"versionCreatedAt":"2025-02-04 16:28:04","video":"","vorDoi":"10.1038/s41612-025-01048-2","vorDoiUrl":"https://doi.org/10.1038/s41612-025-01048-2","workflowStages":[]},"version":"v1","identity":"rs-5932296","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5932296","identity":"rs-5932296","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}