Ecological Monographs, 85(1), 2015, pp. 49–72
Ó 2015 by the Ecological Society of America

Fire evolution in the radioactive forests of Ukraine and Belarus:
future risks for the population and the environment
N. EVANGELIOU,1,13 Y. BALKANSKI,1 A. COZIC,1 W. M. HAO,2 F. MOUILLOT,3 K. THONICKE,4 R. PAUGAM,5 S. ZIBTSEV,6T. A. MOUSSEAU,7 R. WANG,1,8 B. POULTER,1 A. PETKOV,2 C. YUE,1 P. CADULE,1 B. KOFFI,9 J. W. KAISER,5,10,11 AND
A. P. MøLLER12
1

CEA-UVSQ-CNRS UMR 8212, Institut Pierre et Simon Laplace, Laboratoire des Sciences du Climat et de l’Environnement (LSCE),
L’Orme des Merisiers, F-91191 Gif sur Yvette Cedex, France
2
Missoula Fire Sciences Laboratory, Rocky Mountain Research Station Forest Service, Missoula, Montana 59808-9361 USA
3
CEFE UMR 5175, CNRS, Universite´ de Montpellier, Universite´ Paul-Valéry Montpellier, EPHE-IRD, 1919 route de Mende,
34293 Montpellier Cedex 5, France
4
Potsdam Institute for Climate Impact Research (PIK), P.O. Box 60 12 03, 14412 Potsdam, Germany
5King’s College London, London, United Kingdom
6
National University of Life and Environmental Sciences of Ukraine, Kiev, Ukraine
7
Department of Biological Sciences, University of South Carolina, Columbia, South Carolina 29208 USA
8Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871 China
9
European Commission, Joint Research Centre, Air and Climate Unit, Ispra, Italy
10European Centre for Medium-range Weather Forecasts, Reading, United Kingdom
11
Max-Planck-Institute für Chemie, Mainz, Germany
12
Laboratoire d’Ecologie, Syste´matique et Evolution, CNRS UMR 8079, Universite´ Paris-Sud, Bâtiment 362, F-91405 Orsay Cedex,
FranceAbstract. In this paper, we analyze the current and future status of forests in Ukraine andBelarus that were contaminated after the nuclear disaster in 1986. Using several models,
together with remote-sensing data and observations, we studied how climate change in these
forests may affect ﬁre regimes. We investigated the possibility of 137Cs displacement over
Europe by studying previous ﬁre events, and examined three ﬁre scenarios that depended on
different emission altitudes of 137Cs, assuming that 10% of the forests were affected by ﬁres.
Field measurements and modeling simulations conﬁrmed that numerous radioactive
contaminants are still present at these sites in extremely large quantities.
Forests in Eastern Europe are characterized by large, highly ﬁre-prone patches that are
conducive to the development of extreme crown ﬁres. Since 1986, there has been a positive
correlation between extreme ﬁre events and drought in the two contaminated regions. Litter
carbon storage in the area has doubled since 1986 due to increased tree mortality anddecreased decomposition rates; dead trees and accumulating litter in turn can provide fuel for
wildﬁres that pose a high risk of redistributing radioactivity in future years. Intense ﬁres in
2002, 2008, and 2010 resulted in the displacement of 137Cs to the south; the cumulative amountof 137Cs re-deposited over Europe was equivalent to 8% of that deposited following the initial
Chernobyl disaster. However, a large amount of 137Cs still remains in these forests, which
could be remobilized along with a large number of other dangerous, long-lived, refractory
radionuclides. We predict that an expanding ﬂammable area associated with climate change
will lead to a high risk of radioactive contamination with characteristic ﬁre peaks in the future.
Current ﬁre-ﬁghting infrastructure in the region is inadequate due to understafﬁng and lack offunding. Our data yield the ﬁrst cogent predictions for future ﬁre incidents and provide
scientiﬁc insights that could inform and spur evidence-based policy decisions concerning
highly contaminated regions around the world, such as those of Chernobyl.
Key words: carbon stock; Cesium-137; Chernobyl; climate change; ﬁre risk; litter; redistribution;
wildﬁres.

INTRODUCTION
The April 1986 disaster at the Chernobyl Nuclear
Power Plant (ChNPP) in Ukraine (former Soviet Union)
resulted from a ﬂawed Soviet reactor design and serious
mistakes made by the operators. The ChNPP complex,
consisting of four nuclear reactors, is located about 100
km north of Kiev, Ukraine, and about 20 km south of
the border with Belarus. Soviet ofﬁcials began evacuat-

Manuscript received 26 June 2014; revised 29 August 2014;
accepted 5 September 2014. Corresponding Editor: A. T.
Classen.
13
Present address: NILU (Norsk institutt for luftforskning), Instituttveien 18, 2007 Kjeller, Norway.
E-mail: Nikolaos.Evangeliou@nilu.no49

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N. EVANGELIOU ET AL.

ing residents near the ChNPP 36 hours after the
explosion and by 1990, more than 350 000 people had
been displaced and resettled from the most severely
contaminated areas of Belarus, Russia, and Ukraine(UNDP and UNICEF 2002). This left a 2600-km2 area,
now known as the Chernobyl Exclusion Zone (CEZ),
empty of humans. However, around 600 000 emergency
workers were drafted to clean up the contamination andmanage the remaining three reactors (the last of whichclosed in December 2000) and large amounts ofcontaminants still remain inside. North of the borderwith Ukraine, Belarusian authorities created a similar
2200-km2 restricted zone.
Thousands of hectares of a largely rural area wereseverely contaminated as a result of the accident. Forestsand ﬁelds were subjected to a dense cloud of radioactive
fallout that included 137Cs (half-life 30.2 years), 90Sr
(half-life 28.8 years), multiple isotopes of plutonium,
and other radionuclides (NEA 2002). Among the tasksof the cleanup workers (known as ‘‘liquidators’’) werefelling, bulldozing, and burying all the trees in a 4 km
radius around the ChNPP. They also constructed aseries of dikes designed to prevent ﬂooding into the
Pripyat River, and from there into the Dnieper River,which ﬂows through Kiev to the Black Sea. Most of thecontamination sank into benthic river and reservoir
sediments, where it is supposedly stable (IAEA 2006).
With no one to cut saplings and cultivate ﬁelds,
natural ecological succession has gradually transformed
the landscape. Forests that covered 53% of the area
before the disaster now cover more than 70% (IAEA
2001). Stands dominated by birches (Betula pendula) andpines (Pinus sylvestris) have taken over pastures where
farmers formerly grew wheat and ﬂax. Most pines(which are more sensitive to radiation than birches;
Yoschenko et al. 2011) seem normal, although deformed
trees are common in contaminated areas and substantial
negative effects of radiation on tree growth have beenreported (e.g., Mousseau et al. 2013).
Radionuclides have migrated into the forest soil and,for the most part, remain there. Studies have shown that
90% of 90Sr is located in the top 10 cm of the soil (IRL2013), whereas Yablokov et al. (2009) reported that 80%
of 137Cs remained in the top 5 cm in the area. As trees,
grasses, other plants, and fungi transpire (release water),they draw water up from the roots. Water-soluble saltsof cesium and strontium are chemical analogues ofpotassium and calcium, respectively, and are taken up inplace of these crucial nutrients. The leaves fall to theground in autumn, becoming part of the ‘‘litter’’ (theabscised vegetation that covers the forest ﬂoor), thus
returning the radioactive salts to the top layer of the soil.
Without the presence of trees or other permanent
groundcover, contaminants would likely migrate out of
the soil by being dispersed in dust or carried by water.
People living just outside the exclusion zone, who
depend on forests for work, food, fuel, and otherresources, pay the cost for this environmental contam-

