Observed ozone exceedances in Italy: statistical
analysis and modeling in the period 2002-2015
Serena Falasca1,2 ([email protected]),
Gabriele Curci1,2, Luca Candeloro3, Annamaria Conte3, Carla Ippoliti3
Department of Physical and Chemical Sciences, University of L’Aquila, L’Aquila, Italy.
2 Centre of Excellence CETEMPS, Department of Physical and Chemical Sciences, University of L’Aquila,
L’Aquila, Italy.
3 Istituto Zooprofilattico dell’Abruzzo e del Molise ‘G. Caporale’, Teramo, Italy.
1
BACKGROUND
AND MOTIVATION
METHODS
AND RESULTS
MATERIAL
Analysis of
Exceedances
European Geosciences Union General Assembly 2017
Vienna | Austria | 23–28 April 2017
Regression
Model
CONCLUSIONS
KEY POINTS
• The temperature as one of the main drivers of the ozone
B
A
C
K
G
R
O
U
N
D
• “2015 was the warmest year ever recorded on Earth, and it
was not even close.” (NASA cit)
• The European Directive 2008/50/EC on ambient air quality
and cleaner air for Europe establishes objectives and
thresholds for the protection of human health
OUR QUESTION:
• Did the heat wave which occurred in the summer of 2015
affect the ozone season in the same year?
The temperature as one of the main drivers
of the ozone
“Temperature is the most important meteorological factor in driving ozone episodes in polluted
regions” (Shen et al. 2016)
B
A
C
K
G
R
O
U
N
D
95th
In Figure: Frequency at which normalized
percentile QR coefficients
for selected variables were in the top two out of all included variables for
summer O3. Specific meteorological variables (shown in legend) have
been grouped into categories shown on the x axis of the bar plot. […]
(Porter et al. 2015)
(Jacob and Winner 2009)
The European Directive 2008/50/EC
B
A
C
K
G
R
O
U
N
D
“The new Directive 2008/50/EC of the European Parliament and of the Council of 21 May 2008 on ambient air
quality and cleaner air for Europe entered into force on 11 June 2008.
This new Directive includes the following key elements:
• the merging of most of existing legislation into a single directive (except for the fourth daughter directive)
with no change to existing air quality objectives*
• New air quality objectives for PM2.5 (fine particles) including the limit value and exposure related
objectives – exposure concentration obligation and exposure reduction target
• The possibility to discount natural sources of pollution when assessing compliance against limit values
• The possibility for time extensions of three years (PM10) or up to five years (NO2, benzene) for complying
with limit values, based on conditions and the assessment by the European Commission.
*Framework Directive 96/62/EC, 1-3 daughter Directives 1999/30/EC, 2000/69/EC, 2002/3/EC,
and Decision on Exchange of Information 97/101/EC.”
(from http://ec.europa.eu/environment/air/quality/legislation/existing_leg.htm)
Standard for
Ozone
Averaging
period
Value (µgm-3)
Long-term Objective
(LTO)
Maximum daily eighthour mean within
a calendar year
120
Information Threshold
(IT)
1 hour
180
Ozone concentrations
24 monitoring stations were selected among 259 stations following 3 availability criteria:
• ozone data for 2015
• ozone data for 2002-2014 years
• a nearby weather station
M
A
T
E
R
I
A
L
The 24 selected stations are grouped into 6 classes according to 2 criteria:
• the zone (urban, suburban, rural)
• the geographical area (outside or inside the Po Valley)
Po Valley
Non Po Valley
In Figure:
Color: red for “Po Valley” stations, blue for
“Non Po Valley” stations.
Marker: diamond for rural, square for suburban,
asterisk for urban.
Information about the selected
monitoring stations
The 24 selected monitoring stations: properties
M
A
T
E
R
I
A
L
EoI Code
Name
Type
Zone
Latitude
Longitude
Location
IT1397A
CENAS8
I
S
39.22
8.99
Non Po Valley
IT1270A
CENSA1
I
S
39.08
9.01
Non Po Valley
IT1269A
CENSA2
I
S
39.07
9.01
Non Po Valley
IT0459A
CHIARAVALLE2
Un
S
43.59
13.34
Non Po Valley
IT1524A
CN_4003_ALBA
Un
U
44.70
8.032
Po Valley
IT1529A
CN_4078_CUNEO
Un
U
44.38
7.53
Po Valley
B
R
44.41
8.16
Po Valley
Un
S
43.62
13.39
Non Po Valley
Un
S
43.63
13.38
Non Po Valley
IT1519A
IT0463A
IT0461A
CN_4201_SALICET
O
FALCONARA
ALTA
FALCONARA
SCUOLA
IT0883A
FI-SETTIGNANO
B
R
43.79
11.32
Non Po Valley
IT1179A
Gherardi
B
R
44.84
11.96
Po Valley
IT1679A
Grottaglie
B
S
40.54
17.42
Non Po Valley
IT1010A
MAGENTA VF
B
U
45.47
8.89
Po Valley
IT1680A
Martina Franca
T
U
40.70
17.33
Non Po Valley
IT1518A
NO_3106_VERDI
Un
U
45.44
8.62
Po Valley
IT1030A
PARCO BUCCI
Un
U
44.28
11.87
Po Valley
Un
U
44.21
12.04
Po Valley
IT1048A
PARCO
RESISTENZA
IT1453A
PD – Mandria
B
U
45.37
11.84
Non Po Valley
IT1110A
PI-PASSI
B
U
43.73
10.40
Non Po Valley
IT0858A
QUARTO
B
U
44.39
8.99
Non Po Valley
B
S
42.45
14.21
Non Po Valley
B
R
45.17
7.55
Po Valley
B
S
44.96
7.63
Po Valley
IT1423A
IT1121A
IT1125A
TEATRO
D'ANNUNZIO
TO_1099_MANDRI
A
TO_1309_VINOVO
In Table:
Station type:
B - Background
I - Industrial
T - Traffic
Un – Unknown.
