3.3. Meteorological characteristics during lockdown respect to previous years
Meteorological factors have a significant effect on atmospheric pollution. As stated by Gkatzelis et al. 2021, wind velocity, stability, and turbulence have an impact on the dilution, transport, and dispersion of chemicals. Sunshine activates the photochemical production of oxidants that constitute smog, while rainfall has an effect that eliminates from the atmosphere some particles and gases.
In this study, meteorological data were obtained from Barcelona open datasets (Opendata), supplied by the Meteorological Service of Catalonia (Meteocat). As observed in Table 2, some meteorological differences between April 2018, 2019 and 2020 were reported in the control site of Barcelona: Fabra Observatory. During the lockdown period, higher average temperatures and higher humidity were registered (+ 1.2 and + 0.3 ºC and + 3 and + 4.5 %RH, respect to 2019 and 2018, respectively). However, the most important meteorological variation was the total amount of rain registered in the catalan city. As observed in Table 2, the total rainfall registered in Fabra Observatory in April 2020 was 254.6 mm, a value + 6.75 and + 4.3 times higher than the rainfall recorded in 2019 and 2018, respectively. In fact, April 2020 achieved an historical record and stood as the more rainy April month registered in Fabra Observatory for the past 107 years, constituting a 454% of the meteorological average of this month (Betevé; Meteocat).
Table 2
Meteorological parameters registered in Fabra Observatory in April 2018, 2019 and 2020. Data supplied by Barcelona open data sets (Opendata).
Meteorological parameters registered in Fabra Observatory
|
|
April 2018
|
April 2019
|
April 2020
|
Mean daily temperature (ºC)
|
13.6
|
12.7
|
13.9
|
Maximum daily temperature (ºC)
|
24.9
|
21.1
|
21.2
|
Minimum daily temperature (ºC)
|
5.1
|
3.1
|
6.8
|
Relatively daily humidity (%)
|
69
|
70,5
|
73.5
|
Rainfall (mm)
|
58.6
|
37.7
|
254.6
|
Mean daily insolation (MJ/m2)
|
22.5
|
18.3
|
21.2
|
Mean wind speed (m/s)
|
4.2
|
4.2
|
3.7
|
Average wind direction (º)
|
223
|
228
|
218
|
Maximum wind speed
|
18.2
|
21.1
|
20.2
|
Maximum wind direction
|
355
|
334
|
292
|
Finally, some other minor variations were detected regarding the insolation ratio (-0.5 MJ/m2 lower in 2020 respect to the previous two years), in wind speed, which was a bit lower in April 2020 respect to April 2019 − 2018 (3.7 m/s versus 4.2 m/s), and in the wind direction.
Overall, the meteorological differences registered in April 2020 under pandemia respect to the same time in the previous two years (under no pandemia) were fundamentally due to the amount of rain recorded during the lockdown, which was much higher than in the previous two years.
3.4. Time trend profiles and percentage changes of NO 2 , O3 and PM10 for pre-, during and post-lockdown and its relation with anthropogenic mobility
Mobility index (MI) of different human activities along with mean daily profiles of contaminants before (February 15th to March 13th ), during (March 14th to June 21st ) and after lockdown (June 22nd to August 31st ) were studied to evaluate the impact of the anthropogenic mobility on air contamination (Fig. 5). In addition, the percentage changes of average concentrations of contaminants during lockdown and after lockdown respect to the period of time before lockdown were calculated and are shown in Table 3. It can be observed that the levels vary according to urban, semi-urban and rural sampling stations, with the highest NO2 and PM10 values in urban areas linked to a heavier traffic and mobility indices.
