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ORIGINAL ARTICLE
Short-term effects of particulate matter on mortality
during forest fires in Southern Europe: results of the
MED-PARTICLES Project
Annunziata Faustini,
1
Ester R Alessandrini,
1
Jorge Pey,
1,2,3
Noemi Perez,
2
Evangelia Samoli,
4
Xavier Querol,
2
Ennio Cadum,
5
Cinzia Perrino,
6
Bart Ostro,
7
Andrea Ranzi,
8
Jordi Sunyer,
7
Massimo Stafoggia,
1
Francesco Forastiere,
1
the MED-PARTICLES study group
▸Additional material is
published online only. To view
please visit the journal online
(http://dx.doi.org/10.1136/
oemed-2014-102459).
For numbered affiliations see
end of article.
Correspondence to
Dr Annunziata Faustini,
Department of Epidemiology,
Regional Health Service of
Lazio, via Santa Costanza,
53, Rome 00198, Italy;
a.faustini@deplazio.it.
Received 17 July 2014
Revised 16 January 2015
Accepted 27 January 2015
To cite: Faustini A,
Alessandrini ER, Pey J, et al.
Occup Environ Med
Published Online First:
[please include Day Month
Year] doi:10.1136/oemed-
2014-102459
ABSTRACT
Background An association between occurrence of
wildfires and mortality in the exposed population has
been observed in several studies with controversial results
for cause-specific mortality. In the Mediterranean area,
forest fires usually occur during spring–summer, they
overlap with Saharan outbreaks, are associated with
increased temperature and their health effects are
probably due to an increase in particulate matter.
Aim and methods We analysed the effects of wildfires
and particulate matter (PM
10
) on mortality in 10 southern
European cities in Spain, France, Italy and Greece
(2003–2010), using satellite data for exposure
assessment and Poisson regression models, simulating a
case-crossover approach.
Results We found that smoky days were associated with
increased cardiovascular mortality (lag 0–5, 6.29%, 95%
CIs 1.00 to 11.85). When the effect of PM
10
(per
10 mg/m
3
) was evaluated, there was an increase in
natural mortality (0.49%), cardiovascular mortality
(0.65%) and respiratory mortality (2.13%) on smoke-free
days, but PM
10
-related mortality was higher on smoky
days (natural mortality up to 1.10% and respiratory
mortality up to 3.90%) with a suggestion of effect
modification for cardiovascular mortality (3.42%, p value
for effect modification 0.055), controlling for Saharan
dust advections.
Conclusions Smoke is associated with increased
cardiovascular mortality in urban residents, and PM
10
on smoky days has a larger effect on cardiovascular and
respiratory mortality than on other days.
INTRODUCTION
Forest fires contribute to the earth’s planetary con-
centrations of organic carbon (OC) and elemental
carbon (EC).
1
In Mediterranean countries, carbon-
aceous compound emissions from wildfires are made
up of 71% carbon dioxide (CO
2
), 26% carbon mon-
oxide (CO) and 0.3% total particulate carbon.
2
Secondary aerosols may contribute greatly to
increases in carbonaceous particulate matter (PM),
since the large amounts of volatile organic com-
pounds (VOCs) released during forest fires
3
may be
converted into carbonaceous PM by anthropogenic
agents, such as NO
x
and O
3.4
In addition, a number
of polycyclic aromatic hydrocarbons arise from
imperfect combustion of biomass.
5
Exposure to emissions from forest fires is spor-
adic and short lasting; it entails high levels of
combustion-related pollutants and is usually asso-
ciated with high ambient temperature.
67
In the
Mediterranean area, wildfires occur mainly during
warm seasons, in high ambient temperatures, and
are often concurrent with Saharan dust outbreaks.
8
Climatic conditions, including precipitation, winds
and boundary layer height, may influence the
occurrence of fires and exposure to the resulting air
pollutants. All of these issues make it difficult to
assess human exposure to forest fire emissions.
