Nuclear Conflict in Eastern Europe: Climate Disruption & Radiological Fallout

Nuclear Conflict in Eastern Europe: Climate Disruption & Radiological Fallout | 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 Nuclear Conflict in Eastern Europe: Climate Disruption & Radiological Fallout Ananth Ranjithkumar, Nathan Mayne, Anthony C. Jones, Jim M. Haywood This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8344698/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 12 You are reading this latest preprint version Abstract Geopolitical tensions in Eastern Europe underscores the urgency of addressing the climatic and radiological consequences of a regional nuclear conflict. Using an Earth System Model, we simulate a conflict at the Ukraine-Russia border that releases five million-tons of black carbon (BC) into the stratosphere. The extended stratospheric lifetime of BC induces hemispheric climate disruption: the Northern Hemisphere cools by ~ 1°C in year-1, with anomalies of − 5°C in Russia and − 4°C in the United States; surface solar radiation declines by ~ 30 W m⁻² over the US; and precipitation decreases by ~ 40% across mid-latitude croplands. Stratospheric warming alters subtropical and polar jets, displacing the Intertropical Convergence Zone ~ 2–6° southward, delaying climate recovery by ~ 6 years. Long-lived radionuclides transported with BC disperse globally, with ~ 40% depositing in the Southern Hemisphere. These findings underscore the importance of nuclear-risk reduction and provide a robust benchmark for food-security and humanitarian-impact assessments. Earth and environmental sciences/Climate sciences Earth and environmental sciences/Environmental sciences Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 1. Introduction Geopolitical tensions around the world brings into focus the prospect of nuclear war, and its global consequences. Early studies in the 1980s warned that smoke from burning cities and firestorms caused by nuclear detonation could block sunlight and plunge the Earth’s surface into darkness and cold – a “nuclear winter” 1–3 . Subsequent research confirmed these findings and highlighted the potential for long-term agricultural collapse and severe global food insecurity 4 – 10 . Central to all nuclear winter scenario modelling is the role of Black Carbon (BC) aerosol particles lofted into the stratosphere by nuclear-induced firestorms and the subsequent fires days after detonation. Black carbon efficiently absorbs solar radiation, heating the surrounding air and driving the smoke cloud higher into the stratosphere, thereby prolonging the residence time of these aerosol particles resulting in sustained climate anomalies for years. Despite a robust body of research on the climate aftermath of nuclear war, important scenario-specific gaps remain. Past studies have primarily examined an all-out superpower nuclear conflict (United States of America and Russia) resulting in ~ 150 million-tons (or 150 Teragram (Tg)) of BC being emitted into the stratosphere, or South Asian (India and Pakistan) regional wars resulting in 5–50 Tg stratospheric BC 6–8,11–14 . No study to date has focused on the climatic and radiological consequences of a nuclear conflict in Eastern Europe despite current nuclear risks in the region. This region has dense urban-industrial centres and critical infrastructure, and a nuclear conflict there could generate substantial soot and radioactive debris with unique global dispersion patterns. In this study, we use a state-of-the-art climate model 15 to explore a hypothetical nuclear conflict scenario near the Ukraine-Russia border (32.1° E–45° E, 46.4–52.3° N; Area ≈ 6 × 10⁵ km²), releasing 5Tg of BC into the atmosphere, between 9–13 km, with total BC load estimates in this region ranging between 1.4–7.1 Tg (supplementary section 1). The amount of BC released into the stratosphere for the smallest scale nuclear wars modelled in the past range from 1 to 12 Tg, depending on the fuel density, population density and detonation targets 9 , 13 , 14 . Focusing on a 5 Tg BC scenario allows us a direct comparison to earlier studies which focused on a 5 Tg BC India-Pakistan war scenario. The configuration and implementation of these scenarios within UKESM are described in more detail in Section 4 (Methods). We simulate the atmospheric evolution of BC aerosol, the resulting changes in global climate, short term radiological fallout, and track the radionuclides that adhere to the black carbon particles (e.g. Cesium-137 (Cs-137) and Strontium-90 (Sr-90)) to map the long-term radiological fallout from global BC surface deposition. Our results provide the first scenario-specific assessment of the combined climate and radiological consequences of a nuclear conflict in Eastern Europe. 2. Results 2.1 Ukraine – Russia Conflict: Year 1 after Detonation Aerosol dispersion and stratospheric heating over the first 20 days after detonation (Fig. 1 , panels a–f) After detonation, we explore the spatiotemporal evolution of the aerosol particles and the solar-radiative heating of the lower stratosphere (at 20 km) for the first 20 days (Fig. 1 ), which sets the stage for the longer-term climate response. The spatial dispersion of the BC aerosol particles is illustrated in Fig. 1 (panels a–c), which shows the evolution of total aerosol optical depth (AOD) at 550 nm on days 1, 5, and 20. On day 1 (a), the BC particles remain confined to Eastern Europe. By day 5 (b), they have been lofted further into the stratosphere and been transported eastward by prevailing westerly winds across the Northern Hemisphere (NH). By day 20 (c), the particles have dispersed extensively throughout the NH, spreading towards the pole and equator. Corresponding stratospheric temperature changes at 20 km altitude are shown in panels d–f for days 10, 15 and 20. A modest hemispheric-mean stratospheric warming of ~ 2°C in the Northern Hemisphere (NH) and < 1°C in the Southern Hemisphere (SH) is evident by day 10 (d). By day 15 (e) the NH mean stratospheric temperatures have increased by ~ 5°C (SH ~ 1.8°C), and by day 20 (f) it exceeds ~ 8°C (SH ~ 1.6°C), reflecting both the dispersion and solar-radiative heating of the BC particles. These patterns illustrate how even a moderate (5 Tg) BC atmospheric perturbation from a “limited” nuclear conflict can rapidly disperse BC aerosols, globally blocking out sunlight and driving stratospheric heating. a-c , Total aerosol optical depth anomaly at 550 nm on days 1, 5 and 20 after detonation, illustrating aerosol spatial dispersion in the days after detonation. d-f , Stratospheric temperature anomalies at 20 km on days 10, 15 and 20, illustrating a delayed but accelerating atmospheric thermal response. Hemisphere-mean anomalies are annotated beneath each temperature panel. Stippling in panels d-f marks grid points where the anomaly is not statistically significant (two-tailed Student’s t-test, p ≥ 0.05). Atmospheric Black carbon concentration and Temperature (Fig. 2 , panels a-d) Building on the hemispheric dispersion and solar-radiative heating shown in Fig. 1 , we examine the vertical distribution of BC mass concentration and temperature changes at the start (Month 1) and end (Month 12) of the first year (Fig. 2 ). Figure 2 (panels a-b) shows the zonal-mean latitude–altitude cross-sections of BC mass concentration (ensemble mean) in first and last month of the year. In the first month (Fig. 2 a), the mean BC concentration maxima occurs at ~ 15km with concentrations > 0.1 µg m⁻³ in the NH. By contrast, by end of the year (Fig. 2 b, month 12) elevated BC concentrations are observed throughout the stratospheric column across both hemispheres, illustrating the interhemispheric transport of BC. Figure 2 (panels c-d) shows the corresponding zonal mean temperature anomalies (ensemble mean). In the first month (Fig. 2 c), peak zonal mean warming of ~ 15°C occurs near 20 km altitude. By year end (Fig. 2 d), the stratospheric temperature increase becomes more vertically extensive throughout the atmospheric column, with zonal mean temperature anomalies as high as ~ 40°C. The evolution of the vertical and spatial dispersion of BC, and the associated thermal response highlights the critical role of aerosol-chemistry-dynamics feedbacks in modulating both the timing and magnitude of the Earth's climate response. a–b , Black carbon mass concentration (µg m⁻³) in Month 1 (a) and Month 12 (b). c–d , Corresponding zonal-mean temperature anomalies (°C) in Month 1 (c) and Month 12 (d). a–b , Surface temperature anomalies : (a) Monthly mean Temperature anomalies (shading represents the ensemble variability) for the Northern Hemisphere (blue), Southern Hemisphere (red), Russia (green) and USA (purple) (b) Annual-mean temperature anomaly. c–d , Surface solar radiation anomaly : (c) Monthly mean surface solar radiation anomalies (d) Annual-mean surface solar flux anomaly. e–f , Precipitation anomaly : (e) Monthly rainfall anomalies (f) Annual Mean Precipitation Percentage Change. g–h , Stratospheric wind anomalies : (g) Time series of maximum zonal (blue), meridional (orange) and vertical (green) wind anomalies at 40 km. (h) Annual-mean spatial map of wind‐speed anomalies (shading) showing strengthened subtropical jets and altered polar circulations. Stippling indicates grid points where the anomaly is not statistically significant (two-tailed Student’s t-test, p ≥ 0.05). Together, these panels demonstrate how the solar-radiative properties of BC drive substantial changes to climate variables in the 1st year after nuclear detonation. Figure 3 illustrates both the seasonal cycle and annual-mean climate responses in year 1 post-detonation: panels a–b show surface temperature anomalies, c–d the change in downward solar radiation, e–f precipitation anomalies, and d–h stratospheric wind perturbations. We also highlight climate anomalies across the land regions of Russia and the USA. Surface Temperature Cooling (Fig. 3 a–b) The seasonal cycle (a) shows that surface temperature anomalies in the NH develop rapidly within the first few months after detonation, reaching ≈ − 1.5°C by the end of the first year. By contrast, the SH shows negligible temperature anomalies year-round, owing to the thermal buffering influence of the Southern Ocean. The annual-mean temperature response (b) confirms a hemispheric-average cooling of ≈ − 1°C in the NH compared to a slight warming of + 0.01°C in the SH. Strong regional cooling ( > − 4°C) occurs over mid and high-latitude continental regions. Russia experiences the strongest anomaly (≈ − 5°C by end of year), owed to its high-latitude location, minimal buffering from the ocean, and the low heat capacity of its continental land surface. The United States also experiences substantial cooling ( ≈ − 3°C in spring), with ensemble members showing year-end anomalies as extreme as ≈ − 10°C. Solar Dimming (Fig. 3 c–d) As the black carbon disperses across the atmosphere globally, it induces a negative anomaly in the incoming surface solar radiation. In the NH, the downward solar radiation anomaly is ≈ − 20 W m⁻² by April (c). As the BC spreads into the SH stratosphere, the solar flux anomaly is ≈ − 15 W m⁻² by end of year (SH summer). Mid-latitude continental zones in North America and Russia show anomalies between − 10 to − 50 W m⁻² throughout the year, underscoring the vulnerability of key agricultural regions. This is reflected in annual-mean reductions in net primary productivity (NPP) of up to 0.2 kgC m⁻² across large parts of the NH, particularly over regions of North America and Asia (Supplementary Section 2, Figure S1 ). The annual-mean downward solar radiation anomalies (d) are substantial, ≈ −13.4 W m⁻² in the NH and ≈ − 6.3 W m⁻² in the SH. The spatial pattern of solar flux anomaly closely follows the changing stratospheric BC mass concentration through the year (Fig. 2 ), with the largest springtime reductions occurring over the United States, Russia, and much of Eurasia, regions responsible for a significant share of global crop production. Precipitation Disruption ( Fig. 3 e-f, 4 a-b ) : Significant shifts in global precipitation are observed in year 1 as a direct response to the strong NH surface cooling and associated changes in large-scale circulation. Annual-mean precipitation decreases by 20–40% across much of the NH mid-latitudes, with locally larger decreases (up to 80%) over densely populated and agricultural regions of Asia and West Africa (f), alongside land regions of the United States and Russia experiencing precipitation decreases of up to 20 mm month⁻¹ in year 1 (e). These patterns are also consistent with the seasonal cycle shown in Fig. 4 a, where India and Niger experience pronounced monsoon season decreases of ~ 40–100 mm month⁻¹ in July–August. The spatial pattern of drying corresponds closely to changes in the meridional overturning circulation and vertical winds. Meridional Stream-function anomalies and vertical winds over longitudinal sectors (64°E – 91°E and 16°W – 13°E respectively) (Supplementary Section 2, Figure S2-S3), indicate a supressed assent over India and West Africa during the NH summer (JJA) resulting in dryer conditions relative to the control simulation. In contrast, the SH mid-latitudes experience substantial precipitation increases, especially over Southern Africa and Australia, where annual precipitation rises by up to 100%. The seasonal cycle shows that both Australia and Namibia exhibit consistent precipitation increases from February-April, ~ 20–60 mm month⁻¹ more than the control simulation (Fig. 4 b). Stream-function and vertical wind anomalies over longitudinal sectors (9°E – 40°E and 112°E – 154°E) (Supplementary Section 2, Figure S4-S5) confirm the presence of a strengthened anomalous counterclockwise cell and increased vertical winds which indicates enhanced low-level ascent, which explains the increases in precipitation. These hemispheric contrasts are also influenced by the southward displacement of the Intertropical Convergence Zone (ITCZ) by approximately 2–6° between March and June caused by the asymmetric NH cooling. The weakened, shifted ITCZ produces lower equatorial precipitation by ~ 0.5-1.0 mm