Table 3
Average concentrations (µgm− 3) and standard deviations of NO2, O3 and PM10 for time periods March 14th-June 21st (during lockdown) and June 22nd -August 31st (post-lockdown) together with the percentages of change (lockdown versus pre-lockdown and post-lockdown versus lockdown).
|
February 15th- March 13th 2020 (pre- lockdown)
lockdown)
|
March 14th- June 21st 2020 (lockdown)
|
% of change
respect to
pre- lockdown
|
June 22nd- August 31st 2020 (post- lockdown)
|
% of change respect to
pre-lockdown
|
NO2
|
Gràcia
|
40.7 ± 5
|
21.5 ± 4
|
-47%
|
26.0 ± 3
|
-36%
|
Vall d’Hebron
|
27.7 ± 5
|
16.0 ± 4
|
-42%
|
18.8 ± 2
|
-32%
|
Granollers
|
38.0 ± 5
|
16.4 ± 4
|
-57%
|
20.2 ± 3
|
-47%
|
Fabra Observatory
|
10.3 ± 2
|
5.9 ± 2
|
-43%
|
8.5 ± 1
|
-17%
|
Manlleu
|
24.2 ± 2
|
10.5 ± 3
|
-57%
|
10.4 ± 2
|
-57%
|
Begur
|
4.9 ± 1
|
1.9 ± 0.4
|
-61%
|
2.2 ± 0.4
|
-55%
|
Bellver de Cerdanya
|
7.9 ± 2
|
2.9 ± 1
|
-63%
|
4.8 ± 2
|
-39%
|
Juneda
|
7.5 ± 1
|
5.5 ± 1
|
-27%
|
5.2 ± 1
|
-31%
|
O3
|
Gràcia
|
43.4 ± 5
|
61.6 ± 7
|
+ 42%
|
51.9 ± 4
|
+ 20%
|
Vall d’Hebron
|
54.1 ± 5
|
67.3 ± 6
|
+ 24%
|
62.5 ± 5
|
+ 16%
|
Granollers
|
35.0 ± 5
|
57.4 ± 7
|
+ 64%
|
56.4 ± 4
|
+ 61%
|
Fabra Observatory
|
73.3 ± 3
|
86.6 ± 9
|
+ 18%
|
85.3 ± 7
|
+ 16%
|
Manlleu
|
31.1 ± 7
|
46.8 ± 6
|
+ 50%
|
55.1 ± 6
|
+ 77%
|
Begur
|
67.5 ± 2
|
77.8 ± 9
|
+ 15%
|
78.1 ± 5
|
+ 16%
|
Bellver de Cerdanya
|
46.4 ± 7
|
51.4 ± 3
|
+ 11%
|
58.1 ± 7
|
+ 25%
|
Juneda
|
46.9 ± 12
|
58.0 ± 6
|
+ 24%
|
63.1 ± 6
|
+ 35%
|
PM10
|
Gràcia
|
28.3 ± 5
|
18.5 ± 3
|
-35%
|
22.8 ± 3
|
-19%
|
Vall d’Hebron
|
21.4 ± 3
|
13.0 ± 3
|
-39%
|
17.8 ± 2
|
-17%
|
Granollers
|
32.1 ± 4
|
19.5 ± 3
|
-39%
|
24.2 ± 2
|
-25%
|
Fabra Observatory
|
17.2 ± 3
|
12.5 ± 2
|
-27%
|
16.7 ± 2
|
-3%
|
Manlleu
|
32.1 ± 4
|
18.9 ± 4
|
-41%
|
23.0 ± 2
|
-28%
|
Begur
|
n.d.
|
n.d.
|
n.d.
|
n.d.
|
n.d.
|
Bellver de Cerdanya
|
13.2 ± 3
|
9.9 ± 3
|
-25%
|
15.1 ± 3
|
-14%
|
Juneda
|
21.3 ± 4
|
15.3 ± 2
|
-28%
|
20.8 ± 3
|
-2%
|
n.d.: no data available |
Figure 5a illustrates the changes in MI in terms of different human activities for the periods before, during and after lockdown in the three different regional areas where the air quality stations of this study are located (Barcelona, Girona and Lleida). It can be clearly observed that all the activities including transport, industries, social places, and educational sectors were running normally before lockdown (see curves in light-grey-shaded areas of Fig. 5a). However, after the beginning of the state of alarm and lockdown, the mobility index of all the human activities except for the residential (the latter showing an increment during lockdown) notably decreased (see curves in yellow-shaded areas of Fig. 5a). The decline of MI of human activities during the COVID lockdown reported in this study is in agreement with the findings of Zhang et al. 2020. In that study the authors evidenced the same MI trend not only in Spain but in other countries (i.e., United States, France, Italy, Germany, United Kingdom, India, Bangladesh and Pakistan), in which the MI of all human activities decreased a large extent (up to -90% of drop) while the MI for residential activities significantly increased (up to + 30% of increment) since the start of the pandemic.
