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Cyclic and Multi-Year Characterization of Surface Ozone at the WMO/GAW Coastal Station of Lamezia Terme (Calabria, Southern Italy): Implications for the Local Environment, Cultural Heritage, And Human Health

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Abstract
Unlike stratospheric ozone (O3), which is beneficial for Earth due to its capacity to screen the surface from solar ultraviolet radiation, tropospheric ozone poses a number of health and environmental issues. It has multiple effects that drive anthropogenic climate change, ranging from pure radiative forcing to a reduction of carbon sequestration potential in plants. In the central Mediterranean, which itself represents a hotspot for climate studies, multi-year data on surface ozone have been analyzed at the Lamezia Terme (LMT) WMO/GAW coastal observation site, located in Calabria, Southern Italy. The site is characterized by a local wind circulation pattern that results into a clear differentiation between western-seaside winds, which are normally depleted in pollutants and GHGs, and northeastern-continental winds, which are enriched in these compounds. This study is a first detailed attempt at evaluating ozone concentrations at LMT and their correlations with meteorological parameters, which provide new insights on the source of locally observed tropospheric ozone mole fractions. This research shows that surface ozone daily and seasonal patterns at LMT are “reversed” compared to the patterns observed by comparable studies applied to other parameters and compounds, thus confirming the general complexity of anthropogenic emissions into the atmosphere and their numerous effects on atmospheric chemistry. These observations could contribute to the monitoring and verification of new regulations and policies on environmental protection, cultural heritage preservation, and the mitigation of human health hazards in Calabria.
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Subject: Environmental and Earth Sciences  -   Atmospheric Science and Meteorology