day⁻¹ in year 1 (Supplementary Section 2, Figure S6). Collectively, the strongly altered overturning circulation and displaced Intertropical tropical convergence zones explain the hemispheric dipole: widespread dryer conditions across the NH and enhanced rainfall over the SH subtropical regions. Stratospheric Jet Strengthening (Fig. 3 g–h, 5 a-c) The stratospheric wind dynamics driven by atmospheric temperature changes are prominently illustrated through wind anomalies at ~ 40 km altitude (panel g-h), with the column vertical profile of the zonal, meridional and vertical winds shown in Fig. 5 a-c. The time series (g) highlights sustained zonal jet anomalies with velocities ranging between 50–200 m s⁻¹, meridional wind anomalies between 20–70 m s⁻¹, along with smaller but significant vertical wind anomalies between 0.02–0.1 m s⁻¹, indicative of pronounced changes in stratospheric vertical transport and mixing processes, peaking notably in the spring and summer months. The annual-mean wind anomalies at 40 km (h), shows strengthening of the subtropical and polar jets in both hemispheres, alongside perturbations to the vertical winds at high latitudes. In comparison, previous studies 16 modelling a 5 Tg BC India–Pakistan conflict reported lower maximum stratospheric zonal wind anomalies of ~ 40 m s⁻¹ during the NH-winter, whereas our modelled scenario shows peak zonal wind anomaly between 100–200 m s⁻¹ during the same time period, reflecting differences in injection latitude, soot heating distribution, and structural inter-model differences. (a) Zonal-wind anomaly, Δu (m s⁻¹). (b) Meridional‐wind anomaly, Δv (m s⁻¹). (c) Vertical‐wind anomaly, Δw (cm s − 1 ), Impact of Conflict Scenario on Global Climate ( Fig. 6 ) : To evaluate how the geographic origin of the BC alters the subsequent Earth system response, we compare two war scenarios, each with 5 Tg BC released into stratosphere: one originating from the Ukraine–Russia border region (“UKRRUS”) and the other from the widely studied India–Pakistan regional conflict scenario (“INDPAK”) 6,7,9,13,14 . Previous modelling studies of the 5 Tg INDPAK scenario consistently show declines in surface temperature and global mean precipitation 6 , 7 , 9 . While there are notable differences in model setups/configurations in past modelling studies – which includes date of detonation, horizontal and vertical resolution, and aerosol microphysics; our INDPAK simulations produce quantitatively similar results. Reported global mean surface cooling ranges from 0.5 to 2°C 6,7,9,17 , with reductions in global mean precipitation during the first year of 0.2 to 0.5 mm day⁻¹. Figure 6 (panel a) shows the zonal mean AOD anomaly for days 8 and 20 for both scenarios. The UKRRUS aerosol dispersion (blue/green) remains more confined to mid and high latitudes, whereas in the INDPAK scenario (red/orange) there is more aerosol dispersion into the SH and less so towards the NH high latitudes. Panel (b) illustrates the corresponding annual-mean AOD anomaly, highlighting stronger aerosol loading across Northern Eurasia and the Arctic in the UKRRUS case relative to INDPAK. This spatial pattern reflects the more persistent poleward transport of soot in the higher-latitude UKRRUS injection compared to the tropical-latitude INDPAK source. Consistent with these spatial contrasts in aerosol loading, Figure S7 (supplementary section 2) shows that both scenarios produce a comparable global-mean cooling of approximately 0.5°C, but the UKRRUS case has an earlier peak NH cooling (end of year 1) compared with the INDPAK scenario (end of year 2). These differences in aerosol dispersion translate into distinct spatial patterns of climate disruption (Fig. 6 , panels c–e). Consequently, surface temperatures are lower at northern latitudes for UKRRUS (up to − 2°C) than for the INDPAK scenario, but somewhat warmer at lower latitudes ( ≈ + 1°C over parts of South Asia) (panel c). These responses follow the spatial distribution of the change in the surface solar fluxes (panel d). Solar dimming is more pronounced in mid-latitude continental regions for UKRRUS (–0.7 W m⁻² hemispheric mean) but yields a net positive anomaly in the SH (+ 2.2 W m⁻²) because the INDPAK BC plume disperses more across the tropics and into the SH. Relative to INDPAK, the UKRRUS scenario drives a hemispheric asymmetry in the precipitation response (panel e), characterized by widespread suppression in the NH (up to 20 mm month − 1 ) and localized enhancement over Southeast Asia (up to 50 mm month − 1 ). These anomalies are primarily driven by a southward displacement of the ITCZ, which shifts up to 4° further south by month 6 in the UKRRUS scenario compared to INDPAK (Supplementary Section 2, Figure S6). Consistent with this shift, analysis of the meridional stream function and vertical winds confirm strengthened vertical ascent over Southeast Asia driving enhanced rainfall during the NH summer (Supplementary Section 2, Figure S8). (a) Zonal-mean aerosol optical depth (AOD) anomalies at days 8 (solid) and 20 (dashed) for the Ukraine–Russia (blue/green) and India–Pakistan (red/orange) scenarios. (b) Annual-mean AOD anomaly at 550 nm (UKRRUS – INDPAK), (c) Annual-mean surface temperature difference (UKRRUS – INDPAK), (d) Annual-mean change in downward solar radiation (UKRRUS – INDPAK). (e) Annual-mean change in precipitation (UKRRUS - INDPAK) Stippling in panels b-d marks grid points where the anomaly is not statistically significant (two-tailed Student’s t-test, p ≥ 0.05). 2.2 Ukraine-Russia Conflict: Multi-Year Climate Response To evaluate the long-term climate impacts of the nuclear conflict, Fig. 7 illustrates the temporal evolution of key surface climate variables over the subsequent 10-year period. In each panel, solid lines denote the ensemble-mean anomalies, while the shaded envelopes indicate the ensemble spread for the Northern Hemisphere (blue), Southern Hemisphere (red), Russia (green) and USA (purple). Surface Temperature Land regions of Russia experience the largest negative temperatures anomalies (Fig. 7 a), as low as ~ − 6°C (ensemble member minimum). The NH mean surface temperature also falls sharply (approximately − 1°C), whereas the SH temperature response is negligible owing to the buffering effect of the Southern Ocean. Between years 2 and 4, surface temperatures gradually recover as atmospheric black carbon (BC) concentrations decrease, and by year 6, anomalies approach baseline conditions. The temperature response over the US is similar to Russia with the ensemble minimum as low as ~ -4°C. a , Monthly surface air temperature anomalies (°C) , b , Downward solar radiation anomalies (W m⁻²) c , Precipitation change (%) Panels a-c illustrate the multi-year climate disruption and recovery which lasts ~ 6 years. The bold line indicates the ensemble mean and shaded bands representing the 6-member ensemble spread, for the Northern Hemisphere (blue), Southern Hemisphere (red), Russia (green), and USA (purple). Downward Surface Solar Radiation : Incoming surface solar radiation anomalies (Fig. 7 b) closely tracks the temperature changes. In the first year, the NH experiences a maximum decrease of approximately − 13 W m⁻², with the US showing the largest decrease (≈ − 30 W m⁻²) and Russia around − 20 W m⁻². As the aerosol dispersed globally into the SH, the SH anomalies go as low as approximately − 10 W m⁻² between year 1 and 2. From years 1 through 8, solar flux anomalies globally recover and approach baseline conditions. Precipitation changes Precipitation anomalies (Fig. 7 c) closely track the temporal evolution of surface temperature and surface solar radiation anomalies. During the first two years, NH mean precipitation declines by roughly 10–20%, equivalent to about − 6 to -10 mm month⁻¹, with particularly strong reductions over Russia (up to -25%, or ≈ -15 to -20 mm month⁻¹). The USA experiences more modest decreases of ~ 5–10% in comparison to Russia, albeit with substantial ensemble spread. These suppressed precipitation rates persist through years 3–6 before gradually returning toward baseline conditions. Precipitation anomalies in the SH remain minimal, constrained to within ± 5% over the entire simulation period. Together, these multi-year time series demonstrate that a nuclear war in Eastern Europe produces rapid, hemisphere‐wide changes to surface temperature, solar radiation, and precipitation. This is followed by a gradual climate recovery phase, with our model projecting a return to near-baseline conditions within ~ 6 years. 2.3 Fallout Analysis Near term fallout – 48 hours post detonation Due to the inherent complexity and sensitivity of fallout dynamics to environmental parameters such as wind speed, precipitation, and conflict locations, we utilize a simplified empirical fallout model developed by Glasstone and Dolan (1977) 18 . This approach is derived from historical nuclear weapons test data and has been applied to nuclear war impact modelling studies in the recent past 13 , and enables us to estimate areas exposed to radioactive contamination within the first 48 hours following detonation. The 5Tg BC that is emitted into the upper troposphere-lower stratosphere could result from a combination of both groundbursts and airbursts. Our radiological fallout estimates (methodology documented in the supplementary, section 3 ) are carried out for 100 simultaneous 15-kiloton (kt) surface nuclear detonations scenario, evenly distributed across approximately 613,000 km² region along the Ukraine–Russia border (46.4°–52.3°N, 32.1°–45.0°E) (Fig. 8 a). The mean surface winds over the region in the first month is ~ 5.3 m s - 1 (19 km h - 1 ) towards the northeast (~ 40°). Climatologically, radioactive debris from surface detonations would primarily be expected to disperse towards the northeastern shortly after the explosions. By adapting the Glasstone–Dolan fallout model to these specific wind conditions, we determine that each 15-kt detonation generates plumes that extend downwind approximately 62.7 km for radiation doses exceeding 1 Sv, 26.1 km for doses exceeding 5 Sv, and approximately 17.9 km for the highest lethal threshold of 10 Sv (Supplementary Section 3, Table S1 ) in 48 hours. The fallout plume width ranges from ~ 0.9 km for ≥ 10 Sv to ~ 3.2 km for ≥ 1 Sv. Collectively, the 100 detonations produce a cumulative contaminated area of approximately ~ 20,000 km² (in 48 hours) at doses exceeding 1 Sv, ~ 3500 km² above 5 Sv, and ~ 1,600 km² above 10 Sv. For perspective, the 48-hour fallout zone which experience doses ≥ 5 Sv surpasses the size of the Chernobyl exclusion zone (~ 2,600 km²) 19 , although the isotopic composition would differ, with weapon fallout dominated by short-lived fission products (e.g. I-131, Ba-140, Te-132) rather than the longer-lived Cs-137 and Sr-90 typical of Chernobyl 20 . Considering the average population density of the region (~ 49 persons/km², with a total population of ~ 30.2 million), we estimate significant human exposure and health impacts. Approximately a million people would experience radiation doses exceeding 1 Sv, a threshold typically sufficient to induce acute radiation sickness. Within zones receiving ≥ 5 Sv, roughly 170,000 people would encounter severe radiation sickness. The most critically impacted zone, receiving ≥ 10 Sv, would affect approximately an estimated 80,000 people, facing virtually certain fatal outcomes without advanced medical care. For perspective, the regulatory upper limit for artificial public exposure is only 1 mSv per year 21 , highlighting the extreme magnitude of these doses. Beyond immediate health implications, the long-term consequences would persistently affect the region. Areas receiving ≥ 1 Sv would require extended evacuation, prolonged exclusion, or intensive remediation measures. Residual soil contamination, disruption of agriculture, and extensive infrastructure damage would contribute to prolonged socioeconomic instability. This analysis underscores that even a limited, regional nuclear conflict involving relatively low-yield weapons can produce extensive, long-lasting humanitarian and environm.ental devastation 22 . Long term fallout from global BC transport and deposition Nuclear detonation results in the release of several radionuclides which can adhere to BC particles. Radionuclide adherence to aerosol particles has been well documented - for example, in observations following the Fukushima nuclear accident 23 , 24 . The self-lofting of BC into the stratosphere combined with nuclear war-induced precipitation reductions delays wet removal of BC aerosol, prolonging its residence time. These BC-driven atmospheric changes allow radioactive debris to spread broadly before deposition. The atmospheric circulation and gradual surface deposition of BC facilitates widespread global dispersal of these radionuclides. Long-lived radionuclides such as Cesium-137 (Cs-137; T₁/₂ ≈ 30.2 year) and Strontium-90 (Sr-90; T₁/₂ ≈ 28.8 year) are routinely monitored in long-term fallout assessments owing to their persistent environmental residence, propensity for biological uptake, and well-documented health impacts over decadal timescales 25 . Assuming the weapons used are Uranium-235 (U-235) fission bombs, we estimate the yields of Cs-137 and Sr-90 and their adherence to black carbon (BC), with assumptions and parameters detailed in Supplementary Section 4 and Table S2. We recognise that the extent to which radionuclides from surface detonations reach the stratosphere depends on their proximity to large fires and associated convective plumes; therefore, these estimates are an idealised upper-bound case for the distribution of radionuclides with soot. a , Location of the target region at the Ukraine-Russia border where 100 nuclear detonations (each 15 kt yield) are uniformly distributed. b , Temporal evolution of cumulative global and hemispheric BC deposition (in Tg) over a 10-year period, highlighting the e-folding timescale (~ 3.5 years) for global BC removal. Shaded areas represent ensemble spread. c , 10-year cumulative effective dose (mSv) from Cesium-137(Cs-137) and Strontium-90 (Sr-90) deposition. d , Top 10 countries by mean cumulative