A study of surface ozone variability over the Iberian Peninsula during the last fifty years

Atmospheric Environment 45 (2011) 1946e1959

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A study of surface ozone variability over the Iberian Peninsula during the last fifty years M.I. Fernández-Fernández, M.C. Gallego*, J.A. García, F.J. Acero Departamento de Física, Universidad de Extremadura, Avda. de Elvas s/n, 06071 Badajoz, Spain

a r t i c l e i n f o

a b s t r a c t

Article history: Received 17 August 2010 Received in revised form 11 January 2011 Accepted 12 January 2011

There is good evidence for an increase in the global surface level of ozone in the past century. In this work we present an analysis of 18 surface ozone series over the Iberian Peninsula, considering the target values of ozone for the protection of human health and for the protection of vegetation, as well as the information and alert thresholds established by the current European Directive on ambient air quality and cleaner air for Europe (Directive 2008/50/EC). The results show that the stations located on the Cantabrian coast exceeded neither the target value for the protection of human health nor the target value for the protection of vegetation. The information threshold was exceeded in most of the stations, while the alert threshold was only exceeded in one. The seasonal and daily evolution of ozone concentrations were as expected. A trend analysis of three surface ozone concentration indices (monthly median and 98th percentile, and monthly maximum of the daily maximum 8-h mean) was performed both for the whole period of each station and for the common period from 2001 to 2007 for all the months of the year. It was noted that generally the south of the Iberian Peninsula presented increasing trends for the three indices, especially in the last six months of the year, and the north decreasing trends. Finally, a correlation analysis was performed between the daily maximum 8-h mean and both daily mean temperature and daily mean solar radiation for the whole and the common periods. For all stations, there was a significant positive association at a 5% significance level between the daily maximum 8-h mean and the two meteorological variables of up to approximately 0.5. The spatial distribution of these association values from 2001 to 2007 showed a positive northwest to southeast gradient over the Iberian Peninsula. Ó 2011 Elsevier Ltd. All rights reserved.

Keywords: Tropospheric ozone Ozone variability Ozone trends Iberian Peninsula

1. Introduction The global distribution of ozone is an important aspect in the study of the atmosphere. Changes in atmospheric ozone are also important for climate change (Intergovernmental Panel on Climate Change (IPCC), 2007): decreases in stratospheric ozone lead to enhanced UVB radiation in the troposphere, which in turn accelerates certain important photolysis rates. Consequently, the formation rate of tropospheric ozone and the oxidation capacity of the troposphere are affected, depending on the concentrations of nitrogen oxides (Staehelin et al., 2001). On a global scale, ozone formation depends mainly on nitrogen oxides (NOx), whereas on a local scale volatile organic compounds (VOCs) are more important than nitrogen oxides, and on a regional scale both types of ozone precursors have to be considered in the net photochemical ozone production. Tropospheric or surface ozone is a secondary air pollutant, causing health problems and adverse effects on living beings and the physical environment * Corresponding author. Tel.: þ34 924289300x89116; fax: þ34 924289651. E-mail address: [email protected] (M.C. Gallego). 1352-2310/$ e see front matter Ó 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.atmosenv.2011.01.027

(Parmet et al., 2003; Janneane et al., 2003; EPA, 1996; Finnan et al., 1997; Agrawal et al., 2003). The background ozone has several sources, both natural and anthropogenic (Vingarzan, 2004; Castell et al., 2008). Recently, ozone research has been attracting great interest because, during the last century, surface ozone concentrations were considerably raised over rural areas in Europe. Comparisons of ozone background levels with those measured in the late 19th to early 20th centuries indicate that current ozone levels have risen approximately twofold (Stevenson, 2001; Bozo and Weideinger, 1995; Staehelin et al., 1994; Cartalis and Varotsos, 1994). This rise occurred in parallel with industrial development and motor traffic which resulted in a strong increase of emissions of many species, including nitrogen oxides and volatile organic compounds. However, measures have been taken to reduce the emissions of these ozone precursors (NOx and VOCs). Between 1990 and 2008, emissions of VOCs in Spain and Portugal decreased by around 21% and 34% respectively. Emissions of NOx decreased in Spain by 8%; however in Portugal they increased by around 7% (EEA, 2010). Some authors have found that since the 1950s in the northern hemisphere surface ozone has increased at a mean rate of w1e2% per