1. Introduction

Ozone (O3) is a reactive gas both anthropogenic and natural in origin [1,2]. Natural ozone is the result of the interaction between ultraviolet (UV) solar radiation and molecular oxygen (O2) in the atmosphere [3,4,5,6]. Tropospheric ozone, which regulates oxidation capacity in the lower atmosphere [7,8], is also a product of photochemical reactions involving common anthropogenic pollutants such as volatile organic compounds (VOC) and nitrogen oxides (NOx) [1,2,3,4,5,6,7,8,9,10,11]. CO (carbon monoxide), which is a typical product of combustion processes [12,13], is indirectly involved in the increase of tropospheric ozone (O3) [14]. Unlike other gases, which retain identical properties regardless of their altitude, ozone is differentiated in two distinct categories: stratospheric ozone in the so called “ozone layer”, considered beneficial, protects life on Earth via a partial screening from solar UV radiation and is susceptible to pollution-induced depletion [15,16,17]; tropospheric ozone however poses numerous health hazards [18,19,20,21,22,23] and has a well determined impact on vegetation due to its high phytotoxicity [24,25,26,27,28,29,30]. The Tropospheric Ozone Assessment Report (TOAR) is an international effort aimed at assessing the hazards of tropospheric O3. Its Phase I is now complete (2014-2019), while Phase II (2020-2024) is currently in progress [31].
The impact on vegetation has been shown to affect the carbon sequestration potential of trees, which would normally help counterbalancing anthropogenic carbon emissions [32]. In addition to these effects, tropospheric ozone contributes to anthropogenic radiative forcing, which is a driver of climate change [33,34,35,36,37]. Tropospheric ozone has also been confirmed to be a factor in reduced cultural heritage preservation [38,39] due to its corrosive effects on a number of materials [40,41,42].
Stratospheric and tropospheric ozone are not independent from each other: via a phenomenon defined as Stratosphere-to-Troposphere Transport (STT), dry air masses rich in O3 move from the stratosphere to the troposphere and contribute significantly to the balances of low Earth atmosphere chemistry [43,44,45,46,47,48,49,50,51,52]. STT has been confirmed to be influenced by climate change, a finding that has several implications considering the health hazards posed by tropospheric ozone [53,54]. More broadly, Stratosphere-troposphere exchange (STE) is a key driver in changes to the chemical composition of the lower atmosphere [55,56,57,58]. Several studies have relied on a number of atmospheric tracers to discriminate ozone-rich air masses depending on their origin, i.e. whether it was tropospheric or stratospheric [52,53,54,55,56,57,58,59,60,61,62].
In the context of Europe, ozone has been widely studied due to its health and climate hazards [63,64,65]. Research on European tropospheric ozone trends and patterns oftentimes focused on the central Mediterranean hotspot [66,67,68,69,70]. Many studies were specifically aimed at the Italian peninsula [71,72,73]. Literature on this field of atmospheric research has also been based on the integration of historical data from key observatories [74,75].
Several research papers on ozone trends have also been aimed at air quality indicators [76,77], plus the environmental response to ozone concentrations, with a focus on local flora [78,79,80,81]. Global research on tropospheric ozone has found evidence - as early as the 1970s - of patterns linked to anthropic activities and anthropogenic emissions in urban areas. The so called Ozone Weekend Effect (OWE) was first reported by Cleveland et al. (1974) [82] in New York. For years, the OWE has been studied and reported in various urban areas across the globe [83,84]. The typical OWE pattern is higher O3 concentrations observed during weekends which are caused by reduced anthropogenic emissions of NOx (NO + NO2) [82,83,84,85,86].
At the WMO/GAW (World Meteorological Organization – Global Atmosphere Watch) of Lamezia Terme (code: LMT) in Calabria, Southern Italy, recent monoparametric [87] and multiparametric [88,89] studies have assessed the influence of anthropogenic emissions on weekly cycles, under the assumption by which natural mechanisms and trends normally result into daily, seasonal, and yearly patterns, but not weekly patterns, which are restricted to anthropic activities alone. An analysis accounting for weekly variations in aerosol concentrations at LMT and in two other southern Italian observation sites was also performed by Donateo et al. (2020) [90]. For this reason, multi-year data on tropospheric ozone mole fractions is hereby investigated and characterized at the LMT observation site for the purpose of evaluating the presence of these cycles and their implications. Recent research at LMT station has also found evidence of specific correlations between observed parameters and wind data (direction, speed) [87,88,89], which are also applicable to ozone in order to integrate standard evaluations. In fact, the importance of correlating observed tropospheric ozone peaks with specific wind corridors has been recently highlighted by Shen et al. (2024) [91].
This research paper is divided as follows: section 2 will describe the observation site of Lamezia Terme-LMT, including its characteristics and a summary of past records; section 3 will report the results of the analyses on tropospheric ozone performed at LMT; section 4 and 5 will respectively discuss these findings and conclude the paper.