effective dose (mSv) e , Top 10 countries by Collective radiation dose (person–Sv) A decade after detonation, deposition patterns exhibit a hemispheric asymmetry: fallout is initially confined largely to the NH, followed by substantial cross-equatorial transport into the SH, and ultimately dispersing radioactive contamination across the globe (Fig. 8 b-e). Figure 8 b shows that approximately two-thirds of the injected BC is deposited from the atmosphere in the first 4 years, corresponding to an atmospheric e-folding time of ~ 3.5 years (red dashed line). By year 10 nearly all the 5 Tg of BC has deposited globally. The surface deposition is initially concentrated in the NH, which receives most of the fallout in the first 1–2 years, but gradual cross-equatorial transport results in ~ 40% of the BC being deposited in the SH by year 10. Maps of long-lived radionuclide fallout (Supplementary Section 2, Figure S9 a-b) for Cs-137 and Sr-90 shows a widespread global deposition (methodology and assumptions are documented in supplementary section 4), with the highest surface radiation levels up to ~ 10 Bq m⁻² in the NH by year 10. Both Cs-137 and Sr-90 shows a very similar spatial pattern (as both isotopes are transported with the same BC aerosol particles). In contrast, large parts of the SH areas receive negligible fallout ( 0.4 Bq m⁻². These results indicate that the NH mid-latitudes including parts of Central Asia, Europe and the Middle East accumulate the bulk of the global radioactive fallout. Despite the broad geographic extent of radioactive contamination, the cumulative dose map (Fig. 8 c) shows that resulting radiation exposures remain very low. The 50-year cumulative effective dose from Cs137 + Sr90 deposition is at most ~ 0.9 mSv in the most affected regions (e.g. parts of the Central Asia). Most of the NH land area receives ~ 0.1–0.3 mSv, and virtually all populated areas in the SH stay below 0.07 mSv. Such doses are far below the natural background (~ 2.4 mSv yr⁻¹) and by themselves would pose little direct health risk 26 . However, Fig. 8 d indicates discernible differences in the radiation dose at the country level. The highest national mean 50-year cumulative doses (≈ 0.25–0.48 mSv per person) occur in smaller countries situated under the primary BC deposition areas: for example, Tajikistan (0.48 mSv) and Bhutan (0.38 mSv) top the list, followed countries in Europe and Central Asia. Larger countries such as Russia have much higher localized deposition near the detonation zone, but their country average dose is diluted by vast areas with minimal fallout. Collective radiation dose metrics 26 (Fig. 8 e) underscore how population size modulates impact. China and India’s large population, combined with its subtropical latitude, leads to a high collective radiation dose (China ~ 400000 person–Sv and India ~ 200000 person-Sv), followed by countries in Central Asia, Africa and Europe. Figures 7 b–e demonstrate that BC-driven atmospheric transport can distribute radioactive fallout across hemispheres, leading to low-level contamination and associated risks far from the conflict region. For perspective, the hypothetical doses estimated here are several orders of magnitude smaller than those produced by atmospheric nuclear weapons testing prior to the 1963 Partial Test Ban Treaty. By that time, approximately 189 Mt of fission yield had been released into the atmosphere, roughly ten times the total fission yield assumed in our scenario, resulting in global mean annual effective doses peaking near 0.1–0.15 mSv in just one year (1963) 27 . In contrast, our modelled Cs-137 + Sr-90 fallout yields peak regional cumulative doses of ~ 0.8 mSv over a period of 50 years, underscoring how much smaller the long-term radiological burden would be under our simulated scenario. 3. Discussion and Conclusions Our simulations demonstrate that a limited regional nuclear conflict in Eastern Europe, involving a combination of ground and surface bursts that releases 5 million-tons of black carbon into the stratosphere, triggers globally disruptive climate anomalies and radioactive fallout. The Northern Hemisphere surface temperature cools by ~ 1°C in the first year, with land regions of US and Russia experiencing temperature anomalies of up to -4°C and − 5°C, peak downward solar-flux reductions are approximately 40 W m⁻², and precipitation reductions of 20–40% across key mid-latitude agricultural zones. Although the Southern-Ocean heat capacity buffers the Southern hemisphere surface temperature response, the perturbed meridional temperature gradients displace and weaken the Intertropical Convergence Zone. The global climate system recovers gradually: two-thirds of the atmospheric BC is deposited onto the Earth’s surface after ~ 4 years, and near-surface climate metrics return to baseline around year 6. Previous modelling studies of the India-Pakistan war scenario (5 Tg BC) consistently shows declines in surface temperature and global mean precipitation 6 , 7 , 9 . While there are notable differences in model setup/configurations - including horizontal and vertical resolution and aerosol microphysics, our India-Pakistan simulations produce quantitatively similar results. Reported global mean surface cooling ranges from 0.5 to 2°C 6,7,9 , with reductions in global mean precipitation during the first year of 0.2 to 0.5 mm day⁻¹. Comparing the India–Pakistan war scenario with the Ukraine–Russia conflict is critical for assessing the impact of the geographic/latitudinal origin of nuclear conflict-driven BC emissions. Relative to an India–Pakistan scenario, the Ukraine–Russia scenario climate response remains more confined to northern mid and high latitudes, intensifying cooling and solar dimming over Eurasia and North America. Conversely, the India–Pakistan scenario spreads BC more efficiently across the tropics, altering more the Southern-Hemisphere radiative budgets.. BC source-region sensitivities underscore the need for scenario-specific assessments in nuclear war research. Radiological consequences, though modest compared to the climatic disruptions have been quantified. Long-lived radionuclides (Cs-137, Sr-90) adhere to BC and are transported and deposited globally with 40% deposited in the SH. The 50-year cumulative effective doses peak at ~ 0.9 mSv, well below natural background levels (~ 2.4 mSv yr⁻¹). The collective radiation dose is the highest in countries like China, India, and other parts of central Asia, Europe and North America. Thus, even countries distant from the war zone incur quantifiable health burdens via atmospheric transport and radionuclide surface deposition. Our results quantify both the climatic and radiological consequences of a nuclear conflict in Eastern Europe, allowing us to better visualise its detrimental impacts across the world. Although the specific scenario analysed in this study focuses on the Ukraine–Russia border, similar quantities of smoke could be injected into the mid-latitude lower stratosphere from other regional conflicts or urban-industrial targets (e.g., in North Korea or other parts of Europe), producing a broadly comparable climate response. This highlights the general applicability of our findings to any mid-latitude nuclear war of comparable scale. These findings highlight the far-reaching consequences of nuclear war and reinforces the objectives of the Treaty on the Non-Proliferation of Nuclear Weapons (NPT): preventing the spread of nuclear weapons and related technology, promoting cooperation in the peaceful use of nuclear energy, and advancing the goal of nuclear disarmament. 4. Methods In this study, we used version 1.1 of the UK Earth System Model (UKESM1.1) 28–30 , which supports multiple configurations 31 . Our simulations utilize the N96L85 setup, characterized by a horizontal grid resolution of 1.875° longitude by 1.25° latitude, equating to approximately 135 km. The model has 85 vertical levels with 50 levels between 0 and 18 km and 35 levels between 18 and 85 km. The atmospheric composition is modelled through the UK Chemistry and Aerosol (UKCA) 32 , 33 component of UKESM, which incorporates gas-phase and aerosol chemistry. Emissions from anthropogenic sources, biomass burning, biogenic activity, and dimethyl sulfide (DMS) are prescribed using datasets from Hoesly et al. (2018), van Marle et al. (2017), Sindelarova et al. (2014), and Spiro et al. (1992) 34 – 37 . The aerosol scheme within UKCA is referred to as the Global Model of Aerosol Processes, GLOMAP 33 , 38 . It uses a two-moment pseudo-modal approach and simulates multicomponent global aerosol, which includes sulphate, black carbon, organic matter and sea spray. Dust is simulated separately using a different parametrisation 39 . GLOMAP includes key aerosol processes such as nucleation, condensation, coagulation, wet and dry deposition, and aerosol-cloud interactions. The aerosol particle size distribution is characterized using five log-normal modes, 4 soluble (nucleation soluble, Aitken soluble, accumulation soluble, coarse soluble) and 1 insoluble mode (Aitken insoluble). UKCA is fully integrated with UKESM’s dynamical core, enabling the transport of tracers via advection, convection, and mixing within the boundary layer. To simulate a “limited” nuclear war scenario over Eastern Europe (32.1° E–45° E, 46.4–52.3° N; ≈ 6 × 10⁵ km²), we emit 5 Tg of black carbon (BC) aerosol with a mean particle diameter of 150 nm and standard deviation of 1.59, distributed evenly across between 300–150 hPa ( ~ 9 km − 13 km altitude), with coagulation turned off in the stratosphere. The emitted BC particles are assumed to be spherical and are placed in the accumulation soluble mode of the UKCA–GLOMAP aerosol scheme. Each mode represents an internally mixed population whose optical properties are calculated using Mie theory within the RADAER radiation scheme. The complex refractive index for BC used in UKESM 29 is 1.85 − 0.71i at a wavelength of 550 nm, and soluble coatings are represented dynamically through condensation and coagulation with other aerosol species. These assumptions are consistent with the default UKESM1.1 configuration and have been used in previous UKESM aerosol–radiation studies 29 . The model does not explicitly simulate the fire plume because of its coarse resolution, and we assume 5Tg BC is emitted directly into the upper troposphere-lower stratosphere after detonation. The 5Tg of BC emission assumption used in past regional nuclear war studies simulating India-Pakistan are derived from fuel load estimates as detailed in Toon et al., 2007 13 . We acknowledge that some studies 6 have also simulated the co-emission of organic carbon with black carbon following detonation. These emissions depend on factors such as the fuel source, detonation location, and burning efficiency, and can influence the atmospheric lifetime of black carbon 6 . This aspect is not examined in our study. In our study for short term fallout estimates, we assume the 100 detonation locations are uniformly distributed across the region as highlighted in Fig. 8 a. The BC is also emitted uniformly for a week at the start of year 2015, from Jan 1st to Jan 7th. The other emission files follow a Shared Socioeconomic Pathway (SSP) SSP126 scenario, and we use the model start files referenced in Mulcahy et al., 2023 30 to setup 6 different ensemble members. In this study we run 6 ensemble members (for 20 years) for two scenarios with the same start date and setup, one over the Ukraine-Russia border and the other over the entire land region of India-Pakistan. The methodology/assumptions for estimating the radionuclide adherence and global fallout are documented in Supplementary section 4. Declarations Competing interests The authors declare no competing interests. Funding This work was carried out under the SHIVER (StratospHeric aerosol Impacts under Various nuclEaR conflict scenarios) project funded by the Future Of Life Institute (WT998567). Author Contribution AR contributed to the climate modelling using UKESM, scientific analysis of the data and drafting of the manuscript. NM contributed scientific insight in reducing model instabilities. AJ provided scientific insight and finetuning the draft of the paper. JH helped guide and conceptualise the study, provided scientific insight and secured the grant that funded this work. Data Availability The data that supports the findings can be viewed from [10.5281/zenodo.17632006](https:/doi.org/10.5281/zenodo.17632006) and [10.5281/zenodo.17779131](https:/doi.org/10.5281/zenodo.17779131) . These doi’s have restricted access right now and will be made available upon request and made public before publication. References Crutzen, P. J. & Birks, J. W. The Atmosphere After a Nuclear War: Twilight at Noon. Ambio 11, 125–152 (2016). Turco, R. P., Toon, O. B., Ackerman, T. P., Pollack, J. B. & Sagan, C. Nuclear Winter: Global Consequences of Multiple Nuclear Explosions. Science (1979) 222, 1283–1292 (1983). Turco, R. P., Toon, O. B., Ackerman, T. P., Pollack, J. B. & Sagan, C. Climate and smoke: An appraisal of nuclear winter. Science (1979) 247, 166–176 (1990). Abbasi, K. et al. Reducing the risks of nuclear war—the role of health professionals. Matern Child Nutr 19, e13554 (2023). Xia, L. et al. Global food insecurity and famine from reduced crop, marine fishery and livestock production due to climate disruption from nuclear war soot injection. Nat Food 3, 586–596 (2022). Pausata, F. S. R., Lindvall, J., Ekman, A. M. L. & Svensson, G. Climate effects of a hypothetical regional nuclear war: Sensitivity to emission duration and particle composition. Earths Future 4, 498–511 (2016). Mills, M. J., Toon, O. B., Lee-Taylor, J. & Robock, A. Multidecadal global cooling and unprecedented ozone loss following a regional nuclear conflict. Earths Future 2, 161–176 (2014). Coupe, J., Bardeen, C. G., Robock, A. & Toon, O. B. Nuclear Winter Responses to Nuclear War Between the United States and Russia in the Whole Atmosphere Community Climate Model Version 4 and the Goddard Institute for Space Studies ModelE. Journal of Geophysical Research: Atmospheres 124, 8522–8543 (2019). Robock, A. et al. Climatic