M.I. Fernández-Fernández et al. / Atmospheric Environment 45 (2011) 1946e1959

year, with large fluctuations from year to year, mainly in relation to meteorological variations (Feister and Warmbt, 1987; Low et al., 1992). Coherent with this result is the small increasing trend in the 50-percentile value of ozone concentrations in the European Union during the period 1994e1998 reported by de Leeuw (2000). According to Oltmans et al. (2006), at mid latitudes of the SH, tropospheric ozone has shown increases since the early 1990s. In Antarctica, surface ozone amounts declined through the 1980s into the early 1990s with a recovery in the most recent decade reported. However, all months from March to August for this most recent period present smaller amounts then the two earlier periods (1975e1984, 1985e1994). There have been many studies on surface ozone trends in Europe. For example, one can cite the investigations by Sicard et al. (2009) which found for France a slight increase in annual averaged ozone concentrations in rural areas between 1995 and 2003, but a decrease in the upper ozone percentiles and in precursor emissions. In Switzerland in the 1990s, Brönnimann et al. (2002) also observed slight decreases of the ozone peaks but a clear increase in the monthly mean values, and Kuebler et al. (2001) detected a very slight downward trend in ozone in both urban and rural sites in spite of the reductions in ozone precursors between 1985 and 1998. In northwest Europe, Derwent et al. (2003) observed downward trends in episodic peak ozone during the 1990s. This decrease was due to the reduction of ozone precursors. Ordóñez et al. (2005) analysed the influence of meteorological variables (temperature, global radiation, wind speed, wind direction, and relative humidity) on the daily ozone maxima in Switzerland in all seasons from 1992 to 2002. It was observed that the daily maximum ozone concentrations and temperature were strongly correlated. During the warm seasons, the afternoon temperature and the morning global radiation presented a positive correlation with daily ozone maxima both in summer and in spring. Over the Iberian Peninsula (IP) several studies related to surface ozone concentrations have been carried out but, to the best of our knowledge, always limited to a single location or a restricted sector of Iberia. Among others, we can cite the following: diurnal and monthly variations in surface ozone concentrations of five Spanish rural stations were analysed by Gimeno et al. (1999); Sousa et al. (2006) developed a method for prediction of ozone concentrations in the city of Oporto by means of statistical approaches; the behaviour of background ozone in the northeast of the IP was studied by Millán et al. (2002) and Ribas and Peñuelas (2004); Sánchez et al. (2005) investigated the transport of ozone at a high-altitude station in the Central Massif of Spain; and Adame et al. (2008) studied the behaviour, distribution, and variability of surface ozone in the south of the IP. In this work, we present a more extensive analysis of surface ozone time series for 18 locations over the IP. As mentioned above, the formation of tropospheric ozone depends on the concentrations of precursors. Between 1990 and 2008, emissions of VOCs in Spain and Portugal decreased by around 21% and 34%, respectively. Emissions of NOx have decreased in Spain by 8%, but in Portugal they have increased by around 7% (EEA, 2010). The objectives of this work were: (1) to determine whether surface ozone levels in the Iberian Peninsula in the last 20 years comply with the objectives defined by the current European Directive (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); (2) to analyse the possible existence of statistically significant trends in the IP surface ozone time series; and (3) to study the correlation between surface ozone concentrations and meteorological parameters such as temperature and solar radiation. 2. Data We used hourly records of surface ozone concentrations at 18 stations distributed over the IP (see Fig. 1). Table 1 provides

1947

Fig. 1. Geographical locations of the studied stations. Red circles indicate the stations which do not exceed the target value for the protection of vegetation (AOT40). Green circles indicate the stations which do not exceed the information threshold (180 mg m3). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

a detailed list with information about the site, geographical coordinates, altitude, temporal period, and percentage of missing values. The stations were grouped according to their location: Cantabrian coast, ES08, ES16, ES05; Atlantic coast, PT04, ES17; Mediterranean coast, ES02_ES07, ES12, ES03, ES14, ES10, ES06; and inland (or interior of the IP), ES01_ES15, ES04, ES09, ES11, ES13. All of these stations belong to the EMEP (European Monitoring and Evaluation Programme) network. The EMEP programme measures air pollution in rural areas, and relies on three main elements: collection of emission data, measurements of air and precipitation quality, and modelling of atmospheric transport and deposition of air pollutants. In the EMEP directions, hourly measurements of surface ozone, sulphur dioxide, and nitrogen monoxide are made at each station as well as measurements of meteorological variables such as wind direction and speed, overall solar radiation, pressure, temperature, humidity, and precipitation. In the case we are dealing with, the analytical method used to measure the surface ozone concentration, expressed in mg m3, is UV photometry (EMEP, 2001).

Table 1 Locations, coordinates, altitudes, study period, and percentage of missing values of the selected stations. Code Observatory

Longitude Latitude ( N) ( E)

ES01

4.34861

39.54777

917

1993e2000

6.76

3.6 0.49139 2.50305 8.92361 4.31666 3.53333 4.85027 3.14277 3.31694 6.92278 1.10194 5.86667 0.71667 4.35 7.69972 6.55 8.8

37.2 720 40.82055 44 42.45779 445 42.72805 683 39.86666 78 37.23333 1265 43.44222 134 41.28111 1360 42.31944 23 38.47583 393 39.08611 885 41.28333 985 41.4 470 39.51667 1241 43.23111 506 37.05 5 39.08333 43

1993e1995 1993e2000 1993e2001 1993e2000 2008e2009 1995e2009 1998e2009 1998e2009 1998e2009 1999e2009 1998e2009 2000e2009 2000e2009 2000e2007 2001e2009 2008e2009 1990e2007

13.16 4.66 6.30 10.11 3.35 11.00 2.52 4.86 3.84 3.00 2.93 2.38 2.19 9.84 3.76 4.54 18.17

San Pablo de los Montes ES02 La Cartuja ES03 Roquetas ES04 Logroño ES05 Noia ES06 Mahón ES07 Víznar ES08 Niembro ES09 Campisábalos ES10 Cabo de Creus ES11 Barcarrota ES12 Zarra ES13 Peñausende ES14 Els Torms ES15 Risco Llano ES16 O Saviñao ES17 Doñana PT04 Monte Velho

Altitude Period (m)

Missing values %

1948

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Table 2 Threshold values for ozone. Threshold

Value

Measured as

Protection human health Protection vegetation Information threshold Alert threshold

120 mg m3 18 000 mg m3h1 180 mg m3 240 mg m3

Maximum daily 8-h mean AOT40a Hourly average Hourly average

a

AOT40 is the sum of the differences between the hourly mean surface ozone concentration greater than 80 mg m3 and 80 mg m3 using only the 1 h values measured between 8:00 and 20:00 from May to July.