Ecological MonographsVol. 85, No. 1

ination. Many continue to live in areas with 137Cs soil
concentrations greater than 37 kBq/m2. They also
continue to eat mushrooms, berries, and other local
forest foods, despite government restrictions and warnings (NEA 2002). Mushrooms, which are highly prized
by local populations, absorb high concentrations ofradioactive cesium (Linkov et al. 2000). Although 137Cs
content in the majority of edible mushrooms decreased
by 20–30% between 2005 and 2010, fungal species whose
feeding networks (mycelia) reach deeper into the soil
showed substantial increases in the amount of 137Cs
during the same period as radionuclides migrated into
deeper soil layers (NRU 2011).
Chernobyl contamination is also affecting non-humancommunities. Although it has been reported that theabsence of people has attracted a surprising amount of
wildlife, scientiﬁc surveys suggest that the populations ofmany mammals and birds are not as diverse or abundant
as would have been expected in a region where there islittle pressure from human communities (Møller andMousseau 2013). Fewer mammals live and reproduce inhigh-radiation areas than in less contaminated ones
(Møller and Mousseau 2013). Birds show reduced
longevity and male fertility, smaller brains, andincreased frequency of mutations that indicate signiﬁcant genetic damage (Møller et al. 2012). Likewise, somebird populations in contaminated areas are only
sustained via immigration from adjacent uncontaminated regions (Møller et al. 2006).
Ukrainian law requires that the exclusion zone should
be managed as a barrier that ﬁxes contamination
through natural processes; everything deposited in1986 must stay within the guarded area. Prohibiting
residence and economic activities such as commercial
forestry helps keep contaminated materials inside thezone. The effectiveness of such laws is often challenged,
however, since many trucks transporting large logs ofpine and other trees have been observed in CEZ during
the summer of 2013 (A. P. Møller, personal observations).
Proponents of extensive decontamination in Chernobyl see many beneﬁts beyond public safety including(1) more productive timber plantations (thousands ofhectares were in need of thinning even before thedisaster); (2) jobs; and (3) a sustainable energy source(if debris can be burned in biomass power plants). On
the other hand, uncontrolled burning of contaminatedwood may negate these putative beneﬁts by spreading
contaminants far beyond their current locations. Trees
and other groundcover that are currently trapping
radionuclides may become more susceptible to ﬁre.
The stands that now grow on approximately 1800 km2
are largely unmanaged. As trees mature and die andmore sunlight penetrates the canopy, brush and other
understory species are starting to grow. The Chernobyl
forests are thus developing ‘‘fuel ladders’’ of vegetationthat would enable a ﬁre to climb into the tree canopy
and burgeon into a crown ﬁre (Hao et al. 2009). A lackFebruary 2015

FIRE EVOLUTION IN RADIOACTIVE FORESTS

of effective forest management, combined with a generaldrying trend attributable to local climate change, could
lead to catastrophic ﬁres more intense than thosealready seen in Chernobyl.
When forests laden with radionucleotides burn, theyemit radioactive cesium, strontium, and plutonium in
respirable ﬁne particles (Hao et al. 2009). Here, we use
the terms displacement or redistribution of 137Cs todeﬁne the amount of 137Cs present in the vegetation,soil, or litter, which would be emitted in the atmosphericaerosol after a major ﬁre. High-intensity crown ﬁres in
Chernobyl would release large amounts of radionuclides
and transport these emissions hundreds to thousands ofkilometers to human population centers (Hao et al.
2009). Such contamination could trigger long-term,
economically damaging government restrictions on
contaminated milk, meat, and vegetables.
The Ukrainian government faces the challenge ofprotecting its citizens, even as it strives to returnresidents to the rural communities that would provide
them with clean water, food, ﬁrewood, and livelihoods.
Whether Ukraine opts for leaving forests to their slow
but natural recovery or attempts to decontaminate
them, local residents will inevitably be affected byongoing contamination. These effects may be exacerbated by the current political instability in Ukraine anda reduction in the priority of forest management andchanges in ﬁre ﬁghting policy due to other governmental
activities. Therefore, the primary aim of present paper is
to alert the scientiﬁc community about how changes in
Chernobyl forests, accompanied by pronounced climaticchanges, could remobilize radioactivity. Another aim is
to provide scientiﬁc insights that could motivate andinform evidenced-based policy decisions concerning
radioactively contaminated regions around the world.
In this paper, we explicitly investigate a number ofhypotheses to address the two aims listed in the previous
paragraph. We do so by focusing on two areas with thehighest deposition density after the Chernobyl accident,
namely (1) a region centered at the ChNPP between 298 E
to 318 E and 50.58 N to 528 N where deposition density
ranges from 40 to more than 1480 kBq/m2 and (2) a highly
contaminated zone 50 km northeast of the NPP in Belarus(30.58 E to 32.58 E and 528 N to 53.58 N). The
International Atomic Energy Agency (IAEA 2005, 2009)
deﬁnes any area with surface activity larger than 40 kBq/
m2 (for beta and gamma emitters) as contaminated. In aﬁrst hypothesis, we test to what extent wildﬁres incontaminated regions of Ukraine and Belarus result in
atmospheric transport and redeposition of radionuclides.
To this end, we analyze the wildﬁres of 2002, 2008, and2010 in the contaminated regions of Ukraine and Belarus
and document the atmospheric transport and ‘‘new’’deposition of 137Cs throughout Europe after its redistribution by ﬁres. Cesium-137 is among the most dangerous
radionuclides released after nuclear accidents, due to its
long half-life, the radiation type it emits during decay, andits bioaccumulation by organisms (Woodhead 1973). The

51

second hypothesis posits that atmospheric transport of
Cs in smoke will depend on injection heights. The effectof the injection height of 137Cs (present in smoke) on
atmospheric transport is determined by investigating threeﬁre scenarios that differ only by their injection heights.
The third hypothesis suggests that the frequency andmagnitude of ﬁres will depend on the development of thevegetation and climate change. To this end, we model theoccurrence of future ﬁres (2010–2100) in the area,
incorporating several different models (e.g., for vegetationand ﬁre) and satellite data (e.g., MODIS) in order toreduce uncertainty and to present realistic past, present
and future predictions of the hazards and risks fromradioactivity redistribution by wildﬁres. Based on our
ﬁndings, we recommend policy changes aimed at preventing further future contamination. To our knowledge, thisis the ﬁrst paper in which the effects of climate change on
wildﬁres are studied in relation to radionuclide mobility.
137

DATABASES AND METHODOLOGY
Databases for climate model diagnosis
and inter-comparison
Temperature and precipitation ﬁelds in contaminatedareas of Chernobyl were taken from the Program for
Climate Model Diagnosis and Inter-comparison(PCMDI) databases. PCMDI was established in 1989
at the Lawrence Livermore National Laboratory (USA)and aims to develop tools for the diagnosis and intercomparison of general circulation models (GCMs) thatsimulate global climate. The GCMs adopted here arefrom the modeling groups of the Canadian Centre for
Climate Modeling and Analysis (CCCMA); the CSIRO
atmospheric research (CSIRO); the U.S. Department ofCommerce, NOAA, Geophysical Fluid Dynamics Laboratory (GFDL); the NASA Goddard Institute for SpaceStudies (GISS); the Institut Pierre et Simon Laplace(IPSL); the Meteorological Institute of the University ofBonn (MIUB); the Max Planck Institute for Meteorology(MPI); the National Center for Atmospheric Research(NCAR); and the Hadley Center for Climate Prediction
and Research, Met Ofﬁce (UKMO).
Global Fire Emissions Database (GFED3) andStandardized Precipitation–Evapotranspiration Index(SPEI) database
Satellite data on ﬁre activity and vegetation productivity were combined to estimate gridded burned area
and ﬁre emissions. The GFED3 database (which
combines multiple satellite ﬁre products for better
accuracy and longer time series [Giglio et al. 2010]),was used to estimate burned area, because it constitutes
the current reference data set available for all over theworld (Mouillot et al. 2014; GFED3 database available
online).14 The database offers burned area for each 0.58
resolution pixel globally, on a monthly time step, andthe subsequent emissions due to biomass burning,14

http://www.falw.vu/;gwerf/GFED/GFED3/emissions/

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N. EVANGELIOU ET AL.

including carbon (CO, CO2), methane and non-methanehydrocarbons, NOx, SO2, and particulate matter.
Emissions were based on a global estimation of fuelbiomass and moisture content simulated by the biogeochemical model CASA (Potter et al. 1993), coupled witha combustion module (Van der Werf et al. 2003), using
emissions factors from Akagi et al. (2011).
As ﬁre-spread is the result of a combination between
fuel moisture, fuel amount, and landscape pattern (Caryet al. 2006, Krawchuk and Moritz 2011), we investigatedthe continental-scale ﬁre regime as a response to
drought, tree cover, and forest patch presence. Drought
effects are apparent only after a long period with ashortage of precipitation, making it very difﬁcult toobjectively quantify the characteristics of drought
episodes in terms of their intensity, magnitude, duration,and spatial extent. We selected SPEI as an integrative
drought index, which calculates normalized monthly
drought anomalies as the precipitation/potential evapotranspiration differences compared to the averagecalculated over the whole time series. SPEI is expressed
according to the time frame and the month considered
for calculation and is available at a 0.58 resolution
globally for the period 1901 to the present (VicenteSerrano et al. 2012); for instance, we selected the SPEI03
for September corresponding to the integrated drought
index over the three months before September (summer). Statistical analysis for the temporal trend in the
SPEI03 was performed using the non-parametric MannKendall trend test using the Kendall R package and the
Tukey honestly signiﬁcant difference (tukeyHSD function using R [R Development Core Team 2014]) forcomparing burned area distribution among SPEI03
drought classes.
Continental-scale fuel biomass and landscape structure were investigated from tree cover. Kempeneers et al.
(2011) provided data of different remote-sensing products to produce an accurate tree cover map at 1-km
resolution for Europe, including Ukraine and Belarus(Appendix: Fig. A1) as a surrogate for the Corine Land
cover, from which Eastern Europe is not included.
Landscape indices of largest patch index (LPI) andmean patch area (MPA) were calculated (Fragstats;
MacGarigal and Marks 1994) for each 0.58 cell over
Europe based on forest patch analysis derived from thetree cover map reclassiﬁed into forest/non forest at a
50% tree cover threshold.
Moderate Resolution Imaging Spectroradiometer(MODIS) area burned data
To document the multiple ﬁres that occurred in the
two areas of interest, we used the MODIS direct
broadcast (DB) algorithm developed by Urbanski etal. (2009), which combines active ﬁre detection and burnscar detections in single satellite scenes to map burned
areas with a nominal spatial and temporal resolution of
500 m and 1 day, respectively. The MODIS-DB
algorithm provides rapid mapping of burned areas andEcological MonographsVol. 85, No. 1