consequences of regional nuclear conflicts. Atmos Chem Phys 7, 2003–2012 (2007). Jagermeyr, J. et al. A regional nuclear conflict would compromise global food security. Proc Natl Acad Sci U S A 117, 7071–7081 (2020). Coupe, J. et al. Sudden Reduction of Antarctic Sea Ice Despite Cooling After Nuclear War. J Geophys Res Oceans 128, e2022JC018774 (2023). Coupe, J. et al. Nuclear Niño response observed in simulations of nuclear war scenarios. Commun Earth Environ 2, 1–11 (2021). Toon, O. B. et al. Atmospheric effects and societal consequences of regional scale nuclear conflicts and acts of individual nuclear terrorism. Atmos Chem Phys 7, 1973–2002 (2007). Stenke, A. et al. Climate and chemistry effects of a regional scale nuclear conflict. Atmos Chem Phys 13, 9713–9729 (2013). Mulcahy, J. P. et al. UKESM1.1: development and evaluation of an updated configuration of the UK Earth System Model. Geosci Model Dev 16, 1569–1600 (2023). Coupe, J. & Robock, A. The Influence of Stratospheric Soot and Sulfate Aerosols on the Northern Hemisphere Wintertime Atmospheric Circulation. Journal of Geophysical Research: Atmospheres 126, e2020JD034513 (2021). Wagman, B. M., Lundquist, K. A., Tang, Q., Glascoe, L. G. & Bader, D. C. Examining the Climate Effects of a Regional Nuclear Weapons Exchange Using a Multiscale Atmospheric Modeling Approach. Journal of Geophysical Research: Atmospheres 125, e2020JD033056 (2020). Glasstone, S. & Dolan, P. J. The Effects of Nuclear Weapons. Third edition. https://doi.org/10.2172/6852629 (1977) doi:10.2172/6852629. Bondarkov, M. D. et al. Environmental radiation monitoring in the Chernobyl Exclusion Zone-history and results 25 years after. Health Phys 101, 442–485 (2011). Environmental Consequences of the Chernobyl Accident and their Remediation: Twenty Years of Experience | IAEA. https://www.iaea.org/publications/7382/environmental-consequences-of-the-chernobyl-accident-and-their-remediation-twenty-years-of-experience . The 2007 Recommendations of the International Commission on Radiological Protection. ICRP publication 103. Ann ICRP 37, 1–332 (2007). National Academies of Sciences, E. and M. Potential Environmental Effects of Nuclear War. Potential Environmental Effects of Nuclear War https://doi.org/10.17226/27515 (2025) doi: 10.17226/27515 . Kristiansen, N. I., Stohl, A. & Wotawa, G. Atmospheric removal times of the aerosol-bound radionuclides 137Cs and 131I measured after the Fukushima Dai-ichi nuclear accident– A constraint for air quality and climate models. Atmos Chem Phys 12, 10759–10769 (2012). Xu, S. et al. Speciation of Radiocesium and Radioiodine in Aerosols from Tsukuba after the Fukushima Nuclear Accident. Environmental Science & Technology (Washington) 49, 1017–1024 (2015). United Nations Scientific Committe on the Effects of Atomic Radiation. Sources and Effects of Ionizing Radiation Volume I: source. United Nations Scientific Committee on the Effects I, 1–654 (2000). UNSCEAR. United Nations scientific committee on the effect of atomic radiation, sources and effects of ionizing radiation. United Nations I, 66 (2008). UNSCEAR 2000 Report Volume II. https://www.unscear.org/unscear/en/publications/2000_2.html . Sellar, A. A. et al. UKESM1: Description and Evaluation of the U.K. Earth System Model. J Adv Model Earth Syst 11, 4513–4558 (2019). Mulcahy, J. P. et al. Improved Aerosol Processes and Effective Radiative Forcing in HadGEM3 and UKESM1. J Adv Model Earth Syst 10, 2786–2805 (2018). Mulcahy, J. P. et al. UKESM1.1: development and evaluation of an updated configuration of the UK Earth System Model. Geosci Model Dev 16, 1569–1600 (2023). Walters, D. et al. The Met Office Unified Model Global Atmosphere 6.0/6.1 and JULES Global Land 6.0/6.1 configurations. Geosci Model Dev 10, 1487–1520 (2017). T Archibald, A. et al. Description and evaluation of the UKCA stratosphere-troposphere chemistry scheme (StratTrop vn 1.0) implemented in UKESM1. Geosci Model Dev 13, 1223–1266 (2020). O’Connor, F. M. et al. Evaluation of the new UKCA climate-composition model-Part 2: The troposphere. Geosci Model Dev 7, 41–91 (2014). Hoesly, R. M. et al. Historical (1750–2014) anthropogenic emissions of reactive gases and aerosols from the Community Emissions Data System (CEDS). Geosci Model Dev 11, 369–408 (2018). Van Marle, M. J. E. et al. Historic global biomass burning emissions for CMIP6 (BB4CMIP) based on merging satellite observations with proxies and fire models (1750–2015). Geosci Model Dev 10, 3329–3357 (2017). Sindelarova, K. et al. Global data set of biogenic VOC emissions calculated by the MEGAN model over the last 30 years. Atmos Chem Phys 14, 9317–9341 (2014). Spiro, P. A., Jacob, D. J. & Logan, J. A. Global inventory of sulfur emissions with 1° × 1° resolution. J Geophys Res 97, 6023–6036 (1992). T Archibald, A. et al. Description and evaluation of the UKCA stratosphere-troposphere chemistry scheme (StratTrop vn 1.0) implemented in UKESM1. Geosci Model Dev 13, 1223–1266 (2020). Woodward, S. Modeling the atmospheric life cycle and radiative impact of mineral dust in the Hadley Centre climate model. Journal of Geophysical Research: Atmospheres 106, 18155–18166 (2001). Additional Declarations No competing interests reported. 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03:55:24","extension":"html","order_by":21,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":116138,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8344698/v1/a25db6f6c5881ee788889b96.html"},{"id":99018665,"identity":"6522e718-912f-49b9-9a5f-001f6c6f91eb","added_by":"auto","created_at":"2025-12-26 03:55:22","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1730503,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEvolution of aerosol optical depth and stratospheric temperature anomalies (ensemble mean) following 5Tg BC aerosol release into the stratosphere (9 – 13 km) from 100×15 kt detonations at the Ukraine-Russia border (32.1° E–45° E, 46.4–52.3° N; ≈ 6 × 10⁵ km²)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea-c\u003c/strong\u003e, Total aerosol optical depth anomaly at 550 nm on days 1, 5 and 20 after detonation, illustrating aerosol spatial dispersion in the days after detonation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ed-f\u003c/strong\u003e, Stratospheric temperature anomalies at 20 km on days 10, 15 and 20, illustrating a delayed but accelerating atmospheric thermal response. Hemisphere-mean anomalies are annotated beneath each temperature panel. Stippling in panels d-f marks grid points where the anomaly is \u003cem\u003enot\u003c/em\u003estatistically significant (two-tailed Student’s t-test, p ≥ 0.05).\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8344698/v1/a24999574351e3fa629aaa05.png"},{"id":99018671,"identity":"9ce754ec-25b7-414d-a466-44f41a94b6df","added_by":"auto","created_at":"2025-12-26 03:55:23","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":623083,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eZonal‐mean vertical profiles of BC mass concentration and temperature response (ensemble mean) in Month 1 and 12 after detonation.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea–b\u003c/strong\u003e, Black carbon mass concentration (μg m⁻³) in Month 1 (a) and Month 12 (b).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ec–d\u003c/strong\u003e, Corresponding zonal‐mean temperature anomalies (°C) in Month 1 (c) and Month 12 (d).\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8344698/v1/f8bd41fca4e3e6a0eaa75749.png"},{"id":99018677,"identity":"1ae2e7fa-8127-4223-ac03-3cad9cd0f74e","added_by":"auto","created_at":"2025-12-26 03:55:23","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1810589,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSeasonal and annual‐mean surface and stratospheric circulation response in the first-year post detonation.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea–b\u003c/strong\u003e, Surface temperature anomalies: (a) Monthly mean Temperature anomalies (shading represents the ensemble variability) for the Northern Hemisphere (blue), Southern Hemisphere (red), Russia (green) and USA (purple) (b) Annual‐mean temperature anomaly.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ec–d\u003c/strong\u003e, Surface solar radiation anomaly: (c) Monthly mean surface solar radiation anomalies (d) Annual‐mean surface solar flux anomaly.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ee–f\u003c/strong\u003e, Precipitation anomaly: (e) Monthly rainfall anomalies (f) Annual Mean Precipitation Percentage Change.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eg–h\u003c/strong\u003e, Stratospheric wind anomalies: (g) Time series of maximum zonal (blue), meridional (orange) and vertical (green) wind anomalies at 40 km. (h) Annual‐mean spatial map of wind‐speed anomalies (shading) showing strengthened subtropical jets and altered polar circulations.\u003c/p\u003e\n\u003cp\u003eStippling indicates grid points where the anomaly is not statistically significant (two-tailed Student’s t-test, p ≥ 0.05). Together, these panels demonstrate how the solar-radiative properties of BC drive substantial changes to climate variables in the 1\u003csup\u003est\u003c/sup\u003e year after nuclear detonation.\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8344698/v1/d5f5fa1c96d0588289f163d1.jpeg"},{"id":99018681,"identity":"db988bf2-c909-4606-9a1f-00afc90babb5","added_by":"auto","created_at":"2025-12-26 03:55:23","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":621905,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSimulated Year-1 monthly precipitation (mm month\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e-1\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e) for a) India and Niger (NH), and b) Australia and Namibia (SH).\u003c/strong\u003e Comparison of Control (blue) and 5Tg BC UKRRUS (red) scenarios. Solid and dashed lines represent the ensemble means for specific countries (indicated in the legend), with shaded bands indicating the ensemble range.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-8344698/v1/cd1aa91790956500afc1939a.png"},{"id":99018683,"identity":"c5388cd5-27c0-4271-b044-31d0224459e2","added_by":"auto","created_at":"2025-12-26 03:55:24","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":382774,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eZonal mean vertical profile of the zonal, meridional and vertical winds (ensemble mean) in the first-year post detonation.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(a)\u003c/strong\u003e Zonal‐wind anomaly, Δu (m s⁻¹). \u003cstrong\u003e(b)\u003c/strong\u003e Meridional‐wind anomaly, Δv (m s⁻¹). \u003cstrong\u003e(c)\u003c/strong\u003e Vertical‐wind anomaly, Δw (cm s\u003csup\u003e-1\u003c/sup\u003e),\u003c/p\u003e","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8344698/v1/7bc06769b1efc07ad783487b.jpeg"},{"id":99018669,"identity":"7bbc31e1-1aad-467e-9dff-9a8574b9e22c","added_by":"auto","created_at":"2025-12-26 03:55:23","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":2085483,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComparison between a Ukraine-Russia and an India-Pakistan Conflict to assess the influence of detonation location on climate.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(a)\u003c/strong\u003e Zonal-mean aerosol optical depth (AOD) anomalies at days 8 (solid) and 20 (dashed) for the Ukraine–Russia (blue/green) and India–Pakistan (red/orange) scenarios.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(b)\u003c/strong\u003e Annual‐mean AOD anomaly at 550 nm (UKRRUS – INDPAK),\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(c)\u003c/strong\u003e Annual‐mean surface temperature difference (UKRRUS – INDPAK),\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(d)\u003c/strong\u003e Annual‐mean change in downward solar radiation (UKRRUS – INDPAK).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(e)\u003c/strong\u003e Annual‐mean change in precipitation (UKRRUS - INDPAK)\u003c/p\u003e\n\u003cp\u003eStippling in panels b-d marks grid points where the anomaly is \u003cem\u003enot\u003c/em\u003e statistically significant (two-tailed Student’s t-test, p ≥ 0.05).\u003c/p\u003e","description":"","filename":"floatimage6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8344698/v1/d654f6dcbff5912a089b72e6.jpeg"},{"id":99018675,"identity":"91064091-69c6-4b3e-a5d0-f5b0828ec7e4","added_by":"auto","created_at":"2025-12-26 03:55:23","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":784834,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTen-year evolution of climate anomalies at the Ukraine-Russia border.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea\u003c/strong\u003e, \u003cstrong\u003eMonthly surface air temperature anomalies (°C),\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eb\u003c/strong\u003e, \u003cstrong\u003eDownward solar radiation anomalies (W m⁻²)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ec\u003c/strong\u003e, \u003cstrong\u003ePrecipitation change (%)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePanels a-c illustrate the multi-year climate disruption and recovery which lasts ~ 6 years. The bold line indicates the ensemble mean and shaded bands representing the 6-member ensemble spread, for the Northern Hemisphere (blue), Southern Hemisphere (red), Russia (green), and USA (purple).\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-8344698/v1/ad91b28c216c281c5154ca36.png"},{"id":99018678,"identity":"fc08f614-eff8-45e8-87e0-37877f79d126","added_by":"auto","created_at":"2025-12-26 03:55:23","extension":"jpeg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":1188907,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGlobal fallout analysis post detonation at the Ukraine-Russia border.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea\u003c/strong\u003e, Location of the target region at the Ukraine-Russia border where 100 nuclear detonations (each 15 kt yield) are uniformly distributed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eb\u003c/strong\u003e, Temporal evolution of cumulative global and hemispheric BC deposition (in Tg) over a 10-year period, highlighting the e-folding timescale (~3.5 years) for global BC removal. Shaded areas represent ensemble spread.