3. Methods As was mentioned above, the current European Directive on ambient air quality and cleaner air for Europe is Directive 2008/50/EC. This Directive establishes target values of ozone for the protection of human health and for the protection of vegetation as well as information and alert thresholds (Table 2). According to this Directive, UE Member States must inform the population of the dates and duration of periods when the target and threshold values are exceeded and the ozone concentrations that are reached at those times. To analyse the possible existence of statistically significant trends in the IP surface ozone time series, the non-parametric ManneKendall (MeK) test was used. This statistical test was firstly introduced by Kendall (1976), and has been widely applied in a lot of scientific fields, i.e.: hydrology (Kundzewicz and Robson, 2000), climatology (Gallego et al., 2006, 2011), air quality (de Leeuw, 2000; Ruoho-Airola et al., 2004; Sicard et al., 2009, 2011) and precipitation chemistry (Kvaalen et al., 2002; Sicard et al., 2007). The null hypothesis Ho is that the data (X1, X2, . Xn) are identical and independently distributed random variables, and the alternative hypothesis H1 is that the data are

distributed according to an increasing or decreasing trend. The power of the MeK test, the probability of rejecting the null hypothesis, is as high as that of parametric tests. Its advantage lies in its independence of the form of the distribution (Press et al., 1990). The statistic of the test is Kendall’s s, whose expression is the following

s¼

n1 X n X i ¼ 1 j ¼ iþ1

  sgn Xj  Xi ;

where sgn(X) is the sign function, with values equal to 1, 0, or 1 depending on whether the argument is negative, zero, or positive, respectively. The variance of s under the null hypothesis is

varðsÞ ¼

nðn  1Þð2n þ 5Þ : 18

The exact distribution of s can be evaluated. For n > 10, the distribution approaches a normal, especially if the following correction is made:

s0 ¼ s  sgnðsÞ: The normalised variable is evaluated from s0

Z ¼

s0

varðsÞ

:

Obviously, Z is normally distributed with mean 0 and variance 1. It will give the values of the probability of acceptance of the null hypothesis. The MeK test described detects the existence of a trend, but does not provide an estimate of its magnitude. For this purpose, we use the algorithm proposed by Hirsch and Smith (1982), an

Fig. 2. AOT40 and the number of exceedance days related to protection of human health, information threshold, and alert threshold at the Niembro (ES08), Cabo de Creus (ES10), Monte Velho (PT04), and La CartujaeVíznar (ES02eES07) stations.

M.I. Fernández-Fernández et al. / Atmospheric Environment 45 (2011) 1946e1959

1949

Table 3 Summary of the analysis of the directive. Station

Years above information threshold

e 1998, 1990, 2003, ES02_ES07 1998,

ES08 ES10 PT04

Years above Years above protection human health alert threshold

e 2000, 2001, 2002, 2003, 2004, 2005, 2006. e 1996, 1997, 1999, 2001, 2002, 1997 2005, 2006 1999,2001 e

Years above protection vegetation

1999, 2000, 2003, 2004, 2005, 2006, 2007, 2009 e 1998e2009 1998e2006, 2009 1999e2006 1996 1990e1997, 1999e2006

extension of that suggested by Theil (1950a,b,c) and Sen (1968). The statistic of this TheileSen test is related to the slope of the trend found by the MeK test. This test was applied to monthly series of median and 98th percentile hourly surface ozone concentrations, and of the maximum of the daily maximum 8-h mean.

1994, 1995, 1998e2002, 2004e2008

The Kendall rank correlation method was used to study the correlation between surface ozone concentrations and meteorological variables such as temperature and solar radiation. This is one of the empirical measures of dependence of two random variables X and Y based on ranking the elements of the sample (X1,Y1),.,(Xn,Yn). The Kendall coefficient is a rank statistic defined by the formula

Fig. 3. Monthly evolution of ozone at the eighteen stations. (a) Stations with maximum concentrations in April and May. (b) Stations with maximum in June and July. Green circles indicate the stations with the highest ozone levels. Red circles indicate the stations with the lowest ozone levels. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

1950

M.I. Fernández-Fernández et al. / Atmospheric Environment 45 (2011) 1946e1959

Fig. 4. Daily evolution of ozone for the 18 stations in each season.

M.I. Fernández-Fernández et al. / Atmospheric Environment 45 (2011) 1946e1959

1951

Fig. 5. Example of daily evolution of (a) NO and (b) NO2 concentrations in spring.

s ¼

2Sðr1 ; .; rn Þ ; nðn  1Þ

The information threshold was exceeded at all the stations except Logroño (ES04), Mahón (ES06), Niembro (ES08), and Doñana (ES17) (see Fig. 1). The alert threshold was only exceeded at Monte Velho (PT04) in March. As one could expect, the rises above the information and alert thresholds occurred in spring or summer during the central hours of the day, the period with maximum solar radiation and optimal conditions for the physicochemical processes involved in ozone formation (Adame et al., 2008). As example, Fig. 2 shows the results for four stations located at different places over the IP. At Niembro (ES08) on the Cantabrian coast (north of the IP), all years presented exceedances of the target value for the protection of human health except 1998, 2001, 2002, and 2008. Comparison against the target value for the protection of vegetation was made in terms of AOT40. The highest AOT40 was observed in 2005 and the lowest AOT40 in 2002. The information and alert threshold were not exceeded on any occasion. For Cabo de Creus (ES10), in the north of the Mediterranean coast of the IP, the information threshold was exceeded in 1998, 2000, 2001, 2002, 2003, 2004, 2005, and 2006. The alert threshold was not exceeded on any occasion. The target value for the protection of human health was exceeded in all of the years. In Monte Velho (PT04) on the Atlantic coast of the IP, all years presented exceedances of the target value for the protection of human health except 1998 and 2007. The highest AOT40 was observed in 1996. The information threshold was exceeded in 1990, 1996, 1997, 1999, 2001, 2002, 2003, 2005, and 2006. The alert threshold was exceeded thrice in