enables production of a regional emission inventory
within 1 hour of the ﬁnal (Aqua satellite), local MODIS
overpass. Although the algorithm was designed toprocess DB data in near-real time, archived data wereused (Urbanski et al. 2011) to monitor the spatial andtemporal distribution of ﬁres, smoke, vegetation, andﬂooding in the two contaminated areas. The dates andthe spatial distribution of ﬁres were determined from
MODIS active ﬁres for the years 2002, 2008, and 2010.
For the three ﬁre scenarios that assumed that 10% of thecontaminated area is burned (2010 scenario 6, 2010
scenario 7, and 2010 scenario 8), we kept the same
temporal pattern with the ﬁres of 2010 in the area.
MODIS area burned (250 000 m2 per pixel) was
combined with 137Cs deposition densities (kBq/m2) andthe respective emission factors to estimate 137Cs
emission per pixel.
Biomass burning estimates using PKU-FUEL
Inventories of ﬁrewood and straw consumption in thedomestic sector, as well as agricultural solid wasteburning in the ﬁelds, were derived from PKU-FUEL(Peking University Fuel Inventory) for the year 2007 at
0.18 3 0.18 resolution (Wang et al. 2013); the productcovers 36 European countries for the year 2007. The
same inventories for 1986 (0.18 3 0.18) data were derived
by scaling the gridded data with the ratio of national
consumptions between 1986 and 2007. Speciﬁcally, thenational consumption of ﬁrewood and agricultural solid
waste burning were collected from FAO (2013), and thedata on domestic straw consumption from IEA (2013).
The projections show the temporal change of ﬁrewood
and straw consumption in the area, as well as changes inagricultural burning since the date of the accident.
Assumptions on the redistribution of 137Cs
Only four references were found in the relevant
literature and taken into consideration in order to deﬁne
the amount of 137Cs emitted after ﬁres (hereafter,
emission factor). Yoschenko et al. (2006) used threenatural experimental sites in the CEZ. They measured
background radiation, soil, natural litter, and vegetationand then estimated the budget, concluding that theredistribution of 137Cs after ﬁres was at least 4%. Amiro
et al. (1996) carried out experimental burning of straw,
pine, and Norway maple (Acer platanoides) recording
several physicochemical characteristics such as temperature and moisture of the fuel. They concluded that theredistribution of 137Cs is a highly variable processdepending on the ﬁre temperature and the type ofvegetation in the fuel and may range from 20% to 100%.
Horrill et al. (1995) performed experimental burns ofheather (Calluna vulgaris) in an area of Scotland thatwas intensely affected by the Chernobyl accident, sinceheather has been found to accumulate higher levels ofradiocesium than many other upland plants (Bunzl andKracke 1984). They found that 10–40% of 137Cs would
be lost after a heather ﬁre, strongly depending on theFebruary 2015

FIRE EVOLUTION IN RADIOACTIVE FORESTS

temperature (12% after cool burning and 39% after hot
burning). Piga (2010) performed similar ﬁre experiments
in an artiﬁcial experimental site at the Institut deRadioprotection et de Sûreté Nucléaire, France, using
contaminated wood as fuel. He recorded 137Cs levels
before and after burning, as well as the emitted amountin the ambient aerosol, concluding that the redistribution was approximately 10%. These studies indicate thatthe redistribution of 137Cs strongly depends on thetemperature of the ﬁre and the type of vegetation used asfuel. Most of the aforementioned studies were based on
experiments in which controlled conditions were maintained, whereas our study aimed to analyze uncontrolled
wildﬁres. Given that the prevailing temperatures in a
wildﬁre are higher than the controlled experiments, we
expected the redistribution of 137Cs to be close to that
estimated by Horrill et al. (1995) for hot burning,corresponding to approximately 40%.
We also addressed the fate of 137Cs deposited in thesoil and the amount redistributed after ﬁres. Analyses ofdata collected after Chernobyl, and recently after
Fukushima (e.g., Hashimoto et al. 2012) have shownthat 137Cs is accumulated in the topsoil layer (FilipovicVincekovic et al. 1991, Avery 1996) and remains there
for many years with a migration velocity of approximately 0.09 cm/yr (Lujanieneo et al. 2002). Once
deposited, 137Cs is affected by many site-speciﬁc factors
including soil type, rainfall, drainage, terrain, vegetation, and local activities and conditions. Studying four
different contaminated sites in Chernobyl in 1991,
Poiarkov (1995) showed that 84–86% of 137Cs predominated in the litter and the ﬁrst 2 cm of the soil, whereas
the remainder migrated into deeper layers of the soil.
The fraction of 137Cs in topsoil was much higher inFukushima (97%) one year after the accident (Tanaka et
al. 2012). The cesium cation (the predominant species of
Cs in aqueous solution) interacts strongly with manysoils due to its low tendency to hydrate and higher
polarizability than smaller ions like Kþ (Avery 1996). Itsbinding in soils is largely contingent on the content of
inorganic minerals relative to organic matter. The
organic fraction of soils has a larger cation exchange
capacity than inorganic soil particles. Organic mattercan bind Csþ, acting as a transfer parameter for Cs (DeBrouwer et al. 1994, Shand et al. 1994, Lujanieneo et al.
2002). Since 137Cs has a relatively low boiling point of
6698C, it is partially volatilized in smoke even whenbound in soil. Paliouris et al. (1995) showed that morethan 20% of 137Cs is redistributed by large ﬁres in North
American boreal forests. Due to the lack of such studies
in highly contaminated areas, and for simplicity’s sake,we assumed that this ratio was the same as that for the
redistribution of 137Cs following burning (40%).
The transport model
The coupled model LMDZORINCA was used in thesimulations (Szopa et al. 2012) consisting of the aerosol
module INCA (INteractions between Chemistry and53

Aerosols), the general circulation model (GCM),
LMDz, (Laboratoire de Météorologie Dynamique),and the global vegetation model ORCHIDEE (ORganizing Carbon and Hydrology In Dynamic Ecosystems
Environment). The model accounts for emission, transport, photochemical transformations, and dry and wet
scavenging of chemical species and aerosols (Evangeliou
et al. 2013). The horizontal resolution of the model inthe regular grid is 1.278 in latitude and 2.508 in
longitude, whereas the vertical grid is divided into 19
levels from the surface up to about 3.8 hPa. However,the GCM also offers the opportunity to stretch the grid
over speciﬁc regions using the same number of gridboxes. In the present study, the ﬁre incidents were
simulated using the zoom version for Europe, achievinga horizontal resolution of 0.518 3 0.458 for 19 verticallevels. The model can be run in a nudged mode using the
ERA40 reanalysis data, with 6-h wind ﬁelds, by theEuropean Centre for Medium-Range Weather Forecasts(ECMWF 2002) with a relaxation time of 10 days forthe regular grid; in the zoom version, the model was
relaxed to 4.8 days in the center of the zoom and to 10
days outside (Hourdin and Issartel 2000).
Wildﬁres in the years 2002, 2008, and 2010 were
simulated, and three extreme ﬁre scenarios were alsostudied assuming that 10% of the contaminated forests
were burned following different injection regimes
described in detail in Estimates of the altitude of theemissions near Chernobyl and Belarusian forests using the
Plume Rise Model (PRM) (2010 scenario 6, 2010
scenario 7, and 2010 scenario 8). Each simulation lasted
from March to the end of the year. According torelevant measurements of 137Cs activity concentrations
after the recent accident of Fukushima, the detection of137
Cs in the ambient aerosol ended 2–3 months after the
initial emissions (Masson et al. 2011, Long et al. 2012,
McMullin et al. 2012, Paatero et al. 2012); therefore, one
year was sufﬁcient to obtain an overall view of thedeposition of 137Cs after wildﬁres.
Estimates of the altitude of the emissions near Chernobyl
and Belarusian forests using the Plume Rise Model(PRM)
Current deposition densities were needed in order toestimate the redistribution of 137Cs after ﬁres. Therefore,
we used the Radioactivity Environmental Monitoring(REM) database (De Cort et al. 1998), combined withmeasurement data adapted from Kashparov et al.
(2003), assuming an effective half-life of 137Cs of 10
years. Bergan (2000), in the ﬁrst complete study about
ecological loss of 137Cs, reported that ‘‘the calculated
effective half-lives of radiocesium in the surface soil
layer vary across the sites from 10 to 30 years, which isequal to the physical half-life of 137Cs’’. Effective halflife of 137Cs combines its physical decay and also its
ecological half-life (which includes all environmental
removing processes, such as vertical migration, runoff tolarge reservoirs, soil erosion, etc); hence, the data were54