The assessment of human exposure to fires also
presents operational difficulties since the surveil-
lance of fire events is currently the responsibility of
the fire department: they record dates, locations,
durations and extent of burnt areas, but not infor-
mation about proximity and size of the populated
areas affected, which could be relevant when asses-
sing exposure. Satellite data and dispersion models
provide qualitative information about the spatial
extent of wildfires; they also allow a rough estimate
of the contribution of the fire to the ambient con-
centrations of particles, but they do not assess
What is already known
▸Increase in natural mortality occur on forest fire
days.
▸In Europe, forest fires usually occur during the
hot season, are associated with increased
temperature and dust outbreaks and their
health effects are probably due to an increase
in particulate matter (PM).
What this paper adds
▸Mortality for cardiovascular causes increases in
cities during smoky days.
▸PM
10
-related cardiovascular mortality is
modified during smoky days.
▸PM
10
-related respiratory mortality increases on
smoky days.
Faustini A, et al.Occup Environ Med 2015;0:1–7. doi:10.1136/oemed-2014-102459 1
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concentrations at ground level. On the other hand, fixed moni-
tors located in large cities monitor pollutants from anthropo-
genic sources, such as road traffic, domestic heating, shipping,
industries and power generation. Therefore, routine air quality
surveillance may fail to represent the atmospheric pollution
resulting from forest fires,
9
while rural monitors are often
sparse or unavailable in regions affected by fires.
10
A few studies have reported increases in commonly monitored
ambient pollutants, such as fine particles (PM
2.5
), carbon mon-
oxide (CO), sulfur dioxide (SO
2
), ozone (O
3
) and black carbon
(BC), as possible indirect indicators of exposure to fires in urban
areas.
10–12
Levoglucosan is the typical indicator of biomass-
burning emissions
13
and is a well-known biomarker of fire
exposure.
14
Soluble potassium has also been used as a biomass-
burning tracer.
15
Currently, however, experience with these indi-
cators to assess wildfires exposure is very limited.
The health effects of wildfires are probably due to PM (fine
and ultrafine), but may also owe to other combustion-related
factors such as inorganic gases and VOCs, and even the tem-
perature increases generated by nearby fires.
67
Mortality is an
important potential outcome of this exposure,
916–19
in addition
to respiratory symptoms,
20
exacerbations of pre-existing dis-
eases
21–24
and cardiovascular effects.
25 26
As part of the MED-PARTICLES project funded by the
European Union under the LIFE+ framework, we studied the
short-term effects of forest fire smoke and PM on the mortality
of the population living in large cities in southern Mediterranean
Europe. Exposure to fires was defined using satellite observa-
tions, and it was confirmed against daily changes in temperature
and concentrations of fire-related pollutants.
MATERIALS AND METHODS
The study included the cities that took part in the MED-
PARTICLES LIFE+ project, namely Madrid and Barcelona in
Spain; Marseille in France; Turin, Milan, Bologna, Parma,
Modena, Reggio Emilia, Rome and Palermo in Italy; and
Thessaloniki and Athens in Greece. Exposure assessment was per-
formed for 9 years (2003–2011) whereas mortality data were col-
lected in each city, for a variable period of 3–8 years, from 2001 to
2010. Data analyses were carried out for the period 2003–2010.
Exposure assessment
Forest fire events were identified on smoke surface concentra-
tion maps supplied by the NAAPS model (Navy Aerosol
Analysis and Prediction System—US Naval Research Laboratory
Marine Meteorology Division, http://www.nrlmry.navy.mil/
aerosol/), which takes into account both the aerosol optical
depth (AOD) from satellite measurements and the fire-related
smoke plumes. Such aerosol maps are initially generated as fore-
cast products, and are thereafter corrected from satellite AOD
measurements. The smoke concentration at surface ranges from
1toover64mg/m
3
; however, the influence of low-magnitude
wildfires cannot be assessed though they may greatly affect an
urban area when they occur nearby. The use of satellite images
helped us to distinguish between smoky days and smoke-free
days, especially when NAAPS outputs diverged in consecutive
days. The fire-related smoke plumes allowed us to assess the
involvement of surrounding cities.