where ri is rank of Y belonging to the pair (X,Y) for which the rank of X is equal to i, and S ¼ 2N  n(n  1)/2, with N being the number of elements of the sample for which j > i and rj > ri simultaneously. The inequality 1  sc  1 always holds. The Kendall coefficient of rank correlation has been extensively used (see Kendall, 1970) as an empirical measure of dependence. In particular, the test was applied to determine the possible correlations between the daily maximum 8-h mean of surface ozone concentration and daily means of temperature and solar radiation, respectively. 4. Results 4.1. Analysis of the directive Surface ozone concentrations at each station were analysed in accordance with the current Directive. The results for the 18 stations showed the target value for the protection of human health to be exceeded at all the stations except O Saviñao (ES16) and Niembro (ES08), both located on the Cantabrian coast. The target value for the protection of vegetation was surpassed in all the stations with the exception of Roquetas (ES03) in the Ebro valley, and Niembro (ES08), Noia (ES05), O Saviñao (ES16), and Monte Velho (PT04) on the north and west coasts of the IP (see Fig. 1).

Table 4 Magnitude of the trend and p-value of the median for the whole period at each station. INDIC

January B

ES01eES15 ES05 ES08 ES10 ES11 ES13 ES14 PT04 INDIC

ES01eES15 ES02eES07 ES08 ES09 ES10 ES13 a

a

12.65 28.25 3.25 L22.27 11.52 27.03 4.27 4.56

February p-value 0.03 0.09 0.38 0.001 0.19 0.09 0.46 0.23

July

a

March

April

May

June

B

p-value

B

p-value

B

p-value

B

p-value

B

p-value

9.36 36.58 8.06 L23.9 17.78 1.49 26.32 5.73

0.07 0.02 0.12 0.0006 0.11 0.5 0.01 0.12

5.1 31.02 12.74 25.31 4.18 5.72 18.76 4.5

0.31 0.03 0.01 0.0004 0.38 0.38 0.09 0.27

8.34 28.25 13.83 L21.86 9.05 18.39 16.65 8.18

0.12 0.19 0.02 0.0004 0.11 0.17 0.23 0.04

7.24 25.96 8.31 L18.77 20.46 4.84 28.08 6.76

0.08 0.13 0.11 L0.01 0.02 0.46 0.04 0.07

11.24 23.9 2.44 10.25 1.28 L31.85 14.28 5.99

0.1 0.05 0.38 0.06 0.38 L0.004 0.23 0.1

August

September

October

November

December

B

p-value

B

p-value

B

p-value

B

p-value

B

p-value

B

p-value

12.74 3.84 4.27 8.89 L16.52 L22.13

0.03 0.37 0.38 0.19 L0.04 L0.04

6.02 11.95 8.89 13.25 L18.11 10.09

0.23 0.02 0.27 0.10 L0.001 0.08

8.18 10.63 24.49 6.19 L18.88 4.77

0.25 0.04 0.01 0.23 L0.01 0.24

1.36 11.06 6.27 L16.95 L27.72 10.08

0.50 0.005 0.37 L0.01 L0.003 0.06

3.57 11.58 7.86 L13.19 L23.65 6.47

0.31 0.01 0.06 L0.01 L0.01 0.24

11.97 1.95 11.37 4.73 15.61 3.17

0.11 0.38 0.12 0.29 0.10 0.36

Percentage of variation per 100 years. P-value is dimensionless.

1952

M.I. Fernández-Fernández et al. / Atmospheric Environment 45 (2011) 1946e1959

Table 5 Magnitude of the trend and p-value of the 98th percentile for the whole period at each station. INDIC