N. EVANGELIOU ET AL.

corrected for 1 March 2002, 2008, and 2010. The data
were validated using measurement-based maps reported
in the NRU (2011).
Once aloft, air currents can transport ﬁre emissions,affecting their longevity, chemical conversion, and fate.
Models and observations (e.g., Chin et al. 2002, Bertschi
et al. 2004) have shown that aerosol residence times in
the atmosphere and downwind effects on surface air
quality depend on the heights at which emissions are
injected. In a study of 1998 boreal ﬁres, Leung et al.
(2007) concluded that at least half of the carbon is
injected above the boundary layer (3–5 km) as a result of
convection. Studies of crown ﬁres have shown that manyﬁres generate sufﬁcient energy to loft smoke plumes
above the boundary layer (Cofer et al. 1996, Lavoue etal. 2000) up to stratospheric altitudes by supercell
convection (Fromm and Servranckx 2003, Fromm etal. 2008). The goal here was to generate realistic
parameterizations for the injection heights of forest ﬁrescenarios to be used in our global atmospheric model.
Chemical transport models (CTMs) are used toquantify these processes. Unlike all other emissions(except for those from aircraft and volcanoes), ﬁres may
inject their smoke plumes into the troposphere, andoccasionally even into the lower stratosphere, by virtueof the intense radiative energy and convection producedby the burning fuel. The dynamics of the plumeresponsible for the updraft and its ﬁnal emission proﬁletake place at scales than range below CTM resolution
and therefore cannot be modeled; thus, parameterization is usually needed to predict ﬁre injection height at alarge scale. Several plume models have already been
implemented in CTMs, each of them focusing on
different aspects of plume dynamics. The PRM of
Freitas et al. (2007, 2010) emphasizes the role of moist
convection and ambient wind shear. Rio et al. (2010)
developed a model that, together with modeling watertransport within the plume, can interact with ambient
stratiﬁcation. Soﬁev et al. (2012) derived an empiricalmodel from dimensional analysis and optimization,using as input the ﬁre radiative power (FRP), to model
the convection induced by the ﬁre, and the BruntVasisala frequency above the boundary layer to model
the effect of atmospheric stability. To our knowledge,
these parameterizations have not been properly validated. However, Val Martin et al. (2013) used the Multiangle Imaging SpectroRadiometer (MISR) injection
height data set to run a ﬁre-by-ﬁre comparison, andconcluded that the performance of the PRM was notreliable. Such validations on a ﬁre-by-ﬁre basis areproblematic in that the main source of available data,
the MISR injection height data set, might be biased by
the fact that ﬁre observations occur in most cases earlyin the morning when ﬁre intensity and plumes are notyet mature.
Recently, a new approach based on the original
version of PRM has been developed to introduce
additional physical constraints (Paugam et al. 2010).

Ecological MonographsVol. 85, No. 1

In the new PRM2 model, an equation for massconservation was added, the ﬁre-induced convection
was derived from FRP measurements, and the entrainment and detrainment scheme was improved to adapt tomore atmospheric scenarios. Six parameters wereintroduced and optimized to ﬁt well-characterized ﬁreevents. The selection of these particular ﬁres was madethrough the MISR data set, and ﬁres were detected wheneffects of the diurnal cycle (high-latitude ﬁres had more
Terra overpasses, and so had MISR observations madelater in the day), or the time lag between ﬁre radiationand plume development (use of multiple overpass form
Terra and Aqua are used to only consider mature ﬁre)could be considered negligible. For each ﬁre a detrainment proﬁle was computed, allowing estimation of theratio of burned mass emitted in the boundary layer andabove it at the scale of every single ﬁre. Fig. 1 shows
results of the PRM2 model applied to ﬁres detected by
MODIS (for both Terra and Aqua sensors) in the
Ukrainian and Belarusian forests for the years 2003,
2008, and 2010. It shows the average and maximum
injection height above the boundary layer, the maximum
injection height above the ground, the number of ﬁres,and the total ﬁre radiative energy (FRE) in the selected
area. Fig. 1 emphasizes the variability of injection height(with injection up to 7 km) and mean injection heights
above the boundary layer (top panels) and the dependence on the atmosphere, as the maxima above theboundary layer do not necessarily match with the
maximum height above the ground or the ﬁre activity.
For all these reasons, we assumed 137Cs would follow
the same dynamics with ﬁre emissions from the PRM2
and therefore, a mean vertical mass proﬁle wascomputed and applied to the 137Cs emission from ﬁres.
Due to the lack of data in 2002, we used the vertical
distribution of the plume for 2003 (a more conventional
distribution), in which the maximum injection height
reached 2.9 km. For 2008 ﬁres, in which larger injection
heights were obtained by the PRM2 model (FRE wasextremely high, reﬂecting the high ﬁre intensity), theupper limit of the injection was set to 6 km. For the large
ﬁres of 2010, a maximum emission altitude of 4.3 km
was chosen on the basis of the results presented in Fig. 1.
Val Martin et al. (2010) and Kahn et al. (2008) showedthat ﬁres in boreal forests of North America and Alaska
resulted in smoke injections above the boundary layer.
In addition, Soﬁev et al. (2013) published global maps ofemission heights and the resulting vertical proﬁles for
wildﬁres that occurred between 2000 and 2012. They
concluded that regions with moderately high injection
heights include forests in Amazonia, equatorial andsouthern Africa, and central Eurasia, where 90% of themass is emitted within the lowest 3 km of theatmosphere (the boundary layer in these forests can beseen in Appendix: Fig. A2). These regions are notablefor quite strong ﬁres and deep boundary layers (van derWerf et al. 2010), and include the Ukrainian andBelarusian forests. The proﬁles used here were compa-

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FIG. 1. Mean and maximum injection height above the boundary layer (InjHBL; km), maximum injection height above theground (max InjH; km), number of ﬁres, and total ﬁre radiative energy (FRE) in the selected area for the ﬁres in 2002, 2008, and2010.

rable to those presented by Soﬁev et al. (2013), wherein;90% of 137Cs is emitted within 3 km height. Finally,
three extreme scenarios were also studied (10% of thecontaminated area burns), accounting for a maximum
injection at 2.9 km (2010 scenario 6), 4.3 km (2010
scenario 7), and up to 6 km (2010 scenario 8) using thesame proﬁles of the ﬁre years 2002, 2010, and 2008,
respectively. The spatial deposition density of 137Cs (Bq/m2) in these forests is multiplied with the burned area(m2) from MODIS and the emission factor (40%), in
order to estimate 137Cs emissions after ﬁres.

occurrence and can mimic broad geographic patterns
during the peak ﬁre season. Modeled ﬁre season
duration is generally overestimated by about one month,
but shows a realistic pattern of differences among
biomes. Comparisons with remotely sensed burned area
products have indicated that the model reproduces
broad geographic patterns of annual fractional burned
area over most regions, including the boreal forest(Thonicke et al. 2010).

LPJmL-SPITFIRE coupled model for litter carbon
storage

Climate change in Chernobyl and Belarus

A process-based ﬁre regime model, SPread and
InTensity of FIRE (SPITFIRE; Thonicke et al. 2001),
coupled with ecosystem dynamics in the LPJmL (Lund,
Potsdam, and Jena) Dynamic Global Vegetation Model(Sitch et al. 2003, Gerten et al. 2004, Bondeau et al.
2007) was used to explore relationships between litter
carbon stock and ﬁre tendency from 1986 to 2010. The
aim was to study past, present, and future effects of ﬁreson the terrestrial carbon cycle and the associatedemissions of trace atmospheric constituents. The same
coupled conﬁguration was used to estimate futureburned areas and litter carbon storage in Europe andspeciﬁcally in contaminated regions of Ukraine andBelarus up to 2100 under the REMO-A1B climatechange scenario. Comparison with observed active ﬁrecounts have shown that the model reproduces ﬁre

RESULTS
Empirical observations over the past century haveshown that temperatures at the surface have risen
globally, with important regional variations. Global
average warming has been increasing since 1900, with atrend between 0.078 6 0.028C per decade to 0.138 6
0.038C per decade (Scafetta and West 2006). Observations of global precipitation have shown that variability
exists in the amount, intensity, frequency, and type ofprecipitation. Temperatures in Ukraine and Belarus
have become increasingly warmer in spring and summer
since 1950, and precipitation has decreased (or remained
stable) considerably during the same period (Fig. 2). The
most pronounced increase occurred during July–August
2010, when temperatures exceeded 408C accompanied bymany weeks without precipitation. With the projected
increase in CO2 and other greenhouse gases, mostcoupled models predict an increase in the occurrence