In order to be as conservative as possible, we defined a day as
being ‘fire smoke-affected, or smoky’when smoke concentrations
were higher than 8 mg/m
3
; additionally, fire smoke intensity was
classified for each day as low (smoke concentration between 8
and 16 mg/m
3
), medium (smoke concentration between 16 and
32 mg/m
3
) or severe (smoke concentration above 32 mg/m
3
). An
additional assessment of smoke episodes was made on the basis
of their duration, classifying them as isolated episodes (1-day
duration), short episodes (2–4 consecutive days) and long epi-
sodes (5 or more days, where 1 day without smoke in a sequence
of at least five days did not interrupt the sequence).
Finally, to confirm the fire smoke assessment, smoky days
were classified according to the absolute changes of daily mean
temperature,
27
PM
10
, CO and O
3
levels measured at fixed
monitors in each city. The absolute changes in these factors
during smoke events of different duration and intensity (defined
as a multilevel variable with smoke-free days as reference) were
estimated using linear regression analysis adjusting for time
trend (year) and seasonality (month).
The daily mean levels of PM
10
and the other pollutants were
provided for each of the 13 cities included in the study by their
local monitoring networks.
We also identified the presence of Saharan dust advection and
computed the Saharan dust load on daily PM
10
concentrations.
28
Briefly, the estimate of Saharan dust load was performed by using
a method adopted by the European Commission, employing
data from rural monitors near each city (http://ec.europa.eu/
environment/air/quality/legislation/pdf/sec_2011_0208).
Saharan days were classified as advection days without any
Saharan-related PM increase at ground level, days with a PM
10
load of 1–10 mg/m
3
and days with a PM
10
load of more than
10 mg/m
3
.
Health data
Daily death counts due to natural (International Classification of
Diseases Ninth Edition (ICD-9) codes 001–799 or ICD-10
codes A00-R99, excluding injuries, poisoning and external
causes) and cause-specific mortality (cardiovascular ICD-9 390–
459 or ICD-10 codes I00—I99 and respiratory ICD-9 460–519
or ICD-10 codes J00-J99) were collected from each city, for
all-age residents, from mortality registers. Deceased participants
were considered only if they died in the same city.
Data analysis
We studied the associations of smoky days as assessed by satel-
lite, and PM
10
as measured from fixed monitors at ground level,
with natural, cardiovascular and respiratory mortality, in the
period 2003 and 2010. The effect estimates were obtained for
each city using Poisson regression models, simulating a stratified
case-crossover approach.
29
More specifically, time trends and
seasonality were controlled for by including in the regression
models a triple interaction of year, month and day of the week.
All effect estimates were further adjusted for population
decreases in the summer and during holidays, and influenza
epidemics.
30
Figure 1 illustrates the relationships we assumed between
fires, PM, Saharan dust, temperature and mortality. In evaluating
the association of fire smoke with mortality, we did not adjust
for daily PM
10
, as it is an intermediate factor between fires and
mortality. While when evaluating the association of PM
10
with
mortality, we adjusted for the presence of fires. In a separate
model we also assessed whether PM
10
effects were modified by
wildfires, adding an interaction term between smoky days and
PM levels. The p value for relative effect modification (REM)
31
was used to test the interaction hypothesis. We further adjusted
the estimates of fire smoke and PM
10
effects for temperature
and Saharan dust, since they are risk factors for mortality, and
are associated with the occurrence of forest fires and with PM
10
concentrations. Low temperatures were controlled for with a
penalised cubic spline for 1–6 lagged values of air temperature
2 Faustini A, et al.Occup Environ Med 2015;0:1–7. doi:10.1136/oemed-2014-102459
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below the median value in each city; similarly, high temperatures
were controlled for with a penalised cubic spline for values of
0–1 lagged temperature above the median value at each city.
Saharan dust was controlled for by adding the categorical, three-
level variable specified above in the models.
We explored 6-day lags from 0 to 5 days preceding death for
the association between PM
10
and mortality. We also analysed
cumulative exposure using unconstrained distributed lags.
