Fig. 1: Evolution of aerosol optical depth and stratospheric temperature anomalies (ensemble mean) following 5\u2009Tg BC aerosol release into the stratosphere (9\u201313\u2009km) from 100\u2009\u00d7\u200915\u2009kt detonations at the Ukraine-Russia border (32.1\u00b0 E\u201345\u00b0 E, 46.4\u201352.3\u00b0 N;\u2009\u2248\u20096\u2009\u00d7\u200910\u2075\u2009km\u00b2).![\"Fig.](\"https:\/\/www.europesays.com\/europe\/wp-content\/uploads\/2026\/04\/44407_2026_64_Fig1_HTML.png\")
The alternative text for this image may have been generated using AI.<\/p>\n
a\u2013c Total aerosol optical depth anomaly at 550\u2009nm on days 1, 5 and 20 after detonation, illustrating aerosol spatial dispersion in the days after detonation. d\u2013f Stratospheric temperature anomalies at 20\u2009km 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 d\u2013f marks grid points where the anomaly is not statistically significant (two-tailed Student\u2019s t test, p\u2009\u2265\u20090.05).<\/p>\n
Building on the hemispheric dispersion and solar-radiative heating shown in Fig. 1<\/a>, we examine the vertical distribution of BC mass concentration and temperature changes at the start (Month 1, January) and end (Month 12, December) of the first year (Fig. 2<\/a>a\u2013d). Figure 2<\/a>a, b shows the zonal-mean latitude\u2013altitude cross-sections of BC mass concentration (ensemble mean) in first and last month of the year. In the first month (Fig. 2a<\/a>), the mean BC concentration maxima occurs at ~15\u2009km with concentrations > 0.1\u2009\u00b5g\u2009m\u22123 in the NH. By contrast, by end of the year (Fig. 2b<\/a>, month 12) elevated BC concentrations are observed throughout the stratospheric column across both hemispheres, illustrating the interhemispheric transport of BC. Figure 2<\/a>c, d shows the corresponding zonal mean temperature anomalies (ensemble mean). In the first month (Fig. 2c<\/a>), peak zonal mean warming of ~15\u2009\u00b0C occurs near 20\u2009km altitude. By year-end (Fig. 2<\/a>d), the stratospheric temperature increase becomes more vertically extensive throughout the atmospheric column, with zonal mean temperature anomalies as high as ~40\u2009\u00b0C. 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\u2019s climate response.<\/p>\n Fig. 2: Zonal-mean vertical profiles of BC mass concentration and temperature response (ensemble mean) in month 1 (January) and 12 (December) after detonation (BC stratospheric emission occurring between Jan 1st and 7th). Black carbon mass concentration (\u03bcg m\u22123) in Month 1 (January) (a) and Month 12 (December) (b). Corresponding zonal-mean temperature anomalies (\u00b0C) in Month 1 (January) (c) and Month 12 (December) (d).<\/p>\n Figure 3<\/a> illustrates both the seasonal cycle and annual-mean climate responses in year 1 post-detonation: panels a, b the change in downward solar radiation, c, d surface temperature anomalies, e, f precipitation anomalies, and d\u2013h stratospheric wind perturbations. We also highlight anomalies across the land regions of Russia and USA, because they are the world\u2019s two largest nuclear-armed states, and their climates serve as high-latitude and mid-latitude benchmarks for assessing how even a regionally confined conflict in Eastern Europe could impose severe climate stress on the principal nuclear powers.<\/p>\n Fig. 3: Seasonal and annual-mean surface and stratospheric circulation response in the first-year post detonation. Surface solar radiation anomaly: a Monthly mean surface solar radiation anomalies (shading represents the ensemble variability) for the Northern Hemisphere (blue), Southern Hemisphere (red), Russia (green) and USA (purple). b Annual-mean surface solar flux anomaly. Surface temperature anomalies: c Monthly mean temperature anomalies d Annual-mean temperature anomaly. Precipitation anomaly: e Monthly rainfall anomalies f Annual mean precipitation percentage change. Stratospheric wind anomalies: g Time series of maximum zonal (blue), meridional (orange) and vertical (green) wind anomalies at 40\u2009km. 