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of exceedingly warm and dry summers in the future (Fig.
2).
Recent ﬁre history as seen from GFED3 burned area
database
Annual average and maximum values of burned area(BA), total carbon (TC), and total particulate matter(TPM) for Europe derived from the GFED3 databaseare presented for the 1997–2009 period in Appendix:
Fig. A3. The most ﬁre-prone areas were the grasslandsof Eastern Europe and the Mediterranean forests withan average of 5000 ha/cell unit (0.58) corresponding to
2% of the cell. Annual maximum burned area reached
50 000 ha (20% of the grid cell) during extreme ﬁre years.
TC and TPM emitted during ﬁre events depended on thefuel amount available for burning; for example, except
for acting as a spreading agent, grassland steppes
remained a very large atmospheric emitter during ﬁresin the same range with forest ecosystems of high fuelamounts (Appendix: Fig. A2). Located at the interface
between grassland steppes and the temperate/boreal
biomes, Ukraine is affected by both recurrent grasslandﬁres and less-frequent but more intensively emitting
forest ﬁres.
The largest burned areas in Europe during the last
decade occurred in 2003 and 2005 (Fig. 3). In 2001,
ﬁres were widespread in the Eastern Mediterraneanand Ukraine, whereas 2003 was the most extreme year
for ﬁres in grassland steppes. Very important forest
ﬁres occurred in Portugal, northern Ukraine, andGreece in 2005 and 2007, and ﬁres burned considerable forest areas in Russia in 2008. Burned areas
varied between 100 000 ha in 1997 to 837 000 ha in
2003, with an average of 260 000 ha in Europe (JRC2014).
Fire activity and drought in Europe
According to the ‘‘varying constraint hypothesis’’(Krawchuk and Moritz 2011), ﬁre activity is a functionof the fuel amount available. Increasing drought affects
ﬁre activity differently depending on the availability offuel. The last increases ﬁre risk in fuel-unlimited areas
as a consequence of low fuel moisture content, while
decreases ﬁre risk in fuel-limited areas by reducing net
primary production and in turn fuel accumulation.
Using the summer SPEI03 drought index time series forthe period 1901–2009 we computed the driest andwettest extreme years for the 1997–2008 period overChernobyl (Fig. 4a). The driest years (minimum
SPEI03) in the regions of interest were 2003 fornorthwestern Europe (due to the extreme heat wave),

FIG. 3. Continental distribution of maximum ﬁre year in
Europe for 1997–2008 based on the GFED3 database.

2005 in Portugal and northern Russia, 2007 for the
Eastern Mediterranean, and 2000 and 2001 for theBalkan countries. We identiﬁed the wettest year
(maximum SPEI03) as 2003 for the grassland steppesin Eastern Europe (Fig. 4b and c). When comparing
these maps with the highest ﬁre years from GFED3, theyear 2001 did not appear to be extremely dry, although
it was an intense ﬁre year. However, the dry years 2005
and 2007 were identiﬁed as intense ﬁre years in
Portugal and the Eastern Mediterranean, respectively.
We particularly focused on high-biomass forested
ecosystems potentially leading to high particulate
emissions. We cross-tabulated annual anomalies ofburned area occurring in forests (by combining
GFED3 and the tree cover map) with summer SPEI03
anomalies. We observed that signiﬁcantly more burned
areas occur during drier years (negative SPEI03; Tukey
test, P , 0.05) compared to average (SPEI03 around 0)
or wetter (SPEI03 . 0) years (Fig. 4d). This is a genericpattern observed worldwide (Hessl et al. 2004, Xiao
and Zhuang 2007). Since forest ﬁre activity wascorrelated with summer drought, the temporal trendof summer SPEI03 was tested over the CEZ (Fig. 4a).
A signiﬁcant negative trend (Mann-Kendall Test, P ,0.1) was observed for the recent years (signiﬁcant

FIG. 2. Annual land-surface air temperature (8C) and precipitation (mm) between 1900 and 2100 in Chernobyl and Belarus. The
GCMs adopted here are from the modeling groups of the Canadian Center for Climate Modeling and Analysis (CCCMA); theCSIRO atmospheric research (CSIRO); the U.S. Department of Commerce, NOAA, Geophysical Fluid Dynamics Laboratory(GFDL); the NASA Goddard Institute for Space Studies (GISS); the Institut Pierre et Simon Laplace (IPSL); the Meteorological
Institute of the University of Bonn (MIUB); the Max Planck Institute for Meteorology (MPI); the National Centre for
Atmospheric Research (NCAR); and the Hadley Centre for Climate Prediction and Research, Met Ofﬁce (UKMO).

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FIG. 4. (a) Summer SPEI03 (standardized precipitation–evapotranspiration index) time series for the 1900–2010 period in
Chernobyl, Ukraine (black line). Annual P values (Mann-Kendall trend test) for the SPEI03 trend between 1969 and 2009 are alsopresented (dark gray, dashed line) with the 0.1 threshold (light gray, dashed line) and their respective linear interpolation (graylines). Maps of European (b) minimum and (c) maximum summer SPEI03 years based on the SPEI03 months time frame forFebruary 2015

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trends until 2009, Fig. 4a), indicating that the summer
periods became drier over time and suggesting an
increasing trend in forest ﬁre risk.
Fire activity and land cover
Accurate quantiﬁcation of carbon and particulates
emitted during ﬁre events is signiﬁcantly enhanced whenland-cover types affected by ﬁres are characterized. The
presence of continuous and homogeneous patches is a
key variable that allows ﬁres to spread over large areas
during extreme events (Cary et al. 2006). We exploredthe relationship between ﬁre occurrence and land coverin Europe by using the tree cover map for Europe(Appendix: Fig. A1).
Fig. 5a illustrates the relationship between burned
area and tree cover at the continental level. We
observed that the largest burned area occurred inregions with tree cover less than 60%, mostly in thegrassland steppes of Eastern Europe. However, although the mean burned area was low when tree coverexceeded 60%, the 95th percentile remained high forthese areas. This ﬁnding indicated that large ﬁres mightoccur over densely forested regions (potentially leading
to extreme TC and TPM emissions, Appendix: Fig. A3)
when fuel amounts and tree cover are high, although
the average burned area appeared to be much lower.
The continental-level distribution of the probability ofﬁres to spread into dense forests was calculated bymultiplying burned area by tree cover (Fig. 5b).
Eastern Europe and Portugal were found to be theareas that were more prone to create ﬁres in dense
forests, including the contaminated forests of Ukraine
and Belarus, potentially leading to high particulate
emissions.
Because extreme forest ﬁres also depend on thehomogeneity and continuity of forest patches in orderto spread, we computed largest patch index (LPI) andmean patch area (MPA) (Fig. 6a and b). The LPI
identiﬁes the percentage of area of a grid cell wherecontiguous forest pixels are aggregated into a single
patch that could potentially spread a ﬁre without any
fuel breaks. MPA identiﬁes the average size of forest
patches, including LPI and other isolated forest patches.
Boreal forests appeared as the most uniform forest areas
for both indices, whereas forests in Southern Europe
were more fragmented. However, large forest patchesremain in Southern Europe, particularly around theMediterranean basin and the mountainous areas. Whenlandscape indices with burned area (BA) were combined(Fig. 6c and d) to gauge the probability of a ﬁrespreading over large forest patches, we observed that
Portugal and Ukraine were at the highest risk when
considering LPI, and the temperate/boreal forests of

FIG. 5. (a) Box plot representing mean (center line),
standard deviation (box edges), 95th percentile (whiskers),
and outlier events (open circles) of burned areas (GFED3;
measured in hectares) as a function of percent tree cover(Kempeeners et al. 2012). In general, burned areas were smaller
in areas with high tree cover (pushing the median close to zero),
although a few extreme events were recorded at high tree cover.
These rare events, however, emitted a large amount of smokewith respect to the biomass consumed. (b) Forest ﬁre risk as aresult of a combination of burned area (BA, GFED3) and tree
cover (data from Kempeeners et al. 2012) (calculated aspercentage burned per hectare of tree cover). Large ﬁres indense forests are likely to happen in Ukraine and Portugal. The
white square represents the area of our interest in Chernobyl
and Belarus.

September from Vicente Serrano et al. (2012). (d) Box plot representing mean (center line), standard deviation (box edges), 95th
percentile (whiskers), and outlier events (open circles) of burned area for the period 1997–2008 over Chernobyl vs. summer SPEI03
anomalies. Signiﬁcantly higher burned areas occur during drier years (negative SPEI03).