In Catalonia, the decline of MI was maximum in April (up to 100% decrease in retail and recreation), when the strictest lockdown was produced, and started to recover right up to 21st of June, when the state of alarm finished and the “new normality” started (see curves in dark-grey-shaded areas of Fig. 5a). Interestingly, in Girona and Lleida, the activity in parks after the lockdown suffered a substantial increase (up to 400% in Girona and up to 250% in Lleida) whereas in Barcelona, all the different type of human activities returned to normal levels.
In Fig. 5b, daily averages (24 h means) of NO2, O3 and PM10 concentration (µg/m3) for the equivalent period of time (i.e., before, during and after lockdown) are represented.
Concerning NO2, averaged concentrations of this contaminant substantially decreased during lockdown period in 2020 in contrast to the same period of time in 2018 and 2019. Moreover, the differences in the amount of NO2 were evident when comparing the periods of time pre-lockdown, lockdown and post-lockdown during 2020. The percentages of decrease in the eight monitoring stations during the lockdown period respect to the pre-lockdown are shown Table 3 and followed this order: Bellver de Cerdanya (-63%) > Begur (-61%) > Manlleu and Granollers (-57%) > Gràcia (-47%) > Fabra Observatory (-43%) ~ Vall d’Hebron (-42%) and Juneda (-27%). The highest decrease in the two rural stations (Bellver the Cerdanya and Begur) is explained by the fact that they are widely populated in winter as the former is a ski resort and the latter a famous holiday and second residence emplacement and most houses are heated by gasoil or wood burning, which are emission sources of NO2 (Michael Alberts 1994; Saud et al. 2011). However, in both sites people were asked to return to their main residence during lockdown, which was reflected in a high decrease in NO2 levels. This did not happen in the third rural station (Juneda), since this is not a holiday spot. The urban and semi-urban areas had similar NO2 decrease during lockdown and reflect the decrease in mobility observed in all urban areas. As expected, in the period of time right after the end of the state of alarm (June 22nd to August 31st ), the levels of NO2 incremented in all stations, but in no case they returned to the pre-lockdown levels (see last column of Table 3). Moreover, during the lockdown in 2020, the WHOAQG (EUR-Lex) daily reference value of 40 µg/m3 was not exceeded in any site, although this standard value was exceeded in the three urban stations (Gràcia, Vall d’Hebron and Granollers) during the same period in 2018 and 2019. These results are in agreement with those reported by Baldasano, J.M. et al., who reported NO2 levels below the WHOAQG reference value during the second half of March 2020 in 24 stations located in Madrid and 9 stations placed in Barcelona.
Concentrations of O3 showed a substantial increase during lockdown, in the highly populated urban stations of Gràcia (+ 42%) and Granollers (+ 64%), and in the semi-urban station of Manlleu (+ 50%). In the rest of rural stations and in the control station, the registered percentages of change were lower, but still showing an increment of O3 respect to the pre-lockdown period: Juneda and Vall d’Hebron (+ 24%), Fabra Observatory (+ 18%), Begur (+ 15%) and Bellver de Cerdanya (+ 11%) (see Table 3). Increment in O3 levels during the lockdown is related to the reported diminution of NO2 levels and the suppression of the titration effect and was more evident in the most transited and populated stations: Gràcia (60300 inhabit/km2), Granollers (4121 inhabit/km2) and Manlleu (1194 inhabit /km2), see Table 1. Vall d’hebron, despite also being a populated station (7700 inhabit/km2), showed a lower increment of O3 since this station does not receive the direct impact of traffic. After the end of the state of alarm and the return to the “new normality”, with increased traffic and NO2 emissions, concentration of O3 started to decrease again, still showing percentages of increase respect to pre-lockdown levels but in a lesser extend (see last column of Table 3). During the lockdown, the WHOAQG reference value of 100 µg/m3 for O3 was slightly exceeded in one time in Observatory Fabra, and more times in previous years in Fabra Observatory and Begur.