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\u2019s t test, p\u2009\u2265\u20090.05). Together, these panels demonstrate how the solar-radiative properties of BC drive substantial changes to climate variables in the 1st year after nuclear detonation.<\/p>\n As the BC disperses across the atmosphere globally, it induces a significant negative anomaly in the incoming surface solar radiation in year 1. In the NH, the downward solar radiation anomaly is \u2248 \u221220\u2009W\u2009m\u22122 by April (Fig. 3a<\/a>). As the BC spreads into the SH stratosphere, the solar flux anomaly is \u2248 \u221215\u2009W\u2009m\u22122 by end of year (SH summer). Mid-latitude continental zones in North America and Russia show anomalies between \u201310 and \u201350\u2009W\u2009m\u22122 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\u2009kgC\u2009m\u22122 across large parts of the NH, particularly over regions of North America and Asia (Supplementary Section 2<\/a> and Fig. S1<\/a>). The annual-mean downward solar radiation anomalies (Fig. 3b<\/a>) are substantial, \u2248\u221213.4\u2009W\u2009m\u22122 in the NH and \u2248\u22126.3\u2009W\u2009m\u22122 in the SH. The spatial pattern of solar flux anomaly closely follows the changing stratospheric BC mass concentration through the year (Fig. 2<\/a>), 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.<\/p>\n Surface temperature cooling develops rapidly during the first year after detonation (Fig. 3c, d<\/a>). The seasonal cycle (Fig. 3c<\/a>) shows that surface temperature anomalies in the NH develop rapidly within the first few months after detonation, reaching \u2248\u22121.5\u2009\u00b0C 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 (Fig. 3d<\/a>) confirms a hemispheric-average cooling of \u2248 \u22121\u2009\u00b0C in the NH compared to a slight warming of +0.01\u2009\u00b0C in the SH. Strong regional cooling (>\u22124\u2009\u00b0C) occurs over mid and high-latitude continental regions. Russia experiences the strongest anomaly (\u2248\u20135\u2009\u00b0C 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 (\u2248\u22123\u2009\u00b0C in spring), with ensemble members showing year-end anomalies as extreme as \u2248\u221210\u2009\u00b0C.<\/p>\n 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 (Figs. 3e, f<\/a> and 4a, b<\/a>). Annual-mean precipitation decreases by 20\u201340% 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 (Fig. 3f<\/a>), alongside land regions of the United States and Russia experiencing precipitation decreases of up to 20\u2009mm month\u22121 in year 1 (Fig. 3e<\/a>). These patterns are also consistent with the seasonal cycle shown in Fig. 4a<\/a>, where India and Niger experience pronounced monsoon season decreases of ~ 40\u2013100\u2009mm month\u22121 in July\u2013August. 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\u00b0E\u201391\u00b0E and 16\u00b0W\u201313\u00b0E, respectively) (Supplementary Section 2<\/a> and Figs. S2<\/a> and S3<\/a>), 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\u201360\u2009mm month\u22121 more than the control simulation (Fig. 4b<\/a>). Stream-function and vertical wind anomalies over longitudinal sectors (9\u00b0E\u201340\u00b0E and 112\u00b0E\u2013154\u00b0E) (Supplementary Section 2<\/a>, Figs. S4<\/a> and S5<\/a>) 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\u20136\u00b0 between March and June caused by the asymmetric NH cooling. The weakened, shifted ITCZ produces lower equatorial precipitation by ~0.5\u20131.0\u2009mm day\u22121 in year 1 (Supplementary Section 2<\/a> and Fig. S6<\/a>). 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.<\/p>\n Fig. 4: Regional Precipitation impacts in the first-year post detonation. Simulated year-1 monthly precipitation (mm month-1) for a India and Niger (NH), and b Australia and Namibia (SH). Comparison of Control (blue) and 5\u2009Tg 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.