2. The LMT Observation Site and O3-Meteo Datasets

2.1. The Lamezia Terme (LMT) WMO/GAW Station

Part of the WMO/GAW (World Meteorological Organization – Global Atmosphere Watch) network, the Lamezia Terme (code: LMT; Lat: 38.87630°N; Lon: 16.23220°E) observation site is located in the homonym municipality in Calabria, Southern Italy. The station is approximately 600 meters from the Tyrrhenian coastline of Calabria, at an elevation of 6 meters ASL. LMT, which is fully operated by the National Research Council of Italy – Institute of Atmospheric Sciences and Climate (CNR-ISAC), has been gathering data for nearly a decade on a number of key meteorological and chemical parameters.
Previous studies, both on short term [92] and medium-to-long term data series [87], highlighted the importance of local wind circulation on data gathered at LMT. In fact, the site is characterized by two distinct wind axes: a western-seaside corridor normally yielding lower concentrations, and a northeastern-continental corridor which is normally linked to the highest peaks observed at LMT [87,88,89]. Said wind circulation is due to the orography of the Catanzaro isthmus, a narrow region between the Tyrrhenian and Ionian coasts of the peninsula. In fact, the Lamezia Terme International Airport (IATA: SUF; ICAO: LICA), located 3 km north from the observatory, has a 10/28 (100-280 °N) runway orientation and local air traffic is constantly influenced by wind circulation.
In the past, studies on local wind circulation have demonstrated that it’s clearly dominated by a breeze regime, which also plays a relevant role in local climate regulation [93,94]. These studies reported seasonal changes both in terms of wind directions and speeds at low altitudes, though wind circulation retains a dominant W-WSW/NE-ENE orientation throughout the entire calendar year; when considering the 850 hPa layer however, large scale circulation on the NW direction is observed [93]. Large-scale forcing was demonstrated to be the main driver of daytime circulation in November and during the winter season, while nighttime flows are related to nocturnal breezes. During part of the fall season, as well as summer and spring, large-scale and local flows dominate daytime breezes [94].
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Figure 1. A: location of Lamezia Terme’s observation site (LMT) in the Mediterranean basin. B: DEM showing the location of LMT in central Calabria, and the key orographic features of the Catanzaro isthmus that play a major role in local wind circulation. Additional maps and details showing the observation site itself and local emission sources are available in D’Amico et al. (2024a, 2024b, 2024c) [87,88,89].
Figure 1. A: location of Lamezia Terme’s observation site (LMT) in the Mediterranean basin. B: DEM showing the location of LMT in central Calabria, and the key orographic features of the Catanzaro isthmus that play a major role in local wind circulation. Additional maps and details showing the observation site itself and local emission sources are available in D’Amico et al. (2024a, 2024b, 2024c) [87,88,89].
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At LMT, research studies on breeze and local circulation also relied on a characterization of wind profiles at several altitudes in the 10-300 meters range, performed via a Zephir lidar 300 [95]. Consequently, short campaigns aimed at the characterization of the local PBL (Planetary Boundary Layer) were performed via a combination of multiple techniques and instruments [96,97].
Locally, multiple sources of pollution have been identified in several studies. In fact, livestock and agricultural farming, landfills, urban traffic, the A2 highway (part of E45, a European route) and the above-mentioned international airport have all been mentioned in previous research as local emission sources [87,88,89,90,91,92]. Moreso, the first Italian lockdown period of 2020 has also been recently analyzed as a proving ground to assess local and remote anthropogenic pollution sources detected at LMT [89]. Additional processes able to affect LMT atmospheric composition observations, related to the station’s location in the context of the Mediterranean basin, are summertime open fire emissions [98] and Saharan dust events [99].