32 33
For PM
10
we adopted the best lags (0–1 for natural mortality
and 0–5 for cause-specific mortality) previously reported from
MED-PARTICLES.
34
The results were expressed as the percentage
increase in risk (%IR) of natural or cause-specific mortality with
95%CIs. For PM
10
, the effects are per 10 mg/m
3
.
After city-specific analysis, pooled estimates were obtained
from a random-effects meta-analysis for 10 cities (excluding
Parma, Modena and Reggio-Emilia, located in the same region,
where only three fire episodes occurred in 3 years).
Heterogeneity across cities was assessed by χ
2
(Cochran’sQ)
and I
2
tests.
35
Pooled results have been reported for the best
cumulative lag, as identified by the strength of the association
and the lowest heterogeneity.
Finally, we carried out a sensitivity analysis by excluding the
cities where temperature and PM
10
did not increase consistently
with fire smoke concentrations, suggesting a possible misclassifi-
cation of exposure.
RESULTS
The number of smoky days in each city varied, with a total of
391 days affected (2.0% of the studied days). The cities with the
highest number of smoky days were Thessaloniki (6% of days),
Athens (4%), Madrid and Rome (3%) (table 1,figure 2). The
cities most affected by severe smoke were, again, Thessaloniki,
Athens and Rome (table 1). Wildfires were more likely to occur
from April to September (83%) in all cities except Barcelona
(38%; table 1). Thirty-two per cent of smoky days were concur-
rent with Saharan dust outbreaks contributing more than 1 mg/
m
3
of PM
10
at ground level. The largest overlap between smoke
and Saharan dust was observed in Palermo (59% of smoky days),
followed, far away by Rome (39%) and Madrid (37%), in hot as
well as in cold seasons (see online supplementary figure SA).
The daily mean number of natural deaths was 36, across all
cities studied. The daily mean number of cardiovascular deaths
was 13 and the mean number of respiratory deaths was 4 (table 2).
Smoky days were associated with an increase of 1.78% (95%
CI −0.91 to 4.53) in natural mortality (lag 0–1) and of 6.29%
(95% CI 1.00 to 11.85) in cardiovascular mortality (lag 0–5).
No association was observed for respiratory mortality (table 3).
Daily levels of PM
10
(10 mg/m
3
) were associated with natural
mortality (lag 0–1) by 0.53% (95% CI 0.30 to 0.76), cardiovas-
cular mortality by 0.74% (95% CIs to 0.30 to 1.18) and respira-
tory mortality by 1.99% (95% CI 0.80 to 3.20). The results did
not change after adjusting for smoke-affected days (and Saharan
dust). There was an indication that PM
10
-related mortality was
modified by smoke episodes (after controlling for Saharan dust);
the effects of PM
10
on smoky days were higher than on smoke-
free days, amounting to 1.10% for natural mortality, 3.42% for
cardiovascular mortality (with a borderline statistically signifi-
cant effect modification; p-REM=0.055) and 3.90% for respira-
tory mortality (table 3).
Fire smoke intensity and duration were well correlated on the
less affected days (smoke concentration between 8 and 16 mg/m
3
)
but not on the most affected days (smoke concentration above
32 mg/m
3
); 84% of one-day events were mildly affected, whereas
only 23% of 2–4-day events and 45% of 5-or-more-day events
were medium/severely affected. Only 22 days were severely
Figure 1 Direct acyclic graph exploring the effects of forest fires on
Death. The contribution of forest fires on PM concentrations could not
be assessed. The impact of forest fires on temperature could not be
assessed.