Concerning PM10, concentrations of this contaminant during lockdown decreased in all stations, but in a minor extent in comparison to NO2. The percentages of decrease during the lockdown respect to the pre-lockdown were as follows: Manlleu (-41%) > Granollers and Vall d’Hebron (-39%) > Gràcia (-35%) > Juneda (-28%) ~ Fabra Observatory (-27%) and Bellver de Cerdanya (-25%) (no data for Begur, see Table 3). Thus, highest decrease was observed for the semi-urban station of Manlleu and the urban stations of Granollers, Vall d’Hebron and Gràcia. In the stations of Fabra Observatory, Vall d’Hebron, Bellver and Juneda, levels of PM10 during lockdown in 2020 were lower than the WHOAQG annual reference value of 20 µg/m3, in contrast to 2018 and 2019, when the reference value was exceeded. However, in Gràcia, Manlleu and Granollers, such reference value was slightly exceeded at some moments during the lockdown. The percentages of change and the levels of PM10 obtained in our study are in agreement with those reported by Tobías, A et al., in a study performed in two air quality stations in Barcelona. In that study the authors also reported PM10 levels slightly over the WHOAQG limit value in the station placed in the urban center of Barcelona, which suggests a location very similar to our Gràcia station.
Pearson’s correlation coefficients of percentages of change of contaminants in the stations located in Barcelona (i.e., Gràcia and Vall d’Hebron) respect to the mobility index, MI, in the same city were calculated for the period of time February 15th to August 31st and are summarized in Table 4. As it can be observed in the table, NO2 showed a positive correlation with MI both in Gràcia (+ 0.51) and Vall d’Hebron (+ 0.38), which may suggest that the diminution of NO2 levels was in a significant part caused by the MI reduction. In contrast, O3 showed a negative correlation both in Gràcia (-0.56) and Vall d’Hebron (-0.41), indicating that the diminution of human mobility and traffic depletion contributed in an increase of O3 levels in these two neighborhoods of Barcelona due to the lower titration effect. Finally, the correlation of PM10 with MI was, as which occurred with NO2, positive in the two locations, despite a bit lower (+ 0.41, in Gràcia and + 0.33, in Vall d’Hebron), also indicating that part of the diminution of PM10 contamination can be attributed to traffic restrictions during lockdown.
Table 4
Pearson’s correlation coefficient index among the mobility index (MI) and the percentage of change of contaminants for the period of time (February 15th - August 31st ).
|
NO2
|
O3
|
PM10
|
|
Pearson’s correlation coefficient
|
Pearson’s correlation coefficient
|
Pearson’s correlation coefficient
|
Gràcia
|
+ 0.51
|
-0.56
|
+ 0.41
|
Vall d’Hebron
|
+ 0.38
|
-0.41
|
+ 0.33
|
3.5. Hourly profiles and percentage changes of NO 2 , O3 and PM10 during strictest lockdown: April 2020 versus April 2019 and 2018
Detailed evaluation of air contamination changes during the strictest lockdown was performed, focusing the study on data from April 2020 and comparing them to data acquired in April 2019 and April 2018, the latter used as basal concentrations. With that purpose, for these periods of time, hourly profiles of the contaminants and their percentages of change were calculated and evaluated to determine the sources of pollution and human impacts.
Hourly average profiles are represented in the plots of Fig. 6, each plot containing information of one contaminant, one station and three years simultaneously (in blue data from 2018, in green data from 2019 and in red data from 2020). Average values and the associated standard deviations were calculated for each hour as the mean ± SD of all the month of April (n = 30) and are represented in Fig. 6 with continuous lines and shaded areas, respectively.
In order to obtain the percentages of change, the mean concentrations of each contaminant in each station were first calculated as averages of the whole month of April for each year (see Table 5). Then, the percentages of change were calculated as the % of variation among April 2019 versus April 2018 and April 2020 versus April 2019. The reason why the percentages of change were calculated in that way and not considering April 2020 versus April 2018 is the fact that, in most locations, air quality was higher in 2019 respect to 2018. The improvement in air quality observed in 2019 can be attributed to a combination of factors: on the one hand, the implementation of LEZ and on the other hand, the weather patterns of 2019.