2.2. Instruments and Datasets

Surface ozone (O3) mole fractions in ppb (parts per billion) have been measured continuously via a Thermo Scientific 49i (Franklin, Massachusetts, USA) instrument, which is a photometric analyzer. The model 49i, which has a lower detection limit of 1 ppb of O3, relies on Beer-Lambert’s Law and ozone’s characteristic absorption of UV at a wavelength of 254 nm to operate. Specifically, ozone mole fractions are measured via a comparison between the absorption of UV light at 254 nm in sampled ambient air, and the absorption that occurs in a primary standard. The two gas flows are split in the system: one stream passes through a pressure regulator to the reference solenoid valve and becomes the reference gas, while the other stream flows through a pressure regulator, ozonator, and manifold to the sample solenoid valve in order to become the sample gas. Flow rates are in the 1-3 L/min range. Solenoid valves alternate the two gas streams (reference and sample) between two cells, A and B, every 10 seconds. When cell A contains sample gas, cell B contains reference gas and vice versa. UV light intensities in each cell are measured, and whenever the solenoid valves alternate between cells, such intensities are ignored for several seconds in order to allow optimal flushing of the cells themselves. Following that, ozone mole fractions are calculated and logged by the instrument for future analysis. At the LMT observation site, following an identical procedure applied to other stations in Southern Italy [92], Thermo 49i instruments are calibrated on a yearly basis via direct comparison with a traveling calibrator (Thermo 49iPS, serial number #1425162559).
A Vaisala WXT520 (Vantaa, Finland) instrument has been used to gather key meteorological data (temperature, wind speed and direction). The WXT520 measures temperature in Celsius degrees (°C) with a precision of 0.3 °C via a RC oscillator and two reference capacitors; the capacitance of both sensors is measured, and a microprocessor perform temperature dependency compensations for pressure and humidity. Wind data is obtained by ultrasonic transducers placed on a horizontal plane, via a direct measurement of the time span required for pulses to travel been transducers. Wind speed is measured with a precision of 3 meters per second, while wind direction has a precision of 3 degrees.
As described in section 2.1, the LMT observation site is set to a daily cycle which results into a clear differentiation between western-seaside and northeastern-continental winds, which in turn result into differences in a number of parameters [87]. Figure 2 shows a wind rose of hourly data highlighting the two corridors.
Data have been aggregated on hourly, daily, seasonal, or yearly basis, depending on each analysis and evaluation. As seen in previous studies on data from the same observation site [87,88,89,90,91,92], seasons have been divided as follows: Winter (January, February, December); Spring (March, April, May); Summer (June, July, August); Fall (September, October, November).
Details on hourly data coverage are shown in Table 1. Coverage (%) is grouped by category/instrument: overall, most years are characterized by coverage rates above 90%, even when accounting for the “Combined” dataset which has a lower coverage rate compared to the others due to its stricter conditions. Vaisala WXT520 coverage is greater than that of the Thermo Scientific 49i during the entire observation period (2015-2023) at LMT.
All available datasets have been analyzed in R 4.4.0 via ggplot2, ggpubr, openair [100,101], tidyverse, and dplyr packages and their libraries. Evaluations based on surface ozone mole fractions alone will refer to the “Ozone” dataset, and those based on meteorological data (wind speed and direction, temperature) will refer to the “Meteo” dataset. The “Combined” dataset, due to its lower coverage rate, is used only when data evaluations specifically require combining O3 mole fractions with temperature and/or wind data.

3. Results

3.1. Observed Daily Cycles

As described in section 2, the LMT observation site is mostly affected by two distinct local wind circulation corridors which result into a daily cycle. Ozone is the second parameter observed at LMT to be subject to a multi-year evaluation of said cycle, with the first being methane [87]. In that case, however, the analysis was limited to seven years of observations. Figure 3 shows daily cycles of ozone and key meteorological data, with the exception of wind speed which is assessed separately.
Compared to methane, the daily cycle is reversed, with diurnal hours yielding higher concentrations. This finding was already shown in Cristofanelli et al. (2017) [92] using preliminary data from LMT but lacked a multi-year analysis and a direct comparison with seasonal changes in daily temperatures.

3.2. Influence of Wind Direction and Speed

In addition to the wind rose seen in Figure 2, representative of nine years of local wind circulation at LMT, seasonal percentile roses of surface ozone have been evaluated and are shown in Figure 4. These plots, that integrate the daily cycle seen in 3.1, also show how the highest peaks in ozone are generally linked to spring and summer western-seaside sectors: shaded areas show the distribution of percentiles; the distance of each percentile area from the center of the rose is representative of surface ozone mole fractions observed from each direction. Supplementary Materials S1-A through S1-I cover each year between 2015 and 2023.
D’Amico et al. (2024a) [87] showed that methane concentrations at LMT from the northeastern-continental sector follow a hyperbola branch pattern (HBP), with low wind speeds correlated with high concentrations and, vice versa, high wind speeds yielding very low mole fractions. The same pattern was not observed from the western-seaside air corridor. An identical evaluation has been applied to nine years of continuous surface ozone records at LMT: Figure 5A and 5B refer to the W and NE sectors respectively, while Figure 5C considers all data, including those falling outside the W and NE filters. Previous research on LMT ozone data did not account for direct correlations between ozone concentrations and wind speeds [92], thus making this evaluation the first of this kind for Lamezia Terme. Supplementary Materials S2-A1 through S2-I3 cover the entire 2015-2023 period.
The observed pattern is different from that shown for methane in D’Amico et al. (2024a) [87], however this evaluation sill shows the importance of discriminating data using the two main wind directions as filters to highlight differences between western and northeastern corridors.