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FIG. 6. Landscape analysis of forest patches based on a forest map derived from the Kempeeners et al. (2011) tree-cover map
with a threshold of 50%. (a) Largest patch index (LPI, percentage of the grid cell) and (b) mean patch area (MPA, ha) arerepresented with their respective ﬁre risks (c) LPI 3 BA (% per ha) and (d) MPA 3 BA (ha2). The white (black in panel [b]) squares
represent the area of our interest in Chernobyl and Belarus.

Russia were at the highest risk when considering MPA.
This analysis indicated that Mediterranean and Eastern
European forests, including Ukrainian and Belarusian
forests, are highly prone to extremely large ﬁre events
that could produce large emissions of deposited radionuclides.
Since homogeneous landscape patterns (able to carrylarge ﬁres) were found to contribute signiﬁcantly tohigher ﬁre risk, changes in forest cover and in turnlandscape structure within the ChNPP were assessed.
Because the Chernobyl area has been protected fromhuman activities since 1986, we expected that land-coverchanges, including forest expansion or shrubby encroachment, would have happened in the last 25 years.
To test this hypothesis, we analyzed and reclassiﬁed two
Landsat images from winter 1987 and winter 2010 inwhich snow covered the ground but the canopy of trees;
hence contrasts between croplands/grasslands and forests were highly visible and we could easily classify land
cover as forested and non-forested. Fig. A4a in the
Appendix represents land-cover changes between 1987
and 2010; we observed forest expansion north and west

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61

FIG. 7. Litter carbon stock for the period 1986–2010 centered in the Ukrainian (Chernobyl) and Belarusian contaminatedforests.

of the ChNPP (þ25%), characterized by a concomitant
10% increase in forest cover. This observation conﬁrmed
our hypothesis that forests were becoming less fragmented and thus potentially more capable of spreadinglarge wildﬁres. Our local analysis was consistent with therecent analysis of global land-cover change by Hansen etal. (2013; Appendix: Fig. A4b), in which forest increase
was the dominant pattern in the ChNPP exclusion zone
during 2000–2012.
Biomass burning and litter carbon storage
Fig. A5 in the Appendix depicts biomass burning
estimated by the PKU-FUEL model of Peking University for the years 1986 and 2007 in Europe. The year
1986 was chosen as a reference period just after theaccident to show the large variability of the biomass
consumption between the period of the accident and thepresent. Dancause et al. (2010) noted that a majority ofpeople living in contaminated areas in Ukraine habitually burn stalks of potatoes during August–October,increasing the surface concentration of 137Cs by almost afactor of 10. Moreover, most households outside cities
are heated with ﬁrewood (77% of respondents in Rivne
Oblast), and cooking is often done on wood-burning
stoves (52%). Hence, the consumption of ﬁrewood has
increased by a factor of 16 (0.02–0.33 kgm2yr1) incontaminated regions two decades after the Chernobyl
disaster. Consumption of straw has also increased from0.01 to 0.06 kgm2yr1, especially in Belarus. Farmers
also light ﬁres in their ﬁelds to burn weeds, potato stems,
and other plant material; such ﬁres can lead touncontrolled forest ﬁres. However, the MODIS active
ﬁres product showed no increase in agricultural ﬁres up
to 2007 because so few people live inside the contaminated areas of Ukraine and Belarus. Most ﬁres in theseareas were attributable to natural causes such as
lightning.

The LPJmL-SPITFIRE model was used to estimate
the variation of litter carbon stock in Europe since 1986.
Litter carbon storage was plotted for the contaminatedforests in Ukraine and Belarus (Fig. 7). Two main peaks
in litter carbon stock were distinguished in Chernobyl,
one in 1992 and the second in 2002, when litter carbon
storage reached 2400g C/m2. Litter carbon stock in
Chernobyl has doubled since 1986 (particularly after
2000), which is likely due to the lack of any forest
management in the area. Similar results were found forthe forests of Belarus, with lower carbon stocks ingeneral. The increase in accumulation was more
pronounced in recent years with a notable peak in2010 (1200–1850 g Cm2yr1). These carbon stocks arevery high compared to those observed elsewhere. For
example, Averti and Dominique (2011) reported thatlitter carbon stock rates range between 1063 and 1824 g
Cm2yr1 in Central Africa, whereas Raich et al.
(2006) reported litter carbon stock rates in tropicalforests as 700 g Cm2yr1. However, those numbers areproducts of the rate of decomposition through heterotrophic respiration. In cold environments, reduced soil
respiration leads to a build-up of carbon, in contrast to
the fast-cycling tropics. Therefore, the most suitablecomparison was with the data of Covington (1981),
which is 1600 g Cm2yr1 for boreal forests generally;
litter carbon stocks estimated for Ukrainian andBelarusian forests were thus relatively high.
A recent study of litter decomposition and storage in
Chernobyl, however, suggests that our estimates of litter
carbon stock are likely to be lower than those actuallyobserved (Mousseau et al. 2014). The stock of litter
carbon is a function of the annual amount of plantbiomass in litterfall, minus the annual rate of decomposition. Litter mass is also inﬂuenced by the timing andtypes of disturbance inﬂuencing the forest. During theearly stages of stand development, litter increases

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FIG. 8. Examples of 137Cs emissions in the contaminated forests of Belarus and Ukraine after ﬁre events in 2002, 2008, and2010, as well as following the three different ﬁre scenarios (2010 scenario 6, 2010 scenario 7, and 2010 scenario 8). The white boxes
denote the location of the radioactive forests of Chernobyl (Ukraine) and Belarus.

rapidly. Management such as timber harvesting, slashburning, and site preparation dramatically alter litter
properties (Fisher and Binkley 2000), but few studies
clearly document the effects of management on litter
carbon storage (Smith and Heath 2002).
Transport and deposition of 137Cs after ﬁres
Fires in Ukraine and Belarus were simulated for theyears 2002, 2008, and 2010 using the LMDZORINCA
model. MODIS satellite imagery recorded 185 ﬁres in

2002, 50 in 2008, and 54 in 2010 that burned 473, 125,and 137 ha, respectively. The same 54 ﬁre incidents in2010 were used to simulate the three scenarios of ﬁresoccurring in 10% of the contaminated forests (2010
scenario 6, 2010 scenario 7, and 2010 scenario 8). Fig. 8
shows examples of some intense emissions during those
years, in terms of activity concentrations of 137Cs.
Several events in 2002 redistributed and transported
137
Cs over Europe. A major drought and prolonged hightemperatures resulted in unprecedented ﬁres. These ﬁres

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63

FIG. 9. Atmospheric burden of 137Cs (TBq) after the ﬁres in 2002, 2008, and 2010, as well as after the three ﬁre scenarios with
10% of the area being burned (2010 scenario 6, 2010 scenario 7, and 2010 scenario 8). The respective burden from the Chernobyl
accident in 1986 is shown in reference to the levels attained due to the ﬁre events and the scenarios studied.

occurred under extreme ﬁre danger conditions and were
impossible for the authorities to extinguish. These ﬁres
were so serious that peat bogs also burned, followed byforests, causing massive smoke emissions that persisted
for a period of nearly 2 months, sometimes reducing
visibility to below 60 m. These ﬁres resulted in signiﬁcant
exposures of smoke to major population centers such as
Kiev and Moscow. The highest release occurred at theend of July, with 137Cs fallout reaching Sweden,
Finland, and Central Europe (Fig. 8).
Fires in 2008 were of lower intensity and frequency.
However, some took place inside highly contaminatedregions, injecting a signiﬁcant plume into the atmosphere. In March 2008, 137Cs covered Belarus and alarge part of Russia (Fig. 8), and another event inAugust distributed 137Cs more locally (data not shown).
Wildﬁres in 2010 affected several countries ofSouthern Europe, including the Balkan countries,
Turkey, and southern Italy (Fig. 8). The same raging
forest ﬁres affected ;3900 ha locally in the fallout zone
from the 1986 disaster. Despite the observed transport,
it is noteworthy that the atmospheric activity concentrations of 137Cs remained low (1–5 mBq/m3).
The highest exposure to the radioactive cloud fromthe 2002, 2008, and 2010 ﬁres occurred over Central
Europe (Fig. 8), with an annual average air activity
concentration of 137Cs ranging from 17 to 120 mBq/m3,
whereas the maximum displacement of 137Cs wasestimated to be only four orders of magnitude lower
than the initial total deposition in 1986 (85 PBq; De
Cort et al. 1998). In the three scenarios (2010 scenario 6,
2010 scenario 7, and 2010 scenario 8), 10% of thecontaminated forests in Chernobyl and Belarus wereburned (using the temporal pattern of 2010 wildﬁres, as
recorded from MODIS and accounting for a maximum
injection height of 2.9, 4.3, and 6.0 km, respectively). As
the altitude of the release increased, the plume spreadand therefore covered a larger surface area (Fig. 8).
Nevertheless, the transport was not signiﬁcantly different whether 137Cs was released at 2.9 or 6.0 km, likely
because we accounted for a small emission factor of137
Cs after ﬁres (40%) and/or because the highest
releases occurred during summer when surface winds
are relatively weak and do not favor advection. Fig. 9
depicts the atmospheric burden of 137Cs as a time series
for the simulated period (March to December), andindicates that if ﬁres burned 10% of the areas, anenormous amount of 137Cs would be released. In 2002,
when according to MODIS, intense ﬁres were burning
for almost two months inside highly contaminatedareas, ﬁre emissions fell within the same range as the
scenarios (that is, more than 8% of 137Cs remaining from
Chernobyl was released). Differences in the amount of137
Cs that remained in the ambient aerosol and was
ﬁnally transported for longer time periods were due tothe different injection heights used in each scenario. The
lifetime of 137Cs in the atmosphere was calculated as ;5days, which conforms with many other studies.
The deposition of 137Cs was larger in 2002 comparedto the other years (2008 and 2010). 137Cs migrated to thesouth, affecting the Kiev metropolitan area as well as
Romania and Bulgaria (Fig. 10), although the concentrations were low and likely presented a small radiological hazard. The trend of 137Cs migration to the south
has been veriﬁed by measurements of soil concentrations
in Ukraine during the last 25 years presented in the atlasof radioactive contamination of Ukraine (NRU 2011).
Aside from ﬁres, horizontal migration of 137Cs may
occur due to rain, snow melt, and human activities
including trafﬁc, street washing, and cleanup, in whichradionuclides are washed from surfaces and transported
within settlements, some being removed with litter andsewage. One of the consequences of these processes has
been secondary contamination of sewage systems and64