<\/p>\n The stratospheric wind dynamics changes driven by atmospheric temperature changes are prominently illustrated through wind anomalies at ~40\u2009km altitude (Fig. 3g\u2013h<\/a>), with the column vertical profile of the zonal, meridional and vertical winds shown in Fig. 5a\u2013c<\/a>. The time series (Fig. 3g<\/a>) highlights sustained zonal jet anomalies with velocities ranging between 50 and 200\u2009m\u2009s\u22121, meridional wind anomalies between 20 and 70\u2009m\u2009s\u22121, along with smaller but significant vertical wind anomalies between 0.02 and 0.1\u2009m\u2009s\u22121, 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\u2009km (Fig. 3h<\/a>) show strengthening of the subtropical and polar jets in both hemispheres, alongside perturbations to the vertical winds at high latitudes. In comparison, previous studies19<\/a> modelling a 5\u2009Tg BC India\u2013Pakistan conflict reported lower maximum stratospheric zonal wind anomalies of ~40\u2009m\u2009s\u22121 during the NH-winter, whereas our modelled scenario shows peak zonal wind anomaly between 100 and 200\u2009m\u2009s\u22121 during the same time period, reflecting differences in injection latitude, soot heating distribution, and structural inter-model differences.<\/p>\n Fig. 5: Zonal mean vertical profile of the zonal, meridional and vertical winds (ensemble mean) in the first-year post detonation. a Zonal-wind anomaly, \u0394u (m\u2009s\u22121). b Meridional-wind anomaly, \u0394v (m\u2009s\u22121). c Vertical-wind anomaly, \u0394w (cm\u2009s\u22121).<\/p>\n To evaluate how the geographic origin of the BC alters the subsequent Earth system response, we compare two war scenarios, each with 5\u2009Tg BC released into stratosphere: one originating from the Ukraine\u2013Russia border region (\u201cUKRRUS\u201d) and the other from the widely studied India\u2013Pakistan regional conflict scenario (\u201cINDPAK\u201d)6<\/a>,7<\/a>,9<\/a>,16<\/a>,17<\/a>. Previous modelling studies of the 5\u2009Tg INDPAK scenario consistently show declines in surface temperature and global mean precipitation6<\/a>,7<\/a>,9<\/a>. While there are notable differences in model setups\/configurations in past modelling studies\u2014which 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\u2009\u00b0C6<\/a>,7<\/a>,9<\/a>,20<\/a>, with reductions in global mean precipitation during the first year of 0.2\u20130.5\u2009mm\u2009day\u22121. Figure 6a<\/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. Figure 6b<\/a> 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<\/a> (Supplementary Section 2<\/a>) shows that both scenarios produce a comparable global-mean cooling of approximately 0.5\u2009\u00b0C, 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. 6c\u2013e<\/a>). Consequently, surface temperatures are lower at northern latitudes for UKRRUS (up to \u20132\u2009\u00b0C) than for the INDPAK scenario, but somewhat warmer at lower latitudes (\u2248\u2009+\u20091\u2009\u00b0C over parts of South Asia) (Fig. 6c<\/a>). These responses follow the spatial distribution of the change in the surface solar fluxes (Fig. 6d<\/a>). Solar dimming is more pronounced in mid-latitude continental regions for UKRRUS (\u20130.7\u2009W\u2009m\u22122 hemispheric mean) but yields a net positive anomaly in the SH (+2.2\u2009W\u2009m\u22122) 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 (Fig. 6e<\/a>), characterised by widespread suppression in the NH (up to 20\u2009mm month-1) and localised enhancement over Southeast Asia (up to 50\u2009mm month-1). These anomalies are primarily driven by a southward displacement of the ITCZ, which shifts up to 4\u00b0 further south by month 6 in the UKRRUS scenario compared to INDPAK (Supplementary Section 2<\/a> and Fig. S6<\/a>). 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<\/a> and Fig. S8<\/a>).<\/p>\n Fig. 6: Comparison between a Ukraine-Russia and an India-Pakistan Conflict to assess the influence of detonation location on climate. a Zonal-mean aerosol optical depth (AOD) anomalies at days 8 (solid) and 20 (dashed) for the Ukraine\u2013Russia (blue\/green) and India\u2013Pakistan (red\/orange) scenarios. b Annual-mean AOD anomaly at 550\u2009nm (UKRRUS \u2013 INDPAK), c Annual-mean surface temperature difference (UKRRUS \u2013 INDPAK), d Annual-mean change in downward solar radiation (UKRRUS \u2013 INDPAK). e Annual-mean change in precipitation (UKRRUS – INDPAK). Stippling in (b\u2013d) marks grid points where the anomaly is not statistically significant (two-tailed Student\u2019s t test, p\u2009\u2265\u20090.05).