Station zone:
R - Rural
S - Suburban
U - Urban.
ANALYSIS OF EXCEEDANCES
M
R
E
E
T A S
H N U
In Figure:
Number of ozone exceedances, maximum ozone averages and
maximum temperatures for all stations. Number of exceedances
of ozone limit values per station for the years 2002-2015 during
the ozone season (May to September); green bars denote the
exceedances of the daily maximum 8-hour-average of the 120
µgm-3 threshold (long-term objective, LTO), yellow bars denote
those of the hourly ozone of the 180 µgm-3 threshold
(information threshold, IT). Lines denote the season average daily
maximum 8-hour ozone (blue), and the season average daily
maximum temperature (magenta).
O D L
T
D
S
S
In Figure:
Monthly distribution of LTO
exceedances for each year during the
ozone season (May – September).
All selected stations are included.
ANALYSIS OF EXCEEDANCES
M
R
E
E
T A S
H N U
a)
b)
c)
d)
O D L
T
D
S
S
In Figure: Cluster analysis of the maximum 8-hour-average ozone. A cluster is defined as a subset of consecutive days
exceeding the LTO threshold. (a) Number of clusters; (b) Cluster duration (days); (c) Maximum cluster concentration; (d)
Mean cluster concentration. Solid bars denote average over stations, boxplots display the distribution of data from each
station.
ANALYSIS OF EXCEEDANCES
M
R
E
E
T A S
H N U
O D L
T
D
S
a)
b)
c)
d)
S
In Figure: Cluster analysis of the daily maximum temperature. A cluster is defined as a subset of consecutive days exceeding
the threshold of 28° C. (a) Number of clusters; (b) Cluster duration (days); (c) Maximum cluster concentration; (d) Mean
cluster concentration. Solid bars denote average over stations, boxplots display the distribution of data from each station.
ANALYSIS OF EXCEEDANCES
a)
M
R
E
E
T A S
H N U
c)
b)
d)
O D L
T
D
S
S
In Figure: Cluster analysis of the daily humidity. A cluster is defined as a subset of consecutive days exceeding the threshold of
1005 hPa. (a) Number of clusters; (b) Cluster duration (days); (c) Maximum cluster concentration; (d) Mean cluster
concentration. Solid bars denote average over stations, boxplots display the distribution of data from each station.
ANALYSIS OF EXCEEDANCES
a)
M
R
E
E
b)
c)
T A S
H N U
O D L
T
D
S
S
In Figure: Histograms of the cluster mean concentration binned according to: (a) duration of the ozone clusters;
(b) duration of the temperature clusters; (c) mean temperature of temperature clusters.
a)
M
R
E
E
T A S
H N U
d)
ANALYSIS OF EXCEEDANCES
b)
e)
c)
f)
O D L
T
D
S
S
In Figure: Number of ozone exceedances, maximum ozone averages and maximum temperatures for stations outside the Po
Valley: Rural stations (a), Suburban stations (b), Urban stations (c ). And inside the Po Valley: Rural stations (d), Suburban
stations (e), Urban stations (f).
M
R
E
E
T A S
H N U
O D L
T
D
S
S
In Figure:
Slope of the linear regression between the daily maximum temperature and the
maximum 8-hour mean ozone, for the six classes of stations.
REGRESSION MODEL
Independent
variable
Estimate
Std.
Error
value
Intercept
-1.286e+02
7.773e+01
1.995e-01
Pressure
z
Pr(>|z|)
Significance1
-1.655
0.0980
.