Table 1 Smoke-free days and smoke-affected days by season, intensity and length of episodes in 13 cities of the MED-PARTICLES study area
in 2003–2010
City
Study
period
Study
days (N)
No-smoky
days (N)
Smoky
days (N)
Smoky days (N)
by season
Smoky days (N) by
intensity*
Smoky days (N) by length of
episodes
Warm†Cold†Mild Med Severe 1 day 2–4 days 5+ days
Madrid 2003–2009 2557 2490 67 59 8 45 17 5 20 42 5
Barcelona 2003–2010 2922 2875 47 18 29 45 2 0 18 22 7
Marseille 2003–2008 2190 2154 36 28 8 26 9 1 16 12 8
Turin 2006–2010 1826 1812 14 14 0 8 5 1 4 10 0
Milan 2006–2010 1826 1812 14 14 0 8 5 1 4 10 0
Bologna 2006–2010 1826 1812 14 14 0 8 5 1 4 10 0
Emilia-Romagna‡2008–2010 1096 1093 3 3 0 3 0 0
Rome 2005–2010 2191 2137 54 53 1 40 13 1 11 14 29
Thessaloniki 2007–2009 1096 1032 64 53 11 43 16 5 14 13 37
Palermo 2006–2009 1461 1427 34 28 6 28 5 1 8 7 19
Athens 2007–2009 1096 1052 44 42 2 30 8 6 2 16 26
TOTAL 20 087 19 696 391 326 65 284 85 22 101 156 131
*Model estimates according to Navy Aerosol Analysis and Prediction System (NAAPs).
†Warm season=April–September, cold season=October–March.
‡includes three cities (Modena, Parma and Reggio Emilia) in the Emilia Romagna region.
Faustini A, et al.Occup Environ Med 2015;0:1–7. doi:10.1136/oemed-2014-102459 3
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smoke affected, but there were 131 days included in events that
lasted 5 or more days (table 1).
When we estimated the changes of temperature and
combustion-related pollutants according to episode length (see
online supplementary figure SB), we found that mean daily tem-
perature increased by 1.7 C° on smoky days compared to
smoke-free days; it increased by 0.9 C° up to 2.3 C° in the long-
lasting episodes. The average daily concentrations of PM
10
increased by around 7 mg/m
3
on smoky days compared to
smoke-free days, and from 5 to 14 mg/m
3
in summer (data not
shown). CO on smoky days increased by 0.2 mg/m
3
only during
the long-lasting episodes. Similarly, a clear increase in O
3
concentrations (up to 9 mg/m
3
) was observed during long-lasting
smoke episodes (see online supplementary figure SB). When we
estimated the changes in fire-related pollutants by fire smoke
intensity, we found a stronger relationship with PM
10
, and a
weaker relationship with CO and ozone (see online supplemen-
tary figure SB).
After excluding Turin and Milan (where neither temperature
nor PM
10
increased during fire events) from the analysis, the
pooled mortality estimates of PM
10
showed a stronger increase
of respiratory mortality on smoke-affected days than on smoke-
free days, in comparison with the base estimates, which included
the two cities (see online supplementary table SA).
Figure 2 Location, intensity and number of forest fire episodes in the northern Mediterranean area, in the period 2003–2011.
The locations of forest fires are reported in the figure. The cities with fire areas are, from Western to East Europe: Huelva, Madrid, Malaga, Valencia,
Barcelona, Palma de Mallorca, Marseille, northern Italy (Turin, Milan, Bologna), Rome, Cagliari, Napoli/Bari, Palermo, Thessaloniki, Athens, Crete,
Sofia.
Intensity was classified as low (black, for smoke concentration between 8 and 16 mg/m3, medium (light grey) for smoke concentration between 16
and 32 mg/m3 or severe (dark grey) for smoke concentration above 32 mg/m
3
.
The annual mean number of episodes in the location is reported in each circle.