ES01eES15 ES04 ES05 ES08 ES10 ES11 ES13 ES14 PT04 INDIC

ES01eES15 ES02eES07 ES09 ES10 ES11 ES12 ES13 PT04 a

January

February

March

April

May

June

Ba

p-valuea

B

p-value

B

p-value

B

p-value

B

p-value

B

p-value

11.85 17.47 28.31 10.57 20.39 4.71 18.76 21.94 8.39

0.01 0.09 0.05 0.06 0.02 0.30 0.23 0.04 0.02

6.80 19.14 33.50 13.74 18.44 5.67 9.48 19.81 4.57

0.20 0.03 0.03 0.03 0.002 0.36 0.13 0.02 0.18

1.29 6.70 25.97 8.80 7.74 4.77 14.80 19.12 2.48

0.38 0.19 0.05 0.18 0.04 0.18 0.17 0.13 0.26

0.52 7.45 14.46 14.77 8.04 22.90 27.00 8.11 6.59

0.36 0.27 0.27 0.03 0.23 0.01 0.06 0.42 0.02

7.48 8.42 24.17 2.93 20.71 9.68 10.03 19.96 7.40

0.08 0.36 0.09 0.32 0.01 0.18 0.30 0.15 0.08

8.64 2.48 8.56 2.29 17.00 1.03 31.40 3.31 12.07

0.14 0.45 0.45 0.32 0.04 0.44 0.01 0.38 0.01

July

August

September

October

November

December

B

p-value

B

p-value

B

p-value

B

p-value

B

p-value

B

p-value

20.28 4.59 9.23 13.33 2365.00 5.46 17.07 12.09

0.004 0.29 0.23 0.12 0.41 0.14 0.06 0.01

14.31 6.50 14.10 20.76 0.35 9.56 8.41 9.32

0.008 0.007 0.08 0.02 0.50 0.19 0.36 0.08

15.96 3.30 11.25 19.54 9.02 10.85 12.61 6.76

0.03 0.20 0.02 0.04 0.32 0.04 0.11 0.04

10.29 11.89 6.32 20.16 3.72 1.85 10.23 4.31

0.03 0.02 0.19 0.03 0.50 0.50 0.24 0.24

5.32 8.95 10.08 14.91 0.96 3.04 7.17 4.87

0.31 0.04 0.04 0.06 0.50 0.42 0.04 0.14

8.69 2.48 6.23 9.26 15.09 13.72 1.86 10.45

0.16 0.42 0.27 0.18 0.01 0.10 0.50 0.09

Percentage of variation per 100 years. P-value is dimensionless.

March 1997, with this being the only station of the set studied at which this threshold was surpassed. At La CartujaeVíznar (ES02eES07), in the southeast interior of the IP, all years presented exceedances of the target value for the protection of human health except 1993. The highest AOT40 was reached in 1998 and 1999. The alert threshold was not exceeded on any occasion. The information threshold was exceeded in 1998, 1999, and 2001. The results for these four stations shown as examples are summarised in Table 3. This type of analysis of the Directive has also been carried out in other European countries. de Leeuw (2000), for instance, analysed the ground level ozone concentrations in the European Union for the period between 1994 and 1998. For the majority of stations, exceedances of the threshold for health protection, vegetation protection, and population information were found. However, those stations showed downward trends in the number of exceedance days.

4.2. Seasonal evolution of the ozone concentrations Using hourly surface ozone concentrations, monthly ozone averages were obtained for the study period of each station, giving a monthly typical year. Fig. 3 shows the monthly average evolution of ozone concentrations for the study period of each station. This figure is in two parts for clarity. Ozone monthly concentrations show a clear cycle with minima in December and January and maxima in AprileMay (Fig. 3a) and JuneeJuly (Fig. 3b). Maxima of surface ozone concentrations in April and May are probably due to enhanced photochemistry after a winter accumulation of air pollutants (Penkett and Brice, 1986), or, depending on the geographical location, although they may also be partly of natural origin due to stratospheric intrusions which may be favoured by the variation of stratosphericetropospheric exchange (Atlas et al., 2003). The presence of a main maximum in JuneeJuly seems to be due to temperature as

Table 6 Magnitude of the trend and p-value of the monthly maximum of the daily maximum 8-h mean for the whole period at each station. INDIC

ES01eES15 ES04 ES05 ES08 ES10 ES13 ES14 PT04 INDIC

ES01eES15 ES02eES07 ES04 ES08 ES09 ES10 ES13 PT04 a

January

February

March

April

May

June

Ba

p-valuea

B

p-value

B

p-value

B

p-value

B

p-value

B

p-value

13.79 18.19 25.61 8.15 21.19 13.21 18.65 10.07

0.004 0.04 0.03 0.27 0.08 0.03 0.09 0.03

6.95 14.13 34.25 20.60 20.15 4.14 10.23 3.59

0.14 0.09 0.03 0.02 0.08 0.30 0.04 0.19

3.39 11.10 21.87 7.54 11.36 0.08 16.50 1.64

0.21 0.27 0.27 0.38 0.04 0.50 0.17 0.24

4.21 23.32 14.54 15.57 2.94 9.48 24.90 5.75

0.21 0.19 0.27 0.02 0.32 0.38 0.06 0.10

9.92 4.47 28.58 1.96 20.62 5.28 7.98 3.72

0.05 0.45 0.13 0.38 0.01 0.38 0.38 0.09

11.81 19.09 5.40 3.84 12.78 39.50 1.44 9.13

0.06 0.09 0.50 0.38 0.19 0.002 0.50 0.03

July

August

September

October

November

December

B

p-value

B

p-value

B

p-value

B

p-value

B

p-value

B

p-value

12.75 6.14 27.35 5.88 5.94 12.81 14.24 12.17

0.04 0.19 0.01 0.22 0.19 0.15 0.02 0.01

15.56 7.84 34.58 1.96 15.65 19.60 7.01 9.15

0.062 0.10 0.13 0.38 0.007 0.003 0.24 0.10

15.21 12.40 20.87 7.74 12.66 8.20 9.94 5.81

0.01 0.02 0.09 0.27 0.03 0.27 0.05 0.22

8.70 10.08 16.19 6.10 11.42 7.15 5.30 7.64

0.08 0.02 0.13 0.37 0.19 0.10 0.43 0.15

3.99 11.40 12.76 11.04 13.63 16.10 9.47 1.88

0.33 0.01 0.19 0.12 0.08 0.02 0.11 0.33

14.42 4.54 6.85 10.85 4.04 11.66 7.45 5.21

0.06 0.22 0.27 0.01 0.47 0.19 0.36 0.19

Percentage of variation per 100 years. P-value is dimensionless.