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ec,\u003c/strong\u003e 10-year cumulative effective dose (mSv) from Cesium-137(Cs-137) and Strontium-90 (Sr-90) deposition.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ed,\u003c/strong\u003e Top 10 countries by mean cumulative effective dose (mSv)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ee,\u003c/strong\u003e Top 10 countries by Collective radiation dose (person–Sv)\u003c/p\u003e","description":"","filename":"floatimage8.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8344698/v1/a2c11c5923aab84b094a8a51.jpeg"},{"id":99322952,"identity":"99918b74-dea3-410a-8a45-dfb33fe471a0","added_by":"auto","created_at":"2025-12-31 16:44:37","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":10031025,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8344698/v1/a7699b2a-489c-4a08-91ee-3c6df770841e.pdf"},{"id":99018688,"identity":"7cae9b25-eb5d-483f-bd29-18f0ae53d0d0","added_by":"auto","created_at":"2025-12-26 03:55:24","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":9357606,"visible":true,"origin":"","legend":"","description":"","filename":"ranjithkumaretal2025supplementarynpjnew.docx","url":"https://assets-eu.researchsquare.com/files/rs-8344698/v1/66a16e030f0f34ddecb75222.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Nuclear Conflict in Eastern Europe: Climate Disruption \u0026 Radiological Fallout","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eGeopolitical tensions around the world brings into focus the prospect of nuclear war, and its global consequences. Early studies in the 1980s warned that smoke from burning cities and firestorms caused by nuclear detonation could block sunlight and plunge the Earth\u0026rsquo;s surface into darkness and cold \u0026ndash; a \u0026ldquo;nuclear winter\u0026rdquo;\u003csup\u003e1\u0026ndash;3\u003c/sup\u003e. Subsequent research confirmed these findings and highlighted the potential for long-term agricultural collapse and severe global food insecurity\u003csup\u003e\u003cspan additionalcitationids=\"CR5 CR6 CR7 CR8 CR9\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Central to all nuclear winter scenario modelling is the role of Black Carbon (BC) aerosol particles lofted into the stratosphere by nuclear-induced firestorms and the subsequent fires days after detonation. Black carbon efficiently absorbs solar radiation, heating the surrounding air and driving the smoke cloud higher into the stratosphere, thereby prolonging the residence time of these aerosol particles resulting in sustained climate anomalies for years.\u003c/p\u003e \u003cp\u003eDespite a robust body of research on the climate aftermath of nuclear war, important scenario-specific gaps remain. Past studies have primarily examined an all-out superpower nuclear conflict (United States of America and Russia) resulting in ~\u0026thinsp;150\u0026nbsp;million-tons (or 150 Teragram (Tg)) of BC being emitted into the stratosphere, or South Asian (India and Pakistan) regional wars resulting in 5\u0026ndash;50 Tg stratospheric BC\u003csup\u003e6\u0026ndash;8,11\u0026ndash;14\u003c/sup\u003e. No study to date has focused on the climatic and radiological consequences of a nuclear conflict in Eastern Europe despite current nuclear risks in the region. This region has dense urban-industrial centres and critical infrastructure, and a nuclear conflict there could generate substantial soot and radioactive debris with unique global dispersion patterns.\u003c/p\u003e \u003cp\u003eIn this study, we use a state-of-the-art climate model\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e to explore a hypothetical nuclear conflict scenario near the Ukraine-Russia border (32.1\u0026deg; E\u0026ndash;45\u0026deg; E, 46.4\u0026ndash;52.3\u0026deg; N; Area\u0026thinsp;\u0026asymp;\u0026thinsp;6 \u0026times; 10⁵ km\u0026sup2;), releasing 5Tg of BC into the atmosphere, between 9\u0026ndash;13 km, with total BC load estimates in this region ranging between 1.4\u0026ndash;7.1 Tg (supplementary section 1). The amount of BC released into the stratosphere for the smallest scale nuclear wars modelled in the past range from 1 to 12 Tg, depending on the fuel density, population density and detonation targets\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Focusing on a 5 Tg BC scenario allows us a direct comparison to earlier studies which focused on a 5 Tg BC India-Pakistan war scenario. The configuration and implementation of these scenarios within UKESM are described in more detail in Section \u003cspan refid=\"Sec7\" class=\"InternalRef\"\u003e4\u003c/span\u003e (Methods). We simulate the atmospheric evolution of BC aerosol, the resulting changes in global climate, short term radiological fallout, and track the radionuclides that adhere to the black carbon particles (e.g. Cesium-137 (Cs-137) and Strontium-90 (Sr-90)) to map the long-term radiological fallout from global BC surface deposition. Our results provide the first scenario-specific assessment of the combined climate and radiological consequences of a nuclear conflict in Eastern Europe.\u003c/p\u003e"},{"header":"2. Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Ukraine \u0026ndash; Russia Conflict: Year 1 after Detonation\u003c/h2\u003e \u003cp\u003e \u003cstrong\u003eAerosol dispersion and stratospheric heating over the first 20 days after detonation (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, panels a\u0026ndash;f)\u003c/strong\u003e \u003cp\u003eAfter detonation, we explore the spatiotemporal evolution of the aerosol particles and the solar-radiative heating of the lower stratosphere (at 20 km) for the first 20 days (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), which sets the stage for the longer-term climate response. The spatial dispersion of the BC aerosol particles is illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e (panels a\u0026ndash;c), which shows the evolution of total aerosol optical depth (AOD) at 550 nm on days 1, 5, and 20. On day 1 (a), the BC particles remain confined to Eastern Europe. By day 5 (b), they have been lofted further into the stratosphere and been transported eastward by prevailing westerly winds across the Northern Hemisphere (NH). By day 20 (c), the particles have dispersed extensively throughout the NH, spreading towards the pole and equator. Corresponding stratospheric temperature changes at 20 km altitude are shown in panels d\u0026ndash;f for days 10, 15 and 20. A modest hemispheric-mean stratospheric warming of ~\u0026thinsp;2\u0026deg;C in the Northern Hemisphere (NH) and \u0026lt;\u0026thinsp;1\u0026deg;C in the Southern Hemisphere (SH) is evident by day 10 (d). By day 15 (e) the NH mean stratospheric temperatures have increased by ~\u0026thinsp;5\u0026deg;C (SH\u0026thinsp;~\u0026thinsp;1.8\u0026deg;C), and by day 20 (f) it exceeds\u0026thinsp;~\u0026thinsp;8\u0026deg;C (SH\u0026thinsp;~\u0026thinsp;1.6\u0026deg;C), reflecting both the dispersion and solar-radiative heating of the BC particles. These patterns illustrate how even a moderate (5 Tg) BC atmospheric perturbation from a \u0026ldquo;limited\u0026rdquo; nuclear conflict can rapidly disperse BC aerosols, globally blocking out sunlight and driving stratospheric heating.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003ea-c\u003c/b\u003e, Total aerosol optical depth anomaly at 550 nm on days 1, 5 and 20 after detonation, illustrating aerosol spatial dispersion in the days after detonation.\u003c/p\u003e \u003cp\u003e \u003cb\u003ed-f\u003c/b\u003e, Stratospheric temperature anomalies at 20 km on days 10, 15 and 20, illustrating a delayed but accelerating atmospheric thermal response. Hemisphere-mean anomalies are annotated beneath each temperature panel. Stippling in panels d-f marks grid points where the anomaly is not statistically significant (two-tailed Student\u0026rsquo;s t-test, p\u0026thinsp;\u0026ge;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eAtmospheric Black carbon concentration and Temperature (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, panels a-d)\u003c/strong\u003e \u003cp\u003eBuilding on the hemispheric dispersion and solar-radiative heating shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, we examine the vertical distribution of BC mass concentration and temperature changes at the start (Month 1) and end (Month 12) of the first year (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e (panels a-b) shows the zonal-mean latitude\u0026ndash;altitude cross-sections of BC mass concentration (ensemble mean) in first and last month of the year. In the first month (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea), the mean BC concentration maxima occurs at ~\u0026thinsp;15km with concentrations\u0026thinsp;\u0026gt;\u0026thinsp;0.1 \u0026micro;g m⁻\u0026sup3; in the NH. By contrast, by end of the year (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb, month 12) elevated BC concentrations are observed throughout the stratospheric column across both hemispheres, illustrating the interhemispheric transport of BC. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e (panels c-d) shows the corresponding zonal mean temperature anomalies (ensemble mean). In the first month (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec), peak zonal mean warming of ~\u0026thinsp;15\u0026deg;C occurs near 20 km altitude. By year end (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed), the stratospheric temperature increase becomes more vertically extensive throughout the atmospheric column, with zonal mean temperature anomalies as high as ~\u0026thinsp;40\u0026deg;C. The evolution of the vertical and spatial dispersion of BC, and the associated thermal response highlights the critical role of aerosol-chemistry-dynamics feedbacks in modulating both the timing and magnitude of the Earth's climate response.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003ea\u0026ndash;b\u003c/b\u003e, Black carbon mass concentration (\u0026micro;g m⁻\u0026sup3;) in Month 1 (a) and Month 12 (b).\u003c/p\u003e \u003cp\u003e \u003cb\u003ec\u0026ndash;d\u003c/b\u003e, Corresponding zonal-mean temperature anomalies (\u0026deg;C) in Month 1 (c) and Month 12 (d).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003ea\u0026ndash;b\u003c/b\u003e, \u003cb\u003eSurface temperature anomalies\u003c/b\u003e: (a) Monthly mean Temperature anomalies (shading represents the ensemble variability) for the Northern Hemisphere (blue), Southern Hemisphere (red), Russia (green) and USA (purple) (b) Annual-mean temperature anomaly.\u003c/p\u003e \u003cp\u003e \u003cb\u003ec\u0026ndash;d\u003c/b\u003e, \u003cb\u003eSurface solar radiation anomaly\u003c/b\u003e: (c) Monthly mean surface solar radiation anomalies (d) Annual-mean surface solar flux anomaly.\u003c/p\u003e \u003cp\u003e \u003cb\u003ee\u0026ndash;f\u003c/b\u003e, \u003cb\u003ePrecipitation anomaly\u003c/b\u003e: (e) Monthly rainfall anomalies (f) Annual Mean Precipitation Percentage Change.\u003c/p\u003e \u003cp\u003e \u003cb\u003eg\u0026ndash;h\u003c/b\u003e, \u003cb\u003eStratospheric wind anomalies\u003c/b\u003e: (g) Time series of maximum zonal (blue), meridional (orange) and vertical (green) wind anomalies at 40 km. (h) Annual-mean spatial map of wind‐speed anomalies (shading) showing strengthened subtropical jets and altered polar circulations.\u003c/p\u003e \u003cp\u003eStippling indicates grid points where the anomaly is not statistically significant (two-tailed Student\u0026rsquo;s t-test, p\u0026thinsp;\u0026ge;\u0026thinsp;0.05). Together, these panels demonstrate how the solar-radiative properties of BC drive substantial changes to climate variables in the 1st year after nuclear detonation.\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e illustrates both the seasonal cycle and annual-mean climate responses in year 1 post-detonation: panels a\u0026ndash;b show surface temperature anomalies, c\u0026ndash;d the change in downward solar radiation, e\u0026ndash;f precipitation anomalies, and d\u0026ndash;h stratospheric wind perturbations. We also highlight climate anomalies across the land regions of Russia and the USA.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eSurface Temperature Cooling (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea\u0026ndash;b)\u003c/strong\u003e \u003cp\u003eThe seasonal cycle (a) shows that surface temperature anomalies in the NH develop rapidly within the first few months after detonation, reaching\u0026thinsp;\u0026asymp;\u0026thinsp;\u0026minus;\u0026thinsp;1.5\u0026deg;C by the end of the first year. By contrast, the SH shows negligible temperature anomalies year-round, owing to the thermal buffering influence of the Southern Ocean. The annual-mean temperature response (b) confirms a hemispheric-average cooling of \u0026asymp;\u0026thinsp;\u0026minus;\u0026thinsp;1\u0026deg;C in the NH compared to a slight warming of +\u0026thinsp;0.01\u0026deg;C in the SH. Strong regional cooling (\u0026thinsp;\u0026gt;\u0026thinsp;\u0026minus;\u0026thinsp;4\u0026deg;C) occurs over mid and high-latitude continental regions. Russia experiences the strongest anomaly (\u0026asymp; \u0026minus;\u0026thinsp;5\u0026deg;C by end of year), owed to its high-latitude location, minimal buffering from the ocean, and the low heat capacity of its continental land surface. The United States also experiences substantial cooling (\u0026thinsp;\u0026asymp;\u0026thinsp;\u0026minus;\u0026thinsp;3\u0026deg;C in spring), with ensemble members showing year-end anomalies as extreme as \u0026asymp;\u0026thinsp;\u0026minus;\u0026thinsp;10\u0026deg;C.