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FIG. 10. Deposition of 137Cs (wet and dry) after ﬁres in 2002, 2008, and 2010 in Ukraine and Belarus, as well as during the three
scenarios studied (2010 scenario 6, 2010 scenario 7, and 2010 scenario 8). Values present cumulative deposition of 137Cs integrated
to the end of each of the studied years. The white boxes denote the location of the radioactive forests of Chernobyl (Ukraine) andBelarus.

sludge storage, which necessitates special cleanup
measures.
In general, 137Cs has not been transferred at large
concentrations to large urban areas yet. Our simulations
showed that 32.2, 7.2, and 9.6 kBq/m2 of 137Cs were
deposited after the ﬁres in 2002, 2008, and 2010,
respectively, whereas the three scenarios predicted that
.40 kBq/m2 of 137Cs would be deposited over Europe.

The maximum atmospheric dispersion of 137Cs after all
the simulations corresponded to almost 8% of what has
been deposited on the area after the Chernobyl accident,
corrected with an effective half-life of 10 years to 1
March of the years studied and almost 0.1% of the core
inventory of Reactor 4 of ChNPP that exploded on 26
April 1986. Thus, deposition would contribute 1–10 lSv/
yr to the total effective dose of an inhabitant in Kiev.

February 2015

FIRE EVOLUTION IN RADIOACTIVE FORESTSDISCUSSION
Several models, together with remote-sensing data
and direct observations, are employed here for the ﬁrst
time to provide the ﬁrst realistic analyses of past andpresent trends and risks of forest ﬁres in the radioactively contaminated forests of Ukraine and Belarus. We
also issue future predictions of ﬁre incidents. The results
show that temperatures in the contaminated forests are
expected to increase in the future, whereas precipitation
will remain the same or decrease slightly. These changes
have important policy implications for the risk of ﬁreand for ﬁre management.
Roles of vegetation in promoting the risk of ﬁreWorldwide, somewhere between 75 and 820 million
hectares of land burn each year, depending on the year.
Wildﬁres (not including ﬁres intentionally set to clear
land) consume some 3–8% of total terrestrial net
primary productivity annually, releasing on average
1.7–4.1 Gt of carbon into the atmosphere (van derWerf et al. 2010). There is a growing realization thatclimate change may be associated with increasing forest
ﬁre size, frequency, and severity (in terms of thenumber of trees killed) across boreal and sub-boreal
regions (Westerling et al. 2006, Williams et al. 2013),
despite widespread management practices aimed at
reducing ﬂammable materials in forests. Climate
models predict that higher temperatures and longer
droughts will increase wildﬁre frequency, particularly
in semiarid regions. Fig. 2 shows that temperature willcontinue to increase in coming years in Chernobyl andBelarus, and the average annual air temperature will
have reached 148C by 2100. Higher rainfall in someareas could reduce ﬁre frequency, though it could also
foster more vegetation, thus providing more fuel forﬁres. Lightning (an important ignition source) isthought to increase with a warmer climate, and more
intense rainstorms could exacerbate post-ﬁre runoff
and landslides.
Warming trends also may already be contributing
to increasing stress on boreal forests such as thosethat predominate in the Chernobyl region. Warming
can increase tree stress by increasing water deﬁcit andthus drought stress on trees (McDowell et al. 2008)
and/or enhancing the growth and reproduction of
insects and pathogens that attack trees (Raffa et al.
2008). Indeed, a major insect outbreak occurred in
Chernobyl in summer 2011, leaving a large swath offorest with completely defoliated trees. Recent episodes of forest dieback (Breshears et al. 2005,
Williams et al. 2013) and rising tree mortality rates
in otherwise undisturbed forests (van Mantgem andStephenson 2007) may also be due to stress fromwarming climate. Trees subject to chronic water and/or temperature stress are more sensitive to subsequentﬁre damage (van Mantgem et al. 2003), implying thatrecent warming trends may lead to a de facto increase65

in ﬁre severity, apart from changes that may increaseﬁre intensity.
Vegetation type distribution, interannual variation inamount of fuel and fuel moisture content, andlandscape patterns affect fuel continuity and thecapacity of a ﬁre to crown and spread. We exploredthese constraints and their trends throughout Europe
and at local scales in Chernobyl and Belarus. The
relationship between extreme ﬁre years and increasing
frequencies of summer drought will potentially result inlarger burned areas. Grassland ﬁelds appear to be themost ﬁre-prone areas in Europe. When burned area is
combined with tree cover, the Mediterranean andEastern Europe (including the contaminated forests in
Ukraine and Belarus) emerge as the major regions with
forests threatened by ﬁres. Extreme ﬁre events are likely
to occur over large, contiguous forest patches; sincethese regions exhibit both high ﬁre occurrence andlarge forest patches, we conclude that extreme ﬁre
events will likely occur there. These forests extend up to
the interface between large boreal forests (which showlow ﬁre activity due to limited drought) and up to
fragmented, ﬁre-prone areas of Southern Europe(which show lower risks of large ﬁres). Local-scale
analysis illustrated the signiﬁcant forest cover gains
around the ChNPP since 1986, suggesting an increasing
continuity in forest patches and, in turn, higher ﬁrerisk.
Accumulation and loss of carbon litter stocks
In boreal forests generally, the rate of decompositionis slower and leads to the accumulation of a thick litter
layer, also known as a mor (Schlesinger 1997). Anothersource of variability of litter storage is caused by treemortality. Widespread forest dieback due to increasing
drought or heat stress as well as post-ﬁre mortality canlead to short-term carbon inputs to the litter pool thatexceed annual inputs from leaf and root turnover. Thisis exactly what the LPJmL-SPITFIRE predicts for the
Chernobyl and Belarusian forests shown in Fig. A6 ofthe Appendix. Litter carbon stock in the contaminatedforests has increased since 1986, with a major peak in2010 due to the lack of forest management. Thereafter,
carbon litter stocks in Belarus and Ukraine decrease tohalf by 2030 (compared to 2010), interrupted by a rapid
peak in 2035, whereas average litter carbon in Europe(as a whole) remains at the same level (Fig. 11).
However, the situation in the contaminated areaschanges after 2060, when litter carbon storage in
Belarus reaches a maximum after having increasedaround 2.5 times since 1986 (Fig. 7 and Appendix: Fig.
A6). The same trend is observed in Chernobyl, withlitter carbon increasing by a factor of 2 after 1986
reaching the 2010 values (;2400 g C/m2). According to
the LPJmL-SPITFIRE model, litter carbon stocks in
Chernobyl and Belarus gradually decrease again after
2070, as they are probably consumed by increasing

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FIG. 11. Litter carbon stock over Europe 1986–2100 based on the future prediction of the LPJmL-SPITFIRE model. White
rectangle denotes the contaminated forests in Ukraine and Belarus.