M.I. Fernández-Fernández et al. / Atmospheric Environment 45 (2011) 1946e1959

a controlling factor (García et al., 2005). One observes in Fig. 3a that all the stations located on the coast e Cantabrian coast (ES08, ES05 and ES16), Atlantic Ocean (PT04 and ES17), and Mediterranean coast (ES06 and ES10) e present maxima in spring. The lowest monthly mean concentrations correspond to the observatories located on the Cantabrian coast (Niembro (ES08), O Saviñao (ES16)), and the Atlantic coast (Doñana (ES17) and Monte Velho (PT04)). The highest monthly mean concentrations were in Mahón (ES06) on the Mediterranean

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island of the same name, and Cabo de Creus (ES10) on the Mediterranean coast, both stations influenced by the Mediterranean Sea which is a more polluted region than those bordering the Atlantic. In Fig. 3b, the stations located in the interior of the IP show maxima in summer. The lowest monthly mean concentrations were observed in Roquetas (ES03) in the Ebro valley. The highest monthly mean concentrations were observed in San Pablo de los MonteseRisco Llano (ES01eES15) almost in the centre of the IP. Nevertheless, this

Fig. 6. ManneKendall test for monthly median series of surface ozone concentration for the period from 2001 to 2007 (from left to right and from top to bottom): January, February, March, April, May, June, July, August, September, October, November, and December. Upward triangles represent increasing trends and downward triangles decreasing trends. The size of each triangle is proportional to the magnitude of the normalised trend (normalised to the standard deviation). Solid black triangles represent trends significant at the 5% level, solid grey triangles indicate trends significant at the 10% level, and triangles and transparent triangles indicate non-significant trends at the 5% and 10% levels. Isolines correspond to interpolated values of the normalised trend (percentages).

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last station is one of the highest altitude stations of our set, and these commonly show only slight seasonal variation possibly because they sample more tropospheric air. With respect to the season when the maximum concentrations were registered, all the features described are consistent with the findings of Castell et al. (2008) who note that stations located on the coast present maxima in spring. This spring maximum may be explained by the smaller spatial development of the breeze cell during these months, i.e., the levels stay confined relatively close to the production areas. However, at the stations located within the Peninsula, the spring maximum was secondary, while the main maximum was recorded during the summer months reflecting the typical smog maxima.

4.3. Daily ozone cycle In order to analyse the daily evolution of the surface ozone concentrations, hourly ozone averages were obtained for each season at each station, giving a typical day for each season. Fig. 4 shows the daily evolution of surface ozone concentrations for the eighteen stations in each season. This figure has been divided into two graphs to improve the visualisation. The seasons were defined as follows: spring (MarcheAprileMay), summer (JuneeJulyeAugust), autumn (SeptembereOctobereNovember), and winter (DecembereJanuaryeFebruary). As was expected, the highest ozone concentrations were obtained in spring and summer,

Fig. 7. ManneKendall test for monthly 98th percentile series of surface ozone concentration for the period from 2001 to 2007 from January to December. Symbols as in Fig. 6.

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and the lowest in autumn and winter. Niembro (ES08) on the Cantabrian coast was the station which presented the lowest ozone concentrations in winter. This could be due to the low radiation levels in this season. In all seasons, the ozone concentrations showed a clear cycle with minima in early morning and maxima in the central hours of the day. The early morning minimum may be because the residual ozone from the previous night is transformed into NO2 by reaction with NO. This is illustrated in Fig. 5 which, taking only spring by way of example, includes the analysis of the diurnal cycle of NO and NO2 for the simultaneous measurements. In this figure, one observes that early morning minima in O3

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concentrations here correspond to maxima in NOx. The phenomenon can be explained as follows. The NO from traffic emissions is produced in the early morning when human activities begin. Once the minimum ozone levels are reached, the elimination of further ozone by NO is not very effective; the NO2 concentration is greater than the NO concentration, thus enhancing ozone formation (Adame et al., 2008). Another process which can decrease surface O3 concentrations during the night is dry deposition, and this is not effective in the residual layer whose air is mixed downwards in the late morning by vertical mixing when the surface inversion layer breaks up.

Fig. 8. ManneKendall test for monthly maximum of daily maximum 8-h mean of surface ozone concentration for the period from 2001 to 2007 from January to December. Symbols as in Fig. 6.