<\/p>\n Ukraine-Russia conflict: multi-year climate response<\/p>\n To evaluate the long-term climate impacts of the nuclear conflict, Fig. 7<\/a> 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).<\/p>\n Fig. 7: Ten-year evolution of climate anomalies post detonation. a Monthly surface air temperature anomalies (\u00b0C). b Downward solar radiation anomalies (W\u2009m\u22122). c Precipitation change (%). a\u2013c 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).<\/p>\n Land regions of Russia experience the largest negative temperature anomalies (Fig. 7a<\/a>), as low as ~\u20136\u2009\u00b0C (ensemble member minimum). The NH mean surface temperature also falls sharply (approximately \u20131\u2009\u00b0C), 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 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 ~\u22124\u2009\u00b0C.<\/p>\n Incoming surface solar radiation anomalies (Fig. 7b<\/a>) closely tracks the temperature changes. In the first year, the NH experiences a maximum decrease of approximately \u201313\u2009W\u2009m\u22122, with the US showing the largest decrease (\u2248\u201330\u2009W\u2009m\u22122) and Russia around \u201320\u2009W\u2009m\u22122. As the aerosol dispersed globally into the SH, the SH anomalies go as low as approximately \u221210\u2009W\u2009m\u22122 between years 1 and 2. From years 1 through 8, solar flux anomalies globally recover and approach baseline conditions.<\/p>\n Precipitation anomalies (Fig. 7c<\/a>) closely track the temporal evolution of surface temperature and surface solar radiation anomalies. During the first 2 years, NH mean precipitation declines by roughly 10\u201320%, equivalent to about \u22126 to \u221210\u2009mm month\u22121, with particularly strong reductions over Russia (up to \u221225%, or \u2248 \u221215 to \u221220\u2009mm month\u22121). The USA experiences more modest decreases of ~5\u201310% in comparison to Russia, albeit with substantial ensemble spread. These suppressed precipitation rates persist through years 3\u20136 before gradually returning toward baseline conditions. Precipitation anomalies in the SH remain minimal, constrained to within \u00b15% over the entire simulation period.<\/p>\n 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.<\/p>\n Near-term radioactive fallout\u201448\u2009h post detonation<\/p>\n Near-term fallout within the first 48\u2009h after detonation is estimated using the simplified empirical model of Glasstone and Dolan (1977)11<\/a>. Due to the inherent complexity and sensitivity of fallout dynamics to environmental parameters such as wind speed, precipitation, and conflict locations, this approach provides a practical framework for estimating early radioactive contamination. This approach is derived from historical nuclear weapons test data and has been applied to nuclear war impact modelling studies in the recent past16<\/a>, and enables us to estimate areas exposed to radioactive contamination within the first 48\u2009h following detonation. The 5\u2009Tg 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<\/a>) are carried out for 100 simultaneous 15-kiloton (kt) surface nuclear detonations scenario, evenly distributed across approximately 613,000\u2009km\u00b2 region along the Ukraine\u2013Russia border (46.4\u00b0\u201352.3\u00b0N, 32.1\u00b0\u201345.0\u00b0E) (Fig. 8a<\/a>).<\/p>\n Fig. 8: Global fallout analysis post detonation at the Ukraine-Russia border. a Location of the target region at the Ukraine-Russia border where 100 nuclear detonations (each 15\u2009kt 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\u2013Sv)<\/p>\n The mean surface winds over the region in the first month is ~ 5.3\u2009m\u2009s\u22121 (19\u2009km\u2009h\u22121) towards the northeast (~40\u00b0). Climatologically, radioactive debris from surface detonations would primarily be expected to disperse towards the northeast shortly after the explosions. By adapting the Glasstone\u2013Dolan fallout model to these specific wind conditions, we determine that each 15-kt detonation generates plumes that extend downwind approximately 62.7\u2009km for radiation doses exceeding 1\u2009Sv, 26.1\u2009km for doses exceeding 5\u2009Sv, and approximately 17.9\u2009km for the highest lethal threshold of 10\u2009Sv (Supplementary Section 3<\/a> and Table S1<\/a>) in 48\u2009h.