Daily profiles calculated from hourly averages shown in Fig. 6 evidence that NO2 had similar hourly profiles in all stations, showing two maxima. The first maximum appeared between 8:00 and 10:00 am (two-hours delayed in Fabra Observatory), coincident with the rush traffic hour and, thus, can be assigned to the increasing fuel combustion by vehicles. It is interesting to stand out that despite the lockdown and the traffic depletion, this maximum was still observed. The second maximum, a bit lower and wider, appeared around 22:00 pm in all stations. However, mean ranges of NO2 differed among stations. Higher levels were registered in highly populated urban stations of Gràcia, Vall d’Hebron and Granollers (~ 10–60 µgm− 3), followed by semi urban station of Manlleu and control site Fabra Observatory (~ 5–30 µgm− 3), ending with rural stations of Begur, Bellver de Cerdanya and Juneda (~ 2–15 µgm− 3). Thus, we observed a correlation between the NO2 levels and the density of population of the air quality stations, the latter provided in Table 1. When comparing amounts of NO2 among 2018 and 2019, in three stations (i.e., Gràcia, Vall d’Hebron and Fabra Observatory) amount of NO2 decreased, in Granollers’ station there were no differences (i.e., 0% of change) among these two years and in four stations (Manlleu, Begur, Bellver de Cerdanya and Juneda) there was an increment in NO2 levels. In contrast, there was a uniform tendency in % of change of NO2 levels among April 2020 versus April 2019 (see Table 5): in all stations the amount of this contaminant was lower in 2020 (under pandemic lockdown) respect to the same period of time in 2019 (under no pandemic). In particular, the percentages of change from higher to lower were as follows: Bellver de Cerdanya (-63%) ~ Fabra Observatory (-62%) > Granollers (-52%) > Gràcia (-45%) ~ Begur (-44%) > Manlleu (-38%) > Vall d’Hebron (-33%) > Juneda (-23%). As previously observed in Sect. 3.4., the rural station of Bellver de Cerdanya showed the highest relative decrease of NO2, again presumably due to the ceasing hotel and ski resort activities during eastern holidays. These changes in the concentrations of NO2 in the Bellver de la Cerdanya rural station are however only in relative terms and local. Absolute changes show that the NO2 concentrations depletion was much more important in the Barcelona urban area than in the rural areas due to the lockdown situation. Moreover, the weather conditions of April 2020 in Barcelona urban area favored the cleansing of the atmosphere, including NO2 gases, as they were especially rainy. The decrease of NO2 reported in this study due to meteorological and lockdown restrictions is in accordance to previous air quality monitoring studies performed in the cities of Barcelona and Madrid (Baldasano 2020).
Moreover, in all stations NO2 depletion was more evident in the second maximum and in general for the second part of the day (12-24h). In addition, it is worthy to stand out that in all stations, NO2 concentration levels showed significantly lower standard deviation in 2020 respect to the previous years (narrowed red-shaded areas in Fig. 6). In the lockdown period, the WHOAQG annual reference value of 40 µg/m3 was not exceeded in any site, whereas in previous years it was exceeded in Gràcia, Vall d’Hebron and Granollers stations (see Fig. 6), as previously observed when comparing the whole pre-, lockdown and post-lockdown period for the three years (Sect. 3.3).
Hourly average profiles of O3 showed a marked minimum between 8:00 and 10:00 am (again two-hours delayed in Fabra Observatory), coincident with the maximum NO2 concentration, a maximum around 16:00 pm, coincident with the increase of solar radiation and simultaneous to the NO2 minimum between the two maxima, and a minimum around 22:00 pm, coincident with the second NO2 maximum. The latter increase of O3 at night can be attributed to the suppression of the titration effect (see Fig. 2).