Table 2 Mean number of deaths that occurred on smoke-free days and smoke-affected days by intensity in 13 cities of the MED-PARTICLES
study area in 2003–2010
City
Study
period
Study
days (N)
Natural deaths (daily mean N) Cardiovascular deaths (daily mean N) Respiratory deaths (daily mean N)
All
days
All smoky
days
By smoke
intensity* All
days
All smoky
days
By smoke
intensity* All
days
All smoky
days
By smoke
intensity*
Mild Med-severe Mild Med-severe Mild Med-severe
Madrid 2003–2009 2557 60.1 55.8 55.0 57.4 18.0 16.2 16.0 16.8 9.6 7.8 8.0 7.4
Barcelona 2003–2010 2922 41.7 44.6 44.3 47.0 13.3 13.9 13.8 14.2 4.6 5.2 5.1 5.6
Marseille 2003–2008 2190 21.8 24.7 23.3 28.4 6.7 7.5 7.1 8.5 1.5 1.9 1.7 2.2
Turin 2006–2010 1826 20.5 20.9 20.5 21.3 7.9 8.6 8.6 8.7 1.6 1.6 1.5 1.8
Milan 2006–2010 1826 34.9 33.3 31.5 35.7 12.4 12.1 11.5 12.8 3.0 2.4 2.1 2.7
Bologna 2006–2010 1826 10.6 12.2 11.4 13.3 4.1 5.2 4.4 6.3 1.0 1.1 1.0 1.3
Emilia-Romagna†2008–2010 1096 13.1 12.0 12.0 −5.2 4.0 4.0 −1.0 1.0 1.0 −
Rome 2005–2010 2191 57.9 54.5 53.2 58.1 23.6 21.6 21.9 20.8 3.6 2.9 2.8 3.1
Thessaloniki 2007–2009 1096 17.9 18.7 18.1 20.0 8.3 8.8 8.6 9.2 1.7 1.6 1.5 1.8
Palermo 2006–2009 1461 15.3 14.7 14.9 13.7 6.2 6.3 6.4 5.8 0.9 0.9 0.9 1.0
Athens 2007–2009 1096 80.6 84.1 81.6 89.4 36.3 38.1 36.8 41.0 9.2 8.4 8.7 7.9
*Model estimates according to Navy Aerosol Analysis and Prediction System (NAAPs).
†Includes three cities (Modena, Parma and Reggio Emilia) in the Emilia Romagna region.
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DISCUSSION
We found that cardiovascular mortality was significantly higher
in the Mediterranean cities on smoky days. There was a weaker
association with natural mortality and no association was
observed with respiratory mortality. We also found that PM
10
effects on natural, cardiovascular and respiratory mortality were
greater on smoky days than on other days, while an effect modi-
fication was clear only for cardiovascular mortality.
While high toxicity of particles from wood fires (higher than
from particles originating from other sources) has been reported
in experimental and toxicological research,
636
epidemiological
studies have reported conflicting effects of particles on cause-
specific mortality on smoky days,
917–19 22
or very similar
effects of PM
10
on smoke-affected and smoke-free days.
21 22
Our results indicate that PM
10
from forest fires increases mortal-
ity more than PM
10
from other sources does. It is possible that
the stronger effects of particles during smoke-affected days are
due to differences in their composition, but other factors also
play a role in increasing mortality on those days, such as tem-
perature increase. Cardiac patients are more susceptible than
other participants to high temperatures that, in turn, are known
to enhance the effects of ambient particles.
37
The mortality increase associated with PM
10
is consistent with
the estimates reported in multicity European studies: APHEA2,
38
APHENA
39
and EpiAir.
40
All these studies also showed higher
PM
10
effects on respiratory mortality. Then, the effects we found
on cardiovascular mortality during fires may be due to a different
PM composition or increasing temperature.
In contrast, results from studies on the effects of wildfire
emissions on cause-specific mortality have been inconsistent.
Johnston
17
reported the highest effects on cardiovascular mor-
tality, but Morgan
22
did not find any consistent effect with car-
diovascular deaths in Australia, and Analitis
9
found the highest
effects on respiratory mortality in Greece; this last study,
however, used an exposure definition that differs from nearly
every other fire smoke study. The toxicological studies on effects
of fire smoke usually focus on lung damage and have consist-
ently reported trachea-bronchial cell injuries, changes in the
immune cell morphology in the lungs and diminishing ventilator
responses.