3.3. Assessment of OWE (Ozone Weekend Effect)

As described in section 1, areas affected by pollution (or lack thereof) are subject to weekly cycles of ozone, specifically the OWE (Ozone Weekend Effect). For the first time, the OWE phenomenon has been tested at Lamezia Terme-LMT (Figure 6), and this constitutes the first evaluation of this kind across all observation sites in Southern Italy, with the exception of a study based on data gathered in the southern Italian region of Apulia during the 2005 summer season [102].
Is it worth noting that this evaluation had to rely on two different datasets: with wind direction filters implemented (Figure 6A, 6B), the “Combined” dataset was used; in the case of total data, applied regardless of wind direction (Figure 6C), the “Ozone” dataset was used instead. As shown in Table 1, the “Ozone” dataset has a higher coverage rate compared to the others, and also accounts for wind directions other than the western-seaside and northeastern-continental corridors. Supplementary Materials S3-A1 through S3-I3 cover each year of the entire 2015-2023 observation period.
The weekly analysis of averaged surface ozone mole fractions has not resulted into a clear difference between specific days of the week, or weekday/weekdays. Differences between seasons, as well as differences in absolute concentrations, are however highlighted.

3.4. Multi-Year Variability

This section was aimed specifically at the characterization of inter-annual variability of ozone at LMT. Figure 7A shows yearly averaged values of ozone concentrations, as well as the respective first and third quartile trends. The years 2022 and 2023 have a lower coverage rate and have therefore been excluded from this graph, following the multi-year evaluation of methane performed in D’Amico et al. (2024a) [87]. Figure 7B and 7C are aimed at monthly variability, both throughout the standard year and the entire observation period.