numbers of ﬁres during the same period (Appendix:
Fig. A6).
These effects may be further exacerbated in contaminated regions by the inﬂuence of radiation on decomposition and tree growth in the Chernobyl region(Mousseau et al. 2013, 2014). Radioactive contamination impedes decomposition rates of organic matter due
to its negative effects on soil biota. Backgroundradioactivity has reduced the rate of decomposition ofplant material in large areas around Chernobyl (Fig. 12).
When leaf litter collected in uncontaminated areas, farsouth of the exclusion zone, is placed inside highly
contaminated areas, the decomposition rate in contaminated areas is only one-half of that recorded for similartypes of leaf litter in control areas (Mousseau et al.
2014). As a consequence, the litter layer in the mostcontaminated areas is now four times thicker than thatin the least contaminated areas around Chernobyl(Mousseau et al. 2014). The predicted litter carbon
stock likely signiﬁcantly underestimates the potential
hazards related to litter amount in these forests. Clearly,
such large differences in the amount of dead plantmaterial can have radical consequences for the risk of
ﬁre and the magnitude of ﬁres once an ignition has
occurred.
Surface detritus facilitates the capture and inﬁltrationof rainwater into lower soil layers and its removal by ﬁreaccelerates soil erosion (Chanasyk et al. 2003). In
addition, soil litter reduces wind erosion by preventing
soil from losing moisture and providing cover preventing soil transportation. Organic matter accumulation
also helps to protect soils from wildﬁre damage.
Standing vegetation can be severely reduced and soil
litter almost completely removed depending on theFebruary 2015

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67

FIG. 12. Proportional loss (decomposition) of leaf litter from leaf litter bags containing uncontaminated leaf litter and placed in
the litter layer at 20 different sites around Chernobyl during a nine-month period in relation to background radiation level (note log
scale of x-axis).

intensity and severity of wildﬁres and season (Ice et al.
2004).
Radionuclide releases from ﬁres
The largest radionuclide release to date occurred in
2002, when ﬁres in contaminated regions burned foralmost 2 months. However, low radionuclide concentrations were recorded (on the order of 1–5 mBq/m3),
and mostly affected the local population. It seems that137
Cs migrates to the south with time as a result of ﬁres,
washout, and human activities. The amount of 137Cs
redeposited over Europe has been equivalent to 8% ofwhat was deposited following the initial disaster, whichis relatively low compared to the total amount of 137Cs
available in these forests.
It should be stated here that 137Cs redistribution is
not the only problem after a ﬁre event in the Ukrainianand Belarusian forests. Thirteen of 19 radionuclides,
released in the range of PBq in 1986, exhibit half-lives
from a few days to 2 years, meaning that they havebeen lost due to decay. However, of the remaining
radionuclides, four of six are refractory, long-lived
elements (238–240Pu and traces of 241Am) that have been‘‘trapped’’ in the CEZ, whereas the other two (137Cs
and 90Sr) are volatile elements with half-lives of about
29 and 30 years. According to measurements (NRU
2011) and our simulations (assuming an effective halflife of 10 years), we estimate that 2–8 PBq of 137Cs and
1– 4 PBq of 90Sr still remain in the contaminated areasof Ukraine and Belarus, whereas the rest (238–240Pu andtraces of 241Am) are in the order of TBq. In addition,
approximately one-quarter of the total amount ofradionuclides from Chernobyl was deposited in south-

western Russia next to the Ukrainian-Belarusianborders. These parts of Russia have similar habitats
and climate to the contaminated forests of Ukraine andBelarus. However, for logistical reasons, we wereunable to obtain sufﬁciently detailed information for
Russia. Hence, the magnitude of the effects that wehave documented here clearly underestimates the
combined effects predicted for all contaminated areas.
Fireﬁghting and policy changes in contaminated forests
Increased ﬁre risk in these forests and the subsequent
release of radionuclides are exacerbated by the lack of
ﬁreﬁghting infrastructure in the contaminated zone.
Despite political pronouncements, a lack of ﬁnancial
resources impedes the implementation of policies thathave been adopted to date. Although some promisingactions have been introduced by international organizations, renewal of the ﬁre crew and modernization of
the ﬁreﬁghting equipment are both required to combat
the risk of a major ﬁre event.
Since 1991, when the Ukrainian Law ‘‘About legal
status of the territory that was contaminated byradionuclides as a result of the Chernobyl disaster’’
was adopted by the Parliament of Ukraine, the main
objective of the ﬁre policy has been to keep theterritory in ‘‘ﬁre safe condition.’’ Fire prevention wasrecently emphasized as a priority in the Order of the
Cabinet of Ministers of Ukraine (p. 535, 18.07.2012,‘‘Concept of implementation of state policy in a sphereof development of activity in certain zones ofradioactive contamination due to Chernobyl catastrophe’’).

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Ecological MonographsVol. 85, No. 1

FIG. 13. Wildﬁre history in the Chernobyl Exclusion Zone (CEZ).

With an emphasis on prevention, ﬁreﬁghting capacities have not been given enough attention in the area.
During 1986–1992, professional ﬁreﬁghters at the
Chernobyl Fire Station were responsible for forest
ﬁreﬁghting; however, in practice, this staff was mainly
trained for suppressing infrastructural ﬁres, not wildﬁres. The absence of the basic components of forest ﬁremanagement in CEZ, such as prevention, ﬁre detection,
early warning, and a cogent ﬁre management plan, led toa series of catastrophic wildﬁres in August 1992 thatburned ;17 000 ha of contaminated land, including
5000 ha due to a massive crown ﬁre in Opachichi forest
district. As a result, a special forestry enterprise,
Chornobyl Forest, was established in the CEZ in 1992,
with 600 professional forestry staff focused on implementing a forest ﬁre management system.
Despite some success in terms of preventing catastrophic ﬁres during 1993–2010, ﬁre risk and ﬁre hazard
have been increasing steadily in the CEZ. Ignition
sources are present throughout the territory of the CEZ
during the entire ﬁre season as construction of thesecond sarcophagus proceeds and returning villagers,
CEZ staff, and illegal visitors conduct agricultural
burns. According to ofﬁcial statistics, ;1100 small andmedium size wildﬁres occurred during 1993–2010 in
CEZ, including the most contaminated zones (Zibtsev etal. 2011) (Fig. 13).

Fire management has deteriorated during the past
decade due to a dearth of funding and the attendantlack of speciﬁc policy laws and administrative efforts.
Chornobyl Forest staff, including ﬁreﬁghters, has been
cut by almost 40% over the past two decades. The
existing ﬁre detection system, consisting of six lookout
towers, covers only 30–40% of the CEZ, and half of
the wildﬁres usually occur outside its detection radius(Fig. 13). Most of the heavy ﬁreﬁghting equipment is
at least 10 years old, outdated, and not reliable indealing with ﬁre emergencies. The number of ﬁrestations (four), ﬁre crews, and engines per 1000 ha offorest are six to seven times fewer than those of normal
forest stations in Ukraine outside of the CEZ (Fig.
14). Only ;20–30% of the required prevention
measures in the CEZ are executed annually due tolack of funding and the dramatic reduction of theforest road network available for ﬁre engines. Thus,
there are many parts of the CEZ that are practicallyunreachable by ﬁreﬁghters.
Steps forward to improve forest safety should startwith the employment of ﬁre crew personnel who will
execute the prevention measures and take part in the
ﬁreﬁghting process. In reaction to the current situationand the subsequent concern of international organizations (e.g., the United Nations, U.S. Forest Service,
and Organization for Security and Co-operation inFebruary 2015

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69

FIG. 14. Zones with different response times needed for ﬁre crews to reach certain parts of CEZ in case of ﬁre. Lack of forest
roads can delay responses. The four black buildings north, south, west, and east denote the available ﬁre stations; the whitebuildings denote ﬁre observatories. Shades of gray denote response time to access each forest area within CEZ.

Europe), the Government of Ukraine, UNEP (United
Nations Environment Program), and other donors
have recently initiated measures to improve thesituation and decrease ﬁre risk by developing a ﬁremanagement plan and installing a video surveillancesystem that will cover the CEZ and neighboring
territories outside of the zone. This system is expected
to enable specialists to detect ﬁres on monitors undersafe radiological conditions, to conduct ﬁre risk
assessments, and to develop and run ﬁre behavior
models. Finally, early warning systems will be installed
in order to inform the personnel of high radiationlevels, thus preventing unnecessary exposure to radioactive contaminants.
ACKNOWLEDGMENTS
The authors are greatly appreciative of funding from the
project GIS Climat-Environnement-Société, which supported
the workshop entitled ‘‘Role of ﬁre ignition in climate change
and its relation to the redistribution of atmospheric constituents’’ (CNRS Campus, Gif-sur-Yvette, France, 23–26 October2012). During this workshop, international experts on ﬁremodeling, radioecology, and atmospheric science (the authorsof the present paper) were gathered and discussed how tofurther develop and improve their models. The feedback of thisworkshop is incorporated into this paper. J. W. Kaiser was
funded by the European Commission through the FP7 project
MACC-II, contract number 283576.

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SUPPLEMENTAL MATERIAL
Ecological Archives
The Appendix is available online: http://dx.doi.org/10.1890/14-1227.1.sm
Data Availability
Data associated with this paper have been deposited in Dryad: http://dx.doi.org/10.5061/dryad.33mn2