6
On the other hand, it may be that different degrees
of toxicity on cardiovascular and respiratory systems are due to
different PM
10
components or to varying gaseous emissions
(CO, VOCs, NOx or SO
2
) from wildfires. Natural mortality has
been already reported as less affected by fires
917
when
compared to cause-specific mortality. We did not attempt to
explain the high heterogeneity of PM
10
effects on natural mor-
tality during fires, however, it is worth noting that natural mor-
tality is likely to be penalised by a misclassification of accidental
deaths (injuries, poisoning and external causes); these causes of
death are usually not included as plausible effects of air pollu-
tion, but are likely to occur during fire episodes or result from
them at longer distance, in the case of poisoning.
An underestimation of PM levels from wildfires at ground
level is usually due to satellite observations, which incorrectly
identify some aerosol plumes as clouds, and fires produce
smoke as thick as some clouds.
10
On the other hand, an over-
estimate of PM from wildfires would occur because of their
high prevalence of carbonaceous particles, increasing the
absorption of the satellite signal. Therefore, a misclassification
was the most likely bias affecting our assessment of exposure.
The sensitivity analysis we performed excluding cities with no
PM and temperature increases on smoky days, supports the
hypothesis of a misclassification of smoky days in the two cities.
We did not have chemical transport models available to esti-
mate PM aerosol vertical profiles, though they have been shown
to improve the accuracy of satellite estimates of PM
2.5
,
41
nor
were we able to directly estimate the contribution to PM
10
from
forest fires. Therefore, to validate fire exposure, we used indirect
indicators, such as fire-related pollutant levels from fixed moni-
tors despite the important assumptions this required. We
observed a clear PM increase on smoky days and this is consist-
ent with previous studies, which used PM increases as a fire
exposure indicator,
21 22
or validated the satellite data on fires
using background PM
2.5.41
Assessment of fire smoke intensity is even more likely to be
affected by misclassification; it relies on fire characteristics not
directly related to human exposure, such as the extension of the
burnt area,
9
AOD from satellites
42
or plume detection.
26 43
The
weak consistency we observed between smoke intensity and dur-
ation with fire-related indicators, induces caution in relying on
intensity estimates based on satellite data. Moreover, the high
correlation we observed between the shortest episodes and the
mild smoke intensity fell very much between the longest events
and days of intense smoke. A recent study aids in understanding
this issue; Yao and Henderson
44
validated an empirical model to
estimate forest fire-related PM
2.5
using background PM,
remotely sensed aerosols and remotely sensed fires, smoke
plumes from satellite images, fire danger ratings and the venting
Table 3 Pooled* estimates of the effects of smoke and PM
10
(10 mg/m
3
) on natural and cause-specific mortality (all ages) in 10
MED-PARTICLES cities in 2003–2010
Natural mortality, lag 0–1 Cardiovascular mortality, lag 0–5 Respiratory mortality, lag 0–5
Per cent 95% CI I
2
(%) p-het p REM Per cent 95% CI I
2
(%) p-het p REM Per cent 95% CI I
2
(%) p-het p REM
Smoke-affected days 1.78 −0.91 4.53 19 0.260 6.29 1.00 11.85 34 0.140 −3.49 −9.60 3.03 0 0.440
PM
10
0.53 0.30 0.76 22 0.240 0.74 0.30 1.18 1 0.427 1.99 0.80 3.20 39 0.097
PM
10
†0.51 0.16 0.86 50 0.035 0.70 0.14 1.27 25 0.213 2.17 0.89 3.46 43 0.068
PM
10
‡
On smoke-free days 0.49 0.14 0.85 49 0.040 0.65 0.10 1.19 21 0.252 2.13 0.85 3.42 43 0.072
On smoke-affected
days
1.10 −1.51 3.77 51 0.033 0.655 3.42 0.64 6.28 0 0.491 0.055 3.90 −1.63 9.74 0 0.888 0.549
*From random meta-analysis.
†Adjusted for smoky days and Saharan dust in three levels.
‡Adjusted for Saharan dust in three levels and stratified in smoke-free days and smoke-affected days.
p-het, p value of the heterogeneity test; PM, particulate matter; p REM means p value of the difference between the effects on the smoke free days and on smoke affected days; REM,
relative effect modification.