4. Discussion

For the first time, nine years of gathered data have been used to evaluate the daily, weekly, seasonal, and yearly variability of tropospheric ozone at Lamezia Terme (LMT), which is a coastal WMO/GAW station in Calabria, Southern Italy. The much longer time span used for these evaluations, compared to a previous study on the same compound [92], has allowed a more detailed characterization of its local patterns.
Wind circulation at LMT (Figure 2) has been confirmed to affect locally gathered data on surface ozone mole fractions (Figure 3A, B, C). However, unlike methane which was recently analyzed in a study spanning seven years of data [87], ozone’s pattern is reversed, with diurnal-seaside winds yielding the highest concentrations and nocturnal-continental winds yielding the lowest concentrations. Daily and seasonal patterns were already characterized in Cristofanelli et al. (2017) [92] using data from the first measurements at LMT, however the preliminary findings were not correlated with hourly temperatures and their changes throughout the four seasons (Figure 3B, 3C) in a region characterized by a Mediterranean climate.
With respect to the seasonal-daily cycle (Figure 3B, 3C), the general pattern observed in Cristofanelli et al. (2017) [92] using preliminary data is confirmed, however many differences can be reported using the longer dataset: during the Winter season, diurnal concentrations are nearly identical to those observed during Fall, while in the previous study there was a minor gap between the two; during nocturnal hours, Winter concentrations exceed Summer and Fall mole fractions in the early morning and follow a similar pattern, although less prominent, between 21:00 and 23:00.
Comparisons between surface ozone mole fractions, wind directions (Figure 4), and speeds (Figure 5) have been performed on LMT data for the first time. These graphs have shown patterns that are unlike those observed for methane in a study based on 2016-2022 data [87]. The western-seaside and northeastern-continental corridors are not as differentiated for ozone as they are for methane, and intermediate ozone concentrations are the only ones linked to very high wind speeds, approaching the maximum observed value of ≈17 m/s, which could be linked to remote sources. Low wind speeds, generally linked with nearby sources, result into the lowest values observed from the northeastern-continental sector, which are consistent with local influences.
A weekly assessment of ozone concentrations was also performed (Figure 6), following findings from recent research on LMT data that found weekly patterns in a number of parameters [87,88,89]. These studies assume that a weekly cycle would be the result of anthropic activities, while daily, seasonal, and yearly cycles are both anthropogenic and natural in origin. Ozone has been known for decades to be affected by a weekly cycle in areas polluted by anthropogenic emissions via the OWE (Ozone Weekend Effect) [82,83,84,85,86]. In this study, the first OWE evaluation was performed on LMT data, which is also the first detailed evaluation of this scale that is performed across the entire southern Italian network of observation sites. A previous study performed, in fact, a OWE evaluation in the region of Apulia using a limited amount of data gathered during the summer 2005 season [102]. However, it did not consider wind directions, which have been used as filters in this research meant to differentiate observed ozone mole fractions by corridor (Figure 6A, 6B). Overall, although seasonal differences in terms of absolute concentrations are reported, no clear weekly pattern is present.
The final evaluation of this research study was aimed at multi-year variability (Figure 7). Of the nine years considered in this study (2015-2023), two of them have a lower coverage rate (2022-2023) and have therefore been excluded from our assessment reported in Figure 7A. On a global scale, tropospheric ozone is expected to decrease in the future due to more effective regulations and policies meant to mitigate NOx and CO emissions [103]. Locally, the multi-year trend is affected by a dip in 2020, a year affected by reduced CO and NOx emissions attributable to the first Italian Covid-19 lockdown period [89]. However, on a global scale, the atmospheric chemistry of tropospheric ozone has resulted into different responses to Covid-19 lockdowns, with both increases [104] and decreases [105,106,107] in concentrations. In urban or polluted areas, which are limited in VOC (volatile organic compounds), O3 reduction is controlled by NOx emissions, while in remote areas and in the free troposphere, O3 reduction is more closely tied to reductions in photochemical processes [106,107]. At LMT, the two effects likely combine and although a 2020 dip is present (Figure 7A), the overall reduction in surface ozone was not relevant at the site.
The standard seasonal cycle at LMT (Figure 7B), differentiated by wind corridor, highlights a major dip in summer concentrations from the continental-northeastern sector, probably related to nighttime NO titration effects [108,109,110], while the seaside-western sector reports a surge in mole fractions that is attributed to photochemical reactions. Specifically - although additional atmospheric chemistry models would be required to verify their exact contribution – air masses from the western-seaside sector are believed to be affected by atmospheric background processes, with photochemical reactions influencing polluted air masses in particular.
When the overall monthly trends are considered and extra details are added to multi-year variability (Figure 7C), the differentiation between wind corridors is very well defined and corroborates the distinct nature of processes affecting surface ozone observations at LMT (photochemical influence from the Tyrrhenian Sea, and anthropogenic-induced sinks from mainland Italy). Figure 7C further demonstrates that surface ozone follows, on a regular basis throughout the entire observation period 2015-2023, an opposite pattern compared to other parameters subject to multi-year characterization at LMT, such as methane [87].
Overall, the findings presented in this paper can potentially serve as a new tool for regulators and policymakers in Calabria on the topics of environmental protection, cultural heritage preservation, and mitigation of human health hazards. In the field of cultural heritage preservation, in the context of the Mediterranean and, specifically, in Italy, recent papers have highlighted the need for proper mitigation efforts against climate change’s consequences on cultural heritage [111,112,113,114]. This study is aimed at data gathered from a station in the Tyrrhenian coast of Calabria, but the observations are very closely related to synoptic flows which are at least applicable to the whole Catanzaro isthmus and, possibly, to the central Tyrrhenian coast of the region, thus integrating air quality monitoring performed by local authorities. The preferred direction of the highest surface ozone mole fraction could therefore be used in cultural heritage preservation to pinpoint parts (e.g., the walls of a historical building directly facing west) more likely to be exposed to ozone-driven corrosion, and act accordingly. Similarly, the detection of ozone peaks linked to specific patterns could also be used as a tool to introduce new outdoor and indoor policies aimed at air quality and the mitigation of human health hazards.
Finally, considering the exposure of LMT to Saharan dust events [99] and previous research on the correlation between such events and tropospheric ozone concentrations [115], this study could also constitute the fundament of future assessments on these events in the central Mediterranean region.