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eSolar Dimming (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec\u0026ndash;d)\u003c/strong\u003e \u003cp\u003eAs the black carbon disperses across the atmosphere globally, it induces a negative anomaly in the incoming surface solar radiation. In the NH, the downward solar radiation anomaly is \u0026asymp;\u0026thinsp;\u0026minus;\u0026thinsp;20 W m⁻\u0026sup2; by April (c). As the BC spreads into the SH stratosphere, the solar flux anomaly is \u0026asymp;\u0026thinsp;\u0026minus;\u0026thinsp;15 W m⁻\u0026sup2; by end of year (SH summer). Mid-latitude continental zones in North America and Russia show anomalies between \u0026minus;\u0026thinsp;10 to \u0026minus;\u0026thinsp;50 W m⁻\u0026sup2; throughout the year, underscoring the vulnerability of key agricultural regions. This is reflected in annual-mean reductions in net primary productivity (NPP) of up to 0.2 kgC m⁻\u0026sup2; across large parts of the NH, particularly over regions of North America and Asia (Supplementary Section 2, Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). The annual-mean downward solar radiation anomalies (d) are substantial, \u0026asymp; \u0026minus;13.4 W m⁻\u0026sup2; in the NH and \u0026asymp;\u0026thinsp;\u0026minus;\u0026thinsp;6.3 W m⁻\u0026sup2; in the SH. The spatial pattern of solar flux anomaly closely follows the changing stratospheric BC mass concentration through the year (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), with the largest springtime reductions occurring over the United States, Russia, and much of Eurasia, regions responsible for a significant share of global crop production.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003ePrecipitation Disruption (\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ee-f, \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea-b\u003cb\u003e)\u003c/b\u003e: Significant shifts in global precipitation are observed in year 1 as a direct response to the strong NH surface cooling and associated changes in large-scale circulation. Annual-mean precipitation decreases by 20\u0026ndash;40% across much of the NH mid-latitudes, with locally larger decreases (up to 80%) over densely populated and agricultural regions of Asia and West Africa (f), alongside land regions of the United States and Russia experiencing precipitation decreases of up to 20 mm month⁻\u0026sup1; in year 1 (e). These patterns are also consistent with the seasonal cycle shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea, where India and Niger experience pronounced monsoon season decreases of \u003cb\u003e~\u003c/b\u003e\u0026thinsp;40\u0026ndash;100 mm month⁻\u0026sup1; in July\u0026ndash;August. The spatial pattern of drying corresponds closely to changes in the meridional overturning circulation and vertical winds. Meridional Stream-function anomalies and vertical winds over longitudinal sectors (64\u0026deg;E \u0026ndash; 91\u0026deg;E and 16\u0026deg;W \u0026ndash; 13\u0026deg;E respectively) (Supplementary Section 2, Figure S2-S3), indicate a supressed assent over India and West Africa during the NH summer (JJA) resulting in dryer conditions relative to the control simulation. In contrast, the SH mid-latitudes experience substantial precipitation increases, especially over Southern Africa and Australia, where annual precipitation rises by up to 100%. The seasonal cycle shows that both Australia and Namibia exhibit consistent precipitation increases from February-April, ~\u0026thinsp;20\u0026ndash;60 mm month⁻\u0026sup1; more than the control simulation (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb). Stream-function and vertical wind anomalies over longitudinal sectors (9\u0026deg;E \u0026ndash; 40\u0026deg;E and 112\u0026deg;E \u0026ndash; 154\u0026deg;E) (Supplementary Section 2, Figure S4-S5) confirm the presence of a strengthened anomalous counterclockwise cell and increased vertical winds which indicates enhanced low-level ascent, which explains the increases in precipitation. These hemispheric contrasts are also influenced by the southward displacement of the Intertropical Convergence Zone (ITCZ) by approximately 2\u0026ndash;6\u0026deg; between March and June caused by the asymmetric NH cooling. The weakened, shifted ITCZ produces lower equatorial precipitation by ~\u0026thinsp;0.5-1.0 mm day⁻\u0026sup1; in year 1 (Supplementary Section 2, Figure S6). Collectively, the strongly altered overturning circulation and displaced Intertropical tropical convergence zones explain the hemispheric dipole: widespread dryer conditions across the NH and enhanced rainfall over the SH subtropical regions.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eStratospheric Jet Strengthening (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eg\u0026ndash;h, \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea-c)\u003c/strong\u003e \u003cp\u003eThe stratospheric wind dynamics driven by atmospheric temperature changes are prominently illustrated through wind anomalies at ~\u0026thinsp;40 km altitude (panel g-h), with the column vertical profile of the zonal, meridional and vertical winds shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea-c. The time series (g) highlights sustained zonal jet anomalies with velocities ranging between 50\u0026ndash;200 m s⁻\u0026sup1;, meridional wind anomalies between 20\u0026ndash;70 m s⁻\u0026sup1;, along with smaller but significant vertical wind anomalies between 0.02\u0026ndash;0.1 m s⁻\u0026sup1;, indicative of pronounced changes in stratospheric vertical transport and mixing processes, peaking notably in the spring and summer months. The annual-mean wind anomalies at 40 km (h), shows strengthening of the subtropical and polar jets in both hemispheres, alongside perturbations to the vertical winds at high latitudes. In comparison, previous studies\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e modelling a 5 Tg BC India\u0026ndash;Pakistan conflict reported lower maximum stratospheric zonal wind anomalies of ~\u0026thinsp;40 m s⁻\u0026sup1; during the NH-winter, whereas our modelled scenario shows peak zonal wind anomaly between 100\u0026ndash;200 m s⁻\u0026sup1; during the same time period, reflecting differences in injection latitude, soot heating distribution, and structural inter-model differences.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e(a)\u003c/b\u003e Zonal-wind anomaly, Δu (m s⁻\u0026sup1;). \u003cb\u003e(b)\u003c/b\u003e Meridional‐wind anomaly, Δv (m s⁻\u0026sup1;). \u003cb\u003e(c)\u003c/b\u003e Vertical‐wind anomaly, Δw (cm s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e),\u003c/p\u003e \u003cp\u003e \u003cb\u003eImpact of Conflict Scenario on Global Climate (\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e: To evaluate how the geographic origin of the BC alters the subsequent Earth system response, we compare two war scenarios, each with 5 Tg BC released into stratosphere: one originating from the Ukraine\u0026ndash;Russia border region (\u0026ldquo;UKRRUS\u0026rdquo;) and the other from the widely studied India\u0026ndash;Pakistan regional conflict scenario (\u0026ldquo;INDPAK\u0026rdquo;)\u003csup\u003e6,7,9,13,14\u003c/sup\u003e. Previous modelling studies of the 5 Tg INDPAK scenario consistently show declines in surface temperature and global mean precipitation\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. While there are notable differences in model setups/configurations in past modelling studies \u0026ndash; which includes date of detonation, horizontal and vertical resolution, and aerosol microphysics; our INDPAK simulations produce quantitatively similar results. Reported global mean surface cooling ranges from 0.5 to 2\u0026deg;C\u003csup\u003e6,7,9,17\u003c/sup\u003e, with reductions in global mean precipitation during the first year of 0.2 to 0.5 mm day⁻\u0026sup1;. Figure\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e (panel a) shows the zonal mean AOD anomaly for days 8 and 20 for both scenarios. The UKRRUS aerosol dispersion (blue/green) remains more confined to mid and high latitudes, whereas in the INDPAK scenario (red/orange) there is more aerosol dispersion into the SH and less so towards the NH high latitudes. Panel (b) illustrates the corresponding annual-mean AOD anomaly, highlighting stronger aerosol loading across Northern Eurasia and the Arctic in the UKRRUS case relative to INDPAK. This spatial pattern reflects the more persistent poleward transport of soot in the higher-latitude UKRRUS injection compared to the tropical-latitude INDPAK source. Consistent with these spatial contrasts in aerosol loading, Figure S7 (supplementary section 2) shows that both scenarios produce a comparable global-mean cooling of approximately 0.5\u0026deg;C, but the UKRRUS case has an earlier peak NH cooling (end of year 1) compared with the INDPAK scenario (end of year 2). These differences in aerosol dispersion translate into distinct spatial patterns of climate disruption (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, panels c\u0026ndash;e). Consequently, surface temperatures are lower at northern latitudes for UKRRUS (up to \u0026minus;\u0026thinsp;2\u0026deg;C) than for the INDPAK scenario, but somewhat warmer at lower latitudes (\u0026thinsp;\u0026asymp;\u0026thinsp;+\u0026thinsp;1\u0026deg;C over parts of South Asia) (panel c). These responses follow the spatial distribution of the change in the surface solar fluxes (panel d). Solar dimming is more pronounced in mid-latitude continental regions for UKRRUS (\u0026ndash;0.7 W m⁻\u0026sup2; hemispheric mean) but yields a net positive anomaly in the SH (+\u0026thinsp;2.2 W m⁻\u0026sup2;) because the INDPAK BC plume disperses more across the tropics and into the SH. Relative to INDPAK, the UKRRUS scenario drives a hemispheric asymmetry in the precipitation response (panel e), characterized by widespread suppression in the NH (up to 20 mm month\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and localized enhancement over Southeast Asia (up to 50 mm month\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e). These anomalies are primarily driven by a southward displacement of the ITCZ, which shifts up to 4\u0026deg; further south by month 6 in the UKRRUS scenario compared to INDPAK (Supplementary Section 2, Figure S6). Consistent with this shift, analysis of the meridional stream function and vertical winds confirm strengthened vertical ascent over Southeast Asia driving enhanced rainfall during the NH summer (Supplementary Section 2, Figure S8).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003e(a)\u003c/b\u003e Zonal-mean aerosol optical depth (AOD) anomalies at days 8 (solid) and 20 (dashed) for the Ukraine\u0026ndash;Russia (blue/green) and India\u0026ndash;Pakistan (red/orange) scenarios.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003e(b)\u003c/b\u003e Annual-mean AOD anomaly at 550 nm (UKRRUS \u0026ndash; INDPAK),\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003e(c)\u003c/b\u003e Annual-mean surface temperature difference (UKRRUS \u0026ndash; INDPAK),\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003e(d)\u003c/b\u003e Annual-mean change in downward solar radiation (UKRRUS \u0026ndash; INDPAK).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003e(e)\u003c/b\u003e Annual-mean change in precipitation (UKRRUS - INDPAK)\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eStippling in panels b-d marks grid points where the anomaly is \u003cem\u003enot\u003c/em\u003e statistically significant (two-tailed Student\u0026rsquo;s t-test, p\u0026thinsp;\u0026ge;\u0026thinsp;0.05).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Ukraine-Russia Conflict: Multi-Year Climate Response\u003c/h2\u003e \u003cp\u003eTo evaluate the long-term climate impacts of the nuclear conflict, Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e illustrates the temporal evolution of key surface climate variables over the subsequent 10-year period. In each panel, solid lines denote the ensemble-mean anomalies, while the shaded envelopes indicate the ensemble spread for the Northern Hemisphere (blue), Southern Hemisphere (red), Russia (green) and USA (purple).\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eSurface Temperature\u003c/strong\u003e \u003cp\u003eLand regions of Russia experience the largest negative temperatures anomalies (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ea), as low as ~ \u0026minus;\u0026thinsp;6\u0026deg;C (ensemble member minimum). The NH mean surface temperature also falls sharply (approximately \u0026minus;\u0026thinsp;1\u0026deg;C), whereas the SH temperature response is negligible owing to the buffering effect of the Southern Ocean. Between years 2 and 4, surface temperatures gradually recover as atmospheric black carbon (BC) concentrations decrease, and by year 6, anomalies approach baseline conditions. The temperature response over the US is similar to Russia with the ensemble minimum as low as ~ -4\u0026deg;C.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003ea\u003c/b\u003e, \u003cb\u003eMonthly surface air temperature anomalies (\u0026deg;C)\u003c/b\u003e,\u003c/p\u003e \u003cp\u003e \u003cb\u003eb\u003c/b\u003e, \u003cb\u003eDownward solar radiation anomalies (W m⁻\u0026sup2;)\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003ec\u003c/b\u003e, \u003cb\u003ePrecipitation change (%)\u003c/b\u003e\u003c/p\u003e \u003cp\u003ePanels a-c illustrate the multi-year climate disruption and recovery which lasts\u0026thinsp;~\u0026thinsp;6 years. The bold line indicates the ensemble mean and shaded bands representing the 6-member ensemble spread, for the Northern Hemisphere (blue), Southern Hemisphere (red), Russia (green), and USA (purple).\u003c/p\u003e \u003cp\u003e \u003cb\u003eDownward Surface Solar Radiation\u003c/b\u003e: Incoming surface solar radiation anomalies (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eb) closely tracks the temperature changes. In the first year, the NH experiences a maximum decrease of approximately \u0026minus;\u0026thinsp;13 W m⁻\u0026sup2;, with the US showing the largest decrease (\u0026asymp; \u0026minus;\u0026thinsp;30 W m⁻\u0026sup2;) and Russia around \u0026minus;\u0026thinsp;20 W m⁻\u0026sup2;. As the aerosol dispersed globally into the SH, the SH anomalies go as low as approximately \u0026minus;\u0026thinsp;10 W m⁻\u0026sup2; between year 1 and 2. From years 1 through 8, solar flux anomalies globally recover and approach baseline conditions.