Mean ranges of O3 also varied among stations. Contrarily to NO2, higher levels of O3 were registered in Fabra Observatory and Begur stations (~ 60–120 µgm− 3), followed by Gràcia, Vall d’Hebron, Bellver de Cerdanya and Juneda (~ 20–100 µgm− 3), and finally with Granollers and Manlleu (~ 0-100 µgm− 3). When comparing O3 levels among 2018 and 2019 we observed that there was already an increment in ozone in April 2019 respect to April 2018. Such increment was registered in all stations except for Begur, where a slightly decrease was detected. Differences in O3 in April 2020 versus 2019 showed two different tendencies. In two stations the amount of O3 was higher in April 2020 and the percentages of change, from higher to lower, were as follows: Gràcia (+ 12%) > Granollers (+ 3%). However, for the remaining six stations, the amount of O3 was lower in April 2020 respect to the previous year, in the following order: Bellver de Cerdanya (-27%) > Manlleu (-18%) > Juneda (-16%) > Begur (-14%) > Vall d’Hebron (-9%) and Fabra Observatory (-5%). It is important to highlight that the increase produced in Gràcia (and in a lesser extend in Granollers) occurred in the second part of the day (12-24h, see Fig. 6), coincident with the previously reported decrease of NO2. In the lockdown period, the WHOAQG 8-hour reference value of 100 µg/m3 was not exceeded in any site, whereas in previous years it exceeded in Fabra Observatory and Begur stations (see Fig. 6).
PM10 hourly profiles showed a clear increase between 8:00 and 10:00 am in most of stations (Gràcia, Granollers, Manlleu, Bellver de Cerdanya and Juneda). Mean ranges of PM10 were similar for all the stations (~ 10–50 µgm− 3), except for the control site (Fabra Observatory), which registered the lowest levels (~ 5–30 µgm− 3). The comparison among years evidenced a decrease of PM10 in 2020 respect to 2019 in all stations, despite the diminution in Bellver de Cerdanya was little. Larger diminution was registered in the three more transited urban stations: Vall d’Hebron, showing a percentage of diminution of -60%, Gràcia, with a diminution of -25% and Granollers of -26%. This is due to the fact that PM levels are very dependent on the traffic influence (dust resuspension, erosion of road pavements and brakes), and during the lockdown, the density of vehicles in the city of Barcelona decreased: -90% in public transport, -95% in taxis and − 87% in bicycles and other personal mobility vehicles (see Sect. 3.2 of this manuscript). Lower percentages of decrease of PM10 in April 2020 respect to April 2019 were registered in the other stations of Juneda (-23%), Fabra Observatory (-21%) Manlleu (-18%) and Bellver de Cerdanya (-4%). No data of concentration of PM10 in Begur station in April 2020 were available and thus, their percentage of change could not be calculated. Moreover, in the lockdown period, the WHOAQG daily reference value of 50 µg/m3 was not exceeded in any site, and the annual reference value of 20 µg/m3 was only slightly exceeded among 10–12 hours in Gràcia, Granollers, Manlleu and Juneda, while highly exceeded in the same stations and also in Vall d’Hebron and Bellver de Cerdanya in previous years (see Fig. 6).
There are quite a few other studies concerning changes in air quality during the COVID lockdown in many areas throughout the globe (Menut et al. 2020; Ropkins and Tate 2021; Filonchyk et al. 2021), and most of them report NO2 diminution, small increase in O3 and PM10 diminution; the latter being generally a modest depletion in comparison to that of NO2. For instance Menut et al. 2020, reported a large reduction in NO2 concentrations, a lower reduction in particulate matter and a mitigated effect on ozone concentrations over western Europe. Filonchyk et al. 2021, reported reductions of tropospheric NO2 approximately by -10 to 19%, and reductions of PM10 from − 8.5 to -33.9% in 2020 respect to 2019, in Poland, eastern Europe. Also Ropkins and Tate 2021, reported NO2 decreased from − 32 to -50% and O3 increase by + 20% across the United Kingdom. These findings are in accordance to the ones obtained in the present study. Therefore, the results hereby presented confirm the improvement of air quality due to the lockdown that has been observed worldwide, in the region of Catalonia (Spain).