4.327e-03
46.112
< 2e-16
***
1.002e-01
3.231e-03
30.997
< 2e-16
***
Humidity
-1.211e-02
1.222e-03
-9.906
< 2e-16
***
Maximum
temperature
M
R
Wind velocity
-3.720e-01
1.213e-02
-30.673
< 2e-16
***
E
2.158e-03
8.013e-05
26.93
< 2e-16
***
E
Altitude
Inhabitants
2.348e-07
5.147e-08
4.562
5.06e-06
***
Year
8.788e-03
3.883e-02
0.226
0.8210
EE4 (Jan 2006)
4.089e+02
8.329e+01
4.909
9.14e-07
***
EE5 (Jan 2009)
1.988e+02
8.393e+01
2.368
0.0179
*
EE6 (Sep 2014)
-2.727e+03
6.128e+02
-4.450
8.59e-06
***
Month 10
8.978e-01
6.114e-01
1.469
0.1419
Month 11
-1.222e+01
1.148e+02
-0.106
0.9153
Month 12
-1.153e+01
1.136e+02
-0.101
0.9192
Month 2
6.096e-01
7.711e-01
0.791
0.4292
Month 3
3.561e+00
5.911e-01
6.023
1.71e-09
***
Month 4
4.807e+00
5.878e-01
8.177
2.91e-16
***
Month 5
4.719e+00
5.878e-01
8.029
9.86e-16
***
Month 6
4.491e+00
5.885e-01
7.632
2.31e-14
***
Month 7
4.737e+00
5.890e-01
8.042
8.82e-16
***
Month 8
4.187e+00
5.891e-01
7.107
1.18e-12
***
Month 9
3.400e+00
5.887e-01
5.775
7.67e-09
***
Year:EE4
-2.038e-01
4.157e-02
-4.904
9.41e-07
***
Year:EE5
-9.907e-02
4.187e-02
-2.366
0.0180
*
Year:EE6
1.353e+00
3.042e-01
4.448
8.65e-06
***
T A S
H N U
O D L
T
D
S
S
1
number
1Signifincance
codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1.
In Table: 1st column: list of the independent variables used in
the regression model. 2nd column: estimated regression
coefficients. 3th column: standard error. 4th column: z value.
5th column: Pr(>|z|). 6th column: significance.
In Figure: ROC curve for the validation of the
multivariate logistic regression model. The area under
curve (AUC) is 0.914.
CONCLUSIONS
• The highest number of exceedances of the daily maximum 8-hour average ozone was reached
during the notable hot year 2003. 2015 was one of the hottest years after 2003, and the related
ozone season was one of the most severe in recent years, especially at rural sites.
• Ozone is more sensitive to temperature inside the Po Valley, especially at urban stations. Outside Po
Valley, ozone sensitivity to temperature is generally higher at rural stations and lower at urban
stations. We noted a decreasing tendency of the sensitivity from 2003 to 2011, afterwards there is an
inversion of tendency. The trend may be, at least in part, related to the programmed reduction of
NOx emissions.
• The 2015 ozone season was peculiar in terms of the duration of the events: on average, the high
ozone episodes lasted almost 4 days, compared to less than 3 days for recent years, while high
temperature events in 2015 had similar or shorter duration with respect to other recent years. Ozone
mean concentration grows monotonically with the increasing duration of the ozone episode, while it
displays a maximum when grouped according to the duration of high temperature episodes.
• The statistical analysis confirms the crucial role of the meteorological variable on the probability
ozone events: temperature and pressure with a positive coefficient, humidity and wind velocity with
a negative coefficient. Altitude and number of inhabitants present positive and significant
coefficients that favor the exceedances. The introduction of ‘Euro’ regulations explains the
decreasing recent trend.
References:
• Falasca, S.; Conte, A.; Ippoliti, C.; Curci, G. Longer-Lasting Episodes in the 2015 Ozone Season in
Italy in Comparison with Recent Years. In Proceedings of the 1st Int. Electron. Conf. Atmos. Sci.,
16–31 July 2016; Sciforum Electronic Conference Series, Vol. 1, 2016 , B005;
doi:10.3390/ecas2016-B005
• Jacob, J.J.; Winner, D.A. Effect of climate change on air quality. Atmos Environ 2009, 43, 51-63,
doi:10.1016/j.atmosenv.2008.09.051.
• Porter, W.C.; Heald, C.L.; Cooley, D.; Russel, B. Investigating the observed sensitivities of airquality extremes to meteorological drivers via quantile regression. Atmos Chem Phys 2015, 15,
10349–10366, doi:10.5194/acp-15-10349-2015.
• Shen, L.; Mickley, L.J.; Gilleland E. Impact of increasing heat waves on U.S. ozone episodes in the
2050s: Results from a multimodel analysis using extreme value theory. Geophys Res Lett 2016, 43,
4017–4025, doi:10.1002/2016GL068432
Acknowledgements:
• This work is partly funded by the ECOREGIONS project, Identificazione di regioni eco-climatiche
in Italia per un sistema di allerta precoce per le malattie trasmesse da vettori, Istituto Zooprofilattico
Sperimentale “G. Caporale” Teramo, codice IZS AM 05/14 RC.
• Regional Environmental Protection Agencies (ARPA) are acknowledged for proving the
concentration data of Ozone