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4.4. Trend analysis From the hourly ozone concentrations, we constructed monthly series of median and 98th percentile, and monthly maximum of the daily maximum 8-h mean. These index series were used for a twofold study: an analysis of the complete period of each station (in order not to lose any information, using the entire record), and an analysis of a selected common period. Tables 4e6 present the statistically significant results of the trend analysis for these three indices, respectively, for the whole period of each station, listing the magnitude of the trend estimated by the TheileSen test (B) and the significance level (p-value) provided by the MeK test. The trends significant at a 5% level appear in bold type. It is interesting to note that at Cabo de Creus (ES10) in the north of the Mediterranean coast of the IP, the median decreases significantly at the 5% level in all months except December and June, when the decrease is significant at the 10% level. The decrease in the 98th percentile is significant at the 5% level in January, February, March, May, June, August, and September. Finally, the monthly maximum of the daily maximum 8-h mean decreases significantly at the 5% level in March, May, August, and November. At La CartujaeVíznar (ES02eES07) in the southeast interior of the IP, the median increases significantly at the 5% level in August, September, October, and November. The 98th percentile increases significantly at the 5% level in August, October, and November. At San Pablo de los MonteseRisco Llano (ES01eES15) in the interior of the IP (Central Plateau), a decreasing trend significant at 5% is observed for the two indices related to the highest ozone concentrations: the 98th percentile and the monthly maximum of the daily maximum 8-h mean in July, August, September, and October. Lastly, at Noia (ES05) in the north of the Atlantic region of the IP, an increasing trend significant at the 5% level is observed in February for both extreme ozone concentration indices. This behaviour also extends to the monthly maximum of the daily maximum 8-h mean in January. In order to study the spatial distribution of ozone trends over the Iberian Peninsula, we selected a period common to the greatest number of stations and that covers the greatest number of years. This period is from 2001 to 2007, and is common to the following stations: Víznar (ES07), Niembro (ES08), Campisábalos (ES09), Cabo de Creus (ES10), Barcarrota (ES11), Zarra (ES12), Peñausende (ES13) Els Torms (ES14), O Saviñao (ES16), and Monte Velho (PT04). For these stations, a new trend analysis was performed in the common period for the aforementioned three indices: one related to normal values of ozone concentration (monthly median), and two related to extreme ozone concentrations (monthly 98th percentile, and monthly maximum of the daily maximum 8-h mean). The spatial distributions of the trend found for the three indices for the period from 2001 to 2007 are shown in Figs. 6e8. The results for the median are shown in Fig. 6. All months except June present the same pattern of increasing trends in the south of the IP. In January and December, there is a slight increase in the median in the southeast and a decrease in the southwest of the IP. The north of the IP is characterised by a general decrease in the median during all months except June, August, and December when this index shows a positive trend. All months except August and December present a decrease in the northwest of the IP. The northeast of the Peninsula shows negative trends in all months, although in February, March, April, May, June, July, and November slight increases also exist. In the centre of the IP during all the year except February, there is a decrease in the median over the 2001e2007 period. With respect to the behaviour of each of the stations, it is noticeable that at Cabo de Creus (ES10) in the northeast of the IP there are generalised negative trends throughout the year. These decreasing trends are significant at the 5% level in January,

Table 7 Kendall rank correlation between daily maximum 8-h mean and daily mean temperature. Code

Period

Association (Kendall’s s)

ES01eES15 ES02eES07 ES04 ES06 ES08 ES09 ES10 ES11 ES12 ES13 ES14 ES16 ES17 PT04

1993e2007 1993e2009 1993e2001 2008e2009 1998e2009 1998e2009 1998e2009 1999e2009 1998e2009 2000e2009 2000e2009 2001e2009 2008e2009 1990e2007

0.48 0.41 0.46 0.2 0.08 0.45 0.32 0.43 0.48 0.46 0.55 0.22 0.27 0.07

February, August, and October, and significant at the 10% level in March, April, and September. Other stations with noteworthy patterns of behaviour, both of them in the northern sub-plateau, are Campisábalos (ES09) with decreasing trends significant at 5% in January, August, and November, and Peñausende (ES13) with decreasing trends significant at the 5% level in January and June. Víznar (ES07) in the southeast interior of the IP shows positive trends significant at the 5% level in October and November, and positive trends significant at the 10% level in September. The two extreme ozone concentration indices, the monthly 98th percentile (Fig. 7) and the monthly maximum of the daily maximum 8-h mean (Fig. 8), show similar behaviour. Generally, the first six months of the year present a decreasing trend over the entire IP, except for April which presents increasing trends. For the 98th percentile, the first seven months show negative trends in the northwest of the IP. The south of the IP is characterised by an increase of the 98th percentile except in May and June, when decreasing trends are depicted over the entire IP. In the case of the monthly maximum of the daily maximum 8-h mean, the first eight months show decreasing trends in the northwest of the IP, except April. This decrease in the first eight months is also observed in the northeast of the IP except in March, April, and May. On the contrary, the south of the IP is characterised by an increase of this index in all months except February, May, and June. With respect to particular stations, for the median, Cabo de Creus (ES10) in the northeast of the IP presents decreasing trends in all months in these extreme indices: for the 98th percentile, the decreasing trends are significant at the 5% level in February and May; for the monthly maximum of the daily maximum 8-h mean the decreasing trends are significant at the 5% level in May and significant at the 10% level

Table 8 Kendall rank correlation between daily maximum 8-h mean and daily mean solar radiation. Code

Period

Association (Kendall’s s)

ES01eES15 ES02eES07 ES04 ES06 ES08 ES09 ES10 ES11 ES12 ES13 ES14 ES16 ES17

1993e2007 1993e2009 1993e2001 2008e2009 1998e2009 1998e2009 1998e2009 1999e2009 1998e2009 2000e2009 2000e2009 2001e2009 2008e2009

0.45 0.52 0.59 0.35 0.26 0.48 0.41 0.50 0.53 0.50 0.54 0.34 0.39

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Fig. 11. Association values between daily maximum 8-h mean and daily mean solar radiation. Fig. 9. Red circles indicate the stations which present the highest association values between daily maximum 8-h mean and daily mean temperature. Green circles indicate the stations that present the highest association values between daily maximum 8-h mean and daily mean solar radiation. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

in August and November. Víznar (ES07) and Barcarrota (ES11), both in the south of the IP, show significant positive trends in August, September, and October. This could be due to the farming activities carried out during these months in these rural locations, for example, the use of nitrogen fertilisers to prepare the land for sowing. Finally, it is interesting to note that Niembro (ES08) on the Cantabrian coast presents increases of the three ozone concentration indices in all months except January and May. A common behaviour of the three indices is an almost generalised decrease of the surface ozone concentrations over the IP in May and June at all the stations except Els Torms (ES14) in the Ebro Valley, but already near the Mediterranean coast. This result may cause a drop in the AOT40 values calculated from May to July, but the search for its causes and consequences needs further requires further study because, according to EMEP (EEA, 2009), no significant changes in anthropogenic ozone precursors seem to have taken place (at least at over the IP) during the period of the measurements. With respect to the results of numerical simulations, the EEA (2009) report gives the EMEP Eulerian photochemistry model as indicating little