However, a more exhaustive analysis of the acquired data using multivariate statistical and chemometric methods is pursued with the goal of the apportionment of the different sources of the three investigated air quality parameters (NO2, O3 and PM10) and to describe how their temporal and geographical profiles changed during COVID-19. The results of this more exhaustive analysis will be hopefully reported when the COVID-19 pandemic situation finishes.
Table 5
Average concentrations (µgm− 3) and standard deviations (n = 30) of NO2, O3 and PM10 for April 2018, April 2019 and April 2020 together with the percentages of change (April 2019 versus 2018 and April 2020 and 2019).
|
Average
April 2018
|
Average
April 2019
|
Average
April 2020
|
% of change
2019 vs 2018
|
% of change
2020 vs 2019
|
NO2
|
Gràcia
|
49.2 ± 13
|
36.1 ± 10
|
19.7 ± 5
|
-27%
|
-45%
|
Vall d’Hebron
|
32.1 ± 10
|
25.7 ± 9
|
17.3 ± 6
|
-20%
|
-33%
|
Granollers
|
29.7 ± 7
|
29.7 ± 9
|
14.3 ± 5
|
0%
|
-52%
|
Fabra Observatory
|
13.7 ± 3
|
13.2 ± 2
|
5.0 ± 1
|
-4%
|
-62%
|
Manlleu
|
15.2 ± 3
|
16.5 ± 4
|
10.2 ± 2
|
+ 9%
|
-38%
|
Begur
|
3.0 ± 1
|
3.4 ± 1
|
1.9 ± 0.5
|
+ 13%
|
-44%
|
Bellver de Cerdanya
|
7.0 ± 1
|
7.8 ± 1
|
2.9 ± 1
|
+ 10%
|
-63%
|
Juneda
|
6.3 ± 2
|
8.2 ± 2
|
6.3 ± 1
|
+ 30%
|
-23%
|
O3
|
Gràcia
|
50.9 ± 23
|
61.1 ± 20
|
68.2 ± 20
|
+ 20%
|
+ 12%
|
Vall d’Hebron
|
62.1 ± 23
|
77.2 ± 25
|
70.6 ± 20
|
+ 24%
|
-9%
|
Granollers
|
55.5 ± 25
|
63.2 ± 31
|
64.9 ± 21
|
+ 14%
|
+ 3%
|
Fabra Observatory
|
88.8 ± 7
|
97.3 ± 8
|
92.2 ± 9
|
+ 10%
|
-5%
|
Manlleu
|
52.8 ± 19
|
60.1 ± 26
|
49.2 ± 18
|
+ 14%
|
-18%
|
Begur
|
101.0 ± 6
|
96.6 ± 7
|
83.2 ± 7
|
-4%
|
-14%
|
Bellver de Cerdanya
|
67.9 ± 18
|
70.2 ± 19
|
51.3 ± 13
|
+ 4%
|
-27%
|
Juneda
|
60.0 ± 23
|
68.9 ± 26
|
58.0 ± 23
|
+ 15%
|
-16%
|
PM10
|
Gràcia
|
31.7 ± 19
|
22.5 ± 10
|
16.8 ± 8
|
-29%
|
-25%
|
Vall d’Hebron
|
23.6 ± 13
|
27.2 ± 18
|
11.0 ± 6
|
+ 15%
|
-60%
|
Granollers
|
27.3 ± 15
|
23.8 ± 9
|
17.7 ± 6
|
-13%
|
-26%
|
Fabra Observatory
|
n.d.
|
15.4 ± 9
|
12.1 ± 7
|
n.d.
|
-21%
|
Manlleu
|
23.1 ± 13
|
18.4 ± 9
|
15.1 ± 7
|
-20%
|
-18%
|
Begur
|
n.d.
|
10.2 ± 5
|
n.d.
|
n.d.
|
n.d.
|
Bellver de Cerdanya
|
17.3 ± 13
|
10.4 ± 8
|
10 ± 6
|
-40%
|
-4%
|
Juneda
|
23.5 ± 17
|
18.2 ± 12
|
14.0 ± 7
|
-23%
|
-23%
|
n.d.: no data available |