Faustini A, et al.Occup Environ Med 2015;0:1–7. doi:10.1136/oemed-2014-102459 5
Environment
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index (the probability of the atmosphere to disperse smoke
from a fire). In contrast to our results, the correlation between
estimated and observed values was 84%, and decreased on days
with moderate to low levels of smoke up to 59%–58%. Thus
the model more reliably assessed exposure to high-intensity
smoke, than to smoke of low intensity.
CONCLUSIONS
We observed increases in natural and cause-specific mortality on
smoky days; mortality from cardiovascular causes had the
largest increase. PM
10
had larger effects on cardiovascular and
respiratory mortality on smoky days than on other days, suggest-
ing a priority role of particulate as an effective component of
fire smoke. Our study highlighted the need to make improve-
ments in exposure assessments and estimations of fire-related
health outcomes. Wildfire exposure assessment would benefit
from remote sensors, source apportionment of particles during
fires and from a detailed definition of their components, as well
as assessing fire-related increases in temperature. A better under-
standing of the role that meteorology plays in influencing the
direction and the spatiotemporal extension of wild fires is also
important. Health assessments could benefit from the analysis
of other health outcomes such as accidental causes of death
during fires, and specific syndromes related to fire resulting at
longer distance.
Author affiliations
1
Department of Epidemiology, Regional Health Service, Lazio Region, Rome, Italy
2
Institute of Environmental Assessment and Water Research, IDAEA-CSIC, Barcelona,
Spain
3
Aix Marseille Université, CNRS, Marseille, France
4
Department of Hygiene, Epidemiology and Medical Statistics, Medical School,
University of Athens, Athens, Greece
5
Department of Epidemiology and Environmental Health, Regional Environmental
Protection Agency, Piedmont, Italy
6
Institute of Atmospheric Pollution, National Research Council, Rome, Italy
7
Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain
8
Regional Centre for Environment and Health, Regional Agency for Environmental
Protection of Emilia-Romagna, Modena, Italy
Acknowledgements The authors thank Margaret Becker for revising the English
and Simona Ricci for her help with the figures. The authors express their gratitude
to the Naval Research Laboratory for the provision of NAAPS aerosol maps (http://
www.nrlmry.navy.mil/aerosol/), without which this study would not have been
possible.
Collaborators MED-PARTICLES Studygroup—Italy: ERA, P Angelini, G Berti,
L Bisanti, EC, M Catrambone, M Chiusolo, M Davoli, F de’Donato, M Demaria,
M Gandini, M Grosa, AF, S Ferrari, FF, P Pandolfi, R Pelosini, CP, A Pietrodangelo,
L Pizzi, V Poluzzi, G Priod, G Randi, AR, M Rowinski, C Scarinzi, MS, E Stivanello,
S Zauli-Sajani; Greece: K Dimakopoulou, K Elefteriadis, K Katsouyanni, A Kelessis,
T Maggos, N Michalopoulos, S Pateraki, M Petrakakis, S Rodopoulou, ES, V Sypsa;
Spain: D Agis, J Alguacil, B Artiñano, J Barrera-Gómez, X Basagaña, J de la Rosa,
J Diaz, R Fernandez, B Jacquemin, A Karanasiou, C Linares, BO, NP, JP, XQ, AM
Sanchez, JS, A Tobias; France: M Bidondo, C Declercq, A Le Tertre, P Lozano,
S Medina, L Pascal, M Pascal.
Funding This research was supported by the European Union under the grant
agreement LIFE+ ENV/IT/327.
Competing interests None.
Provenance and peer review Not commissioned; externally peer reviewed.
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Project
Europe: results of the MED-PARTICLES
mortality during forest fires in Southern
Short-term effects of particulate matter on
Forastiere and the MED-PARTICLES study group
Ostro, Andrea Ranzi, Jordi Sunyer, Massimo Stafoggia, Francesco
Evangelia Samoli, Xavier Querol, Ennio Cadum, Cinzia Perrino, Bart
Annunziata Faustini, Ester R Alessandrini, Jorge Pey, Noemi Perez,
published online February 17, 2015Occup Environ Med
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