Fig. 10. Association values between daily maximum 8-h mean and daily mean temperature.

reduction in AOT40 and SOMO351 in Spain from 1995 to 2005, presumably reflecting the smaller emission changes over the area of this country. This result is consistent with the reduction in extreme ozone concentrations (98th percentile and daily maximum 8-h mean) found for the most of the IP in May and June. The Europe-wide modelled trends predict a reduction in extreme ozone concentrations (MTDM2) from April to September that is only in agreement with measurements over the IP for the Cantabrian coastal region. 4.5. Correlation analysis As was mentioned above, a Kendall rank correlation analysis was made of the daily maximum 8-h mean with both the daily mean temperature and the daily mean solar radiation for the whole period and the common 2001e2007 period. There were no temperature data for Roquetas (ES03) or Noia (ES05), and no solar radiation data for Monte Velho (PT04), Roquetas (ES03), or Noia (ES05). Tables 7 and 8 present the respective association values obtained for the whole period. They were all significant at the 5% level. The greatest association values, of around 0.5, were observed at the stations located in the northeast quadrant of the IP (see Fig. 9). Figs. 10 and 11 show the respective spatial distributions of the association values for the years 2001e2007. The patterns are similar to those obtained for the whole period. All the association values were significant at the 5% level. In Fig. 10 (showing the association values between surface ozone concentrations and temperature), the greatest association values correspond to the stations located in the eastern half of the IP. Monte Velho (PT04), O Saviñao (ES06), and Niembro (ES08) on the north and west coasts of the IP presented the lowest association values. In Fig. 11 (showing the association values between surface ozone concentrations and solar radiation), the greatest association values correspond to the stations located in the southeast of the IP, precisely where the highest temperatures over the IP are observed. According to Solberg et al. (2008) and Vautard et al. (2003), high temperatures lead to stabilisation and subsidence due to dryness of the soil

1 SOMO35 Accumulated ozone concentrations in excess of 70 mg m3 (or 35 ppb). SOMO35 is the sum of the amounts by which maximum daily 8-h concentrations (in mg m3) exceed 70 mg m3 on each day in a calendar year (WHO, 2001). 2 MTDM mean of the 10 highest daily maximum ozone concentrations (based on hourly mean data) during AprileSeptember, corresponding approximately to the mean of the data  95th percentile.

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leading to low humidity in the lower troposphere. The stagnation of the air mass over elevated emissions in continental areas raise the ozone concentrations. O Saviñao (ES06) and Niembro (ES08) on the Cantabrian coast presented the lowest association values. In both figures, there appears a northwest to southeast positive gradient for the correlation between the surface ozone concentrations and the two meteorological variables. 5. Conclusions There have been many studies of surface ozone levels for different regions around the world, especially in the northern hemisphere. We have here described the results of an analysis of surface ozone series over the IP. The result of the Directive analysis for our set of 18 stations showed the target value for the protection of human health to be exceeded at all the stations except O Saviñao (ES16) and Niembro (ES08), both located on the Cantabrian coast. The target value for the protection of vegetation was exceeded at all the stations except Roquetas (ES03) in the Ebro valley, and Niembro (ES08), Noia (ES05), O Saviñao (ES16), and Monte Velho (PT04) on the north and west coasts of the IP. The information threshold was exceeded at all the stations except Logroño (ES04), Mahón (ES06), Niembro (ES08), and Doñana (ES17). The alert threshold was only exceeded at Monte Velho (PT04) in March, noting that this station is one of those presenting a spring maximum. The monthly evolution in ozone concentrations was characterised by maximum concentrations during spring and summer. The lowest concentrations were observed in winter. With respect to the daily evolution of the ozone concentrations, as expected, the highest levels were reached in the central hours of the day and the lowest in the early morning. A trends analysis showed that in general, for the common period from 2001 to 2007, the median, 98th percentile, and monthly maximum of the daily maximum 8-hour mean presented decreasing trends in the north of the IP. This could be due to the reduction of ozone precursors in the IP for the period from 1990 to 2008, as was reported by Derwent et al. (2003) for northwest Europe. However, the south of the IP presented increasing trends, especially in the last six months of the year. This probably reflects the high temperatures during the summer. At Cabo de Creus (ES10), the three surface ozone indices increased in all months. Significant positive trends were also observed for the extreme ozone concentration indices at Víznar (ES07) and Barcarrota (ES11), both in the south of the IP. For the whole period, worthy of note was the case of Cabo de Creus (ES10) where the median decreased significantly at the 5% level in all months except in December and June decrease was significant at the 10% level. In the case of the extreme indices, this decrease was only present in some months of the year. Finally, for all the stations there was a positive association of approximately 0.5 in value, significant at the 5% level, between the daily maximum 8-h mean and the two meteorological variables daily mean temperature and daily mean solar radiation. This was also observed by Ordóñez et al. (2005) in Switzerland for the period from 1992 to 2002. The spatial distribution of these association values for the years from 2001 to 2007 showed a northwest to southeast positive gradient over the IP. This seems reasonable given that the northwest of the IP, characterised by continuous rain during most of the winter, is the wettest region and the southeast of the IP is the driest. Acknowledgements The authors thank J.M. Vaquero for his helpful comments. They also express their gratitude to the Ministry of Environment and Marine and Rural Affairs of the Spanish Government and the EMEP

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