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003ePrecipitation changes\u003c/strong\u003e \u003cp\u003ePrecipitation anomalies (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ec) closely track the temporal evolution of surface temperature and surface solar radiation anomalies. During the first two years, NH mean precipitation declines by roughly 10\u0026ndash;20%, equivalent to about \u0026minus;\u0026thinsp;6 to -10 mm month⁻\u0026sup1;, with particularly strong reductions over Russia (up to -25%, or \u0026asymp; -15 to -20 mm month⁻\u0026sup1;). The USA experiences more modest decreases of ~\u0026thinsp;5\u0026ndash;10% in comparison to Russia, albeit with substantial ensemble spread. These suppressed precipitation rates persist through years 3\u0026ndash;6 before gradually returning toward baseline conditions. Precipitation anomalies in the SH remain minimal, constrained to within \u0026plusmn;\u0026thinsp;5% over the entire simulation period.\u003c/p\u003e \u003c/p\u003e \u003cp\u003eTogether, these multi-year time series demonstrate that a nuclear war in Eastern Europe produces rapid, hemisphere‐wide changes to surface temperature, solar radiation, and precipitation. This is followed by a gradual climate recovery phase, with our model projecting a return to near-baseline conditions within ~\u0026thinsp;6 years.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Fallout Analysis\u003c/h2\u003e \u003cp\u003e \u003cb\u003eNear term fallout \u0026ndash; 48 hours post detonation\u003c/b\u003e \u003c/p\u003e \u003cp\u003eDue to the inherent complexity and sensitivity of fallout dynamics to environmental parameters such as wind speed, precipitation, and conflict locations, we utilize a simplified empirical fallout model developed by Glasstone and Dolan (1977)\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. This approach is derived from historical nuclear weapons test data and has been applied to nuclear war impact modelling studies in the recent past\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e, and enables us to estimate areas exposed to radioactive contamination within the first 48 hours following detonation. The 5Tg BC that is emitted into the upper troposphere-lower stratosphere could result from a combination of both groundbursts and airbursts. Our radiological fallout estimates (methodology documented in the supplementary, section \u003cspan refid=\"Sec6\" class=\"InternalRef\"\u003e3\u003c/span\u003e) are carried out for 100 simultaneous 15-kiloton (kt) surface nuclear detonations scenario, evenly distributed across approximately 613,000 km\u0026sup2; region along the Ukraine\u0026ndash;Russia border (46.4\u0026deg;\u0026ndash;52.3\u0026deg;N, 32.1\u0026deg;\u0026ndash;45.0\u0026deg;E) (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003ea).\u003c/p\u003e \u003cp\u003eThe mean surface winds over the region in the first month is ~\u0026thinsp;5.3 m s\u003csup\u003e-\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e (19 km h\u003csup\u003e-\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e) towards the northeast (~\u0026thinsp;40\u0026deg;). Climatologically, radioactive debris from surface detonations would primarily be expected to disperse towards the northeastern shortly after the explosions. By adapting the Glasstone\u0026ndash;Dolan fallout model to these specific wind conditions, we determine that each 15-kt detonation generates plumes that extend downwind approximately 62.7 km for radiation doses exceeding 1 Sv, 26.1 km for doses exceeding 5 Sv, and approximately 17.9 km for the highest lethal threshold of 10 Sv (Supplementary Section 3, Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e) in 48 hours.\u003c/p\u003e \u003cp\u003eThe fallout plume width ranges from ~\u0026thinsp;0.9 km for \u0026ge;\u0026thinsp;10 Sv to ~\u0026thinsp;3.2 km for \u0026ge;\u0026thinsp;1 Sv. Collectively, the 100 detonations produce a cumulative contaminated area of approximately\u0026thinsp;~\u0026thinsp;20,000 km\u0026sup2; (in 48 hours) at doses exceeding 1 Sv, ~ 3500 km\u0026sup2; above 5 Sv, and ~\u0026thinsp;1,600 km\u0026sup2; above 10 Sv. For perspective, the 48-hour fallout zone which experience doses\u0026thinsp;\u0026ge;\u0026thinsp;5 Sv surpasses the size of the Chernobyl exclusion zone (~\u0026thinsp;2,600 km\u0026sup2;)\u003csup\u003e19\u003c/sup\u003e, although the isotopic composition would differ, with weapon fallout dominated by short-lived fission products (e.g. I-131, Ba-140, Te-132) rather than the longer-lived Cs-137 and Sr-90 typical of Chernobyl\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eConsidering the average population density of the region (~\u0026thinsp;49 persons/km\u0026sup2;, with a total population of ~\u0026thinsp;30.2\u0026nbsp;million), we estimate significant human exposure and health impacts. Approximately a million people would experience radiation doses exceeding 1 Sv, a threshold typically sufficient to induce acute radiation sickness. Within zones receiving\u0026thinsp;\u0026ge;\u0026thinsp;5 Sv, roughly 170,000 people would encounter severe radiation sickness. The most critically impacted zone, receiving\u0026thinsp;\u0026ge;\u0026thinsp;10 Sv, would affect approximately an estimated 80,000 people, facing virtually certain fatal outcomes without advanced medical care. For perspective, the regulatory upper limit for artificial public exposure is only 1 mSv per year\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, highlighting the extreme magnitude of these doses.\u003c/p\u003e \u003cp\u003eBeyond immediate health implications, the long-term consequences would persistently affect the region. Areas receiving\u0026thinsp;\u0026ge;\u0026thinsp;1 Sv would require extended evacuation, prolonged exclusion, or intensive remediation measures. Residual soil contamination, disruption of agriculture, and extensive infrastructure damage would contribute to prolonged socioeconomic instability. This analysis underscores that even a limited, regional nuclear conflict involving relatively low-yield weapons can produce extensive, long-lasting humanitarian and environm.ental devastation\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003cb\u003eLong term fallout from global BC transport and deposition\u003c/b\u003e \u003c/p\u003e \u003cp\u003eNuclear detonation results in the release of several radionuclides which can adhere to BC particles. Radionuclide adherence to aerosol particles has been well documented - for example, in observations following the Fukushima nuclear accident\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. The self-lofting of BC into the stratosphere combined with nuclear war-induced precipitation reductions delays wet removal of BC aerosol, prolonging its residence time. These BC-driven atmospheric changes allow radioactive debris to spread broadly before deposition. The atmospheric circulation and gradual surface deposition of BC facilitates widespread global dispersal of these radionuclides. Long-lived radionuclides such as Cesium-137 (Cs-137; T₁/₂ \u0026asymp; 30.2\u0026nbsp;year) and Strontium-90 (Sr-90; T₁/₂ \u0026asymp; 28.8\u0026nbsp;year) are routinely monitored in long-term fallout assessments owing to their persistent environmental residence, propensity for biological uptake, and well-documented health impacts over decadal timescales\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Assuming the weapons used are Uranium-235 (U-235) fission bombs, we estimate the yields of Cs-137 and Sr-90 and their adherence to black carbon (BC), with assumptions and parameters detailed in Supplementary Section 4 and Table S2. We recognise that the extent to which radionuclides from surface detonations reach the stratosphere depends on their proximity to large fires and associated convective plumes; therefore, these estimates are an idealised upper-bound case for the distribution of radionuclides with soot.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003ea\u003c/b\u003e, Location of the target region at the Ukraine-Russia border where 100 nuclear detonations (each 15 kt yield) are uniformly distributed.\u003c/p\u003e \u003cp\u003e \u003cb\u003eb\u003c/b\u003e, Temporal evolution of cumulative global and hemispheric BC deposition (in Tg) over a 10-year period, highlighting the e-folding timescale (~\u0026thinsp;3.5 years) for global BC removal. Shaded areas represent ensemble spread.\u003c/p\u003e \u003cp\u003e \u003cb\u003ec\u003c/b\u003e, 10-year cumulative effective dose (mSv) from Cesium-137(Cs-137) and Strontium-90 (Sr-90) deposition.\u003c/p\u003e \u003cp\u003e \u003cb\u003ed\u003c/b\u003e, Top 10 countries by mean cumulative effective dose (mSv)\u003c/p\u003e \u003cp\u003e \u003cb\u003ee\u003c/b\u003e, Top 10 countries by Collective radiation dose (person\u0026ndash;Sv)\u003c/p\u003e \u003cp\u003eA decade after detonation, deposition patterns exhibit a hemispheric asymmetry: fallout is initially confined largely to the NH, followed by substantial cross-equatorial transport into the SH, and ultimately dispersing radioactive contamination across the globe (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eb-e). Figure\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eb shows that approximately two-thirds of the injected BC is deposited from the atmosphere in the first 4 years, corresponding to an atmospheric e-folding time of ~\u0026thinsp;3.5 years (red dashed line). By year 10 nearly all the 5 Tg of BC has deposited globally. The surface deposition is initially concentrated in the NH, which receives most of the fallout in the first 1\u0026ndash;2 years, but gradual cross-equatorial transport results in ~\u0026thinsp;40% of the BC being deposited in the SH by year 10.\u003c/p\u003e \u003cp\u003eMaps of long-lived radionuclide fallout (Supplementary Section 2, Figure S9 a-b) for Cs-137 and Sr-90 shows a widespread global deposition (methodology and assumptions are documented in supplementary section 4), with the highest surface radiation levels up to ~\u0026thinsp;10 Bq m⁻\u0026sup2; in the NH by year 10. Both Cs-137 and Sr-90 shows a very similar spatial pattern (as both isotopes are transported with the same BC aerosol particles). In contrast, large parts of the SH areas receive negligible fallout (\u0026lt;\u0026thinsp;0.1 Bq m⁻\u0026sup2;), but some areas close of 45S receive\u0026thinsp;\u0026gt;\u0026thinsp;0.4 Bq m⁻\u0026sup2;. These results indicate that the NH mid-latitudes including parts of Central Asia, Europe and the Middle East accumulate the bulk of the global radioactive fallout.\u003c/p\u003e \u003cp\u003eDespite the broad geographic extent of radioactive contamination, the cumulative dose map (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003ec) shows that resulting radiation exposures remain very low. The 50-year cumulative effective dose from Cs137\u0026thinsp;+\u0026thinsp;Sr90 deposition is at most\u0026thinsp;~\u0026thinsp;0.9 mSv in the most affected regions (e.g. parts of the Central Asia). Most of the NH land area receives\u0026thinsp;~\u0026thinsp;0.1\u0026ndash;0.3 mSv, and virtually all populated areas in the SH stay below 0.07 mSv. Such doses are far below the natural background (~\u0026thinsp;2.4 mSv yr⁻\u0026sup1;) and by themselves would pose little direct health risk\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. However, Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003ed indicates discernible differences in the radiation dose at the country level. The highest national mean 50-year cumulative doses (\u0026asymp;\u0026thinsp;0.25\u0026ndash;0.48 mSv per person) occur in smaller countries situated under the primary BC deposition areas: for example, Tajikistan (0.48 mSv) and Bhutan (0.38 mSv) top the list, followed countries in Europe and Central Asia. Larger countries such as Russia have much higher localized deposition near the detonation zone, but their country average dose is diluted by vast areas with minimal fallout.\u003c/p\u003e \u003cp\u003eCollective radiation dose metrics\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003ee) underscore how population size modulates impact. China and India\u0026rsquo;s large population, combined with its subtropical latitude, leads to a high collective radiation dose (China\u0026thinsp;~\u0026thinsp;400000 person\u0026ndash;Sv and India\u0026thinsp;~\u0026thinsp;200000 person-Sv), followed by countries in Central Asia, Africa and Europe. Figures\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eb\u0026ndash;e demonstrate that BC-driven atmospheric transport can distribute radioactive fallout across hemispheres, leading to low-level contamination and associated risks far from the conflict region.\u003c/p\u003e \u003cp\u003eFor perspective, the hypothetical doses estimated here are several orders of magnitude smaller than those produced by atmospheric nuclear weapons testing prior to the 1963 Partial Test Ban Treaty. By that time, approximately 189 Mt of fission yield had been released into the atmosphere, roughly ten times the total fission yield assumed in our scenario, resulting in global mean annual effective doses peaking near 0.1\u0026ndash;0.15 mSv in just one year (1963)\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. In contrast, our modelled Cs-137\u0026thinsp;+\u0026thinsp;Sr-90 fallout yields peak regional cumulative doses of ~\u0026thinsp;0.8 mSv over a period of 50 years, underscoring how much smaller the long-term radiological burden would be under our simulated scenario.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Discussion and Conclusions","content":"\u003cp\u003eOur simulations demonstrate that a limited regional nuclear conflict in Eastern Europe, involving a combination of ground and surface bursts that releases 5\u0026nbsp;million-tons of black carbon into the stratosphere, triggers globally disruptive climate anomalies and radioactive fallout. The Northern Hemisphere surface temperature cools by ~\u0026thinsp;1\u0026deg;C in the first year, with land regions of US and Russia experiencing temperature anomalies of up to -4\u0026deg;C and \u0026minus;\u0026thinsp;5\u0026deg;C, peak downward solar-flux reductions are approximately 40 W m⁻\u0026sup2;, and precipitation reductions of 20\u0026ndash;40% across key mid-latitude agricultural zones. Although the Southern-Ocean heat capacity buffers the Southern hemisphere surface temperature response, the perturbed meridional temperature gradients displace and weaken the Intertropical Convergence Zone. The global climate system recovers gradually: two-thirds of the atmospheric BC is deposited onto the Earth\u0026rsquo;s surface after ~\u0026thinsp;4 years, and near-surface climate metrics return to baseline around year 6.