<\/p>\n The fallout plume width ranges from ~0.9\u2009km for \u226510\u2009Sv to ~3.2\u2009km for \u22651\u2009Sv. Collectively, the 100 detonations produce a cumulative contaminated area of approximately ~20,000\u2009km\u00b2 (in 48\u2009h) at doses exceeding 1\u2009Sv, ~3500\u2009km\u00b2 above 5\u2009Sv, and ~1600\u2009km\u00b2 above 10\u2009Sv. For perspective, the 48-h fallout zone which experience doses \u22655\u2009Sv surpasses the size of the Chernobyl exclusion zone (~2600\u2009km\u00b2)21<\/a>, 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 Chernobyl22<\/a>.<\/p>\n Considering the average population density of the region (~49 persons\/km\u00b2, 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\u2009Sv, a threshold typically sufficient to induce acute radiation sickness. Within zones receiving \u22655\u2009Sv, roughly 170,000 people would encounter severe radiation sickness. The most critically impacted zone, receiving \u226510\u2009Sv, 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\u2009mSv per year23<\/a>, highlighting the extreme magnitude of these doses.<\/p>\n Beyond immediate health implications, the long-term consequences would persistently affect the region. Areas receiving \u22651\u2009Sv 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 environmental devastation24<\/a>.<\/p>\n Long term radioactive fallout from global BC transport and deposition<\/p>\n To assess the long-term fallout arising from global BC transport and deposition, we consider the release of radionuclides during nuclear detonation that can adhere to BC particles. Radionuclide attachment to aerosol particles has been well documented, including in observations following the Fukushima nuclear accident12<\/a>,13<\/a>. 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; T\u2081\/\u2082\u2009\u2248\u200930.2\u2009yr) and Strontium-90 (Sr-90; T\u2081\/\u2082\u2009\u2248\u200928.8\u2009yr) 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 timescales25<\/a>. 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 BC, with assumptions and parameters detailed in Supplementary Section 4<\/a> and Table S2<\/a>. 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.<\/p>\n 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. 8b\u2013e<\/a>). Figure 8b<\/a> 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\u2009Tg of BC has deposited globally. The surface deposition is initially concentrated in the NH, which receives most of the fallout in the first 1\u20132 years, but gradual cross-equatorial transport results in ~40% of the BC being deposited in the SH by year 10.<\/p>\n Maps of long-lived radionuclide fallout (Supplementary Section 2<\/a> and Fig. S9<\/a>a, b) for Cs-137 and Sr-90 show a widespread global deposition (methodology and assumptions are documented in Supplementary Section 4<\/a>), with the highest surface radiation levels up to ~10\u2009Bq\u2009m\u22122 in the NH by year 10. Both Cs-137 and Sr-90 show 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 (<0.1\u2009Bq\u2009m\u22122), but some areas close of 45S receive >0.4\u2009Bq\u2009m\u22122. 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.<\/p>\n Despite the broad geographic extent of radioactive contamination, the cumulative dose map (Fig. 8c<\/a>) shows that resulting radiation exposures remain very low. The 50-year cumulative effective dose from Cs137\u2009+\u2009Sr90 deposition is at most ~0.9\u2009mSv in the most affected regions (e.g. parts of Central Asia). Most of the NH land area receives ~ 0.1\u20130.3\u2009mSv, and virtually all populated areas in the SH stay below 0.07\u2009mSv. Such doses are far below the natural background (~2.4\u2009mSv\u2009yr\u22121) and by themselves would pose little direct health risk26<\/a>. However, Fig. 8d<\/a> indicates discernible differences in the radiation dose at the country level. The highest national mean 50-year cumulative doses (\u22480.25\u20130.48\u2009mSv per person) occur in smaller countries situated under the primary BC deposition areas: for example, Tajikistan (0.48\u2009mSv) and Bhutan (0.38\u2009mSv) top the list, followed by countries in Europe and Central Asia. Larger countries such as Russia have much higher localised deposition near the detonation zone, but their country average dose is diluted by vast areas with minimal fallout.