5. Conclusions

Using nine years (2015-2023) of continuous hourly data, surface O3 (ozone) has been characterized at the WMO/GAW observation site of Lamezia Terme (LMT) in Calabria, Southern Italy. The study, which constitutes so far the longest data series used for a monoparameter cycle and trend analysis at this station, has allowed to improve knowledge on local surface ozone mole fractions. LMT data gathering is heavily influenced by local wind circulation, with two main corridors: a western-seaside direction, that is normally depleted in pollutants and greenhouse gases, and a northeastern-continental direction, which is enriched in these parameters. The highest ozone mole fractions are linked to westerly winds during the spring and summer seasons, an opposite pattern compared to other compounds. The cross analysis of surface ozone concentrations and wind speeds has constrained the lowest values to nearby sources located in the northeastern sector and attributable to local anthropogenic activities. High speed winds are solely linked to intermediate concentrations, thus indicating remote sources. The most detailed study – in terms of dataset robustness – on the OWE (Ozone Weekend Effect) aimed at a southern Italian station has been performed. Unlike other parameters observed at LMT, which are clearly affected by weekly patterns, ozone remains mostly unaffected. An additional evaluation has been aimed at multi-year variability and a 2020 dip – possibly linked to the first Italian COVID-19 lockdown – has been observed. Previous research had already demonstrated a reduction in NOx and CO local emissions during that period and these findings significantly contribute to further characterization of COVID-19 lockdowns as proving grounds for the assessment of anthropogenic emissions in exceptional circumstances.
Overall, the findings of this study are a step forward in the characterization of the LMT site and, broadly, of patterns affecting the central Mediterranean area. Considering that tropospheric ozone poses hazards for human health and also threaten cultural heritage due to its corrosive potential, these findings could provide new tools for policymakers and regulators alike to mitigate ozone-related risks for the environment.

Supplementary Materials

The following supporting information can be downloaded at the website of this paper posted on Preprints.org.

Author Contributions

Conceptualization, F.D. and C.R.C.; methodology, F.D., C.R.C., D.G., T.L.F., P.C.; software, F.D.; validation, C.R.C., I.A., D.G., T.L.F., P.C., M.B.; formal analysis, F.D.; investigation, F.D.; data curation, F.D., I.A., D.G., E.A., T.L.F., P.C., M.B., L.M., D.P., S.S. and G.D.B.; writing—original draft preparation, F.D.; writing—review and editing, F.D., CR.C., I.A., D.G., E.A., T.L.F., M.D.P., P.C., M.B., L.M., D.P., S.S. and G.D.B.; visualization, F.D., C.R.C., D.G., E.A. and T.L.F.; supervision, C.R.C. and P.C.; funding acquisition, C.R.C. and M.D.P. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by AIR0000032 – ITINERIS, the Italian Integrated Environmental Research Infrastructures System (D.D. n. 130/2022 - CUP B53C22002150006) under the EU - Next Generation EU PNRR - Mission 4 “Education and Research” - Component 2: “From research to business” - Investment 3.1: “Fund for the realization of an integrated system of research and innovation infrastructures”.

Data Availability Statement

The datasets presented in this article are not readily available because they are part of other ongoing studies.

Acknowledgments

To be filled in later (anonymous reviewers, editors).