\u003c/p\u003e \u003cp\u003ePrevious modelling studies of the India-Pakistan war scenario (5 Tg BC) consistently shows declines in surface temperature and global mean precipitation\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. While there are notable differences in model setup/configurations - including horizontal and vertical resolution and aerosol microphysics, our India-Pakistan simulations produce quantitatively similar results. Reported global mean surface cooling ranges from 0.5 to 2\u0026deg;C\u003csup\u003e6,7,9\u003c/sup\u003e, with reductions in global mean precipitation during the first year of 0.2 to 0.5 mm day⁻\u0026sup1;. Comparing the India\u0026ndash;Pakistan war scenario with the Ukraine\u0026ndash;Russia conflict is critical for assessing the impact of the geographic/latitudinal origin of nuclear conflict-driven BC emissions. Relative to an India\u0026ndash;Pakistan scenario, the Ukraine\u0026ndash;Russia scenario climate response remains more confined to northern mid and high latitudes, intensifying cooling and solar dimming over Eurasia and North America. Conversely, the India\u0026ndash;Pakistan scenario spreads BC more efficiently across the tropics, altering more the Southern-Hemisphere radiative budgets.. BC source-region sensitivities underscore the need for scenario-specific assessments in nuclear war research.\u003c/p\u003e \u003cp\u003eRadiological consequences, though modest compared to the climatic disruptions have been quantified. Long-lived radionuclides (Cs-137, Sr-90) adhere to BC and are transported and deposited globally with 40% deposited in the SH. The 50-year cumulative effective doses peak at ~\u0026thinsp;0.9 mSv, well below natural background levels (~\u0026thinsp;2.4 mSv yr⁻\u0026sup1;). The collective radiation dose is the highest in countries like China, India, and other parts of central Asia, Europe and North America. Thus, even countries distant from the war zone incur quantifiable health burdens via atmospheric transport and radionuclide surface deposition.\u003c/p\u003e \u003cp\u003eOur results quantify both the climatic and radiological consequences of a nuclear conflict in Eastern Europe, allowing us to better visualise its detrimental impacts across the world. Although the specific scenario analysed in this study focuses on the Ukraine\u0026ndash;Russia border, similar quantities of smoke could be injected into the mid-latitude lower stratosphere from other regional conflicts or urban-industrial targets (e.g., in North Korea or other parts of Europe), producing a broadly comparable climate response. This highlights the general applicability of our findings to any mid-latitude nuclear war of comparable scale. These findings highlight the far-reaching consequences of nuclear war and reinforces the objectives of the Treaty on the Non-Proliferation of Nuclear Weapons (NPT): preventing the spread of nuclear weapons and related technology, promoting cooperation in the peaceful use of nuclear energy, and advancing the goal of nuclear disarmament.\u003c/p\u003e"},{"header":"4. Methods","content":"\u003cp\u003eIn this study, we used version 1.1 of the UK Earth System Model (UKESM1.1)\u003csup\u003e28\u0026ndash;30\u003c/sup\u003e, which supports multiple configurations \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. Our simulations utilize the N96L85 setup, characterized by a horizontal grid resolution of 1.875\u0026deg; longitude by 1.25\u0026deg; latitude, equating to approximately 135 km. The model has 85 vertical levels with 50 levels between 0 and 18 km and 35 levels between 18 and 85 km. The atmospheric composition is modelled through the UK Chemistry and Aerosol (UKCA) \u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e component of UKESM, which incorporates gas-phase and aerosol chemistry. Emissions from anthropogenic sources, biomass burning, biogenic activity, and dimethyl sulfide (DMS) are prescribed using datasets from Hoesly et al. (2018), van Marle et al. (2017), Sindelarova et al. (2014), and Spiro et al. (1992) \u003csup\u003e\u003cspan additionalcitationids=\"CR35 CR36\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. The aerosol scheme within UKCA is referred to as the Global Model of Aerosol Processes, GLOMAP\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e,\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. It uses a two-moment pseudo-modal approach and simulates multicomponent global aerosol, which includes sulphate, black carbon, organic matter and sea spray. Dust is simulated separately using a different parametrisation\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. GLOMAP includes key aerosol processes such as nucleation, condensation, coagulation, wet and dry deposition, and aerosol-cloud interactions. The aerosol particle size distribution is characterized using five log-normal modes, 4 soluble (nucleation soluble, Aitken soluble, accumulation soluble, coarse soluble) and 1 insoluble mode (Aitken insoluble). UKCA is fully integrated with UKESM\u0026rsquo;s dynamical core, enabling the transport of tracers via advection, convection, and mixing within the boundary layer.\u003c/p\u003e \u003cp\u003eTo simulate a \u0026ldquo;limited\u0026rdquo; nuclear war scenario over Eastern Europe (32.1\u0026deg; E\u0026ndash;45\u0026deg; E, 46.4\u0026ndash;52.3\u0026deg; N; \u0026asymp; 6 \u0026times; 10⁵ km\u0026sup2;), we emit 5 Tg of black carbon (BC) aerosol with a mean particle diameter of 150 nm and standard deviation of 1.59, distributed evenly across between 300\u0026ndash;150 hPa (\u003cb\u003e~\u003c/b\u003e\u0026thinsp;9 km \u0026minus;\u0026thinsp;13 km altitude), with coagulation turned off in the stratosphere. The emitted BC particles are assumed to be spherical and are placed in the accumulation soluble mode of the UKCA\u0026ndash;GLOMAP aerosol scheme. Each mode represents an internally mixed population whose optical properties are calculated using Mie theory within the RADAER radiation scheme. The complex refractive index for BC used in UKESM\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e is 1.85\u0026thinsp;\u0026minus;\u0026thinsp;0.71i at a wavelength of 550 nm, and soluble coatings are represented dynamically through condensation and coagulation with other aerosol species. These assumptions are consistent with the default UKESM1.1 configuration and have been used in previous UKESM aerosol\u0026ndash;radiation studies\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. The model does not explicitly simulate the fire plume because of its coarse resolution, and we assume 5Tg BC is emitted directly into the upper troposphere-lower stratosphere after detonation. The 5Tg of BC emission assumption used in past regional nuclear war studies simulating India-Pakistan are derived from fuel load estimates as detailed in Toon et al., 2007\u003csup\u003e13\u003c/sup\u003e. We acknowledge that some studies\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e have also simulated the co-emission of organic carbon with black carbon following detonation. These emissions depend on factors such as the fuel source, detonation location, and burning efficiency, and can influence the atmospheric lifetime of black carbon\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. This aspect is not examined in our study.\u003c/p\u003e \u003cp\u003eIn our study for short term fallout estimates, we assume the 100 detonation locations are uniformly distributed across the region as highlighted in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003ea. The BC is also emitted uniformly for a week at the start of year 2015, from Jan 1st to Jan 7th. The other emission files follow a Shared Socioeconomic Pathway (SSP) SSP126 scenario, and we use the model start files referenced in Mulcahy et al., 2023\u003csup\u003e30\u003c/sup\u003e to setup 6 different ensemble members. In this study we run 6 ensemble members (for 20 years) for two scenarios with the same start date and setup, one over the Ukraine-Russia border and the other over the entire land region of India-Pakistan. The methodology/assumptions for estimating the radionuclide adherence and global fallout are documented in Supplementary section 4.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis work was carried out under the SHIVER (StratospHeric aerosol Impacts under Various nuclEaR conflict scenarios) project funded by the Future Of Life Institute (WT998567).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAR contributed to the climate modelling using UKESM, scientific analysis of the data and drafting of the manuscript. NM contributed scientific insight in reducing model instabilities. AJ provided scientific insight and finetuning the draft of the paper. JH helped guide and conceptualise the study, provided scientific insight and secured the grant that funded this work.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data that supports the findings can be viewed from [10.5281/zenodo.17632006](https:/doi.org/10.5281/zenodo.17632006) and [10.5281/zenodo.17779131](https:/doi.org/10.5281/zenodo.17779131) . These doi\u0026rsquo;s have restricted access right now and will be made available upon request and made public before publication.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCrutzen, P. J. \u0026amp; Birks, J. W. The Atmosphere After a Nuclear War: Twilight at Noon. \u003cem\u003eAmbio\u003c/em\u003e 11, 125\u0026ndash;152 (2016).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTurco, R. P., Toon, O. B., Ackerman, T. P., Pollack, J. B. \u0026amp; Sagan, C. 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Modeling the atmospheric life cycle and radiative impact of mineral dust in the Hadley Centre climate model. \u003cem\u003eJournal of Geophysical Research: Atmospheres\u003c/em\u003e 106, 18155\u0026ndash;18166 (2001).\u003c/span\u003e\u003c/li\u003e\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-clean-air","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [npj Clean Air](https://www.nature.com/npjcleanair/)","snPcode":"44407","submissionUrl":"https://submission.springernature.com/new-submission/44407/3","title":"npj Clean Air","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-8344698/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8344698/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eGeopolitical tensions in Eastern Europe underscores the urgency of addressing the climatic and radiological consequences of a regional nuclear conflict. Using an Earth System Model, we simulate a conflict at the Ukraine-Russia border that releases five million-tons of black carbon (BC) into the stratosphere. The extended stratospheric lifetime of BC induces hemispheric climate disruption: the Northern Hemisphere cools by ~\u0026thinsp;1\u0026deg;C in year-1, with anomalies of \u0026minus;\u0026thinsp;5\u0026deg;C in Russia and \u0026minus;\u0026thinsp;4\u0026deg;C in the United States; surface solar radiation declines by ~\u0026thinsp;30 W m⁻\u0026sup2; over the US; and precipitation decreases by ~\u0026thinsp;40% across mid-latitude croplands. Stratospheric warming alters subtropical and polar jets, displacing the Intertropical Convergence Zone\u0026thinsp;~\u0026thinsp;2\u0026ndash;6\u0026deg; southward, delaying climate recovery by ~\u0026thinsp;6 years. Long-lived radionuclides transported with BC disperse globally, with ~\u0026thinsp;40% depositing in the Southern Hemisphere. These findings underscore the importance of nuclear-risk reduction and provide a robust benchmark for food-security and humanitarian-impact assessments.\u003c/p\u003e","manuscriptTitle":"Nuclear Conflict in Eastern Europe: Climate Disruption \u0026amp; Radiological Fallout","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-26 03:55:16","doi":"10.21203/rs.3.rs-8344698/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-08T11:10:34+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-07T04:06:20+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-05T22:45:54+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-04T13:55:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"120450549958681613251954415891357624906","date":"2025-12-28T02:04:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"13535645600024835620932288945705909301","date":"2025-12-27T13:06:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"128920430146200862060749106996981765126","date":"2025-12-27T12:03:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"313589018558823741592244736878922132534","date":"2025-12-24T01:41:34+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-24T01:29:40+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-18T04:52:51+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-18T03:53:53+00:00","index":"","fulltext":""},{"type":"submitted","content":"npj Clean Air","date":"2025-12-12T10:07:54+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"npj-clean-air","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [npj Clean Air](https://www.nature.com/npjcleanair/)","snPcode":"44407","submissionUrl":"https://submission.springernature.com/new-submission/44407/3","title":"npj Clean Air","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"08261c95-4506-40fe-a1cd-5fd035f9702d","owner":[],"postedDate":"December 26th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":60148991,"name":"Earth and environmental sciences/Climate sciences"},{"id":60148992,"name":"Earth and environmental sciences/Environmental sciences"}],"tags":[],"updatedAt":"2026-03-12T07:10:45+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-26 03:55:16","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8344698","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8344698","identity":"rs-8344698","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}