<\/p>\n Collective radiation dose metrics26<\/a> (Fig. 8e<\/a>) underscore how population size modulates impact. China and India\u2019s large population, combined with its subtropical latitude, leads to a high collective radiation dose (China ~400,000 person\u2013Sv and India ~200,000 person-Sv), followed by countries in Central Asia, Africa and Europe. Figure 7b\u2013e<\/a> 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.<\/p>\n For perspective, the 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\u2009Mt 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\u20130.15\u2009mSv in just 1 year (1963)27<\/a>. In contrast, our modelled Cs-137 + Sr-90 fallout yields peak regional cumulative doses of ~0.8\u2009mSv over a period of 50 years, underscoring how much smaller the long-term radiological burden would be under our simulated scenario.<\/p>\n","protected":false},"excerpt":{"rendered":"Ukraine\u2013Russia conflict: year 1 after detonation After detonation, we explore the spatiotemporal evolution of the aerosol particles and…\n","protected":false},"author":2,"featured_media":20600,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2],"tags":[14906,14908,14907,4],"class_list":{"0":"post-20599","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-europe","8":"tag-climate-sciences","9":"tag-environmental-health","10":"tag-environmental-sciences","11":"tag-europe"},"_links":{"self":[{"href":"https:\/\/www.europesays.com\/europe\/wp-json\/wp\/v2\/posts\/20599","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.europesays.com\/europe\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.europesays.com\/europe\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/europe\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/europe\/wp-json\/wp\/v2\/comments?post=20599"}],"version-history":[{"count":0,"href":"https:\/\/www.europesays.com\/europe\/wp-json\/wp\/v2\/posts\/20599\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/europe\/wp-json\/wp\/v2\/media\/20600"}],"wp:attachment":[{"href":"https:\/\/www.europesays.com\/europe\/wp-json\/wp\/v2\/media?parent=20599"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.europesays.com\/europe\/wp-json\/wp\/v2\/categories?post=20599"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.europesays.com\/europe\/wp-json\/wp\/v2\/tags?post=20599"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}![\"Fig.](\"https:\/\/www.europesays.com\/europe\/wp-content\/uploads\/2026\/04\/44407_2026_64_Fig2_HTML.png\")
The alternative text for this image may have been generated using AI.<\/p>\n![\"Fig.](\"https:\/\/www.europesays.com\/europe\/wp-content\/uploads\/2026\/04\/44407_2026_64_Fig3_HTML.png\")
The alternative text for this image may have been generated using AI.<\/p>\n![\"Fig.](\"https:\/\/www.europesays.com\/europe\/wp-content\/uploads\/2026\/04\/44407_2026_64_Fig4_HTML.png\")
The alternative text for this image may have been generated using AI.<\/p>\n![\"Fig.](\"https:\/\/www.europesays.com\/europe\/wp-content\/uploads\/2026\/04\/44407_2026_64_Fig5_HTML.png\")
The alternative text for this image may have been generated using AI.<\/p>\n![\"Fig.](\"https:\/\/www.europesays.com\/europe\/wp-content\/uploads\/2026\/04\/44407_2026_64_Fig6_HTML.png\")
The alternative text for this image may have been generated using AI.<\/p>\n![\"Fig.](\"https:\/\/www.europesays.com\/europe\/wp-content\/uploads\/2026\/04\/44407_2026_64_Fig7_HTML.png\")
The alternative text for this image may have been generated using AI.<\/p>\n![\"Fig.](\"https:\/\/www.europesays.com\/europe\/wp-content\/uploads\/2026\/04\/44407_2026_64_Fig8_HTML.png\")
The alternative text for this image may have been generated using AI.<\/p>\n