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 2. Wind rose of frequency counts and wind speed thresholds, based on hourly data gathered at LMT between 2015 and 2023. Each bar has an angle of 8 degrees. Calm refers to instances of 0 m/s, which have never occurred (0%) during the observation period.
Figure 2. Wind rose of frequency counts and wind speed thresholds, based on hourly data gathered at LMT between 2015 and 2023. Each bar has an angle of 8 degrees. Calm refers to instances of 0 m/s, which have never occurred (0%) during the observation period.
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Figure 3. Main characteristics of daily patterns as observed at the LMT observation site between 2015 and 2023. All data refer to hourly aggregations. A: ozone mole fractions grouped on a yearly basis (2022 and 2023 are excluded due to their lower coverage rate, as shown in Table 1); B: average hourly concentrations of ozone, differentiated by season; C: seasonal changes in temperatures.
Figure 3. Main characteristics of daily patterns as observed at the LMT observation site between 2015 and 2023. All data refer to hourly aggregations. A: ozone mole fractions grouped on a yearly basis (2022 and 2023 are excluded due to their lower coverage rate, as shown in Table 1); B: average hourly concentrations of ozone, differentiated by season; C: seasonal changes in temperatures.
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Figure 4. Smoothed seasonal percentile rose plots showing hourly variations in ozone concentration thresholds by wind direction. Shaded areas refer to percentiles, while the radius refers to observed mole fractions in ppb.
Figure 4. Smoothed seasonal percentile rose plots showing hourly variations in ozone concentration thresholds by wind direction. Shaded areas refer to percentiles, while the radius refers to observed mole fractions in ppb.
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Figure 5. Correlation between wind speeds and ozone mole fractions, divided by sector. A: western-seaside (240-300 °N); B: northeastern-continental (0-90 °N); C: total data.
Figure 5. Correlation between wind speeds and ozone mole fractions, divided by sector. A: western-seaside (240-300 °N); B: northeastern-continental (0-90 °N); C: total data.
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Figure 6. Evaluation of the OWE (Ozone Weekend Effect) based on hourly ozone data gathered at LMT, differentiated by weekdays. The dotted horizontal line represents average concentrations. A: western-seaside (240-300 °N); B: northeastern-continental (0-90 °N); C: total data.
Figure 6. Evaluation of the OWE (Ozone Weekend Effect) based on hourly ozone data gathered at LMT, differentiated by weekdays. The dotted horizontal line represents average concentrations. A: western-seaside (240-300 °N); B: northeastern-continental (0-90 °N); C: total data.
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Figure 7. A: Multi-year variability of surface ozone mole fractions at LMT. The years 2022 and 2023 are not shown due to their lower coverage rate. B: yearly cycle with monthly averages differentiated by wind corridor. C: differentiated monthly averages referring to the entire observation period (2015-2023).
Figure 7. A: Multi-year variability of surface ozone mole fractions at LMT. The years 2022 and 2023 are not shown due to their lower coverage rate. B: yearly cycle with monthly averages differentiated by wind corridor. C: differentiated monthly averages referring to the entire observation period (2015-2023).
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Table 1. Coverage of “Ozone” and “Meteo” datasets with respect to the total number of hours throughout the entire observation period 2015-2023. The “Combined” dataset refers to hours were both instruments were operating at the same time. Both 2016 and 2020 were leap years.
Table 1. Coverage of “Ozone” and “Meteo” datasets with respect to the total number of hours throughout the entire observation period 2015-2023. The “Combined” dataset refers to hours were both instruments were operating at the same time. Both 2016 and 2020 were leap years.
Year Hours Ozone (%) Meteo (%) Combined (%)
2015 8760 92.13 95.9 90.50
2016 8784 96.16 96.34 93.85
2017 8760 95.92 93.8 91.30
2018 8760 98.12 77.05 75.73
2019 8760 94.2 98.59 94.16
2020 8784 98.5 99.98 98.48
2021 8760 91.15 99.74 90.98
2022 8760 85.22 90.11 81.98
2023 8760 81.95 96.3 80.55
Total 788881 92.592 94.22 88.612
1 Sum. 2 Average.
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Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
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